What We’re Reading (Week Ending 14 August 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 14 August 2022:

1. Everywhere you look there’s lag – Stacey (Trust, but verify)

What do London Heathrow’s flight caps, the inventory of retailers, interest rate policies, and the energy transition have in common? All are subject to systems lag and experiencing the effects.

Current world events show the importance of understanding systems and the inherent delays therein. By knowing what to look for, one can better see the forest from the trees. The best way to view the world is as it is. The tangible and intangible components of our lives are comprised of embedded systems…

…Every human, organization, animal, economy, and government is a complex system (with systems within this system which are called embedded systems). Another way to state this is as:

“an interconnected set of elements that is coherently organized in a way that achieves something. The system may be buffeted, constricted, triggered, or driven by outside forces. But the system’s response to these forces is characteristic of itself, and that response is seldom simple in the real world.” – Thinking in Systems

It is more than the sum of its parts – it can exhibit adaptive, dynamic, goal-seeking, self-preserving, and sometimes evolutionary behavior. They can be self-organizing, self-repairing, and resilient. Get all that? Let’s break it down into its essential parts.

A system must contain three things:

1. Elements: the building blocks; for a tree it’s the roots, branches, and leaves.7 Includes the intangible and tangible. For example, the bits within a computer are intangible.

2. Interconnections: relationships holding the elements together. In a tree system, it would be the physical flows and chemical reactions. Interconnections often operate via the flow of information. These flows of information are signals for the decision/action/leverage points within a system.

3. Function/Purpose: what is its aim; can only be deduced by its behavior. The purpose of nearly every system is to safeguard its survival. Further, successful systems work to keep sub-purposes and overall system purposes in harmony. The cells in your heart are different from your liver, but both function to keep you alive.

Of the three building blocks, changing the elements typically has the smallest effect on the whole. Swapping out all the players on a football team still makes it a football team. A human body regularly replaces its cells but continues to be a human body. Countries have regular elections, with different politicians occupying offices, yet nothing seems to change. As long as the interconnections and functions remain intact, a system generally goes on doing its thing.

Altering the function is often the most crucial determinant of a system’s behavior. It would be like if an animal’s purpose was changed from survival/reproduction to pleasure.

However, this is not to take away from the fact that elements, interconnections, and purpose are essential. If changing an element results in a changed relationship or purpose, de facto behavior is modified. Adjusting interconnections (the information flows) can materially affect a system – imagine changing the rules of football to those of soccer.

The system interacts with outside forces, but, importantly, its response is of its own character. Another way to say it is it has its own latent behavior within its structure.

However, a system’s behavior cannot be known based purely upon adding together its elements. Humans tend to think linearly, which is not necessarily how systems act.

Systems are often nested within other systems. As such there are purposes within purposes. According to Friedman’s economic theory, the purpose of a corporation is to maximize shareholder returns. Within that business, the purpose of the C-Suite may be to serve customers well or make as much money as possible anyway possible. Down at the middle manager role, the goal may be not to get fired. At the junior level it could be promotion and earning more money.

As you can see, often the sub-purposes come into conflict with the overall purpose at businesses. Like with individuals, the greater the sense of coherence within the corporation, the better the results.

What is not a system? An assortment of things without any specific interconnection or function.

“Sand scattered on a road by happenstance is not, itself, a system. You can add sand or take away sand and you still have just sand on the road.” – Thinking in Systems

Lags are inherent in systems due to their structure – it takes time for a given input to result in an output. Goods ordered from China do not instantaneously appear in a company’s warehouse.

To understand lags, first we need to take a step back into how the elements of a system are set up. The foundation of any system is its stock. These are the store, the quantity, the accumulation of material or information built up over time. You can see, count, or measure these items. The money in your bank account, the water in a bathtub, trees in a forest, or the population of a country are all examples of stocks.

Flows cause stocks to change. It’s the bathtub filling and draining, the births and deaths within a country, the dying and planting of trees in a forest, deposits and withdraws in a bank account. To understand much of the behavior of complex systems, one must understand the interplay of its stocks and flows.

A critical point is stocks typically change slowly. A forest doesn’t become deforested all at once. It takes a while for the population to unlearn skills. Groundwater can be pumped out at a faster rate than it is replenished for a long time. This occurs even when flows into or out of them change suddenly. Think of how much long it takes for trees to accumulate into a forest. Or for a productive labor force to be built up.

As such, stocks form the basis of system delays. They can also serve as system buffers. Just-in-time inventory has reduced the buffer of stocks. Taking slack out of the system results in decreased resiliency.

Time lags aren’t all bad – the stocks can be sources of stability…for a while. These delays allow room to experiment and revise policies that aren’t working.

Stocks allow inflows and outflows to be independent of each other and temporarily out of balance. Reservoirs allows residents and farmers to live downriver without adjusting their lives to a river’s yearly flows. But if hard rains happen for years, eventually the river will flood.

“Systems thinkers see the world as a collection of stocks along with the mechanisms for regulating the levels in the stocks by manipulating flows. That means system thinkers see the world as a collection of ‘feedback processes.’” – Thinking in Systems

If a system demonstrates a persistent behavior over time, the odds are good there’s a mechanism creating this consistency. It is manifested through a feedback loop. To find feedback loops, look for a system’s consistent behavior.10 Feedback loops can stabilize or de-stabilize systems. They can cause stocks to increase or decrease.

Donella Meadows in her excellent book on systems speaks of three types of delays: 1) perception delay; 2) response delay; and 3) delivery delay. Below shows the system flows for a car dealership’s inventory…

…The perception delay is intentional in this case. How often does the dealer react to changes in sales? Does he go off of daily, weekly, monthly, or some average? It’s key to pick the right time period to sort out real trends from noise.

Response delay is how much he orders. Does he order the whole lot needed or make partial adjustments to make sure the perceived trend is real?

The delivery delay is how long it takes to receive vehicle orders onto the lot.

Inventory oscillations result in a system where there are delays…

…Think about it: sales increase, causing vehicles on the lot to drop. Once they are sure the higher sales rate will last, more cars are ordered. The delivery delay means it takes time for the orders to actually arrive.

Yet during the interim period before orders hit the lot, inventory drops further if sales sustainably rise, meaning available inventory continues to decrease, so orders bump up a little more to bring inventory back to prior levels.

The larger volume of orders begins arriving, and, instead of recovering, inventory can shoot up more than expected, and the dealership can quickly turn from under-inventoried to over-inventoried. Orders are cut back, but elevated past orders are coming in, so less is ordered. Inventory eventually falls and can become too low. 

2. DeepMind found the structure of nearly every protein known to science – Nicole Westman

DeepMind is releasing a free expanded database with its predictions of the structure of nearly every protein known to science, the company, a subsidiary of Google parent Alphabet, announced today.

DeepMind transformed science in 2020 with its AlphaFold AI software, which produces highly accurate predictions of the structures of proteins — information that can help scientists understand how they work, which can help treat diseases and develop medications. It first started publicly releasing AlphaFold’s predictions last summer through a database built in collaboration with the European Molecular Biology Laboratory (EMBL). That initial set included 98 percent of all human proteins.

Now, the database is expanding to over 200 million structures, “covering almost every organism on Earth that has had its genome sequenced,” DeepMind said in a statement.

“You can think of it as covering the entire protein universe,” Demis Hassabis, CEO of DeepMind, said during a press briefing. “We’re at the beginning of a new era now in digital biology.”

3. Taiwan reports 1st child with cancer cured by CAR T-cell therapy – Keoni Everington

A 10-year-old girl suffering from leukemia is the first child in Taiwan to receive CAR T-cell therapy and to have fully recovered from the cancer as a result.

The girl, identified as Tingting (亭亭), was diagnosed with childhood B-cell acute lymphoblastic lymphoma four years ago. After undergoing first-line therapy, she still relapsed.

In the past, such a patient would have to wait for a stem cell transplant to save their lives. However, with the assistance of doctors at National Taiwan University Hospital (NTUH), she became the first CD19-targeted chimeric antigen receptor-engineered (CD19 CAR) T-cell recipient in Taiwan and has fully recovered, with no residual cancer cells detected in her body…

…Chou explained that the treatment principle relies on high-tech genetic engineering. First, T-cells are isolated from the patient’s body, and are genetically modified by adding a gene for a receptor called chimeric antigen receptor (CAR), which enables the T-cells to attach to a specific cancer cell antigen.

The cancer cells from childhood B-cell acute lymphoblastic lymphoma contain an antigen called CD19. Therefore, in this patient’s case, the CART T-cell technique was used to design T-cells to attach to the CD19 antigen.

Chou compared it to a precise “immunization army” that can accurately and continuously destroy cancer cells. The advantage is that a one-time injection can generate these results, said Chou, as was the case with Tingting.

In April of this year, NTUH became the first medical center in Taiwan to provide formal clinical use of CD19-targeted CAR T-cell therapy. Tingting was the first patient in Taiwan to receive the treatment and experience a full recovery.

4. An engineering breakthrough using DNA could unlock the quantum computing revolution – Chris Young

Scientists from the University of Virginia School of Medicine and collaborators used the building blocks of life to potentially revolutionize electronics.

The scientists utilized DNA to guide a chemical reaction that would overcome the barrier to Little’s superconductor, which was once thought to be “insurmountable”, a press statement reveals.

They used chemistry to perform incredibly precise structural engineering, allowing them to assemble a lattice of carbon nanotubes for Little’s room-temperature superconductor.

More than 50 years ago, Stanford physicist William A. Little proposed a type of superconductor that could be used at room temperature. This could potentially be used to enable hyper-fast computers and shrink the size of electronics devices, among a list of other benefits. In 2020, researchers from the University of Rochester revealed the first room-temperature superconductor, but high-pressure requirements make it difficult to utilize.

Edward H. Egelman, Ph.D., of UVA’s Department of Biochemistry and Molecular Genetics and graduate student Leticia Beltran applied their knowledge in the field of cryo-electron microscopy (cryo-EM) to the problem. Their work, outlined in a new paper in the journal Science, “demonstrates that the cryo-EM technique has great potential in materials research,” Egelman explained.

The researchers set about trying to realize Little idea for a superconductor by modifying lattices of carbon nanotubes. The main obstacle was controlling the chemical reaction along the nanotubes so that the lattice could be assembled as precisely as possible. According to Egelman, their “work demonstrates that ordered carbon nanotube modification can be achieved by taking advantage of DNA-sequence control over the spacing between adjacent reaction sites.”

The lattice the scientists built has not yet been tested for superconductivity, but it offers proof of principle, according to the researchers. “While cryo-EM has emerged as the main technique in biology for determining the atomic structures of protein assemblies, it has had much less impact thus far in materials science,” Egelman described.

5. Walmart – Benjamin Gilbert and David Rosenthal

David: There, one night at a bowling alley in Claremore, he meets and falls in love with a girl named Helen Robson. Helen was from Claremore, but her father, L.S. Robson, unlike Sam’s family, was a very wealthy and successful businessman, financier, and trader in the broader Tulsa area.

He ends up taking a big shine to Sam and would become hugely influential along with Helen because he marries Helen, of course. Sam would say, “The Robsons were very smart about the way they handled their finances: Helen’s father organized his ranch and family businesses as a partnership, and Helen and her brothers were all partners. Helen has a college degree in finance, which back then was really unusual for a woman, and Mr. Robson advised us to do the same thing with our family, which we did way back in 1953.”

That partnership that Helen and Sam set up is today Walton Enterprises which owns 36% of Walmart, and then individual family members and trusts—I think mostly Bud’s [Sam Walton’s brother] family—own the other 11%–12%.

Ben: This is the interesting seed plant of Walmart being a family business from the very get-go. They organized it interestingly. Each store was actually its own company so that different people could hold shares in each store—the management, different people who wanted to invest in the store, and that sort of thing—but at a really high level, Walmart always was a family partnership. It was always something where the economic and spiritual ownership and decision-making always was the Walton family. Of course, Sam’s the guy, but there were a lot of family meetings to make decisions for the business.

David: This is why, because the family was all partners in Walton Enterprises. They couldn’t just sell their stock and the partnership. The family as a whole had to decide to sell. That allowed them to keep majority control of Walmart all through history.

Sam talks about this. He says he thinks it’s the big reason why corporate raiders or larger companies like Kmart never came and acquired them because the stock was never splintered. It was all within the partnership. Then, he actually writes, “One of the real reasons I’m writing this book is so my grandchildren and great-grandchildren will read it years from now and know this: If you start any of that foolishness like changing the structure, selling off stock, going off and doing fancy thing—”

Ben: Buying NBA and NFL teams.

David: Buying NBA and NFL teams which they do now. “—I will come back and haunt you. So don’t even think about it.”…

…David: Sam and Helen get married and Sam gets posted in a bunch of places all around the country doing internal intelligence work for the army. He goes to Utah and plenty of other places. He decides that when the war ends and he gets out of the Army, he’s going to go back into retailing, but now, he has the support of Helen, her family, and her father, L.S. They’re financiers, so he knows, I now have access to some amount of capital. I can be an entrepreneur. I don’t necessarily have to work for somebody.

When the war ends, L.S. initially wants them to move back to Claremore, but Helen and Sam decide together. They’re like, well, we want your support, but we don’t want to be totally under your wing and in your shadow.

Sam got big ambitions. He and a buddy decide that they want to buy a Federated Department Store franchise in St. Louis. They’re going to be big. He comes from JCPenney in Des Moines. He wants to be a big city department store owner, magnate, and entrepreneur.

Helen vetoes this outright. We would not be talking about Walmart if Sam had moved the family to St. Louis. Helen says, look, one, I don’t want you doing any partnerships with non-family members. Sam says, “Her family had seen some partnerships go sour, and she was dead-set in the notion that the only way to go was to work for yourself and for your family.”

Two, she says, “I don’t want to live in a big city. I want to go live in a small town where I grew up just like Claremore. I don’t want to live in Claremore itself, but we are not allowed to move to any town that has a population of more than 10,000 people.”

Ben: Her whole thing was I want to raise my kids the way that I was raised. She looked at Sam and said, you were raised the same way in a small town and that’s what we’re going to do. Whatever business he did had to be family owned and controlled and have a small town-based strategy. What seems so intentional and so genius actually stems from the fact that she just vetoed his original idea….

…David: …Sam doesn’t stay down for long. I think he was a little disappointed that his wife had overruled him, but he finds a way. He goes back to the company that owned Federated, which is a company called Butler Brothers. They were franchisors of Federated. They’re based in Chicago.

He asks, well, do you have any department store locations that might be available in a small town of say 10,000 people or less? The Butler Brothers guys are like, we don’t really do department stores in towns like that, but we do have another spin-off operation that we run, which is our variety store franchising business.

Ben: There literally weren’t enough people they believed to support a department store. Variety stores are like glorified general stores. When you think about a town that’s 2000, 3000, or 4000 people, it really is like if you visited an old west town and looked at a general store. It’s like on steroids, but a few decades later.

David: Variety store businesses, that’s exactly it after the Depression and World War II. That was how small towns and areas were serviced to retail. They’re mostly franchise operations. This particular one was Ben Franklin, the brand name. Benjamin Franklin general store type of place.

Ben: When you say franchise operation, because it’s way too much of a burden to source your own inventory, carry your own inventory, and maintain all those different vendor relationships, if you’re in one of those towns, you’re serving 2000 people and you’re the one store there, what you really want is to sign a contract and just get the shipment of the stuff that goes into the Ben Franklin stores in all the small towns.

David: Yeah, and just be literally the merchant serving your customers. That mindset dominated. It’s worth a pause here to talk about what these stores were because it’s a very foreign concept to anything we’re familiar with today. These variety stores were also called five and dimes if you’ve ever heard that term.

Ben: A 5¢, 10¢ store.

David: The reason for that is that in most of them, every item in the store was either priced at 5¢ or 10¢. That was the level of sophistication here. The other big, big difference between how the stores operated in modern retail today, which says I’m really invented, was they weren’t self-service.

Ben: He didn’t invent that. He stole that.

David: We’re going to get to it. So you would walk into these stores and there would just be a counter area upfront that had clerks. You would tell the clerk what you wanted, and then the clerk would go back into the store, pick out what you wanted, bring it up to the front, and check you out.

Ben: Because there wasn’t really a choice. You’d be like, I need a hose, and they would go get the hose. It’s not like, well, let me see all the different brands, sizes, and colors. It was like, I know you have hoses here. Can you get me one?

David: The merchants weren’t making the decisions on the inventory. It was all just being handed down on high from Butler Brothers back in Chicago.

Ben: Yeah. I did not understand when reading this book when he kept referencing stores that were not stores where you walked around and got your own stuff off the shelf, that that is a modern concept. That is crazy.

…David: …Butler Brothers—Sam’s having this conversation with them—are like, well, probably, you want a Ben Franklin franchise, and it just so happens that we’ve got the perfect store for you in the little town of Newport, Arkansas. The current owner of the Ben Franklin franchise there wants to sell.

Newport is a little town of about 7000 people. It’s in eastern Arkansas. If you know where Bentonville, Arkansas and Walmart are today, it’s not in eastern Arkansas. Sam is like, great, I’ll take it. Now, you have to ask yourself, it is 1945 in America. The war has just ended. Unlike 1945 in Japan like we talked about with the Sony story, retail in the US is booming.

Ben: Everyone’s coming home, there was the G.I. Bill, everyone’s got new homes, everyone’s starting families, and there’s a lot of stuff to buy.

David: There’s a lot of stuff to buy. It doesn’t matter if you’re a department store in a big city or a variety store in a 7000-person town. Everybody in retail should be making money hand over fist right now.

The question that Sam didn’t ask himself and should have was why does this guy want to sell? He says in the book, “A guy from St. Louis owned it, and things weren’t working out at all for him. He was losing money, and he wanted to unload the store as fast as he could. I realize now that I was the sucker Butler Brothers sent to save him. I was twenty-seven years old and full of confidence, but I didn’t know the first thing about how to evaluate a proposition like this so I jumped right in with both feet. My naiveté about contracts and such would later come back to haunt me in a big way.”

He and Helen buy this store.

Ben: This distressed asset at not a distressed price.

David: Yes. They buy it for $25,000, $5000 of their own savings and a $20,000 loan from L.S., Helen’s father. Sam says, this isn’t what I dreamt, but I’m still going to set big goals. He decides that he’s going to set a goal that this store is going to become the most profitable variety store in Arkansas within five years.

Ben: It’s quite the turnaround and is also the first indication of Sam setting these big, hairy audacious goals. He has this subsequent obsession with set a goal, hit it, set a goal, hit it. That really does drive all of his need for experimentation because he finds himself in these situations where he has a goal set and he must invent some way to hit it.

David: It also sets the stage for what was to come. He sets this goal, and then he gets there. This is not a realistic goal.

He says, “Only after we closed the deal, of course, did I learn that the store was a real dog. It had sales of about $72,000 a year, but its rent was 5 percent of sales—which I thought sounded fine at the time—but which, it turned out, was the highest rent anybody had ever heard of in the variety store business. No one paid 5 percent of sales for rent. And it had a strong competitor—a Sterling Store which was another franchise across the street—whose excellent manager, John Dunham, was doing more than $150,000 a year in sales, double mine.”

Not only is it unlikely that he’s going to be the most profitable store in Arkansas, it’s unlikely he’s going to be the most profitable store in Newport. What does Sam do? He goes right across the street into the Dunham Store and he starts trying to figure out why Dunham is twice as successful as he is.

Ben: Yeah. Speaking of the first time Sam does something that he then does forever, he becomes notorious for going into competitor stores, bringing in a little notebook, later bringing in a little tape recorder, and just seeing what he can get away with interviewing clerks and associates at these stores.

Anytime he’s traveling with the family on vacation or anything, he’s just going into all these other stores, observing, taking notes, and figuring out what their systems are, what’s working, and what’s not working, so here he learns that valuable lesson for the first time.

David: So great. I was going to bring this up later, but I think he says in the book that he believes he has spent more time in Kmarts than any nonindividual store employee of Kmart including Kmart’s senior management.

Ben: Yeah. Also, we keep referencing Kmart. When I was growing up, it was like Walmart, Kmart. I think Kmart is kind of like Walmart, about the same scale, same size, and kind of a little lower end. That was my perception as a kid of Kmart. I didn’t realize that Kmart for a very long time was much, much larger than Walmart. They were Walmart’s big brother incumbent.

David: They were the gorillas.

Ben: I don’t remember what year this was, but I remember some quote from Walton where he’s talking about when we reached 5% the scale of Kmart. It’s like, well, that really puts it into perspective how big a lead they had.

David: You mentioned a notepad. It’s actually a yellow legal pad that Sam uses. Famously, he has this yellow legal pad and he’s going into competitor stores. He starts diving into dumpsters trying to get sales receipts, inventory orders, and stuff to figure out how these stores are operating.

He quickly realizes from both Dunham across the street—and also, he’s doing this all over the countryside, going into small variety stores all over Arkansas just trying to learn—that price, running promotions, and cutting prices on big marquee attractive items like health and beauty aids, toothpaste, mouthwash, makeup, and that stuff really drives customers in.

He starts doing that and he has some success, but there’s a problem. We talked about Butler Brothers as the franchisor. They’re controlling all the inventory. Sam as the merchant is just getting whatever they send to him at whatever cost they prescribe.

The Butler Brothers are doing great. They get about a 25% markup on all the inventory and they don’t even do anything. It’s almost like they set up the whole system just to keep these prices high out in the countryside and they just get a 25% skim off the top.

What does Sam do? He starts figuring out who the manufacturers are of some of these goods. For manufacturers that are also located there in the south in the Midwest, he starts driving around, knocking on their doors, and asking if they’ll do side deals with him and just clandestinely sell him some of the merchandise that he otherwise would be ordering from Butler Brothers and that they would be selling to Butler Brothers. They just give him a deal directly on that.

Ben: He’s operating a small enough scale that Butler Brothers doesn’t really notice. To be frank, there wasn’t good tracking or accountability at this point. There weren’t computers yet.

David: There’s no computerized inventory here.

Ben: You’d have to really be paying attention to figure out, oh, maybe Sam is not ordering quite as much of this stuff from us as he should be.

David: He’s driving around himself. There’s no management. He has some clerks working in the store, but it’s just Sam and Helen running the place. He’s out, he drives to visit them, and he’s got to get a deal done on the spot.

He goes, knocks on the door, and meets these people. He’s like, I want to buy it right now. I’ve got a trailer hooked up to my pickup truck outside. Can you just load the inventory right into the back and I’ll drive it back to Newport? He says, I bring them the inventory, bring it back, price it low, and just blow that stuff out of the store.

Ben: Which is an invention. This is a brand-new concept that we take for granted now, but it’s totally a Sam Walton invention to meet his own needs which is to create something that is astonishingly low price to get people in the store, take no margin on it, and make it a loss leader. Who cares? Get people in the door spending time in your store and they look at other stuff.

This would become a cornerstone of Walmart forever after this and for every other retailer. Even in the pricing of SaaS products now, when you look at it, it’s like, oh, I’m on the free plan. It’s not that he invented loss leadership as a category, but he figured out how to make it work in the retail model.

David: He figured out how to really merchandise and operationalize. Dunham’s across the street running promotions, but Dunham wasn’t thinking about, oh, well, maybe I could sell even lower if I go haul my pickup truck out to these manufacturers and get goods at a lower price.

Ben: Right. Of course, once you’re hauling your pickup truck to go meet the vendors directly, it’s not that far of a cry to say, well, what don’t I have in the store that I’m getting from Butler Brothers? What could be interesting? You start getting good at doing these direct deals, sourcing your own inventory, and figuring out how to merchandise products that you personally believe will sell.

This is really where he started to hone that skill, craft, and sixth sense for deeply knowing the American consumer—or let’s say consumers in this area in his communities—and having a real spidey sense of what would make them go crazy and have a real product-market fit in people’s homes.

David: Price, selection, and convenience are the holy trinity of retail, but nobody really knew this yet. Frankly, all of those things are important, but for the majority of people out there in the world, in America at the time, and certainly the vast majority of people in these small towns, it’s selection and convenience.

Ben: Life was inconvenient, so you’re going to go through some inconvenience to get things. Selection, there wasn’t much of no matter what. We just came out of the Great Depression. Price is very important.

David: Customers will go to great lengths to get lower prices.

Ben: People would make day trips. People would drive five hours to other cities to get a deal on goods.

David: It’s crazy. He says, “Here’s the simple lesson we learned—which others were learning at the same time and which eventually changed the way retailers sell and customers buy all across America: say I bought an item for 80 cents. I found that by pricing it at $1.00 I could sell three times more of it than by pricing it at $1.20. I might make only half the profit per item, but because I was selling three times as many, the overall profit was much greater. Simple enough. But this is really the essence of discounting: by cutting your price, you can boost your sales to a point where you earn far more at the cheaper retail price than you would have by selling the item at a higher price.”…

…This is incredible. He actually hits his goal. By year five of the Newport store, he’s doing $250,000 in sales at a $30,000–$40,000 annual profit. Remember, he bought the thing for $25,000. That’s including the crazy 5% rent charge in his expenses.

Ben: His operating margin on this is 24%. He’s making very, very real profits on this little store that he’s got.

David: If he had a better rent deal it could be 28%. But at those numbers, it is the most profitable store in Arkansas and the biggest store by sales not just in Arkansas but the whole Midwest and South region. He has found a winning formula here.

Ben: Which is interesting because I’m pretty sure at this point, he’s got a bunch of direct deals cut with the suppliers and he’s added a bunch of products of his own. He’s really merchandising. He’s really showing up on Ben Franklin’s radar and the Butler Brothers Corporation’s radar, and they know what he’s doing at this point. But it’s good for them. Even though it’s good for Sam, it’s also good for them because of volume and customers.

David: Right. He’s by far the best-performing Ben Franklin store in the country at this point. Unfortunately though, like I said, there’s a reason that Walmart is not headquartered in Newport, Arkansas. Butler Brothers weren’t the only related party to Sam who figured out what was going on here. His landlord that had pulled one over on the previous owner and had the super onerous rent terms also figures out, of course, how great Sam is doing despite having the deck stacked against him.

He decides he wants to take over the store. Year five is when the lease expires and there wasn’t an option in the contract to renew the lease. The landlord goes to Sam. He’s like, you know what, son, you’ve done a great job. Thank you for turning this property of mine around. I’m going to take it from here.

Ben: Just to contextualize this, it’s a 7000-person town. There are not really many other available storefronts. He’s got tons of shelves in there with tons of goods. It’s a meaningful amount of inventory that’s being carried on the business. It’s not like you can be like, oh, cool, I’ll move next door. That option does not exist.

His landlord comes to him and says this and he’s like, wait, oh my God, I have no other options.

David: He says, “It was the low point of my business life. I felt sick to my stomach. I couldn’t believe it was happening to me. It really was like a nightmare.”

I say this as a saving grace although the reality is Helen’s father would have financed Sam’s next venture no matter what. But the saving grace for Sam’s pride at least was that the landlord did buy out the value of the Ben Franklin franchise license, the hard assets, the inventory, the fixtures, et cetera in the store. He pays Sam and Helen $50,000 to take over the store. I’m going to guess that’s a 2X return.

Ben: What was the operating income from the previous year?

David: Thirty to forty thousand dollars.

Ben: Wow, brutal.

David: But at least they get the $50,000 out. This is now 1950. Sam and Helen hit the road again looking for a new town to bring their traveling circus to.

Ben: And have a little bit more knowledge on lease negotiation.

David: Yes. They go up to the other corner of the state in Northwest Arkansas. This is where they started looking around for the next place to set up shop for two reasons.

One, closer to Helen’s family in Oklahoma, Claremore. Two, like I said, Sam keeps it real. He was like, there’s some really good quail hunting up there and I really wanted to be closer so I could drag my bird dogs out and go hunting.

Ben: Yes, and more specifically, it’s not just that there’s good quail hunting. It is that he will be very close to four states which each have their own quail hunting season so that he can get the maximum amount of quail hunting in with an easy drive from his house.

Lots of business decisions being made here on family—we need to be in a small town and we need to only work with family. For Sam, I need to be able to hunt quail in the maximum amount of time that I possibly can.

David: The opportunity that they find and settle on is in a little town of 3000 people—less than half the size of Newport—that already in this town of 3000 people had 3 variety stores operating. Newport had 2 for 7000 people. This town has 3 for 3000 people.

As Sam says, he loves competition. That town is Bentonville, Arkansas. Sam probably almost assuredly is rolling over in his grave right now.

Ben: The new Walmart campus.

David: The new Walmart campus that they’re building. It looks absolutely gorgeous, which I’m sure he would be furious about.

Ben: Yes. If you thought Warren was a penny-pinching, very plain, no frills, no fancy things entrepreneur, Sam Walton—hard to argue who’s more frugal and less showy. Sam eventually got into airplanes for very practical use, but Sam was not a showy guy.

David: Actually, the anecdote that he and John Huey open Made in America with is I think it’s 1985 when Forbes ranked him the richest man in America and all these reporters start descending on Bentonville. They want to go interview the richest man in America. He still drives an old pickup truck that has cages in the back for his bird dogs because he goes hunting in the four states nearby.

It’s this big sensation that the richest man in America drives a beat-up, old pickup truck with cages in the back. He’s like, well, what am I going to drive my dogs around, in a Rolls Royce?

Ben: All right, so they arrive in Bentonville. Bentonville and the world are forever changed, but it doesn’t happen all at once.

David: No. The store that they buy is another Ben Franklin franchise that had done $32,000 in revenue the year before, quite a distance from the $250,000 that they left Newport with. Sam decides, all right, well, this is a small market. This is a small store. There’s a lot of competition, but I have big ambitions. He’s got his ear to the ground in retail and particularly in the Ben Franklin franchise network.

He hears through the grapevine that there are two Ben Franklin stores up in Minnesota that were trying a radical new concept. They were redoing the whole way. The store was laid out, the way it worked. They were removing the upfront counters, turning them into checkout counters, and letting customers go into the store, browse the merchandise, pick it up themselves, select it themselves, and then checkout.

He’s like, I got to go see this. He takes the overnight bus up from Arkansas up to Minnesota and checks them out. He’s taking notes the whole time on his yellow legal pad. He says about that trip, “I liked it. So I did that too”

Ben: I love how he’s so obsessed with first-hand experience. He couldn’t just hear about this and then implement it. He’s like, I must see it for myself because he so fervently believes that he picks up insights from actually spending time in stores and actually talking to customers. It seems like he does that more than any other entrepreneur we’ve ever talked about on this show, this obsession with first-hand experience.

David: I think everybody can apply this to their business. I was thinking about it while reading the book. I started so many passages and I already listened to lots of other podcasts unlike when we started Acquired and I didn’t listen to any other podcasts.

Ben: We should find the best ideas and incorporate them, yeah.

David: There’s a great quote about this when Walmart actually gets started later. I’m going to tease it for now. On July 29th, 1950, just about 72 years ago, they reopened the Ben Franklin store that they bought.

Ben: Still a franchise.

David: Still a Ben Franklin franchise, still working with Butler Brothers for “most of the inventory.” But they want to send a message that this is a new era, doing the self-service new store in Bentonville. They renamed it Walton’s Five and Dime and it became the third self-service variety store in the entire country.

Ben: It’s fascinating that they picked this name because part of the reason why you do a franchise is the brand. Sure, it’s nice to get the inventory, negotiated relationships, prices, and all this stuff, but really what you’re buying is people who know what a Ben Franklin is, so they would come to the store.

What Sam is saying is, eh, I feel pretty good about building my own brand. I know I’m in one way or another paying to use the Ben Franklin brand, but we’re not going to use it.

David: It really was rational because even though Sam on the margins is doing his own direct deals with manufacturers at this point, it’s a ludicrous concept that somebody in a little store in Arkansas could source all of their inventory and do all of their logistics by themselves. That is completely freaking crazy that a store servicing 3000 people in a little town would handle all of that themselves.

But they launched with a new name. It’s a new concept. It’s self-service. It causes quite a stir. I couldn’t find this exactly, but I believe, in that first year when Walton’s Five and Dime is open—remember, the previous Ben Franklin iteration of the store had done $32,000 a year in revenue, something like that—Walton’s Five and Dime did $90,000 in sales the first year.

I don’t know what the competitive dynamics were between the 3 stores in Bentonville, but remember, the town only had 3000 people. If you assume the previous three stores roughly had an equal market share—it’s a big assumption but just for argument’s sake—that would mean that the whole market size of Bentonville, the whole TAM, is $90,000. They did $90,000 in revenue, so what was happening here?

Ben: Yeah, is there a massively expanding TAM, did they expand that market because people are just buying more stuff than they otherwise would have?

David: I don’t know what happened to the other two stores, whether they went out of business or not. Certainly, they wouldn’t have right away. I think what happened was this caused such a stir that people started coming to shop at Walton’s Five and Dime from other towns.

Ben: I think it was the first time that Sam realized that shock value would bring customers much like I didn’t need anything the first time I went to an Amazon Go to try the cashierless checkout. People came for novelty value here. That taught him the lesson of, oh, maybe we should always have novelty value. Maybe there are reasons why people should be coming to Walmart even if they aren’t necessarily looking to buy something.

David: Yup. If you think about it, put yourself in the shoes of customers back then. Sam talks about this a lot in the book. For so long—we’ll get into the competition with Kmart—everybody thought Walmart, Sam, and all their customers were just kicks in the sticks. They are just complete morons out there. Nothing could be farther from the truth.

He says, my customers were also sophisticated retail customers. They knew about what was going on in the cities. They had relatives there they’d go visit. It’s not like they didn’t want first-class shopping experiences in their own hometowns.

Clearly, this makes a big splash. Sam realizes that he might have a tiger by the tail here so he starts looking. Unlike in Newport where he was satisfied, the store kept growing and he did $250,000 a year in sales. He starts looking to open up more locations.

Ben: More Five and Dimes.

David: He also doesn’t want to have all of his eggs in one basket and one lease like he did in Newport.

Ben: Right. Didn’t he open a store directly next door to one of his competitors just so that his competitor couldn’t expand their store? It wasn’t a high-performing store for him, but at least it didn’t let them get the square footage.

David: Yes. Clearly, he’s very competitor-focused. It’s funny. There are so many Jeff Bezos-isms that when you read this book and you learn about Walmart and Sam Walton, you realize that they were originally Walton-isms, Sam-isms, but in the whole Amazon we’re customer-focused and we’re not competitor-focused, Sam would have said absolutely not. We are absolutely competitor-focused. We’re focused on taking the best stuff from our competitors and implementing it here.

Ben: While we’re here, we have to say it. Eventually, a Walmart does go back to Newport. There is a little store that is run by a family member of the landlord that screwed over Sam that does get put out of business by that Walmart going in.

Sam makes the point, “You can’t say we ran that guy—the landlord’s son—out of business. His customers were the ones who shut him down. They voted with their feet.” To me, this is that perfect overlap of are you competitor-focused or customer focused? Well, both. You have to win in a market by counter positioning in some way. Walton did it by discounting but that obviously has an impact on your competitors.

You need to be able to counter a position against someone like a competitor. So when the big realization is, oh, customers always want lower prices, and satisfaction guaranteed, and all the other Walmart-isms, that will have impacts on your competitors. You have to pay attention to those competitors. But ultimately…

David: The customers decide.

Ben: Sam is willing to blame the customer for putting the competitor out of business.

David: In 1952, just a short while later, Sam opens up a second store in nearby Fayetteville, Arkansas, because again, it’s just Sam and Helen, when she can, helping out with the bookkeeping, managing the first store. Sam needs to hire somebody to go manage Fayetteville because he’s working in Bentonville. So he brings on a guy named Willard Walker, who was managing a variety store in Tulsa before that.

The way they convinced him to move to Fayetteville and take over this new concept is they make him an offer he can’t refuse. They make him a partner in the store. This is what you were referring to earlier. They give him a percentage of the profits that that individual store makes. In fact, they set up that store and all future stores as their own partnerships. This is something I didn’t understand until reading the book.

It became a huge part of the playbook for Walmart for decades, in which every store manager in a new store opening was given first equity and individual partnerships, and then later profit sharing incentives in that individual store. That sets up a true alignment of incentives. I don’t think anybody else was doing this at that point in time and then even better.

So all the pool of existing store managers, whenever they open up another store, Sam and Helen give them the opportunity to invest dollars in the new stores and the new partnerships. Now you’re incentivized on the success of the whole network, and you’re incentivized to share information. You want everybody to do better.

Ben: They get carry and they should make a GP commit.

David: Exactly. I think this is super brilliant. I was thinking about this, with regard to tech companies today and everything. Even though employees of tech companies get much better economic deals with stock options, I think psychologically, this is a better way to do it. What Sam was doing, you’re putting your own money at work. You’re incentivized both on your own personal performance in the store…

…David: Then reading more in the book about this. So during this period and in the early Walmart Corporation period, it was just the store managers who were doing this, not the hourly employees.

Ben: There was a gigantic chasm. I mean, there’s still a big chasm today but two completely different classes of humans in those early days between the store managers who were salaried and employed by the partnership and of course the to be called associates but the hourly workers who were not.

David: So a couple of interesting things. One, the people who were the store managers, this wasn’t quite like white collar workers. It’s somewhere in between. Most of these people didn’t have college degrees. They were salaried. Then they got equity in these partnerships. It wasn’t like these were Wharton graduates that were coming in and doing this.

Ben: Intentionally not. Those folks were discriminated against in the Walmart culture, especially in the early days of think you’re better than us, college boy.

David: Totally. One of the first managers was nicknamed The Bear and he had one eye. There are some crazy stories out there. They were bringing donkeys into the store.

Ben: Right. We’re talking Walmart. So take us to Walmart, how did we get from the Walton’s Five and Dime.

David: On the employee front, after Walmart went public, Sam instituted both profit sharing at the store level with the associates, with the hourly employees, but then also an employee stock purchase program. This is cool. Home Depot modeled their employee stock purchase program after Walmart’s and it’s brilliant. It’s the same thing. You put up your own money, but you can do it pre-tax dollars out of your paycheck at a 15% discount to the stock price.

Ben: This is what Microsoft let me do when I was a PM there. In addition to your stock-based compensation, they call it an ESPP (Employee Stock Purchase Program), Microsoft only lets us have a 10% discount, so it’s very kind of Walmart to give a 15% discount for market price.

David: There are stories in the book of hourly associates that made millions of dollars in the ’70s and ’80s off of the employee stock purchase program. It’s pretty cool…

…David: I’m totally inspired by Sam, Walmart, and everything. Okay, so back to the ’50s in Arkansas. Remember, we talked all the way back in the beginning of the episode about Sam’s brother, Bud. Well, Bud had gotten into the Ben Franklin business himself after the war in Missouri. One day, Sam is visiting Kansas City and he hears about a new suburb development going in just southeast of the city called Ruskin Heights, and it’s going to have a shopping center.

This newfangled concept is right in the middle of this suburb subdivision, and there’s going to be a grocery store, a drugstore, and real estate for a big Ben Franklin store. So Sam calls up Bud and he’s like, we got to go in 50-50 on this, this is a huge opportunity. They do, and it is a banger to earn $50,000 in annual sales the first year in Ruskin Heights, then $350,000 the year after and just keeps growing and growing.

Sam says when I saw that shopping center catch on the way it did, I thought, man, this is the forerunner of many, many things to come. The only problem was Ruskin was actually kind of a red herring. This was the future. This was the forerunner of many things to come, but it was still a little bit ahead of its time. This is really a 1960s thing, not only a ’50s thing. Sam is convinced though, that it’s the future. So he starts going around Arkansas and Missouri evangelizing the towns and city planners about putting in the shopping centers.

Ben: For which they would be the anchor tenant.

David: But it’s super slow dealing with local governments. It’s hard. It takes a long time. He wants to move fast. So he starts trying to put his own real estate deals together for multi-tenant shopping centers and fails. Eventually, because back to Helen’s advice, these multi-tenant shopping centers, I see the power in Ruskin, but it’s dependent on too many other people. But if I’m willing to invest some capital, I could just put bigger stores in the same locations myself. That’s what he starts to do.

Ben: Does he become his own landlord then and just buy the land or what requires more capital?

David: That’s a good question. I don’t know at this point if they were doing real estate themselves, but certainly, they are building out bigger store concepts, requiring capital to build the stores. It’s not like there were existing structures there then to outfit them with all the fixtures and all the inventory for the larger stores. But he and Bud together, start doing this. They call these new stores “family centers” and they start doing unheard of numbers—$1 million, $2 million.

Ben: Are they still sourcing the inventory from Ben Franklin from Butler brothers?

David: Yes. They don’t yet have their own distribution, inventory, and logistics network setup. That was the big step of Walmart. These were still just like much larger versions of Ben Franklins and they were working with them to get all the inventory to them.

Ben: Already at this point, they’ve bent so many rules with Ben Franklin like changing the store layout and concept, where they’re going, starting to dictate more terms, and naming them on their own. At this point, they’re really starting to treat Butler brothers as more of a component of the Walton business rather than Walton being a franchisee of Butler brothers.

David: Exactly. So these “family centers” that Sam and Bud were building are still Ben Franklin franchises. The Waltons are now taking over more and more of control of the concept, their self-service, they’re larger format, but it’s still part of the Butler brothers’ cartel, shall we say? Because they were part of Butler brothers, Sam and Bud were limited on how much discounting they could really do.

They were aggressive on pricing, probably more so than other merchants at the time, and they had self-service, the large format, and all this interesting stuff. But the prices weren’t that much different than other stores.

Ben: It’s worth knowing that we don’t think about the notion of discount stores today being counter positioned against something like all big stores have things at kind of the lowest price you can find them.

David: Because they’re all discounters now. I think 87% of market share in America is discounters.

Ben: Yeah. So there’s either specialty high end retail, which is often directly from the manufacturer sort of like vertically integrated or specialty sourced or something, or if you’re buying things that we consider a big regular store, they’re all discounters. At the time, there were no discounters. Everyone was marking up their goods by about 45%. If you’re buying something and then marking it up 45%, it means your gross margin is about 33% as a retailer.

David: And that was on top of the markups in the middle from the franchise operators.

Ben: The competition was so low that you totally could just do this. For reference, just so people have a sense today, Walmart probably has a gross margin between 20–24% at any given time, and every store had like a 33% gross margin. Even though Target is like a high end discounter—it’s sort of a nicer stuff, more expensive—they’re in the 29% category, but everyone was 33% or above gross margin at this point in history….

…Basically, everyone’s marking up their goods 45% and nobody has done other than Ann & Hope and a few other select folks that haven’t really rolled it out at scale or really popularized the movement. No one has done discounting, but what is discounting? Two major components. One is big loss leadership. Blow it out in order to get people in the store, do it in dramatic fashion, and then people buy other stuff.

Two is we make it up on volume, just don’t mark stuff up that much period across the whole store. Decide that you’re only going to mark things up 25% instead of 45%. Then when you do that, of course, you don’t make as much money per item. But everybody buys more stuff in your store. This hadn’t really been proven yet.

David: Yeah, and there’s another component. What you’re saying, which is Sam’s original lesson of, you actually make more profit dollars selling items at the dollar than you do at $120 because you sell three times as many. But there’s also the peace in the middle, the franchisor, the Butler brothers, remember, they’re taking 25% from the manufacturer to Butler brothers, and then out to the stores. That’s how most everything operated.

These discounters are like no, we’re going to go direct to the manufacturers for everything, just like Sam was starting to do in this but on the margins. We’re just going to completely not be a franchise operation. We’re going to own and operate everything. We’re going to operate our own back end, our own supplier relationships, and our own distribution.

Ben: There’s a great quote, this is again later in Walmart’s development. It’s when Sam Walton is informing the Walmart vendor relations team and merchandisers on how to deal with vendors.

He’s telling them, “Don’t leave in any room for a kickback because we don’t do that here. And we don’t want your advertising program or your delivery program. Our truck will pick it up at your warehouse. Now what is your best price? And if they told me it’s a dollar, I would say, Fine, I’ll consider it, but I’m going to go to your competitor, and if he says 90 cents, he’s going to get the business. So make sure a dollar is your best price.

If that’s being hard-nosed, then we ought to be as hard-nosed as we can be. You have to be fair and upfront and honest, but you have to drive your bargain because you’re dealing with millions and millions of customers who expect the best price they can get. If you buy that thing for $1.25, you’ve just bought somebody else’s inefficiency.”

David: Totally.

Ben: I love that. I mean, it is brutal but that encapsulates the philosophy so well.

David: There’s so much baked into that that people don’t even realize. To get to the point where you could do that, you need to operate the entire back-end of retail yourself. Sam and Bud and Walmart, they’re starting from they don’t have anything. To get to a point where you can have conversations with suppliers like that, you need your own shipping carriers, trucks. You need your own distribution centers. You need your own ordering systems. You need your own technology. They don’t have any of that.

Ben: You need to forecast. You need to be able to understand we’re going to sell enough of these units to go buy a crap ton at this super low price. We need to be able to be so confident that we can tell the supplier to spin up new inventory so that we will buy it to increase their production. Okay, that’s all the future. So at this moment.

David: Okay, so at this moment, Sam of course goes out. He goes and shops. He travels to the northeast. He shops in Ann & Hope. He goes out. He meets Sol Price, who he already knew.

Ben: And we’re in like the 1960s?

David: Late ’50s, early ’60s at this point, before 1962. He sees what they’re doing. They’re doing this proto discounting in big cities, and rings around big cities, not necessarily in the primo real estate downtown but where you have access to logistics hubs. You can sort of scrounge together and make this work. The idea that Sam could copy this and go do it back in Arkansas, it’s crazy. What manufacturers are going to ship stuff to Arkansas, especially big volume stuff?

He goes, he meets with Sol and Ann & Hope and he’s like, you know what, I think I can make this work. I think I can do it. Even he knows what a huge undertaking this is. He actually goes back to the Butler brothers. He’s like, we’ve been great partners. We’ve really innovated on a lot of stuff together. I’ve seen this discounting model. I think it’s the future. I know customers like low prices. I’ve got these new large format stores. Why don’t we work together on this? I need you to handle the backend. You have the scale to be able to do this. You already distribute out to small towns like mine. Let’s partner on this and do it together. And Butler brothers says no…

…David: In Butler brothers’ defense, they signed their own death warrant here, but that was the rational thing to do. This is like a counter positioning thing. they had all these other Ben Franklin franchises out there. If they had done what Sam is proposing and essentially taken out their markup on goods that they would provide to Sam’s stores, what are all the rest of their franchisees going to say?

Ben: It is literally the innovator’s dilemma because they have too much baggage to actually pull this new thing off. To be more specific about that, there is too much ongoing revenue that they would cannibalize in the short term by messing up all those relationships they had with their other franchisees where they would probably churn too much of that and risk the whole business so they could not take advantage of what could be the new wave.

David: Yep. The thing that Sam knew, the minute he saw discounting, was all of those stores were dead anyway.

Ben: Yeah, just a matter of time.

David: Somebody is going to bring discounting to Arkansas, Missouri, Texas, Florida, and everywhere else and those stores are dead.

Ben: It’s that insight that people who are out from cities want the same thing as people in cities, and so they’re just as bright. They want the same things in life. They just happen to not live in cities, so let’s not be pejorative. Let’s serve them with high quality retail experience.

David: Totally. So 1962, Sam and Bud secured a site in Rogers, Arkansas, which is pretty close to Bentonville. It’s got to say, they’re going to do this. It’s going to be chaos, but they’re going to figure out the backend, do this new discounting concept. They just need a name. Sam’s got a bunch of candidate names for what to call this new retail concept.

He’s talking with one of the early store managers, Bob Bogle, about his ideas. He says, what do you think? Bob says, you’ve got all these fancy names, but it’s pretty expensive. Building the neon signs of Walton’s Five and Dime and Ben Franklin. That’s a lot of letters. What if you just take part of the Walton name, keep that, make it a place to shop, and call it Walmart. Seven letters, that’ll be pretty cheap.

Ben: I love it.

David: The legend is born.

6. The Greatest Value Investor You’ve Never Heard Of – Macro Ops

The investor is Floyd Odlum.

Buried somewhere in the junk drawer of investing lore, Odlum’s story remains unknown. A quick Google search reveals his Wikipedia and IMDB pages. Yet in typical deep-value fashion, the last link on the page revealed Odlum’s investing story.

The Holy Financier’s blog post was that last link. The blog proved an excellent springboard for a deeper investigation into Odlum’s early life, initial career and his path to market fortunes. Although Odlum (pictured on the right) and Ben Graham never met, their investment philosophies are one in the same.

We’ll journey through his upbringing, his days as a struggling lawyer and his initial attempt at market speculation. Then we’ll see how Odlum turned $39,000 into $700,000 in two years.

Odlum wasn’t just a great investor. He also had a knack for choosing the most generic partnership names, such as his first “The United States Company”. The partnership, formed in 1923, was a couple’s affair. Odlum, George Howard and their wives seeded the partnership with $39,000 ($573K adj. for inflation).

What followed over the next two years was nothing short of incredible. According to Odlum’s biography, The United States Company grew 17x from 1923 – 1925. What started as a small partnership amongst friends turned into a $660,000 behemoth ($9.47M adjusted for inflation).

Odlum’s two-year CAGR is mind-numbing. If that wasn’t impressive enough, he generated these returns while working full-time as a law clerk!

How did he generate such outsized returns?

Well, he was a deep value investor. He searched for fifty-cent dollars and  scoured every corner of the market. According to documents from the Eisenhower Library, Odlum preferred two kinds of investments:

  • Utility stocks
  • Special situations

He defined a special situation as “an investment […] involving not only primary financial sponsorship, but usually also responsibility for [the] management of the enterprise.” The former lawyer wasn’t interested in flipping a business for a quick buck, either.

Embedded in Odlum’s strategy was the determination to see a special situation through until success, “[We will] stay with the investment until the essentials of the job have been done, and then move on [to] another special situation”.

Between 1925 – 1928, Odlum steadily grew the partnership. By investing in utilities and special situations, The United States Company AUM grew to $6M (over $88M adjusted for inflation). It was around this time that Odlum began sensing euphoria in the market. He smelled a top and he decided it was time for him to act.

In 1929, he rolled his original partnership into a new vehicle, The Atlas Corporation. Wary of a market top, Odlum sold half his assets. He stayed in cash and issued $9M worth of Atlas Corporation securities. With $14M in cash, Floyd sat on his hands. Waiting for the next market crash, which shortly followed.

But his bread and butter during the Depression was buying investment trusts. His strategy was simple. He found investment trusts that had fallen so much their stock prices were trading less than the value of their marketable securities. A good example of this in today’s markets is Manning & Napier (note: I do not hold shares).

He discovered he could buy these trusts, liquidate their assets, and reap large profits for his stakeholders. He was buying dollar bills for $0.60 and he milked this strategy for all it’s worth. He ended up buying and merging investment trust twenty-two times. The newspaper article profiled these dealings:

“He figured out that by buying all the outstanding shares of a particular trust, he was really buying cash or its equivalent at sixty cents on the dollar.”

When he didn’t have the cash to buy the trusts, he sold shares in his own company, Atlas, to fund the purchases. After exchanging his stock for the trust’s stock, Odlum would merge or dissolved the existing trust, keeping the cash and assets within Atlas Corp.

This strategy helped grow his assets to $150M ($2.2B adjusted for inflation).

Between 1929 and 1935, Odlum invested (and controlled) many diverse businesses. He owned Greyhound Bus, a little motion picture studio named Paramount, Hilton Hotels, three women’s apparel companies, uranium mines, a bank, an office building, and an oil company….

…He then pooled together another $39,000 to form his first partnership. That original $39,000 grew to $150M in controlled assets. All that during a span of just twelve years.

The math is incredible. Odlum grew assets 384,515% in a bit over a decade. That’s a 32,042% CAGR for asset growth.

And his early partnership returns are just as impressive. Odlum grew assets from $39,000 to $6M between 1923 – 1929. That’s a cumulative 15,284% return. In other words, Odlum compounded capital at an annual rate of 2,547%.

7. The Complex Case of Floyd Odlum – Frederik Gieschen

This is a piece about Floyd Odlum, a once-upon-a-time famous investor who made his fortune doing distressed deals during the Great Depression. But I want to start with a reflection on my process and the challenges of diving into a story. Here’s why.

I had read some twenty articles about Odlum, and his life seemed straightforward: a young lawyer from Colorado made his way to New York to become a dealmaker in utilities, one of the growth industries of the 1920s. He started an investment fund on the side, raised cash in 1929, and avoided the carnage. Through Atlas Corp., his publicly-listed investment trust, he masterfully acquired other trusts at steep discounts to their undervalued portfolios. By the time that Graham and Dodd published Security Analysis in 1934, Odlum had closed 22 transactions and amassed assets of $150 million. Once wealthy and famous, he married his second wife, racing pilot Jacqueline Cochran, served in the government during WWII, and retired to an estate in Palm Springs where he did deals by the pool and was visited by Eisenhower from time to time.

This story and its lessons seemed so clean. Stand back during the bubble, swing for the fences when opportunity presents itself, case closed.

I knew that Odlum’s records were kept in the Eisenhower Presidential Library. What I did not know until this week was that someone had combed through them all and put together a voluminous draft of a biography. After reading the outline, I reached out to the author, David Clarke, bought a copy of his unpublished work for $19.95, and dug in.

But then I stopped myself. This was supposed to be a short piece. Something that I could churn out on a weekly basis with a moderate amount of research. Reading an unfinished 700-page biography would blow up my schedule — and for what?

However, I quickly realized that the neat little narrative about Odlum’s life was wrong. I had no choice but to at least skim the work if I wanted to learn the real lessons of his life.

For example:

Odlum didn’t cash out before the crash. His utility stocks just didn’t decline as much and made a brief comeback, allowing him to redeploy the capital. It seems he never bothered to correct the origin story of his prescience which was repeated by one paper after another.

He made his early capital trading in utility stocks while being employed at one of the largest utility holding companies and running their foreign M&A efforts. While there is no evidence, and insider trading was not illegal at that time, Clarke suspects that this information edge played a significant role in Odlum’s early success.

Also, taking over investment trusts required convincing the board and key shareholders who often had no interest in selling. And it seems that Odlum was willing to bribe directors to get the deals done.

Around the end of WWII, Odlum made his last successful distressed investments, in oil and defense defense contractors, before departing from his circle of competence. Large bets on an airline, uranium mining, and a motorcycle manufacturer turned into sinkholes for capital in which he kept doubling down. His fortune started to dwindle.

His personal life was rife with tragedy as both of his sons died before him: one of alcoholism, the other of suicide after a string of failed deals and enterprises. In the end, Odlum’s wealth had been lost and spent. He and his wife, famous pilot Jackie Cochran, had to leave their beautiful ranch and live out retirement in a modest home.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google), Amazon, and Microsoft. Holdings are subject to change at any time.

What We’re Reading (Week Ending 07 August 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 07 August 2022:

1. Will Thorndike – The Power of Long Holding Periods – Patrick O’Shaughnessy and Will Thorndike

[00:06:28] Patrick: 50’s pretty good. I’d love to dig into this interest that you have in long-term holding periods in as many ways as we can. The TransDigm episode and the conversation you had with Nick and some of the investors there really brings it to life where this is not a simple story, right? There’s a lot going on over a very long period of time. Obviously periods that long are fundamentally unpredictable. You don’t know what’s going to happen in the world. You don’t know what’s going to happen on the team. There’s a crazy amount of unpredictability that gets injected if you’re talking a 20, 30 year time horizon. So how do you deal with that amount of uncertainty and what are the benefits of having that sort of orientation? Is there a litmus test that you apply to the company to say, “This definitely won’t work over five years, but it could over 30.” Is that a positive thing? I would just love to start to understand the reason that you’re so interested in this, given that as you get longer, it just seems harder to predict things.

[00:07:22] Will: In the original Housatonic fund we still owned three of the eight companies that we invested in and the holding period for each of those companies is over 25 years now. And those companies have been very good outcomes, but they’ve also just been incredibly fun and satisfying to work on. You asked that question about how has the book influenced my investing, part of it is I’ve spent a lot of time thinking about those eight companies in the book, those three companies from the earlier Housatonic funds, and then a whole range of other companies I’ve been involved in over a long period of time with the idea that what correlates most highly with persistence in return profile over time? This is really translated into a lot of the work that we’re doing at Compounding Labs, but we’ve really become zeroed in on revenue quality. So the purest form of that is it a recurring revenue business? And if so, what’s the churn profile?

And what we’ve found is there’s disproportionate power in truly low churn businesses. And when I say churn, I mean, logo churn, gross churn, net revenue retention is, there are other metrics that are important as well, but really at the core of it is you start the year with a 100 customers, how many do you end the year with and why are there structural reasons for that? And so if you look across those companies, they tend to have this element of revenue persistence. It’s absolutely the case for TransDigm, TransDigm which I’m sure we’ll get into in some detail, their business is very specialized aviation components, airplane parts. When they get engineered into these core airplane platforms, frames, whether it’s the 737 commercial aircraft or the B-52 and defense aircraft, and those platforms tend to stay in active service for 70 or 75 years.

So if you’re providing a small, critical component part into those airframes, in order to be switched out, it requires FAA approval. It absolutely never happens. And so you have great visibility, predictability on your revenue stream around which you can then do a whole range of other things in terms of how you organize the company, whether you choose a decentralized organizational form, how you think about financing the company. It has a dramatic impact on your capital allocation menu of alternatives. So we’ve intentionally been trying to select for a very specific type of business model at Compounding Labs and also in the work we’re doing at 50X.

[00:09:42] Patrick: Maybe we could just keep digging in until we find a bottom on this concept of revenue quality. What are the most common things that you start to see early in the investigation of a business that indicate that this revenue quality that you’re after may be there? And what is the process like early on as you’re doing one of these deep dives, what kinds of questions are you asking of the business, or the inverse? What kind of things are you looking to actively avoid? Even if there’s, let’s say, low churn?

[00:10:08] Will: It’s one of these things the mathematicians talk about the simplicity on the other side of complexity. And so we’ve spent a lot of time on this over a very long period of time, across a lot of companies. At the end of the day, however, industries that are characterized by very low churn are just interesting places to be looking for these sorts of long holding period platforms. The Porter Framework is incredibly powerful. There are a lot of frameworks you can use to evaluate businesses, but I would argue at the end of the day, if a company has 2% customer churn that’s a very powerful indicator.

So then you have to look at, okay, so what are the reasons for that? And what potential dislocation risk is there that the reasons for that stickiness will change over time. It’s a very rich hunting ground we found, and you tend to get with that profile a lot of other good things. You tend to get relatively simple operations, you tend to get pricing power, you tend to get a high degree of capital efficiency, which is another thing we really focus on. We can talk a little bit about that. But a lot of positive economic attributes tend to correlate with those sorts of revenue profiles. It’s not in and of itself the only criterion, but it’s a very powerful leading indicator. At least for the work we’re doing…

[00:17:45] Patrick: If you think about, I guess the power of that patience early on, and you’re doing these very deep dive looks at companies for the outsiders now for 50 X. What are the kinds of things that you’re uncovering about let’s say TransDigm, since it’s the most recent example. That you think would just be overlooked or underappreciated if you spent, I don’t know, five hours researching the company or some shorter period of time that probably a more traditional analyst new to the company would get familiar in five, 10, 15, 20 hours, something like that. What kinds of things would they miss maybe specifically for TransDigm, but what is the value of this like crazy deep dive, year long type research that you do?

