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Saying Goodbye: 10 Years, a 19% Annual Return, and 17 Investing Lessons

9 years 7 months and 6 days. This is how much time has passed since I started managing my family’s investment portfolio of US stocks on 26 October 2010. 19.5% versus 12.7%. These are the respective annual returns of my family’s portfolio (without dividends) and the S&P 500 (with dividends) in that period.

As of 31 May 2020

I will soon have to say goodbye to the portfolio. Jeremy Chia (my blogging partner) and myself have co-founded a global equities investment fund. As a result, the lion’s share of my family’s investment portfolio will soon be liquidated so that the cash can be invested in the fund. 

The global equities investment fund will be investing with the same investment philosophy that underpins my family’s portfolio, so the journey continues. But my heart’s still heavy at having to let the family portfolio go. It has been a huge part of my life for the past 9 years 7 months and 6 days, and I’m proud of what I’ve achieved (I hope my parents are too!).

In the nearly-10 years managing the portfolio, I’ve learnt plenty of investing lessons. I want to share them here, to benefit those of you who are reading, and to mark the end of my personal journey and the beginning of a new adventure. I did not specifically pick any number of lessons to share. I’m documenting everything that’s in my head after a long period of reflection. 

Do note that my lessons may not be timeless, because things change in the markets. But for now, they are the key lessons I’ve picked up. 

Lesson 1: Focus on business fundamentals, not macroeconomic or geopolitical developments – there are always things to worry about

My family’s portfolio has many stocks that have gone up multiple times in value. A sample is given below:

Some of them are among the very first few stocks I bought; some were bought in more recent years. But what’s interesting is that these stocks produced their gains while the world experienced one crisis after another.

You see, there were always things to worry about in the geopolitical and macroeconomic landscape since I started investing. Here’s a short and incomplete list (you may realise how inconsequential most of these events are today, even though they seemed to be huge when they occurred):

  • 2010 – European debt crisis; BP oil spill; May 2010 Flash Crash
  • 2011 – Japan earthquake; Middle East uprising
  • 2012 – Potential Greek exit from Eurozone; Hurricane Sandy
  • 2013 – Cyprus bank bailouts; US government shutdown; Thailand uprising
  • 2014 – Oil price collapse
  • 2015 – Crash in Euro dollar against the Swiss Franc; Greece debt crisis
  • 2016 – Brexit; Italy banking crisis
  • 2017 – Bank of England hikes interest rates for first time in 10 years
  • 2018 – US-China trade war
  • 2019 – Australia bushfires; US President impeachment; appearance of COVID-19 in China
  • 2020 (thus far) – COVID-19 becomes global pandemic

The stocks mentioned in the table above produced strong business growth over the years I’ve owned them. This business growth has been a big factor in the returns they have delivered for my family’s portfolio. When I was studying them, my focus was on their business fundamentals – and this focus has served me well.

In a 1998 lecture for MBA students, Warren Buffett was asked about his views on the then “tenuous economic situation and interest rates.“ He responded:

“I don’t think about the macro stuff. What you really want to do in investments is figure out what is important and knowable. If it is unimportant and unknowable, you forget about it. What you talk about is important but, in my view, it is not knowable.

Understanding Coca-Cola is knowable or Wrigley’s or Eastman Kodak. You can understand those businesses that are knowable. Whether it turns out to be important depends where your valuation leads you and the firm’s price and all that. But we have never not bought or bought a business because of any macro feeling of any kind because it doesn’t make any difference.

Let’s say in 1972 when we bought See’s Candy, I think Nixon [referring to former US President, Richard Nixon] put on the price controls a little bit later, but so what! We would have missed a chance to buy something for [US]$25 million that is producing [US]$60 million pre-tax now. We don’t want to pass up the chance to do something intelligent because of some prediction about something we are no good on anyway.”

Lesson 2: Adding to winners work

I’ve never shied away from adding to the winners in my portfolio, and this has worked out well. Here’s a sample, using some of the same stocks shown in the table in Lesson 1.

Adding to winners is hard to achieve, psychologically. As humans, we tend to anchor to the price we first paid for a stock. After a stock has risen significantly, it’s hard to still see it as a bargain. But I’ll argue that it is stocks that have risen significantly over a long period of time that are the good bargains. It’s counterintuitive, but hear me out.

The logic here rests on the idea that stocks do well over time if their underlying businesses do well. So, the stocks in my portfolio that have risen significantly over a number of years are likely – though not always – the ones with businesses that are firing on all cylinders. And stocks with businesses that are firing on all cylinders are exactly the ones I want to invest in. 