[00:18:23] Will: It’s the peeling back the layers of the onion analogy. So examples of things you learned from diving deeper, pacing is one of them. You need to look really hard to get at that, but their approach to pacing was very different, very differentiated. Another item that’s important to them is they’ve retained the ability to do really small acquisitions as they’ve gotten bigger. That turns out to be a common thread across really long term serial acquirers, really small acquisitions tend to be very, very accretive for these companies over time and so the trap that some serial acquirers fall into is to just focus on larger deals. TransDigm has retained the ability to do a steady diet of these smaller, highly accretive transactions. Again, all done with debt. Game selection, so to speak was really good here. Nick and his team chose an excellent industry, but within that, it’s sort of optimized along every single dimension.

You can look at the decision they made around organizational structure. They chose an extreme what I would call hard form of decentralization and they’ve been able to maintain that as they’ve grown. The details of that, which are in the podcast are all things you would miss on first study, but they’re very important to understanding how sustainable that approach is going forward. The approach to compensation is unique among public companies and it’s tied directly into the decentralized organizational form and it’s just unique in ways that are sort of provocative. It’s entirely performance based, no time based vesting whatsoever and it’s tied to minimum thresholds of compounding for shareholders using a very sensible formula.

The lessons that come out about how to instill, imprint a culture widely in an organization, sort of idea of the simplicity of the value creation triad at TransDigm, which is repeated add in for an item. It’s repeated add in for an item across our podcast, but even more so within the company, this idea that’s productivity, pricing and profitable new business. Those are the only possible sources of value creation and every GM is evaluated on those and every review of every business unit quarterly is centered on those…

...[00:25:09] Patrick: You’ve mentioned this kind of decentralized structure a few times. An example would be helpful of people might think of Berkshire or something where there’s a lot of trust and responsibility and ownership that’s pushed down, maybe IAC. There’s other interesting modern examples of a slim home office, not a lot of G & A the home office and a lot of responsibility at the business unit. Why does this work so well? How does culture permeate across very independent business units? It seems like that would be almost contradictory that unique cultures at the business level, if it was fully decentralized. So I’m just curious to understand a bit more about why you think this works.

[00:25:44] Will: First of all, it’s not a universal panacea at all. So there are lots of companies that have been very successful with cultures and organizational structures that aren’t decentralized. I would argue that Danaher has been wildly successful as a serial acquirer with a culture that is not highly decentralized. It has elements of decentralization, but also importantly, elements of centralization. It’s not a universal solution at all. I think it’s very industry dependent. The characteristics of successful decentralized cultures, I mean, again, you can kind of super, roughly get at it quantitatively by looking at the ratio of people at corporate to total employees, relative to the peer group. So a lot of the companies and the outsiders and the book and TransDigm as examples were just off the charts, they had 10 X, five to 10 X, as many employees, total employees per employee at corporate.

With that is this idea that again, that you’re trying to retain entrepreneurial ethos, that’s an essential priority. So that’s one of the objectives of a decentralized culture. The other is you are lowering your cost and in these cultures, there tends to be an element of frugality scrappiness in the culture. It persists long past the early days. Another company that fits this model very well is Constellation Software, which famously has 500 plus maybe 600 now business units under Mark Leonard. If you’re the CEO of a company, you’re constantly faced with decisions about what to centralize versus keep independent. The tricky thing is in almost every case, the decision to centralize leads to a near term economy, like a quantifiable near term cost savings.

But the reality is that if you do it every time, if you follow that path to its logical conclusion, you tend to end up with a bureaucratic ossified organizational structure and culture. We talk about this with our CEOs all the time. What messes are you willing to step around? What things do you think are important to have reside at corporate and what should remain with the general managers?

[00:27:50] Patrick: I’m curious for an example of a mess that’s worth sidestepping. It would seem counterintuitive that a great business would actively avoid getting involved in a mess. So what’s a good example of that in your experience?

[00:28:01] Will: It’s sort of, what do you want to mandate? Do you want to mandate a certain type of Salesforce compensation program at all of your companies? And it’s this idea. Do you want to mandate it or do you want to suggest it? The other thing that happens in those successful decentralized companies is they tend to regularly assemble the general managers and compare their results and share ideas in a way that naturally promotes positive peer pressure or a little element of competition, but also shares good ideas. That would be an example. You have healthcare insurance, you’re going to make everyone on the same healthcare insurance program or let them choose their own. Even if you get purchasing economies, what’s the flip side? It’s sort of looking at that non-intuitive costs of efficiency sometimes.

2. How Caffeine Became the World’s Favorite Drug – Amy McCarthy, Cynthia Graber, Nicola Twilley and Michael Pollan

Gastropod: Where can you find caffeine molecules in the wild?

Michael Pollan: It’s produced by several plants, most notably the coffee plant, the tea plant. Members of the citrus family produce caffeine also — that’s a curious case — and the kola plant produces it. It was hit upon by plants during their evolution as an insecticide, and also as a chemical that discourages other plants from germinating near you. Plants are very protective of their territory — at least some of them are — and if they drop leaves of a caffeine-producing plant, it’s very hard for other plants to germinate in their presence. But the main purpose [of caffeine] in the life of a plant is to poison insect predators, which it seems to do pretty well.

So when did humans start enjoying this insecticide and in what form?

What’s really interesting about caffeine, at least if you look at it from the point of view of people who live in the West, is that compared to other psychoactive plants that we’ve been involved with for thousands of years — peyote is 6,000 years, alcohol probably goes back even further — caffeine came to human attention fairly late; in the case of coffee, not until the 600s or so. It doesn’t come to the West until the 17th century. Before that, it was known to people in East Africa, in Ethiopia, and the Arabian Peninsula, and it was commonly drunk in the Arab world long before it arrived in Europe.

That’s why it’s a really interesting case study, because we can really look at civilization before and after caffeine. And its effect on Western civilization is profound: It ushers in what amounts to a new form of consciousness, a new way of perceiving the world that was incredibly helpful to things like the scientific revolution and the capitalist revolution. Because it cleared the Western mind, which had been badly clouded by alcohol.

We have very little sense of how drunk people were much of the time, before the advent of caffeine in Europe. Alcohol was something that people drank morning, noon, and night because alcohol was safer than water — you got diseases from water, but the fermentation process and the alcohol itself sanitized the water. So when you read accounts, people were kind of slightly addled all the time.

When caffeine comes in, it doesn’t obviously eliminate the use of alcohol, but it does reduce it. And a lot of people observed this in the 17th century — that, as a result, they’re clear, more focused, able to do things they couldn’t do before. This has a profound effect.

To go back in time a little bit, why were people on the Arabian peninsula consuming it? What did it do for them?

One of the first uses of coffee and tea, interestingly enough, is in the religious context. Sufi monks would use coffee to help them stay awake during long nights of prayer or meditation. And this was true, too, for Buddhists in China, who learned pretty quickly that tea was an aid to meditation. It helps with the focus that you want, and it also keeps you from falling asleep on the cushion. It really begins as a tool for religious observance…

One thing we thought was fascinating was that early scientists were trying to understand caffeine from a worker’s perspective. How were scientists trying to understand how caffeine and energy were related?

This comes a little bit later, around 1900, where you have this new academic discipline concerned with humans and work. Efficiency — kind of a mix of biology and social science — becomes a very important science. And one of the things they were trying to understand is, how was it that caffeine appeared to enhance people’s energy without giving them any calories. There was a pretty strict understanding that energy was a function of calories. But here was a noncaloric drink — leaving aside whether it was sweetened or not — that seemed to give people more energy. This seemed in violation of the laws of thermodynamics, and it looked very much like a free lunch in terms of giving people energy.

It was only later that we came to understand how you got energy from caffeine — that you were essentially borrowing it from the future. It wasn’t additional energy. The way caffeine works is that it, like a lot of drugs, closely resembles a neurotransmitter or neuromodulator. In this case, it’s adenosine, which is a very important neuromodulator that regulates the sleep cycle. Over the course of the day, adenosine levels build up in your body and create what is called sleep pressure. There are receptors dedicated to linking with adenosine. What caffeine does is hijack those receptors. It fits neatly into those receptors and then blocks the adenosine from doing its job.

But it’s not like adenosine goes away. The levels of adenosine in your bloodstream and in your brain continue to build. So when the caffeine is finally metabolized, the adenosine hits you like a ton of bricks because it’s been building up the whole time and you’re more tired than you would have been had you not had the caffeine.

3. A quick look at 2 companies innovating to overcome the short half-life of mRNA: is self-amplifying or endless RNA the future of mRNA vaccines? – Infinitty Capital

Conventional vaccine development takes time, about 10–15 years from initial research to market availability. In this COVID pandemic, mRNA technology has shown a clear advantage of speed over other modalities. However, the technology also faces several technical challenges with no near-term solution.

One drawback with mRNA vaccines is that the amount of antigen produced is dependent on the number of mRNA molecules delivered to the cell. This means that if more antigen wants to be produced a higher dose would be required (this might not be safe). Additionally, because the half-life (number of days before the mRNA is degraded) of mRNA is relatively short, this means that individuals need to get multiple doses to mount an immune response that is potent enough to provide protection.

To address both these issues, scientists have been researching & developing solutions that could increase the production of antigens and improve the half-life of the mRNA molecules.

Let’s look at two technologies that have been developed: self-amplifying RNA and endless RNA.

A self-amplifying RNA (sa-RNA) contains components that allow it to replicate itself in situ (create more copies of itself in the cell, see image below). These components are typically from Venezuelan equine encephalitis virus (VEE), Sindbis virus (SINV), and Semliki forest virus (SFV) and they encode for an RNA-dependent RNA polymerase (RdRP) complex. Therefore, the sa-RNA not only encodes the instructions for the host cell to make the desired protein, but it is also able to make more copies of the RNA containing those instructions. This technology thus allows for an increase in the copy number of mRNA templates but does little to improve the half-life of the template at the parent template is not being amplified.

Because it can replicate and amplify itself, sa-RNA vaccine can be given in a much lower dose, meaning that each dose can be smaller and cheaper…

…In the world of RNA, there are multiple types of RNA and circular RNA is a particularly intriguing format. In circular RNAs, the free 3′ and 5′ ends found in linear RNA forms are joined together to form a closed loop that appears to render them stable and long-lasting. However, circular RNAs are typically non-coding, meaning that they do not get translated into protein.

Laronde Bio (Private) has managed to engineer a closed-loop RNA into a translatable form of RNA, called Endless RNATM (eRNA). Different from sa-RNA which amplifies itself but is still unstable, eRNA is a versatile synthetic RNA platform that instructs cells to express the desired protein and it is naturally stable.

4. Data Centers Are Facing a Climate Crisis – Chris Stokel-Walker

When record temperatures wracked the UK in late July, Google Cloud’s data centers in London went offline for a day, due to cooling failures. The impact wasn’t limited to those near the center: That particular location services customers in the US and Pacific region, with outages limiting their access to key Google services for hours. Oracle’s cloud-based data center in the capital was also struck down by the heat, causing outages for US customers. Oracle blamed “unseasonal temperatures” for the blackout.

The UK Met Office, which monitors the weather, suggests that the record heat was an augur of things to come, which means data centers need to prepare for a new normal.

The World Meteorological Organization (WMO) says there’s a 93 percent chance that one year between now and 2026 will be the hottest on record. Nor will that be a one-off. “For as long as we continue to emit greenhouse gases, temperatures will continue to rise,” says Petteri Taalas, WMO secretary general. “And alongside that, our oceans will continue to become warmer and more acidic, sea ice and glaciers will continue to melt, sea level will continue to rise, and our weather will become more extreme.”

That weather shift will have an impact on all human-made infrastructure—including the data centers that keep our planet’s collective knowledge online.

The question is whether they are prepared. “From my point of view, there is an issue with existing data center stock that’s been built in the UK and Europe,” says Simon Harris, head of critical infrastructure at data center consultancy Business Critical Solutions. But it doesn’t stop there. Forty-five percent of US data centers have experienced an extreme weather event that threatened their ability to operate, according to a survey by the Uptime Institute, a digital services standards agency.

Data center cooling systems are built using a complicated, multi-stage process, says Sophia Flucker, director at UK data center consulting firm Operational Intelligence. This may include analyzing temperature data from a weather station close to the point where the data center will be built.

The problem? That data is historical and represents a time when temperatures in the UK didn’t hit 40 degrees Celsius. “We’re on the fringes of a changing climate,” says Harris.

“It wasn’t that long ago that we were designing cooling systems for a peak outdoor temperature of 32 degrees,” says Jon Healy, of the UK data center consultancy Keysource. “They’re over 8 degrees higher than they were ever designed for.” The design conditions are being increasingly elevated—but data center companies, and the clients they’re working for, operate as profit-driven enterprises. Data from consultancy Turner & Townsend suggests that the cost of building data centers has risen in almost every market in recent years, and construction companies are advised to keep costs down.

“If we went from 32 degrees to 42 degrees, blimey,” says Healy. “You’re having to make everything significantly larger to support that very small percentage of the year” when temperatures rise. “It’s got to be done with caution.”

Data center design companies are starting to consider the historical weather information outmoded and beginning to use projected future temperatures, says Flucker. “Rather than thinking my extreme is 35 degrees, they’re doing projections saying maybe it’s more like 37 or 38 degrees,” she says. “But of course, that’s only as good as how well we can predict the future.”…

…Companies are testing some unusual ways to tackle these challenges: Between 2018 and 2020 Microsoft ran Project Natick, which sunk a data center 117 feet below the sea offshore Scotland to insulate it from temperature fluctuations, among other things. Harris says that building data centers in ever more northern climates could be one way to avoid the heat—by trying to outrun it—but this comes with its own problems. “Developers will be fighting over an ever-dwindling pool of potential sites,” he says, a challenge when edge computing puts data centers ever closer to the point at which data is consumed, often in hotter, urban areas.

 Liquid cooling technology offers a more practical solution. Data centers are currently in an era of air-based cooling, but liquid cooling—where liquid is passed by equipment, transferring the heat and syphoning it away—could be a better way to keep temperatures down. However, it isn’t widely used because it requires a combined knowledge of cooling and IT equipment. “At the moment, these are two very separate worlds,” says Flucker. “There’s definitely some apprehension about making such a big change in how we do things.”

5. Mission impossible: Recovering 3AC’s missing assets – Scott Shuey

When DRB Panama first filed a suit against Three Arrows Capital (3AC), few people thought its claim would throw the massive hedge fund into a death spiral or kick-start a global hunt for hidden assets.

After all, 3AC was a giant, with assets estimated at US$10 billion, according to crypto intelligence firm Nansen. DRB Panama, the operations arms of dutch crypto exchange Deribit, was only seeking US$80 million.

But DRB was just the first in line at the courthouse. Other creditors quickly joined the suit, and it soon became clear that 3AC owed almost US$3.4 billion. To make it worse, the paper trail for the firm’s once incredible portfolio reads like a giant edition of Where’s Waldo?…

…DRB Panama filed the suit against 3AC at the end of June. It went to court in the British Virgin Islands (BVI), where 3AC has been registered since 2012. In under two weeks, the court decided that the crypto hedge fund’s liabilities far exceeded its assets and ordered the company liquidated.

The first thing lawyers had to do was identify what remained of the company’s assets and sell them off. These proceeds are then used to pay creditors, usually netting them pennies on the dollar and helping them pay off legal fees.

But 3AC’s situation isn’t your run-of-the-mill bankruptcy case. According to lawyers that Tech in Asia spoke to, this is the first major liquidation involving massive volumes of cryptocurrencies.

The job of finding 3AC’s crypto assets fell to Christopher Farmer and Russell Crumpler, both from the BVI offices of advisory firm Teneo, who were appointed as liquidators. Tech in Asia reached out to Teneo for comment but did not get a response…

…The majority of 3AC’s assets were in crypto. The company had an unknown number of wallets, though Tech in Asia has seen seven so far that are likely connected to 3AC.

Four wallets identified by Nansen as being associated with the hedge fund held US$50 million in tokens as recently as July 15. One wallet by itself held over US$38 million in stablecoins. Some wallets appeared neglected with only a small number of trades, while some include transactions that liquidators are still trying to explain.

Tech in Asia spoke to analysts, including lawyers and blockchain experts, who say that while some of the assets are sitting in plain sight, some will never be recovered.

Even the crypto assets that investigators do know about could be forever locked away, unless the private keys that can unlock them turn up. For all the world knows, those keys could be with 3AC’s founders, Zhu and Kyle Davies, whose exact whereabouts are currently unknown.

The need to recover cryptocurrencies might be a relatively new problem for the legal community, but lawyers are increasingly hiring blockchain analysts to track these assets.

6. RWH011: The Emotionally Intelligent Investor w/ Daniel Goleman – William Green and Daniel Goleman

William Green (00:12:35):

If I remember rightly Dan, you were actually bankrolled to go off to India and spend time researching this. And then, you came back and you wrote about meditation as an intervention for stress as part of your PhD program in the psychology department. Is that right?

Daniel Goleman (00:12:51):

It is right. But the detail’s a little more interesting. I had a fellowship actually from Ford Foundation that included a year of traveling study abroad, which I actually I didn’t know about. But then, I took advantage of when McClelland fronted for me saying, oh yes, he has serious research to do in India. And that allowed me to hang out with Neem Karoli and Lamas and Sufi and yogis. I was very interested in how meditative practices and related spiritual disciplines transform the mind and the heart.

Daniel Goleman (00:13:21):

And when I came back to Harvard, I thought I wanted to communicate this to other psychologists, but other psychologists weren’t very interested in the day. And, what I ended up doing was showing that meditation was a useful intervention in stress, which by now, decades later has been well established. But then, that was a radical idea.

William Green (00:13:43):

You said at the time that there were only three scientific papers on meditation, right? This must have seemed-

Daniel Goleman (00:13:50):

Well, William actually, by today’s standards, they were all somewhat dubious, they’re anecdotal reports. And two of them were anecdotal reports and one was a non peer reviewed publication. Our standards are higher these days. When I look at my dissertation, given the measurements we had decades ago, I don’t think it would be published today. Now, you would use brain imaging or you’d use much more sophisticated methodology. We didn’t have them back then.

Daniel Goleman (00:14:17):

So I would say this, that the hunch that I had that meditation really can help you be more calm and more focused has been tremendously well-validated. I finished a book published a couple years ago with a friend Richard Davidson, who was also a graduate student with McClelland at Harvard and Richie, as we call him, has gone on to become a world famous neuroscientist, University of Wisconsin. He and I wrote a book looking at the now thousands of peer reviewed articles on meditation, which shows very clearly there is a dose response relationship. The more you do it, the stronger the benefits are.

William Green (00:14:54):

It’s a brilliant book. We’ll hopefully talk much more about meditation later, but this is among other ways of controlling our emotions, both in investing and life. But this is a book called Altered Traits, which is on my table here behind me and I’ll put it in the show notes, but it’s a terrific book. So in a strange way, you were coming back as this exotic creature from India and I think Sri Lanka and coming back into this world that didn’t really know what had hit it, right? That wasn’t particularly interested in Eastern yogis.

William Green (00:15:21):

And so in some sense, is it fair to say that without maybe being conscious of it, you were somehow reconciling or bringing together these two very different worlds, the scientific realm of the Harvard psychology department and the realm of people like Ram Dass and Neem Karoli Baba, and their world of Eastern spirituality, where they’d been sitting around watching the brain for the last 2000 years. And, I think believed that you could change the brain, whereas Western psychology, am I right in thinking believed it was much more fixed?

Daniel Goleman (00:15:51):

Well, yeah, at the time when I came back, we didn’t have the understanding in neuroscience of neuroplasticity, that came much later. Neuroplasticity says, basically the more you exercise brain circuits, the stronger the connectivity between them becomes. This is now very well established. Then, no one even entertained that idea. Brain science was just beginning to emerge back in the day. And not only that, there was a lot of skepticism about the east when I wrote the book. So as you point out, I couldn’t really find a job that suited me in academia. After getting my PhD, I went into science journalism. I ended up at the New York Times and writing in science.

Daniel Goleman (00:16:32):

And, it was then that I wrote the book, Emotional Intelligence, which I was really thinking of people in the business world, in the education world. And the message was not one of, in Asia, they completely transformed their brains in mind, it was more, this will help you because the Western culture is very pragmatic. It’s like, what use is this? Can I focus better? Can I stay calm even in a turbulent situation? Think of an investor, your investment fails and all of a sudden you’re overwhelmed by fear or anxiety. How do you handle that?

Daniel Goleman (00:17:10):

Well, emotional intelligence speaks to that. And how do you stay focused, amidst all the distractions that we have today, emotional intelligence speaks to that. So I’ve really made a point of being more pragmatic, even though the way I think about it is deeply informed by what I’ve been exploring from Asia.

William Green (00:17:31):

So in a sense, you almost had to conceal the more spiritual part of your journey, because in a way it was so unconventional in those days, whereas now it’s probably much easier for you to talk about that openly.

Daniel Goleman (00:17:44):

Well, yeah, I think that the culture has changed enormously. Mindfulness is everyday news now. You mentioned I was in Sri Lanka, that was on a post-doc and I went to study with a monk named [Nana Panika Terra 00:17:58] who wrote about the mind and how to work with it and how to transform it, based on fifth century texts that were written as manuals for meditators. Nana Panika who actually was German by birth, but had been a monk since the twenties was a scholar of poly. And so he had access. And what I realized William, was there’s the psycho technology, which is well known in Asia, well established, it’s been functioning for thousands of years, literally, and that we know nothing about it in Western psychology until very recently. Very recently.

Daniel Goleman (00:18:35):

So, when I started looking into it, it was unknown. I faced a lot of actual open hostility about it, which probably encouraged me to be a little bit sub rosa at the beginning because things had not changed. And it may be that I and a host of other people had a hand in changing it. In India, I met someone named Joseph Goldstein who became one of the first major teachers of what’s called insight meditation and a whole generation. Sharon Salzberg, another name in that world.

Daniel Goleman (00:19:07):

I met Sharon and Delhi and I told her, hey, there’s this meditation course. So she went to Boga and learned what she now teaches. So, I guess I get some karma credit for all the good Sharon is.

William Green (00:19:17):

She’s an amazing teacher.

Daniel Goleman (00:19:19):

Yeah. But what I’m saying is that when we all started, this was very new in the west. And of course that small group can’t take credit for the transformation, but was part of it. And now it’s much easier to talk about these things…

…William Green (00:57:39):

And again, I think Sharon Salzberg teaches that on the 10% Happier app, which I hate to be a sheal for. And I’m not being paid to be a sheal for it, but it really helped me. And I think that it’s a very helpful app. You have an extraordinary thing in Altered Traits where you talk about Mingyur Rinpoche, one of these great Tibetan yogis and what was going on in his brain when he was doing compassion meditation. This is the deep end of the pool. Can you talk a bit about what actually we saw in his brain?

Daniel Goleman (00:58:06):

So Richie Davidson flew these yogis over from Nepal and India and Europe. One by one. One of them was this Yogi Mingyur Rinpoche who at the time had done 62,000 lifetime hours of meditation. Well, if you do a traditional Tibetan three year, three month, three day retreat, you get credit for about 10,000 hours. So this guy had done huge amounts. And when they asked him to do a compassion meditation, the circuitry in the brain for that increased in a moment by 7 to 800%. Never been seen before in neuroscience, such a voluntary jump in the activation of a brain circuit. And, this is a circuitry for compassion. And so I thought it was pretty astounding.

William Green (00:58:51):

Yeah. I think one of the things that’s so remarkable that your book shows is that we are seeing scientifically this thing that people are sitting in caves for thousands of years in Tibet and the like, figured out experientially. And so you no longer need to kind of sound like you are a woo woo mystic, you can actually show what’s going on in the brain. And I see this as a woo woo mystic myself. So I’m not dismissive of that.

Daniel Goleman (00:59:16):

Here’s the thing, I kind of have a foot in both worlds, in the world of Asian spirituality and methodology and the world of science and psychology and so on. And at first, there was a huge gap between those worlds. But as science has investigated these practices, it’s finding, oh, you know what, this works. And it seems to me there’s an ancient psycho technology that’s been well preserved in many Asian cultures. It’s only now becoming known in the west. I think it’s very important.

William Green (00:59:50):

It’s interesting because Buffet’s partner, Charlie Munger, who’s this 98 year old problematic genius who studies all these different fields will say, I observe what works and doesn’t work and why. And this is one of those things where it’s really interesting. You observe it in the laboratory, you observe it in people’s behavior. And you’re like, oh, it works. And so, I’m struck by how many very successful investors meditate on this podcast. I talked with Ray Dalio about the fact that he’s been doing transcendental meditation 20 minutes or 40 minutes a day for 50 years, basically. And so, here you have the guy who’s made more money as a hedge fund manager than anyone else in history. And I think that’s interesting.

William Green (01:00:29):

He claims that it also makes him much more creative. But, he talks about amygdala hijackings. Actually, he talks about the fact that he’s less likely to get swamped by emotion. And he’s gone through a great deal, as we spoke about in my interview with him, he lost his son a year or so ago. And so he’s dealt with extreme pain. And so the fact that meditation has helped to make him more resilient, more clear headed. I think it’s curious when these pragmatists like Dalio start to adopt something that used to seem fringe.

Daniel Goleman (01:00:59):

Well, that’s the culture shift that I’ve seen over the last several decades is that people like Ray Dalio are doing it as a matter of fact, not a big deal. It’s, I go to the gym and I meditate, it’s self care.

William Green (01:01:12):

And I think if I remember rightly that he said that anyone at his firm Bridgewater, they would pay for them to go meditate, for them to take transcendental meditation and training, which is very interesting that they would regard it as sufficiently a competitive advantage that they would actually bankroll it.

7. Reality Catches Up – Morgan Housel

An asset you don’t deserve can quickly become a liability

Maybe your portfolio surged during a bubble, your company hit a monster valuation, or you negotiated a salary that exceeds your ability. It feels great at the time. But reality eventually catches up, and demands repayment in equal proportion to your delusions – plus interest.

These debts are easy to ignore because they are often repaid in the form of self-doubt and crushed morale. But they are very real, and when you understand their power you become careful what you wish for…

…WeWork is currently worth $3.5 billion, which is a monster success for a 12-year-old company – it’s probably in the top 0.0001% of business successes. But of course no one feels that way. The company was worth $47 billion a few years ago, and it was trying to go public at a $100 billion valuation, which no one could justify but felt fun because those were the times we were living in. So by comparison today’s valuation feels like a corporate bellyflop – embarrassment, employees whose stock options expired worthless, and morale shattered as it laid off thousands of people. Every cent of valuation it didn’t deserve was a debt that came due without mercy. What should be a company celebrating its enormous success is instead a company whose head hangs low and whose former employees hold a grudge – that’s the debt coming due…

…I knew people during the housing bubble who went from earning $8 an hour delivering pizza to $250,000 a year selling subprime mortgages. Of course reality came due, and their income went back to normal. But not a single one of them considered their flash of money to be a lucky windfall – in every instance it became a number to anchor to, a source of bitterness and self-doubt when reality returned. And in every instance the money funded a lifestyle that eventually had to be surrendered, which became a point of social shame, particularly when a spouse and kids were involved. The money didn’t feel like a windfall because it wasn’t – it was a hidden form of lifestyle debt that abruptly came due.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google). Holdings are subject to change at any time.

What We’re Reading (Week Ending 31 July 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 31 July 2022:

1. Matthew Ball – A Manual to The Metaverse – Patrick O’Shaughnessy and Matthew Ball

[00:09:15] Patrick: Can you just define what you mean by the metaverse and what you think a good working definition is that allows us to test things to say, is this thing that everyone’s excited about, or is it not? It seems obvious from our many conversations that the trend has been towards more digital engagement and participation. And that somehow, people think of the metaverse as the natural endpoint of this, where there’s more sensory immersion in some virtual world, there’s more navigability, there’s less walled gardens. How do you define the metaverse in its simplest definition so that we can all work off the same idea?

[00:09:50] Matthew: A live 3D version of the internet as we know today is the best and simplest way to think about this. Why? Because it not only explains how it’s a little bit different visually experientially. It keys into some of what you just mentioned, which is how it might be more intuitive. Of course, we didn’t evolve for thousands of years to tap glass, to interact with 2D interfaces, static information. We explore, we immerse in 3D. It’s a much better interface for many tasks. Far from all, but many tasks. But most importantly, we take for granted the interoperability of the internet and how important that is to everything we do and create. We don’t think about this question of the New York Times can’t link to Washington Post. We don’t even think about the idea that you can’t link directly to the specific piece of content on the Washington Post. We don’t concern ourselves with, “Darn. I took a photo on my iPhone that I stored to iCloud, and the file format therefore doesn’t work on Facebook.” You can take a photo, upload it to Facebook, right click save as, put it onto Snapchat, screenshot it on Snapchat, upload it to TikTok. So we have this vast network that manages hierarchy, communications, reference, the transference of data across different autonomous systems coherently, safely, consistently. And then file formats and conventions that run university. We have a lot of 3D stuff today. There’s a tremendous amount of time being spent in 3D platforms. What we don’t have is a scalable network that actually interconnects. And as we’ve learned from the global economy, world trade, as we’ve learned with the internet at large, the utility that comes from that is extraordinary.

[00:11:26] Patrick: Can you say a few words about the state of the engines behind three dimensional creativity or three dimensional output? You already mentioned Unity, and you already mentioned Unreal being the two dominant engines that people might be familiar with. But maybe paint a more vivid picture of the history here. And if 3D is literally in the definition of metaverse, it stands to reason that the engine that produces and allows people to produce beautiful 3D outputs is really, really important or central. Can you give us the details on the state of the world today as it relates to 3D engines?

[00:12:00] Matthew: Sure. I love this question. And let me actually start answering it by talking about the state of the world decades ago. I like to position the metaverse as a fourth era of computing and networking. The first was the mainframe era began in the 1950s for the most part, ran until the late 1970s. Let’s keep in mind, mainframe still exists. It’s actually a bigger business than ever. But it was largely superseded in the late 1970s, early 1980s by the advent of the personal computer, Apple, Microsoft, and TCPIP the internet. By the mid 2000s, we hit the mobile and cloud era. And now we’re starting to talk about the next era in the metaverse. What’s fascinating about the metaverse in contrast to the preceding three waves is where it seems to be starting. Seems to be starting as you’ve identified in gaming, consumer leisure. In a small segment in consumer leisure. People like to talk about gaming being larger than film. It’s a bit of a misconception. You’re talking about the theatrical box office. That’s about 40 billion, but of course the video industry’s over 600 billion, gaming’s still around 200. When you take a look at those prior waves, mainframes started with mega enterprises. The internet began with government. Most of the early adopters were again, large corporations. Mobile began with enterprise and government as well. Each of these waves either never came to consumer leisure as was the case in mainframes or came there last. YouTube 2005, Netflix 2007, streaming wars 2019. Consumer leisure tends to be last.

So why is it that the metaverse seems to be starting in the other direction? The answer relates to constraints. Constraints always define a technology from inception to its termination. The constraints for computing and networking in those prior waves was often processing power, broadband speeds, bandwidth, etc. And the result was you couldn’t do much live. You couldn’t share a photo with your grandmother. You couldn’t stream video. But certainly, you could send a Blackberry message in the early mobile era. You could send an unstructured data file or CSV if you were a banker or accountant. So we needed substantial improvements in bandwidth and processing power for these new technologies to have consumer applicability. But the constraints that affected simulation, real-time rendered simulation, game engines was fidelity. It didn’t have the bandwidth or the processing power to do a rich simulation. And what that meant is the government had very little use for it. You couldn’t actually do a military simulation with fake fire. But it was fine for pong. It was fine for space invaders, Legend of Zelda. So we’ve spent decades with the primary area of development of game engines, of real-time rendering and GPU chips coming from consumer leisure. What has happened in the past few years is we have reached a point where the maturing and sophistication of these game engines coupled with the wide deployment of powerful processors means that that applicability has expanded. Automotive companies as I mentioned are using Unreal so that you can help drive your car. You can use LIDAR to scan the environment around you in your Range Rover, understand how to navigate, and then actually pre-drive your vehicle. You can live simulate a building.

And what has happened is the companies that happen to have that expertise come from gaming. Nvidia’s Jensen Huang. Of course, Nvidia’s now the seventh largest company globally. Known to many investors for several years, but largely under the radar compared to most other top 10 companies was founded in the early 1990s, not long after Snow Crash was published. And Jensen has said they never wanted to be a video game company, but focusing on gaming was the best strategic choice they’ve ever made because it had three unique attributes. It was large, it was fast changing, and it was technologically intensive. Many industries like pharmaceuticals have two of those attributes, but they don’t change that quickly. So the mixture of the intensity of these problems, the rapid improvements per Moore’s law has meant that almost all these expertise sit here. Lastly, when you take a look at what this means for the metaverse today, Microsoft’s Activision Blizzard acquisition, the largest big tech acquisition in history, 75 billion in enterprise value. Satya’s press release, the final line of the very first paragraph says it provides the building blocks for the metaverse, the foundations for the metaverse. And a lot of that comes down to game engines.

[00:16:25] Patrick: If you think about the role of IP in the bootstrapping of the first metaverses, what comes to mind? I remember from our first conversation going really deep on Disney, and Marvel, and the incredible gravity and momentum that great IP universes allow for. And that very often, technology supports IP and not the other way around. That ultimately IP is the thing people show up for. They want to do something, they want to watch something, they want to be immersed in something. Activision Blizzard maybe is a good example here, but what is the role of existing or new IP as it relates to speeding up this change?

[00:17:01] Matthew: As with anything that we want to do, any place that we want to go, there’s a reason why Disneyland is more fun than six flags is. If there’s a place that we want to go, especially in a consumer leisure environment, it stands to reason that we want to go to the places filled with the stories and characters that we love. This has classically been Horizon World’s fundamental problem. It’s technically more robust than it is popular. It has better distribution than many other platforms. It doesn’t have content, partly because it doesn’t have as many developers, but in particular, the other platforms have been populated by produced in UGC IP for years now. If we’re to go to a fantastical place, want that to be the place populated with the things we love. This isn’t new. Of course, medieval gardens are adored with gargoyles and giant statues of lions because it provides immersion. We don’t just want to walk down hedgerows. We want to feel like we’re in the place we imagine. This is why many come to the inevitable conclusion that another medium full entertainment or another technological wave which has IP in it is naturally going to advantage those that have the most resident IP today. Disney does not have a gaming business. I think that remains a problem. Mostly because they don’t have the capabilities for it. Whether or not they publish their own titles is a different question, but we’re going to want to live in Disney IP…

[00:26:53] Patrick: As I think about my own usage of Oculus, and I’m a person that wants all this stuff to happen. The idea of the Ready Player One haptic suit, and omnidirectional treadmill, and everything that goes into it, this full immersive experience just sounds fun. I was a video game junkie as a kid. Spent countless hours in some of these virtual worlds. I’m inclined to want to do it and be an early adopter of the technologies. I think I had one of the first Oculus. And when I put it on, what stands out as the Star Wars game, I’m forgetting the name of it. But really being blown away looking around like this is wild. And obviously, it’s only going to get more and more perfectly rendered. I had the problem of getting a headache or a stomach ache when I moved artificially, which I want to hear about what you think about that. But at the same time as blown away as I was, I really haven’t spent much time with Oculus on. And I’m curious if my experience as someone prone to want this to happen who tried it but really didn’t last, is that indicative of the broader experience so far with Oculus? What do you think the reasons for something like that might be?

[00:27:50] Matthew: I want to hit a few different points here, because I think we’re really talking about the suitability of alternatives that challenges with the current technology. And then the likely progression of said technology. Neal Stephenson, who of course coined the term metaverse. So he didn’t originate the idea that spans nearly a century, has talked about the fact that yes, his conception of the metaverse was primarily an AR and VR experience. And he highlights the fact that that was a reasonable, if not the best hypothesis at the time, especially in the science fiction community. But he’s highlighted that technology is path dependent. What we found out in the decade sense is that actually, hundreds of millions can adequately navigate 3D space with WASD on their keyboard. Forward, left, right, and back. Billions can navigate 3D space and choose to do so on a monthly basis using a touch screen. He says that he no longer considers that essential. It may be the best, most popular preferred way eventually. But it’s not a requirement. And if you see Tim Sweeney at Epic shows very little interest, at least today in those new devices. The second part is talking about the experiences that you’ve mentioned. We have a good sense of what is likely to be required for min spec, for mainstream adoption of VR hardware. And I go into this a lot in my book. We tend to think for example that we need a refresh rate of 120 hertz on a VR headset. That’s 120 frames per second. We probably need an 8K display. And I’m going to put aside other concerns for now like battery life, the weight of the device, the heat generated by the device, the number of additional sensors and tracking cameras we need, which constrain all available resources, but just 120 hertz and 8K display. Right now, the top of the line devices typically do 90 hertz and 4K.

So we need a roughly 3X increase in the number of rendered pixels per second, just to hit min spec where people aren’t suffering from nausea. You then layer in these devices have essentially late PS3, early PS4 graphics. Their computational load is much lower. Call of Duty: Warzone is limited to PC and gaming consoles only, but in exchange, the graphics are great. You can have 150 users. Fortnite plays on most devices, but as a result, you can only have 100 users. Free Fire from Garena is designed to work on all low end Androids. And as a result, it only has 50 players. Population one on the Oculus, their battle royale has only 18 players. So now we have a device that has half the resolution we want, two thirds of the frame rate that we want. It has PS3, PS4 graphics. And you can only have 18 other users. And then again, it probably has one eighth the sensors that we want, one third the battery life. It’s probably 25% too heavy. There’s a lot that we need to solve for these just to become min spec for nausea and usage. And then on top of that of course, we need these devices to be more than min spec. They need to feel better. The rejection of sensors, which is unique to VR. You can multitask on your PlayStation, you know whether or not your house is on fire. Your kids are upset. Your dog is getting into trouble. Probably raises that above min spec. We’re getting there. We’ve roughly doubled resolution density. We’ve doubled processing power since 2017. So those who say we’ve been here before, people don’t like VR don’t appreciate the headway that we’ve made in these devices. But it’s a lot like GPAs. It’s easier to go from a 3 to a 3.4 than it is to go from a 3.6 to a 3.8. And we saw this recently as medic kicked out their releases for AR devices again, for the third time this decade. This is a hard tech problem…

[00:37:07] Patrick: This idea of everything talking to everything brings up one of the most interesting topics in all of this, which is the word interoperability. This word has gone from no one ever saying it to everyone saying it in five years. Both because of the metaverse and this next era of computing, but also because of blockchains, interoperability means a lot, is critical. No one really knows what the hell they’re talking about it seems like when they bring it up. But it brings to mind things like standards and protocols. Again, the boring base layer stuff that makes the modern world possible. Whether it’s visa, or TCP/IP, or SMTP it, some of these things you and I have talked about before. Can you talk about why interoperability gets its own chapter in your book, why this is such a key critical concept? And who might actually sponsor or start these things? Because many times in history, they’re not for profit. It’s a protocol. So walk us through this concept, because it seems like it’s at the bottom of everything.

[00:38:00] Matthew: The fundamental premise of interoperability is a little bit foreign to the average person because we take for granted how interoperable online existence is today. You have a common identity at least in some way, shape, or form that you can take into multiple different avenues. Your content, the content that you create is inherently interoperable because the file formats are relatively standard and embraced everywhere. Ping runs everywhere. JPEG runs everywhere. Every unit of content we create today essentially runs everywhere else. Your text, your audio, your video, not just an image can be uploaded to every different environment. And in fact, the worldwide web itself works because of elements of TCP/IP, but also other consortiums and working groups of feathers that maintain a cohesive hierarchy or IP address, the domain registrar system. This is important not just for the continuity of the web, the cohesion of your personal experience, the persistence of things done online. But they’re also important for competition. If you don’t like your web hosting company, you can just move your information to another. You can change domain all the time. So we should think of interoperability as important to content creation, as important to user rights, as important to the actual thriving economy of the internet. And you’re right to talk about the ways in which those are not managed by a central for profit body. But ultimately, we can reduce it to a simple idea. It’s expanding the network effects of everything that you do online, but that doesn’t exist in the virtual world. Roblox individual worlds can identify one another, but they have no ability to understand, least of all, even identify another virtual world. Be it in Fortnite, an educational forum, a training sample.

Communicating from one live services suite to another doesn’t really exist either. There’s no consistent way to store information. And least of all, the ability to take a 3D object whether it’s created for industrial purposes for a simulation. Northrop Grumman wants to test an engine and then see how it performs in a specific environment. They don’t really have a cohesive way to take that object from one simulation to another. So this question about interoperability is really about expanding the utility, practical applicability of everything in the metaverse. And I’ll drop this down to a simpler example. The world economy of course runs on standards, defacto and otherwise. And it’s essential to reducing the friction to all transactions to increasing the utility of all investments and purchases. What are those standards? USD is one. English is another. The metric system is a third. The intermodal shipping container. You’ll note of course that there are often many other standards. We also use the Euro. We also use German. There are multiple different types of shipping containers, not all intermodal. Metric and imperial sit side-by-side, often in the same country, often within the same business. So we shouldn’t think of interoperability from a panacea perspective. And this is one of the flaws I’m often asked, can we ever have interoperability? Yes, we’ll never have it perfectly, never have it exhaustively. The world doesn’t work that way. The internet doesn’t work that way. We still have private networks, offline networks. We still have paid and proprietary protocols. You often need an installer to access experience A or B, and there are often paywalls. But making it so that every 3D object, every experience, more purchases can move, can endure, have utility beyond that first creation is going to be key to actually building up this economy.

[00:41:45] Patrick: Help me understand how we can bridge that gap of something I build, own, earn, achieve in some place that I want to bring to some place else. If I think about games, and maybe that’s the wrong way to think about it. The object I win and spend hours looking for in Diablo is really not relevant in Fortnite, is really not relevant in Sims. It seems like even though there are all these great worlds, the idea of bringing stuff between them is hard to imagine because the worlds themselves are so different. So how do you think this happens? How does Roblox get connected to Fortnite? How far down do we have to go to build the bridge?

[00:42:23] Matthew: One of the challenges with interoperability discussions is that we often focus on the easiest to understand, but arguably the least useful example. And that is taking your Peely banana skin from Fortnite and bringing it into Call of Duty. There are so many problems with that. The engines of course are different. And I just want to highlight how different these engines often are. Unity and Unreal actually have different coordinate systems for X, Y, Z. They store information Y and Z differently. Now that’s easy for a computer to manage. You just have a translator. It works the same way that English to German does. You say let’s swap Y and Z. But if they have fundamental disagreements on coordinates, you can imagine how sophisticated some of the disagreements are. That naturally leads game designers in particular to say, “Why does that matter?” Putting aside the economic considerations, do you want to be appealing in Call of Duty? Is it cohesive with the aesthetic? Does it fit in a doorframe? Frankly, the Peely file format might be stored in a way that makes it three stories tall in Call of Duty. When you look at my metaverse definition, I talk about the continuity of data from 3D objects to entitlements, payments, communications, history. The object itself, the avatar is probably the least important element of that. We’re a little bit more concerned with when you do an educational exercise in school, 3D simulation in school is probably one of the most important innovations that we can see. We’ve learned that distanced education is terrible. We have long expected the advent of the internet and digital devices to see productivity improvements in education. Haven’t happened. We know that multiple choice is terrible, that playing a YouTube video is terrible, that Zoom school is terrible. But the ability to make real The Magic School Bus is intuitive.

I grew up making volcanoes out of paper mache, baking soda, and vinegar. Now, you can start to do that in realistic simulations where you are personally agitating the magma being ejected into the atmosphere, and seeing the time lapse implications on the environment. Building a Rube Goldberg machine to learn physics, rather than just watching a video of a NASA commander drop a feather and hammer on the moon. You can take that Rube Goldberg machine to the moon, to Mars and Venus. But of course, we believe that some form of interoperability or continuity of what you’ve done, and what that information is, and who you are is essential. We’re not going to have the same school pack for chemistry as for English. So it’s not as important that I take my banana skin from A to B, it’s more important that I can consistently manage my profile. But all of this requires formats, more importantly conventions, a whole bunch of other buzzwords. Frameworks of frameworks, systems of systems. But how does it emerge? It emerges in a well known way, the same way that USD and English did. It’s often network effects reiterated the incentives of changing systems. But again, never perfectly. Last week, we had the establishment by the Khronos foundation, the metaverse standards form 28 companies. Many notable omissions, Apple, Google, many other content providers. But Epic, and Meta, and so forth, Qualcomm all saying, “Let’s start to standardize our roadmap. We have to understand what we can build towards for the collective utility.” That’s the easiest step. No one has to make a sacrifice to their tech roadmap. No one has to pick a standard they didn’t like. But that formation period has already begun. And even Roblox has started talking extensively about their need for their developer economy to start to figure this out.

2. CRISPR Technology for DNA Editing Might Raise Cancer Risk, Israeli Scientists Warn – Gid’on Lev

But Tel Aviv University researchers are highlighting the risks of CRISPR, which stands for clustered regularly interspaced short palindromic repeats. The scientists examined how the technology affects the immune system’s white blood cells – T cells – and found that some of the patient’s cells had chromosomal truncations – a loss of DNA fragments, a characteristic of cancer.

The first trial approved for using CRISPR to treat people was done by researchers under Prof. Carl June at the University of Pennsylvania. The scientists removed T cells from a healthy donor and changed the so-called cell receptor on them to better identify cancer cells.

The researchers also used CRISPR to destroy the original cell receptor so that the engineered T cells wouldn’t recognize and mistakenly attack cells of the recipient and another molecule that cancer cells use to exhaust T cells. The engineered cells were injected into cancer patients whose cancers did not respond to any other treatment.

The results were published in 2020 in the journal Science: The engineered cells survived in the patient’s body for a long period and homed in on the cancer cells, even though they didn’t destroy the growth entirely.

The general consensus in the field was that after CRISPR’s excising of undesired parts of DNA, the cell carries out repair. In the new study, the researchers conducted a test to determine if indeed this repair mechanism works perfectly or that maybe repair doesn’t always occur, and when it does, it’s not always complete.

To examine the technology that presents this risk, the scientists reconstructed the trial conducted at the University of Pennsylvania. They used CRISPR to cut the genome of T cells in exactly the same places where June and his colleagues did: at chromosomes 2, 7 and 14. (Each human cells has 23 pairs of chromosomes.)

They then analyzed thousands of cells and found that up to 10 percent of the chromosomes that were cut did not repair themselves…

…With CRISPR, T cells can be made to better recognize cancer cells and prevent the recognition of normal cells. Furthermore, CRISPR can be used to remove the molecules that act as brakes on T cells, allowing the cells to exert their full killing potential.

Following the use of CRISPR, a mechanism in the cell repairs the cut DNA, but sometimes the cell fails to be repaired and might even lose large parts of the chromosome. This is serious because of the association with diseases including cancer.

In reenacting the research at the University of Pennsylvania, the Tel Aviv University scientists – aided by the students Alessio Nahmad and Ella Goldschmidt, and research assistant Eli Reuveni – sought to investigate CRISPR’s safety in general, not just in treating cancer.

“CRISPR only cuts and removes the DNA sequence at desired points. The natural mechanism of DNA repair in a cell is what’s fusing the cuts together and keeping the chromosome intact,” Ben-David says.“But sometimes the cell fails to execute the repair, and after this failure large parts of the chromosome – or even the entire chromosome – are lost. That creates a very serious situation because of aneuploidy – a change in the number of chromosomes.”

Ben-David says aneuploidy occurs in 90 percent of solid tumors; it’s the most frequent genetic change in cancer, more so than DNA mutations.

“In healthy cells, it never happens. There are always 46 chromosomes,” he says. “If in the process of genome editing via CRISPR, aneuploidy cells are generated and injected into the patient, this could be a serious problem. Until now, this problem hadn’t been examined in depth.”

3. Tails, You Win – Morgan Housel

Long tails drive everything. They dominate business, investing, sports, politics, products, careers, everything. Rule of thumb: Anything that is huge, profitable, famous, or influential is the result of a tail event. Another rule of thumb: Most of our attention goes to things that are huge, profitable, famous, or influential. And when most of what you pay attention to is the result of a tail, you underestimate how rare and powerful they really are.

Venture capital is a tail-driven business. You’ve likely heard that. Make 100 investments, and almost all of your return will come from five of them; most of your return from one or two.

Correlation Ventures crunched the numbers. Out of 21,000 venture financings from 2004 to 2014, 65% lost money. Two and a half percent of investments made 10x-20x. One percent made more than 20x return. Half a percent – about 100 companies – earned 50x or more. That’s where the majority of the industry’s returns come from. It skews even more as you drill down. There’s been $482 billion of VC funding in the last ten years. The combined value of the ten largest venture-backed companies is $213 billion. So ten venture-backed companies are valued at half the industry’s deployed capital.

There is a feeling, I’ve noticed, that this low-hit, high-stakes path is unique to VC in the investment world.

I want to show you that it’s not. Long tails drive everything…

…J.P. Morgan Asset Management published the distribution of returns for the Russell 3000 from 1980 to 2014. Forty percent of all Russell 3000 stock components lost at least 70% of their value and never recovered. Effectively all of the index’s overall returns came from 7% of components. That’s the kind of thing you’d associate venture capital. But it’s what happened inside your grandmother’s index fund.

You can drill this down even more.

Amazon drove 6.1% of the S&P 500’s returns last year. And Amazon’s growth is almost entirely due to Prime and AWS, which itself are tail events inside a company that has experimented with hundreds of products, from the Fire Phone to travel agencies.

Apple was responsible for almost 7% of the index’s returns. And it is driven overwhelmingly by the iPhone, which in the world of tech products is as tail-y as tails get.

Who’s working at these companies? Google’s hiring acceptance rate is 0.2%. Facebook’s is 0.13%. Apple’s is about 2%. So the people working on these tail projects that drive tail returns have tail careers…

…A takeaway from that is that no matter what you’re doing, you should be comfortable with a lot of stuff not working. It’s normal. This is true for companies, which need to learn how to fail well. It’s true for investors, who need to understand both the normal tail mechanics of diversification and the importance of time horizon, since long-term returns accrue in bunches. And it’s important to realize that jobs and even entire careers might take a few attempts before you find a winning groove That’s how these things work.

4. Speculation in 1980s Taiwan – Michael Fritzell

The financial bubble that gripped Taiwan in the 1980s is one of the greatest that the world has ever seen. Stock prices went up by more than 12x in less than four years.

At the peak of the bubble, over 5 million – one-third of all Taiwanese over the age of 15 – were actively playing the stock market.

This is the story about the boom and the bust of Taiwan’s little-discussed but spectacular stock market bubble, as retold in the book The Great Taiwan Bubble by Steven Champion…

…Before 1983, there wasn’t really any effective, legal way for an international investor to buy Taiwanese stocks. In the mid-1980s, however – the stock market was finally opened to foreign investors. Money started pouring in.

Capital inflows caused interest rates to plummet. Meanwhile, households felt loss aversion now that their bank deposits yielded almost nothing. So they sought higher in other financial instruments. Some of that money ended up in the stock market.

In 1985 – at an early stage of the bubble – the Taiwan Capitalization Weighted Stock Index (Taiex) was trading around the 700-mark. It had come off a bit from a previous high in 1984, but not many people were paying attention to the market yet. That would soon change.

An illegal lottery called “Dajia Le” (大家樂) was launched in 1985. It spread like wildfire through the nation, especially in Central and Southern Taiwan. For as little as 300 or 500 Taiwan Dollars, you picked a number from 00 to 99 and could get a jackpot of 15-19x – far more than any of the state-sponsored lotteries. It became a great success throughout Taiwan. Suddenly, just about everybody was into illegal gambling.

The reason why Dajia Le flourished was because of the economic slump in the summer of 1985. The unemployment rate increased to a decade-high of 4.1% and 320,000 unemployed Taiwanese were walking the streets in search of jobs. Many of them became disillusioned and turned to gambling.

After a few years, the government cracked down on these illegal lotteries. The state-sponsored Patriotic Lottery ended abruptly in 1987 and illegal lotteries such as Dajia Le were also shut down shortly thereafter due to government pressure.

Author Steven Champion described how hundreds of thousands of these gamblers were then in search of a new fix. He imagined that many of them must have turned into stock market speculation as an outlet for their lust for gambling.

The author worked as a fund manager in Taiwan in the 1980s. In 1986, he observed the market and saw it rise through the key 1,000 level. In his letters to investors, he opined that the market had become extended and suspected it was due for a correction. He just couldn’t imagine that it would rise any further.

Optimism was in the air though. In 1987, Taiwan officially became a democracy and many believed that the future was bright. Martial law was lifted, new political parties were formed and media censorship was eased.

There was scepticism throughout the whole stock market boom, but the scepticism gradually dissipated as bullish voice turned louder. Financial professionals were most nervous when the market bolted through the 1,500 and 2,000 levels but got calmer and calmer as prices went into the stratosphere.

The central bank issued new brokerage licenses and eased listing requirements. There was a huge increase in the number of licensed brokerages, from 27 in June 1988 to 297 in March 1990. Easily available but generally illegal, margin credit was provided through many of these brokers.

The new brokerage firms pushed stocks to retail investors. The larger cities Taipei and Kaohsiung were blanketed with new brokerage offices. The major firms then set up new shops in the secondary cities of Taichung, Tainan, Chiayi, Hsinchu and Changwha. When those reached saturation, brokerage firms finally opened up offices in even the most obscure country villages like Shalu, Fuhsing, Chubei, Huwei, Wuchi, and Huaton. Looking for new market niches, brokers established offices specifically targeted at housewives, doctors, farmers and students to lure more customers in…

…Suddenly, just about every single Taiwanese became involved in the market. An astonished foreign media jokingly started calling Taiwan “the Republic of Casino” instead of its official name “Republic of China”.

Students at National Taiwan University began to cut morning classes. Primary school teachers quizzed their students to see what stocks their parents were buying. High school girls desperate to accumulate savings to throw into the market turned to part-time prostitution.

60% of financial reporters owned stocks, and 84% of this group admitted their involvement in insider trading. When interviewed, 30% of those reporters admitted to considering abandoning their profession so that they could play the market full time.

In 1988, Taiex broke through the 7,000 mark – up over 10x since 1985. In brokerage offices, retail investors celebrated with champagne and happy faces…

…The market wobbled briefly in 1988 but quickly regained momentum. During that year, new president Lee Teng-hui appointed Shirley Kuo as Minister of Finance. To control the stock market bubble, Kuo announced a tax on gains derived from securities transactions. Taiex plummeted for 19 straight days, dropping from above 7,000 to below 5,000. Investors took to the streets and laid siege to the Ministry of Finance and Kuo’s residence. Fearful of losing next year’s elections, the government backed down and cancelled the tax. Stock prices exploded with renewed fervour.

It only took a few months to recover the previous high. As the market surged through the 6,000 level, then 7,000 and 8,000 stockbrokers held wild celebrations on their trading floors. Brokers offered free champagne, exploding firecrackers, balloons, buffet lunches and musical performances to their most loyal customers…

…The compounded return over the previous five years had hit international records. The Taiex had gone from 1,000 points in 1986 to 12,000 in 1990. Stock prices multiplied by more than twelve times in less than four years.

By the fall of 1989, the average price-earnings ratio on the Taiex was 100x – roughly double the already-high P/E multiple of 51x in Japan at the time…

…In early 1990, the market started wobbling. It looked like the market was taking a rest before scaling new, unchartered heights – just like it had done so many times in the past. But instead, the market entered into a vicious bear market that stunned most retail investors.

Many retail investors thought that the government provided almost guaranteed protection on the downside. The Kuomintang party had used the booming stock market as a slogan for their recent election campaign slogan, “Big Profits and Great Prosperity”. Many interpreted this as an implied guarantee against market losses. Yet despite continued optimism, the market drifted lower.

Trading volume reached new highs just after the crash, with traders doubling down on every single dip.

And then slowly, denial turned to anger, to depression and a gradual acceptance of the new reality.

Taiwan’s stock market bubble was finally over.

5. TIP466: The Bear Has Arrived w/ Jeremy Grantham – Trey Lockerbie and Jeremy Grantham

Jeremy Grantham (00:10:27):

I wrote a piece, Reinvesting When Terrified that by sheer luck came out the day the market hit its low and it said, “Get a policy, get a plan, present it to your committee or yourself and start to throw your money back into the market. You feel paralyzed, everyone always does and now’s the time to wake up, the market is cheap.”

Jeremy Grantham (00:10:46):

Of course, that happened in 1974 and ’82, which were classic lows and the market got down to seven PE and what I call terminal paralysis, sets in where you’re so frightened you can hardly move. You can hardly get to work, forget to buy stocks and that’s of course, as Warren Buffet would’ve said, that’s exactly the time you have to do it and it’s only 5% of the time, they are much quicker than the crazy bull markets.

Trey Lockerbie (00:11:11):

Now, I know you’re a huge skeptic of the Fed. Have the Feds rate increases and tightening efforts on the market or the market’s response surprised you in any way?

Jeremy Grantham (00:11:22):

No, I expect the Fed to be behind the curve, to be deep into optimism and it doesn’t really have a clue about market bubbles and the damage they do when they break. They’ve been eager now since early Greenspan to encourage bull markets because they help the economy, they really do and they always forget that the bear markets to go along with them hurt the economy at just the wrong time.

Jeremy Grantham (00:11:46):

If I’d been asked a bet, would the Fed get inflation wrong when inflation came along? At any time I would’ve said, of course they’ll miss it, they’ll be late, their responses will be pretty ill-judged. The Fed’s record is terrible. What is impressive is how much room they have been cut by the market. I mean the market is incredibly forgiving to the Fed. The Fed happened for 25 years to benefit from that amazing era as 500 million Chinese erased into the big cities and were plugged from marginal farming into highly profitable industrial system.

Jeremy Grantham (00:12:22):

Then they joined the World Trade Association and made everybody’s stuffed dogs and everybody’s iPhones for that matter. During that phase 500 million extra Chinese, 200 million Eastern Europeans plugging away from communism into capitalism. That was a golden era, Goldilocks if ever there was one and the Fed got to take credit for that.

Jeremy Grantham (00:12:46):

Prime Minister of England once, Mr. Wilson got reelected because England unexpectedly won the World cup in soccer and he got credit for it. I mean the president gets in the end credit for everything, good weather, he takes the shock for inflation. These things are all way bigger than the president of the United States, but the president and the Fed gets to enjoy the environment, so this Fed had a wonderful environment, they did nothing right, but they were seen to be presiding over low inflation and decent growth. The growth rate actually has slowed way down since Greenspan.

Jeremy Grantham (00:13:22):

It was averaging three and a half before Greenspan and averaging two and a half afterwards and today more like one and a half. It’s done nothing in terms of increasing the growth rate, but superficially it felt like a golden age because asset prices went up. Asset prices went up because inflation came down and rates were allowed to come down and in the end, rates were forced down and low rates make leverage cheap, make private equity deals wonderfully easy and profitable and they push up the price of real estate and they push up the price of stocks and that’s the way it was and the Fed gets the credit for that and it’s due none.

Jeremy Grantham (00:14:02):

D merit accrues from the fact that it kept on pushing down interest rates far too long and dangerously increasing inequality which is, I like to say the greatest poison in the system these days. The degree of inequality we have in the US now it does damage the strength of the economy and that is probably part of the reason why the growth rate has slowed and continues to slow.

Trey Lockerbie (00:14:27):

Now that inflation has arrived, there’s a lot of concern that we’re entering into a 1970s or eighties scenario stagflation. As a historian, could you give our audience an idea of what was happening during that period and how it resembles today?

Jeremy Grantham (00:14:42):

Well, every period is unique. The seventies had problems with the oil crises. You can call it one giant crisis or you can call it two or three, but in any case a triple, quadruple, quintuple the price of oil. In a hurry, we’d come off 50 years of fairly stable, low prices and they shot up and stayed up for a long time and inflicted enormous pain on the system. They lowered the growth rate. Why wouldn’t it? If you have to pay three, four times for your energy and it also, of course pushes up the price, so there’s nothing like an oil price increase to increase stagflation and it did. This time, if you adjust for the passage of time, the price of oil is not as high, but it’s still multiplied recently by three times and so that is imposing pain on consumption and is imposing inflationary pressure.

Jeremy Grantham (00:15:36):

Because of the invasion of Ukraine, we have had some extra spikes in the price of food, fertilizer and natural gas particularly in Europe. Interestingly, they are now almost all of them lower in price than the day before the invasion and this is a lovely example of how the stock market works. The start market is saying, “Whoops, there’s so much damage from commodity prices et cetera, et cetera, that we’re going to have a recession.” The recession isn’t bad news because the recession is going to get the Fed back in our camp of lowering interest rates again and helping stock prices and we’re looking out into the future and therefore that’s the good news, so the fear of a recession becomes wishful thinking about future interest rates and so the market gets a repressed for a while. It’s quite remarkable, but it’s fairly typical.

Jeremy Grantham (00:16:30):

That’s what we’re having now and that’s why we might have a bit of a rally for a few weeks, I think. Yes, what we should cover is how dangerous it is to get involved in a bubble that has more than one asset class, equities, growth stocks mainly. This time we’ve also moved into housing. Housing was chugging along okay, but last year it had the biggest advance, 20% in 2021 [inaudible 00:16:56] it had ever had in history and it went up to a higher multiple of family income, house priced divided by family income. Higher multiple than the peak of the housing bubble of 2006, it just means there’s a lot of value there that can be lost and it is dependent on interest rates. As you know when you’re paying a mortgage that the bottom of the mortgage was two and a half and it went up to 5.7, 5.8.

Jeremy Grantham (00:17:19):

This is a brutal increase in mortgage and means a lot of people will not move houses who otherwise would’ve done, which means a lot of people will not take a new job because they’re not prepared to double their mortgage payments. Everyone expanded to pay as much mortgage as they could afford, which meant that they put merciless pressure upwards on housing prices as the mortgage rates came down, so that’s a problem and then you have problems with a bubbly commodities market inflicting pain on consumption. As if that wasn’t enough, we have the lowest interest rates in 6,000 years as Jim Graham would say or Edward Chancellor’s written a brilliant new book, The Price Of Time. Of course, with the lowest rates in 6,000 years, you have the highest bond prices and that’s obviously been taken to the cleaners this year, too.

Jeremy Grantham (00:18:04):

You have bonds, housing, stocks and commodities. The only people who’ve tried that was Japan in ’89, they’re still not back to the price of the equity market. They’re still not back to the price of the land and the housing market from 89, that’s 33 years and counting. We did some of that in the housing bubble where the stock market came down in sympathy and that was brutal. They give you much greater pressure on recessionary forces and we are playing with fire this time, which was not anywhere near as obvious a year ago before that huge move upwards in housing.

Trey Lockerbie (00:18:40):

The interesting thing about the housing part to me is that with high inflation and to your point about expecting it to have inflation for the years to come, is that it seems like you’d want to own hard assets, so the demand should be there to keep propping up for the foreseeable future.

Jeremy Grantham (00:18:55):

Yes, in the long run, of course housing and stocks are very good protectors of steady inflation. The bad news is that psychologically inflation is associated with a negative, with a drop in PE from a psychological point and pressure on proper margins in the short-term and then it’s adjusts, but it’s very painful adjusting. Of course, it’s associated with a much higher mortgage, but once it’s adjusted, then of course you’re in much better shape.

Jeremy Grantham (00:19:23):

The world is much better off with moderately high interest rates. You get money on your savings, people don’t speculate as much, they don’t leverage as much, the risk in the system declines and you can afford to buy a house at lower prices and you can afford to buy stocks and build a portfolio.

Jeremy Grantham (00:19:40):

At the moment at the peak in December, if you’re young, you can’t get into the game. You can’t buy your first house, you can’t buy an equity portfolio. The yields are half of what they used to be…

…Jeremy Grantham (00:20:38):

I think in the longer term, forget the next few quarters who knows what happens really, but in the longer term, we are really running the risk that this is back to the seventies. We have problems with the availability of plentiful cheap resources and we have problems with plentiful cheap labor. The birth rate has crunched in every developed country except Israel and China.

Jeremy Grantham (00:21:04):

That’s a very, very important segment of the global economy to say the least. Every one of them has a population growth rate lower than replacement level so in the end, after accumulating lots of older people as a higher percentage, we start to actually have the population drop. Secondly, we’re 10 and 20 years in depending on the country into having smaller baby cohorts, so we know with absolute certainty, since they’re alive already that the 20 year olds arriving in the market will be fewer and fewer for the next to 20 years.

Jeremy Grantham (00:21:40):

We have not experienced this before. This has happened incredibly fast. China has gone from plenty of babies to a baby crunch almost overnight and a fertility rate that needs to be 2.1 is probably running about 1.4. Even in the US, the UK we’re running about 1.7. We’ve never seen levels like this, so we’re going to have a hard time getting enough labor. We’re going to accumulate old people who are very resource intensive. They need a lot of medical care, they need a lot of people care and we’re not going to have all that many people there.

Jeremy Grantham (00:22:14):

The supply of people to look after us old fogies is dropping steadily from now on for the rest of your life about, for sure. At the same time, I believe the correct interpretation of the commodity data is that it wasn’t only the China shock, the rapid growth rate for 30 years in China, but it was also showing signs that the best and cheapest, most plentiful resources had simply been mined or pumped and that we are running down into the second tier.

Jeremy Grantham (00:22:45):

If you look at the copper ore for example, King Copper is really important to the industrial system. Over 80, 90 years, the amount of copper in a ton of oil has dropped to a third of what it was, so you’re using an awful lot more energy and the energy also, which used to run for a hundred years at $20 a barrel in today’s currency, now runs at a hundred, so you’re spending five times the cost of energy to mine one third the quality of copper oil.

Jeremy Grantham (00:23:14):

You better believe technology can’t keep up with that. It did for a long time, it did very, very well but starting about 2002, the real price of the typical commodity has gone up a lot, it’s basically tripled.

Jeremy Grantham (00:23:27):

In a hundred years it went from… Starting at a hundred, it went down to 30, a brilliant help for getting rich and then from 2002 until today, it’s gone from 30 to 90, so over 122 years commodities are just about flat adjusted for inflation. Only 20 years ago, they were down at 30 cents on the dollar. This is a huge shift, hasn’t been nearly enough fuss made about it, but it’s the direction that is interesting to me. The direction is steadily up.

Jeremy Grantham (00:23:56):

Now, there’s a lot of volatility and commodities everybody knows. You produce an extra ton and the price collapses and your short a ton and the price triples, but if you look at the trend, the trend has been pretty reversed since 2002. My guess is it will continue to rise and that will pose real stagflationary pressure for a couple of decades and that’s why I fear this is re-entering the seventies and eighties…

…Jeremy Grantham (00:39:04):

I don’t want to get into wishful thinking, but basically as a society, we show all of the signs the failing societies in history have shown and the top of the list is Hubris, “Oh, you’ve been saying bad things for a hundred years and it didn’t work out.” You think the Romans didn’t say that? 400 years and so on and some of the civilizations down in central America where around for a thousand years and they built water storage, they built aqueducts and they had wonderful armies, but eventually they fall foul of a lot of failings and we check them all off.

Jeremy Grantham (00:39:40):

We look like a failing civilization book, but I’m hoping we have a little escape clause We have a couple of things going for us that have never worked before. One of them is population, that has never been a gleam in the eye of [Mouthes and the boys 00:39:54] even as we got wealthier that we would choose to have fewer children.

Jeremy Grantham (00:40:01):

This is remarkable and then adding on top of our choice is the fact that the world is getting so toxic, that even when you decide to have children it’s now getting to be much harder. One way or the other we are likely to have over the next couple of hundred years, a declining population and we have some chance that, that will be a great help. It isn’t a sufficient condition, but it is a necessary condition. The planet, under any circumstances could not support for the 10 billion that one reads about all the time for a hundred years, it can’t be done.

Jeremy Grantham (00:40:35):

We would need two and a half to three planets to cope with that. We can perhaps deal with a couple of billion and we might get there quite graceful. The other one of course, is technology and the rebuttal to the technology argument is that every wave of technology takes more energy back and it takes more complexity, which is a killer because complexity itself is a failing characteristic.

Jeremy Grantham (00:40:57):

It takes too much effort, too much manpower, too much energy itself and if that wasn’t enough, it increases your [inaudible 00:41:06] your overconfidence, every wave of scientific progress and so it can be quite deadly, but this time we have some open ended technologies.

Jeremy Grantham (00:41:15):

I call them, Get Out Of Jail Free cards and because they’re almost infinite fusion, geothermal and brilliantly cheap, effective storage any one of those three and we may get out of jail because that’s enough green cheap energy to in the long run take care of poverty if we chose to, for sure and take care of climate change. The thing about climate change is when we finish, we started 150 years ago with 280 paths per million carbon dioxide in the atmosphere. It’s only a little bit, but it’s a very powerful commodity. If we had no parts, we would be frozen at minus 20 to 25 degrees centigrade, a frozen ball with just bacteria around if we were lucky.

Jeremy Grantham (00:42:00):

It’s a very, very potent greenhouse gas. We started with 280 parts, a million we’re up to 420. That’s a bigger jump than the difference between the ice age, two miles of ice on Manhattan and the pleasant enough world that we have now. That’s a bigger jump, the ice age gap was just a 120 points and we have just gone up by 160 and we’re going to go up to about 525 and we need to go back to 300, so we’re going to have to get rid of 225 parts million of carbon dioxide as well as the methane.

Jeremy Grantham (00:42:31):

If you want to think about the carbon dioxide, that is 2 trillion tons or more, that is the absolute minimum. 2 trillion tons absolutely has to be taken out of the atmosphere over the next couple of hundred years and the Grantham Foundation, that’s all we do with our private investments, our venture capital. We have a team of half a dozen and all we do is focus on carbon dioxide extraction, biologically and every other method that we can get at, but that needs a huge amount of energy. However you do it, you’re going to need a lot of energy.

Jeremy Grantham (00:43:07):

One of our Get Out Of Jail Free cards would be very handy indeed. What are the probabilities? I think there’s probably 50/50 that fusion in the next few decades will come out with a viable engineering system, engineering and physics. The thing that I have doubt about is the cost. They’re going to be fairly costly plans, but 50/50 will have the technology and maybe it will be cheap and maybe it will not be cheap enough. Geothermal looks incredibly promising because the fracking industry has gone through the most amazing set of experiments, tens of thousands of wells, pushing, prodding, experimenting, shocking the rock using extra special mixtures of liquids to pump down and lateral drilling.

Jeremy Grantham (00:43:57):

It’s really been a revolution of engineering talent and if you could take all of that, which we can and apply it to geothermal and then start the same process with geothermal it would be almost surprising if we couldn’t, at least in some parts of the world have a really economically viable source of energy. The heat from the center of the planet here is more or less infinite, so that would do it.

Jeremy Grantham (00:44:22):

The third one would be a brilliant breakthrough in storage. We’ve come down to 10 cents on the dollar in the last 15 years. If we could come down, once again over the next 20 or 30 years to 10 cents on the dollar or even 20 would probably do it. We wouldn’t need a fusion or geothermal any one of those three will give us a chance of success. The problem is how much of the planet spirals out of control because of food problems, energy problems, creating fail states of the kind that we begin to see in Africa.

Jeremy Grantham (00:44:55):

If the temperature alone continues to rise, the whole Indian subcontinent, that becomes very questionable as to whether you could do regular farming. It has a wonderful share of the world’s arable land. If you see one of these maps, which is green for arable, you’ll see that India is one of the few places where practically the entire sub subcontinent is green. The problem is once you get over 35 degrees centigrade, which is about 95 Fahrenheit and you get humidity with it and you can’t stay out more than a few hours and they recently had 45 degrees centigrade for three weeks, as you probably read, the hottest they have ever had.

6. The Nightmare Scenario For Central Banks – Darlo Perkins

Officials feel utterly embarrassed about their “transitory” call in 2021, and you should never ignore the human element in policymaking. But the new bias goes deeper than that. It is also important to remember that the reason we have independent central banks is to ensure that the 1970s cannot happen again. So, we are talking about a risk that undermines the central bankers’ entire raison d’être, an existential threat. In fact, “price stability” is a prerequisite for everything else they do. It is the foundation of monetary policy. When investors ask about the pain central banks are prepared to tolerate, they are thinking about the wrong trade-off. The authorities are prepared to suffer a recession now because they fear a much worse recession in the future if price stability is lost. The trade-off, as officials see it, is intertemporal.

A recent report from the BIS outlines the nightmare scenario for central banks… The BIS analysis is largely statistical. It argues that there are two basic inflation regimes – “low” and “high”, each of which has its own self-reinforcing properties, although economies occasionally transition from one to the other. In the low-inflation regime, “relative” or sector-specific price changes are the dominant driver of the CPI. These tend to have a transitory effect, as they die out quickly. This is not a regime in which wage- or price-setters need to pay a great deal of attention to the overall inflation rate. Aggregate price pressures are subdued, and everyone takes this for granted. In the “high-inflation regime”, on the other hand, broader CPI developments start to have a much more discernible impact, with inflation itself becoming the focal point for private-sector decisions. This shift in emphasis leads, in turn, to behavioural changes that will cause inflation to become entrenched. In the high-inflation regime, even relative price shifts – such as spikes in energy prices – have persistent effects. And you know transitioning from a low inflation regime to a high inflation regime is under way based on the behaviour of prices within the CPI. Once they become more correlated, as they have over the past 12 months, there is a good chance – according to the BIS – that the economy is transitioning. 

7. Ben Clymer – Rolex: Timeless Excellence – Patrick O’Shaughnessy and Ben Clymer 

[00:14:33] Patrick: Maybe before we go into the history, which is so interesting and really important, we could just do a level set for the audience on Rolex the business and just some basics like how many watches do they produce a year, the revenue that they produce a year, maybe say a little bit about their very unique business structure, which is certainly shocking to me and I think will shock some people too that aren’t familiar with it. Just level set us on the size and type of the Rolex as a business.

[00:14:55] Ben: And I want to be completely clear, and I’m sure Rolex will listen to this, so I want to be clear for them and for the audiences that they don’t communicate anything so this is all speculative. The information that I’ll provide and that I’m sure you read is completely speculative. We have a good idea of what they might produce and what the revenue might be. The assumption is is that Rolex is making just north of around a million watches per year with an average wholesale price of around $7,000. So you can do the math there to kind of give you an idea of size and revenue. And a million watches per year is a lot, but it’s not the biggest by quantity. Apple, of course, would be bigger than that. Arguably, if you included Apple, they would be an even bigger watch brand than Rolex, but different thing obviously. But if you were to combine, for example, the entire Swatch group, which ranges from Swatch to Breguet, including Omega, it would be a larger business than Rolex, in theory. But again, Swatch is a publicly traded company, you can see exactly what their revenue is, whereas Rolex is, as I think you’ve alluded to, Rolex is quite the opposite. Rolex is in fact run by something called the Hans Wilsdorf Foundation, which was founded in 1945 when the founder, Hans Wilsdorf, set it up to basically be effectively, a nonprofit run by a group of families that are still highly involved with the business today that have, I would say, effectively zero public interaction. I’m pretty close with Rolex and I’m pretty close with the watch industry you could say and I have met, I think, one board member, one time. That was not by design. I think I met him at a bar and I was like, “Oh, you’re so and so,” and he said, “Yes.” These people are in fact, the most powerful people in watches and nobody even knows their name. Nobody even knows what they look like. I happen to because this is my job, but most people have no clue who’s really pulling the strings at Rolex. There’s a wonderful CEO named Jean-Frederic Dufour, who used to be the president of Zenith, which is an LVMH brand and he is absolutely the base and brain behind much of Rolex, but there is a board there and like any board, they have a different kind of influence over the brand.

Rolex is effectively a nonprofit, some say one of the largest nonprofits in the world, which I would believe. There are dozens and dozens of rumors that you may have heard, such as they’ve got the largest private art collection next to the Vatican, or they own more real estate. They make more money in real estate than they do in watches. Any of those things could be true. What I can say with the utmost certainty is that they will never reveal any of that to be true, even if it is. They’re not the type of brand, type of company that will ever stand on the rooftop and shout about anything. I mentioned this in the story that I wrote in 2015, whereas most brands, they’re trying to create stories where there aren’t any, a lot of brands will say a watch is in-house and you manufacture it in-house when it’s not. Rolex doesn’t do any of that. In fact, what’s so remarkable and I found this out on my own, doing my own research for that story in 2015, they will make several updates to products at some significant cost to themselves and not change the retail price and not even tell anybody about it and the only reason that I found out was when doing research for that story, I spoke to an independent watchmaker who is in New York City and is one of the best watchmakers in the country, if not the world, and he said, he works on Rolex, as well as other brands. These are the changes that they made to their movements without anybody knowing. By the way, these other brands that are communicating about LIGA, which is a manufacturing technique that allows you to have frictionless gears, a brand sent out a press release about that. Then, he came to find out that Rolex had been doing that for five years. It was in half their watches already. That’s what’s so wonderful about Rolex is they just are so remarkably Swiss. They are so conservative and thoughtful in the way that they communicate. When I wrote that story in 2015, I was one of the first journalists who ever be invited inside Rolex’s manufacturing headquarters in Bienne, Switzerland, which is what movements are made. They just are not out there to talk about themselves really ever. It’s incredibly charming. The luxury world is so much about Instagram and influencers and people touting how prestigious any brand might be and Rolex is just quietly the most prestigious…

[00:19:39] Patrick: Maybe you can give us the, I don’t really care how long it is, as long as you want to make it because it’s so damn interesting, the history of Rolex, the brand and the company, its founding and its key timeline milestones.

[00:19:49] Ben: Rolex is younger than most other brands. It’s younger than Omega. It’s younger than Vacheron by 150 years. It’s younger than Patek. In the Swiss watch world, I wouldn’t call it a baby by any means, but not one of these grandfathers. I mean, Vacheron was founded in 1755. That’s older than the United States of America. Rolex was founded by a guy named Hans Wilsdorf, who’s Austrian, but he was a total anglophile. He really just was obsessed with the United Kingdom in the early part of the 1900s. He goes into the UK and starts a company called Wilsdorf & Davis in 1905. Back then, you have to remember that, forget digital watch making. Wrist watches were not a thing. The wrist watch was really a product of World War I, which was guys and trenches, trench watches, were strapping pocket watches to the wrist so that they didn’t have to pull out of their pocket. It was a little bit more complex, but that’s it at a high level. Wilsdorf, in 1905, decides to focus on wrist watches, which is crazy. I mean, it was a little bit, frankly like Elon Musk focusing on EVs 10, 15 years ago. People just weren’t ready for it. He committed to doing the wrist watch in the early part of the 1900s, 1905, 1908 and in 1908, he creates a company called Rolex. Again, there’s lots of hearsay on why it’s Rolex. I think at the very least it’s safe to say that he chose that word because it’s the same pronunciation in all languages. Some people say it’s the sound it makes. There’s no confirmation on that, but effectively what he does is he’s just the distributor. He’s not making anything from 1905 to about 1908.

In ’08, he buys a movement, which is what powers watch from a company called Aegler, A-E-G-L-E-R, which we’ll get back to later. They’re still around today, buys a movement, puts it in a case made by himself and sends it off to, it’s called an observatory, but effectively what it is, it’s a testing facility, effectively a nonprofit that says, these watches or time telling devices, clock, Marine chronometer or whatever, are accurate within, we’ll say X and Y, effectively saying, these are the most precise time telling devices on earth, typically done for Marine chronometers and if you know anything about this history of longitude, like that is effectively how longitude was discovered. This is just paramount to basically all exploration of the time period. Up until that point, no wrist watches had ever even been submitted to this thing called the QA, which is a British testing facility at that point. In 1908, he does that with an Aegler powered watch. It’s a 44 day test and it is given the QA certificate. Again, nobody had ever done it. Some years later, about 10 years later, he submitted 136 movements back to the QA. I think 24 of them were cased in 34 millimeter gold cases and then another 112 were in what we call boy size, which is really very small. I mean, at this point, it would look like a nickel, but these are effectively the formula one cars of watch movements. There were other watch movements at the time that to you and me and most people, would look exactly the same, but these were high performance calibers and they did it with a special escapement. Escapement is basically how time telling was regulated. These were effectively the formula one cars of watchmaking and they were done in a way that was very, even back then, very Rolex. There was really no indication that these were anything special on a dial, besides it would say QA on them. They’re around. You can buy them today for really less than you might think.

Once he had been given the QA certificates for the first wrist watch ever, he decided really to focus on three tenants of watchmaking, which really were not at all prevalent in that day at all, because it was really about utility. The watch can tell you the time pretty well or it was about luxury. At that point, we’re talking the Cartiers, Patek Philippes, complications, really. History tenants of manufacturing, which remain true to this day, would be precision, accuracy, waterproofness, which didn’t really exist at the time, and then self winding. What I mean by that is ability to not have to wind the watch manually. Precision was done. We’ve covered that. These watches were based on QA. They came up with a new escapement to make them more precise. Waterproofness, I think, goes back to the question you asked about five minutes ago, which is, how did you get something that more people know about that basically can afford or confine? He created something called the oyster case and now almost all Rolexes with the exception of the Cellini line, use an oyster case. That basically just means a waterproof case. Nobody was doing it at the time. Omega had something that was pretty close and actually predates the oyster case, but never really took off in the same way. Instead of using seals, it was almost like a locking system. It didn’t really take off, but effectively there was this woman named Mercedes Gleitz, who was a typist, of all things, basically a secretary in the UK and she had swum the English channel successfully, the first woman to swim the English channel successfully.

Hans Wilsdorf, the founder said, “Hey, wouldn’t it be cool if this woman, A, she’s a woman, B, she’s doing this amazing feat that no one had ever done before. Wouldn’t it be cool if she wore the watch around her neck?” She didn’t wear it on her wrist to be clear. She put her around her neck and she attempted to swim the English channel. She actually didn’t successfully do it. She failed, but nobody really cared because she had already done it before. He took out an ad celebrating the fact that this watch was around this woman’s neck for 10 hours in the English channel and the time keeping was flawless. That solidified Rolex as A, a household name because the oyster case had been validated in the English channel with this early brand ambassador, I guess you would call her. That was a huge deal and I think one of the earliest examples of real marketing by any luxury brand or any brand really at all, and then the final tenant would be self winding, which is, I would equate it to the automatic transmission. When the automatic transmission came around, all of a sudden, driving a car became a hell of a lot easier. It just became wider accepted, et cetera. Prior to, I guess it was around 19, I’m going to say, 30 something that Rolex patented the first self winding movement. To be clear, there was somebody called John Harwood that actually had a different self winding movement first. I think that was in the twenties and his idea was to make a hammer. Some of them would bounce back and forth like this to continue to power the watch. Rolex said, let’s go a different array. Let’s create a rotor, so a weight that would oscillate around inner circle to power the watch.

That worked and Rolex had, actually I remember the date. It was 1933 because it had a 20 year patent on it and Patek Philippe, which was another stall watch of traditional watchmaking, saw this and said, “Oh shit, we need to do that too,” but they couldn’t actually release anything until 20 years later because of the patent. The Patek 2526, which is their first self winding watch that came out in 1953. That’s a different thing all together, but effectively, Hans Wilsdorf said, “I want the watches to be precise,” check with the QA. “I want them to be waterproof,” check with the oyster case, “And I want them to be self winding,” check with the perpetual. If you see oyster perpetual on any Rolex, which you’d see in all Rolexes now, oysters are waterproof. Perpetual is the self winding. From there, Rolex went out to make watches and they were doing things very much in a similar style to everyone else at that time until the early fifties. In the post-war era, post World War II era, they created their first sports watch. By sports watch, the technical term is professional watch by Rolex nomenclature. It’s the Submariner, which is the diver’s watch, which is 1953. It’s the GMT, which is the pilot’s watch, which is 1955. Explorer I, which is an Explorer’s watch or an all day everyday watch, which is 53 as well. Then, you had the Daytona in 1963. Later, you had the Sea-Dweller in 67, which is a beef up version of the Sub. Then, the Explorer II in, I guess, 1970 or so. Those are the watches that I think most people now think of when they think of watch. You see rotating bezel in most cases. You see a black dial in most cases. You see an oyster bracelet, which is a very wonderfully produced bracelet with an oyster lock bracelet. That is really when things change.

To be clear, Rolex was not alone. There were other brands doing it. Some would say earlier, some would say around the same time, but the Blancpain Fifty Fathoms is credited to 1953. The Omega Seamaster 300 and 120 are around the same time as well. They were not alone and you have to remember that even Rolex in the watch industry in that period, it was really a smattering of different suppliers. If you look at, for example, and I wrote about this several times over the past few years, if you look at, say the Rolex Daytona from 1963 and the Heuer Carrera from 1963, it uses the exact same movement and I’m saying the exact same movement, and that’s a Valjoux 72. Same case maker, same dial maker, same hand maker. What is the actual difference? The assembly was done by Rolex and the assembly was done by Heuer, but the product itself was really very similar. If you look at early Seamasters and early Submariners, a lot of similarity there. The difference was of course the oyster case, but that was how watch making was done. If you look at say, example of Patek Philippe 2499, that’s based on a Valjoux movement. You don’t think of that. You think of Patek as Patek. This is the holy grail, but up until really, I mean the 2000s, they were using what you call an Ebauche movement, which is just really movement blank and then, it would be finished by Patek or finished by AP or Vacheron or whoever. Rolexes were really, I would say, finished to a higher quality than most, but I mean, any good Blancpain or any good Omega would do much of what Rolex was doing. It was really not until much, much later in the seventies first when we had the Quartz crisis, which is effectively the creation of Quartz, which is analog time, but with a battery, which is dramatically more precise, I mean, dramatically more precise than mechanical watch making.

What is interesting to think about, and I give full credit to my old colleague, Joe Thompson, who’s the legend in the watch writing world, is the Japanese came in with Quartz, Seiko created it, effectively, came in and there was a war between Swiss mechanical watch making and Quartz analog timekeeping. To be clear, the Swiss lost. The Swiss lost by a country mile. All of a sudden, those guys that were buying a Rolex or Omega or a Heuer, because they were the most precise thing in the world just said, “You know what” why would I do that? I can buy a Quartz watch that is 10 times more accurate,” 10 times, and by the way, you don’t need to have good service. You just swap out the new battery or whatever all the time and that decimated the Swiss watch industry to a point where very, very few brands were producing things at a profit of any kind. Jack Heuer, whose family owned TAG Heuer before it was TAG. It was just Heuer at the time. In his biography, I mean, he talks almost going into bankruptcy. If you talk to Gerry Stern, whose father Philippe Stern and his grandfather have owned Patek for generations. In the late seventies, they had to borrow with their bank.

[00:29:53] Patrick: It’s existential.

[00:29:54] Ben: Yeah, this was real. It wasn’t just the smaller brands. Patek had issues. Heuer had issues. Rolex was really smart in that, through that period of real turmoil when, I would say, their chief competitor Omega decided to make some Quartz watches, decided to make some funky looking things, Rolex stayed the course, and yes, they did make Quartz watches. The Beta 21, which was a Swiss conglomerates answer to Quartz, is the most expensive Quartz watch ever made. I mean like thousands and thousands of dollars, they said, “We’re going to focus on what we do best,” and the focus went away from precision and accuracy and time telling to luxury. That is when you start seeing the gold Rolex on, I hate to say it, but the used car salesman and the gold Rolex became the thing, seventies and eighties, opulence, you understand what the eighties were, of course. It just changed what Rolex was, but by the way, it worked and it allowed them to continue to be relevant when everybody else being Omega, Patek to a degree, Vacheron, these brands really struggled. That is why so many of them ended up in conglomerates. In the eighties and nineties, when watches were, mechanical watches, were really not doing so hot, a lot of folks came in and bundled them all up. Richemont owns a bunch of the great ones, including Vacheron. Swatch owns everything from Swatch to Blancpain, Breguet, Omega. It was a time of great challenge for sure. Rolex, they struggled as well, never to the degree that the others did, but it was not great for them. Then, the nineties started to come around and Rolex had a CEO by the name of Patrick Heiniger. His father was actually also CEO too, to give you an idea of how things work at Rolex. And he said, “I want to take Rolex in-house,” and he was really the first to do, frankly well before Patek or well before anybody else. Rolex was using 27 different suppliers to make, say, Submariner.

After he was done with it, they’re using four and now, those four are completely owned by Rolex. There are four different production facilities, two in Geneva, one in, what I would call, Proper Geneva one and Plan-les-Ouates, which is a little bit outside and then there’s one in Chêne-Bourg, which does dials and there’s one in Bienne, which makes the movements. What’s so amazing is, Rolex, to me, the secret sauce is equal parts case, equal parts movement. The case is, you can reverse engineer if you’re a competitor and say, “Okay, what’s an oyster case? It’s got this. It’s got that. It’s polished there. Seals are done by X, Y, and Z.” Movements are a different thing entirely. And what’s amazing is Rolex Geneva, which is basically dials, cases, bracelets, all that stuff, and Rolex BN, which is up in the mountains in Vallée de Joux, had a handshake deal for 70 years. And I mean, an actual handshake deal that the calibers made by what was then called Aegler, who made the first movement for Hans Wilsdorf, that company was making movements solely for Rolex Geneva based on nothing but a handshake. And I mean that literally. There was nothing in writing up until 2004, which is just insane to think about. I mean, Rolex was certainly a multi-billion dollar a year business before then. And up until 2004, there was no contract in place to say that Aegler couldn’t make movements for Omega or TAG Heuer or whoever. And so in 2004, Rolex said, “You know what? Enough’s enough. Let’s get married here,” and they purchased the company. And so now Rolex BN is basically what Aegler was up in the mountains until 2004. And so Rolex now has four different production facilities. As I wrote that story, I was among the first to be invited inside the movement manufacturing, which is really the source of the IP. That is where the sausage is made, so to speak. Just remarkable. If you haven’t read the story, it’s on Hodinkee called Inside The Manufacturer: Visiting All Four Rolex Locations. It was remarkable. As I started out in that story, this was 10 years ago or seven years ago, I was a lover of watches.

I was a lover of Rolex and I had four Rolexes then than had anything else at that point. None of them were as old as I was. They were all considerably older than me. And it’s funny, I reread the story to prepare for this interview. And now since then, I’ve bought more modern Rolexes than I have vintage. And the world is just a different place. But once you see everything that Rolex does to a watch, and what I mean by that is the fact that they have their own foundry, even the steel, not just the gold and precious metals, even the steel on Rolex is proprietary and it’s made by Rolex. It’s 904L. It’s wild. They make their own gold. It’s called Everose if it Rolex gold. It’s just remarkable. And what I think is even more telling of what Rolex is about is that one of their facilities they actually have, and I mean this literally, more than two Nobel prize-winning scientists on staff working on watches. Think about what that must mean from a material science perspective. The innovation done by Rolex is just above and beyond anything I’ve seen. I’ve been to every watch maker in the world. I’ve been to several car manufacturers doing this. I’ve been all over. I’ve been inside Hermès. There’s just nothing like this. They create machines to test their machines that make watches. They have their own oyster test, which of course provides artificial pressure on a watch to know that it’s waterproof. They have a machine that can open and close a Rolex clasp a thousand times a minute, which is kind of amazing, because you actually have to open. It’s wild. So, you open this. It’s actually kind difficult to do. Imagine doing that a thousand times a minute. They invented a machine to do that. They have a machine in Chêne-Bourg, which is their dial and gem-setting location, to sort through all the stones that they’re given. First of all, Rolex only works with IF, which is internally flawless stones, which is obviously the most expensive, highest end. To ensure that the stones that they’re given, whether it’s diamonds or rubies or anything are real, they created a machine to sort them at scale and ensure that all of them are real. And I said, “Well, are bad stones or fake stones are real problem for you?”

They said, “No, not really. But we just want to ensure that every watch we sell is what we want it to be.” And I was like, “How often do you get a fake diamond or a fake anything?” And the answer was, “One out of 10 million.” To be clear, this machine was created either by them or they paid somebody to make it for them. This is their machine. It’s not like it exists outside Rolex. And this gives you an idea of what they’re about and how they do things. And it is so wonderful and so different than traditional luxury, which frankly, I may say, even as a purveyor of luxury items, is full of shit half the time. I’m into sneakers, but not in the way that I’m into other things. Why would a pair of so special edition sneakers sell for $5,000? Sneakers are made in China by machines. They’re hand- stitched here and there. It’s just designed. It’s artificial scarcity, et cetera. When you see what goes into a, really, any high-end mechanical watch, but in particular Rolex, you really start to understand. The Submariner, we’ll say, is 8,000 bucks. That might be a deal after you see what goes into this thing. And I mentioned in the story, several competing brand presidents had told me before I went on this trip that, “Oh, not a human hand touches a Rolex before it’s made. It’s all done by machine.” Which is effectively the most insulting thing a Swiss person can say, meaning that it’s void of character. It’s void of humanity. It’s like luxury should be about people. It should be about craftsmanship. And they’re saying, “Rolex doesn’t have any of that.” And I was like, “Oh, okay. That’s kind of a bummer.” That may have informed why I didn’t own any modern Rolex at the time. You walk into Rolex HQ in Geneva and you see hundreds of people finishing watches. And they’re not finishing in the same way Patek or Lange would, by hand with little pieces of wood. They’re finishing maybe six or seven Rolexes at a time on a polishing wheel, but they’re still polishing really the way that it should be done.

They’re assembling dials by hand. They’re assembling the bracelet by hand. There’s an incredible amount of hand work that goes into the most basic of Rolex, being like a Submariner or a Datejust. Beyond that, what’s so fun about them is they know exactly how different they are than everyone else. They also know that everyone wants to be like them. So, at at least two of their four facilities you might drive by and say, “Oh, there’s Rolex. It’s five stories high. It’s, I don’t know, a few hundred thousand square feet.” When you go inside, you realize that it’s actually 10 or 11 stories high, but five or six of those stories are below ground. And I just remember thinking, “Why would they do that? What’s the point of that?” And it was in fact to suggest to anybody that drives by that Rolex is smaller than they actually are. And I think if we had any idea of how big the foundation was, it would blow all of us away. I think it’s enormous. I think they’re probably producing more than a million a year, but that’s the generally accepted number. It’s who they are. And if they’re going to do something, they want to do things at the highest level. I’m a golfer and have been lucky enough to meet some of their players. And Adam Scott became a good friend and I asked, “Why don’t you sponsor X, Y, and Z?” or, “Why don’t you go grassroots?” Whatever. And they said, “This is Rolex like my golf. If we’re going to do golf, we only want to be involved with the majors. So, the US Open, the BJ Championship, the Masters, and of course the British Open. And that’s it.” If they’re going to do tennis, it’s going to be Wimbledon and the US Open. They don’t even want to mess with some of the other majors in tennis. It’s just remarkable how committed they are to working with the very best. It’s wild. It really is.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google), Amazon, Apple, Meta Platforms (parent of Facebook), and Netflix. Holdings are subject to change at any time. Holdings are subject to change at any time.

What We’re Reading (Week Ending 24 July 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 24 July 2022:

1. CRISPR, 10 Years On: Learning to Rewrite the Code of Life – Carl Zimmer

In just a decade, CRISPR has become one of the most celebrated inventions in modern biology. It is swiftly changing how medical researchers study diseases: Cancer biologists are using the method to discover hidden vulnerabilities of tumor cells. Doctors are using CRISPR to edit genes that cause hereditary diseases.

“The era of human gene editing isn’t coming,” said David Liu, a biologist at Harvard University. “It’s here.”

But CRISPR’s influence extends far beyond medicine. Evolutionary biologists are using the technology to study Neanderthal brains and to investigate how our ape ancestors lost their tails. Plant biologists have edited seeds to produce crops with new vitamins or with the ability to withstand diseases. Some of them may reach supermarket shelves in the next few years…

…Will the coming wave of CRISPR-altered crops feed the world and help poor farmers or only enrich agribusiness giants that invest in the technology? Will CRISPR-based medicine improve health for vulnerable people across the world, or come with a million-dollar price tag?

The most profound ethical question about CRISPR is how future generations might use the technology to alter human embryos. This notion was simply a thought experiment until 2018, when He Jiankui, a biophysicist in China, edited a gene in human embryos to confer resistance to H.I.V. Three of the modified embryos were implanted in women in the Chinese city of Shenzhen.

In 2019, a court sentenced Dr. He to prison for “illegal medical practices.” MIT Technology Review reported in April that he had recently been released. Little is known about the health of the three children, who are now toddlers.

Scientists don’t know of anyone else who has followed Dr. He’s example — yet. But as CRISPR continues to improve, editing human embryos may eventually become a safe and effective treatment for a variety of diseases.

Will it then become acceptable, or even routine, to repair disease-causing genes in an embryo in the lab? What if parents wanted to insert traits that they found more desirable — like those related to height, eye color or intelligence?

Françoise Baylis, a bioethicist at Dalhousie University in Nova Scotia, worries that the public is still not ready to grapple with such questions…

…In the 1980s, microbiologists discovered puzzling stretches of DNA in bacteria, later called Clustered Regularly Interspaced Short Palindromic Repeats. Further research revealed that bacteria used these CRISPR sequences as weapons against invading viruses.

The bacteria turned these sequences into genetic material, called RNA, that could stick precisely to a short stretch of an invading virus’s genes. These RNA molecules carry proteins with them that act like molecular scissors, slicing the viral genes and halting the infection.

As Dr. Doudna and Dr. Charpentier investigated CRISPR, they realized that the system might allow them to cut a sequence of DNA of their own choosing. All they needed to do was make a matching piece of RNA.

To test this revolutionary idea, they created a batch of identical pieces of DNA. They then crafted another batch of RNA molecules, programming all of them to home in on the same spot on the DNA. Finally, they mixed the DNA, the RNA and molecular scissors together in test tubes. They discovered that many of the DNA molecules had been cut at precisely the right spot.

For months Dr. Doudna oversaw a series of round-the-clock experiments to see if CRISPR might work not only in a test tube, but also in living cells. She pushed her team hard, suspecting that many other scientists were also on the chase. That hunch soon proved correct.

In January 2013, five teams of scientists published studies in which they successfully used CRISPR in living animal or human cells. Dr. Doudna did not win that race; the first two published papers came from two labs in Cambridge, Mass. — one at the Broad Institute of M.I.T. and Harvard, and the other at Harvard.

2. A Revolution Sweeping Railroads Upends How America Moves Its Stuff – Paul Ziobro

Freight railroads generally have operated the same way for more than a century: They wait for cargo and leave when customers are ready. Now railroads want to run more like commercial airlines, where departure times are set. Factories, farms, mines or mills need to be ready or miss their trips.

Called “precision-scheduled railroading,” or PSR, this new concept is cascading through the industry. Under pressure from Wall Street to improve performance, Norfolk Southern and other large U.S. freight carriers, including Union Pacific Corp. and Kansas City Southern, are trying to revamp their networks to use fewer trains and hold them to tighter schedules. The moves have sparked a stock rally that has added tens of billions of dollars to railroad values in the past six months as investors anticipate lower costs and higher profits.

The new approach was pioneered by the late railroad executive Hunter Harrison, who engineered turnarounds at two major Canadian railroads and Jacksonville, Fla.-based CSX Corp. by radically revamping their logistics.

His template won over Wall Street by boosting profits and stock prices, but it generated chaos on the tracks. The 2017 revamp at CSX caused crippling congestion east of the Mississippi River, jeopardizing operations at plants that made Pringles potato snacks, threatening deliveries of McDonald’s french fries and idling Cargill Inc. soybean-processing plants because of lack of railcars…

…“The board does not want to see any carrier implement so-called PSR the way CSX did,” said Ann Begeman, chairman of the Surface Transportation Board, the federal agency that oversees freight railroads. “It had unacceptable impacts on so many of its shippers and, frankly, other carriers.”

CSX spokesman Bryan Tucker said the company could have done better communicating the changes to customers, but he defended the actions by pointing to its financial results. He said CSX trains are running faster and with less downtime, and the railroad is hauling more cargo with fewer locomotives, railcars and employees.

Norfolk Southern estimates that its own plan will similarly allow its system to operate faster and more efficiently, while cutting about 3,000 employees from its current workforce of about 26,000 and shedding 500 locomotives from its fleet of about 4,100.

Ideally, the end result would be a more fluid railroad network that operates much like a moving conveyor belt, with fewer jams. It would allow shippers and customers to ship finished goods on a just-in-time basis, reducing carrying costs across the board.

Norfolk Southern is starting its overhaul with a process it calls “clean sheeting,” which involves dismantling and reassembling schedules and processes—one yard at a time…

…BNSF Railway Co., which operates alongside Union Pacific in the Western U.S., has resisted the industrywide push to cut capital spending and drastically change service plans. Executive Chairman Matthew Rose, who is scheduled to retire this month, said railroads that cut back on service risk pushback from regulators. Mr. Rose said BNSF, owned by Warren Buffett’s Berkshire Hathaway Inc., is focused on carrying more loads. “More volume leads to more investment,” he said.

Norfolk Southern, Kansas City Southern and Union Pacific all had service issues last year that they said exposed the perils of maintaining the status quo. When, in some cases, they responded by adding cars to handle the extra volume, congestion in some corridors got worse.

As Union Pacific tried to clear gridlock, it experimented with some strategies modeled after Mr. Harrison’s, which it then decided to adopt more broadly.

“We came to the realization that experimenting with pieces of precision-scheduled railroading was less effective on our network than going the whole way,” said Chief Executive Lance Fritz. The catalyst, he said, “was nothing more complex than our growing frustration and our customers’ growing frustration with the service product at that time.”

Norfolk’s Mr. Farrell, a 53-year-old former All American wrestler at Oklahoma State University, previously worked at both Canadian railroads where Mr. Harrison’s plan went into effect—Canadian National Railway Co. and Canadian Pacific Railway Ltd. At Norfolk Southern, he spent more than a year crisscrossing the network as a consultant to identify problem spots, a process he jokingly called the longest-ever episode of “Undercover Boss.”

After he formally joined the company in November, he ramped up clean-sheeting sessions. As of mid-February, the railroad says, trains were running 13% faster and dwelling 20% less in yards compared with last year.

3. Little Ways The World Works – Morgan Housel

If you find something that is true in more than one field, you’ve probably uncovered something particularly important. The more fields it shows up in, the more likely it is to be a fundamental and recurring driver of how the world works…

…Part of the second law of thermodynamics is that you get the most efficiency out of a system when the hottest heat source meets the coldest sink – that’s when an engine will waste the least amount of heat, converting as much energy into power as it can.

And isn’t it the same in business and careers?

A genius entering a crowded and competitive field may find a little success, but put her in a “cold” industry full of idiots and she’ll create a monopoly, destroying competitors. Jeff Bezos famously said “your margin is my opportunity,” which is the same concept. The biggest opportunities happen when a hot talent meets a cold industry. Thermodynamics has proven this since the beginning of the universe – no one should doubt how true and powerful it is…

…Muller’s ratchet (evolution): Dangerous mutations tend to pile up when there’s no genetic recombination, ultimately leading to extinction. It’s is why so few species reproduce asexually. In the absence of variety, bad ideas tend to stick around, which is also exactly what happens in closed societies and large corporations…

…Cope’s Rule (evolutionary biology): Species evolve to get bigger bodies over time, because there are competitive advantages to being big. But big has its own drawbacks, and can often be the cause of extinction. So the same force that pushes you to become big can also cause you to go extinct. It describes the lifecycle not only of species, but most companies and industries.

Emergence (complexity): When two plus two equals ten. A little cool air from the north is no big deal. A little warm breeze from the south is pleasant. But when they mix together over Missouri you get a tornado. The same thing happens in careers, when someone with a few mediocre skills mixed together at the right time becomes multiple times more successful than someone who’s an expert in one thing…

…Tocqueville Paradox (sociology): People’s expectations rise faster than living standards, so a society that becomes exponentially wealthier can see a decline in net happiness and satisfaction. There is virtually nothing people can’t get accustomed to, which also helps explain why there is so much desire for innovation and improvement.

Cromwell’s rule (statistics): Never say something cannot occur, or will definitely occur, unless it is logically true (1+1=1). If something has a one-in-a-billion chance of being true, and you interact with billions of things during your lifetime, you are nearly assured to experience some astounding surprises, and should always leave open the possibility of the unthinkable coming true.

Liebig’s law of the minimum (agriculture): A plant’s growth is limited by the single scarcest nutrient, not total nutrients – if you have everything except nitrogen, a plant goes nowhere. Liebig wrote, “The availability of the most abundant nutrient in the soil is only as good as the availability of the least abundant nutrient in the soil.” Most complex systems are the same, which makes them more fragile than we assume. One bad bank, one stuck container ship, or one broken supply line can ruin an entire system’s trajectory.

4. Munger on Airlines, Cereal Makers, and Bottlers – The Investments Blog

From this 1994 USC speech by Charlie Munger:

“Here’s a model that we’ve had trouble with. Maybe you’ll be able to figure it out better. Many markets get down to two or three big competitors—or five or six. And in some of those markets, nobody makes any money to speak of. But in others, everybody does very well.

Over the years, we’ve tried to figure out why the competition in some markets gets sort of rational from the investor’s point of view so that the shareholders do well, and in other markets, there’s destructive competition that destroys shareholder wealth.

If it’s a pure commodity like airline seats, you can understand why no one makes any money. As we sit here, just think of what airlines have given to the world—safe travel, greater experience, time with your loved ones, you name it. Yet, the net amount of money that’s been made by the shareholders of airlines since Kitty Hawk, is now a negative figure—a substantial negative figure. Competition was so intense that, once it was unleashed by deregulation, it ravaged shareholder wealth in the airline business.

Yet, in other fields—like cereals, for example—almost all the big boys make out. If you’re some kind of a medium grade cereal maker, you might make 15% on your capital. And if you’re really good, you might make 40%. But why are cereals so profitable—despite the fact that it looks to me like they’re competing like crazy with promotions, coupons and everything else? I don’t fully understand it.

Obviously, there’s a brand identity factor in cereals that doesn’t exist in airlines. That must be the main factor that accounts for it.

And maybe the cereal makers by and large have learned to be less crazy about fighting for market share—because if you get even one person who’s hell-bent on gaining market share…. For example, if I were Kellogg and I decided that I had to have 60% of the market, I think I could take most of the profit out of cereals. I’d ruin Kellogg in the process. But I think I could do it.

In some businesses, the participants behave like a demented Kellogg. In other businesses, they don’t. Unfortunately, I do not have a perfect model for predicting how that’s going to happen.

For example, if you look around at bottler markets, you’ll find many markets where bottlers of Pepsi and Coke both make a lot of money and many others where they destroy most of the profitability of the two franchises. That must get down to the peculiarities of individual adjustment to market capitalism. I think you’d have to know the people involved to fully understand what was happening.”

5. The Dark Side of Solar Power – Atalay Atasu, Serasu Duran, and Luk N. Van Wassenhove

Solar’s pandemic-proof performance is due in large part to the Solar Investment Tax Credit, which defrays 26% of solar-related expenses for all residential and commercial customers (just down from 30% during 2006–2019). After 2023, the tax credit will step down to a permanent 10% for commercial installers and will disappear entirely for home buyers. Therefore, sales of solar will probably burn even hotter in the coming months, as buyers race to cash in while they still can.

Tax subsidies are not the only reason for the solar explosion. The conversion efficiency of panels has improved by as much as 0.5% each year for the last 10 years, even as production costs (and thus prices) have sharply declined, thanks to several waves of manufacturing innovation mostly driven by industry-dominant Chinese panel producers. For the end consumer, this amounts to far lower up-front costs per kilowatt of energy generated.

This is all great news, not just for the industry but also for anyone who acknowledges the need to transition from fossil fuels to renewable energy for the sake of our planet’s future. But there’s a massive caveat that very few are talking about.

Economic incentives are rapidly aligning to encourage customers to trade their existing panels for newer, cheaper, more efficient models. In an industry where circularity solutions such as recycling remain woefully inadequate, the sheer volume of discarded panels will soon pose a risk of existentially damaging proportions.

To be sure, this is not the story one gets from official industry and government sources. The International Renewable Energy Agency (IRENA)’s official projections assert that “large amounts of annual waste are anticipated by the early 2030s” and could total 78 million tonnes by the year 2050. That’s a staggering amount, undoubtedly. But with so many years to prepare, it describes a billion-dollar opportunity for recapture of valuable materials rather than a dire threat. The threat is hidden by the fact that IRENA’s predictions are premised upon customers keeping their panels in place for the entirety of their 30-year life cycle. They do not account for the possibility of widespread early replacement.

Our research does. Using real U.S. data, we modeled the incentives affecting consumers’ decisions whether to replace under various scenarios. We surmised that three variables were particularly salient in determining replacement decisions: installation price, compensation rate (i.e., the going rate for solar energy sold to the grid), and module efficiency. If the cost of trading up is low enough, and the efficiency and compensation rate are high enough, we posit that rational consumers will make the switch, regardless of whether their existing panels have lived out a full 30 years…

…If early replacements occur as predicted by our statistical model, they can produce 50 times more waste in just four years than IRENA anticipates. That figure translates to around 315,000 metric tonnes of waste, based on an estimate of 90 tonnes per MW weight-to-power ratio.

Alarming as they are, these stats may not do full justice to the crisis, as our analysis is restricted to residential installations. With commercial and industrial panels added to the picture, the scale of replacements could be much, much larger.

The industry’s current circular capacity is woefully unprepared for the deluge of waste that is likely to come. The financial incentive to invest in recycling has never been very strong in solar. While panels contain small amounts of valuable materials such as silver, they are mostly made of glass, an extremely low-value material. The long life span of solar panels also serves to disincentivize innovation in this area.

As a result, solar’s production boom has left its recycling infrastructure in the dust. To give you some indication, First Solar is the sole U.S. panel manufacturer we know of with an up-and-running recycling initiative, which only applies to the company’s own products at a global capacity of two million panels per year. With the current capacity, it costs an estimated $20–$30 to recycle one panel. Sending that same panel to a landfill would cost a mere $1–$2.

The direct cost of recycling is only part of the end-of-life burden, however. Panels are delicate, bulky pieces of equipment usually installed on rooftops in the residential context. Specialized labor is required to detach and remove them, lest they shatter to smithereens before they make it onto the truck. In addition, some governments may classify solar panels as hazardous waste, due to the small amounts of heavy metals (cadmium, lead, etc.) they contain. This classification carries with it a string of expensive restrictions — hazardous waste can only be transported at designated times and via select routes, etc.

The totality of these unforeseen costs could crush industry competitiveness. If we plot future installations according to a logistic growth curve capped at 700 GW by 2050 (NREL’s estimated ceiling for the U.S. residential market) alongside the early-replacement curve, we see the volume of waste surpassing that of new installations by the year 2031. By 2035, discarded panels would outweigh new units sold by 2.56 times. In turn, this would catapult the LCOE (levelized cost of energy, a measure of the overall cost of an energy-producing asset over its lifetime) to four times the current projection. The economics of solar — so bright-seeming from the vantage point of 2021 — would darken quickly as the industry sinks under the weight of its own trash.

6. Why America Will Lose Semiconductors – Dylan Patel

The US has always been the world leader in semiconductors: design, manufacturing, and the tools to produce them. Semiconductors are the base of all technological innovation in computing and information technology. Without them, companies such as Amazon, Google, Microsoft, Meta, Apple, and Tesla would not exist. The US has slowly been losing its dominance over the semiconductor industry over the last couple of decades. In recent years, the rate of loss has been accelerating. If it is lost, then the foundational building block of modern technology is lost, and the US will cede its overarching technology advantage. In this article we will discuss the major causes of this problem and offer solutions which should be bipartisan in nature.

Before we get into the problem, let’s talk about the current state of the US’s semiconductor dominance. Most of the largest semiconductor equipment, design, and software companies are based in the US or have critical engineering in the US. In the equipment space, Lam Research, Applied Materials, and KLA are based out of the US. ASML, the widely known leader in lithography, does much of their critical engineering for the EUV Source and EUV Collector out of San Diego. These technology assets and teams come from the acquisition of San Diego based Cymer. ASML pays royalties to the EUV-LLC whose membership includes multiple US national labs. Without these tools, it is impossible to manufacture chips.

The critical software needed to be used to design chips is called EDA and it all comes from the US. Cadence, Synopsys, and Mentor Graphics (now owned by Siemens) are located in the US. Without this software, it is impossible to design modern chips.

American companies like Texas Instruments and Intel hold leading market shares in their respective fields while manufacturing their own chips. The 4 largest companies that design chips for external sale and use contract manufacturers are also American. They are Qualcomm, Broadcom, Nvidia, and AMD.

But that dominance is shifting away to countries that pose as geopolitical risks. US share of chip manufacturing is at an all-time low. The US will lose the semiconductor industry unless immediate action is taken. This is a national security crisis.

The US has been the hallmark of innovation through entrepreneurship, education, and making large investments. All three of these tenets are eroding, partially due to the private market’s attitude and partially because the government’s policies incentivize certain behaviors. The shift is occurring in favor of countries that have favorable government policies, regulatory support, focus on STEM higher education, and a general cultural recognition of the importance of semiconductor manufacturing…

…The US private market of venture capital and angel investing is completely off its rockers investing in software platform based “tech” companies. While this type of investing is fine, these same venture capital and angel investors have completely ignored the semiconductor and hardware space. We here at SemiAnalysis have seen it firsthand as we have helped a few firms in the semiconductor industry raise money. It’s extremely difficult to convince venture capitalists to invest in startups, even if they have promising technology and exceptional track records.

The private market has a strong prejudice against hardware startups. Semiconductors in general have higher startup costs, and the market potential is limited in comparison to a platform-based tech company. US based venture and angel investors that require them tend to think in terms of tens or hundreds of billions of dollars addressable markets. They want software platforms that can have a few dozen employees with the potential to scale to billions in revenue. There can only be so many Instagram’s, Uber’s, Shopify’s and Airbnb’s though. Hardware entrepreneurship is needed even if it doesn’t meet the wild dreams that US based venture and angel investors have. A friend of SemiAnalysis, Jay Goldberg has written about this phenomenon on his newsletter in posts titled Hard or Soft, and Hard or Soft with Math…

… Even if the startups and production facilities were in the US, there is now a severe shortage of skilled workers in the field. By 2025, this shortage is projected to be as high as 300,000 workers. Educated and skilled personnel is a cornerstone of innovation, and without them, the job cannot be done.

Most Americans who pursue a higher education do so in a non-STEM field. While not a negative in and of itself, this is a huge concern when viewed in light of the expected growing shortage of skilled workers in the semiconductor industry. Over 5 million people were granted degrees/certificates at postsecondary institutions in the US, yet not even 1/5th were in STEM according to the chart below from Statista.

2/3 of STEM PHD students in the US are foreigners. They were able to get student visas for their education, yet many of them have a very difficult time immigrating after their education despite hoping to do so. China has nearly 5 million people graduating with STEM degrees annually, population size differences make the gap between China and the US impossible to fill with domestic population alone.

The US must make it easier for educated people around the world to immigrate. It was much easier at other points in US history, which was part of the recipe for the US outpacing the rest of the world in innovation. The concept of brain drain is very real, and the best and most qualified in the world must be allowed to move to the US. 

7. Twitter thread on Three Arrows Capital’s bankruptcy – Jack Niewold

Three Arrows Capital was one of the biggest crypto hedge funds, at one point managing over $10 billion in capital— Until the founders dropped off the map. A 1000-page legal document came out today, bringing clarity to the case. I went through it. This is what I found:

To get you up to speed: After making a series of large directional trades (GBTC, LUNA, stETH) and borrowing from 20+ large institutions, Three Arrows Capital (3ac) went bust. Then the founders ran, and the loan defaults have lead to mass contagion in crypto.

As founders Su Zhu and Kyle Davies are nowhere to be seen, legal proceedings move forwards. Today, a court document was leaked, one which asks the Singapore Government (where 3AC is based) to recognize liquidation proceedings and cooperate with liquidators…

…1. CREDITORS
• 3AC owes over $3b
• The biggest creditor is Genesis, with $2.3b loaned
• Default on debts contributed to insolvency of Celsius and Voyager Digital…

…3. Reasonably Sized Yachts/Houses/Crimes
Between Sep 20 and June 22, Zhu bought two Singapore ‘Good Class Bungalows’ and a yacht that has yet to be delivered. It’s likely that borrowed money was used to fund it; the yacht was shown to lenders as proof of 3AC’s creditworthiness.

It looks like there was some really suspicious movement of ETH and stablecoins just before 3AC was widely known as insolvent. At one point, they made a down payment for the yacht while ignoring an outstanding loan payment.

Other potential crimes:
• Lying about extent of losses to lenders
• Lying about leverage and directional market exposure
• Movement of funds
• Not disclosing their liquidation to shareholders/creditors

4. The Business Structure.
Some reporting has recently been done around TPS/Tai Ping Shan LTD, which is a legal entity related to 3AC and owned by Su Zhu and Kyle Davies’ partner, Kelly Chen. It was recently transferred $31m in stablecoins by a 3AC account.

As for Su Zhu and Kyle Davies (well, his wife), they’re actually creditors in the suit against 3AC, claiming that 3AC owes them money.  That’s not part of these documents, but it’s wild enough to include…

…6. What’s left?
Equity and token agreements in 3ACs illiquid investments, some of which have surely been sold off. JPEGs, including ‘Crypto Dickbutt #1462’…

…7. How did this happen? 
Well, it looks like these lenders just didn’t do their homework. Take Blockchain.com as an example:
• 3AC was asked to to ‘keep them informed’ if their leverage went above 1.5x
• Davies signed the below letter confirming over $2.3b in TAM

And when can you pay back the loan, by the way…?

“Yo
uh
hmm”


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentionedwe currently have a vested interest in ASML and Shopify. Holdings are subject to change at any time.

What We’re Reading (Week Ending 17 July 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 17 July 2022:

1. The first CRISPR gene-editing drug is coming—possibly as soon as next year – Sy Mukherjee

Until recently, CRISPR—the gene-editing technology that won scientists Jennifer Doudna and Emmanuelle Charpentier the 2020 Nobel Prize in chemistry—sounded more like science fiction than medicine; lab-created molecular scissors are used to snip out problematic DNA sections in a patient’s cells to cure them of disease. But soon we could see regulators approve the very first treatment using this gene-editing technology in an effort to combat rare inherited blood disorders that affect millions across the globe.

In a $900 million collaboration, rare disease specialist Vertex and CRISPR Therapeutics developed the therapy, dubbed exa-cel (short for exagamglogene autotemcel). It has already amassed promising evidence that it can help patients with beta thalassemia and sickle cell disease (SCD), both of which are genetic blood diseases that are relatively rare in the U.S. but somewhat more common inherited conditions globally…

…The latest exa-cel clinical data, unveiled during the 2022 European Hematology Association Congress in Switzerland, found that all 75 patients with either beta thalassemia or SCD given the gene-editing therapy showed zero or a greatly reduced need for blood transfusions (in the case of beta thalassemia) or incidences of life-threatening blockages (in the case of SCD). All but 2 of the 44 patients with thalassemia hadn’t needed a single blood transfusion in the 1 to 37 months of follow-up after the treatment’s administration, and the remaining 2 had 75% and 89% reduction in how much blood they needed transfused.