Lesson 3: The next Amazon, is Amazon

When I first bought shares of Amazon in April 2014 at US$313, its share price was already more than 200 times higher than its IPO share price of US$1.50 in May 1997. That was an amazing annual return of around 37%.

But from the time I first invested in Amazon in April 2014 to today, its share price has increased by an even more impressive annual rate of 40%. Of course, it is unrealistic to expect Amazon to grow by a further 200 times in value from its April 2014 level over a reasonable multi-year time frame. But a stock that has done very well for a long period of time can continue delivering a great return. Winners often keep on winning.    

Lesson 4: Focus on business quality and don’t obsess over valuation

It is possible to overpay for a company’s shares. This is why we need to think about the valuation of a business. But I think it is far more important to focus on the quality of a business – such as its growth prospects and the capability of the management team – than on its valuation.

If I use Amazon as an example, its shares carried a high price-to-free cash flow (P/FCF) ratio of 72 when I first invested in the company in April 2014. But Amazon’s free cash flow per share has increased by 1,000% in total (or 48% annually) from US$4.37 back then to US$48.10 now, resulting in the overall gain of 681% in its share price.

Great companies could grow into their high valuations. Amazon’s P/FCF ratio, using my April 2014 purchase price and the company’s current free cash flow per share, is just 6.5 (now that’s a value stock!). But there’s no fixed formula that can tell you what valuation is too high for a stock. It boils down to subjective judgement that is sometimes even as squishy as an intuitive feeling. This is one of the unfortunate realities of investing. Not everything can be quantified.   

Lesson 5: The big can become bigger – don’t obsess over a company’s market capitalisation

I’ve yet to mention Mastercard, but I first invested in shares of the credit card company on 3 December 2014 at US$89 apiece. Back then, it already had a huge market capitalisation of around US$100 billion, according to data from Ycharts. Today, Mastercard’s share price is US$301, up more than 200% from my initial investment. 

A company’s market capitalisation alone does not tell us much. It is the company’s (1) valuation, (2) size of the business, and (3) addressable market, that can give us clues on whether it could be a good investment opportunity. In December 2014, Mastercard’s price-to-earnings (P/E) ratio and revenue were both reasonable at around 35 and US$9.2 billion, respectively. Meanwhile, the company’s market opportunity still looked significant, since cashless transactions represented just 15% of total transactions in the world back then.

Lesson 6: Don’t ignore “obvious” companies just because they’re well known

Sticking with Mastercard, it was an obvious company that was already well-known when I first invested in its shares. In the first nine months of 2014, Mastercard had more than 2 billion credit cards in circulation and had processed more than 31.4 billion transactions. Everyone could see Mastercard and know that it was a great business. It was growing rapidly and consistently, and its profit and free cash flow margins were off the charts (nearly 40% for both).

The company’s high quality was recognised by the market – its P/E ratio was high in late 2014 as I mentioned earlier. But Mastercard still delivered a fantastic annual return of around 25% from my December 2014 investment.

I recently discovered a poetic quote by philosopher Arthur Schopenhauer: “The task is… not so much to see what no one has yet seen, but to think what nobody has yet thought, about that which everyone sees.” This is so applicable to investing.

Profitable investment opportunities can still be found by thinking differently about the data that everyone else has. It was obvious to the market back in December 2014 that Mastercard was a great business and its shares were valued highly because of this. But by thinking differently – with a longer-term point of view – I saw that Mastercard could grow at high rates for a very long period of time, making its shares a worthy long-term investment. From December 2014 to today, Mastercard’s free cash flow per share has increased by 158% in total, or 19% per year. Not too shabby.   

Lesson 7: Be willing to lose sometimes

We need to take risks when investing. When I first invested in Shopify in September 2016, it had a price-to-sales (P/S) ratio of around 12, which is really high for a company with a long history of making losses and producing meagre cash flow. But Shopify also had a visionary leader who dared to think and act long-term. Tobi Lütke, Shopify’s CEO and co-founder, penned the following in his letter to investors in the company’s 2015 IPO prospectus (emphases are mine):

“Over the years we’ve also helped foster a large ecosystem that has grown up around Shopify. App developers, design agencies, and theme designers have built businesses of their own by creating value for merchants on the Shopify platform. Instead of stifling this enthusiastic pool of talent and carving out the profits for ourselves, we’ve made a point of supporting our partners and aligning their interests with our own. In order to build long-term value, we decided to forgo short-term revenue opportunities and nurture the people who were putting their trust in Shopify. As a result, today there are thousands of partners that have built businesses around Shopify by creating custom apps, custom themes, or any number of other services for Shopify merchants.