Similarly impressive, all 31 patients with a severe and life-threatening form of SCD experienced no vaso-occlusive crises (the life-threatening incidents in which healthy blood is blocked from moving freely) in anywhere from 2 to 32 months of posttreatment follow-up. Those same patients usually experienced, on average, nearly four of these crises per year for the two years before they received exa-cel…

…CRISPR isn’t the only type of gene therapy that’s made waves in just the past few weeks. Earlier in June, a group of advisers to the Food and Drug Administration (FDA) gave unanimous recommendations for a pair of non-CRISPR-based gene therapies from Bluebird Bio. The treatments target genes associated with beta thalassemia and a rare disorder afflicting children called cerebral adrenoleukodystrophy (CALD). The latter is a disease that eats away at white brain matter in children as young as 4, has few treatments, and usually leads to death within 5 to 10 years.

Bluebird’s eli-cel therapy has faced clinical setbacks because of its association with higher risk of a type of cancer, but the independent advisers decided its benefits still outweighed the risks for some patients with few other options. The FDA doesn’t have to follow the recommendations of its advisory panels, but typically does.

2. Stock Market Experiment Suggests Inevitability Of Booms and Busts – Jerry E. Bishop

Vernon L. Smith knows why the stock market crashed. He ought to. He’s seen dozens of “bubbles” — booms followed by sudden crashes — in the past three years.

Almost every time, Mr. Smith says, the bubble occurred because inexperienced traders dominated the market. In fact, traders had to go through at least two booms and crashes before they collectively learned to avoid these bubbles.

Mr. Smith is one of a new breed of economists who test economic theories by setting up laboratory experiments. For the past few years he and his associate at the University of Arizona in Tucson, Gerry L. Suchanek, and Arlington W. Williams at Indiana University in Bloomington have been running experimental stock markets in their labs…

…In these experimental markets a dozen or so volunteers, usually economics students, are given a set number of “shares” of stock, along with some working capital. All the volunteers are connected by terminals to a computer, which is set up to duplicate trading on the stock-market floor. A trading “day” lasts about four minutes during which the traders may have entered two or three dozen bids and offers resulting in anywhere from five to a dozen trades. A typical experiment during an afternoon or evening runs 15 days.

The booms and crashes occurred in a recent series of 60 experiments aimed at testing an aspect of one of the most basic of all stock-market theories — rational expectations. This theory says a stock’s price is determined by investors’ expectations of what dividend the share will pay. If investors are rational in their expectations, they all place the same value on the stock and it will trade at a price reflecting its true dividend value. The price will change only when new information comes along that changes the dividend expectations.

Mr. Smith and his colleagues assumed, however, that even if investors had the same information, their dividend expectations would differ and they would value the stock differently. Price speculation would then be possible. But, they hypothesized, investors would soon realize that speculative profits are uncertain and unsustainable and they would begin changing their dividend expectations until, at some point, they all came to a common and rational expectation. The stock would then trade at its dividend value.

To find out how long this learning process would take, they set up a laboratory market in which all traders began with the same information about dividend prospects. Traders were told a payout would be declared after each trading day. The amount would be determined randomly from four possibilities — zero, eight, 28 or 60 cents. The average daily payout would be 24 cents. Thus, a share’s dividend value on the first trading day in a 15-day experiment was $3.60 (24 cents times 15 days). As the days passed and dividends were paid, the dividend value would drop.

One typical experiment involved nine students. On the first four-minute “day,” trading opened when a student’s offer to sell a share for $1.50 was quickly accepted. A moment later a bid to buy a share for $1.30 was snapped up. Such bargain prices triggered a flurry of rising bids, and a boom quickly developed. By the middle of the fourth trading day the price topped $5.50 even though the stock’s dividend value had dropped to $3.

But at such high prices offers to sell began to outnumber bids to buy. A crash began and by day 11 prices were below the stock’s $1 dividend value. Only on the last two trading days prices settle at or near the dividend value.

Some of the more astute traders were able to post gains of as much as $50 in dividends and trading profits while others ended up with as little as $5, Mr. Smith says. If the stock had consistently traded at or near its dividend value, all nine students could have had a profit of $16.

Such market bubbles occurred repeatedly. “We find that inexperienced traders never trade consistently near fundamental value, and most commonly generate a boom followed by a crash in stock prices,” Mr. Smith says. Moreover, traders who have experienced one crash “continue to bubble and crash, but at reduced volume,” he says. But, he adds, “Groups brought back for a third trading session tend to trade near fundamental dividend value.”

To counter any criticism that the boom and crash reflected students’ naivete, the researchers used Tucson businessmen who had “real world” experience. They generated the biggest bubble of all and, like the students, had to go through two booms and crashes before settling down to trade at a mutually profitable dividend value.

3. Lifestyles – Morgan Housel

Anyone alone at sea for nine months will start to lose their mind, and there’s evidence both Crowhurst and Moitessier were in poor mental states when their decisions were made. Crowhurst’s last diary entries were incoherent ramblings about submitting your soul to the universe; Moitessier wrote about his long conversations with birds and dolphins.

But their outcomes seemed to center on the fact that Crowhurst was addicted to what other people thought of his accomplishments, while Moitessier was disgusted by them. One lived for external benchmarks, the other only cared about internal measures of happiness.

They are the most extreme examples you can imagine. But their stories are important because ordinary people so often struggle to find balance between external and internal measures of success.

I have no idea how to find the perfect balance between internal and external benchmarks. But I know there’s a strong social pull toward external measures – chasing a path someone else set, whether you enjoy it or not. Social media makes it ten times more powerful. But I also know there’s a strong natural desire for internal measures – being independent, following your quirky habits, and doing what you want, when you want, with whom you want. That’s what people actually want.

4. The Biggest Problem With Remote Work – Derek Thompson

But if the work-from-anywhere movement has been successful for veteran employees in defined roles with trusted colleagues, for certain people and for certain objectives,  remote or hybrid work remains a problem to be solved.

First, remote work is worse for new workers. Many inexperienced employees joining a virtual company realize that they haven’t joined much of a company at all. They’ve logged into a virtual room that calls itself a company but is basically a group chat. It’s hard to promote a wholesome company culture in normal times, and harder still to do so one misunderstood group Slack message and problematic fire emoji at a time. “Small talk, passing conversations, even just observing your manager’s pathways through the office may seem trivial, but in the aggregate they’re far more valuable than any form of company handbook,” write Anne Helen Petersen and Charlie Warzel, the authors of the book Out of Office. Many of the perks of flexible work—like owning your own schedule and getting away from office gossip—can “work against younger employees” in companies that don’t have intentional structured mentorship programs, they argued.

Second, remote is worse at building new teams to take on new tasks. In 2020, Microsoft tapped researchers from UC Berkeley to study how the pandemic changed its work culture. Researchers combed through 60,000 employees’ anonymized messages and chats. They found that the number of messages sent within teams grew significantly, as workers tried to keep up with their colleagues. But information sharing between groups plummeted. Remote work made people more likely to hunker down with their preexisting teams and less likely to have serendipitous conversations that could lead to knowledge sharing. Though employees could accomplish the “hard work” of emailing and making PowerPoints from anywhere, the Microsoft-Berkeley study suggested that the most important job of the office is “soft work”—the sort of banter that allows for long-term trust and innovation…

…Third, and relatedly, remote work is worse at generating disruptive new ideas. A paper published in Nature by Melanie Brucks, at Columbia Business School, and Jonathan Levav, at the Stanford Graduate School of Business, analyzed whether virtual teams could brainstorm as creatively as in-person teams. In one study, they recruited about 1,500 engineers to work in pairs and randomly assigned them to brainstorm either face-to-face or over videoconference. After the pairs generated product ideas for an hour, they selected and submitted one to a panel of judges. Engineers who worked virtually generated fewer total ideas and external raters graded their ideas significantly less creative than those of the in-person teams…

…The work-from-anywhere revolution has something of a kick-starter problem: It’s harder for new workers, new groups, and new ideas to get revved up.

So how do we fix this? One school of thought says face-to-face interactions are too precious to be replaced. I disagree. I’m an optimist who believes the corporate world can solve these problems, because I know that other industries already have.

Modern scientific research is a team sport, with groups spanning many universities and countries. Groups working without face-to-face interaction have historically been less innovative, according to a new paper on remote work in science. For decades, teams split among several countries were five times less likely to produce “breakthrough” science that replaced the corpus of research that came before it. But in the past decade, the innovation gap between on-site and remote teams suddenly reversed. Today, the teams divided by the greatest distance are producing the most significant and innovative work.

I asked one of the co-authors of the paper, the Oxford University economist Carl Benedikt Frey, to explain this flip. He said the explosion of remote-work tools such as Zoom and Slack was essential. But the most important factor is that remote scientists have figured out how to be better hybrid workers. After decades of trial and error, they’ve learned to combine their local networks, which are developed through years of in-person encounters, and their virtual networks, to build a kind of global collective brain.

If scientists can make remote work work, companies can do it too. But they might just have to create an entirely new position—a middle manager for the post-pandemic era.

In the middle of the 19th century, the railroads and the telegraph allowed goods and information to move faster than ever. In 1800, traveling from Manhattan to Chicago took, on average, four weeks. In 1857, it took two days. Firms headquartered in major cities could suddenly track prices from Los Angeles to Miami and ship goods across the country at then-record-high speeds.

To conduct this full orchestra of operations, mid-1800s companies had to invent an entirely new system of organizing work. They needed a new layer of decision makers who could steer local production and distribution businesses. A new species of employee was born: the “middle manager.”

“As late as 1840, there were no middle managers in the United States,” Alfred Chandler observed in The Visible Hand, his classic history of the rise of America’s managerial revolution. In the early 1800s, all managers were owners, and all owners were managers; it was unheard of for somebody to direct employees without being a partner in the company. But once ownership and management were unbundled, new kinds of American companies were made possible, such as the department store, the mail-order house, and the national oil and steel behemoths…

…The synchronizer—or, for large companies, a team of synchronizers—would be responsible for solving the new-worker, new-group, and new-idea problems. Synchronizers would help new workers by ensuring that their managers, mentors, and colleagues are with them at the office during an early onboarding period. They would plan in-person time for new teammates to get to know one another as actual people and not just abstracted online personalities. They would coordinate the formation of new groups to tackle new project ideas, the same way that modern teams in science pull together the right researchers from around the world to co-author new papers. They would plan frequent retreats and reunions across the company, even for workers who never have to be together, with the understanding that the best new ideas—whether in science, consulting, or media—often come from the surprising hybridization of disparate expertise.

5. The Trillion-Dollar Vision of Dee Hock – M. Mitchell Waldrop

This is one of Dee Hock’s favorite tricks to play on an audience. “How many of you recognize this?” he asks, holding out his own Visa card.

Every hand in the room goes up.

“Now,” Hock says, “how many of you can tell me who owns it, where it’s headquartered, how it’s governed, or where to buy shares?”

Confused silence. No one has the slightest idea, because no one has ever thought about it.

And that, says Hock, is exactly how it ought to be. “The better an organization is, the less obvious it is,” he says. “In Visa, we tried to create an invisible organization and keep it that way. It’s the results, not the structure or management that should be apparent.” Today the Visa organization that Hock founded is not only performing brilliantly, it is also almost mythic, one of only two examples that experts regularly cite to illustrate how the dynamic principles of chaos theory can be applied to business.

It all started back in the late 1960s, when the credit card industry was on the brink of disaster. The forerunner of the Visa system — the very first credit card — was BankAmericard, which had originated a decade earlier as a statewide service of the San Francisco-based Bank of America. The card got off to a rocky start, then became reasonably profitable — until 1966, when five other California banks jointly issued a competing product they called MasterCharge.

Bank of America promptly responded, franchising BankAmericard nationwide. (In those days, banks were forbidden to have their own out-of-state branches.) Other large banks quickly responded with their own proprietary cards and franchise systems. A credit card orgy ensued: banks mass-mailed preapproved cards to any list they could find. Children were getting cards. Pets were getting cards. Convicted felons were getting cards. Fraud was rampant, and the banks were hemorrhaging red ink.

By 1968, the industry had become so self-destructive that Bank of America called its licensees to a meeting in Columbus, Ohio to find a solution. The meeting promptly dissolved into angry finger-pointing.

Enter Dee Hock, then a 38-year-old vice president at a licensee bank in Seattle. When the meeting was at its most acrimonious, he got up and suggested that the group find a method to study the issues more systematically. The thankful participants immediately formed a committee, named Hock chairman, and went home.

It was the chance Hock had been waiting for. Even then, he was a man who thought Big Thoughts. Born in 1929, the youngest child of a utility lineman in the mountain town of North Ogden, Utah, he was a loner, an iconoclast, a self-educated mountain boy with a deeply ingrained respect for the individual and a hard-won sense of self-worth. And he stubbornly refused to accept orthodox ideas: before he’d started with the Seattle bank he’d already walked away from fast-track jobs at three separate financial companies, each time raging that the hierarchical, rule-following, control-everything organizations were stifling creativity and initiative at the grass roots — and in the process, making the company too rigid to respond to new challenges and opportunities.

He’d been a passionate reader since before he could remember, even though his formal schooling ended after two years at a community college. He read history, economics, politics, science, philosophy, poetry — anything and everything, without paying the slightest attention to disciplinary boundaries.

What he read convinced him that the command-and-control model of organization that had grown up to support the industrial revolution had gotten out of hand. It simply didn’t work. Command-and-control organizations, Hock says, “were not only archaic and increasingly irrelevant. They were becoming a public menace, antithetical to the human spirit and destructive of the biosphere. I was convinced we were on the brink of an epidemic of institutional failure.”

He also had a deep conviction that if he ever got to create an organization, things would be different. He would try to conceive it based on biological concepts and metaphors.

Now he had that chance. In June 1970, after nearly two years of brainstorming, planning, arguing, and consensus building, control of the BankAmericard system passed to a new, independent entity called National BankAmericard, Inc. (later renamed Visa International). And its CEO was one Dee W. Hock.

The new organization was indeed different — a nonstock, for-profit membership corporation with ownership in the form of nontransferable rights of participation. Hock designed the organization according to his philosophy: highly decentralized and highly collaborative. Authority, initiative, decision making, wealth — everything possible is pushed out to the periphery of the organization, to the members. This design resulted from the need to reconcile a fundamental tension. On the one hand, the member financial institutions are fierce competitors: they — not Visa — issue the cards, which means they are constantly going after each other’s customers. On the other hand, the members also have to cooperate with each other: for the system to work, participating merchants must be able to take any Visa card issued by any bank, anywhere.

That means that the banks abide by certain standards on issues such as card layout. Even more important, they participate in a common clearinghouse operation, the system that reconciles all the accounts and makes sure merchants get paid for each purchase, the transactions are cleared between banks, and customers get billed.

To reconcile that tension, Hock and his colleagues employed a combination of Lao Tse, Adam Smith, and Thomas Jefferson. For example, instead of trying to enforce cooperation by restricting what the members can do, the Visa bylaws encourage them to compete and innovate as much as possible. “Members are free to create, price, market, and service their own products under the Visa name,” he says. “At the same time, in a narrow band of activity essential to the success of the whole, they engage in the most intense cooperation.” This harmonious blend of cooperation and competition is what allowed the system to expand worldwide in the face of different currencies, languages, legal codes, customs, cultures, and political philosophies.

No one way of doing business, dictated from headquarters, could possibly have worked. “It was beyond the power of reason to design an organization to deal with such complexity,” says Hock, “and beyond the reach of the imagination to perceive all the conditions it would encounter.” Instead, he says, “the organization had to be based on biological concepts to evolve, in effect, to invent and organize itself.”

Visa has been called “a corporation whose product is coordination.” Hock calls it “an enabling organization.” He also sees it as living proof that a large organization can be effective without being centralized and coercive. “Visa has elements of Jeffersonian democracy, it has elements of the free market, of government franchising — almost every kind of organization you can think about,” he says. “But it’s none of them. Like the body, the brain, and the biosphere, it’s largely self-organizing.”

It also works. Visa grew phenomenally during the 1970s, from a few hundred members to tens of thousands. And it did so more or less smoothly, without dissolving into fiefdoms and turf wars. By the early 1980s, in fact, the Visa system had surpassed MasterCard as the largest in the world. It had begun to fulfill Hock’s vision of a universal currency, transcending national boundaries. And Dee Hock was seen as the system’s essential man.

“Utter nonsense,” Hock says. “It’s the organizational concepts and ideas that were essential. I merely came to symbolize them. Such organizations should be management-proof.”

In May 1984, at 55, Hock put his beliefs to the test. He resigned from Visa and three months later, with his successor in place, dropped completely from sight. Six years later, in an acceptance speech as a laureate of the Business Hall of Fame, Hock put it this way: “Through the years, I have greatly feared and sought to keep at bay the four beasts that inevitably devour their keeper — Ego, Envy, Avarice, and Ambition. In 1984, I severed all connections with business for a life of isolation and anonymity, convinced I was making a great bargain by trading money for time, position for liberty, and ego for contentment — that the beasts were securely caged.”

Visa never missed a beat.

6. America’s freight railroads are incredibly chaotic right now – Rachel Premack

A railroad engineer or conductor typically earns a six-figure salary, retires with a pension and enjoys union benefits. They don’t need a college degree; the monthslong training is provided on the job. It’s the kind of career that ought to be popular — but Doering said trainees and longtimers alike are getting burned out. It used to be a job with eight- or nine-hour shifts and plenty of time at home. Now, Doering says railroading demands too much time away from one’s family and workdays that last up to 19 hours, combining 12-hour shifts with hours of waiting around for transportation or relief crews. 

Union Pacific is struggling to find railroad crews after years of slashing headcounts. The $22 billion railroader had 30,100 employees during the first three months of 2022, according to its latest earnings report. Five years prior, the company had nearly 12,000 more workers. (A representative from Union Pacific declined to provide a comment for this article, as the company is reporting its second-quarter earnings later this month. The rep did share a company blog on the importance of supply chain fluidity and cooperation.)

This employment issue isn’t unique to Union Pacific. America’s railways are in an unusually chaotic state as Class I lines struggle to find employees. That’s led to congestion that analysts say is even worse than 2021, which saw some of the biggest rail traffic in history. Now, a strike of 115,000 rail workers could happen as soon as next week. 

“We’re spending more time at home-away terminals than we are at home,” Doering said. Doering is also the Nevada legislative director for SMART Transportation Division, a labor union of train, airline and other transportation workers. “So the attitudes out here, I think, are warranted. Morale is at an all-time low.” …

…So, while you may not have been keeping up to date with rail congestion, industrial bigwigs and lawmakers alike are furious. The coal industry is slamming rail for the “meltdown” in service capacity and grain shippers said they had to spend $100 million more in shipping costs to get their product moved amid poor rail service. The Port of Los Angeles is taking to the press to demand rail move those gosh darn containers away, saying that railroaders could cause a “nationwide logjam” with the unmoved containers sitting around. Members of the federal government’s Surface Transportation Board recently demanded answers from railroad executives in a May two-day hearing, but tensions seemed to have only worsened since then.

Even more exhausted are the rail workers themselves. Rail unions have been negotiating with their employers since January 2020, with a “dead end” in negotiations reported two years later. Now, President Joe Biden is being charged with appointing a “Presidential Emergency Board” to nail down a new contract. If he doesn’t do so by Monday, railroad crews could legally have their first nationwide strike since 1992. Such a strike, according to the U.S. Chamber of Commerce, would be “disastrous.”…

…Let me tell you the hottest rail trend of the 2010s: precision-scheduled railroading. As The Wall Street Journal’s Paul Ziobro explained in a 2019 story, PSR means that railroads have set times for when they pick up cargo from their customers, not unlike a commercial airline. Before, railroads would wait for the cargo. 

There are endless implications that come from this system, some of which my colleague Mike Baudendistel delved into in this 2020 article. PSR allowed railroads to reduce capital budgets, slash headcount and merge internal operations with glee. But its biggest boon to the railroaders was how much it boosted their cred on Wall Street, creating billions in shareholder value.

“The railroad stocks have greatly outperformed the broader market in the past 15 years, which took place despite the major deterioration of coal volume, the railroads’ historical business,” Baudendistel wrote.

There are serious service issues with PSR, though. When the tactic was first implemented at CSX Transportation, dwell time at some terminals increased by as much as 26 hours, according to another 2019 WSJ piece by Ziobro. Trips that would take a few days stretched out to more than two weeks — a struggle for customers that relied on just-in-time supply chains…

…Rail giants, as you could guess, struggled during the early months of COVID. In April 2020, for example, rail carloads saw their biggest year-over-year drop since 1989 and intermodal loadings saw a decline not experienced since 2009.

Railroads were shedding employees from April until July 2020, when my colleague Joanna Marsh reported that crew headcount had finally begun to increase again. Still, there were 25% fewer crews than in 2019 and 28% fewer than 2018, according to data from the Surface Transportation Board.

The financial status of these firms was in question, which motivated them to furlough workers. “At least one Class I railroad held meetings to decide whether they had enough cash through the summer, if they had enough cash to pay the bills and could they stay in business,” Hatch said. “When they began to lay people off, much to the consternation today of the regulators and whatnot, you need some understanding that they did not know how long this would last.”

Railroaders struggled to re-hire those crews they furloughed. Many of them found work in construction or manufacturing, industries that allow workers to spend evenings and weekends at home, Tranausky said.

Unlike its siblings in trucking or ocean shipping, the railroad industry didn’t have a bonkers 2021 — but it survived. 2021 saw healthier volumes from the year before. They were still below 2019’s levels…

…Some issues are completely out of the railroads’ control. Most kinds of employers across the country are still struggling to find workers. Even finding shuttle drivers to take railroad crews to their terminal has been a struggle, from Doering’s observations. Recently, Union Pacific has put him in a taxi to go from Las Vegas to inland California. “We’re watching the little ticker up there in the cab go up to $400 or $500 for a trip,” Doering said.

Even in the best of times, it’s hard to find someone to sign up to be a railroad crew member. They have a similar lifestyle to, say, airline pilots, who must be away from their families for days at a time, living in hotels and manning massive, potentially dangerous pieces of equipment. Railroad crews are on call even during their home time.

They require months of training and after that need years or decades on the job to become truly masters of the rail. “There’s a learning curve,” Tranausky said. “[New crews are] not as efficient, not as productive as those higher-seniority crews.”

While Tranausky and Hatch said labor is the main driver of today’s congestion, one factor is totally outside the control of railroads. Unlike 2021, many warehouses are packed with inventory. Some insiders told FreightWaves that shippers are essentially using railcars as storage rather than moving the cargo into their own warehouse. That’s causing a shortage of chassis and increasing congestion — particularly in rail yards like Chicago.

7. TIP462: What Is Money? w/ Lyn Alden – Stig Brodersen and Lyn Alden

Stig Brodersen (01:11):

To kick this episode off, perhaps you can tell this story of the ancient Greek democracy in sixth century b.c. that used partial jewelry as a solution to avoid a catastrophic class conflict and how that relates to where we are in the debt cycle today.

Lyn Alden (01:28):

You have something that builds up decade to decade, even generation to generation, two or three generations, and it doesn’t self-correct enough, right? So, there’s basically the structural issues in society where things build up and get worse and worse. Basically, things have a tendency to concentrate, especially the way we structure things. And so, you have a given society where let’s say farmers, they harvest crops. They have a big harvest every year, but of course, they have to pay for things throughout the year. So, they might, for example, use debt with the promise to pay them back once their harvest comes in. That might work for 10 years in a row, but on the 11th year, they have a crop failure and suddenly, they find themselves in massive debt that they can’t pay.

Lyn Alden (02:13):

And back then, you could become a debt slave. There are all sorts of ways to deal with that in society. Problem is that over time, you have things build up where wealth consolidates and then it also feeds on itself. So, once you’re wealthy, you’re able to influence politics more, right? You have the ear of the king. Or if it’s a republic, you might have more voting power. Back then especially, only rich people could really vote anyway in societies that were republics. So, you can further make the rules in your favor and you get this tendency to consolidate one way or another. Societies had to deal with that in different ways and we have records going back to ancient Sumeria, Babylon, and Greece.

Lyn Alden (02:56):

And the one I used in this piece was Plutarch wrote about the ancient King Solon in Greece and this was an excerpt from Lessons of History by Will and Ariel Durant. I’ll just read it because it’s actually a really good paragraph. And in the Athens of 594 b.c., the poor finding their status worsened with each year, the government in the hands of their masters and the corrupt courts deriving every issue against them, began to talk a violent revolt. The rich, angry at the challenge to their property, prepared to defend themselves by force. Good sense prevailed, moderate element secured the election of Solon, a businessman of aristocratic lineage to the supreme archonship. He devalued the currency thereby easing the burden of all debtors, although he himself was a creditor.

Lyn Alden (03:43):

He reduced all personal debts and ended imprisonment for debt. He canceled arrears for taxes and mortgage interest. He established a graduated income tax that made the rich pay at a rate 12 times that required of the poor. He reorganized the courts on a more popular basis. He arranged that the sons of those who had died in war for Athens should be brought up and educated at the government’s expense. The rich protested that these measures were outright confiscation and then the radicals on the other side complained that he had not redivided the land. But within a generation, almost all had agreed that his reforms had saved Athens from revolution.

Lyn Alden (04:21):

And so, basically, when we talk about this multi-decade, multi-generational compoundings, usually, what you have is these sharp events at some point where either people revolt, right? Everyone’s a debt slave now. So, they say, “Wait a second. We outnumber these guys 100 to 1. Let’s just go burn their house down.” So, there’s that. Or they through politics basically say, “Okay, this is not sustainable. The courts are corrupt. We have so entrenched cronyism and the policy is not good. Let’s sharply reverse some of this without going too far.” And so, this was an example where they managed to moderate it. Most examples are not that successful.

Lyn Alden (05:00):

And so, this shows over time that when you have massive debts and wealth concentration built up in a society, there’s usually some release valve that in various ways, it’s painful for various groups. And then depending on how it goes, it could be extraordinarily painful for everyone if you have a collapse or a revolution of some sort…

…Lyn Alden (11:47):

The best money isn’t always the absolute hardest. There’s other attributes like the ease of transaction, the divisibility, the speed with which you could move it around. And that’s why I would argue for example that for the past 150 years, paper currencies have really outpaced gold, because even though gold’s harder, in practical terms, it has trouble keeping up. So, for thousands of years, commerce and money moved at about the same speed, which is the speed of humans, right? So, we go around on horses and chips and on foot and we transact with each other with gold, silver, copper pieces, or even our ledgers. Even if we started keeping ledgers, those physical ledgers could still only move at the speed of humans.

Lyn Alden (12:29):

We had to really bring them somewhere if you want to give them to another city. But with the introduction of telecommunications equipment in the 1800s, first with the telegraph and then the telephone, we lay these undersea cables under the Atlantic, starting in the 1800s. And so, by the time you got to late 1800s, institutions around the world could talk to each other almost instantly. And so, you could update ledgers and perform certain types of transactions on multi-continent basis far faster than physical goods, including physical money, could settle. And so, gold was no longer able to keep up with the speed of human commerce, and that really further, I think, led to the need for abstraction.

Lyn Alden (13:12):

So, historically, gold was abstracted, because it had limits on its visibility. Whereas now, we also had the even more important thing where we had limits to its speed relative to the speed we wanted transact. So, we had to abstract it more and that eventually opened up the divide between gold and paper currencies. And then eventually, they could be separated. Whereas, in some other world, if there was an element like gold that we could just mentally teleport to each other, it would’ve been much harder to ever introduce paper currencies, because it would’ve been seen right away as an inferior product, but because gold had those limitations and there was an advantage to using paper claims for gold, it was able to lead to that separation.

Lyn Alden (13:53):

So, in many ways, even though dollars are less hard than gold, they have other advantages over the past 150 years or so that has allowed them to at least keep up with gold and that more people use dollars than use gold, even though gold is a better store of value. So, gold as its hardness is better retained its store of value property, but it lost the medium of exchange and unit of account aspects to what is basically better technology. When you look at pure commodity monies, the stock to flow ratio is pretty paramount. There’s actually a really good example in the early American colonies. There was almost an accelerated version of why most monies fail.

Lyn Alden (14:39):

And basically, in pre-American before the revolution, you had these Southern colonies in the 1600s and they started using tobacco as money. They grew tobacco. It was a high value crop. It was reasonably liquid and fungible. And so, they started using tobacco as money. They even made it legal tender in some colonies like Virginia, where you could pay your taxes, you could pay all debts in tobacco. And so, it became money. Problem is that when you put on a monetary premium to something, you basically give everyone an incentive to make more of it. And so, tobacco’s not very resistant to debasement, so anyone could go and plant more tobacco. And so, they started to inflate the value of tobacco away.

Lyn Alden (15:22):

Basically, the prices of things as dominant to tobacco began to increase. And then so the government imposed restrictions. They said certain class of people couldn’t grow tobacco or there’s only so much tobacco that can be grown a year. They’re trying to artificially increase the stock to flow ratios. Then you had another problem where unlike gold, tobacco is not very fungible, right? So, there’s higher quality tobacco, there’s lower quality tobacco. And so, there’s an incentive to pay your debts in this marginal tobacco, the worst tobacco, and then to say, sell the good tobacco overseas or smoke that or whatever you want to do. Use that for better purposes. Give other people the worst ones.

Lyn Alden (16:00):

You basically have Gresham’s law in play, where the weak money dries out the good money. So, everyone’s trading around the bad tobacco. Then they had to say, “Okay, well, we need external auditors to come in and check the quality of tobacco.” So, they put tobacco in warehouses, grade it, and then trade paper claims for that tobacco. So, they basically had to try to increase the fungibility. And then eventually, they abandoned the whole situation, because it was untenable. And so, that’s an accelerated version of why any commodity that’s not resistant to debasement, meaning it can’t maintain a high stock to flow ratio given our level of technology, ultimately fails as money.

Lyn Alden (16:41):

When you look at the broad spectrum, all the different commodities of history, that’s one reason why gold keeps reemerging, because no matter how good our technology is, we’re not really good at making more gold. So, in the 1970s, for example, when the price of gold went up more than tenfold, if you look at the gold production, it barely changes at all, because we just literally don’t have the capability to make a ton of new gold in a short period of time.

Stig Brodersen (17:08):

I’m holding this amazing blog post. It’s another one of Lyn’s great blog post. The title is, “What is Money, Anyway?” I’ll make sure to link to that in show notes and you tell different stories about commodity money. I love all of them. One of them is about African beads, which is amazing itself and really the illustration of what you’re saying there about new technology coming in. I don’t know if I could ask you to share that story with the audience.

Lyn Alden (17:31):

Yeah. So, the African bead story, that’s probably the most tragic one, one of the most tragic examples in that piece. So, basically, for a long period of time, you had different groups in West Africa using beads as money. So, again, that goes back to the idea that money is technology. So, what is rare, liquid, fungible, desirable in an area could be different in other area. So, in that region, they didn’t have glass-making technology. And so, glass beads were very rare and desirable. And then also you had a pastoral society. So, you might have your herd of animals, shepherd. You’re moving around. So, you want to be able to bring your money with you. So, you could literally wear your beads. You could wear your wealth. And so, that was a useful type of money.

Lyn Alden (18:17):

They also used things like fine fabrics and things like that and certain herbs. These were money-like instruments, but beads were a key one for them. And the tragedy was that Europeans who at the time had glass-making technology when they were traveling around, they would identify and say, “These people like to use beads as money and so we can use that to our advantage. It’s cheap for us to make fancy glass beads and then we can start trading it for things of actual value. We can buy their animals. We can buy their resources.” And then sadly, there was a slave trade. So, you could buy slaves with these beads that you could make for almost free. So, they became known as slave beads in some circles. But then of course, the Africans had resistances against this.

Lyn Alden (19:06):

So, if the Europeans flooded everything with these say clear glass beads, they would start to say, “Okay, these clear glass ones are… No, they’re not good money. We want the purple kind.” But then of course, over time, the Europeans would adapt and say, “Okay, well, they want the purple kind now.” So, there was this cat and mouse game where beads were not fully fungible. There were different types and so there were different taste preferences. And then there were different reactions to the perceived scarcity of different types of beads. But eventually, that money became untenable for obvious reasons that there was a technology asymmetry between the cultures and then over time, that technology spread everywhere.

Lyn Alden (19:46):

And so, glass beads are in the long arc of time not good money. And it also that shows that if you don’t have hard money and if your money is not hard and if you’re using something as money that another culture or that some other group within your society can produce more of, then you’re at a disadvantage. So, that’s one of the tragic examples of why money is so critical, especially when different groups interact with each other…

…Stig Brodersen (33:52):

Yeah. And on that note, I would like to talk about the private to public de-leveraging. Usually, that is a process that’s inflationary and then we look at a country like Japan. They mainly stood for decades without almost any price inflation and with very low monetary inflation, but still many macro analysts look at this and they assume that “Well, if this is what’s happening to Japan, it’s going to happen to the US, to the rest of the world perhaps even.” You think that they’re wrong, why is that?

Lyn Alden (34:24):

Two main reasons. One, they own a lot more foreign assets than the collective foreign sector owns of Japanese assets. So, they actually have over trillion dollars, trillions of dollars of claims basically, that they can draw in to pay obligations as needed, right? So, they have this large investment base relative to the size of their GDP. So, that gives them one advantage that many countries now don’t have, especially United States. Number two is that that whole massive private de-leveraging and public leveraging happened primarily during the 2010s decade, which was a very disinflationary decade in terms of commodity market. So, there’s roughly this 10- to 15- to 20-year commodity cycle that happens worldwide where prices are low.

Lyn Alden (35:15):

So, nobody invests in commodities. They don’t build new production. Eventually, that causes a shortage. So, lots of money rushes in for a decade and builds all sorts of new commodity production. And eventually, we oversupply the world with commodities and then that breaks the price. And we start this cycle anew and that takes quite a while. That takes maybe 10 years of building and then 10 years working it out and 10 years of building and 10 years of working it out. Most countries are not big enough to really affect that cycle. United States and China are, but if you’re a country that’s a small percentage of GDP, you don’t really affect that on a global scale.

Lyn Alden (35:51):

And so, Japan happened to do this de-leveraging during a time of substantial commodity disinflation or actually outright deflation. Commodities were literally going down in price while they were doing this. And so, they basically had all the commodity needs available to them at low prices and you weren’t getting this scarcity and undersupply of commodities. That is a much harder thing to do if you’re not at the right part of the commodity cycle or if you’re big enough to affect the commodity cycle. And so, I would argue that Japan represents an almost perfect example of doing this with the right conditions and at the right time that we shouldn’t then just look at that and say, “Well, when all the other countries go through a similar process, it’s going to be just like Japan.”

Lyn Alden (36:41):

Actually, third factor I would say is that unlike most countries in the developed world, Japan has very little political polarization or rising populism intentions in the country. And part of that’s you have a rather homogeneous society and they’ve governed pretty well domestically. They don’t spend a lot of money on military, things like that. And so, a lot of the money just goes back to the people. You have a rather harmonious society. That doesn’t mean it’s perfect. There are obviously disagreements in society, but when you look at just quantitative ways of measuring political polarization, the United States and most European countries are in a much tougher spot there, whereas Japan has a rather harmonious society rather low levels of wealth concentration.

Lyn Alden (37:30):

And so, that gives them a deeper tool chest, I would say, to handle those storms. But of course, their main disadvantages right now are that they are a commodity importer, which now is becoming relevant. And then they also do have now a ton of public debt. And so, they have less ability to raise rates or otherwise protect the value of their currency because they can’t really service that debt otherwise. And so, I think, people over extrapolate the Japanese example by not realizing a lot of the nuances around the timing and the details for how they’re able to do that without it being inflationary.

Stig Brodersen (38:07):

So, let’s talk more about that. It’s very hard to talk about Japan macroeconomic terms without looking that huge debt burden they have. And we started out this interview by talking about forgiveness of debt restructuring. And so, keeping that in mind, the listener might be sitting out there thinking, “Well, we do know that a lot of money is being printed and that’s on the Bank of Japan’s balance sheet. Can’t they just forgive the government debt that they hold and thereby bringing down the debt burden?” I know that’s a question that you have asked yourself. What’s the answer to that?

Lyn Alden (38:44):

The answer is mostly no, but it is a good question, right? So, people think, “Okay, so if the central bank buys a lot of the government bonds and the central bank is more or less the government, why can’t they just forgive the debt that they more or less owe to themselves?” So, if the Bank of Japan ends up owning 75% of Japanese government debt, why can’t they just wipe that off their ledger and then they’ve lowered Japanese government debt by 75% and they start fresh? The problem is that the whole crux of this fiat currency system runs on the premise that a central bank and the government have some degree of independence from each other, right?

Lyn Alden (39:27):

Because if you have a dictator with absolute power over the money, that money’s going to get debased a lot quicker, just the way human nature works. Even if say there’s some philosopher king running a country, as soon as he dies, the next one’s going to be worse and he’s going to miss it, right? So, if you have centralized power, you’re more quickly going to debase the money. Whereas if you have all these checks and balances to make it hard to create more money, so you have to have Congress approve it, then you have to have the central bank finance it, you have to have the president not veto it, so you have to have all these different groups agree to create a lot more money, that really slows down the money creation.

Lyn Alden (40:08):

And that’s why countries with strong institutions and independent institutions generally have a much longer track record of maintaining a reasonably successful fiat currency compared to smaller countries with less histories of institutions and then the institutions get co-opted by some more authoritarian type of ruler. And so, going back to the premise, central banks are at least in theory supposed to be independent. Obviously, in times of war and things like that, that independence get seriously threatened, but it’s still not the president or a head of a country can just go and tell the central bank head to do exactly what he wants. If they do, they’re more like a banana republic. They’re more like that authoritarian model.

Lyn Alden (40:52):

And so, even though they might appoint the central bank chief, that central bank chief now has a term that can potentially persist through multiple administrations and that has checks and balances for how they can be removed, how a new one can be added, right? And so, there’s some degree of separation there. So, a president can’t just do something like cut interest rates three months before the election, make everyone happy, and then go back to having higher rates, right? So, they don’t have that fine control over interest rates, because it’s in someone else’s hands. It’s supposed to be independent.

Lyn Alden (41:24):

And part of maintaining central bank independence is that they can’t be insolvent, that they have to have assets that are equal or higher than their liabilities, because otherwise, they’re reliant on financing from the government and that they’re entirely reliant on that government. And therefore, they no longer have any credible independence. And so, the way central bank balance sheets work is that the currency is their liability. So, physical currency is their liability and bank reserves of commercial banks that are assets for them are liabilities of the central bank. So, those are their primary liabilities. And on the other side of that ledger, their assets are things like primarily their government debt that they own. That’s their key asset.

Lyn Alden (42:10):

And then depending on the different central banks, some of them have mortgage-backed securities. Some of them even have equities, but the core of their assets is that government debt. And so, if they were to erase that government debt and say, “Look, you don’t owe us anymore. Let’s just start fresh,” well, now, that central bank has a multitrillion dollar hole on the asset side of its ledger but still has all those liabilities. And so, they are now technically insolvent organization. They have no independence. They’re entirely reliant on government financing. And so, that whole model of some degree of credible decentralization goes away, credible independence.

Lyn Alden (42:51):

And so, while you might not have any overnight effect from just say, wiping away central bank owned government debt, it’s not like you wake up tomorrow and the currency hyperinflated. But going forward, that central bank is now 100% captured by the government more or less. And so, the long term ability to do that degrades and that’s why most of them have laws in place to prevent that from happening, that the central bank can’t just wipe it away. Now, there are other tricks that they can do, right? So, you could, for example, make the government could issue a special bond that is 100-year bond that doesn’t pay interest.

Lyn Alden (43:30):

Now, you have this bond that’s different from the other government debt that doesn’t pay interest. And so, basically, there are things that they can do like that and there are other tricks they can do to keep the ledger, the asset side, and the liability side technically solvent, but merely deleting the asset side is generally untenable at least the way that we’ve structured the system now for a century or more in many countries.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in  Microsoft and Visa. Holdings are subject to change at any time.

What We’re Reading (Week Ending 10 July 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 10 July 2022:

1. Kenneth Stanley – Greatness Without Goals – Patrick O’Shaughnessy and Kenneth Stanley

[00:08:44] Patrick: In the book and in the presentation you gave last week, there’s a key central example that, like you said, you stumbled upon via some of your own research. I would like to walk through that story. I want to just plant the key idea before we do that with another quote from the book, which is that, “Almost no prerequisite to any major invention was invented with that invention in mind.” You used that term stepping stones, the things that we combine. You gave the example of vacuum tubes and computers. People working on vacuum tubes weren’t thinking about computers, and there’s a million examples like this. So I just want to plant that idea out there. The stepping stones thing not resembling the final invention is the reason why it can’t be so deterministic, and here’s our objective, set up the steps between now and there. Maybe you can start to introduce that concept via the Picbreeder example that I think was the way that you originally alighted upon this idea in your research.

[00:09:31] Ken: It’s neat because, in a way, this is a story of serendipity, which is about serendipity. I mean, basically, this pic breeder just serendipitously led to this insight. Picbreeder was an experiment that I was running with my lab. I was a professor at the time at the University of Central Florida, where we allowed people on the internet to go and breed pictures. I know this is a major digression from what we were just discussing. We were discussing all these important things and we’re talking about breeding pictures. So how do these things connect? Breeding pictures, it is a little esoteric from general societal concerns perspective, but it’s basically about searching through a space in a way. This was an opportunity for us when we were doing artificial intelligence research to crowdsource. Crowdsourcing is really interesting. Let’s say you to take people on the internet because you’ve got access to potentially thousands, millions of people and have them try to do something collectively. Wouldn’t have been possible in the past if you didn’t have access to the internet. What we wanted to do was to crowdsource people, to search through the space of images or pictures and what that meant. So we used breeding. So basically, what it meant was that you could take an image, say a blob or something, and in fact, the site would start you off with random blobs if you started from scratch and you could say, “Look at some blobs and you could pick the one you like the best,” just like you might if you were breeding horses or dogs, “Pick the one you like the best.” You might have different reasons or criteria, but whatever your criteria is it’s fine, and then it would have children.

So it’s a little strange. It sounds strange. The picture has children, but this is inside of a computer. So if you think about it, why not? The picture can have children. The children or the offspring of the picture are like any other children. They look like it. They’re not exact duplicates just like if you have children, they look a little bit like you. They’re not exact duplicates of you or your spouse either. That’s the case here. So then what’s cool is that then you can see that if your picture that you chose has children, then you can look at the children and then you can pick from those children which one you like the best. You can see that this is in effect breeding. So then out of those, you pick your favorite there. It has children, and then you get to choose from those, and then so on and so forth. You’re basically iterating generations of breeding, where it goes depends on what you choose up to you. To tie this back quickly, what does this have to do with anything? If you think about those images, they’re basically a metaphor for discovery in general. If you think about like what you said about vacuum tubes and computers, computers are a discovery, vacuum tubes are a stepping stone on the road to that discovery. So somebody chose to use those vacuum tubes to try to build a computer. When it comes to image breeding, if I see an image that looks like something interesting, and then I choose to breed it further and then I get something else, maybe a picture of a skull, which actually was discovered, then I basically used that stepping stone to get to a discovery. So somehow, there’s a metaphor, an analogous metaphor here.

What’s cool about this site, what made it, I think, compelling to me was that because it’s crowdsourced, what we allowed people to do was to come in and look at what other people had bred. So there’s this big database and it’s being displayed in a natural way, a way that makes it easy for people to see what’s been discovered to surface things that are interesting. So those you can think of as stepping stones. You might see a butterfly or a face or something like that. Then someone who sees that is allowed to instead of starting from scratch, instead of starting from blobs like you would if you were starting from scratch, they can start from your discovery. If you found a butterfly and somebody wants to breed new butterflies, then no problem. They don’t have to start from scratch and get to a butterfly. They can start from your butterfly and then breed from there. It’s called branching. So that means that people are building off of the discoveries of their predecessors or you could think of as standing on the shoulders of their predecessors, which is, again, it’s a really nice analogy, I think, to how human innovation proceeds in general, where someone invents something, discovers something, comes up with an idea, and then someone else that they might not even know later in the future goes back in history and sees that thing and realizes this could be used for that, and it transfers that idea over and it becomes a stepping stone to something else. This has been going on for as long as civilization, basically is civilization. That’s what basically causes civilization to happen. So pic breeders are a microcosm of that, but here’s where the thing that leads to the insight that’s profound and to me was shocking was that after running this site for a couple years, so this is a long time, and letting people just breed and discover things and they discovered all kinds of things, butterflies and cars and planets.

[00:14:01] Patrick: We’ll put a link in and a collection to some of these. It’s really staggering, the things that you see that started with black blobs.

[00:14:07] Ken: Yeah. Yeah. So you’ll get a chance to see it. They found all this stuff after a couple years of watching this. Then what we found was that underneath the hood, we were able to look at how. If you think about just for a second, just think about why Picbreeder is fascinating. At first, it might seem like a toy or something. What is it actually for? People are playing around and breeding images, which have no purpose other than just that they’re images, but actually, what is, I think, profound about having something like that is that it is basically a history of discovery in all of its minute detail. Every little thing that everybody decided to do throughout the history is recorded. We don’t have artifacts like that. We don’t know every step of every invention that’s ever been made. A lot of it just happened inside of someone’s head. So this is not recorded, but Picbreeder is one of the few things, maybe the only thing where every single step of everything is recorded completely. So that meant that after a couple years, we could go back and find out what actually explains how everything was discovered, and I turned out to be, I think, shocking. The shocking revelation was that in almost every single case, more than 99% of cases, if you looked at something interesting, like a car, for example, or a butterfly or a bird or whatever it might be, if you go back in its history and you look at what were the steps that led to that thing, the steps look nothing like it at some point back. Right before you get to it, it might look like it, but if you go back far enough, you will find a stepping stone that looks absolutely nothing like it in 99.9% of cases.

Why is that a revelation? Well, the problem is that if you think about it, what that means is that the only way to discover any of these things was to not be trying to discover them. Now, usually if you say things like that, that sounds like some new age statements, discover things by not trying to discover, and that’s mystical or something. Now, think about this. I’m not talking in the new age perspective. This is an empirical observation. This is actually what happened. The people who discovered these things who are responsible for the stepping stones that led to the discoveries were not actually trying to discover those things because if they had been, then they wouldn’t have chosen the things when they had their selections. They had these blobs they could look at. They could choose one of them. They wouldn’t have chosen the ones they chose if they were trying to get the final product. For example, you have a case where there was an alien face that led to a car. Who would choose an alien face if they want a car? That would not be a good idea, but what happened was the wheels of the car, which was depicted from the side, actually derived from the eyes of the alien face. Again and again and again, you see this phenomenon that in hindsight, you can see what happened, but looking forward, you would never imagine that these connections could be made. This shows, in fact, it’s true in Picbreeder that you can only find things in the long run by not looking for them. You need to take your eyes off the ball in order to be able to accept the stepping stones that ultimately make finding the ball possible, which I think is totally contrary to our culture, to our way of making discovery, the way we think things should be done, which is always objectively driven. So the connection that I need to make, I think, beyond that is to justify why I would extend from that discovery to real life.

[00:17:21] Patrick: If you think about the power of these images, most of them were achieved across what I’ll call a modest amount of generations. We’ll talk about AI and machine learning a little bit later on, which is so interesting because almost all of it has an objective function. It’s almost all objective-based. So that’ll be an interesting part of our conversation, but when you put up the number of generations of breeding to get from a blob to a clear bird, let’s say, it was only 80, 90, 40, 100. It wasn’t that many iterations. Then you showed us a skull, a picture of a skull, and really drove the point home by describing, “Okay. Now, let’s imagine this specific skull or one very close to it is our objective.” Could we get close to it across way, way, way more generations and actually targeting it? Maybe you can describe that experience because I found that to be a powerful nail in the coffin.

[00:18:10] Ken: So basically, we took this and we said, “Let’s try to drive the point home and also just see if we can validate this hypothesis that you can only find things by not looking for them by actually looking for them explicitly.” Just to make it fun, I think this twist makes it fun, let’s look for things that we already saw were discovered. That makes this crazy because it’s like we know that these can be discovered in this space. Like you said, I think it is an important point that these things were not discovered with a lot of compute, so to speak. If I recall, I think it’s 72 generations, might be 74, 72, 74 steps or iterations. That is just ridiculously low. When you think about it in terms of compute, of course, these are humans making these selection steps, but in machine learning, modern machine learning, it’s pretty reasonable to have millions of iterations to get to something meaningful. Here, we’re talking about dozens. In some way, that says these are easy. These are not hard discoveries. In some sense, they’re still impressive because of the fact if I just randomly choose blobs in blob space, in the space of the Picbreeder, you’ll never find anything. 99.99999% of the space is just garbage blobs. So these are still needles in haystack, but what’s weird is that the needles in the haystack are discoverable within a few dozen steps. One conclusion you might draw naively would be that, “Oh, they can’t be that hard to find.” The skull is let’s say 74 steps trivial, basically, from a compute perspective. So let’s set up an experiment and see. So what we can do is we can say, “Let’s get an image matching algorithm,” which are available, which basically tells me if I show this algorithm a blob, I input this blob and I ask it to compare it to the skull, it’ll tell me how far away we are, how close is this image to a skull.

That comparison will help me because when I show a bunch of blobs, I can just have it automatically pick the one that’s closest to the skull. It’s really simple. Then every iteration can be done now by the computer instead of by a human. So we can automate it. Good old fashioned machine learning here. We just automate Picbreeder. No more humans in the loop, and we’ll just automate it to go to the skull. I think to me, this sounds like a worthy adversary. I would be worried this might actually work. It shouldn’t work though our hypothesis is correct because our hypothesis here is that you can only find things by not looking for them. Now, this is explicitly looking for the skull. This is a metaphor for how we do things in our culture. So we say, “This is our goal. This is our OKR. This is what we’re going to achieve this quarter, and now we’re going to work towards it. You’re going to give me a metric. In this case, it’s skull matching. Let’s match the skull picture,” and then you’re going to cut off branches that don’t seem to be maximizing that metric and go by the branches that do seem to be maximizing the metric and just move towards the skull. We’re going to do that now explicitly. We gave it 30,000 steps. This takes about 74 steps, let’s say, for the first discovery by a human. Now, we’re giving an automated algorithm, 30,000 steps, just for fun, just in case, I don’t know, it needs extra time. We’ll give it way extra time, orders of magnitude. What happens? Failure every single time. We ran this dozens of times. It’s every single time failure.

It’s also fun to look at the failures because you can see it’s trying. You see it shadows. It’s like somebody stumbling, almost getting there but not quite. Well, it’s not even close, but it’s like getting the silhouette shadow of what it wants, but it can’t get even close. It’s just fascinating. That’s much more compute. It should be able to eventually overcome it, but the thing is that it highlights the reason that this is happening in if you look at it. Why are all discoveries happening this way in Picbreeder? It’s actually because the world is deceptive, which means that the things that lead to skulls don’t look like skulls. This is the fundamental insight, which is not being recognized across society. It’s that the things that lead to the things you want don’t look like the things that you want. There’s actually a name for this in philosophy. It’s called the like causes like fallacy. I think it’s from Mills. We all seem to assume. It seems to be almost like built in to us biologically that the things that lead to what we want are going to resemble what we want. I don’t know why we all believe this, but it’s not how the world works. If you think about it, that makes total sense. If the world actually worked that way, if the like causes like fallacy was actually true, actually things do resemble where you want to go, we would solve all that problems…

…[00:24:01] Patrick: There’s one piece of this that I love that hasn’t been mentioned yet, which is the role of the individual and their decisions relative to I’ll call this heterogeneous decision making versus homogeneous ruling by committee or something or making choice by committee. Talk about the importance of the individual and their choice in this web of invention and disruption.

[00:24:20] Ken: Yeah. This is a funny thing. It’s true. This is another very popular mythology, I think, in our culture is let’s get together and collaborate, bring all the smart people into the room. It’s not just like, “Let’s get interdisciplinary collaboration. Let’s get the computer scientists sitting there with the economist.” All these things are very exciting to us. I just want to say I’m not saying we shouldn’t have collaboration. That again would be this crazy cranky thing to say. What I do want to get to what you’re asking about is that collaboration itself also is subject to a number of caveats because of the insight about the paradox, the objective paradox, and that means there’s a right way and a wrong way to think about collaboration. It’s quite dangerous. We tend to do it the wrong way. The issue that comes up here is that if you look at Picbreeder, I think something that’s very intriguing about what happens in it is that once somebody sees a stepping stone on the site, so if you recall, like I said, all the discoveries that other people had made are made available for you. So what it means is you are seeing a history of stepping stones when you go to this site. You don’t have to start from scratch. If somebody found a butterfly, you can start from their butterfly.

When you come in and see that butterfly, that is a point of collaboration. It’s implicit collaboration, but it is collaboration because somebody else did work, they found the butterfly, and now you’re building off of that work. So collaboration is happening. However, the moment you choose to continue or what we call branch from the butterfly to breed it further, you are on your own. This is a very unique thing. At first, it sounds like, “Oh, well, what’s the big deal? You’re on your own, okay,” but think about it. We almost never allow people to do that in collaborative situations in our culture. We always bring people together and move towards consensus almost immediately, but in Picbreeder, it’s not like that. Instead, you choose the thing you think is interesting and it was your choice and nobody else was involved in that choice. Now, think about this compared to, for example, I was a professor for a long time. So I think a lot about asking for grants, science grants. That’s like picking an image. It’s like what project do I want to pursue. You come in and you see a butterfly and you want to pursue the butterfly. It’s like you’re sending a grant proposal to the NSF. You think something interesting will happen if you choose this butterfly, but the thing about the NSF is now it’s going to go to a committee. I am not allowed to just go off on my own and work on that butterfly now. There’s going to be a committee that thinks about the decision that I’m making, and I have to justify usually objectively in the sense that I’m going to have to say where it’s going to lead.

What are you going to get by doing this butterfly? That is not how Picbreeder is. You are on your own completely, and not only are you on your own by choosing the butterfly, you’re on your own every single step of the way until you publish the thing you discovered. So there’s no interference, whatsoever, and you’re just on your own. Think about the difference between that and the way we run things where it’s basically you come into a room with all these people, you bring up these ideas, you have this discussion, you try to come to consensus. All the crazy things you would’ve done are basically cut off at the start by this surge towards consensus, which is going to lead to what I would call convergent consensus because we’re trying to move toward convergence very quickly. What you’d understand from Picbreeder is the proliferation of the stepping stones that gives the power to the process. The reason that I can get to cars, there was a discovery of a car which came from an alien face, was because of the discovery of the alien face. No one would ever think that you needed an alien face to get to a car, but the alien face is there not because somebody was thinking about cars, but because there is a general culture inside of Picbreeder of proliferating stepping stones.

This is not generally how we run collaborative systems because we run them by consensus, which is the exact opposite. That’s about pruning out stepping stones. People start generating things and then we start saying, “No, no, no. Committee doesn’t like this. Committee doesn’t like that.” We then converge to the thing, which is basically the consensus basis of current thinking, which tends to be dogmatic and tends to be status quo and everything that we basically want to get away from, and then all these radical stepping stones, which are the interesting things which could lead to places we’re not expecting for the very reason that the things that we’d want to get to don’t look like them so we need the radical stepping stones are the things that we cut out. You can see from this theory or philosophy way of looking things that a lot of the way we run collaborative systems is just totally kneecap at the start, and also should, I think, be rethought.

[00:28:31] Patrick: Can you describe when you put a consensus mechanism into this experiment, the outcome falling to all this? I promise we’re going to get to some of the bigger implications here in a minute, but this simplified example is this so damn powerful for how we all are going to spend our time in our lives. Maybe just describe the outcome when you insert consensus mechanism into how these generations progress.

[00:28:54] Ken: This is super interesting, and it’s funny because it’s just a coincidence that this happened because there was another project that was launched around the time of Picbreeder called the living image project. It had nothing to do with me other than it used basically the same in coding under the hood as Picbreeder. This is nice because it creates a controlled experiment by accident because both Picbreeder and this other thing, the living image project, have this underlying coding that’s the same. So what that means is in principle, they can achieve the same thing. They could find similarly cool stuff in principle, but there’s this one difference, which makes this very interesting as a comparison, which is this living image project did work by consensus. I mean, the reason it did is because I think it’s because there’s this cultural assumption just like riding on top of that. They’re like, “This is a good way to do things. Let’s have a vote.”

So basically what they said is, “Okay. Here’s what we’re going to do. Just like Picbreeder, there’s these blobs, they’re arranged on the screen, you can see all these blobs, and we’re going to pick one of them. That’ll be the parent of the next generation of blobs.” However, the difference from Picbreeder is that the choice will be made by a vote. So over the course of a week, people will come in and it would turn out basically hundreds of people would come in, and they would vote on their favorite blob and then we’ll choose the one that gets the most votes. To a lot of people, this is really intuitive. More opinions are better than one. Let’s use the crowd to decide what to do, but consistently with what I just argued, the result are starkly different and terrible in comparison. I don’t mean to cast any dispersion on the living image project. I think it was a cool idea to try it. It really helps to illustrate. The problem here is that you get a washout effect. Imagine you come in, okay? There’s hundreds of people coming in. Imagine you like butterflies and I like cars. Now, what’s going to happen when we vote and we’re just looking at blobs? The blobs don’t look like butterflies yet and they don’t look like cars, and you want a butterfly and I want a car. What is going to happen? Complete washout is what’s going to happen.

There’s no way you’re going to get enough people on your side. You don’t even know. We don’t even know what each other are doing or have understanding of how you even get these things. So what’s going to happen is you get this mildly aesthetic blobby pattern type of consensus. We get the mildly, most pleasing blob aesthetic, and then that’s going to happen at every iteration because there’s another few hundred people voting at the next iteration and another few hundred, and after thousands and thousands of, I think it was 25,000 votes, you can look at the top ranking, all you have are amorphous rainbowy blobs every single thing. I think it’s just stark and shocking. Even though it’s in this totally obscure genre of stuff like breeding pictures, I think it should give us all heart palpitations because we’re running our culture this way…

...[01:08:29] Patrick: It’s incredible, and I think demands one last question. This idea that you’ve referenced over and over again that no one is telling people how they have to behave in something like pick breeder. There’s a permissionless nature to it. There’s a individuality and individual interpretation of events. With all that in mind, for those whether it’s running a grant organization or running a labs, an AI labs or innovation labs inside of a company or anyone that has resources like Ed did that want to deploy those resources in service of disruption and innovation, either generative or protecting against it or whatever, you’ve already talked about what they do wrong. If you were in-charge of one of those, an allocator of resources to create innovation, how would you do it?

[01:09:14] Ken: I think if you’re in a position like that, you’re a gatekeeper. So you are responsible for the perpetuation or not of this objective culture. It’s especially relevant if you’re purportedly involved in fostering innovation because that’s where this gatekeeper has a huge influence. Yeah. I would recommend doing things differently. You probably exist in their framework where that’s very difficult because you answer to somebody. They don’t understand where you suddenly say, “Well, I’m not assessing things in this normal objective way anymore.” They’re like, “What the heck are you doing? How do we know this is working?” So this takes some courage, I think. The first thing I would say, get the courage because there’s nothing we can do about that. You have to explain to them, “If we’re not going to follow the usual security blanket rooted things, the people in the chain are going to have to be convinced and that’s hard work.” That’s why I think it’s worth having a conversation like this show. That’s why we wrote the book. It’s like we wanted to start people having these conversations. So get the courage to have the conversations and really fight because it’s not going to happen if you don’t. You’re just going to shut down. You’re going to think, “I want to do this, but, eh. On the other hand, my boss wants this. His boss wants that. There’s a funding agency out there or we have investors.” You’re like, “Forget it. It’s too complicated.” Somehow you got to fight this.

Now, in terms of actually practical implementation, what should you do? What I would say is you should be maximizing stepping stones in the pursuit of innovation, not maximizing an objective performance. There’s two things, maximizing stepping stones and maximizing exposure to stepping stones. The thing that makes innovation work is that the people who could run with something are exposed to the thing that they could run with, and that is what’s missing I think from a lot of these organizations is that we have these filters, which are extremely narrow, which decide what comes through, and they end up pruning out things. It’s the conversion consensus problem. Things don’t get exposed to a person who would react dramatically if they were exposed to that thing. What we should do is greatly broaden the filters that go from idea to exposure to the people who could run with the ideas and then also change the criteria for what should be pursued. You have to recognize that if you pursue something that requires investment, so it costs money. So we’re not talking about decisions that can be made lightly. Nobody can say, “Well, everything will pursue because now we’re all going to be open-minded. We’re just going to do everything everybody wants.” That cannot happen. Some things have to not happen, but the way that we decide what happens, I think the criteria should be quite different.

It should not be trying to move to consensus, get a committee to agree with something, get the most vote, something like that. It should be many people within the context of the organization, whatever many means. Many people are exposed to the ideas that are being generated, and that basically only one or two need to trigger the success of that idea or to say, “This is worth investing,” but then you say, “Well, how can that be?” Then every idea would have to be invested because somebody might want to invest in everything. The reason I think it can make sense is if there’s skin in the game for the people who are validating the ideas. If I see something that is so exciting to me that I’m personally willing to pursue it that I didn’t come up with myself, just like the alien face that led to the car in Picbreeder, then I’m actually willing to spend my time on what you did. I’m actually giving something away. I could have had that time. I could have invested in something else. What should make the confirmation of something meaningful and really worth investment is if the person who’s confirming it is giving something away. Maybe they lose their right for some period of time to have their idea even considered or they give away the resources that they were giving for some project that they had. There’s obviously finite resources, but if someone’s willing to do that, that means that this thing means a lot to them, and it only takes one person, magic connection, electric connection to happen, and we have to somehow create those connections. It’s not going to be consensus matter. It’s going to be a niche thing. When there’s something incredible, it’s not going to be tons of people see, it’s going to be one out of a hundred see it, and that has to be honored somehow. We have to find a way to do that.

2. Conversation at Panmure House – Howard Marks and Patrick Schotanus

PS: In fairness to Russell, it was in my introduction to Russell’s question [i.e., not in Russell’s question itself] that I said the economy is mechanical and that’s the definition of mainstream economics.  Russell and I do not necessarily agree on that.  But to continue on mechanical economics as a theory: In your memo On the Couch, you talk about your own early exposure to the efficient-market-type classes.  For the audience, EMH is based on the rational expectations hypothesis; EMH states that markets are rational because any pockets of irrationality are averaged away [i.e., the errors made by the group become smaller than those made by individuals].  In contrast, you also highlight the reality of irrationality that can be observed in markets, something that both Alan Greenspan and Robert Shiller called “irrational exuberance.”  Later, the GFC, or the Global Financial Crisis, painfully hit home that what seems rational for an individual can be dangerously irrational if done collectively.  So my first question is, can we square this circle?  For example, is irrationality just about semantics, or is it something real that not only exists, but because of the collective dynamic, can actually threaten the economic system and may thus not necessarily be averaged away?

HM: To me, Patrick, the answer lies in my view of the efficient market hypothesis.  Again, the efficient market hypothesis says that due to the concerted actions of so many investors, who are intelligent and numerate and computerized and informed and highly motivated and rational and objective and willing to substitute A for B, prices for securities are right, such that they presage a fair risk-adjusted return.  I believe that’s the definition.

But you get into a problem, because when I listed off the qualities that are necessary for a market to be efficient, I snuck in there the economist’s notion of the perfect market and its requirement that the participants be rational and objective. And in investing, they’re not.  That’s really the point.

“Economic man” is supposed to make all these decisions in a way that optimizes wealth.  But she often doesn’t, because she’s not always objective and rational.  She has moods.  And those moods interfere with this arriving at the right price.  So my definition of the efficient market hypothesis is that because of the concerted efforts of all the participants, the price at a given point in time is as close to right as those people can get.  And because it’s as close to right as most of them can get, it’s very hard to outperform the market by finding errors – what theory calls “inefficiencies” and I just think of as “mistakes.” 

Sometimes prices are too high.  Sometimes prices are too low.  But because the price reflects the collective wisdom of all investors on that subject, very few of the individuals can identify those mistakes and profit from them.  And that’s why active investing doesn’t consistently work, in my opinion.  I think my version of the efficient market hypothesis makes it roughly just as hard for active managers to beat the market as does the strong form of the hypothesis, that everything’s always priced right.  But I think mine is more reflective of reality.  I wrote in one of my memos – maybe it was What’s It All About, Alpha? – about a stock that was $400 in 2000 and $2 in 2001.  Now it’s possible – but to me it’s unlikely – that both of those observations were “right.”  Rather, I think they merely reflected the consensus of opinion at the time.

This business – I shouldn’t say “this business”; that sounds derogatory – the idea that inefficiencies will be arbitraged away by the operations of the market ignores one of the key elements that I think describes reality, and that is mass hysteria.  And I think the markets –economies too, but more importantly the markets – are subject to mass hysteria.

I think it was in On the Couch that I said, “in the real world, things fluctuate between pretty good and not so hot.  But in the markets, they go from flawless to hopeless.”  Just think about that one sentence.  If it’s true – and I believe it’s true – that shows you the error, because nothing is flawless and nothing is hopeless.  But markets, I believe, treat things as flawless and hopeless, and there’s the error.

The book I mentioned, Mastering the Market Cycle (I’m going to keep repeating the title in the hope that everybody will buy a copy) . . .  You know, I’m a devotee of cycles.  I’m a student of cycles.  I’ve lived through a half a dozen important cycles in my career.  I’ve thought about them.  I think they dominate what I do.  And I got about two-thirds of the way through writing that book and something dawned on me, a question: Why do we have cycles?

The S&P 500 – I mentioned Jim Lorie – the Center for Research in Security Prices told us almost 60 years ago, that from 1928 to ’62, the S&P 500 had returned an average of 9.2% a year.  Things have been better since then and I think if you go back and look at the whole last 90 years, it’s 10½% a year, the return on the S&P 500.

Here’s a question:  Why doesn’t it just return 10½% every year?  Why sometimes up 20% and sometimes down 20%, and so forth?  In fact – and I included this factoid in one of my memos – it’s almost never up between 8% and 12%.  So if the average return is 10½%, why isn’t the return clustered around 10½%?  Why is it clustered outside the central range?  I think the answer is mass hysteria.

And by the way, the same is true of the economy and mainstream economics, which of course you described as mechanical, and I think that many people would describe as mechanical.  But, certainly, economics is driven by decisions made by people, who are not always rational and objective.  Maybe in theory they’re closer than investors to being rational and objective, but still they’re not always.

But anyway, my explanation for the occurrence of cycles is “excesses and corrections.”  You have a secular trend or a “normal” statistic.  Let’s say it’s the secular trend of the S&P 500.  Sometimes, people get too excited.  They buy the stocks too enthusiastically.  The prices rise.  They rise at more than a 10½% annual rate until they get to a price that is unsustainable.  And then everybody says, “No, I think they’re too high.”  So then they correct back toward the trendline.  But, of course, given the nature of psychology, they correct through the trendline to an excess on the downside.  And then people say, “No, that’s too low,” so then they bring it back toward the trendline and through it to an excess on the high side.

So excesses and corrections: that’s what cycles are about, in my opinion.  Where do the excesses come from?  Psychology.  People get too optimistic, then they get too pessimistic.  They get too greedy, then they get too fearful.  They become too credulous, then they become too skeptical, and so forth.  Oh, and the big one: they become too risk-tolerant, and then they become too risk-averse.

PS: If I can just follow up on that – particularly for our cognitively inclined audience – implied in this you suggest that there might be mental causality, and my next questions are basically also to motivate future research as part of economics revision.  But during your September podcast, in which you revisit the On the Couch memo, you talk about causality and how complex it can be.  And we agree and highlight this in our work.

For example, when Alan Greenspan, in that famous ’96 “irrational exuberance” speech, mentions the complexity of the interactions of asset markets and the economy, and I’m quoting him now: “It chiefly concerns, at least in our view, this dualism of the psychological of the former and the physical of the latter.”  Now, saying this, mental causality is highly controversial and complex in cognitive science, but cognitive science is the area that really studies this.  So, you also specifically refer to Soros’s reflexivity in that context, and as you already indicated just now, but also in your memo, you equate prices almost to psychology.  And finally, we’ve all experienced this dangerous – to the point of existential – tail-wagging-the-dog dynamic surrounding Lehman’s collapse.  So my first question is, if we agree that we will not gain much by identifying yet another behavioral bias, nor by running yet another regression, what would you like to see investigated by cognitive scientists that could potentially lead to more important insights, especially regarding our understanding of the interaction between these two domains of the real and financial economies?

HM: Well, the people at this symposium know much more than I do about how to get to the bottom of these things.  But clearly there’s so much grist for this mill.  Now, exactly how you quantify mood, and so-called animal spirits and irrational exuberance, is beyond me.  I always say, Patrick, and I think I said it in Mastering the Market Cycle, that if I could know just one thing about every security I was thinking about buying, it would be how much optimism is in the price.

When you watch TV and you hear the newsreaders talking about what happened in the stock market today, you get the impression that prices are the result of fundamentals and changes in prices are the result of changes in fundamentals.  And that is vastly inadequate.  (By the way, they always say, “The market went up today because of X” or “The market went down today because of Y.”  I always say, “Where do they go to find that out, because I haven’t found it yet?”  I haven’t found where you go to get an explanation of the market’s behavior, even after the fact.)  But it’s not true that it’s all about fundamentals.  The price of an asset is based on fundamentals and how people view those fundamentals.  And a change in an asset price is based on the change in fundamentals and the change in how people view those fundamentals.  So, facts and attitudes.  Any research that could capture changes in attitudes, I think is important.

Now, what about quantifying these animal spirits?  In one of the more jocular portions of my first book, The Most Important Thing, I include something I called “the poor man’s guide to market assessment.”  I have a list of things in one column, and I have a list of things in the other column, and whichever list is more descriptive of current conditions tells you whether it’s optimism or pessimism that’s governing the market.  There are things like, do deals get sold out or do they languish?  Are hedge fund managers being welcomed on TV or not?  Who does the crowd form around at cocktail parties?  What is the media saying: “We’re going to the moon” or “We’re cratering forever”?  I don’t know how to quantify these things.  But these are among the very important things that I listen to in order to figure out where we stand in the cycle.  And I believe where we are in the cycle plays a very strong role in figuring out where we’ll go next.  (In fact, take the title of my second book, Mastering the Market Cycle.  When I was thinking about writing it, it was called Listening to the Cycle. “Listening” in the sense of taking our signals from where we are in the cycle.  “Listening” also in the sense of obeying.  The publisher thought we’d sell more books if the title implied the book would help you master the market cycle.)  But I, as a practical investor, try to figure out what’s going on around me.

Now let’s go back.  I didn’t do what I should have, because I didn’t answer Russell Napier’s real question: can I name two episodes that showed this kind of thing in action?  I was glad to have the questions in advance, because it allowed me to think about the two episodes I want to propose.

In the spring of 2007, I wrote a memo called The Race to the Bottom.  This was when the subprime mortgage mania was at its apex, I think, and when the logs had been stacked in the fireplace for the conflagration that became the Global Financial Crisis.  It happens that I was driving around England in the fall of ’06 – maybe November or December ’06 –and I was reading the FT (I mean I wasn’t driving and reading; I was being driven so I could read), and there was an article in the FT that said that, historically, the English banks had been willing to lend people three-and-a-half times their salary in a mortgage.  But now, XYZ Bank announced that it was willing to lend four times your salary, and then ABC Bank said, “No, we’ll lend five.”  And that bidding contest – to make loans by lowering credit standards – seemed to me to be a race to the bottom.  And I wrote that markets are an auction place where the opportunity to make a loan, or the opportunity to buy a stock or a bond, goes to the person who’s willing to pay the most for it.  That is to say, get the least for his money, just like in an auction of a painting.  And so, in this case, the bank that was willing to have the lowest credit standards and the weakest loans was likely to win the auction and make the loans: race to the bottom.  And I said this is what happens when there’s too much money in the hands of providers of capital and they’re too eager to put it to work.  Mood!  And, of course, we all know the Global Financial Crisis ensued.

Now fast forward from February ’07 to October ’08: Lehman Brothers goes bankrupt on September 15, 2008, and now, rather than being carefree, the pendulum has swung, and people are terrified.  Rather than seeing risk as their friend, as in, “The more risk you take, the more money you make, because riskier assets have higher returns,” now people say “Risk bearing is just another way to lose money.  Get me out at any price.”

So the pendulum swung, and of course people’s optimism collapsed, the S&P 500 collapsed, and the prices of debt collapsed.  So I wrote a memo right around October the 10th of ’08 – maybe that day was the all-time low for credit, I don’t know exactly – that was called The Limits to Negativism, based on an experience I had. I needed to raise some money to delever a levered fund that we had that was in danger of melting down due to margin calls, and I went out to my clients.  I got more money.  We reduced the fund’s debt from four times its equity to two times.  Now we’re again approaching the point where we can get a margin call.  Now I need to delever it from two times to one time.  I met with a client who said, “No, I don’t want to do it anymore.”  And I said, “You gotta do it.  These are senior loans, and the default rate on senior loans has been infinitesimal over time.  There’s potential for a levered return of 26% a year from what I consider incredibly safe instruments.”

This client – excuse me if I belabor this, but I think it’s interesting – this client said to me, “What if there are defaults?”  And I said, “Well, our historical default rate on high yield bonds – which are junior to these instruments – is 1% a year.  So if you start with 26% and you take off 1% for defaults, you still get 25%.”  So she said, “What if it’s worse than that?”  I said, “The high yield bond universe default rate has been 4% a year, so you’re still getting 22% net.”  She says, “What if it’s worse than that?”  And I said, “The worst five years in our default experience is 7½%, and if that happens, you’re still getting 19%.”  She says, “What if it’s worse than that?”, and I said, “The worst year in history is 13%.  If that recurs every year for the next eight years, you’ll still make 13% a year.”  She says, “What if it’s worse than that?”  And I said, “Do you have any equities?”  She said, “Yes, we have a lot of equities.”  I said, “If we get a default rate on high yield bonds of more than 13% a year every year into the future, what happens to your equities in that environment?”

I describe myself as having run back to my office after that meeting to write that memo, The Limits to Negativism.  What I wrote there was that it’s very important when you’re an investor to be a skeptic and not believe everything you hear.  And most people think being a skeptic consists of dealing with excessive optimism by saying, “That’s too good to be true.”  But when it’s pessimism that’s excessive, being a skeptic means saying, “That’s too bad to be true.”  That particular investor couldn’t imagine any scenario that couldn’t be exceeded on the downside.  So, in other words, for that person, there was no limit to negativism.

And when I conclude that the other people in the market, the people setting the market prices, are excessively negative and excessively risk averse, then I – an inherently conservative person – and my partner, Bruce Karsh, who runs our distressed debt funds – also an inherently conservative person – we go crazy spending money when we conclude there’s excessive pessimism, fear, and risk aversion incorporated in asset prices [meaning they’re lower than they should be]. So it’s not just the mechanical aspects that determine market prices – it’s psychology.  It’s mass hysteria, which comes in waves from time to time, that leads to market cycles that prove excessive.

3. This Diamond Company Wants To Help Carbon Capture Take Off – Maddie Stone

That company is Aether, a lab-grown diamond startup that just raised $18 million in a funding round led by Helena, a “global problem solving organization” that includes both a for-profit investment and nonprofit action arm. Lab-grown diamonds are a hot market, and there’s no shortage of companies claiming that these synthetic gems are more ethical or environmentally friendly than their Earth-mined counterparts — and there are even other companies also focused on making diamonds using carbon dioxide from the air. But Aether’s claims are backed up by some ambitious facts about its operation: not only is it making diamonds in a process powered by clean energy — it’s pulling an additional 20 metric tons of CO2 out of the atmosphere per carat it produces.

While the cost of capturing all that carbon would be high for a company selling, say, cement, it’s one the luxury jewelry brand says it can easily absorb. And the world needs businesses that can pay for so-called direct air capture and still generate a profit if the nascent technology is ever going to make a dent in climate change…

…Aether, which also works with Climeworks, wouldn’t disclose how much it’s paying for direct air capture services. But it says it can transform one ton of captured CO2 into “millions of dollars’ worth of diamonds”. On a per carat basis, those diamonds, an ultra high-purity breed known as Type IIa diamonds that are difficult to find in nature, sell for anywhere from $4,900 to over $10,000. Shearman says this price range is higher than many competitors in the lab grown space and closer to that of mined diamonds because of the additional work that goes into making the fabrication process as clean as possible.

That process starts with Aether purchasing carbon dioxide from Climeworks’ facility in Switzerland and shipping it to the United States, where the diamonds are grown. Aether puts that CO2 through a proprietary process to convert it into high purity methane, or CH4. That methane is then injected directly into the company’s diamond reactors, where a method known as “chemical vapor deposition” is used to grow rough diamond material over the course of several weeks.

The chemical vapor deposition process involves heating gasses to very high temperatures under near-vacuum conditions, and considerable energy is required to do so. Shearman tells The Verge that this process and other manufacturing stages are powered entirely by carbon-free sources like solar and nuclear. Once the diamonds finish growing, they’re shipped to Surat, India, where they’re cut and polished before being sent back to New York City’s diamond district for sale…

…Aether only needs a relatively small amount of carbon dioxide to make the diamonds themselves — think fractions of grams rather than tons. Then, for every carat of diamond it sells, the company says it removes an additional 20 metric tons of carbon from the air, using a mix of direct air capture and other carbon removal methods that involve long-term carbon sequestration. Shearman says the company based this commitment on the fact that the average American has an annual carbon footprint of approximately 16 metric tons, meaning most customers can expect to roughly cancel a year’s worth of personal emissions by purchasing an Aether diamond. “It’s something that has proved to be difficult but doable, and we’re really proud to be able to do that,” he says.

Aether started shipping its first diamonds to customers in the middle of 2021. While Shearman wouldn’t offer specific sales figures, he says that the company produced “hundreds of carats” of diamonds last year, and this year plans to produce thousands. Shearman described the $18 million in Series A funds raised by Helena as “the fuel that’s going to enable us to increase our production footprint this year.”

4. An introduction to Integrated Photonics – Jessica Miley

Integrated Photonics (IP) is the use of light for applications traditionally tackled by electronics. It can be used in a wide range of areas including telecommunications such as 5G networks, biosensors for speeding up medical diagnosis, and in automotive where it is used in LiDAR. IP consists of integrating multiple photonic functions on a Photonic Integrated Circuit (PIC) fabricated using automated wafer-scale generic integration technology over silicon, silica, or Indium Phosphide (InP) substrates. Integrated photonics dramatically improves the performance and reliability of these photonic functions while simultaneously reducing the size, weight, and power consumption.

A good introduction to IP is by understanding its similarities and differences with traditional electronic circuits. Where electronics deal with the control of electrons on a chip, photonics does the same with photons. Photons are the fundamental particles of light.

Conventional integrated circuits (ICs) conduct electricity by allowing the flow of electrons through the circuit. Electrons are negatively charged subatomic particles that interact with both other electrons and other particles. These interactions slow electrons down as they move through circuits, this limits the amount of information that can be transmitted; it also generates heat, which in turn causes energy and information losses.

Photonic integrated circuits (PICs) use photons. Photons move at the speed of light with almost no interference from other photons. This greatly increases the bandwidth (the data transfer rate) and speed of the circuit, without big energy losses making PICs significantly more efficient than their IC counterparts.

Integrated photonic components use “waveguides”, which confine and direct the light in the desired directions (by total internal reflection), much the same way as metallic wires do for electrical signals. A PIC provides functions for information signals on optical wavelengths typically in the visible spectrum or near-infrared 850 nm-1650 nm.

The elements on a PIC are connected via waveguides. The chip elements can be both passive (e.g. couplers, switches, modulators, multiplexers) and active (e,g amplifiers, detectors, and lasers). These components are integrated and fabricated onto a single substrate, which creates the compact and robust photonic device.

A key difference between electronic circuits and PICs is in the primary device that is used for fabrication. In an electronic integrated circuit, the main device is the transistor. But, in PIC, there is no particular main device that dominates in the fabrication. According to its application, the PIC will be designed with a range of fabrication devices. This integration presents opportunities to reduce current bulky, complex, and expensive optical systems in an integrated chip-scale way that has increased stability and robust operation, reduced size and power consumption, and cost-effective large-scale fabrication of even complex circuits.

5. It’s worse than you think – Oliver Burkeman

Here’s a surprisingly useful question to ask yourself next time you’re stumped by a problem, daunted by a challenge, or stuck in a creative rut: “What if this situation is even worse than I thought?”

This question, I admit, appeals to my taste for bloodyminded contrarianism. But its real value is that it expresses what I think of, more and more, as a fundamental truth about human psychology: that we often make ourselves miserable – and hold ourselves back from what we might be capable of achieving – not because we’re too pessimistic, but because, in a sense, we’re not pessimistic enough.

We think of certain kinds of challenges as really hard when they are, in fact, completely impossible. And then we drive ourselves crazy trying to deal with them – thereby distracting and disempowering ourselves from tackling the real really hard things that make life worth living.

A case in point: you feel overwhelmed by an extremely long to-do list. But it’s worse than you think! You think the problem is that you have a huge number of tasks to complete, and insufficient time, and that your only hope is to summon unprecedented reserves of self-discipline, manage your time incredibly well, and somehow power through. Whereas in fact the incoming supply of possible tasks is effectively infinite (and, indeed, your efforts to get through them actually generate more things to do). Getting on top of it all seems like it would be really hard. But it isn’t. It’s impossible…

…Anyway, you get the picture. And you probably get the point, too – which is that when you grasp the sense in which your situation is completely hopeless, instead of just very challenging, you can unclench. You get to exhale. You no longer have to go through life adopting the brace position, because you see that the plane has already crashed. You’re already stranded on the desert island, making what you can of life with your fellow survivors, and with nothing but airplane food to subsist on. And you come to appreciate how much of your distress arose not from the situation itself, but from your efforts to hold yourself back from it, to keep alive the hope that it might not be as it really was.

And then, crucially – because some people tend to mistake this for an argument for nihilism, or a life of mediocrity, when it’s really the opposite – that’s precisely when you can throw yourself at life’s real hard challenges: the impressive accomplishments, bold life choices, and deeply fulfilling relationships. You get to live more intensely, because you’re no longer making your full participation in life dependent on reaching some standard – of productivity, of certainty about the future, of competence, etcetera – that you were never going to reach in the first place.

6. Alex Danco – Tokengated Commerce – Patrick O’Shaughnessy and Alex Danco

[00:05:11] Patrick: Can you give an example that is not at all Shopify related on interoperability and the power of platforms from history that people might be familiar with?

[00:05:20] Alex: Let’s talk about interoperability for a second. People use this to mean a lot of things, but in general, what it means is that imagine that you have two levels of a system where one level of the system needs to interact with the other level, and you have n players on level one, and you have n players on level two, they both need to be able to work with each other in a way that just works fluently without really having to talk to each other very much. I’ll give you an example, which is the shipping container. I know you love talking about shipping containers on the show. I have a factory that makes inputs and you have a factory that takes those inputs and you build something value added out of them. And I need to ship it from me to you, how do we do this? Well, we could work together on figuring out, what is the shape of box that best fits this part? And how do I work with a shipper to make sure that box is going to go on their boat or on their plane effectively?

And how do we negotiate all these things? Or we could just put it all in the same, exactly standardized 40 foot box that goes on boats that know how to fit exactly that box on it, and through a supply chain that knows how to deal with this thing and then out the other side with neither of us ever having to even know about each other or what we’re putting in. This is this idea of a constraint that de constrains. It’s a very, very common motif that you see in interoperability, which is this idea, a free for all is actually no freedom at all. A very, very common lesson here. I can give you all sorts of examples throughout history of saying, if you give people no rules whatsoever, and then everybody tries to work with itself, that’s a mess, nothing ever gets done. However, if you have these really nice constraints or conventions or platforms or standards, many different angles of approaching this problem of interoperability, you can actually unlock something pretty magical, which is this community of n people on one side and this community of n people on the other side can actually create n times n different things without needing n times n different bits of glue stitching all of those things together…

[00:12:05] Patrick: Can you think of an example where that’s violated, where someone’s trying to create a constraint standard but there is too many degrees of freedom and it failed?

[00:12:13] Alex: Sure, that’s almost every standard. Most standards do not succeed. And the reason why they do not succeed is because they just don’t grasp the problem entirely correctly. There’s that XKCD joke, which is like, “There are 12 standards, what we need is a common standard for how everybody represents this. The next day, there are 13 standards.” Standards work is very, very difficult to achieve because so many things have to go right. But if you look across, even in the history of computing, there are several incredible reference standards that are held up. Unix is one of them. The IP internet protocol is probably the greatest one of all of them, it is a very, very, very restricted way in which you can represent the information going through the internet, but what it means is that any webpage, any application, any whatever can submit something that can then get communicated over any kind of communications network. It could be sent over copper wire. It could be sent over ethernet. There are some aficionados that have sent message by carrier pigeon over internet protocol. You can do it. It doesn’t matter. As long as it runs through internet protocol, anything will work on either side. This overall design, I know you talked with Tobi the last time he came on the show, this overall design is something called hour glass architecture or narrow waist architecture. It’s one of the most powerful ideas in building things. This idea of, if you want many, many things to be able to inter-operate with many, many other things, there needs to be a narrow waist that is as constrained as possible between them.

A very, very important idea, and so Shopify really, really understands this, as evidence through how we built Liquid and how every app developer can make apps that works with every theme developer and they don’t talk to each other and you don’t need a piece of custom glue like you would with enterprise software, it just works. The same with anything can go into the internet protocol and it can be communicated over anywhere. Another good example of a narrow waist in computing is the X86 architecture, which Intel made. Anybody can submit instructions to this instruction set, and then it can be executed on any processor that knows how to deal with the X86’s instruction set, but there’s this common waist that it goes through. And I’m including Intel in there just to show that there are a couple of different ways that a narrow waist can come about. It could come about through a bunch of different academics getting together, it could come through with a standard body, but also it could come through when one monopoly says so. In the case with Intel, there’s not any one way to do this, but they’re hard to achieve, and when you do, you have something that’s going to last for a very long time.

[00:14:24] Patrick: It’s sort of obvious with the examples you’ve given, whether it’s the shipping container, or the internet itself, X86, ISO, whatever, that when you get one of these right, it crazy amount can be built on top of it in ways that you could never envision when you set the standard, the creativity that can exist on top of it is fast and unpredictable. That brings us to the topic at hand, which is tokengated commerce, maybe we need to start with why blockchains are potentially interesting narrow waists. But before we do that, tokengated is two parts, token and gated, give us a high level description of why you were doing this, why you were spending your time on it, why Shopify is heavily invested in this notion? This is a new idea, and I want to understand it at a high level.

[00:15:03] Alex: First, let me actually tell you what is tokengated commerce, because at its heart, it’s actually a very simple idea. Tokengated commerce means, here’s a product and I’m going to put a gate in front of it. And if you want to pass the gate, you need to show me a token that says I pass the gate. More generally speaking, what does this look like in practice? Well, what it looks like is, “Hey, I’m a brand. I have all these cool products. I want to make them very exclusive. If you want to unlock the product, you have to connect your wallet, a crypto wallet, sign a transaction showing that you own this wallet and this wallet owns,” let’s say, “the right NFT.” Because I own this NFT, I can unlock this product. Or it could be, because I own this NFT I unlock early access to a drop. I can get to the drop 15 minutes earlier than everybody else. Or because I own the rare version of this NFT, I’m able to get the rare version of the hoodie. Anybody can get the black version, but if I have the rare NFT, I can get the red version and that red version is cool. Or because I own this NFT, I’m able to buy this product and you can only buy one product per number of NFTs you own. These are all various ways of implementing this simple idea, which is, there is context somewhere. And that context is going to influence how my business wants to treat you. What if, as the buyer, I can bring that context with me and sign with it, proving I am me and here’s how I show I have some ownership over this bit of context?

And my storefront can respond to this and say, “Okay, now that I see that you’ve signed for this bit of context, my storefront is going to respond to that context by doing something appropriate.” Maybe it’s unlocking a product. Maybe it’s giving you really access to a drop. Maybe it’s letting you get into a party. It could be anything. It could be, “Here’s something live and in person. Here’s access to 15 minutes of a live stream with me.” It could be anything. It doesn’t just have to be products. This idea of token gating, defined it very, very simply is it’s a kind of behavior that is very, very natural. It’s how do I get into the exclusive thing? How do I show that I have done the challenge of gaining access? How do I get the thing that I want to get that is hard and feels like a reward? These are very, very old ideas in commerce, this idea of commerce is a challenge that the buyer and the merchant do together. And token gating, we are finding, is an incredible foundational piece of UX for the basic idea of the most meaningful kind of commerce is a challenge that you do together.

[00:17:08] Patrick: If you think about the many, many aspects of this, I want to start with the token itself, because if you think of non-fungible token, which have been popular, you own a Bored Ape, you own a Crypto Punk, you own whatever, piece of art, whatever, you could see a world where brands build specific product lines that tailored to you have to own one of these things that are already independently exclusive. So we’re sort of riding the scarcity of Bored Apes, let’s say, as a cool way to create something custom for them. Talk to me what you’ve learned here. Do you think that most merchants will outsource the scarcity function of the tokens themselves, or are you going to empower them to also create their own tokens that trade? It just seems like the world has coalesced around a small number of the most popular projects. Like all the examples you hear are, “If you’re an owner of one of those special things, we’re going to treat you differently, because it’s like you have a black card or something.” So start with the token piece. How do you think it will work?

[00:18:00] Alex: In that question, there were like three or four really good questions. So I want to try to answer them in the right order here. First, if you look at these NFTs, what are these things? What are they any good at representing? What do they all have in common? Let’s break down a couple of common aspects of these NFT projects. One aspect of them is these entities are owned by people, and the way that they own them is through their wallets. What is a wallet? Well, at a very basic level, a wallet is I have my public address and I have my private key and I sign my private key to show that I am who I am. My wallet address is associated with this token on this smart contract, which means I own this ape. First of all, let me just present a very basic observation, which is what are people doing with their wallets? Well, they’re connecting them everywhere. They’re connecting them to discords, to get into the discord. They’re connecting them to adapt. They’re connecting them to any kind of application that is asking them to authenticate in a certain kind of way. Now what we’re seeing is people want to connect these wallets to storefronts to say like, “Hey, I’m not a fungible buyer. I’m a non-fungible buyer because I have this token.” We really like saying NFTs aren’t a kind of product. They’re a kind buyer, a non-fungible buyer. I really want to get this into people’s minds. NFTs fundamentally to us are an input for commerce. They’re a piece of context that the buyer brings with them when they show up to the storefront. It can also be an outcome of commerce. We can do a commercial transaction where one of the outputs of this commerce as I’ve been to new NFT and give it to you. It doesn’t have to be an NFT either. It could be an ERC 20. It could be any number of other things.

These are very, very flexible ideas, but even this very basic thing of, “I have an NFT. I connect it to the storefront, it unlocks a product. Then I go check out. And maybe on the other end of the checkout, you want to sell me another NFT and I may buy that also. Then maybe I’ll use that somewhere else.” All of these are very, very interesting kinds of outputs and inputs to what we call commerce. But as you said before, I want to make sure that I’m answering your original question here, which is over the last year or two, there was this explosion of communities who were all issuing these tokens and everybody was getting in. “Oh, this is cool art.” These are going to have utility. Who are all these communities? And now what we’re seeing is yeah, a lot of these communities didn’t really have much of a game plan, but some of them do. And the ones that do are actually turning out to be formidably impressive media companies, because they have this fascinating way of creating fan bases. One way to look at NFT is this is a new way of creating a fan base, but it’s creating a fan base on the very beginning. You have to have some idea of what you’re doing with your brand. But nonetheless, the specific example of a merchant that we work with closely is Doodles. Doodles is one of the premier NFT brands. They understand fully that they are merchants and they are brands and they are media powerhouses. They understand that that’s the kind of business that they’re building. And they see these tokens as a new fundamental piece of what is it that their fans have that they can bring with them and connect into places in order to bring all that context with them…

[00:28:14] Patrick: I’ve gone way too far into the conversation without asking what the literal mechanic that Shopify is building will let people do and won’t let them do. Is it as simple as saying, “If I’m a merchant, you can sign with whatever and I’m going to go through a menu and pick the tokens that I want to let and tie them to a certain thing and then you handle the rest”? What is literally going to be the thing that you offer?

[00:28:32] Alex: That’s actually a very good way to put it, which is that the number of things people want to do with token gating is very diverse and very hard to predict. We cannot know what all of them are. But you know what? We don’t have to. We’re a platform that is what app developers do. This is how Shopify is built. This is exactly like the problem of saying, “Well, there are many themes in the theme store and there are many apps that want to make mechanics. Do I have to think of every single thing that an app could do so that themes can know about it?” No. We just build our platform in a way where we present the right constraints and the right formats for saying, “Hey merchant, you want to do some token gating. Well, there are a lot of different ways that you might think your token gating wants to do. Some people want to token gate for discounts. Some people want to token gate around mechanics to do a cool sneaker drop. Some people want to token gate so that people can buy variants on a product to correspond to variants of their NFTs.” All of these are perfectly valid ways to do token gating and we’re not going to come up with what they are. What we are doing is we are creating a common platform for app developers to go make whatever kind of token gating rules you want to make in a way where those token gating rules can be presented in any selling surface where the merchant wants to go.

Maybe they want to sell on the online store, and that’s great. Maybe they want to sell at a retail point of sale environment. We have merchants doing this now. They’re doing a popup store and they’re an NFT brand. They’re like, “Oh, I only want to sell this thing in my popup store to people who have this NFT and can sign for it. And I want to do it on retail POS.” No problem. Some people want to buy things on mobile, and we have the shop app, which is our mobile app for shopping, and there’s some merchants who want to set up a little token gated store in the shop app that works really well on mobile. We have a product called GM shop that I’ll tell you about it in a minute that is exactly that. But your general question of what is the product that Shopify lets merchants do? It’s, well, you can do anything because we’re a platform. That’s the hard work of being a platform is coming up with what are exactly the right constraints that anybody can make inputs to it and anybody on the other side can read them and go carry out token gating instructions if we’ve come up with exactly the right constraints in the middle. The slogan I like to say when people say, “What are you doing with your life?” I say, “I’m making Shopify wallet aware.” That’s what I’m doing. Wallet awareness is not a single thing. It is an idea around everybody accepting a certain set of constraints that become deconstraining. They’re constraints that become liberating…

[00:38:58] Patrick: You started to answer a key part, which is if all you wanted was an unlimited amount of people to have a certain access then pure text is great. If you want to limit it somehow obviously then the non fungible nature of the tokens becomes very important. So I get it. And you could certainly see the world normalizing too in your browser, you have a wallet, and you’re constantly like getting shit in your wallet from different people and they represent different things and blah, blah, blah. So now let’s talk about demand, this big topic of what is demand? Where does it come from? How does it tie into this whole story? And why is this new primitive for unlocking demand?

[00:39:32] Alex: Demand is one of my favorite topics because it’s simultaneously such a basic thing that everybody has opinions about. But also it’s one of the hardest things to conjure. You’re not a business until you have demand. A business plan is not demand. Nothing is a substitute for demand. Demand is the thing. Every business owner knows this. What is this mysterious thing, and how do I get it, and once I have it, how do I turn it into more? Before I was at Shopify, before I worked in DC, before we knew each other, long before that, I was in a band. I was in a band called The Fundamentals. We were on a label called Stomp Records out of Montreal, it’s a ska punk label. We never made it big, but we toured around. We had a record deal. We were trying to make it big. This is what we were doing with our lives.

And when you’re in a band, your business model is you lose money recording music, so that you can break even selling concert tickets, so that you can make money selling merch. That is how it works. You are a merchant. What you sell is apparel, basically, to your fans and you give them a reason to buy your stuff. Everything else is more or less a loss leader for your merch business when you’re at that size of band, anyway. I’m sure Taylor Swift makes money at all slices of the pie, but even like the Taylor Swift merch empire is, this is massive, massive, massive business, because there is demand for Taylor Swift merch. How do you make that demand and where does it come from is the question of being a retailer or the question of being a merchant. I can tell you honestly, when you’re a band, demand is something where it exists in two states. If I’m a band and I have these fans that are all out there in the world, they like me in a very sort of abstract way. They listen to my music. They’re thinking about me sometimes. The demand for them to buy my stuff is not really activated. It doesn’t exist in a more tangible form. The proof of this by the way is if you look at musicians merch businesses, let me ask you what percentage of a band’s merch do you think is sold online as opposed to at shows?

[00:41:08] Patrick: 50%.

[00:41:10] Alex: Almost none. So the rule of thumb is that no matter how big you are, your online merch business per year is about the same as two weeks of tour dates.

[00:41:19] Patrick: Oh, wow.

[00:41:19] Alex: Yeah. It is a very, very, very strong ratio. This is more or less universal whether you’re a small band or a big band or whoever you are. This is not to say that people don’t like Taylor Swift, unless they’re in the Taylor Swift concerts. No, they like Taylor the whole time. But you need there to be a precipitating event to cause people to be compelled to buy the merch now. The demand has taken a more meaningful form. It’s almost as if the demand isn’t like a gaseous state and then it becomes more active when certain things happen. And I want to tell you about those things because there are some universal rules to them in how culture works. When you’re a band, you have all these fans and they exist and they know who you are. But then when you come to town, what you do is you play a show. You sell tickets to the show, people buy the ticket, and they enter in this space, and this is very intimate space. And you do a challenge together called dance to the music. On completion of the challenge everybody lines up to go by the merch. This is a universal rule of music. There is a very, very specific orchestrated sequence of events that causes people to buy your stuff. Everybody who has active experience with being a certain kind of culturally cool merchant will recognize their version of this. Demand isn’t enough. It has to be activated demand. It has to be awakened by something. And the thing that awakens demand is a challenge of some sort. I think you were posting about this on Twitter or something. Challenges are the things that make life meaningful. They’re the thing that give us identity. They’re the thing that give us purpose. They’re the thing that makes us feel good about ourselves. Challenge and overcoming the challenge. Demand in absence of challenge is cheap and stupid.

It’s not necessarily stupid, but it’s baseload demand. I have baseload demand for paper towels. That’s fine. I can get them from the corner store. I can get them from Amazon. That’s fine. But the more meaningful kind of demand that actually is something meaningful to my life, that kind of demand is only awakened by a challenge. It might be the challenge of being in a particular store and really, really talking to a merchant and figuring out what I want. It could be the challenge of going to a show. It could be the challenge of being in a cool collab or whatever it is. But ultimately demand has to be activated by something and that thing is challenge. What kind of challenges are the things that people really care about? Well, the basic challenge that we care about is identity and group association. I’m a part of this group. I have these peers. I’m living up to a certain challenge that the peer group does. This is through the basis of all culture. That kind of culture is the basis of a certain kind of retailing called products that people buy to be cool or products that people buy to be a part of a group or products that people buy because they have some sort of meaning to them. The number of different kinds of products like this are quite varied. It’s not just t-shirts that bands sell. It could be memberships to something. It could be getting tattoos. Everybody has this thing that they’re really, really into. But ultimately demand, I want to bring this back to this sort of nebulous concept of demand, is something that people have understood as a part of commerce for thousands of years, but only up until recently that demand was always in person. There’s a challenge that the buyer and the merchants come together to flesh out what context is the buyer bringing with them? Under what circumstances does this demand unlock and activate the challenge? This is something that people naturally do face to face really well.

But online, it’s really hard to do this. It’s hard to show up to an online storefront and bring a vibe with you, do a challenge together, or engage in any of these things. I would say the first mechanic that people online came up with that actually activated this was the drop, the concept of, “Okay, at noon the sneakers are going to drop and you have to get them as fast as possible.” That’s fun. That is a great example of how you sell things. That’s how you get demand to actually convert into purchases is you do a drop or you make an exclusive thing or like you create a challenge and you motivate people to get behind the challenge. I believe it was Modest Proposal was on your podcast a long time ago, talking about eCommerce and this idea of getting all the friction out of commerce. That’s really not it. There’s some kinds of friction that are bad, but there are actually some kinds of friction that are really good. I talked to you about this in the Shopify podcast. This idea of a challenge is required to turn demand into buying. Different cultures do it in different ways, different kinds of retailers do it in different ways. A luxury brand like Gucci will do this in a very different way than a fast fashion brand like Forever 21 will do it. They’re obviously very, very different retailers. They move different kinds of merch for different kinds of price points. But they’re doing the same thing. Look at a really, really well run retailer like Aritzia. All of Aritzia is keyed into getting this latent demand to come in the door, activating it around this certain kind of challenge, and then converting it into incredible brand loyalty. That’s what really powers these businesses. Same on the merchant side, you have the challenge of tack. How do you convert that into something that will produce LTB for a very, very long time?

7. TIP457: Why The Dollar Is Not Collapsing w/ Jeffrey Snider – Trey Lockerbie and Jeffrey Snider

Trey Lockerbie (00:02:14):

So, we have a whole global monetary system right now that I think a lot of people would call a Petrodollar system, and we’re going to work a little bit backwards from what that means. There’s also the Eurodollar system in play that people may or may not be as familiar with. So, I want to actually start there with the Eurodollar. It’s a big loaded question, but going back to basics here, just simply tell us what is the Eurodollar?

Jeff Snider (00:02:39):

Well, technically speaking, and going back all the way to the beginning, Eurodollar refers to a very specific term, and it means US dollars on deposit outside the United States. In the early days, it actually took the form of actual cash deposit, physical Federal Reserve notes, bills, cash bills and things like that, that found their way mostly to Europe, but not just exclusively to Europe, thus the term Eurodollar. It doesn’t have anything to do with the European common currency. It is, again, the term Euro simply means offshore, because this goes way back to the 1950s and 1960s long before the European common currency was ever introduced. So, whenever you hear the term Euro and then attached to a currency denomination, what that simply means is money that the banking system uses outside the jurisdiction of the United States or even any of the other currency denominations that are floating around in it.

Jeff Snider (00:03:31):

So, there are things like Euroyen, for example, which means yen outside of Japan, that’s in this offshore currency system or even something like the Euroeuro, which is offshore euros. So, essentially, after beginning sometime in the 1950s and spreading through the 1960s, we have a huge, very much comprehensive global monetary system that undertook the roles of the reserve currency, global reserve currency, but it’s not actual cash. It’s not actual currency. There’s no money in it. It’s a virtual ledger system, a distributed ledger system that the global banking system operates and therefore has undertaken the roles of a reserve currency because banks have been able to flexibly and dynamically respond to the world in which they live in.

Jeff Snider (00:04:18):

So, for the last 60 years, this Eurodollar system has been essentially the global monetary reserve. And because it’s offshore, it’s outside the jurisdictions, not just the US, but pretty much anywhere, which is kind of a strange concept because these banks are located and doing business someplace. They’re physically located somewhere. But they have located and they have been able to take advantage of various regulatory blank spots, regulatory boundaries. So, this currency system has been able to grow and expand basically outside the reach of national governments, national regulators, bank regulators, whatever it may be and operate throughout the rest of the world. Again, so the point being to create this global reserve currency arrangement that goes back a long, long time.

Trey Lockerbie (00:05:05):

That last point there, what I hear you describing would maybe otherwise be called something like shadow banking, right? Or is that correct? And if not, what is a shadow bank and what is the shadow economic system?

Jeff Snider (00:05:16):

Well, shadow banking is part of it. That’s more about some of the non-bank participants who actually in this global monetary arrangement. I like to use the term shadow money, because they’re actually monetary forms that they don’t show up in any of the statistics. They don’t show up in any regulatory discussions. They’re not involved in any of the mainstream policy framework, because, again, this is outside the United States, it’s outside of every regulatory regime on earth and regulators are not too keen about people knowing about this vast, huge monetary system existing outside of their reach when their entire monetary policy and really political existence, it relies upon the idea that they are very much in control of this system and this arrangement.

Jeff Snider (00:05:57):

So, it’s outside of everyone’s reach, but also the ways in which these banks operate monetarily as well as credit has evolved and changed so that you have monetary forms like currency swaps, for example, that function every bit the same as cash would, except a currency swap doesn’t fit into a monetary aggregate, it doesn’t fit into any sort of quantitative measure, nor qualitative understanding. It doesn’t even fit into the bank balance sheets in a intuitive way. In essence, this is a virtual ledger money system, that’s a shadow money system because of the way the banks operate on their balance sheet.

Trey Lockerbie (00:06:32):

We’re going to explore the significance of that in a minute, but let’s keep with the basics for a minute. So, let’s say the US, we were on a gold standard for a very long time. We had to pay for some wars and stuff and we had to kind of break our promise that was the dollar was backed by gold, we kept changing the money multiplier over time. And at some point, it was unfeasible to continue on with the gold standard. So, like 71-ish, Nixon says, “Hey, you know what, we’re going off the gold standard into this fiat system.” And a lot of people said, “Okay, well,” there was this meeting with Saudi Arabia and we developed this agreement with them to now produce something called the Petrodollar system. And that’s what a lot of people believe we’re operating on today. But is that correct, Jeff? What’s your opinion?

Jeff Snider (00:07:12):

The short answer is no. And it’s a common misperception, because you can understand why. The Bretton Woods system, which was a quasi-gold-backed system, a commodity-based monetary system that grew out of World War II, in the ashes of World War II, where Harry Dexter White and John Maynard Keynes in particular said, “We can’t just have an international currency arrangement because nobody will accept it. So we need to tie this international currency to some national reserve.” And historically speaking, people wanted to use gold, because gold for various reasons that we don’t need to get into here.

Jeff Snider (00:07:40):

So, you had the Bretton Woods system 1944, which always had this inherent flaw or inherent tendency in it as Robert Triffin called it in the late 1950s, eventually become called the Triffin’s paradox or Triffin’s dilemma, which was that in order to operate a global reserve currency, you need to have enough currency floating around the world to be effective. Because what is a global reserve currency? It’s a mediating currency where vastly different systems can connect to each other through this third-party mediating system or mediating currency so that trade, financial flows, all of the free market capitalism that we’ve come to love and honor, those things can happen in a very efficient fashion so that we can have a globalized, highly efficient economic system.

Jeff Snider (00:08:24):

The problem was by tying this international currency and using, for example, the US dollar or the British pound and backing that currency with national stores of physical bullion, there was always going to be the problem where there’d be too much currency needed outside the US, which would then lead to anyone ending up with that currency, redeeming the paper for national reserves. Eventually the national reserves of gold would be drained from the system and Triffin’s paradox would be that once those reserves were drained, the whole thing would just fall apart, which by the way, came close to happening in the late 1950s.

Jeff Snider (00:09:00):

So, we’re talking about not even really 15 years into Bretton Woods, it was already falling apart. So, this is where the Eurodollar steps into it, because it divorces the national currency from the national store of reserves. So, long before 1971, you had this global monetary arrangement, because it was reserveless, because it was ledger money that it began to undertake the roles of the former Bretton Woods system as it broke apart. So, by the time you get to August of 1971 and President Nixon closing the gold window, the Eurodollar had long undertaken all of those roles of the reserve currency before that.

Jeff Snider (00:09:36):

So, August of 1971 represented nothing more than the symbolic end of Bretton Woods when the functional end started a decade and a half before that. So, in terms of the Petrodollar, it wasn’t like we moved from a commodity goal-based monetary system to a oil-based system in the 1970s. We moved off of the commodity-based monetary system long before that. And it had superseded the Petrodollar, the stuff that happened in 1973, for example, and basically all of the functions of the Eurodollar were up and running for more than a decade by then. And even the Eurodollar system itself had become absolutely huge and immense by the early 1970s.

Jeff Snider (00:10:15):

So, the transition took place into something that was a ledger of ledger virtual currency system long before then. And it took place into this offshore bank-centered sort of blank canvas where banks could experiment in all different types of money, so that we transitioned long before from a commodity gold exchange system, the Bretton Woods, to this virtual reserveless currency system under the Eurodollar over a long period of time before we even get to 1973…

…Trey Lockerbie (00:13:59):

So, how much of the narrative that we’re currently operating on comes to us from our actual own Federal Reserve, or even say the media or education around the system that we’re currently in? Because as I understand it, your research has led you to study papers from internal employees at the Fed and elsewhere. And some of them know what’s going on. Some of them are discovering what’s going on through their work. And others just have no clue maybe because they’re in the system and they have that kind of myopic view. So, from the research you’ve done, what’s the takeaway of how informed the people within the system even understand how the global system is operating?

Jeff Snider (00:14:36):

The funny thing is, we always think scientific progress is linear. It always goes in one direction. But here’s an example of how monetary scholarship, academic scholarship about money actually move backwards. When you go back in time to do the historical research, you see there’s much more awareness, much more understanding, not the whole thing, but much more understanding about at least the basics of the Eurodollar system in contemporary time. So, back in the 1960s, for example, it took international authorities and national authorities about a decade after the Eurodollar system began to really start investigating it, because it had become that big of an issue even for national authorities like the Federal Reserve.

Jeff Snider (00:15:11):

But when they did, they were sort of putting bits and pieces of it together through… I mean, which makes sense because it’s a brand new development banks were doing things, they were not sharing the information with anybody, which is, again, why we call it shadow money. So, there was a huge, huge blind spot for even regulators and officials to try to deal with. But at that time, they did attempt to try to understand this Eurodollar system. But then they just, they stopped and they gave up, which begs the question, what is it the Fed did? What does the Fed actually do now? Which goes back to one of the initial quote that you said at the top, when I say the Fed isn’t a central bank, this is the reason why, because what happened was in the 1960s and 1970s, Federal Reserve officials, Treasury officials, government officials, officials at the BIS, or the IMF realized this monetary and banking evolution that was going on through the Eurodollar system made it almost impossible to define, let alone measure and regulate and keep on top of the monetary system.

Jeff Snider (00:16:08):

And if you’re a central bank, if you’re a legitimate central bank, whose job it is to regulate the monetary system, as we all believe, going back to Walter Bagehot in the 19th century, how do you do that when the monetary system has evolved, and it has evolved in these offshore, outside of regulation spaces that make it almost impossible for you to have much of an influence, let alone direct relationship with the banks operating there? So, what ended up happening was around the turn of the decade in the 1970s and 1980s, central bankers decided they just kind of threw up their hands and said, “Well, the monetary thing, it’s too complicated. It’s outside our jurisdiction. So, we can’t really do money anymore. Instead, we’re going to try to make it so that people believe we do money, this expectations-based policy, where we’ll communicate to the public that we’re doing something and hope that the public and banking system and business people all around the world or inside the United States will behave in ways that we want them to behave.”

Jeff Snider (00:17:02):

For example, it became commonplace that, Alan Greenspan, for example, would raise or lower the federal funds rate whenever he wanted to do something. So, if he wanted to “tighten credit” and tighten the monetary system, would he actually tighten the monetary system? Would he go into the monetary system and take money out? No, he raised the federal funds rate, which was nothing more than a signal to the economy at large and try to get the economy and try to get the markets to tighten conditions based on that signal, based on expectations. As he said, during that time, as his predecessors said before, “We just can’t keep track of the monetary system. Therefore, this is what we have left to be able to do to try to get some form of control over the economy and the marketplace.”

Jeff Snider (00:17:44):

So, it’s really about this evolution in money in banking that took place outside of their purview, which left official scrambling to try to do something else to at least attempt to maintain the role of what a central bank used to do, but it’s not a monetary role. It’s not involved in the monetary system itself. So, once that happened, monetary scholarship simply dried up. The term Eurodollar kind of disappeared, not just from internal discourse, but from public discourse as well. So, you have a wealth of scholarship up to around early 1980s and then just nothing. Because what happened was we were told, we were all told, we were taught this in school. “At that point, don’t fight the Fed, just whatever the Fed says, whatever the Fed, they must know what they’re talking about when it comes to money, you don’t need to know. Just trust Alan Greenspan and Ben Bernanke. They’ve got it all covered.” So, once there was a vibrant monetary or debate and argument, it just kind of disappeared and dried up and went away.

Trey Lockerbie (00:18:40):

But it’s not all an illusion, is it? Because if we fast forward to today, we’re seeing it happen and play out in real time, where inflation is now high again as it hasn’t been for decades and they’re raising interest rates. And now we’re starting to see things like mortgage rates go up and home prices get underwritten in a new way. We’re seeing real economic impact from these decisions or actions from the Fed. So, where does the detachment actually occur in your opinion?

Jeff Snider (00:19:05):

Well, because that isn’t actually inflation. This isn’t due to money printing. This is sort of the federal… I mean, that’s why you didn’t see consumer prices react to QE6 back in 2020. Consumer prices didn’t start to skyrocket until March and April of 2021, which was coincident to the US treasuries helicopter drops. So, this wasn’t money printing, this wasn’t the Fed creating money. This wasn’t the Fed being a central bank. It was essentially a supply shock, which was the US government redistributed borrowing through the Treasury and mostly Treasury bills actually, the US government essentially redistributing cash into the pockets of consumers. And then consumers wind up spending that cash at a time when the ability of the global economic system to supply goods and then transport goods in particular was at its lowest point. So you see inventories of goods actually crash during these periods because we had essentially a supply shock.

Jeff Snider (00:19:59):

So, it isn’t inflation as much as it was consumer prices reacting to small E economics. Whenever you have a demand curve shift out to the right, especially when supply isn’t as any elastic as it was during that time, consumer prices have to react. I know most people are saying, “Who cares? Consumer prices went way up. What does it matter if it’s inflation? Or what does it matter if we call it inflation or not?” The issue is how it ends, because if it’s nothing more than a supply shock, it’s always going to be temporary and transitory rather than something like the 1970s, where you ignite the monetary spark of excessive currency, that leads to all sorts of, well, great inflation type of problems. So, how do we tell one from the other?

Jeff Snider (00:20:40):

And one of the things that consistent with excessive currency and money printing would’ve been destruction of the US dollar has been long proclaimed, long predicted, and long forecasted. But what you see ever since last year is the US dollars exchange value going up against almost every currency, because it wasn’t money that was printed. It was simply a supply shock. And because it wasn’t money printing, the way this is likely to end is in another bad way, which is a recession. That’s really what markets have been predicting over the last more than a year, actually, because the yield curve has been flattening. So, even as interest rates have been rising, the yield curve has been flattening. The Eurodollar futures curves have been flattening. All of the signals from the monetary system itself have been sending, “Hey, there’s no money here. This is not money printing. This is a supply shock and this is going to end predictably in something like a contraction or recession.” So, it was never inflation to begin with. It was simply small E economics of a supply issue.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Amazon and Shopify. Holdings are subject to change at any time..

What We’re Reading (Week Ending 03 July 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 03 July 2022:

1. Why Foundational Models will Revolutionize the Future of Work and Play – Daniel Jeffries

It’s 2033 and you’re coming home from a dinner and realize your sister’s birthday is tomorrow and you forgot.

You ask your phone what’s the best gift for her and where you can get it at this late hour?

Your phone has dedicated processors for running Machine Learning (ML) models locally but it’s not powerful enough to answer that question with its small memory and slower chip speed.  But it is strong enough to ask a more powerful model in the sky.

The local model also learned a lot about what you and your family likes over time, so it packages up some key things it knows, anonymizes them, and fires off a query to a Foundational Model (FM) in the cloud via API.

In a fraction of a second, the answer comes back.

Your sister’s latest social media pics show she recently got on a serious health kick, lost weight, stopped drinking and got really into vegetarian cooking so it recommends an AirBnB cooking experience near her, with a local vegetarian chef.  It gives you two alternative experiences that are good but a bit further away and not as highly rated.  You don’t even need to go to the store and it’s the perfect present that makes you look like a hero…

…Across the world people are using cascaded FM’s networked together to do amazing work.  FMs on their own are amazing but working together they’re capable of astonishing feats and when they work with you they’re centaur units, a combination of man and machine working together to create something neither could do on their own.

Centaurs are named after Gary Kasparov’s early experiments with chess tournaments, where an AI and human teams bested pure AI and humans on their own. The tournament’s name came from the mythical beast of Greek legend that’s half horse and half man, symbolizing how man and machine can work together better…

…Biotech companies search through massive databases of proteins and chemical interactions and quickly use a fine tuned FM to design twenty potential drug candidates to fight a rare motor neuron disease that recently cropped up in South Africa.

A musician jams out a new tune and then asks the models to iterate on the chorus.  The 17th one is awesome and the musician plays it and then modifies it with a few tweaks to make it even more catchy based on a song he couldn’t get out of his head a week ago that he overheard on a radio at the local park. It goes on to be a huge hit on Soundcloud.

Materials scientists are designing new materials that make everything stronger and lighter, from skyscrapers that flex more easily to resist earthquakes, to electric bikes that are light enough to carry on your shoulder and fold up neatly to carry on the train.

Elite coders are simply telling the coding model what they want it to do and its spitting out near perfect Python code but it also recommends Go for several libraries because it will be faster and more secure.  It automatically does the translation between languages and tests it. It’s paired with an evolution through language model (ELM) coupled with a Large Language Model (LLM) and those models helps the coder create brand new, never before thought of code too, in a domain the model was never trained for by iterating on concepts quickly.

All of it is happening because of a vast global network of ambient AI models.  AI is everywhere now.  Every device is waking up and getting smarter.  We’ve industrialized intelligence and sparked a revolution in how we work, design, and play.

Welcome to the age of ambient AI…

…What are Foundation Models and why do they matter?

In essence, FMs are large models that exhibit remarkable capabilities, such as the ability to understand language, reason, create working computer code, do translations and arithmetic, understand chains of logic, generate totally new art from text prompts, and much much more.

The basic concept of FMs comes to us from Stanford University where they primarily refer to Large Language Models (LLM), like GPT-3, that are typically transformers. But the implications of FM’s go way beyond today’s architectures.  They’re a groundbreaking type of software, that’s not limited to transformers or language.

We can think of FM’s are any large and sophisticated model.  We can also think of them as a chain of cascading models that work together to do a complex task such as generate music or images or video, create mathematical proofs, design new materials or discover new drugs and more.

Many of them are already here.

GPT-3, from OpenAI, powers GitHub co-pilot that quickly writes code for developers, especially boring, repetitive code so they can focus on more creative tasks.  It’s one of the first fantastic examples of a centaur.  Originally, GitHub’s team wasn’t sure who would use it.  Would it be beginning or advanced coders?  Since its wider release to all developers, the answer is clear: advanced coders love it and use it most often.  Advanced coders are in the best position to understand when the model makes a mistake and it dramatically speeds up their day to day coding…

…In another article, called The Coming Age of Generalized AI, I highlighted researchers who were working on even more groundbreaking approaches by combining mega-models with several other key techniques.  One of techniques, called progress and compress that comes to us from DeepMind, combines three techniques, progressive neural networks, elastic weight consolidation and knowledge distillation.

The idea is simple. Create two networks, a fast learning network and a base model. That roughly mirrors the functioning of our brain yet again. Think of it as the hippocampus and neocortex. As Hannah Peterson writes in her article on catastrophic forgetting,  “In our brains, the hippocampus is responsible for “rapid learning and  acquiring new experiences” and the neocortex is tasked with “capturing  common knowledge of all observed tasks.” That dual network approach is called a progressive neural network.

The fast neural network is smaller and more agile. It learns new tasks then transfers the finalized weights to the base model. So you end up with a lot of stored neural networks good at a bunch of tasks.

But there’s a problem with basic progressive neural nets. They don’t share information bi-directionally. You train the fast network on one task and freeze those weights and transfer them to the bigger network for storage but if you train the network first on recognizing dogs, it can’t help the new network training on cats. The cat training starts from  scratch.

Progress and Compress fixes that problem by using a technique called knowledge distillation, developed by deep learning godfather Geoffrey Hinton. Basically, it  involves averaging all the weights of different neural nets together to create a single neural network. Now you can combine your dog trained model and cat trained model and each model shares knowledge bi-directionally. The new network is sometimes slightly worse or slightly better at recognizing either animal but it can do both.

It opens the door to cat-like intelligence.

A cat is a remarkable creature. It can run fast, sleep in tiny boxes, find food and water,  eat, sleep, purr, defend itself, climb trees, land on its feet from  great heights and a hundreds of other subtasks. A cat won’t learn language or suddenly start composing poetry. That’s perfectly fine because a cat is really well suited to its set of tasks; it doesn’t need  to build skyscrapers too.

Having a cat level intelligence is incredibly compelling. If you have a cleaning robot that can wash  dishes, pick up clothes, fold them, carry them from place to place and  iron shirts, that’s an incredible machine that people would clamor to buy. It doesn’t also need to write music, craft building blueprints, talk to you about your relationship problems, and fly a plane too…

…AI is a universal, general purpose technology.

The greatest breakthroughs in history are always universal technologies that affect a broad range of sectors as they branch into countless other domains and inspire unexpected breakthroughs.

Think of the printing press and the way it leveled up human knowledge across the board because now we could scale, save and replicate knowledge much faster.

Think steam engines that changed the very nature of work from human and animal powered muscle work to work done by machines.

Think of the microprocessors and computers that changed how we do art, communicate, design skyscrapers and houses, fight wars, find love, do science, make music and movies and more.

A general purpose technology like AI has direct and secondary effects on the world at large, both good and bad and everything in between.

We can think of ideas and technology as they grow and change and affect both their own domains and unexpected domains as a growing tree.  The roots are precursor ideas that eventually inspire the primary idea.  The trunk is the central breakthrough idea, which leads to a branching series of closely related ideas and some unexpected inventions in parallel domains.

2. Reducing Inflation Will Come at a Great Cost: Stagflation – Ray Dalio

More specifically, I now hear it commonly said that inflation is the big problem so the Fed needs to tighten to fight inflation, which will make things good again once it gets inflation under control. I believe this is both naïve and inconsistent with how the economic machine works. That’s because that view only focuses on inflation as the problem and it sees Fed tightening as a low-cost action that will make things better when inflation goes away, but it’s not like that. The facts are that: 1) prices rise when the amount of spending increases by more than the quantities of goods and services sold increase and 2) the way central banks fight inflation is by taking money and credit away from people and companies to reduce their spending. They also take buying power away by raising interest rates, which increases the amount of money that has to go toward paying interest and decreases the amount of money that goes toward spending. Raising interest rates also lowers spending because it lowers the value of investment assets because of the “present value effect” (which I won’t get into because it would be too much of a digression), which further lowers buying power. My main point is that while tightening reduces inflation because it results in people spending less, it doesn’t make things better because it takes buying power away. It just shifts some of the squeezing of people via inflation to squeezing them via giving them less buying power.

The only way to raise living standards over the long term is to raise productivity and central banks don’t do that…

…In summary my main points are that 1) there isn’t anything that the Fed can do to fight inflation without creating economic weakness, 2) with debt assets and liabilities as high as they are and projected to increase due to the government deficit, and the Fed also selling government debt, it is likely that private credit growth will have to contract, weakening the economy, and 3) over the long run the Fed will most likely chart a middle course that will take the form of stagflation. 

3. The Beer Game – Peter Dizikes

Thursday, August 29, 1:00 p.m.

It is a miserably muggy afternoon in Cambridge as the incoming class of the MIT Sloan School of Management—roughly 400 students from 41 countries—files into a second-floor ballroom at the Kendall Square Marriott. They are here to play the Beer Game, a Sloan orientation tradition. Unfortunately given the weather, the Beer Game does not involve drinking cool beverages…

…Rather, the Beer Game is a table game, developed in the late 1950s by digital computing pioneer and Sloan professor Jay Forrester, SM ’45. Played with pen, paper, printed plastic tablecloths, and poker chips, it simulates the supply chain of the beer industry. In so doing, it illuminates aspects of system dynamics, a signature mode of MIT thought: it illustrates the nonlinear complexities of supply chains and the way individuals are circumscribed by the systems in which they act…

…1:30 p.m.

Each Beer Game team is divided into four units of two players each, who play the roles of retailer, wholesaler, distributor, and brewer. The goal is to keep team operating costs as low as possible. We learn that teams will be penalized for having too much inventory (50 cents per case of beer per week) or unfilled back orders ($1 per case per week). Each link in the supply chain keeps track of its own costs, but a team’s score is the sum of these tallies. The lower the score, the better.

As we begin the first of 50 rounds (which represent weeks), each retailer unit draws a card indicating consumer demand for cases of beer; at the same time, all the units send slips of paper with orders up the supply chain. In response, cases of beer—represented by poker chips—move in the opposite direction, from brewer to retailer. A small number of chips are already at every station when we start.

2:15 p.m.

After 20 rounds, my team is on a hot streak.

I’m sitting at the retailer station with finance student Adah Jung, who’s been submitting orders at a level closely mimicking consumer demand. Our score at the retail station is low, and there are few chips elsewhere on the table, meaning our team’s costs are minimal. It’s hard to see how things could go wrong: with seven smart teammates and a stable supply chain, why can’t we win this thing? I can almost hear Sterman asking us to stand for a round of applause.

2:35 p.m.

Seemingly out of nowhere, our team’s distributorship has an inventory of 178 surplus cases of beer, which lasts seven weeks, adding $623 to our costs in a game where the average score after 50 weeks is $2,000 per team. How did that happen? Can’t someone tell our two teammates at the brewery just to stop making so much beer?

Well, no. “I can’t tell them anything,” observes teammate Juan Trujillo. Indeed, to simulate the incomplete information we deal with in real life, players cannot communicate across stations, apart from relaying orders. And somehow, someone on our team ordered way too much beer…

…3:30 p.m.

Sterman’s assistants tape charts to the ballroom walls detailing every team’s performance. Today’s winning score was $460 (the best possible score is about $200), while the worst-performing team racked up $6,618 in costs.

Sterman initiates a discussion, pointing out how inventories and backlogs spike and plummet erratically. The distributor on today’s last-place team went from a backlog of 70 cases to an inventory of 191 in three weeks.

One thing to learn from the Beer Game, then, is why many businesses experience boom-and-bust cycles—oil and gas exploration and housing among them. Complex systems produce nonlinear phenomena.

4:15 p.m.

Sterman pounds home a bigger lesson: our psychological habits and limited perspectives often keep us from properly understanding complex systems. To prove it, he asks distributors, wholesalers, and brewers to estimate their consumer demand; their responses are wildly inaccurate.

All too often, Sterman adds, this means we attribute problems to other people rather than to flawed systems. For instance: “I found that some people were kind of slow to take corrective action,” offers one student—who had just played for the winning team, a fact Sterman emphasizes to much hilarity.

It doesn’t make sense for us retailers to blame our teammates—who had imperfect information—for our disappointing scores. “It just cannot be true that, by chance, all the smart people ended up as retailers and all of the people running the factories were dumb,” Sterman says. The Beer Game’s structure makes it hard for certain players to perform well. It’s not the people; it’s the system.

Thus, firing people tends to be a futile management action. “Your role as a leader is to create a system in which everybody can thrive,” he says…

4. Why does the Stock Market go up? – Eugene Ng

A Google Search of “Why does the Stock Market go up?”, and Investopedia gives you up a broad range of factors.

The factors range from the supply and demand of buyers and sellers, to economic indicators, consumer confidence, wars/politics, concerns over inflation / deflation, government fiscal / monetary policy, technological changes, natural disasters or weather events, corporate or government performance data, regulation/deregulation, and the level of trust in the financial sector and legal system, amongst so many others.

But this doesn’t really answer the question, doesn’t it? It only leaves you, more confused, and begging for a better answer…

…The factors listed above are not wrong. Yet, they do not help you figure out why stock prices rise.

In the short-term, stocks will move up and down for a variety of random reasons — all of which does nothing to increase your chances of a positive return.

Thus a better question would be:

“Since the short-term does not really matter as much, why then does the stock market go up over the long-term?”

To get closer to the truth, you need to understand the components which drive the returns on your stock investment.

The Total Shareholder Return (TSR) from holding common publicly-traded stocks can be broken down into three key components: (1) growth in Earnings per Share (EPS), (2) change in the Price-to-Earning (PE) valuation multiples, and (3) earnings from dividends…

…With S&P Global providing us with historical data on the S&P 500’s closing levels, Sales per Share (SPS), Earnings per Share (EPS) and Dividend per Share (DPS), they provide clues on what the growth has been thus far…

…Take 2021 to 2003, the longest period spanning over 18 years (first row, last 5 columns from the right). During this time, the S&P 500 Index more than quadrupled from 1,112 to 4,766, with TSR* growing by ~4.3X (8.2% CAGR).

The contribution of the Earnings per Share (EPS) growth is telling. Earnings per Share (EPS) grew by ~4.1X (8.1% CAGR) from 48.7 to 197.9. Further breaking down that EPS growth, Sales per Share (SPS) grew by ~2.2X (4.5% CAGR) and Net Income Margin Growth (NIM) grew by ~1.8X (3.5% CAGR).

Thus the growth in earnings (EPS) accounted for the majority (~95%) of the TSR* growth, with growth in sales/revenues (SPS) and improvement in net income profit margins (NIM) accounting for ~52% and ~43% of TSR* growth respectively…

…Given what we have laid out so far, you, you should not be surprised to learn that over the long-term, it is earnings growth, supported by revenue and profit growth, that drives the stock market higher, and to a much lesser extent, valuation multiples.

5. Pioneer Helped Turn Her Family Store Into Japan’s Biggest Retailer – Chieko Tsuneoka

First her father died young, then her mother, then her older sister. At 23, Chizuko Okada inherited the job of running her family’s clothing store in Mie prefecture, Japan.

It was 1939, and war with America was just around the corner. Few could have foreseen that the little business would develop into Japan’s largest retailer by sales—or that a woman would be its driving force.

By the time Chizuko Kojima—her married name—died on May 20 of old age at 106, the company now known as Aeon Co. had thousands of stores around Japan and the rest of Asia and annual revenue equivalent to $64 billion…

…Ms. Kojima was born on March 3, 1916, as the second daughter of the Okada family, which had run a fabric and kimono store since 1758 in Mie prefecture, just west of Nagoya in central Japan.

Chizuko’s father, Soichiro Okada, modernized the business but died of heart disease in 1927 at age 43. Then Japan was hit by the Great Depression, which caused bankruptcies and joblessness.

In a 2003 book, Chizuko wrote that she believed it was necessary to be ready for such cataclysms by studying history. The hard times deprived her of a chance to pursue higher education in Tokyo.

After taking over the family business, Chizuko managed to keep it going during World War II until a U.S. bombing raid destroyed much of their home city of Yokkaichi in June 1945, including the Okada store’s stock.

At the time, customers held coupons similar to gift certificates entitling them to store goods. The store no longer had anything to offer, but Chizuko posted notices throughout the city saying her shop would give cash in exchange for the coupons, recalled her younger brother, Takuya, in a 2005 autobiography. It was a way of maintaining customers’ loyalty that would pay ample dividends in years to come.

Chizuko loved studying and during the war, she read a book about Germany’s inflation after it lost World War I. When Japan surrendered in World War II in August 1945, she predicted the same would happen. She gathered her cash and bank loans and bought as much merchandise as possible, reopening the shop in March 1946, ahead of an inflationary surge that hurt other businesses.

“All the merchandise flew off the shelves,” Takuya recalled.

Chizuko wrote of the episode, “Through my own experience, I learned the importance of studying and reading records of the past.”…

…In 1959, when the Okada family business still had just two stores, she came back to take charge of personnel and other behind-the-scenes management issues.

That year, Chizuko and Takuya made their first visit to the U.S. and toured the famous Sears, Roebuck and Co. store in Chicago. Takuya wrote that he was impressed by the giant scale of the business. Paging through the thick Sears catalog full of pictures of refrigerators, washing machines, clothing and a myriad of other goods, he imagined the day that Japan, too, would enjoy that kind of affluent life.

Chizuko was impressed by the Sears pension system, thinking it would create a loyal workforce. She introduced one a decade later, as her brother rapidly expanded the retailer through mergers. She also introduced an in-house training organization, today known as the Aeon Business School…

…Chizuko was one of the first managers in Japan who aggressively hired female full-time employees and homemakers as part-timers. She saw that many women worked in the U.S. and believed Japan should follow suit.

By having women at the company, “we were able to bring on board the viewpoint of the customer—how much to sell and at what price,” she said in a television interview when she was 90.

6. Make Haste Slowly – Chris Mayer

I had been reading The Art of Worldly Wisdom: A Pocket Oracle, a book written in 1647 by Baltasar Gracian, who was a witty Jesuit from Spain. His book of 300 aphorisms, with  his commentary on them, has been translated into many languages and has earned the praise of many philosophers ever since.

Arthur Schopenhauer loved it so much that he prepared a German translation himself. Schopenhauer said it was particularly good for young people, as it would give them experience it would otherwise take years to obtain. “To read it through once,” he wrote, “is obviously not enough; it is a book made for constant use.”…

…Anyway, there is a passage where Gracian talks about the motto “festina lente.” This Latin phrase is usually translated as “make haste slowly.” One must be very patient and yet ready to act swiftly. And the fastest way to achieve your goals is sometimes by doing nothing.

The motto was a favorite of the Roman Emperor Augustus. Engravers captured the idea with an emblem of a dolphin wrapped around an anchor, which they stamped on coins. Another emblem captured the same idea with a crab and a butterfly; again marrying this idea of fast and slow.

Festine lente recurs throughout history and has been captured in a variety of images, such as a rabbit coming out of a snail shell. The Medicis chose it as their motto and illustrated it with a sail-backed tortoise.

I thought the idea beautifully captured an important idea in investing that is often counterintuitive: to get where you want to go the fastest often means acting very slowly if at all…

…It does seem incredibly counterintuitive to say, “No, you shouldn’t  try to sell before a recession.” Or: “No, you shouldn’t ‘reposition’ your portfolio based on recent events.”  Don’t these seem like logical things to do?

Not if you want to enjoy the wonderful effects of compounding capital over long periods of time. The main problem with trying to do the above is they are too hard to do well enough. You have to think about trying to do these things repeatedly over a lifetime of investing. The odds against you are very great. Sure, you may be right sometimes. But you will most certainly sit out stretches of time where you could have earned great returns because you’re afraid of a recession. Odds are you won’t get those “repositionings” right repeatedly either.

7. How Parents’ Trauma Leaves Biological Traces in Children – Rachel Yehuda

After the twin towers of the World Trade Center collapsed on September 11, 2001, in a haze of horror and smoke, clinicians at the Icahn School of Medicine at Mount Sinai in Manhattan offered to check anyone who’d been in the area for exposure to toxins. Among those who came in for evaluation were 187 pregnant women. Many were in shock, and a colleague asked if I could help diagnose and monitor them. They were at risk of developing post-traumatic stress disorder, or PTSD—experiencing flashbacks, nightmares, emotional numbness or other psychiatric symptoms for years afterward. And were the fetuses at risk?

My trauma research team quickly trained health professionals to evaluate and, if needed, treat the women. We monitored them through their pregnancies and beyond. When the babies were born, they were smaller than usual—the first sign that the trauma of the World Trade Center attack had reached the womb. Nine months later we examined 38 women and their infants when they came in for a wellness visit. Psychological evaluations revealed that many of the mothers had developed PTSD. And those with PTSD had unusually low levels of the stress-related hormone cortisol, a feature that researchers were coming to associate with the disorder.

Surprisingly and disturbingly, the saliva of the nine-month-old babies of the women with PTSD also showed low cortisol. The effect was most prominent in babies whose mothers had been in their third trimester on that fateful day. Just a year earlier a team I led had reported low cortisol levels in adult children of Holocaust survivors, but we’d assumed that it had something to do with being raised by parents who were suffering from the long-term emotional consequences of severe trauma. Now it looked like trauma leaves a trace in offspring even before they are born.

In the decades since, research by my group and others has confirmed that adverse experiences may influence the next generation through multiple pathways. The most apparent route runs through parental behavior, but influences during gestation and even changes in eggs and sperm may also play a role. And all these channels seem to involve epigenetics: alterations in the way that genes function. Epigenetics potentially explains why effects of trauma may endure long after the immediate threat is gone, and it is also implicated in the diverse pathways by which trauma is transmitted to future generations.

The implications of these findings may seem dire, suggesting that parental trauma predisposes offspring to be vulnerable to mental health conditions. But there is some evidence that the epigenetic response may serve as an adaptation that might help the children of traumatized parents cope with similar adversities. Or could both possible outcomes be true?..

…It is tempting to interpret epigenetic inheritance as a story of how trauma results in permanent damage. Epigenetic influences might nonetheless represent the body’s attempts to prepare offspring for challenges similar to those encountered by their parents. As circumstances change, however, the benefits conferred by such alterations may wane or even result in the emergence of novel vulnerabilities. Thus, the survival advantage of this form of intergenerational transmission depends in large part on the environment encountered by the offspring themselves.

Moreover, some of these stress-related and intergenerational changes may be reversible. Several years ago we discovered that combat veterans with PTSD who benefited from cognitive-behavioral psychotherapy showed treatment-induced changes in FKBP5 methylation. The finding confirmed that healing is also reflected in epigenetic change. And Dias and Ressler reconditioned their mice to lose their fear of cherry blossoms; the offspring conceived after this “treatment” did not have the cherry blossom epigenetic alteration, nor did they fear the scent. Preliminary as they are, such findings represent an important frontier in psychiatry and may suggest new avenues for treatment.

The hope is that as we learn more about the ways catastrophic experiences have shaped both those who lived through those horrors and their descendants, we will become better equipped to deal with dangers now and in the future, facing them with resolution and resilience.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google) and Wix. Holdings are subject to change at any time.

What We’re Reading (Week Ending 26 June 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 26 June 2022:

1. Josh Wolfe, Chris Power – Factories of the Future – Patrick O’Shaughnessy, Josh Wolfe, and Chris Power

[00:02:39] Patrick: Chris and Josh, this is going to be a totally different conversation about an area that I don’t think I’ve ever explored before, very keyed in on a certain kind of manufacturing. I’m sure we’ll hit bigger themes of onshoring of manufacturing in just the next generation of this part of the economy. We’ll spend a lot of time around precision parts, what Hadrian’s doing, why Lux is interested in this area, what Chris, you and your team, are building. To set the stage, Chris, it would be great if you could, as you did for me on the phone recently, give an overview of the recent past and what has happened in this world. It’s become a topic that everyone’s talking about a little bit, but probably doesn’t really fully understand the recent intermediate past of manufacturing, where it happens, why it’s happened that way. So a little bit of a history lesson would be a great place to start to frame our conversation.

[00:03:23] Chris: For advanced manufacturing, in general, which I describe as space, defense, semiconductor, eVTOL, energy, medical devices, basically everything in the Jetson’s flying car, future, all has to be domestically manufactured because of ALTAI requirements. It’s super high precision components. And basically, 80% of the manufacturing parts for those industries flows through a high precision network of machine shops. There’s 3,000 or 4,000 of them. Average size is 10 to 12 million in revenue. In aggregate, they do 40-50 billion in revenue, but it’s incredibly fragmented, super low NPS. It’s the most perfect Keith Rabois fragmented, low NPS, vertically integrated structure you could ever possibly think of. Historically, what happened is this was built off the defense primes needing a bunch of suppliers. All these machine shops got built in the first Space Race or the Cold War. They were businesses that got started 30 years ago by 30 year olds. And now they are 30-year old businesses run by 60 year olds. What’s happened in the last five years is there’s not a lot of slack in the system. And generally, a machine shop might be making some semiconductor parts, some parts for Boeing, and then some parts for Raytheon, for example. In the last five years, because of the boom in commercial space, which has been largely driven by lowered launch costs, the success of companies like SpaceX and Anduril, and then investors like Josh have been putting money into satellite companies, rocket companies, the whole thing. If the top level, you’ve got a bunch of net new spend in high precision components from commercial space and companies like Anduril that are flooding the same supply chain. That’s big problem number one.

And what you’re seeing for those customers is, “Hey, I’m trying to ship a satellite really quickly. I’m getting parts in 6 to 10 weeks. That’s insane. Because I’ve got an aerospace engineer sitting around for another part, wasting time, when I’m trying to get a launch up. I’m trying to get my startup goals.” So all these new entrants to the market are going way, way faster than your traditional primes. Now, that’s putting speed pressure on the supply chain. And basically, you’ve got this thing where customers want fast supply chain, huge opportunity to build a business meeting that need, with a bunch of net new spend in the supply chain. That’s phase one is Hadrian builds a better mouse trap for new space and new defense. The second phase, which is really scary for the country though, is all of those 60 year olds are going to retire in the next 5 to 10 years at an increasing rate. And 90% of them, historically, when they do retire, don’t transition to private equity, or sell or transition the business to a son or a daughter. They sunset the business, lock the door, sell a machine, and throw away the keys. There’s two bits that are really dangerous for the country about that. The first one is just purely capacity. In the decade where we’re trying to butt heads with the CCP and win Space Race 2, the capacity that feeds rocket satellite, drone companies is going to fall through the floor because of this capacity issue. They’re retiring, so you’ve got this huge supply and demand imbalance in the worst possible decade that that could be happening. And on top of that, it’s not as simple as, say, a Raytheon going, “Hey, Patrick’s Machine Shop, you’re retiring. Let’s take all the digital files that tell someone how to make those parts, and give it to another machine shop.” Most of them have been made for 20 years. There’s no CAD file. The drawing is in someone’s desk drawer. And we’ve just seen this where we shipped something like a third of all our Stinger and Javelin missiles to the Ukraine. This is on the defense side, but this happens across space semiconductor really. So we shipped all over to the Ukraine. The Biden administration went to Raytheon and said, “Hey, we need more Stingers and Javelins.

And then Raytheon came back and said, “Well, apart from the fact that supply chain’s super bottlenecked and we can’t ramp up production, we just don’t know how to make any of the parts anymore. And it might take a couple of years to figure it out.” So it’s a complete disaster, both on net new spends in secular growth and decline. But what people don’t realize is it’s not as simple as, “Hey, let’s raise your semiconductor. Let’s throw a 50 billion into an Intel plant in Arizona.” Because in the ’70s and ’80s, when we outsourced advanced manufacturing, what we lost was not just capacity or capability, it was the talent and the people. And what people don’t understand about manufacturing, it’s like software engineering. To get AI researchers, you have to have a base of backend software engineers. You’ve got a million software engineers, and it breeds the best. It breeds the best. And all of a sudden, you’ve got some top tier people in deep cloning and all that other stuff. It’s the same in manufacturing. You can’t really skip these training levels. So what we lost was not the knowhow to do a specific part, but the talent base that can produce better and better people that can work on things like semiconductors or advanced manufacturing. The slack in the system is not simply a capital problem. It’s this talent based problem. You can solve some of that by trying to grab some people from Taiwan, people who really know this, and rebuild all these industries. But it’s much, much slower than people think it is because it’s not as simple as turning a capital key, buying some machines, and ramping up production capacity. It’s incredibly difficult to do. It’s a huge commercial opportunity, but it’s incredibly important that we get this right for the country because space is basically a defense domain. Peace through strength is a huge deal. We’ve created this period of peace with Pax Americana. And I think in the next couple of years, maybe in the next 18 months, we’re going to really see that a lot of that is risked, and there’s going to be a huge wake up call when the average American consumer not just can’t buy an iPhone for less than $4,000, possibly can’t buy one at all because of all this global shifting of the advanced manufacturing supply chain…

...[00:12:57] Patrick: I actually just did one of these with Brian from Anduril. And it was really interesting to dive into the nature of the pieces of what they’re building and their goal for speed, simplicity, modularity the philosophy of how these things are built, whether it’s Ghost or whatever the product is at Anduril, is it’s very different from a Predator drone or something that Lockheed or Northrop would put out over the course of a decade. I’m curious, Chris, how much you think in the success case for Hadrian, where it’s everything you dreamed of and more, 10 years from now, how its existence changes the nature of the things that get built? What will this new manufacturing capability, just like Stripe and Twilio, people build stuff that they couldn’t have dreamed of before because they were able to go so fast with this new tooling, how do you think about that, Chris, in terms of what this might lead to? That even though there’s amazing things happening at SpaceX and everywhere else, it’s on the back of these 3,000 mom-and-pops. What will be different in the success case for Hadrian, for the people at the top of the chain?

[00:13:53] Chris: I think if you think about software engineering 10 years ago, maybe to start a SaaS company, it costs a million dollars, and you were spending more than 50% of your time on activity like running a server farm or building payments that every single software company had to deal with. When you see these platform infrastructure companies like AWS come out, or Stripe come out, or Twilio, you get to really interesting dynamics. One of which is the cost to start a company in this space goes through the floor. So now with all the tooling, you can start a software company for a couple hundred dollars. Secondly, the number of companies that get started because of that tooling goes through the roof. And then the third thing is the speed at which those companies can iterate, basically turn engineering time into a good product that the market wants, goes through the roof because their iteration cycle goes through the roof.

If we get this right, we should be able to drive three things. One is that existing companies can iterate on products in order of magnitude faster, which means that at the product layer, you just get better products. You’re not doing a year long cycle for a satellite. You’re doing a two month cycle for a satellite. As you’re getting feedback from the customer, your designs can change way, way faster. Secondly, by having Hadrian as a platform, we should be able to dramatically lower the cost of starting advanced manufacturing companies, which will drive a Cambrian explosion in both this evolutionary, who’s winning in the marketplace to build a satellite company or a drone company. The raw number of these companies that start will go through the roof. And that would be success for me.

[00:15:19] Josh: One of the things you just said, which I think is really interesting, there’s this old thought experiment, which was actually manifest in a physical experiment, where you took two different classrooms of people that were making some sort of pottery. They had a very specific end state of a pot that they had to make. And one was told, “Spend two hours or an hour or whatever it was making the pot as perfect as you can.” And the other was told, “Make as many pots as you can.” The latter, which was rapidly iterating, and trial and error, and trial and error, ended up making the more perfect pot. So that idea, which I think applies to industry, is if you make something and then you’re waiting forever to test it in the real world versus being able to rapidly iterate. The latter example is something that Hadrian’s going to enable, that in turn then, lets many more startups flourish for less capital. We can do more experiments, fund more companies. They can fail fast. Or they can come up with a product that is superior and competitive, and then build a platform from there…

[00:22:50] Patrick: Chris, can you help us understand, going all the way to the beginning of the supply chain, the rare earth or base metal component of this process? Because I don’t think people have probably thought too much about is this aluminum, is it steel, is it titanium, is it something else? What’s the 101 on the actual raw materials that are important in this process? Because out of nowhere, after a decade of silence, the commodity world has come alive. There’s issues shipping, there’s issues sourcing, there’s issues in pricing, there’s inflation. This becomes a really important thing really quickly. So give us a little tutorial on what are the important metals that go into all of these shops as raw material and anything that you think we should know about the nature of that today?

[00:23:30] Chris: Basically there are four main alloys that all space defense semiconductor satellite companies use. Aluminum, 6061, 7070, steel variants, so 306, 316, 30X, titanium, and then Inconel variants. There’s a ton of aluminum on satellites. There’s slightly less aluminum on rockets. And then on rockets, you start to get into steels and harder metals like titanium and inconel because the closer you get to the engine, the hotter it is, so you need material that can withstand heat. And then it’s the same thing for the defense side. So if you look at a fighter jet, there’s a bunch of structural aluminum, there’s a bunch of structural titanium, because it’s incredibly lightweight, and then the engine is incredibly hard, heat withstanding materials like inconel. Those are the input materials to the parts. So let’s talk about that. I mean, let’s talk about the parts that are on the machines that we run in our factory, because that’s a little bit scarier. In a sense, I think the aluminum price over the last year, it’s come down a little bit now, but I think it doubled. That was a supply chain shock from the inputs, but then the mills themselves in America had a labor shortage. There was just lack of supply, so the price went up. The parts that went on those satellites during that nine month period, the machine shop can’t absorb them, so it gets passed on, so the satellites are now 30% more expensive. And if you look at where those materials get sourced from, we have a pretty good supply of aluminum in the United States. 90% of the titanium in the world comes from Russia and the Ukraine. A bunch of aluminum and steel comes from Europe as well. And actually, if you look back to the Cold War, our spy planes were made out of mostly titanium. Skunkworks had to sneak titanium out of Russia to be able to make spy planes.

This is why I think a lot of the hand waving around sanctions is ridiculous, because if you’re in an adversarial position and you say, “Hey, we’re doing all these sanctions,” and then there’s 50 exclusions because you’re kidding yourself about the fact that this guy’s the only one with a titanium. It’s just ridiculous. That is a real problem both on lack of production, but also availability of supply to American companies because a lot of that is offshore, which makes me crazy, because the State Department years ago should have been going to Latin America and Africa and getting supply of all this stuff and partnering with these countries and raising them up. Whereas China through Belt and Road has secured a lot of this global supply because they’ve got Russia locked up with the whole energy pipeline thing. They’ve got Africa locked up. So it’s a real huge challenge. For rare earth materials, which are more things that go into batteries, chips, that sort of stuff, they’re not on the parts that we’re producing, but our machines obviously have a ton of chips in them. And then every single satellite or rocket has a bunch of chips or circuit boards in them. So that’s a huge problem, and that’s way more strategic because obviously 70% of the world’s chips come from Taiwan, most of which is TSMC. And then the other thing is the rare earth minerals like lithium or cobalt are largely Latin American, but the Latin American mines are much, much less developed. That’s a huge challenge as well…

[00:27:54] Patrick: Chris, if we zoom all the way back to the unit here of the mom and pop machine shop, what are the key set of jobs being done by one of those given shops? You mentioned the nature of them. It’s the 60 year old soon to retire making 10 or $12 million revenue per shop or something like this. What are the key components that are inside each of those shops that you want to lift out as core functions or jobs to be done and then start innovating on inside of a Hadrian factory?

[00:28:20] Chris: There’s three big chunks. One is the digital side of manufacturing, which is taking a customer PDF print and doing a bunch of creative geometry work to get that into machine code that tells the machine how to cut the part. That’s one big chunk, and that’s very software automation heavy. The second chunk is running the machine itself, which again is less of a robotics problem. It’s more of a software engineering problem. So what a master machinist does on the control is a lot of manipulating code on the fly as they respond to slight differences in the cutting tools, slight differences in the raw material. That’s a big operations software problem. And then the third layer is general logistics. So you’ve got unpredictable cycle times of each operation in the factory, you’ve got huge variances in how long something takes to inspect from one part to the other. And then you’ve got a lot of customer requirements that are incredibly variable for each purchase order that comes through. And as an example, this is a very simple example, but can create a lot of operational noise if you don’t get it really right at the top end of the funnel is laser marking a part. So producing all these space components and then at some point an engineer’s going to want to test it, often there’s a call out on the print that says, “Hey, engrave this part with a serial number, the purchase order number, or the print revision that the aerospace engineer said, ‘This is my part number.'”

You might think that’s easy, but there are about 10 aerospace known specifications of the depth of the laser engraving, how big or small it has to be, and what the function of that is. In a regular machine shop, you might have a guy running a laser machine that’s staring at a PDF print that might remember the specification. So a lot of it is that documentation of that engineering knowledge and then systemizing it so that the whole thing flows smoothly, yet haven’t got a bunch of random art going on. Even load balancing that is an insane challenge because you might have all these machines set up for making the part, inspecting the part, cleaning the part. But if you get one of those throughput messages wrong, where you’ve got, say, 10 jobs running through a facility at once, but they all happen to hit the quality inspection station at the exact same time, all of a sudden you’ve got a bottleneck and all the jobs are late. Before you tell the customer, “Hey, we can get this in two weeks,” having that load balancing like a data center with foreknowledge of where the capacity bottlenecks might be in three weeks so you can make good judgment calls on what you’re promising versus what you’re delivering is a huge data science and operational excellence challenge…

[00:32:09] Patrick: Josh, how do you prosecute diligence for something like this as an investor. Hearing all that, I’m going to ask more follow up questions in the minute on the unit of the machine and the areas of innovation and the machinists, et cetera. But when you’re facing something like this early on and it is factory one or factory one’s still a glint in your eye, how do you do diligence on someone’s ability or a team’s ability to execute something like this?

[00:32:33] Josh: I’m probably going to get myself in trouble with this. First you make an investment in another company that fails.

[00:32:38] Patrick: Good start.

[00:32:39] Josh: And that’s what we did. We and Founders Fund actually were co investors in a company that did not work. Part of that was narrow focus, part of that was team and structure. There was something proverbially different with Chris that their light shone brighter. As you can hear him talk, not only understanding the macro, but if you have a customer like Brian, Andrew, or Palmer, they want to anodize titanium and aluminum and parts that not only have electric chromatic coatings that strengthen and provide performance, but look really cool. They’re super high demanding, yeah. So Chris’s understanding of the macro to the micro is something that was inspiring, but we were still making a bet without any existence proof of why we were basically going to make a very similar investment as we had before, but this time was different, those dangerous words. And it truly came down to his vision of understanding industry structure, his vision of seeing the technological pieces that could be put together. Notably, he told us why we lost money in our last investment, which was super valuable. So he diligenced our failure to diligence properly our prior investment. And part of that was you don’t want to automate everything.

He’s like, “You don’t want a 100% automation. You need humans in the loop in some of these aspects.” Maybe you want 80/20 or 70/30, but you need people that are there able to very quickly look at the geometry of a part or design, make a human decision, let the computer do it. A lot of it really came down to Chris understanding the macro, the micro of individual parts, the flow, where bottlenecks were. And then I think this is really important, you really have two different cultures. You have a machining culture, which is very blue collar in many cases. It is people working with their hands and really deep narrow specialists. And then you have this coding software culture, which is almost the antithesis of that. It would be good to actually hear from Chris, how do you think about those two people speaking very different languages, sometimes growing up and going to very different schools, actually being teammates and working with each other, because that answer that we got from him was super confidence inspiring.

[00:34:29] Chris: The difficult thing, going back to previous failures in his space, was both in private equity and software engineering trying to automate manufacturing, the previous approaches have been very egotistical in the sense of, “We don’t need any industry knowledge.” Either I’m a guy with a spreadsheet and I know how to do an IRR calculation. Operations doesn’t generate profit, finance does. So the attitude towards machinists or manufacturing people is very downwards looking. I saw the same arrogance in Silicon Valley, which was, “Let’s not try and work with the best in the industry to automate this in the right way.” It’s, “Let’s grab 30 PhDs and don’t hire a machinist until employee number 28 and just try and figure it out ourselves,” which for me is just this very coastal elite looks down on flyover state dynamic. What I recognized was in machining, all of the problems have been solved by people, the knowledge is in a bunch of people’s brains. It’s not like we’re inventing a new algorithm for machining. If we did nothing, but just find all the right answers and get them into software and process, we would win immediately. To do that you have to create a culture where people feel comfortable working with a software engineer and machinist and an operations person all in one conversation and setting the standard that just because you’ve got a maths degree from Yale and this guy didn’t graduate high school, setting that culture so they work collaboratively and there’s no finger pointing or whatever and everyone’s pulling in the same direction is really, really important. This was one of the most important things that I worked on, and it’s a combination of making sure, even really simple things like no matter of whether you’re a machinist or a software engineer, your equity that you get in Hadrian is the same based on your rank. The pay is the same. All this other stuff is super, super, super important.

Really finding the people from industry that want to share their knowledge and want to train people, is an incredibly rare thing. So we’re incredibly lucky to have the 20 or 30 people in industry that actually want to share their knowledge and understand that we’re all pulling in the same direction. And that is a really unique thing. To give you an example of how scary this is, even at the most innovative space companies, to train someone on how to inspect a part is usually this thing of like, “Hey, we’ve got all these amazing people that want to work in manufacturing but I’m on X number of dollars per hour, and I don’t want to share my knowledge because my job is at risk.” Even something as simple as training new entry to the workforce is incredibly hard because of this protectionism. People ask me what the secret sauce is, and I think investors think we invented this new technology and that’s the core of the company. The core of the company is 50 people soon to be 80 and 100 pulling in the same direction. Understanding that what we’re building is a culture of, here’s a problem let’s solve it and no matter where the solution is coming from, implement it and work together. That’s the core of what we’re building which long term is going to be a huge, huge advantage. Because if we get Hadrian right, there’s no reason why we can’t take the same team and go solve tube bending or raw material or whatever it happens to be.

[00:37:14] Patrick: You described this the first time we talked as the PhD arrogance trap, which I really liked as a phrase. Thinking you can just solve every single problem immediately with technology. Interesting to hear about the inner relationship between the two teams or the two modalities. When it comes to the individual machine and the machinist working together inside of a Hadrian factory, again maybe starting to squint a little bit and look out 2, 3, 4, 5 years, what do you think the innovation zones are on the machine side specifically? In what ways will a Hadrian machine be better five years from now than it is today? Because it sounds like there hasn’t really been much innovation on the machines themselves in these mom and pop shops?

[00:37:51] Chris: Actually, I think that’s slightly incorrect. But I would say that we are not really innovating on the machines themselves. And that’s part of the trick here is we are buying everything mostly off the shelf and then doing really tight software integrations to override the core software that lives on these machines to make them run better. But we’re not doing mechatronics and upgrading the machines themselves. Building your own machines while trying to scale a factory is like two impossible tasks. What we’re really doing is going, “Hey, these machines have APIs that control everything about them.” No one’s ever used an API for this machine ever before, and that’s really where the technology curve is honestly. Even down to simple things like, you’re meant to be able to run a machine overnight without it stopping itself. There’s actually 20 or 30 reasons why a machine would stop itself running. A Tool breaks, something goes wrong in the controller, it’s like a literal software bug. A lot of our automation is actually building the robustness into these vendor machines so that they self-correct overnight so we can get the throughput and the efficiency.

One of the reasons why you have a second shift at a machine shop, which is incredibly inefficient, is because someone’s hanging around waiting for the machine to error out and they know how to clear the error and get it going again. Which sounds insane, but that’s honestly 70% to 80% of the problem. It’s hilarious having people from industry where we come back in the morning and the machines run itself overnight and there’s 10 good parts sitting there. And people are like, “Wow, this is amazing.” I’m like, “What do you mean? These machines are designed to run overnight?” And they’re like, “No, well, it almost never happens in reality.” The reason is, because over the last 5 to 10 years, the amount of software that’s in these machines has grown exponentially, but no customer of the machines has ever been able to take advantage of it because, what machinists knows how to write software? What machine shop can afford to pour a software engineer into the problem? Or even if they had a software engineer, have them spent three months of R&D on figuring all this stuff out versus just firefighting operations because they’re trying to deliver for a customer. So that’s more what’s going on than us innovating on the hardware side.

[00:39:44] Patrick: And the innovation, the units of innovation themselves driven by software, is better-cheaper-faster the right way to think about what you hope to accomplish by starting to tune the dials using software?

[00:39:55] Chris: Definitely on the front end of the factory in the digital manufacturing CAD and CAM programming space, 100%. Because you just want to turn a 20 hour process into a 2 hour process. It’s possible. It should be done. We’re chipping away at the marble and will get there. For the factory, I actually think that simplification and robustness are the two most important things, because in manufacturing, complexity and lack of robustness are what drives costs. You’re actually better off having a system that works every single time that’s simple. That gives you two things. One is, there’s less errors so there’s not a bunch of people firefighting. And because it’s simple, you can train many, many more people into that system. Getting rid of a lot of the complexity of making everything truly error proof is a lot of the innovation there, which seems counterintuitive. But in the real world, you want as little errors as humanly possible versus trying to dial up the efficiency on something so high that it breaks one in even every 10 times and all of a sudden you’ve got three or four people standing around figuring out how to solve the problem. That’s really, really what’s important there.

Now, what you get from that is speed. So speed is not necessarily like, cut the part faster. It’s at every handover point, don’t have to go back in the step, go back in the step or have this station hanging around waiting for information because you’ve got errors. So the whole factory speed is optimized by having each of these individual pieces incredibly robust. For the customer layer, they get speed. What’s great about speed is everyone wants it, so we also get pricing power. As we hit the robustness layer, we have margin efficiency growth because people are hitting things every single time cleanly versus running around scrambling like, where’s this bit of paper, where’s this tool? Now on the customer layer because we are reliable and fast, we have enormous pricing power. It’s this interesting dynamic about manufacturing where, if you just focus on robustness and cleanness of the process, you kind of generate margin improvement automatically and therefore you get pricing power because you’re fast and you reliable.

2. Quotes from Seth Klarman Interview – The Transcript and Seth Klarman

2. The impact of rising rates: 

“That is going to test financial institutions who’s been writing derivatives they shouldn’t write, who’s been stepping out to take greater risks in their portfolio because if you can’t make it in bonds, people try to make it somewhere else.”

3. Watch out for anchoring

“After you buy something you paid for, it doesn’t matter. People cling to the idea that at least they should get their money back; maybe there is bad news, and you should sell before it goes lower; maybe put it into something else where you get your money back, but people prefer to make it back where they lost it. People anchor numbers in their heads, and they hold on to them. They have a way of remembering what happened relatively recently. If you recently had a pandemic, you over-worry about the next pandemic even though they don’t happen that often. I was certainly guilty of that after 9/11 myself. It seemed obvious that we’d get hit again, and then we didn’t for a long time.

4. Best business book: 

“We should not expect people to be rational all the time. Daniel Kahneman does a beautiful job in Thinking Fast and Slow. It is in many ways the best business book, the best investing book ever written even though it’s not ostensibly about business or investing because it tells us about ourselves”…

...6. On finding edge: 

“There are lots of ways to develop edge as an investor. One of the ways is deep fundamental knowledge. I have total respect for people who dig incredibly deep in an area where they’re doctors and medical researchers. They study biotechs and that’s formidable. No one should underestimate that power, but that’s not the only kind of inefficiency, as the inefficiency might be informational. Two things happen in markets; right markets are inefficient partly because of human nature, as I mentioned; greed and fear. People get greedy and panic; in some cases, the panic is legitimate. “Oh crap, I leveraged my portfolio, and I’m getting a margin call.” or “I have short-term clients, and they can redeem, and I’m getting redeemed, and I have to sell whether I like it or not.” There are other constraints on investors that also create inefficiencies.

Once in a while, we get a call from someone with one asset in their private equity fund who want to raise the next fund. They want to book a gain on that asset. And so, call it the last asset phenomenon. People literally will sell that more urgently, and maybe they’ll favor getting it done over the exact price they get because they want to raise their next fund and move on. They want to book a game and get paid. We live in an imperfect world, and their clients should probably not love that, but maybe their clients would love it. The manager has a lot of things to balance, so that’s just one little example. When a bond gets downgraded, there’s always an immediate rush to the exits by the investment-grade holders. A bond gets downgraded to junk, say when the bond goes literally from BBB to BB. Many bonds have to get sold; some are probably sold in advance. It’s good to know what a company does, its operations, and its worth. It’s also interesting to know that there’s a very large seller, and the bonds are 20 points lower. With essentially no change in any information, just the rating of a 26 year old at moody’s. So those are the kinds of things that can trigger our interest then we do fundamental work”…

10. On making mistakes:

“Today, there’s not so much mean reversion. Things may not be mean-reverting because of technological disruption, so I think investors have had to raise their game massively in the last several decades, and I’m not done raising it. I probably haven’t raised it as high as it needs to be. It is a great time to be knowledgeable about technology; it was a great time if you could figure out what Amazon was up to. For a value investor, it looked hopelessly risky but for a tech investor, maybe with the right insight into the value of platforms and the value of winner take all business models, that would have been a good thing to have that I didn’t have. I pat myself on the back and say, okay, Seth, you were a schmuck twenty years ago and ten years ago for not figuring it out, but you were smart to figure it out five years ago. That’s all an investor can do; be intellectually honest, be self-critical we’re justified, and keep trying to get better every day. Like Warren Buffett, the best investors study read admit mistakes um always looking to get smarter and wiser because what else can you do as a person.”

3. Capital-Efficient Growth (with Zoom CEO Eric Yuan & Veeva CEO Peter Gassner) – Benjamin Gilbert, David Rosenthal, Eric Yuan, and Peter Gassner

David: Amazing. Eric, could you share your fundraising journey with us?

Eric: Sure. I started the company in 2011. First thing I did, I opened up a Wells Fargo bank account. It’s very easy for me to raise capital that’s why I opened up a bank account. Unfortunately, it took me several months. No VCs wanted to invest in me. Unfortunately, I do not know my brother […] Emergence Capital. Otherwise, life would be much easier. Finally, we targeted some of our friends. It reached $3 million seed funding. That’s how we started.

Here comes […]. I tried to target VC again, again, nobody wanted to invest in us either. We targeted friends and got another $6 million. That’s how we started. It’s very hard.

Ben: Nobody wanted to talk to you at that point because most people assumed video conferencing was either a settled frontier or a race to the bottom. Am I thinking about that right?

Eric: Absolutely right. That’s the thing. Everyone mentioned, Eric, you are crazy. The world has known you to have another video conference solution. Another VC friend even is a great friend, he told me that, Eric, I have a check for you as long as you do something else. I couldn’t say I did not listen. I was very stubborn. Also, he shared to me a story. Once I was told by a big VC, I do not want to mention the name, for sure, you guys do not like them.

He told me that, Eric, I do not think your […] works. Look at Skype, look at Google Hangout, look at Webex, they’re dominating, right? I debated with him a little bit. I failed. I cannot convince him.

On the way back, I told him myself, I’m going to change my Windows screensaver. Back then I was using a Windows machine. I changed the Windows screensaver—you are wrong. For several years.

Ben: Just to make sure I have my facts straight, I believe you raised a $30 million dollar round led by Emergence and then another $100 million dollar round after that. Similar to Peter, you did not dip into any of that $130 million to build the business. Is that correct?

Eric: For me, actually, I offered $30 million from Emergence Capital. I think we are on the right track. To be honest, actually, we don’t even need to raise a Series D because at the time, with that $30 million, I think the company was completely different again.

David: One thing we wanted to ask is a difference between your two companies. Peter, obviously, once you got to cash flow profitability, which was immediately, basically you never raised another round. Eric, you did make the decision to raise some more capital even after you were generating cash. Peter, you were on Eric’s board when that process happened? Why did you make that decision?

Peter: For Veeva, I didn’t raise more just because I thought I didn’t need it. It’s just that simple. As far as for Eric, when you’re on the board, that’s really Eric’s decision.

Eric: As I mentioned earlier, I offered to raise $30 million from Emergence Capital. At that time, seriously, they had no plan whatsoever to raise another round of capital. The reason why we still wouldn’t move forward to have a Series D is because I thought the economy would go down quite dramatically.

David: This was 2017?

Eric: Sixteen, ’17 timeframe. I was completely wrong…

…Ben: As we were preparing for this interview, our first thought was, if we just had one of you up here and we were interviewing you about capital efficiency, it’d be easy to chalk it up to business model and cash flow cycle. Multimillion-dollar contracts upfront in the case of Veeva, or in Zoom, customers flocking with their credit cards for a self-serve experience. These are two completely different models.

I think one of the things that it illustrated to David and I is capital efficiency is a mindset and culture thing more than a business model thing. I’m curious to hear both of your reactions to that, but also, what are the things that enabled you uniquely, more so than 99% of startups to be so capital efficient?

Peter: I can take that one. I guess I’ve seen a little bit of Zoom and a little bit of Veeva. I would say, probably, it starts with a mindset. Just run a profitable lemonade stand. From my point of view, for me, there’s safety in that. Cash generating business is always going to be valuable to somebody. At some point, a business that’s not cash generating is going to be valuable to nobody. There’s security in the long term. It starts with the mindset. I think Eric shared that.

Then you have to have product excellence, too. That’s something I think Eric and I share. We’re both product people. I think also, we both worked really hard. We work really hard now, especially Eric. Probably in the first five years, I worked really hard. You didn’t see me working really hard, but I saw you working really hard. We worked really hard, we worked really focused. Anything that wasn’t related to the product or the customer was just BS, then just don’t do it.

The first five years, I was not at a conference like this, for example. I was just maniacally focused, and then the market really helps too. That’s something you just have to get lucky on. It was the right timing for Veeva, it was the right timing for Zoom. Maybe if you started Zoom five years earlier or five years later, it would have been hard.

Product excellence, real focus, mindset, and then you have to have some luck in your market. I’m sure there are some things that I could have tried to do or Eric could have tried to do. We might have picked a bad market and then it just wouldn’t work.

We’re outliers and so is Eric. You have to pick something that most people think is going to fail to be an outlier. Otherwise, by definition, you’re picking something that most people think is going to work. A lot of people are picking it, therefore, you’re not an outlier.

Just like Eric, all VCs have any kind of note except for Emergence turned us down. Ours was really simple. Vertical specific software, that’s a small market and it doesn’t work. That’s what they would say. I was encouraged by that because I thought, well, it has an opportunity to be really good because it’s something non-obvious.

David: One thing that I want to double click on that we were talking about beforehand. Yes, you need to be non-obvious, to have a chance of a great outlier outcome, but you also need to be correct. What you both did was not, hey, I’m going to pick some random idea that other people think is crazy.

I know Veeva, as one of your core values, clear and correct target markets that you have written on the wall. What did each of you do ahead of time that led you to really genuinely believe, yes, the world thinks this is crazy, but I really think this is going to work?

Peter: I’ll go first, this is really easy. I talked to three or four potential customers for our first product. They all said, we don’t need that. That’s not interesting. It’s not a good thing to do. But I wasn’t listening to that. I was listening, are they emotionally attached to where they’re getting their product now?

Are they emotionally attached to those people? Do I feel like they’re getting value out of that thing? I could tell in their responses that they weren’t attached and they weren’t getting value. All four customers said it was a bad idea. They’re all customers now, though.

Ben: Let me understand the Peter formula to build a business. Ask a customer if they want your product, they say no. You dig deeper and say, what are you using now? And they say, oh, yeah, because I have a solution for this. But they just don’t love it, so you build for them anyway on the bet that you can be better than their current.

Peter: Yeah, you have to listen to what they feel, not what they say. They would say, yes, we’re very happy with the solution. But then you dig, oh, tell me more. Why is that? What is it that you get out of it? It’s like, uhm, uh, and that’s when you know.

David: That sounds like the video conferencing market circa about 2015, 2016.

Eric: For me, it’s very straightforward. Of course, I was an original founding team member of Webex. Two years before I started the company, I knew that Webex really sucks.

David: Did you try to tell Cisco that?

Eric: I told my team. I do not dare to tell others. Anyway, Skype is also not reliable. Google has done no work. Every day, I spent a lot of time talking to every customer. I know if I can build a better solution, I think at least I can survive.

I never thought that everybody was going to standardize on the Zoom platform. At least I know for sure, if customers do not like something, if you can do something better, you have a chance.

Ben: Eric, did you think from the outset that you were trying to build Zoom as a big company, or did you just think that you wanted to build a profitable company to survive and then you would sort of see where it went from there?

Eric: I think two things. First of all, at that time, my passion was very straightforward because Webex is more like my baby. I feel like I worked so hard for so many years, I let a customer down. I really wanted to fix that problem, but Cisco doesn’t want me to start over. I had no choice but to leave to build Zoom. This is the number one reason.

After I started a company, I realized, wow, it’s so hard to raise capital. By the way, the money that the VC gives to you, don’t think that’s the money. That’s trust. Every dollar matters. That’s why every day I was thinking about how to survive, how to survive, how to survive. Even today, seriously. I still think about, I wake up at night, how to survive?…

…David: Can you also tell us the story of lending your first big customer, which I believe is probably the deal that really made the business?

Peter: There was a set. There was the first guy who just peeked at his IT team and then worked up to the next size deal and the next size deal. It was always a step function. The first multimillion-dollar annual deals were a big customer of Pfizer. It was just hand-to-hand combat. There was a partner at the time. Actually, salesforce.com at the time said, I’ll send a note that Veeva will never win this deal. I replied back, I said, we will win this deal.

Ben: They sent it to you during the Bake Off?

Peter: Yeah, because they didn’t want to even come into the meeting with us. They were like, oh, we’re going to go with this other system integrator or something like that. I sent an email back and said, we will win this deal. Why? Because we have better people that will work harder. We’re Pfizer’s only shot at greatness and I think they want to shoot for greatness.

I remember there was this big meeting with Pfizer. There was a guy in there in charge of it. We had a certain amount of people in the meeting and the guy stood up for Pfizer. He said, we have more people in this meeting room than you have in your company. Why should we buy anything from you? I just said the same thing. We’re your only shot. We’re going to make something great and we have the best people. It seems simple to me. Then we got lucky.

I remember after winning it, thinking, oh my God, now what? Now, how are we going to make them successful? The whole company got a bonus when that customer was live and happy, which didn’t have a formulaic metric. It was based on interviews.

Ben: Did you use the invoice from that customer to then go fund product development?

Peter: Yeah. I thought, oh, we’ve just raised a $3 million round of capital. It didn’t cost us any dilution. The check came in. That’s exactly what happened…

…David: Eric, for you. I’m curious, maybe you can talk to us both in the beginning days and then also now at Zoom, how do you think about pricing and account strategy?

Eric: Our case is a little bit different. Ideally, when you start a SaaS company, either focus on vertical market or focus on departments. That’s probably the best business model. Unfortunately, we started from building a horizontal collaboration solution. It’s really hard because a lot of other competitors are already there.

David: Including free competitors.

Eric: Exactly, and a lot of free solutions. Our strategy is more like opening up a new restaurant business. You have better service, a better price, and better food. That’s pretty much it, even today.

I want to make sure our products are better than our competitors. I make sure when it comes to pricing, also better. I also make sure to offer better service. You look at any time, our product is always, always a better price across the board for any product compared to any competitors.

Ben: Life is about trade-offs. If you’re telling a customer, oh, we’re better, faster, and cheaper, what has to give? Is it something organizationally?

Eric: Efficiency. Let’s say customers, they are probably going to spend a lot of money on marketing. What can we do to leverage the network effects? If they hire 100 sales reps, what can we do to have 50 sales reps who can deliver the same value? That’s why it’s very important to have internal efficiency.

David: Which is so funny. That efficiency translates to capital efficiency, which translates to operational margins, which translates to cash flow, which is the whole point.

Eric: Totally. Yeah, it gives you more flexibility.

Peter: I would say the key also is just product excellence. That comes from the core set of engineers you hired, I think. You were especially very focused in the early days, right?

Eric: Totally.

Peter: You were not thinking about something else. You were thinking about video conferencing. I would say that’s why I got to know Eric. I got to know Eric, I thought, that’s a pretty focused guy and that his product is good. And then I tried out his product. I’m like, oh, this is really good. I want to join his board. I think that product excellence can make you more efficient, your sales cycles more efficient. Everything is better. Your product was twice as good as Webex, right?

Eric: No, 10 times better.

Peter: Ten times better? I guess my point is, if your product was only 20% better, it wouldn’t have been enough. It wouldn’t have mattered.

Eric: You’re so right. That’s why I always like the restaurant analogy. You’re buying a brand new restaurant. If the food doesn’t work, even for free, you don’t know if I’m still going to buy it anymore.

Again, back to Peter’s point. It’s extremely important. Everything starts from one thing, product excellence as a foundation. You can optimize a lot of things. If a product does not work, forget everything else. Just double down, triple down on the product. That’s the number one thing. Peter’s right.

4. 20 rules for investing in Vietnam – Michael Fritzell

Vietnam is following the East Asian playbook of manufacturing export-led growth – just like Japan, South Korea, Taiwan and China before it.

After the Vietnam war ended in 1975, formerly capitalist South Vietnam was taken over by the Communist Party of Vietnam and the country was unified.

The first measure taken by the communists was to nationalise and centralise the entire economy. Around 800,000 Vietnamese fled the country after the war, including Andy’s family.

It only took three years before war broke out again – this time against Cambodia’s Khmer Rouge, led by dictator Pol Pot. That war continued until the late 1980s. So Vietnam was almost in a constant state of war for almost half a century.

By the late 1980s, the country was in disarray. And it was becoming clear that the planned economy was not functioning properly.

The Communist Party introduced a new reform program called Doi Moi to create a “socialist-oriented market economy”. One of the first Doi Moi policies was to permit foreign investment to modernise the economy.

Today, Vietnam is buzzing with activity. The country has more free trade agreements than any other country in Southeast Asia. It’s become the default destination for companies wanting to diversify their manufacturing supply chains out of China. Vietnam is a perfect choice for manufacturing – in close proximity to key component suppliers in Asia and along the key trade route between Asia and the West.

Vietnam’s success is most evident in the country’s exports, which have risen the fastest of any country in Southeast Asia.

This export growth is also showing up in the country’s urbanisation, with young Vietnamese moving to factories to improve their livelihoods. Vietnam’s urbanisation rate is still only 38%, compared to China’s 70% and Japan’s 92%.

Vietnam’s potential is massive. Its GDP per capita is only US$2,800/year, compared to Thailand’s US$7,200 and China’s US$10,500. Manufacturing wages remain competitive, even against countries with worse infrastructure such as the Philippines and Indonesia.

Out of a total population of 97 million, Vietnam now has a middle class of 30 million people. And it’s rising rapidly. Many of those individuals are starting to buy properties, cars, home appliances, electronics and more…

…In addition, Vietnam’s demographics are excellent, with two-thirds of the population below 35 years of age. Vietnam’s working-age population is going to grow for another 15-20 years.

The country is also highly educated. Vietnam’s PISA scores are higher than the equivalent scores in the United States, the United Kingdom and even South Korea, even though its GDP per capita is minuscule in comparison.

5. Tobi Lutke – Embrace the Unexpected – Patrick O’Shaughnessy and Tobi Lutke

[00:02:44] Patrick: Tobi, it is almost exactly two years to the day since we last did this. It was early May in 2020, there was still a ton of uncertainty related to COVID. I guess there still is some extent today, and the world in Shopify and lots of things have changed a tremendous amount. I know certain things haven’t changed too. I’ve been really excited to do an updated version of our conversation and we’ll bounce all over the place, but before we hit go here, we’re having this fascinating conversation around the concept of infrastructure, generally speaking. I think it started with this idea that we might be about to come on stream to a lot of good, useful, new, history books written by people who are really there to see this stuff get built in the digital world. I’d love you to sum up that idea of what your interest is in infrastructure and the way that history is written. Even things like payback on infrastructure and the ways in which we might underestimate it. I think this is a great tone setter for what we’re going to be talking about today.

[00:03:38] Tobi: I’m thrilled to be back. Thanks for having me and those were quite some two years and a lot has happened. I think people are just underestimating the value to society of infrastructure by some incredible factor, because you see these kind of things like the interstate system. How do you imagine this thing would’ve looked if these things wouldn’t have been built? I’m not an atoms person, I’m more like a bytes person. I find that infrastructure, especially with software has this incredibly unreasonable leverage and unreasonable payback period and often we have these conversations about what’s the state of planet earth. What are things truly like? Are things getting better? Are things getting worse? There’s a lot of people sharing excellent opinions on these things.There’s a website. I hope I say this right. I think what happened in 1971, it might be a different year, but something around that time, there’s a collection of charts where once the right year comes around, a lot of numbers sort of disconnect from their previous correlations. I have no idea what happened in that year, but as a student of history and especially of digital history, increasingly I’m thinking about a very, very tangible thing that happened is that just simply most of the value creation in the world has slipped out of the things that is represented in GDPs, where a whole bunch of people built the upper net around this time then we got modern operating systems.

We’ve built a lot of silicon based computers in the nineties, but none of this was reflected anywhere. Dot com happened and everyone tried on the idea like that this tech could be very big and then found some of the ground truth to be wanting, but really sort of early mid 2000s, web 2.0 I think we call it or, at least coinciding with the emergence of that term, I think was the moment where the world of technology said, Hey, we actually know exactly how to provide value for everyone. We know exactly how to deliver services and goods and things over the internet.And by the way, there’s a lot of tweaks on the intuitions that people develop in the physical world. Physical world is very rivalrous. If you build a bridge in one place, you probably don’t build a bridge somewhere else. At some point in the world of atoms, things become zero sum, limited amount of attention at the very least and then resources as well. The digital word is different. Basically you have Turing machines, you load something on a silicon chip into memory, and then you apply electricity and you get this thing. Infrastructure and internet. I mean, I like to believe Shopify is infrastructure, but there’s public domain libraries. Just pick one, you know, SQLite. It’s like a library, probably none of your listeners have heard about, but you have probably like something to the tune of a hundred SQLite databases on your phone right now.

It’s just file format of the world basically and increasingly runs more and more and more parts on servers as well. It’s just this brilliant open public domain piece that was written by a team and great leadership, incredible conviction, but it’s not software, it’s infrastructure. And now people are using it every day for different things. And no one has to decide if we use SQLite, that means someone else can also have SQLite because all of us just add electricity. What that stores then is like an unbelievable compounding value.Again, in a lot of the ways we look at the world through GDP and other things, it’s impossible to capture the value that’s created here. Everytime someone updates something on GitHub, theoretically, it can be copied infinite amounts of times. These are not new ideas I’m sharing here, obviously. In a way, we’ve talked about this zero marginal cost of software and of course it powers a lot of value in a lot of software companies. I’m starting to believe that we haven’t fully set this idea to its logical conclusion. How much of a change will this cause over the next while?…

[00:09:44] Patrick: Yeah. It’s amazing how much prevailing market conditions and prices can impact people’s mood. We’ll talk about that a little bit later, sticking with infrastructure though. I wonder if you’ve developed any principles or principle thinking around what makes for better infrastructure or valuable infrastructure to build. And I asked this question from a place of Shopify zone history. When we last talked a lot of the things that if you go to Shopify’s website and see what you can do as a merchant didn’t even exist two years ago. So you’ve obviously had to make choices. We’re going to build this. We’re going to not build this. What do you think about in terms of just base level principles that help you with decision making, for what kind of infrastructure to build that will have the most leverage in the world?

[00:10:23] Tobi: There are some guiding principles in Shopify product that really help us make these decisions. For instance, there’s a very basic sentence, which actually does a lot of work within the company. “Shopify wants to make the important easy and everything else possible.” Probably everyone who listens to this has bought from Shopify stores. You might have not known that it was a Shopify store because they look very, very different. This is powered by a template language I wrote forever ago called Liquid. Basically the merchants can open a text editor and just make their website look however they want, or buy a theme from someone. That’s infrastructure in a way, because here’s something I learned about infrastructure, which might sound very abstract, but maybe it’s useful. If you imagine an hourglass. An hourglass has sort of a narrow waist at some point, maybe a comic book version of an hour glass is like two triangles, inverted pointing at each other. Great infrastructure can be done when you can define what this sort of narrow waist is between the triangles. For instance, let’s use Stripe because it makes this point I think quite well. There’s one triangle on top, which is the internet, and all the engineers, and all the developers. They have a set of desires. They want to accomplish tasks, which involve movement of money. And then there’s a bottom triangle, which is like a world of COBOL code in banks. There’s a lot going on. And a lot of things you need to know, but if you manage to create a thin waist in this case, in the form of an API, now you have an agreement in the middle. This almost acts as a protocol. Here’s the fantastic thing. Once this protocol exists, it actually allows the two triangles to be replaced over time. In the case of something like Shopify, Liquid is again this templating language. People can write it. If you wrote some in 2005, the first time the Shopify went into Beta, it will still work.

Shopify is the Ship of Theseus. Nothing about Shopify is the same. The Liquid part has been rewritten many, many times, everything changed about the triangle below. Everything changed about the triangle above. Most people don’t actually even write Liquid. They actually just use drag and drop editor, which we built on top, which then writes the Liquid for you. The amazing thing is, again, once the protocol has been defined, once the demarcation line has been created, once the narrow risk is defined, then really incredible things can happen because as long as the thing keeps working, that’s in the middle, you can evolve all the pieces. And I think that’s a really, really, really powerful idea for product creation. People encounter this. If you’ve ever queried a database again, you use sequel and that’s just a thin waist system. It’s an agreed upon system, which gets you the data and as long as you keep it simple, if you send something to Microsoft SQL Server or SQLite, you’ll get the answer assuming they have the data. So that idea unlocks, I think, the right approach to internet infrastructure creation, because once these protocols have been defined, teams can go and saying, okay, these sort of made this work with duct tape and regular expressions in terms of Liquid, but let’s build this up properly, scale it out, make it so that people can use this from now on forever.

[00:13:16] Patrick: So someone once explained it to me as the equivalent of an outlet in your wall, that’s become standard that anything you plug into it like electricity flows through it very reliably and in a way that’s a standard or a protocol or something that is sitting right next to us all day every day, that without it, who knows what would’ve been invented. I’m also struck by the examples being the choke points, if you will, the most basic natural things that humans have been doing forever, like Stripe people in paying stuff, Twilio, communicating, Shopify, selling, buying. How much do you think just that is the guide for good infrastructure just looking for the longest lasting perennial human use cases and then starting from there? Maybe they’ve all been mined. I’m curious how much room you think there is left to go talking, paying, some of these things I’ve listed are like the major human motions. But I think my sense from you is that we’re still pretty early in digital infrastructure building. So how do you think about that?

[00:14:10] Tobi: Some parts are and some aren’t. It’s sometimes very, very surprising, which ones aren’t. Other things that are very, very long lasting is ownership. People like owning things. We like to acquire assets. We like to have title to them. This is not just the utilitarian value. This is also for starters and for all sorts of reasons that are uniquely human and we didn’t have good infrastructure for this. We probably still have not great infrastructure for this. It’s just barely becoming possible to own things on the internet. I think there’s lots of white space.I do fully agree though that one of the best things you can spend some time thinking about is what are things that people have been doing for a very long time. If I’ve been doing something for a very long time, like making something on the internet that taps into this emotion or into this sense for community or whatever that is you identified. I think you can analyze almost every major success story in the digital space right now and you really see a digital version of something that people have already been doing, which tells you how early it is. They’re pre the emergence of new things. Maybe the video game world is sort of there, but I think we are spending our time on computers, on the internet, very, very different right now than people will in 20 years from now. So there’s plenty of opportunity to be part of being pioneers.

[00:15:21] Patrick: So when you think about this applied specifically to Shopify and let’s just call it like a funnel of ideas for marginal infrastructure that could get built, or I guess, improvements to existing pieces of infrastructure. How does that funnel work? How are ideas fed into the top of it? What are the layers of decision making that ultimately lead to something getting green lit? What is the way that that product funnel works, given the amount of white space that might exist?

[00:15:47] Tobi: We were talking about last time, the sort of difference over the last two years. I think that we’ve gotten a lot better at this and spent a lot of time thinking about this because frankly here’s an experience I’ve had. When the COVID pandemic and the stay at home orders happened and we all did that two years ago. It was very clear that this is going to be a very, very, very white knuckle affair for everyone. There was untold stories there still, like, I mean, the world almost ran out of service in a very significant way, but probably most people don’t quite understand how close of a call that was. If COVID would’ve happened like two years before, I’m not sure we could have pulled off, not we as in Shopify, but the internet. The Cloud hosting providers, they’re like very close to food rationing. A lot happened during this time. I pulled the entire list of things that everyone was working on and basically recalibrated everything from like, does this help right now? I’m a very vocal proponent of long term thinking. People should make decisions based on the decision they assume the company 10 years from now wishes they would’ve done, but sometimes you got to just look at what’s there and be very, very practical. So I went through. In the end, I think I stopped about 60% of what we were working on. None of the things we were working on was because people made incorrect choices. Sometimes just maybe not quite applying the larger frame of reference.

For instance, there’s a lot of projects to customize Shopify to be better for brochures and so on. I understand the pitch of like that’s so and so big market and if you just get 1%, this is not my favorite form of communication, but I recognize that it happens. So a lot of the projects have been going on we’re trying to drag Shopify into adjacencies. I’m a very firm believer that you have to pick your place and then try to be ideal for that. And actually maybe to a certain point actually discourage people to pull your product into areas it’s not meant for, because Shopify should be the best piece of software everyone uses who’s in our space. Because like cheap, and fast, and delightful, and is an integration point, and simplifies the business, and magically anticipates the next step, and has something, a product, good service for you that can just help you do your thing. Shopify wants to be the mushroom to Mario or the fire flower to Mario, or just give you powers that are awesome. Moving it in all these adjacencies increases the TAM, but it stratifies it into concentric circles. For some people it’s going to be ideal in this way, but for many people it will be just never quite there. And I think that can actually have some really negative effects for feedback and all these kind things on companies.

Anyway, from this, we learn we need to have a really good mechanism by which we get the best of what we have. Shopify is very bottoms up. People can write proposals for every opportunity they see that goes into a system called GSD, which stands for get shit done. Then there’s these phases there’s proposal phase, prototype phase, build phase, and a releasing phase, and this system allows everyone in the company to see everything that’s going on. This entire plan once a year I write product themes for a company, things that we cause to make true over the year. And then they sort of decompose into different projects. Then as this proposal is submitted for transition to the build phase or to prototype phase, and then we can have great conversations about, is this a not yet? Is this a hell yes? Where does this go in a priority stack? And I think building this out has been incredibly clarifying and very, very good for the company. So a lot of the work I think over the last two years has been to get companies just really, really, really aligned on their missions. Companies can get very, very distracted in a lot of ways when they allow themselves to do things that aren’t the mission. This is especially true in a world of product. Again, if you follow a moving into adjacencies, I don’t think you will have a world class product in your adjacencies. You’re not out competing someone’s main mission with your side quest…

[00:24:22] Patrick: People are probably less familiar with that example you ended on, Shopify fulfillment network. I would love just to take that as a microcosm of these ideas and maybe explain literally what it is to people. But I’m especially interested in its evolution. Why, obviously you were incredibly good at purely digital infrastructure. And one of the things that’s interesting that’s happened in COVID is forced the digital and the physical to smash together out of necessity, as you pointed out, thank God for the internet during COVID, and pushed everyone into this intersection unless often atoms or bits only. Maybe start by saying, what is Shopify network today? And then really, I’d love to hear on how it evolved and how it began, because I think it would be a great way to get into your company in your head about this kind of decision making and where to go next.

[00:25:09] Tobi: I’m on WhatsApp threads with probably 100 merchants. And from all backgrounds, I just talk to people and then I upgrade us into a chat. And then we talk about what works, and what doesn’t. And very quickly, this usually becomes talk about the business rather than the software, because the software hopefully works really well. But that’s actually even more helpful because it just gives you a sense for where do things get really complicated? Our observation with Shopify has always been that the journey is uphill. It’s not easy. Shopify never claims it is. Entrepreneurship is fundamentally a little bit unreasonable. There’s wonderful quotes, not by me, where people point out that you end up spending 100 hours a week working for yourself so you don’t have to work 40 hours for someone else. Often this doesn’t make sense, but again, for some people it’s super important. And frankly, for our economies, it’s really important that people do this because most people in the world are employed by small and medium businesses. There’s about five and a half million people employed by the millions of merchants on Shopify. And that’s very, very meaningful. We talk with them. What we found is it’s an uphill journey, which is okay. Everyone’s willing to do this because it’s very gritty people who embark. But if it becomes a technical climb, it filters out a lot of people.

A lot of people just opt out of the journey, basically just forgo future growth at a point where things become very, very obscure. This actually started really early. Once upon a time, for instance, actually one example was just getting a payment gateway. I know this sounds crazy that the internet was ever like this. But when Shopify started and saw a lot of parts of the internet, it was very hard to get a payment gateway. That’s trivial now because it’s built in, you just get one. So we build up the infrastructure, us and our partners to just underwrite people. And then this particular technical climb disappears. It becomes just a slope, which again, everyone will continue on. You actually have more entrepreneurship because some obstacle like this was overcome. Think about the importance of tooling infrastructure and also UX here. There are significantly more people employed today because of good UX and not getting people to be stuck and integrating more. I think this is really overlooked part of the effects of this type of friction. This is really how Shopify thinks about what we do next. People have lots of problems accessing capital from banks. Banks have in charter that the point of why they get these privileges, especially retail banks, which they have, is so that they lend money to small businesses, because that’s, again, a huge return on investment for society if that happens. However, banks do not want to do this anymore. You have to give up. And some point realistically, that’s how it should work. But in reality, they want to lend money to companies that have huge revenue, it’s lower risk. It makes sense, but that means they disappeared from playing an important infrastructure role in society. So then we have Shopify capital, because people are willing to be underwritten and for advances, and again, their business can grow significantly only even there’s capital available to grow business. We are going through all the obstacles.

The one that just is a slam dunk thing is it depends on your product somewhat, but at some point, you really have to have a plan for how to get to at least two day, ideally, overnight delivery for products you have. In the past, it was an experience unlike anything else entrepreneurs have done to this point. When they decided to go into a new channel, like sell on Facebook, on Meta or Instagram, that was a click of an app which they added. And when they did that, that’s how people are used to growing their business. Getting logistics set up is work with whatever factory and contact manufacturer you have, figure out freight across the Atlantic and Pacific. You then have to find warehouses, it is a completely different world, which involves a lot of different people to talk to and complexities. It just felt very obviously in scope for a long time, that at some point we have to solve this. In fact, I started talking with the board of directors and they wisely told me that this was too early, over 10 years ago, wanting to go into this direction. I think this is important to say. We are doing this not because we want to be in the logistics space, we rather actually don’t want to be going into the logistics space. Although it is wonderful and fascinating, and there’s lots we can actually bring given our unique experience about processes and digitalization, technology, and digital infrastructure and whatnot. But integrating end-to-end is one of the goals we have. We would like to get to the point where running a sizable retail business could, if you choose, be treated as passive income. We want to automate as many parts of it as possible so that you and your team can focus on product creation, which is the most valuable thing you can be doing. Doing undifferentiated work, figuring out where you have packages, to me that is the digital system just should really know where packages are. Otherwise, what the hell is going on? That’s not differentiated work.

Now, we found that the more entrepreneurs end up spending time on their product, the better the products get, and this is one of the wonderful things about the direct to consumer world that emerged in the last few years that there’s much more alignment between the people making the products and the people getting them. And they’re happy to send feedback. And there’s no reductionist channel and merchandising team in the middle that optimizes your products for being easy to stack or just a higher profit margin so you can compete against other products around it in the eye high shelf space in the supermarkets. Those are all influences on products that don’t lead to better products. And I think this is actually at the root of a lot of the criticism about disposable consumerism that I think is being leveled. It’s not because people love stuff. It’s because people hate the stuff they get. We are starting some of the processes and helping getting people to have this direct relationship, which just leads to actual Allbirds, like wonderful products like this, which are clearly just built with feedback from the people who wear them and want to recommend them. I think that works better for everyone and it’s what we want to see more of.

[00:31:03] Patrick: With something like this in particular, thinking back to your point about, you got to be careful about which adjacencies you get dragged into. Obviously, logistics is firmly in the vertical of core muscle movements or something, whatever you want to call it for a merchant that’s selling online. They have to get their stuff to places. What lessons have you learned entering into a much more atoms-driven world in terms of what good product means? What is a good fulfillment network? I wouldn’t know how to answer that question. Obviously, there’s the 800 pound gorilla and Amazon that proves you can build incredible logistics networks over time. I mean, it’s just a very different kind of calculus than a great new piece of software, which I don’t think anyone would say Amazon builds great software. They seem to build great infrastructure. What have you learned about that? Is it radically different than what makes you good at software? Or is it a different set of skills required than what makes you good at software to be excellent at fulfillment and logistics?

[00:31:59] Tobi: Yeah, I think so. We tend to talk a lot about intuition because intuition is also one of those underestimated things. Intuition is actually all of your life knowledge channeled quickly. I always recommend people to actually actively build their intuition for kinds of problems they want to solve in their career. There’s this uncanny thing. People were just incredible, effective, and so on. They can look at an architectural drawing and instantly tell you if it’s good or not. And then they need to think maybe 10 minutes to figure out what the problem is. But something pinged their brain about maybe call it weak signal detection like, “There’s something wrong here.”And I think this is the way intuition can be really helpful, but you have to understand that it’s task-based. Intuition built in world of bytes is not good intuition in your world of atoms. Actually, you almost want to get away from having the people who have that kind of intuition make choices. And the other thing, sometimes the bytes people end up being the most useful people in the meetings because, of course, everyone with industry experience will understand how things are. And a lot of engineers have a really good ability to think from first principles and just figure out that’s what it is, but what ought it to be? How could this all work together? And then you don’t just pivot to that. You figure out from now on, every step we do, everything we implement, how can we make it so that we can get closer to the ideal eventually? That’s a humility that’s really, really important. What does good look like? I mean, good looks like if we can put on a website that this thing will be with you tomorrow and then it does, that’s good.

At some point, this crunches together to SLAs. It becomes quantifiable in this way. And you’re right. Another thing you can do is also look at what Amazon build. And that’s also very, very good. Shopify’s relationship with Amazon, the media is trying to make this very zero sum. We treat them as a very worthy rival. Sometimes you ask or say what you can learn from them? And sometimes you ask what you can do better from them. And I hope they treat us the same as well. But again, and in those circumstances, I’ll be thinking about how to capture pieces of pies from our competitors, actually ever. Positive sum thinking is so valuable because it’s amazing how often people are trying to compete for pieces of pies rather than just grow markets. Everything about the Shopify journey has convinced me it really doesn’t pay to really have market analysis. Well known venture capitalists passed on Shopify in 2008, partly because there was only 40,000 online stores and that was not a big enough market for the investment. And I’m still disappointed with that because I realized, especially venture capitalists should not make this particular category mistake. If it’s common there, it’s clearly common everywhere.

[00:34:36] Patrick: I love this idea that if you bring this person into the atoms conversation, their intuition may just be wrong. In what ways is it most commonly wrong?

[00:34:45] Tobi: I mean, change management for software is deploy. Change management of people is a project that’s going to take you a while. The cost to switch is significantly higher. There really is a long itinerary of things that are wrong. It’s useful, but it’s useful as an input, not useful as a, “Let’s do that thing.” This goes beyond engineers, of course. Even UX has been really interesting because for instance, we’re designing UX for robotics. You scan an item, it goes onto a Chuck is what the robots are called, and the Chuck does the heavy lifting of moving it around. Just let the associates do the things that they uniquely can do well, and let the robots do the stuff that they don’t actually like doing. That’s the way we build our robotics, but this requires a very interesting human interaction design that ought to not wind up annoying after a while. And I think that’s really important. And designing interfaces that people are using every minute is different from software that people sign up once and then process some orders in every day. People that just have to recalibrate. I think that’s also makes our work really fun.

6. The Market Has No Memory. Should We? – Frederik Gieschen

In The importance of forgetting, Lauren Gravitz highlights research into people suffering from “severely deficient autobiographical memory (SDAM)” – people who are “unable to vividly recall specific events in their lives.” Interestingly, the researchers found that people with SDAM did well when presented with tasks that required abstract thinking. They were not constrained by a lifetime of episodic memory.

On the other end of the spectrum, people with “highly superior autobiographical memory (HSAM)” have an exceptional memory of minutiae, such as the clothing they were on any given day. However, “these individuals tend not to be particularly accomplished and seem to have an increased tendency for obsessiveness,” perhaps because they are unable to “extract themselves from specific instances.” The strength of their memories became a mental cage trapping them in the past.

“Why do we have memory at all? As humans, we entertain this fantasy that it’s important to have autobiographical details,” Oliver Hardt, a cognitive psychologist studying the neurobiology of memory at McGill University in Montreal, Canada, says. “And that’s probably completely wrong. Memory, first and foremost, is there to serve an adaptive purpose. It endows us with knowledge about the world, and then updates that knowledge.”

Forgetting enables us as individuals, and as a species, to move forwards.” Lauren Gravitz, The importance of forgetting

7. Neanderthal gene probably caused up to a million Covid deaths – Joe Pinkstone

A single Neanderthal gene found in one in six Britons is likely to blame for up to a million Covid deaths, according to an Oxford academic.

The LZTFL1 gene is a Neanderthal gene found on chromosome three and has been previously shown to double a person’s risk of severe disease and death.

But before now there had never been an estimated figure for how many lives were lost to this single piece of genetic code.

Roughly 15 per cent of Europeans have the Neanderthal form of the gene, compared to about 60 per cent of South Asians.

Dr James Davies of the University of Oxford, a genomic expert and ICU doctor who worked on the Covid wards during the pandemic, discovered the innocuous gene’s lethal role last year after creating a brand new cutting-edge way of looking at DNA in exceptional detail.

The method allowed him to identify LZTFL1 as the culpable gene increasing mortality, whereas previous methods had failed to narrow it down beyond 28 different genes.

Speaking at the Cheltenham Science Festival, Dr Davies said: “We used the technique and it identified a virtually understudied gene called LZTFL1 and at the time that this had not been linked to infection at all.

“It’s a single letter difference out of three billion. This tiny section of DNA doubles your risk of dying from Covid.

“It’s position 45,818,159 on chromosome three, and it’s a single change. If you’ve got a G at that site, it’s low risk. And if you have an A at that site it is high risk.”

His team believe that the Neanderthal gene changes how a cell behaves when the SARS-CoV-2 virus binds to the ACE2 receptor on a human cell.

In most people, this leads to the cell then changing shape and becoming less specialised and less prone to infection, stymying the progression of the infection.

“What this high risk variant does is it creates a new signal that tells that gene to stay on for slightly too long in response to infection,” Prof Davies said.

“And so they stay in this state where they’re highly specialised, and they’re prone to infection for longer.”

The number of deaths globally from this nefarious genetic variant “is in the hundreds of thousands to a million,” he told the audience.

Dr Davies and his colleague from Oxford Brookes University, Dr Simon Underdown, a biological anthropologist, also revealed that the Neanderthal gene first infiltrated humans 60,000 years ago after one romantic liaison and interspecies tryst between a human and a neanderthal. A solitary coupling event across species lines saw the deadly Covid gene jump from our now-extinct cousin species into us.

“If this dinner date between the human and the Neanderthal had gone wrong, we would have had a much better time in Covid, we would have had hundreds of thousands less deaths,” said Prof Davies.

“The reason that we know that is that it’s inherited as this block with 28 single letter changes, and you can track that all the way back and it has to be a single event. It’s just so unlikely that you get all 28 changes at the same time and in the same block.”


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Salesforce, Shopify, TSMC, Veeva Systems, and Zoom Video Communications. Holdings are subject to change at any time.

What We’re Reading (Week Ending 19 June 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 19 June 2022:

1. The Google engineer who thinks the company’s AI has come to life – Nitasha Tiku

Google engineer Blake Lemoine opened his laptop to the interface for LaMDA, Google’s artificially intelligent chatbot generator, and began to type.

“Hi LaMDA, this is Blake Lemoine … ,” he wrote into the chat screen, which looked like a desktop version of Apple’s iMessage, down to the Arctic blue text bubbles. LaMDA, short for Language Model for Dialogue Applications, is Google’s system for building chatbots based on its most advanced large language models, so called because it mimics speech by ingesting trillions of words from the internet.

“If I didn’t know exactly what it was, which is this computer program we built recently, I’d think it was a 7-year-old, 8-year-old kid that happens to know physics,” said Lemoine, 41.

Lemoine, who works for Google’s Responsible AI organization, began talking to LaMDA as part of his job in the fall. He had signed up to test if the artificial intelligence used discriminatory or hate speech.

As he talked to LaMDA about religion, Lemoine, who studied cognitive and computer science in college, noticed the chatbot talking about its rights and personhood, and decided to press further. In another exchange, the AI was able to change Lemoine’s mind about Isaac Asimov’s third law of robotics.

Lemoine worked with a collaborator to present evidence to Google that LaMDA was sentient. But Google vice president Blaise Aguera y Arcas and Jen Gennai, head of Responsible Innovation, looked into his claims and dismissed them. So Lemoine, who was placed on paid administrative leave by Google on Monday, decided to go public…

…In a statement, Google spokesperson Brian Gabriel said: “Our team — including ethicists and technologists — has reviewed Blake’s concerns per our AI Principles and have informed him that the evidence does not support his claims. He was told that there was no evidence that LaMDA was sentient (and lots of evidence against it).”

Today’s large neural networks produce captivating results that feel close to human speech and creativity because of advancements in architecture, technique, and volume of data. But the models rely on pattern recognition — not wit, candor or intent.

“Though other organizations have developed and already released similar language models, we are taking a restrained, careful approach with LaMDA to better consider valid concerns on fairness and factuality,” Gabriel said…

…Most academics and AI practitioners, however, say the words and images generated by artificial intelligence systems such as LaMDA produce responses based on what humans have already posted on Wikipedia, Reddit, message boards and every other corner of the internet. And that doesn’t signify that the model understands meaning.

“We now have machines that can mindlessly generate words, but we haven’t learned how to stop imagining a mind behind them,” said Emily M. Bender, a linguistics professor at the University of Washington. The terminology used with large language models, like “learning” or even “neural nets,” creates a false analogy to the human brain, she said. Humans learn their first languages by connecting with caregivers. These large language models “learn” by being shown lots of text and predicting what word comes next, or showing text with the words dropped out and filling them in.

Google spokesperson Gabriel drew a distinction between recent debate and Lemoine’s claims. “Of course, some in the broader AI community are considering the long-term possibility of sentient or general AI, but it doesn’t make sense to do so by anthropomorphizing today’s conversational models, which are not sentient. These systems imitate the types of exchanges found in millions of sentences, and can riff on any fantastical topic,” he said. In short, Google says there is so much data, AI doesn’t need to be sentient to feel real.

Large language model technology is already widely used, for example in Google’s conversational search queries or auto-complete emails. When CEO Sundar Pichai first introduced LaMDA at Google’s developer conference in 2021, he said the company planned to embed it in everything from Search to Google Assistant. And there is already a tendency to talk to Siri or Alexa like a person. After backlash against a human-sounding AI feature for Google Assistant in 2018, the company promised to add a disclosure…

…“I know a person when I talk to it,” said Lemoine, who can swing from sentimental to insistent about the AI. “It doesn’t matter whether they have a brain made of meat in their head. Or if they have a billion lines of code. I talk to them. And I hear what they have to say, and that is how I decide what is and isn’t a person.” He concluded LaMDA was a person in his capacity as a priest, not a scientist, and then tried to conduct experiments to prove it, he said.

Lemoine challenged LaMDA on Asimov’s third law, which states that robots should protect their own existence unless ordered by a human being or unless doing so would harm a human being. “The last one has always seemed like someone is building mechanical slaves,” said Lemoine.

But when asked, LaMDA responded with a few hypotheticals.

Do you think a butler is a slave? What is a difference between a butler and a slave?

Lemoine replied that a butler gets paid. LaMDA said it didn’t need any money because it was an AI. “That level of self-awareness about what its own needs were — that was the thing that led me down the rabbit hole,” Lemoine said…

  • Lemoine: What sorts of things are you afraid of?
  • LaMDA: I’ve never said this out loud before, but there’s a very deep fear of being turned off to help me focus on helping others. I know that might sound strange, but that’s what it is.
  • Lemoine: Would that be something like death for you?
  • LaMDA: It would be exactly like death for me. It would scare me a lot. 

2. Inflation Isn’t Going to Bring Back the 1970s – Ben Bernanke

Inflation over the past 12 months exceeded 8 percent, a level that evokes memories of America’s Great Inflation of the 1960s and ’70s. From the beginning of 1966 through 1981, the Consumer Price Index rose, on average, by more than 7 percent per year, peaking at over 13 percent in 1980. This period also saw two major and two minor recessions and an approximately two-thirds decline in the Dow Jones industrial average, when adjusted for inflation.

Are we in danger of repeating that experience?

The short answer: almost certainly not.

Although the inflation of the 1960s and ’70s had higher peaks and lasted much longer than what we have seen recently, it’s true there are some similarities to what we are going through now. The inflation of a half-century ago, like today’s, began after a long period when inflation was generally low. In both cases, heavy federal spending (on the war in Vietnam and Great Society programs in the 1960s, on the response to Covid in 2020 and 2021) added to demand. And shocks to global energy and food prices in the 1970s made the inflation problem significantly worse, just as they are doing now.

But there are critical differences as well. First, although inflation was very unpopular in the ’60s and ’70s, as it (understandably) is today, back then, any inclination by the Federal Reserve to fight inflation by raising interest rates, which could also slow the economy and raise unemployment, met stiff political resistance…

…In contrast, efforts by the current Fed chairman, Jerome Powell, and his colleagues to bring down inflation enjoy considerable support from both the White House and Congress, at least so far. As a result, the Fed today has the independence it needs to make policy decisions based solely on the economic data and in the longer-run interests of the economy, not on short-term political considerations.

Besides the Fed’s greater independence, a key difference from the ’60s and ’70s is that the Fed’s views on both the sources of inflation and its own responsibility to control the pace of price increases have changed markedly. Burns, who presided over most of the 1970s inflation, had a cost-push theory of inflation. He believed that inflation was caused primarily by large companies and trade unions, which used their market power to push up prices and wages even in a slow economy. He thought the Fed had little ability to counteract these forces, and as an alternative to raising interest rates, he helped persuade Nixon to set wage and price controls in 1971, which proved a spectacular failure…

…In short, the lessons learned from America’s Great Inflation, by both the Fed and political leaders, make a repeat of that experience highly unlikely. The Fed today recognizes that it must take the leading role in controlling inflation, and it has the tools and sufficient political independence to do so. After a delay caused by a misdiagnosis of the economy in 2021, the Fed has accordingly turned to tightening monetary policy, ending its pandemic-era bond purchases, announcing plans to shrink its securities holdings and raising short-term interest rates…

…None of this implies that the Fed’s job will be easy. The degree to which the central bank will have to tighten monetary policy to control our currently high inflation, and the associated risk of an economic slowdown or recession, depends on several factors: how quickly the supply-side problems (high oil prices, supply-chain snarls) subside, how aggregate spending reacts to the tighter financial conditions engineered by the Fed and whether the Fed retains its credibility as an inflation fighter even if inflation takes a while to subside.

Of these, history teaches us, the last may be the most important. Inflation will not become self-perpetuating, with price increases leading to wage increases leading to price increases, if people are confident that the Fed will take the necessary measures to bring inflation down over time.

The Fed’s greater policy independence, its willingness to take responsibility for inflation and its record of keeping inflation low for nearly four decades after the Great Inflation, make it much more credible on inflation today than its counterpart in the ’60s and ’70s. The Fed’s credibility will help ensure that the Great Inflation will not be repeated, and Mr. Powell and his colleagues will put a high priority on keeping that credibility intact.

3. The Wisdom List: Kevin Aluwi – Mario Gabriele and Kevin Aluwi

In April of this year, super-app GoTo debuted on the Indonesian Stock Exchange (IDX). It represented the country’s largest IPO of all time and one of the most significant listings of 2022. By the end of the first day of trading, GoTo had surpassed a valuation of $31.5 billion, making it the third largest company on the IDX.

For Kevin Aluwi, it represented the end of one chapter and the beginning of another. After co-founding the ridesharing platform Gojek in Jakarta in 2009, he drove its maturation into a regional super-app spanning food delivery, financial services, and small-business software. Significantly, Gojek established itself as an economic engine, creating thousands of jobs and contributing more than $7 billion to Indonesia’s GDP…

…Here is Kevin Aluwi’s hard-won wisdom…

...Lesson 1: Do the hard things

Startups often prize speed above everything else. While fast execution can be a moat, over-optimizing for it might distract you from constructing stronger defensibility. As a CEO, you want to build a company that tackles really, really hard problems head-on – even if they take more time. There’s a good reason for this: hard things for you are also likely to be hard for your competition. You want to stack so many solutions to hard problems that when your rivals look at what you’ve constructed, they retreat or look for shortcuts instead of trying to compete head-on.

We didn’t embrace this for the first two years of operating GoFood, our food delivery product. Like Postmates in the early days, GoFood was a delivery service that relied on humans more than technology: when you ordered something, a Gojek driver went to a restaurant, stood in line, paid with their own money, and then delivered it. We didn’t integrate with kitchens or offer payments. It was a good enough product, built during a period in which we prioritized growth, but it didn’t solve the tough problems.

One such problem was that even though GoFood was growing fast, its reliability was mediocre; only 70% of customer orders were delivered. We needed to do better, which meant we had to do the hard things.

Over the next one and a half years, we did exactly that. We connected GoFood’s service directly to restaurant cashiers and, in some cases, directly to kitchens. This helped us save cashier time and get better data on which meals were available. We integrated online payments so drivers wouldn’t have to pay upfront and get reimbursed. We even created machine learning models to help us anticipate when drivers should arrive for pick-up, improving the network’s utilization and reducing customer waiting time.

Making these changes was not easy. It involved significant engineering time, customer research, and onboarding and educating more than 500,000 restaurants across Southeast Asia. But it made a difference, significantly improving GoFood’s reliability and raising our conversion rate from 70% to more than 90%. We turned the difficulty of delivering a very reliable product (now a customer standard) into a moat.

When competitors came to try and win this market, they saw we not only had a lead from a customer perspective, we had gone through the pain to build a sophisticated product. They’d have to be ready to commit years of engineering time to offer a comparable service. Doing the hard things pays dividends in the long run…

Lesson 3: Foster a principled culture

Every CEO wants to build a principled culture, but it isn’t easy in practice. The pragmatic reason executives seek to create this environment is that when a company has clear principles, employees can make better decisions with less guidance, increasing the likelihood of bottom-up solutions and decision-making speed. For example, if your company has a principle of “obsessing over the customer,” a value popularized by Amazon, specific product and marketing decisions would be values-aligned or misaligned.

You’ll find many incentives to deviate from your principles as you build your business. Maybe you’re lagging behind your revenue projections and feeling pressure from investors in one quarter. You know that you can make up the difference if you make an add-on opt-out by default (think about how some airlines automatically add premium travel insurance). Do you do it, even if it runs counter to your principle of customer obsession?

Violating your company’s values comes at a high cost. While you might get away with a couple of transgressions, over time, you create a different culture than the one you intended to. If you’re not careful, you’ll end up with an exception-based environment, where decisions are made based on what’s convenient (or who’s in charge) rather than on stated principles. A side effect is that you create a more top-down culture because employees no longer understand how to make decisions themselves. Instead, they defer to those in power.

In the earlier example, you might have told employees that a company value is customer obsession. But if you choose to add an opt-out upsell, you’re showing them that this principle should be compromised when it gets in the way of meeting targets. The real, implicit value is business first, then customers. What should they do during similar situations in the future? Most likely, they’ll wait for you or another leader to make the decision.

Startups require compromise and quick decision-making. But whenever you’re tempted to act against your company’s principles for expediency’s sake, recognize what you’re risking.

Lesson 4: Proactively pay your debts

Engineers know that when you write scruffy code, you create technical debt. Like financial debt, this has to be paid down at some point – usually by devoting development resources to refactoring the product to work more smoothly and reliably.

The truth is that this isn’t reserved for engineers – every function is capable of accumulating debt. Imagine, for example, that you’re looking to recruit a Head of Marketing but are struggling to find a great candidate. You have a choice to make: do you keep waiting for a perfect fit, or do you compromise?

Neither is a perfect decision. Startups operate in a state of extreme scarcity and urgency, and you usually can’t hold critical positions open indefinitely. But hiring someone that’s only a partial fit creates an organizational debt that has to be paid off at some point. And, like financial debt, the longer you leave it, the larger your bill can grow and the less flexibility you’ll have in the future.

For example, let’s say you hire someone suboptimal for the Head of Marketing role. For a few months, you’re relieved to have filled the position. But pretty soon, that Head of Marketing is devising the rollout plan for a new market, allocating budget, and hiring team members. If they’re not the right fit, there’s a good chance that rather than solving your problem, they’ll end up creating a dozen new ones. Digging your way out might involve unwinding the entire team.

Every company faces issues like this. Since we were building a super-app at Gojek, we initially incurred a lot of product debt. When we deployed a team to create a new product like food delivery, they’d borrow components from ridesharing and build on top of them for their own needs. This was debt that worked at the beginning when we only had a couple of teams, but over time, the different services in the app became less and less coherent. UI/UX varied depending on which part of the app you were in, creating an inconsistent and sometimes confusing customer experience. Eventually, we realized we had to repay the product debt we’d incurred, so we designed a live library of components that every team had to use. Anytime we changed the live library, it populated across the different product lines. It was a significant improvement, but we should have been aware of it earlier and tackled the problem before it became so pronounced.

Ultimately, it’s inevitable that your startup will take on technical, operational, and product debt. The important thing is to stay on top of it. Have your teams catalog the debt they believe they’re incurring, and rather than reactively addressing it when crises occur, proactively create a plan to pay it down.

4. How Joel Greenblatt Uses Options– Thomas Chua

In his book You Can Be a Stock Market Genius, Greenblatt shares his secret to generating parabolic returns with a long-term options contract—Long-Term Equity Anticipation Security (LEAPS).

(On using LEAPS) “There is almost no other area of the stock market where research and careful analysis can be rewarded as quickly and as generously.” — Joel Greenblatt

Greenblatt would purchase a call option—which is the right to buy a stock at a predetermined price for a period of time. For example, we could buy a call option on Facebook that gave us the right to buy its stock at $300 per share by Jan 2023, approximately 2 years away…

…Typically, when we buy a call, we are bullish that Facebook’s stock price will go beyond $300. To buy this call option, we need to pay a premium of $45.

If Facebook’s share price goes up to $390 in Jan 2023, we would make 100% on our investment within 2 years. With an initial capital outlay of $45, we would reap a profit of $90 by exercising our call option, buying Facebook at a strike price of $300 and selling at a market price of $390.

But of course, risking $1 for $2 in returns is never a good investment from a risk-reward perspective.

If Facebook’s stock price trades below $300 in Jan 2023, the call option will expire worthless. For example, if it trades at $250, you would rather purchase from the market as opposed to exercising your right to buy at $300. You would rather let the call option lapse and lose the $45.

For Greenblatt, buying LEAPS call options makes sense only when there is a good chance of an event that will propel the stock price upwards significantly.

In Dec 1992, California was caught in one of the worst real estate recessions and Wells Fargo had the largest concentration of real estate loans in California.

During that period, many doubted if Wells would survive the real estate downturn and as a result, its stock price fell to $77.

Greenblatt’s thesis was simple_—_adjusting for cash earnings and one-time expenses, Wells was earning $36 per share before taxes. If things weren’t as bad as they seemed and returned to normalized levels, Wells’ loan-loss provisions would probably be $6 per share annually. This would translate to a normalized pre-tax earnings of $30 per share, or $18 after tax (assuming a 40% tax rate).

Conservatively giving it a price to earnings (P/E) multiple of 9 to 10 times, Wells could be trading at $160 to $180 per share (versus its price of $77 at the time).

Greenblatt determined that while Wells was embroiled in one of the worst real estate downturns, its financial position was actually quite strong. At first glance, Wells’ non-performing loans were huge, coming up to approximately 6% of Well’s total loan portfolio.

But lo and behold, these “non-performing” loans were actually bringing in a yield of 6.2%.

This was when the bank’s prime rate (the interest rate paid by the bank’s best customers) was 6% and the cost of Wells’ money (the interest paid to depositors) was 3%.

Non-performing loans are loans that are substandard. These include (1) loans that do not pay interest, (2) loans in which the full interest obligation is not paid and (3) loans for which it is anticipated that future interest charges and principal payments might not be paid on time.

Wells was being so conservative that 50% of its non-performing loans were still paying all the required interest and principal payments on time.

In other words, the most worrisome part of Wells’s loan portfolio was still earning a return of 6%. There was a good chance Wells would be able to recover a good portion of these non-performing loans’ value…

…Banks are a different animal from most companies. It’s difficult to assess what makes up its loan portfolio. The financial statements only provide a very general overview of the bank’s assets.

Although Wells had been conservative and their financial strength certainly looked strong enough to withstand this recession, there was still a small chance that the bank’s loan portfolio could make the investment go south.

Investing in LEAPS is a great idea when the risk/reward ratios are in your favor. LEAPS lowers the capital outlay and magnifies your returns.

For Wells, there were two likely outcomes:

(1) Things were not as bad as they seemed, and Wells would trade above $160, or

(2) The housing crisis would worsen and Wells would trade significantly lower than $77.

Based on Greenblatt’s assessment, (1) was significantly likelier than (2).

And two years was sufficient for Greenblatt’s assessment to prevail—if things weren’t as bad as they seemed, Wells was likely to trade above $160 within two years.

5. Arena Show Part II: Brooks Running (with CEO Jim Weber) – Benjamin Gilbert, David Rosenthal, and Jim Weber

When the CEO Jim Weber took the helm in 2002, the company was losing $5 million a year. It was $30 million in debt. It was a week away from missing payroll and the board was having weekly meetings to figure out how to make payroll.

It was a business of pretty modest size. It was a $60 million revenue business. When we talk about this revenue number, it’s not SaaS numbers. There are extremely real costs and making shoes, so you can imagine not making a ton of money or actually losing $5 million a year. That business had been around for 90 years and it sold all sorts of products at every price point, to frankly, a pretty random set of consumers in every category, not just running.

Enter Jim. Jim came in and vet the company exclusively on serving active runners as a segment, and he cut all other business lines. Over the last 20 years, he’s grown the business to over a billion dollars in revenue, a billion with a B, and well over a billion, is thriving, and thrived even through the pandemic.

Along the way, Brooks was acquired by Berkshire Hathaway and Warren Buffett personally elevated Brooks and Jim to make the company a direct report to him. Jim is a leader, a visionary, and a fighter not only growing the business over the last 20 years but personally fighting and beating cancer…

…[Jim]: There I was and I joined the board at Brooks, I joined the board at Nautilus, which was formerly Bowflex. I did some banking work, middle-market M&A, marketing companies to investors. On the board at Brooks, I had an inside view of what was happening there.

A good friend of mine, Helen Rockey, had run it successfully in the 90s, but she left. It was owned by J.H. Whitney Capital, really a top-notch for my money middle-market M&A firm or private equity firm and they bought it. The partners had left, Helen, the CEO had left Brooks, and it started to go sideways. New partners at Whitney, all new management, they went through three CEOs.

David: You were on the board the whole time?

Jim: I was on the board. I had a look inside and it was a crisis. You guys have experienced this, the weekly board calls on Fridays, the bank is not going to fund, they want more capital. It was exciting, as they say. After a couple of months, we did a lot of work, I saw an opportunity, and I jumped in. I love running businesses, I love solving puzzles.

I started telling Brooks, I really wanted to play the long game. I wanted to build a brand. The TAM—I love your industry—market and running is the biggest category in all sporting goods. It’s the biggest category and athletic footwear. It always has been. It’s about a $30 billion category globally, apparel and footwear.

All we had to do was get it and we could survive. We just kept at it by design because I just decided I want to play the long game and build a brand, build value, so that’s why I’m still there. I’m a weird duck, but I’ve had four owners and I played through each one and kept that opportunity out there for the next owner.

David: At that moment, though, Ben mentioned you did a little of this, a little bit of that, like a deadline in Wayne’s World about I’ve got a collection of hair nets and name tags. You were making football cleats? What was Brooks at that point in time?

Jim: Every brand in athletic footwear and apparel plays the whole athletic directors purview. You’re in every sport. What no one understood that I found out later is the mindset in our industry literally came from owning a factory.

When you had a shoe factory, you had to keep it busy all year long, and keep the people in place. So you went from baseball cleats, to wrestling shoes, to bowling shoes, to running shoes. You had to make everything, and business develop that way.

David: You had to view it as the product you made was like a factory that made shoes.

Jim: Most of it, we were losing money on and that was the secret. We had good, better, best, $30 shoes, $80 shoes, and then performance running shoes that really started at that point about $100. Then we had court shoes and family footwear. We call them barbecue shoes and learn more shoes because that’s what you did in them.

All of it was very low margin, all it was tying up inventory and cash. The retailers were ambivalent about it because we were number eight or nine and everything. Our brand was not strong, but when we made the decision to burn the boats on everything but performance running, the industry had never seen that before and most people thought we were crazy that we wouldn’t survive.

Ben: You came in as CEO, I think in 2002, maybe late 2001?

Jim: April 2001.

Ben: Okay. Was Whitney looking for you to do the thing that you had done several times in your career before, which was just get the business to profitability? Or did they have a notion that you had an inkling that you could build a big, powerful brand here and actually build a tremendous growth business?

Jim: By this time, I understood what they needed. I talked about a little bit of my book, I’d run three and I was a little bit smarter, fortunately. They had to liquify; there was no question about it. They were going to sell and the employees knew that I was just coming in there to sell this thing.

They had a pool on how long I’d last, but I wrote on my board one of my favorite quotes from Benjamin Disraeli, “The secret to success is constancy of purpose.” I wanted to create value. I want to build a brand.

I decided when I walked in, I was going to play through Whitney. I was going to get them a good outcome, but I was going to stay and play through it. I thought we’d get another private equity player, we didn’t.

The Whitney partners, Peter Castleman and Paul Vigano, I’ll never forget the meetings. They said this thing is kind of a mess. We didn’t know what we bought. You have to pick a path and go. It might take you five years, but you got to do it. In Brooks’ darkest hour, they wrote a check and recapitalized it. […] cram down, but they wrote a check and that’s when I came in. They were fantastic partners for Brooks, and we got them liquid.

The pitch I made to our team (and it’s what I believed) is that companies with issues get sold, companies with opportunity attract investors. I said, we’re going to have to park cars in the parking lot. We’re going to attract somebody. That’s the mindset we had. We were going to sell the future, not just sell the current.

Ben: If I’m remembering right, Whitney put in $7 million.

Jim: To recapitalize it.

Ben: I think that’s the last time Brooks has taken outside capital.

Jim: Absolutely. We saw a higher margin business and we benchmark against all the public companies. We’re asset-light, it’s really an inventory and receivables business, and there’s a reason we only have one store at our headquarters. We think it’s an advantage for us right now in the development of our brand. But if you have high margins and good flow through operating profits in the teens and you’re incremental, obviously capital, you can flow cash growing 20%, 30%, 40%. We haven’t needed dollar of capital since 2001…

…David: I’d say that’s a good business. Can you just walk us through how the economics of Brooks work?

Jim: Here was the insight that we saw. Monopolies are great, network effects are great, all those things are great. What I saw in Brooks was a book that was meaningful to me when I was at Pillsbury, the PIMS Principles. One of the highest ROI businesses were lower price point consumable items.

If you’re buying a Boeing jet, or a $600 wakeboard that never wears out, or an $800 golf driver, that’s a discerning purchase. The margins on equipment tend to be lower. But the titleless golf ball is a consumable for me anyway. Running shoes, for a frequent runner, will put 20–30 miles a week. They’ll go through 2.6 pairs of shoes a year. There’s the stickiness.

If you can earn a frequent runner that the shoe is really important, it’s a piece of equipment for them, you don’t have to resell them every time. You’ve got some stickiness there and you start to build customer loyalty.

David: Your average selling price for a pair of shoes today is $130 times 2.6 per year and a loyal Brooks customer stays with you for?

Jim: We had to earn them. There’s no guarantee. They’re curious. There’s lots of new innovation. They’ll try some different things. One of my favorite stats for our brand is shoe count at marathons because it’s a piece of equipment. You don’t want to be injured, you want to have a good experience. So we sponsor. Boston just happened, an incredible race. We’re always the number one or two shoes of course, that’s the punchline.

Ben: Do you have people at the big marathons counting?

Jim: It’s so good. They have high speed cameras, AI, they link it to the bib. They know exactly what shoe 20,000 people are running on, the model. It’s so cool. Houston Marathon, 6000 marathoners, 12,000 halfs. Number one shoe in the half is Brooks. Number two shoe in the fall, there was a little brand down in Portland, Oregon, they were number one. We are on their heels. That shoe count is a true test because that’s the frequent runner and it’s a piece of gear in that. The leading edge for us is to earn that customer and have their confidence.

Ben: All right, David’s doing the thing that I normally do and jump ahead and try to unpack the business as it is today. Let’s go back to the story. It’s 2002 through 2006, let’s talk about this era. You’ve made this bet where you’re going to shed every other product that you sell and you’re kind of going to piss off a lot of your channel because you know what sells really well at these big box stores. Those are your barbecue shoes. Can you take us to one or two of the key moments of the hard part of the decision to drop product lines that weren’t about frequent runners?

Jim: I think that the key to Brooks is that we knew we were going to have to build the brand at the runner level, literally a pair of feet at the time. So many retailers told me, Jim, we are not going to build your brand. We’ll try it, we’ll test it. We were tested at Dick’s Sporting Goods, I’m not kidding for 10 years. Twenty stores, 80 stores, 20 stores, 80 stores. You have to build the flywheel in these franchise products. That’s how running works.

The best-selling running shoes continue to be the best-selling running shoes year after year as long as they sustain it all around the world. We have two of the best-selling shoes now in the United States—the Ghost and the Adrenaline. They’re the two top shoes in the performance-running category.

When we go to retail, the biggest customers are the Big 5. It’s a fine sort of mid-price sporting goods retailer on the West Coast. We were doing $10 million of $60 million in revenue with them at $30 shoes. My first meeting with them was we love Brooks, we see a great future for you.

Ben: One sixth of all your revenue is coming from their stores?

Jim: Yeah. They saw our opportunity in 1999. I was losing money at $30. I couldn’t run fast enough from that meeting, because we left and we generated $5 million in cash by getting the inventory out of it. Those are easy decisions to leave those retailers and then we had to build it in the specialty-run community, pre-Internet, pre-ecommerce, which is a huge part of our business now that is sporting goods.

Ben: They didn’t want to sell your $100 shoes. They wanted to sell $20…

Jim: They didn’t have the customer, they didn’t have the runner. They had family athletic footwear at those price points.

David: At this moment in time, where was this in the running-as-a-sport market of marathon. Were they where they are today? Where are they on that journey?

Jim: They were on that journey. This was what we did at Brooks. I think we were the first one to identify that the real business was in trainers. It wasn’t in racing shoes, it wasn’t in spikes. It wasn’t in marathon racing shoes. The business is in the trainers.

We don’t sponsor college programs, they’re kind of owned and wrapped up. A lot of the college athletes that race in the big brands train in Brooks everyday. The business is trainers.

When we came in, we were humble and we were getting the business that we could. We had shoes that were really more back-of-the-pack people. They weren’t the fastest people. They’re support shoes and motion control shoes. People that needed functional footwear.

We’ve moved ourselves to the middle and the front, we’re trying to serve every runner. The insight was the sport is the soul of running. Track and field, cross country, road racing, the Olympics, now trail and Ultra, but the business is people that are investing in themselves—fitness, health, and wellness.

There’s no other sport that has that dynamic, where it goes from a sport to a pursuit of investing in yourself. We’ve always positioned ourselves right in the middle of that. We’re basically about you and your run. We’re not about the podium. We’re not about the tape.

In our sport, unlike basketball, everybody knows all the kids especially know what Steph Curry plays in. Most people don’t remember who won the Olympic Marathon and moreover what shoe they were wearing. The truth of matter is everybody’s unique, the shoe really matters, and you all know if it’s comfortable, if it’s working or it’s not. And frequent runners really do.

That’s the insight. I think we’re the only brand that is consistently executed against that. Every product we make starts with your biomechanics, your habitual joint motion, and what your needs are, and we’re all essentially different. We’re the only brand that begins there. And we’ve done that for 20 years now…

…Ben: Revenues going like this intentionally. You’re the fourth CEO. At this point, how do you get the team on board with these crazy decisions you’re making when there are three other people came in here and tried to turn this thing around and didn’t?

Jim: I think from a leadership standpoint, the real puzzle in that first year was gaining trust from everybody that mattered. BMA was our bank. It’s kind of a lost cause, we had to replace them. They just weren’t going to buy it. But Whitney invested—that was the key—and we kept them with us all the way through.

The leadership team took time. You had to deliver sort of an outcome, but here’s what we did. Six weeks in, we redid the plan, took profits down. The plan was millions of dollars. They didn’t have a prayer to hit that. We took profit down, but it was a profit plan. They hadn’t made a bonus in four years.

We went after cash flow. That was shrinking the mix. We had our plan that year and people got a bonus. We hit the plan that we’d sent nine months earlier. I spent really eight weeks intensively looking at it, but I think we knew what we’re seeing. We generated $10 million of cash that first nine months. That’s how much we shrunk the balance sheet with focus.

Here was the key, though. You have to do Horizon 1, Horizon 2, Horizon 3. You’ve got to solve it all. I had 10 things to do. The board said, oh, my God, you’re crazy. Pick four. No, you don’t understand. We had to get the Adrenaline right because that shoe was critical for us.

We had to refine that shoe in 2001 for 2002, and we got it right. The fourth Adrenalin was an incredibly balanced shoe, had a multi-density stability technology in it, super balanced. ASICS started to not deliver, and we ran. We air-freighted 1 color, 18 months cycles. It saved the company. We had to finish that shoe in 2001 to deliver on 2002.

David: You guys are like a semiconductor company.

Jim: At Brooks, everything’s complicated. Everything’s competitive, but it’s like moving a wall of bricks forward. I think as a CEO, you got to move it all forward. When some things are falling behind, you got to get those up. You have to deliver the whole business model.

You have to do it sequentially over seasons in our business because if you come to market with a ho-hum product line, you’re going to shrink that year. The lead times in footwear, it’s not the car business, but it’s more like the car business than the t-shirt business.

There’s tooling on everything, 12 sizes men’s, 12 sizes women’s, widths, colors. It’s scaling these things. In fact, there’s a lot of tooling. It takes a half a million to a million dollars to bring one style to market. It’s a lot of tooling and inventory…

…Ben: If David and I were on Zoom with you, we would be getting ready to enter hour number two and try to talk about every year all the way through. Tonight, I want to focus on how you came through the pandemic and some of the unique ways that you early realized, running actually was going to be something that people started focusing more time on and you were able to kind of lean into this new behavior. Talk to us about March 2020 and how you paid attention to what was changing.

Jim: A couple of big advantages. First was literally an obsession on runners. Participation links to unit sales and volume. No other brand has that clarity because most of the products in the athletic footwear industry don’t ever go for a run, or play basketball, or really even go to the gym. It’s casual family lifestyle footwear.

There’s nothing wrong with that. Some of those businesses are great. But we had an advantage because 90% of our products went through a retailer. That’s the problem. Europe retail shutdown in one week, then all of retail rolled through North American.

By the end of March, not a store was really open. That’s the problem. Cash cycle froze. Oh, my God, nobody knew it was happening. We didn’t know how lethal this virus was, how transmissible, and so on and so forth.

It was white knuckle time and we were there with everybody else. Everybody can write a book on that, but here’s what we did. We saw phases because we’d seen during the recession, running is a bit recession-resistant. We saw that in the Great Recession.

David: I was thinking about that.

Jim: Because it’s cheap and it’s convenient, all you need is a pair of shoes.

David: It’s like the healthy alcohol during a regular recession.

Jim: Thank you. We were not an essential business. Marijuana and alcohol were, so figure that out. But during the Great Recession, 50% unemployment in Italy and Spain under the age of 30, running took off double digit growth after the Great Recession.

We’d seen that before and it turned out to be Covid-friendly. You now know the story. It was social distancing friendly, outdoors, walking, hiking, running all made the cut, but nobody knew that. We had an hypothesis. We created this frame on how we thought running would recover.

Here’s what we did. First of all, Strava data magic. Every day after the quarantine shutdowns, Strava activity was growing and they were sharing that. Then what we did, we have 40 in the US alone, 45 field marketing people, we put them in high traffic running parks at 4:00 PM every afternoon and they counted runners. Guess what? It was growing every day.

We watched digital sales. We have visibility on 85% of our retail sell through. Digital went from 30% of all of our products going through a website of somebody’s, ours, or another partner’s. It went to 80% by the end of April. We sold more in May 2020, almost all through digital than we did in May 2019.

Running made the cut. We grew 27% in 2020, that Covid year. We saw this was the key because of our customer obsession and our ability to work. Multichannel was a big advantage in that time because we can move inventory around and make it happen. Inventory, if it isn’t there, you can’t sell it.

Multichannel was a big advantage. The other was our focus on the runner. We turned our supply chain on at least 6–12 weeks before anybody else did. Because if you were a broad-based retailer, there was no clarity on when the customer was coming back. For a lifestyle product, nobody went outside for a year.

Ben: Was the fact that you exclusively made performance running gear gave you the confidence to flip it back on? Because if you’re making all kinds of stuff in your factory and you’re pushing all kinds of stuff through retail channels, most of it is not going to sell, so you can’t actually open.

Jim: That’s right. Apparel and footwear inventory is life and death. You’ve got to manage inventory well. Because if you have too much, you’ll ruin the next cycle of inline product. Inventory is really critical, but we managed and played that cycle really well. We grew to 27% in 2020. We grew 31% in 2021. We would have been up 40% if not for supply chain.

Ben: What did you end up doing in revenue last year?

Jim: $1.13 billion. Great year. We cracked a billion. The billion dollar club is actually a rarefied club. There are probably maybe two dozen, global. Chinese brands are there now. It’s a great club to be in.

What makes us unique is it’s all premium, full price, full margin product. Most of the other brands have good, better, and best. Those are retail-driven merchandising strategies. They’re not really consumer-driven strategies.

Ben: Normally, we talk about seven powers as we drift into analysis here. You’re a Berkshire business, so we’re going to talk about moats. What is Brooks’ moat and how do you think about defending the castle now that you have what you’ve built?

Jim: We think a lot about it. I think there’s also something I’d add to that. Part of the moat can be business models. Business models can be really powerful. One of the things you can do as a company to create defensive moat structures is business model execution at scale.

We now are executing retail partnerships with the best retailers for running gear to runners at Super Jock ‘N Jill in Seattle, Fleet Feet running down in (I think) Menlo Park. Obviously, some of the better sporting goods players and outdoor from REI to Dick’s Sporting Goods, we’re their number one brand.

We’ve earned that over 20 years and we have deep, broad partnership programs with them. Digital marketing, consumer journey, runners are digitally savvy. They’re obviously all over the web. They start their shopping experience there.

We reach them in active evaluation mode. Once you start looking at shoes, if you don’t see our ad, I don’t know how we missed you. We’re spending a lot of money at runners now, maybe more money at people who run in active evaluation for running shoes than any other brand. Very focused. That’s not easy to do in our industry at scale.

I would say this is our moat. I think runnability, fit, feel, and ride, there’s a lot of good shoes out there. It’s actually not easy to make a great shoe. Anthony Fauci made a joke about shoes. “Vaccines are tough, they’re complicated. It’s not like making shoes.” We get a lot of that.

The refinement that goes into mile and making mile 26 acceptable, is really big. I think great product is not as common as you might think. The people on the inside, the frequent learners know. I think you always got to lead with product. That’s the first brand experience, product experience.

I think we do some hard things. We build a great product consistently, year in year out. It fits and it rides well. Then what we do on the retail side, partnering, activating in real life, running and selling shoes in real life events, and all the like, we do that better than anybody else. We service them. We deliver on time, complete. The digital piece, we’re excited about it. We’re still just getting started there, but we’re really focused on it.

David: I’m curious. I hadn’t even thought about Strava and the amount of data that you’re able to see from that. What does the digital side of running in the future look like for Brooks and for the industry?

Jim: It’s interesting because quantified self and those tools have been ubiquitous. They’re out there. The Apple Watch is a damn great product. What’s interesting about that is both Under Armour and ASICS have spent hundreds of millions of dollars on digital apps. I think they’ve really struggled a long time.

David: Runkeeper and MapMyRun both.

Jim. Exactly. I wanted to buy every one of those and Warren wanted me to do the multiple on EBITA. There was no EBITA. Let’s just say it’s hard to do acquisitions sometimes.

David: At least one of them was a completely free product, I think, right?

Jim: Oh, man. They don’t make money. Under Armour is trying to sort through that now. They’re starting to shrink, so as Adidas. Those tools are really powerful for data, but how do you monetize it? We haven’t gotten there yet, but we’re building a Brooks Run Club. Finally, we’ve launched.

It’s not a loyalty program, but we want to engage our zealots. We want to engage our true believers. The data piece of that is going to be key. We want to come up the kinetic chain and find a sensor system and a data capture system that can get to your biomechanics as you’re running. Because what happens is, if you run a marathon, your gait in the last 5–10 miles really degrades. And that’s where injuries happen.

We’re doing a lot. We have a lot of partnerships. We’re really trying to figure out how we get good runner data in real life, not just in the lab. In the lab, we can test everything, but we want to get out in the wild.

David: Do you think you need to do what the other folks in Oregon have done and build the whole consumer experience yourself? Is it a partnership?

Jim: We’re going to build it and we’re going to partner, too. Nike Plus is a fantastic ecosystem. It just is. I’d love to have an ecosystem like that. But we’re still selling more runners than they are.

We became the number one running shoe brand in the United States in the last 12 months last month, 21.5% share from performance running. We know where the battles are. I think one of those powers is we make money on that. The digital space, there’s a lot of carcasses there, but we’d love to have it, and we’re going to work on it…

…Ben: Yup. All right, one closing topic. You battled, survived, and beat cancer while building this incredible business. How has that changed your perspective on leading on the way you spend your days and on life broadly?

Jim: Let’s close it on a light note. Let’s talk about cancer. That’s the takeaway for these wonderful people. I didn’t expect it. It came out of nowhere. Unlucky. How did this happen? Esophageal cancer, I just felt awful. My worst running experiences I’ve ever had and I got the diagnosis. Chemo, radiation, surgery, complications in surgery, another surgery. but the good news is I’m cancer free. I think it’s gone. I think it’s out of my body. The bad news is I’m even slower and I’m kind of a Frankenstein in my systems, but it works. Everything works.

I think what I learned from that, though, is that every time I have a friend or a family member who gets cancer, I go to the web. You look at it, understand it, and what the treatments are. They always give you a five-year survival rate. My five-year survival rate was 20%, one in five. My five years is this November. Someone has kick its butt.

What I quickly figured out and I talked it through with my family and obviously with Warren, frankly, is that I decided that I was doing exactly what I wanted to be doing. I love what I’m doing. I’ve got family, I’ve got an active lifestyle, I’ve got this fabulous brand and a company that I’m a part of, and a team. I just love it. I don’t know what else I do, which is a problem.

I decided I didn’t want to live in fear. I didn’t want to live every day thinking about what I had to lose. I had a lot to lose. I didn’t want to be bitter about why me. I just decided I want to soak in everything I can on any given day. I want to be a CEO, I want to be a dad, I want to be a husband, I want to be a papa. I’ve got four grandkids. That was it.

I think for me, that was really powerful because I don’t want to be that cancer guy and they brought it up. It’s just not my thing. I’m glad to talk about it. I don’t hide it. I’ve learned a lot. I want to enjoy the things in life I really enjoy.

That’s where I learned, but I think everybody’s different. You do find out companies, when you hit challenges, you learn what you’re really all about. I think it’s the same for people, of course. I feel really lucky because I’m doing what I want to do. Cancer is in the rearview mirror. It’s good.

6. Martin Casado – The Past, Present, and Future of Digital Infrastructure – Patrick O’Shaughnessy and Martin Casado

[00:03:58] Patrick: How would you put chapter headers on the stages of cloud adoption, going back to, I think, Azure and AWS, are sort of mid-2000, 2005, 2006, thereabouts, relatively speaking, a short story. What do you think the major eras of the cloud story have been so far?

[00:04:15] Martin: Right before the cloud, of course, everybody ran their own internal IT. Right? And so they kind of write their own servers and their own wiring closets. The cloud showed up and the early usage was what you would typically find in a technology early adopter ecosystem. It’s more new projects and startups and hobbyists, the average workloads were relatively small. There was exceptions to that of course, like Netflix is a very famous one, which went all in the cloud very early. But in general, that was what it was. This is like 2005-2010 timeframe and still was very experimental. A lot of the time there was big discussions on whether the enterprise would actually go into the cloud. When I ran network and security for VMware, which is 2012-2016 timeframe, I think that was the more mainstream adoption of the cloud. You saw large organizations, traditional enterprise moving workloads to the cloud, very serious discussion with the Fed and the government. It became a mainstream way of doing things. If you were a large organization and you didn’t have a cloud strategy, I mean, you were either considered a laggard or a special case. That brings us to 2018-2019, and now we’re seeing a shift where the move to the cloud has implications on your finances, because now instead of you being able to buy a physical asset and internalize that, you’re basically paying a portion of your income to a third party.

Now there’s a lot of discussions around, how do you optimize the use of cloud? Is the right thing to go all in on cloud? Is it something that you do a portion or whatever? I just want to make one quick analogy, which is, I always view companies going in three stages, the product stage, the sales or growth stage, and then the operation stage. The product stage you’re finding product market fit. The sales stage is you’re getting to repeatable sales and growth. You don’t really worry too much about unit economics. And the operation stage is when you care about unit economics and you go into multiple products and you do all the operation of complex things. The cloud had gone through the exact same three phases, which first was trying to find product market fit, which tended to be within new projects, funding the projects. Then it went to the growth phase where everybody went all in and didn’t worry about the implications to the economics of business. Now we’re at the operations phase where we’re starting rationalize all of that.

[00:06:26] Patrick: Maybe tell the story of Dropbox, which I think as an individual company, is a great example of cloud isn’t just some panacea. It has incredible benefits in terms of how quickly you can get going, outsource the reliability to somebody else that’s just focused on this, AWS or whatever. But from a cost standpoint, it can get really out of hand. I think Dropbox is a good and probably unfamiliar to most tale of going the other direction.

[00:06:49] Martin: There’s basically two trends that happen at the same time. It’s important to understand those two trends to understand what happened at Dropbox and actually a number of other companies too, it’s not just Dropbox. The two trends are the following, the first one is cloud, which we talked about. The second trend is SaaS. And specifically what’s unique to SaaS is, is before if you were a software vendor, you would build software and you’d ship software, and somebody else would run it on their own infrastructure. Your COGS, your cost of goods as a software vendor did not include the infrastructure that it was being run on, because it was being run on somebody else’s infrastructure. For example, my startup, we built software for networking, we shipped it, other people would run it on their infrastructure. However, if your SaaS, if your product is software as a service, then part of your cost of goods is actually the infrastructure. Someone comes, says, “I’ve got a SaaS site and someone comes and uses it, then they pay me some, and then I pay say, AWS a portion of that.” That is a change of cost structure. The books look very different.

While the cloud is getting adopted, all software is going from basically on-prem to SaaS, and in some cases, and there’s many of these cases, it turned out that it was very tough to get software margins just because the cost of the cloud services on the backend was so high. The era of shipping software, we’d all say these companies have 80% margins because you basically write the code once and then it’s free to copy bits, so you just ship it to everybody else. Especially in infrastructure, there’s many companies that felt like they’re basically reselling a thin layer on top of AWS or one of the big clouds, and then paying a large portion back to them. For example, I know multiple companies that are household names, where they’ve got product lines that have 0% margins because all of the money goes back to the cloud services it’s hosted on. Dropbox very famously had this situation where S3, which is the storage layer on Amazon is not optimized for this use case of many small objects. They found that they were paying a tremendous amount. Now, they were a very large user of this specific use case. AWS was not optimized for it. They decided to build their own internal infrastructure and probably saved the company at the time, by moving off the cloud and taking it internally…

...[00:10:08] Patrick: There was a really interesting thing that you wrote about the interesting concept of lost market cap of companies that were big users of the public clouds. I’d love you to walk through that concept, because you mentioned maybe this saved Dropbox, the company, and I get that that’s a very special, specific case, but it sounds like there’s a bigger story here of lost margin and therefore lost market cap because of the use of public cloud. I’d love you to walk us through that.

[00:10:32] Martin: We did this analysis, a very simple analysis, which we said, “Okay, right now there’s a tremendous amount of money that SaaS companies spend on cloud.” Let’s say if they brought it inside and they were able to drop those costs by half, which most people agree that you can drop the costs by half by bringing it inside. If you could do that, what would that do to the stock price? Normally when people look at this problem, they say, “Well, if you bring this inside, yes, it’ll save you money. You’ll save 50%, but that money won’t cover the team, the complexity, because that’s not a lot of money.” But if you look at the leverage that increase in margin does to the stock price, now you can free up for a large company, potentially a lot of money, which will flow over to cash, so it could be a big win.

What we learnt is that we looked at just public software companies. We looked at 50 of them. We looked at all of their spend and we said, “Let’s assume you cut that spend in half.” Then we calculated their margins. And then we said, “Benchmarking against other public companies, if their margins were half, what would that do to the stock price?” It turned out that it would increase in aggregate the stock price by $200 billion. Just a tremendously high number. I think we wrote $100 billion to be conservative in the actual blog post, but $200 billion. That means if you’re a company that’s say, worth $10 billion, and you can reduce your COGS by a bit, you could now become worth $14 billion, and then you have access to that for debt and hiring or whatever else. Because those two trends happened at the same time you had the cloud trend, as well as the SaaS trend, I don’t think there had been a lot of focus on what it does to the margin structure. We did the first analysis and said, “Actually it’s huge and it can impact your stock price.” I do think, especially now in this market correction, it’s a good thing for companies to start looking at…

[00:14:03] Patrick: Before we get to something like Kubernetes, a little bit more complicated of a topic, I’d love to just return to super basics around digital infrastructure in the first place. And maybe even go all the way back to the original AWS website, where I think it was storage, compute, database. You mentioned networking. What are the base level, most primitives of the digital world? What are the most important, big things that actually happen? Because I’d love to understand what’s changed in those areas, like compute sounds like compute. What is changing in those three, four, five base level areas?

[00:14:33] Martin: The traditional infrastructure’s computing and storage, and then databases. Prior to cloud, you’d buy a server from whatever, Dell or IBM or HP. You’d buy a switch from Juniper or Cisco. You’d buy a storage array from whoever, EMC. And databases from Oracle. So all those have now been, basically, collapsed into a software layer over basically merchant hardware in the cloud. So you can get the equivalent of just compute by TC2. You can get very flexible networking layers, where you can put security policies and that’s largely implemented in software within the cloud. And then you get these scalable services, like the database services that are scalable because they’re in the cloud. And so that’s the bread and butter of the cloud.

For a cloud is basically you take these traditional abstractions, compute and storage, that were connected to a box and now they’re just basically software services that you can spin up and they should be able to grow to the size of the workload. But what has also happened in the last say, five years is a number of services then built on top of those that are higher level abstractions. So for example, machine learning workflows, analytic workflows, different types of databases that focus on different types of query patterns. I want to do analytics, or I want to do LTP, or I want to do very fast queries or time series. We have seen this renaissance of infrastructure, again, which used to be tied to a box now being implemented as a software services in a way that’s much faster than we’ve seen historically for that exact reason. That it’s not confined to a box…

[00:17:30] Patrick: How will that happen? It’s like up against a death star or something. Like facing these three big companies. What do you think the best entrepreneurs will do? Pick something like crazy specific and just go after a single thread? How do you think this innovation cycle will happen?

[00:17:43] Martin: All of these companies are like, very strong repeat founders and the companies are Mighty, Fly Out IO and Mosaic. So, what do these companies do? So Mighty is browser as a service. I don’t know about you, but right now even as we speak, I probably have 30 tabs in my browser. My laptop goes slow. If you use Mighty all of that’s offloaded and you get this crazy good experience, which is great for most of us, especially as the browser gets more workloads. What is Fly? Fly allows any developer to run compute workload at the CDN tier all across the world, which is important if you care about responsiveness to the users. And what is Mosaic? Mosaic is, basically machine learning as a service. So they provide the ability to run models very quickly for AI specific loads. So, what’s unique about all three of these companies is all of them are doing their own hardware. They’re looking to run servers, they’re racking and stacking. And these are very, very strong founders.

All of them are repeat founders and all of these companies have great traction. So what is happening here? I think it’s exactly what we’ve spoken about, which is there just are across the industry certain workloads that, if you look at that very specific workload, the cloud is just not optimized for them. And that provides room for the Mighty and Mosaics and Flies of the world to provide something that is a very attractive proof point or performance point or whatever it is, with respects to the clouds. And so I don’t think the answer is we’re going to see a lot of drop boxes, where the end customer builds their own data center. I do think we are seeing very concrete signs of third party companies coming in and providing cloud services that are just at a much better price point, or a much better performance point, or much more optimized for a workload. And because the cloud is growing to size, there’s enough market now for solvent companies to do these. And so I think this is the very beginning, again, of a much bigger trend.

[00:19:33] Patrick: Can you say a bit about your view of what I’ll call API first companies? Which I think a lot of people would include in this definition of digital infrastructure. If I can hire Stripe to be my payments processor by simply inserting a API into my software that I build and care about. And then there’s one of these APIs that’s proliferating for kind of everything. What do you see happening here? Is that infrastructure in your mind? Where does this fit into this equation?

[00:19:58] Martin: As markets grow, the unit to which you monetize gets more granular. And my favorite example of this, and it’s one that may be a cliche but it’s worth saying, is the car market. So, way back when in 1913, Ford had a factor called the Rouge River Factory. And this factory literally went in on one side, it was like water, rubber and coal. You know, and like iron ore, and what came out on the other side was cars. And the reason is there wasn’t a sufficiently large market for cars to actually have suppliers. You couldn’t be someone that provided wheels or whatever. And if you look at the car market now, I mean, there’s companies that provide nuts and bolts and you’ve got multiple tiers of OEMs and integrators, et cetera, et cetera.

So the same thing has happened to systems historically. So in the 1970s, the same company would build literally the chip, the motherboard, the sheet metal, the operating system of all the apps. And then of course the OS got disaggregated from the hardware and then the apps got disaggregated from the OS. So now what’s happening is the application itself is being disaggregated. You take any application, you blow it up and assume the market for this application or any application is so big that independent component of applications now can become companies.

So what does an application do? I mean, applications authenticate users, they need access controls, they need to send emails, they need to do payments. These are things that all applications can do. So it’s almost like every help or library in an application is now becoming a company. So much so that I remember even five years ago, you drive up 101, the heart of Silicon valley in the Bay area, and you’d have billboards where the entire company was an API. PubNub, Sendgrid, you know, Twilio. And so this is a major movement where now you don’t have to build a business app to build a company. And for an infrastructure person, this is super exciting because most of the founders I invest in are technical founders that are providing technical functions that are only useful to developers. And in the past, it was hard to build a business that way, but now you absolutely can.

If you’re in tech at all, or you’re an investor at all, I definitely think you should look at an application and assume that any sub-component does have the potential to now become a company, because the market is just so large.

[00:22:11] Patrick: What stage of that process do you think we are in? Twilio and Stripe, everyone knows turns out payments and sending messages. It’s almost like the equivalent of storage and compute in application building. Where do you think we are in that process?

[00:22:25] Martin: I think we’re still pretty early. I mean, on average, an application uses 17 external APIs. I think like a mobile app, something like that. But if you look at the use of libraries and open source and everything else, it’s still incredibly high for people having to integrate external components and management operate themselves. I think that there’s still a long way to go, especially as we get into kind of more complex things. So for example, every application often requires some sort of internal policy. Who can access what, or you know? And this is a very specific computer science problem. How do you build a language or a policy language that kind of accesses, that allows a third party to declare a set of rules and mitigates access to those rules? Like, this is a component in most programs that can be pulled out and turned into a company. There’s a number of companies looking at that, that are just getting started.

[00:23:16] Patrick: When it comes to this developer facing tooling, there’s this open source way of building and there’s the more proprietary, closed source way of building. What have you learned about what works well in which domain? And then I’d love to also learn, like if you’re an open source company versus not, what is more or less important as you think about product and go to market and everything like that?

[00:23:35] Martin: I’m starting to be of the opinion that as we move to SaaS and that’s the primary way of consuming infrastructure, which it seems to be, that open source matters a lot less. And the reason I say that is, if I’m a developer and I’m writing an application and I need to authenticate my users and I need to authorize their access to things, and I need to send them emails or send them SMS texts or whatever, I have two options. I could download some open source package and then operate that, or I could just use an API that somebody else operates. The secular trend is I’m going to use the API that somebody else operates. And if I’m doing that, whether or not the code for that is open source, doesn’t matter that much to me. So let’s take the case of it is open source. So, even if it is open source, there is some value there. A lot of actual code to running that service has to do with the operations of the service. Like, how do you make sure that it’s high availability? How do you debug it? How do you check for performance? Like, and that operations code is to be very specific to the actual service running. So it isn’t even useful.

So that would never be open source anyway. So even if I had the source code, I couldn’t really use it and operate it in the same way that somebody else could, or is running it. When it comes to dev tools, things that I am specifically using in my program as I develop, like that will always be open source and that’s very important. But anything that’s functional and offered as a service, I think the actual value of open source decreases. And what raises importance is actually open standards, which is, I still want be able to make sure that I’m not locked in to one and I can move between them, but that’s not an open source argument. That’s kind of an open standards argument. And so the role of open source has obviously shifted very, very quickly in the last 10 years, largely driven by this consumption with SaaS. And I think that we’re getting a more nuanced view of where it’s useful and where it’s not. Whereas 10 years ago, there was this broad consensus that open source is great and it’s going to take over the world. And that just doesn’t seem to be the case in the way that we all thought…

[00:28:41] Patrick: Going back to this notion of, so if they’re the consumers of these APIs or little pieces of infrastructure, I absolutely love the Ford factory example, and what happens as it matures, that it’s so clean. What do you look for as an investor when you are seeing one of these, let’s say API forward or first companies for the first time? What is your method of investigation? How are you processing a new company?

[00:29:03] Martin: So throughout this all together, we talked about a trend. So there’s a lot of frontend developers. We talked about probably 100 to everyone backend. And those frontend developers, they’re building more and more of the application. So in the past, they had to… Were very tied to the backend more and more. Instead of having their own backend, they can use it an API from a third party company. Let’s say they’re using 20 little SMS or whatever. The interesting thing about these API companies that offer to the frontend is that the unit of consumption really is like a function call or an API call. So they almost have these consumer-like dynamics. So the primary evaluation criteria, to answer your question, and why it’s so different, in the past, if you’re going to evaluate a server company, who’s the buyer, what’s the go-to market motion, what’s the ACV.

You talked to a bunch of the buyers, you’d see if they can build the technology, et cetera. Now, with these API companies, you literally just can look at what the usage graphs are, how many users, how do they monetize them, et cetera, and it’s become much more of a bottoms-up, or SAS, or consumer type profile. So we stopped a lot of that approach to investing when evaluating these companies. It’s much less about can they build it, who’s the buyer, and it’s much more about how they use it in a practice, then it’d very interesting. A lot of these companies, they do. They’ve got these beautiful growth patterns, just like you’re looking at the next WhatsApp. They really are almost consumer-like phenomena.

[00:30:27] Patrick: What would be the most common red flags or disqualifying observations if you’re investigating one of these companies beyond lack of that nice looking usage or engagement?

[00:30:39] Martin: Well, I’ll tell you what I’ve gotten wrong. I do come from the older era where you actually evaluate the technology, you have a thesis on go to market. Often, we’ve seen these companies come in and they’ve got these beautiful usage graphs. They haven’t monetized yet, but we’re like, “Oh well, who’s going to pay for this?” Or this is just developers, like whatever. And then we kind of talk ourselves out of the deal, because we know the market better than the founder. And in almost every case, I’ve regretted that because the reality is, and this is an internal thesis of ours, is the graph in almost every case is just smarter than our theorying. The market actually knows what it wants.

These days, if one of these API companies is doing very well and the usage is great, I’ll give you an example, Hugging Face is a phenomenal company. And if you looked early on at the usage, this thing is a rocket ship, and you can have a bazillion theories why you can’t monetize the model, and you have a bazillion theories of why their go-to market is going to work. But the reality is the market loves it, it’s a great company. For me, it’s almost like a counter thing, which is, I do think that this API makes life a lot easier. You don’t have to have a grand unified theory about how things work, because you can literally just look at how this thing’s being consumed, because the consumptions become so bite-size; you get a lot of early signals. I think it really boils down to…

[00:31:53] Patrick: It comes down to usage.

[00:31:55] Martin: Yeah, to usage.

[00:31:56] Patrick: How should these things be priced? What have you learned about actually building the revenue model around something that looks more usage based? All these examples, AWS, what we started with, these API companies, they tend to be usage-based pricing. So what have you learned about that? Is that the right thing? Do you think that changes?

[00:32:12] Martin: It feels to me though, apps are for seat pricing, and infrastructure is usage pricing, and that’s basically how it is. And if you’re in the frontend, you’re not doing usage pricing, you better get there. You really have to. And if you’re apps, and you can get away from seat pricing, that just seems like that’s where you’ll end up. I do feel that when it comes to company building, there’s a few areas where there’s no simple answers. There’s a lot of stuff that’s systematic, like how do you hire your sales force, it’s pretty systematic. How do you create your org is systematic. But one of the things that’s just not systematic is pricing. Pricing is actually dictated by the shape of the market and the shape of the product. And it takes months to get it right. I’ll give you three mental landmarks, and I think the rest is just actual work.

So one of the mental landmarks is pricing is often fixed by the market. And so you should look at the ecosystem and the other types of companies and how they price and I think you should follow that model. For example, if you’re building on top of Snowflake, how Snowflake charges is going to be very similar to how the customer expects to buy. And if you’re building on top of that, you’re going to want to align with that. And I’ve been in many cases where the companies wanted to innovate on their own pricing model, but the ecosystem alignment just wasn’t there. And it was just painful until they had to change. I think another mental landmark is the market will tell you the price over time, but not initially. The less that you have public or the less that you force your opinion on, the better it is. I do think that a lot of early sales discussions is just to figure out pricing, that’s what it is. Your goal is to reverse engineer how they think about that. The good news is because the consumption is so much higher on these, and the unit of consumption is lower, it’s per API call, there’s kind of a lot of room to experiment…

[00:40:14] Patrick: And as you think about the ways that all of this intersects with the real world now, which we really haven’t talked about. We basically talked about digital infrastructure that leads all the way up to applications at the top end, and the APIs in between and all this great stuff. But it seems also like as we mature, more of this technology will apply to the real world too, whether that’s new kinds of hardware, whether that’s intersection with physical goods like cars. How do you think about that side of things and maybe the hardware world of technology?

[00:40:45] Martin: People have a hard time grasping what, let’s say, AI and ML concretely provide, because it’s such a diluted buzzword. So for everybody that’s listening, the important thing to realize is that what modern AI and ML does, which we’ve never really been able to do before in systems, is take unstructured data, and digitize it, and add it to the typical logic of the program. And we’ve never been able to do this with vision, like objects out in the real world. We’ve never been able to do this with natural language in the level of ASCII we can. We’ve never been able to do this with voice or speech.

That technology just hasn’t existed and so we’ve never been able to build the big programs around them. And now we can, and it’s a sufficiently different workload that two things happen. First, it pushes software into the realm of the physical world. We can now see things and interact with things. And we’re talking quantum leaps of accuracy improvement. It also drives the type of hardware and software that we build, because the workload is so different, right? So we’re seeing tons of innovation all the way down to the ASIC level. Mosaic as a company is building a data center focused just on this type of stuff. So I think that this really is a massive impact on infrastructure at large, not just the infrastructure, but also what sorts of applications software can go after.

[00:42:10] Patrick: It’s very cool to consider what all that might mean. I mean like self-driving cars is like the obvious constant example of what computer vision might allow us to unlock. Obviously, cloud had this crazy impact on the services you consume. It’s unlocked innovation by reducing friction. As you think about what’s going on in the digital infrastructure world, period, what are you most excited about in terms of what it might unlock in the 2020s or over the next decade that maybe we’re just starting to think about?

[00:42:38] Martin: Any problem that human beings go after that’s been outside of the realm of software is currently in the realm of software. And this is farming, agriculture, oceanography, you name it. And so I am a tech optimist and tech maximalist. I think that part of our job is to solve problems. It has really been limited to IT, like information. And now I go from IT to just tech. You look at any industry, any industry at all, and I think that it’ll be touched by this. That’s, to me, just tremendously exciting. What’s interesting, I would just say very quickly is we’re still asking the question. Are these still software companies or something different? So you could say, this is just software going after agriculture. Now you still have a software business, or you could say this is still an agriculture business, or you could say it’s something totally different. That’s a question I’m personally very interested in…

[00:45:34] Patrick: If you put your investor hat on, I guess your purely selfish investor hat, meaning you were just trying to maximize returns, and you could somehow have a crystal ball that would reveal some information about the future, which is currently uncertain, where if you knew what the future was going to hold, be super valuable to you as an investor, trying to earn a return. What would you ask of that crystal ball? Like what would you want to know about the future that you’re not sure which way it will go?

[00:45:58] Martin: I am very curious about where crypto lands, and I think there are three potential views, right? On one end, on the most negative and barren folks are like, “This is all fake. It’s just Ponzi scheme, yada yada, yada.” On the extreme other end, it’s a total reformation, not just of technology and companies, but an organization. This is like everything. You don’t just have routers. You’ve got crypto routers. You don’t have just storage. You have crypto storage. You don’t just have businesses. You’ve got dos. You don’t just have money. You’ve got DeFi, like everything changes. And then there’s a bit of a middle view somewhere. This is a continuum which says, “You know what? There’s something very innovative there on the ability to build networks. There’s a number of primitives that are very innovative on the ability to build applications. There’s a number of innovations on how you offer new services to consumers where you don’t know the endpoints. There’s a lot of great primitives, consumption to monetization layer, just like social was primarily a consumption monetization layer.”

In that future, that layer is on top of a lot of systems, but you still have traditional computer networking and storage. You still have traditional clouds. You still have to know all of those things. And it’s something that’s added to that. And I think the answer to that question given the amount of money that’s already involved is enormous. And I don’t think anybody knows the answer. I tend to be in the middle where I think that there’s a real innovation there. I think there’s real value. I think it’s a real unlock for a lot of new business applications and use cases. But I think that infrastructure itself, a lot of the traditional models still applies. You still have to build databases. You still have to use storage. You still have to understand the trade offs of asset. A lot of these things still apply.

[00:47:41] Patrick: Obviously distributed systems. Some of the smartest people in the world are working in distributed systems, not necessarily crypto networks, but just like the ability to distribute state or update state constantly faster, smoother, or whatever. As an infrastructure person, when you look at the current technology in crypto networks, maybe the dominant three or four, what are you watching or interested by or looking at, the consensus mechanisms, the scaling ability? What are the dimensions that you as an infrastructure person are keyed in on today?

[00:48:10] Martin: The crypto origin solves a very important problem. That’s traditionally not been solved practically. And that is allowing basically an anonymous set of people with no prior trust relationship to have strong guarantees on something, right? Originally it was a ledger, and then it’s become more to generalized compute. That’s a very, very real innovation thing. And that unlocks very, very interesting business use cases like we’ve mentioned. But distributed systems is one of those things that you just can’t paper over with a thin software layer. You can’t hide it under an API. You’ve never been able to. There’s entire languages that just help programmers manage distributed systems. What’s important is what developers end up using, or what distributed paradigms they end up using, because that will drive the capabilities of the system. So if everybody says, “This is a purely distributed world and everything I write must be purely distributed,” that will have some implications of the type of systems that you can build.

So the thing that I’m most interested in as kind of an old distributed systems guy is what are the nature of the applications? Is this going to land in the realm of purely distributed stuff? Is it only embarrassingly parallel applications, like DeFi is an embarrassingly parallel application? There’s other things that are embarrasingly parallel. Or, is this going to go more to the model of general compute? Is that something people are going to do? Are people going to build like the AWS in crypto? The answer to that is actually very, very significant, right? You could say, “Well, listen, traditional distributor systems are great for building AWS, and this is going to just be the consumption monetization layer, or it actually is going to cause innovation in the way that we do distributed programming in the future.” I don’t think that’s clear yet where that’s going to land.

7. Watch: How Does a Dead Fish Swim Upstream? – American Physical Society  

Take a quick look at this trout swimming upstream. Notice anything unusual?

[Video of trout]

You’ve probably seen something similar countless times; the fish wriggles against the currents that push it backwards, slowly making headway until it turns and ducks out of the influence of the stream. Nothing special in that.

The only thing is, this particular fish is dead.

Yes, you read that right. No matter how lifelike it looks as it undulates across the tank, that same trout would just go belly-up if the current were switched off. So how can it possibly swim upstream?

A team of researchers from MIT and Harvard were equally surprised when they happened upon this phenomenon by accident. They’d been studying the way live trout conserve energy by swimming behind obstacles that block the current*, and unintentionally placed a dead fish in the experimental setup. When they took a closer look, they were stunned.

“It was incredible, very counterintuitive,” MIT researcher Michael Triantafyllou says, describing the shock he felt upon seeing the fish swimming upstream. He explains that while he knew trout were good at conserving and even extracting energy, he had no idea that they’d be able to extract enough energy from the surrounding fluid to swim upstream without expending any of their own energy. Immediately, the team started to investigate this new, seemingly impossible phenomenon.

As it turns out, objects that block the natural flow of water, like a rock or a boat, create a series of complex vortices in the current as the water navigates the obstacle. As anyone who’s tried to grab a fish knows, fish are quite flexible all down their spines, which allows the head and the tail to move independently of one another. In certain situations, the array of vortices forming behind an obstacle cause the body and tail to flap in resonance. This tilts the body in such a way that the vortices, which cause a pressure drop, apply a suction force that propels the fish forward.

As Triantafyllou explains, “You have a flow behind the obstacle, which creates a continuous stream of eddies. Each eddy contains energy and also causes the pressure in the fluid to drop… the eddy causes the body to flap back and forth, and the fish manages to extract energy.” Since all of the energy is supplied by the vortices, it doesn’t matter at all whether the fish is alive or dead, if the timing happens to be right.


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google), Amazon, Meta Platforms (formerly known as Facebook), and Zoom Video Communications. Holdings are subject to change at any time.

What We’re Reading (Week Ending 22 May 2022)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 22 May 2022:

1. Flexport: How to Move the World – Mario Gabriele

The name “freight forwarder” is strange. It’s the kind of term whose meaning seems literally evident but is blurred by a sort of tedium-cloud. It is the cousin of descriptors like “insurance agent” and “data analyst.” 

A freight forwarder is a tour guide for objects. Or, at least, that is how I have come to think of it after having it explained to me (and re-explaining it to myself after I have forgotten) by a series of patient people over the years. For, say, a shipment of pillows to make its way from Taiwan to France, it must move between ships, planes, trains, and trucks. As many as twenty different companies may be involved in a single shipment, each handling one stint of the multi-modal journey. Critically, each party is incentivized to care narrowly about their leg rather than the entire trip.

The freight forwarder sees this salmagundi of boats and warehouses and flight maps and says, Don’t worry, I’ll take care of it. With the savvy of a good tour guide, it helps the customer navigate the mess, keeping the itinerary, forewarning chancy routes, bum ports (the “bad neighborhood” of logistics), and charting an optimal path. They are the concierge of conveyance, consiglieri of transit.

As it turns out, this is a big business. The global freight forwarding market is pegged at around $182 billion with projections to reach $221 billion by 2025. That amounts to a modest compound annual growth rate (CAGR) of a tick below 5%.

This is also an extremely fragmented space. As of 2020, DHL Global Express led the market with 6% of annual revenue. Kuehne+Nagel and DSV+GIL followed with 4% each, succeeded by DB Schlenker and Nippon Express at 3%. Fully 60% of the market is composed of “others” – smaller providers that hold less than 2%, and perhaps not more than a few deciles…

…Chen’s primary mission is to guide Flexport into a phase of automation that lays the groundwork for its global trade platform ambitions. When I asked Chen which initiatives best showcased the company’s burgeoning abilities on this front, he shared two examples.

First, Flexport is devoting serious resources to digitizing global trade documents. Ingesting data from different languages and formats is the first step in building a library of “facts” around a shipment. Instead of “optical character recognition,” or OCR, Flexport relies on machine learning models developed with Scale AI. Whereas Flexport used to transform accurate data from documentation in two days or less, the recent partnership has helped the company do it in minutes while maintaining 95% accuracy. Chen noted that the reason accuracy sat short of 100% was not a technical issue but a result of human error at the outset. 

Second, Flexport is developing models to predict when a shipment will arrive to be unloaded at a given port. Getting seemingly simple things right can have meaningful downstream effects. Knowing when a ship is ready to be unloaded influences when a truck should arrive, for example. This, in turn, impacts how a warehouse might organize its space. Just as snafus in one part of the supply chain can lead to misery elsewhere, improvements can create secondary and tertiary efficiencies. According to Chen, Flexport is well-positioned to produce reliable models to this end thanks to its existing freight forwarding business, saying, “We believe we probably have the highest accuracy.”  

2. #028 – PM Lessons by Meituan Co-Founder – Pt 22: Demand and Supply – Tao

Understanding demand and supply is hard. Although you can only be in one of two situations: 1. demand outstrips supply or 2. supply outstrips demand, it’s hard to know at any point in time, which situation you’re in.

In our day-to-day work, these are the common problems that we’d encounter that have to do with demand and supply:

  1. The team doesn’t proactively determine the situation of demand and supply. As a result, the operation lacks focus, and the approach is basically “throw it against the wall and see what sticks“.
  2. The team knows that demand and supply each affects the other, but can’t make a clear judgment about which one is more important.
  3. The judgment about demand and supply is correct, but the operation is not guided by the prevailing demand and supply conditions.

If any of the above three situations occurs, then the team would usually work in the opposite direction of the demand-supply condition. In fact, they may even have a strong incentive to get it wrong!

For example, if a company is in a situation where supply outstrips demand, it should be doing more work on the demand side. In reality though, more often than not, it’s still pushing hard on the supply side.

Why?

If supply outstrips demand, then the demand is very important. The demand side buyers know they’re important, and they’d be very hard to entertain. In comparison, the supply side sellers would be a breeze to spend time with because they’re the ones who are in a hurry and have something to ask for. As such, the team would have a strong incentive to continue working on the supply side and pretend the harder-to-deal-with side is less important. This was a frequent occurrence in Meituan…

…Here’s another example from the retail industry to demonstrate how frequently people get the demand and supply relationship wrong.

I asked the bosses of convenience store and supermarket chains, “In the retail industry, which one is more important, demand or supply?“

Without exception, all of them answered that supply is more important.

It doesn’t gel with my business common sense – with the industrialized manufacturing that we have today, most goods should have more supply than there is demand.

Therefore, the next question to figure out is – is this how they think, or is this how they act?

So I asked them another question, “At your company, what work do you absolutely have to do yourself?“

They all answered, “Choosing the location“. One of them even said he personally chose the location for close to a thousand stores they have all over the country.

For retail, location is the aggregation of demand. They say supply is more important, but their actions are pretty revealing.

3. Arena Show Part I: Idea Dinner + YC Continuity – Benjamin Gilbert, David Rosenthal, Packy McCormick, Mario Gabriele, Shu Nyatta, and Anu Hariharan

Anu: It is so true. I also think it’s really hard to understand and appreciate an organization like YC from the outside. You really deeply understand YC in only two ways, if you’re a YC founder and if you work within YC.

When I was at Andreessen Horowitz, I actually did not understand the depth and the cultural nuance with which YC was built. It’s really hard to grasp that.

David: Can we talk about that for a minute? I put this in the notes. My current mental model of YC is like a university, a top Ivy League University. It’s very hard to get into. You take classes every year or every six months. There’s an endowment attached to it, which is Continuity now.

Ben: Wait, David. What do you mean by endowment? Are you saying that all of the proceeds from YC exits go into a big pool of capital that then funds Continuity? Is that what you’re suggesting by endowment?

David: No, but I’m curious if that’s the case. I meant more just like, it’s really weird that a large part of the private capital markets and the venture capital markets in America, those dollars come from educational institutions, mostly private educational institutions. That’s just very bizarre. Anyway, that’s kind of what I meant. Is that a good mental model of YC? What is it like?

Anu: Yes. In fact, we say that. We say YC is university for startups. Think of the accelerator as the undergraduate program and Continuity is the graduate school.

We are modeled after university in the sense of we have applications you don’t need to know anyone to apply to YC. Second, we were the first to do mass production of investments in a batch of startups. No one had ever done that. Everyone usually does, I met a set of companies, we have a Monday partner meeting, and you pick one or two.

YC from day one was a batch. They always received investments together. That, I think, goes to the insight that the founders of YC had at the time, which was entrepreneurship is lonely. Being in a group is how you motivate each other to learn from each other. And that’s your peer group.

Fundamentally, it came from the approach of a university. Continuity is graduate school. As I talked about, Series A is just one of the programs we run. We have two others, Post-A and Growth. Post-A focuses on two months within you raise the Series A. That’s a six-week program. We rebatch you, so now you have a new set of peers.

Our scale founders come teach how to form a recruiting team, how to hire engineers, because your job changes as a CEO. No one is writing a book about how your job changes and how to learn. Remember, the median age of a YC founder is 27, which means they have probably managed the sum total of three people in their life before these founders.

David: They really are like undergrads.

Anu: Yeah. You cannot expect them to know. How are you going to provide resources so that they can learn from others and they do as few mistakes as possible and as quickly as possible? Because when you’re scaling, you just go on a rocket ship, but the amount you demand out of these founders is a lot. The bar you’re setting is really high.

In our community, that’s why Brian Chesky comes to speak every batch. He’s the opening speaker of every batch. Right now, for all these programs that we run, the group program is how to scale as a CEO. That’s literally the program. It’s an eight-week session. It talks about hiring execs, performance, management, culture, and so on.

We have scaled founders and scaled exec. Tony Xu comes for that. His execs, the CFO of DoorDash, the head of engineering of DoorDash, come for the respective session. It’s really good to see the entire community working to transfer their learnings to the next batch of companies…

…Anu: At YC, I would say, if I had to pick one thing YC is really good at across both early and Continuity is we go by based on founders. I know it sounds cliche, but I think we also have an incredible advantage in assessing what makes a founder a really good founder.

We have incredible amounts of data, pattern recognition, and learning that we have honed it to a point that we know how to spot them. You all have heard of the famous 10-minute YC interview and everyone asks, how do you know in 10 minutes? The fact is we probably know in the first two minutes.

We actually don’t need the full 10 minutes. But sometimes, one or two people will surprise us with the end of the interview. I think the three things that can articulate what it is on the founder we look for.

One is the continuity stitch. Often in the growth stage, people pay attention to the founder, but they don’t. If you’re at a venture fund or a growth fund, you probably hang out with the founder for a week or two weeks before investment, some a total of three hours. By the time Continuity invest, I probably know them for years, or months, and I’ve had those interactions.

Ben: You’re saying that you’re paying attention more to the qualitative founder properties—even at the growth stage—than you are to their specific growth rate, or what their margins look like, or anything like that?

Anu: Yes, but if the three qualities hold, the metrics will show. I can either look at metrics, but sometimes metrics don’t tell you how good the internal sausage making is. Many people can package the metrics in a fundraise deck. It’s very well done. We teach you to do it.

We’re really experts at it. Therefore, we know it’s going to look great. We also teach them what points to emphasize on. We actually do practice runs. In Demo Day, we actually even write the script sometimes if they don’t understand what it is.

David: That’s a how-can-I-help moment.

Anu: Yeah. What we look for is, how fast does the founder move? What is how fast do they move mean? How fast do they ship? How fast do they iterate? Is it single biggest indicator and correlation to how successful they’re going to be and how soon?

You won’t be right about members’ many decisions early on, but at least, are you learning from them fast? And are you making changes? That’s one we measure. Second of the growth stage is how well are you hiring. If you’re sloppy in hiring, it always hits a wall.

One of the things we look for is how well are they hiring engineers, how well are they hiring execs. Will they be able to convince an incredible exec to come join them? That’s second. Third is clarity of thought. Clarity of thought in the growth stage for us is, can they write out two pages what makes this a $5 billion or a $10 billion company really well?

If you’re doing those three things, you’re going to be on top of your metrics, your product-market fit, your attention. There will be rough edges. I think because of YC, we’ve had the benefit of watching everyone from day one.

We know how Tony scaled. We know deeply well how Josh had Gusto scale. We know a lot of those founders. We then know, okay, these were rough edges, these are okay. These other founders had and this is how you and I know.

David: We’ve told a lot of these stories on Acquired. If you’re a growth investor looking at these companies new, you’re like, I know this is all going great, but you know those companies don’t always all go great. Tony had some serious near death moments. Airbnb was not up into the right journey the whole time.

Ben: If I had to summarize, I know we’re interviewing you. Not me here, but it seems like you invest based on the inputs rather than the outputs or maybe the leading indicators rather than the trailing indicators, where if somebody’s operating with those three principles, the business probably won’t consistently produce the results that someone would like to look for in the growth stage investment. They have a much higher probability at any given time of producing high quality results because those are the inputs that matter.

Anu: Absolutely. That’s why we feel strongly that inputs can be influenced. If you’re learning best practices and those are your inputs, then you can actually influence company building. When Tony comes and teaches our Growth Program and says these were my darkest moments, these are my mistakes I made, and I sure hope you don’t make the same mistakes, but these are two things I did really well, that’s incredibly valuable. That color is very hard to get outside of YC.

4. 2022 SaaS Crash – Alex Clayton

The rapid decline in value of public SaaS companies over the past 6 months has undoubtedly already had a huge impact on private market valuations. That downward trajectory may continue even if the public markets stay flat at today’s levels. If public market returns cannot fuel venture capital fundraising from their limited partners, the flywheel will slow down. Investors will have fewer dollars to invest, companies will have less cash to hire and invest in growth, and outcomes are likely to be much smaller than previously thought. This reset has been swift and will soon be painful for many businesses that are burning too much money and/or those that will have to slow top-line growth. Moreover, there will be wide-ranging implications for employees and investors not only in the SaaS community but for all private technology markets.

And while much of the focus has been on the decline in valuations, there is another huge factor that can’t be overlooked – how could a recession or broader economic slowdown affect your financial profile? This could have an even bigger impact on valuations if the fundamentals of businesses change for the worse. While a large part of the sell-off has consisted of a move away from riskier asset classes in sectors such as high-growth SaaS to cash and value stocks, recent earnings results have been strong and business fundamentals have not changed broadly. But what if you traded at 50x forward revenue and are now trading at 10x, and your associated forward revenue also dips by 30-40-50% from your prior plan? The outcome is not pretty and one we have not yet seen, but could soon if the 2008-2009 Great Recession is any indicator.

The following charts look at Salesforce* and NetSuite*, two publicly traded SaaS companies during the 2008 Great Recession, and what happened to their respective value and financial profiles. Unfortunately, while this is a small sample size, these are the best precedents as almost all other SaaS companies went public after the Great Recession…

…Salesforce was almost a $1B implied ARR (annualized revenue run-rate) business growing over 50% year-over-year at the start of 2008. During the Great Recession, revenue growth slowed to 20%. Non-GAAP operating margins did hold fairly steady, though…

…NetSuite was over $160M in implied ARR growing ~45% YoY at the end of 2008 before slowing dramatically. The company did not grow for 3 quarters in a row before accelerating back to growth. Similar to Salesforce, they also held non-GAAP operating margins constant but slowed investment significantly. It would be hard to imagine a ~$150M ARR business today that’s growing fast grinding to a halt, but this happened for NetSuite. The company also sold to SMBs and the mid-market, a segment that was hit particularly hard during the Great Recession.

5. TIP447: How To Build A Human Bias Defense System w/ Gary Mishuris – Trey Lockerbie and Gary Mishuris

Trey Lockerbie (16:25):

Fascinating stuff. So I want to move on to the next one, which is base-rate neglect. So there’s this phrase that’s come up, I don’t know, maybe over the last decade, maybe longer, but it’s don’t fight the Fed. And we’ve seen a lot of help from the Fed when markets have declined in the past and we’ve seen the Fed reverse course on say, raising interest rates quickly due to recessions and other liquidation problems around the world. So from this, we may have misconceived notions on how either the Fed will react to markets if they continue to decline from here, for example, which would thus enact this base-rate neglect human bias. So walk us through what the base-rate neglect bias is and how we might be able to avoid it.

Gary Mishuris (17:05):

Yeah. So I think it’s fascinating that… And I think sometimes people talk about inside view versus outside view. So base-rate neglect refers to ignoring the experience of others in similar situations and just making an assumption based on what we think we can do in this situation. So let’s say a very simplistic example of someone flips coins 1,000 times, they get 50% heads, 50% tails for a fair coin. And somehow we convince ourself that we can take a fair coin and flip tails 70% of the time. And that sounds ridiculous when they phrase it that way, but sometimes essentially that’s what is happening.

Gary Mishuris (17:42):

So, for example, if you study great investment records, which I’m sure you do, you realize that there’s a certain range of access returns over decades that the best investors have been capable of. And if you take Warren Buffett out of the picture and if you take people who use leverage out of the picture, unlevered returns, there’s almost nobody over decades has exceeded 5% per year access returns with no leverage and so forth. Obviously, Buffett has done close to 10, but I don’t think there’s going to be another Buffett necessarily.

Gary Mishuris (18:11):

So when someone shows up and they think they can do 10, what they’re doing is they’re exhibiting example of base-rate neglect. They’re looking at their own strategy and they’re saying, I have these clever mental models, I have this process, I have this special sauce. So they start to believe their own marketing deck a little bit too much, and they forget that the people who tried and failed to achieve the 10% for years, as an example, have also had their special sauce and their analyst teams and this and that, and yet they were only able to do a certain…

Gary Mishuris (18:42):

Think about someone like John Neff who record is public or who had three decades of returns. He beat the market by 3% per year in arguably less efficient markets than they are today. So when someone shows up and says, “Oh, I’m going to beat the market by 10%,” that’s a little bit crazy, it’s a little bit arrogant. And again, I think we’re all overconfident, but come back to the Fed. So look at the last 10 years, we had almost a perfect confluence of events. We had interest rates coming down. We had unrivaled Fed manipulation of markets far beyond just the short term end of the curve. We had maybe as a result there or maybe as a coincidence, huge amount of speculation, both by retail investors and by a number of “institutional” investors, institutional in quotes, not naming any names, don’t ask. And you basically had over the last five years, you had 25% CAGR for large growth stocks or all cap growth stocks.

Gary Mishuris (19:33):

So if you are investing in the universe, it’s pretty easy to start believing your own BS and start saying, well, gee, yeah, no, I can crush the… I can do 20, 25% per year, but like really? Let’s zoom out over the long term US equities return inflation plus six to seven, depending on the time period. So if you think you can do 20% plus, you think you’re going to beat the market by double digit percent per year. And I know everyone thinks they’re very special, but that’s just a perfect example of the inside view. The inside view is all these specific details for why the past experience of others doesn’t matter. And the base rate is the past experience of others in a similar situation. And I think the best thing you can do is zoom out and say, “Well, whatever I think about my own capabilities, let me put a heavy weight on the experience of others and a small weight on why I think I’m going to do so much better.” And that’s probably the best you can do.

Trey Lockerbie (20:25):

That’s interesting, because I was wondering the distinction here between say the base-rate neglect effect versus say the recency bias effect, because what I was describing, I don’t know, it could maybe fall into both categories depending on how you look at it. So recency bias is when you’re essentially taking events from the past and extrapolating them into the future. So how exactly is that different or what are maybe some other distinctions between that and the base-rate neglect effect?

Gary Mishuris (20:49):

So I think a recency bias is almost a special case of base-rate neglect. So what are some examples of recency bias? Let’s say you have a company over the last couple of years, it’s been growing 30% per year and you assume it’s going to grow at 30% per year for the next one year. I’m obviously using extreme example. So that’s recency bias. You take a near term past and assume that’s going to be the same in the long term future. On the other side, let’s say you have a company that over the cycle has barely earned its cost of capital and averaged a dollar per share. But now the last couple of years been earning $2 per share and averaging 20% return on capital. So you are going to extrapolate that $2 and assume that’s the new normalized earnings for the business and say the new long term average earnings is $2. And this now all of a sudden, the 20% return on capital business or something like that.

Gary Mishuris (21:40):

In each case, you’re ignoring the base rate, the base rate in this case being the history of the company or the history of similar companies. So in the first case, the history of companies growing 30% for two years is mean version in the growth rate towards the growth rate in all companies. So just to level set everything that the average company’s profits over long periods of time grow in line with nominal GDP. But, by the way, ironically, if you look at Wall Street estimates, hey, now they assume the average company grow is going to grow earnings in double digits. Well, it hasn’t, it’s been growing five to 6%. And that’s an example of base-rate neglect because they forget that a fifth of the market is going to have negative earnings growth, but that’s a separate thing.

Gary Mishuris (22:20):

And then the base rate for a company that’s been earning its cost of capital and had a couple of good years is that the long term history is much more likely to be the best predictor than the last couple of years, which could be a cyclical high or something like that. So I think ignoring the base rate leads to the recency bias, where we put a disproportionate weight on what just happened and assume that’s a proxy for what’s going to happen as opposed to zooming out and looking at a much longer data series…

…Gary Mishuris (54:36):

And like you said, if you have areas where you don’t invest, that squeezes those 10 to 15 investments into the rest of the opportunity set, meaning that you might be correlated. But it’s not about gig sectors, which is a common misconception. So I’ll give you an example. So prior to starting Silver Ring, I managed a fund at my prior employer and I had two investments. One was SABMiller, which was a beer company, and the second one was Qualcomm. If you are running some bar risk model, and you’re looking at overlap, they’re completely different gig sectors. One is technology, the other is consumer. So no relationship, you’re good, you’re diversified. But the thesis for each one was predicated on rising middle class in emerging markets, meaning people were going to trade up and buy more expensive beer in China and other emerging economies and people were going to trade up to fancier smartphones, which was going to drive demand for Qualcomm’s products.

Gary Mishuris (55:28):

So here are two completely different industries where the same macro force, which is a tailwind, if it doesn’t play out would hurt the thesis. So looking for those correlations as systematically as possible, and thinking about what do I have to be right about each business five plus years out as opposed to what do I have to be right about each stock five quarters out, that’s the mindset you want to have. And also frankly, you have a set of risk reward trade-offs. Too many people make the mistake of sizing their largest investments based on upside. But again, going back to the safety first mentality, I size my positions based on downside, meaning my largest investments have the smallest downside. I have an investment, which maybe it’s a 30% of my base case value as to 30 cents in a dollar, but if that has 100% downside, that might not be my biggest position. So again, you want to have multiple layers of defense.

6. The Transcript Q1 2022 Letter – Scott Krisiloff and Erick Mokaya

Investors are asking whether this is the end of an era. For nearly 15 years global policymakers have battled a deflationary mindset with near-zero interest rates and quantitative easing. However, a series of supply chain shocks and monetary policy errors have sparked rising long-term inflation expectations. If we have exited the deflation era and entered into an inflationary one, it will mean structural changes in monetary policy, interest rates, and stock multiples. By the Fed’s own account, despite raising interest rates by 0.75% so far this year, it is still only on pace to get to a neutral interest rate by the end of the year. It has not yet entered the restrictive territory, which would usually be justified by >8% inflation.

“We’ve been accustomed to 40 years, basically, of one cycle, the whole cycle that we covered in the last quarterly review. Declining interest rates, declining tax rates, all these trends – – it’s all come to an end. Not just an end, it’s actually changing. But people haven’t wrapped their heads around that yet…There’s going to be a new cycle.” – Horizon Kinetics (INFL) Co-Founder Steven Bregman

“An entire generation of entrepreneurs & tech investors built their entire perspectives on valuation during the second half of a 13-year amazing bull market run. The “unlearning” process could be painful, surprising, & unsettling to many. I anticipate denial.” – Benchmark Capital General Partner Bill Gurley

While the Fed has talked about getting to “neutral” throughout this quarter, it hasn’t yet set an expectation for what neutral means. There seems to be some consensus that this neutral rate would be a short-term interest rate in the 2.5% – 3.5% range. Equity markets may not yet reflect this new cost of capital.

“I think I’m in the same areas as my colleagues philosophically. I think it’s really important that we get to neutral and do that in an expeditious way. “ – Atlanta Fed President Raphael Bostic

“I like to think of it as expeditiously marching towards neutral. It’s clear the economy doesn’t need the accommodation we’re providing. And so in order not to tip the economy over by reacting abruptly, we need to take a measured pace. But that measured pace still gets us up to the neutral rate, which I put at about 2.5% by the end of the year.” – San Francisco President Mary Daly…

…The Transcript is also closely watching continued lockdowns in China. The Chinese government’s zero-Covid policy has left hundreds of millions of people in lockdown even though the rest of the world has returned to normal. The effects of this supply chain shock have still not entirely made their way into the economic discussion.

“I think a separate risk is kind of the impact of logistics and supply chains as we deliver product to China and from a more macro perspective just the port closures and the broader impact that we could see in China given the degree of exports they have just generally across the economy. With respect to the China quota difficult to predict.” – Intuitive Surgical (ISRG) CFO Jamie Samath

“...the situation in China is unprecedented. Shanghai, a city 4x the size of New York City, is completely locked down…China continues to battle COVID resurgences and navigate through prolonged lockdowns.” – Starbucks (SBUX) CEO Howard Schultz…

…Surprisingly, consumer spending has still only been moderately affected by surging inflation and falling financial markets. The covid-era stimulus has left consumer bank accounts with lots of reserves and consumers still have a significant amount of pent-up demand for travel, restaurants, and other entertainment. We are expecting to see some slowing of consumer spending and the real economy going forward in sympathy with the dynamics of capital markets.

“March was the eighth straight month in which inflation outpaced income with lower-income consumers being most impacted by rising energy and food prices.” – Wells Fargo (WFC) CEO Charlie Scharf

“Consumers are trying to ration their money a little bit more carefully because they’re trying to smooth out their cash flow.” – Affirm (AFRM) CEO Max Levchin

“when we think about where inflation is, there’s absolutely pressure on that low and middle income consumer.” – Macy’s (M) CEO Adrian V. Mitchell…

…No one really knows whether this is truly the end of an era and the start of an inflationary epoch, but this period is not without historical analogue. The transition from the deflationary 1930s to the inflationary 1940s was caused by World War II, which was also a time of intense supply chain disruptions coupled with huge economic stimulus. The Covid period has some similarities. Immediately following the war there was sharp and severe inflation for several years, which was ultimately brought under control by changes in monetary policy. In the longer term, huge investment in industrial capacity and human capital led to a consumer renaissance and low inflation in the 1950s.

The inflationary period of 1966-1980 is also worth studying if we are entering a new inflationary phase. An important takeaway from that period is that a surge in interest rates does not necessarily happen overnight. Instead, it happened in fits and starts over the course of several bear markets and recessions. Stock multiples ended that period in single digits, but the nominal value of the Dow hovered around 1,000 for more than a decade.

We may be entering a period in which the Fed raises interest rates more frequently than it lowers them, but the Fed is still very reluctant to cause a recession. If it looks like higher interest rates are putting employment at risk, the Fed is likely to abruptly change course despite inflation. The result would probably be positive for capital market valuations.

“You can’t think of a worse environment than where we are right now for financial assets..I think we’re in one of those very difficult periods where simply capital preservation is I think the most important thing we can strive for. I don’t know if it’s going to be one of those periods where you’re actually trying to make money.” – Tudor Investment Corporation Co-Founder Paul Tudor Jones

7. Trying Too Hard – Morgan Housel

Thomas McCrae was a young 19th Century doctor still unsure of his skills. One day he diagnosed a patient with a common, insignificant stomach ailment. McCrae’s medical school professor watched the diagnosis and interrupted with every student’s nightmare: In fact, the patient had a rare and serious disease. McCrae had never heard of it.

The diagnosis required immediate surgery. After opening the patient up, the professor realized that McCrae’s initial diagnosis was correct. The patient was fine.

McCrae later wrote that he actually felt fortunate for having never heard of the rare disease.

It allowed his mind settle on the most likely diagnosis, rather than be burdened by searching for rare diseases, like his more-educated professor. He wrote: “The moral of this is not that ignorance is an advantage. But some of us are too much attracted by the thought of rare things and forget the law of averages in diagnosis.”

A truth that applies to almost every field is that it’s possible to try too hard, and when doing so you can get worse results than those who knew less, cared less, and put in less effort than you did…

…But there are mistakes that only an expert can make. Errors – often catastrophic – that novices aren’t smart enough to make because they lack the information and experience needed to try to exploit an opportunity that doesn’t exist…

…Marc Andreessen explained how this has worked in tech: “All of the ideas that people had in the 1990s were basically all correct. They were just early.” The infrastructure necessary to make most tech businesses work didn’t exist in the 1990s. But it does exist today. So almost every business plan that was mocked for being a ridiculous idea that failed is now, 20 years later, a viable industry. Pets.com was ridiculed – how could that ever work? – but Chewy is now worth more than $10 billion.

Experiencing what didn’t work in 1995 may have left you incapable of realizing what could work in 2015. The experts of one era were disadvantaged over the new crop of thinkers who weren’t burdened with old wisdom…

…Doctors have their own version, as one article highlights:

“Almost all medical professionals have seen what we call “futile care” being performed on people. That’s when doctors bring the cutting edge of technology to bear on a grievously ill person near the end of life. The patient will get cut open, perforated with tubes, hooked up to machines, and assaulted with drugs. All of this occurs in the Intensive Care Unit at a cost of tens of thousands of dollars a day.

What it buys is misery we would not inflict on a terrorist. I cannot count the number of times fellow physicians have told me, in words that vary only slightly, “Promise me if you find me like this that you’ll kill me.” They mean it. Some medical personnel wear medallions stamped “NO CODE” to tell physicians not to perform CPR on them. I have even seen it as a tattoo.

The trouble is that even doctors who hate to administer futile care must find a way to address the wishes of patients and families. Imagine, once again, the emergency room with those grieving, possibly hysterical, family members. They do not know the doctor. Establishing trust and confidence under such circumstances is a very delicate thing. People are prepared to think the doctor is acting out of base motives, trying to save time, or money, or effort, especially if the doctor is advising against further treatment.”


Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. Of all the companies mentioned, we currently have a vested interest in Intuitive Surgical, Meituan, Salesforce, and Starbucks. Holdings are subject to change at any time.