This is a prime example of how we approach value and something that potential investors must understand: we do not chase revenue as the primary driver of our business. Shopify has been about empowering merchants since it was founded, and we have always prioritized long term value over short-term revenue opportunities. We don’t see this changing…

… I want Shopify to be a company that sees the next century. To get us there we not only have to correctly predict future commerce trends and technology, but be the ones that push the entire industry forward. Shopify was initially built in a world where merchants were simply looking for a homepage for their business. By accurately predicting how the commerce world would be changing, and building what our merchants would need next, we taught them to expect so much more from their software.

These underlying aspirations and values drive our mission: make commerce better for everyone. I hope you’ll join us.”       

Shopify was a risky proposition. But it paid off handsomely. In investing, I think we have to be willing to take risks and accept that we can lose at times. But failing at risk-taking from time to time does not mean our portfolios have to be ruined. We can take intelligent risks by sizing our positions appropriately. Tom Engle is part of The Motley Fool’s investing team in the US. He’s one of the best investors the world has never heard of. When it comes to investing in risky stocks that have the potential for huge returns, Tom has a phrase I love: “If it works out, a little is all you need; if it doesn’t, a little is all you want.” 

I also want to share a story I once heard from The Motley Fool’s co-founder Tom Gardner. Once, a top-tier venture capital firm in the US wanted to improve the hit-rate of the investments it was making. So the VC firm’s leaders came up with a process for the analysts that could reduce investing errors. The firm succeeded in improving its hit-rate (the percentage of investments that make money). But interestingly, its overall rate of return became lower. That’s because the VC firm, in its quest to lower mistakes, also passed on investing in highly risky potential moonshots that could generate tremendous returns.

The success of one Shopify can make up for the mistakes of many other risky bets that flame out. To hit a home run, we must be willing to miss at times.  

Lesson 8: The money is made on the holding, not the buying and selling

My family’s investment portfolio has over 50 stocks. It’s a collection that was built steadily over time, starting with the purchase of just six stocks on 26 October 2010. In the 9 years, 7 months and 6 days since, I’ve only ever sold two stocks voluntarily: (1) Atwood Oceanics, an owner of oil rigs; and (2) National Oilwell Varco, a supplier of parts and equipment that keep oil rigs running. Both stocks were bought on 26 October 2010.

David Gardner is also one of the co-founders of The Motley Fool (Tom Gardner is his brother). There’s something profound David once said about portfolio management that resonates with me:

“Make your portfolio reflect your best vision for our future.” 

The sales of Atwood Oceanics and National Oilwell Varco happened because of David’s words. Part of the vision I have for the future is a world where our energy-needs are met entirely by renewable sources that do not harm the precious environment we live in. For this reason, I made the rare decision to voluntarily part ways with Atwood Oceanics and National Oilwell Varco in September 2016 and June 2017, respectively.

My aversion to selling is by design – because I believe it strengthens my discipline in holding onto the winners in my family’s portfolio. Many investors tend to cut their winners and hold onto their losers. Even in my earliest days as an investor, I recognised the importance of holding onto the winners in driving my family portfolio’s return. Being very slow to sell stocks has helped me hone the discipline of holding onto the winners. And this discipline has been a very important contributor to the long run performance of my family’s portfolio.

The great Charlie Munger has a saying that one of the keys to investing success is “sitting on your ass.” I agree. Patience is a virtue. And talking about patience… 

Lesson 9: Be patient – some great things take time

Some of my big winners needed only a short while before they took off. But there are some that needed significantly more time. Activision Blizzard is one such example. As I mentioned earlier, I invested in its shares in October 2010. Then, Activision Blizzard’s share price went nowhere for more than two years before it started rocketing higher.

Peter Lynch once said: “In my investing career, the best gains usually have come in the third or fourth year, not in the third or fourth week or the third or fourth month.” The stock market does not move according to our own clock. So patience is often needed.

Lesson 10: Management is the ultimate source of a company’s economic moat

In my early days as an investor, I looked for quantifiable economic moats. These are traits in a company such as (1) having a network effect, (2) being a low-cost producer, (3) delivering a product or service that carries a high switching cost for customers, (4) possessing intangible assets such as intellectual property, and (5) having efficient scale in production. 

But the more I thought about it, the more I realised that a company’s management team is the true source of its economic moat, or lack thereof.

Today, Netflix has the largest global streaming audience with a pool of 183 million subscribers around the world. Having this huge base of subscribers means that Netflix has an efficient scale in producing content, because the costs can be spread over many subscribers. Its streaming competitors do not have this luxury. But this scale did not appear from thin air. It arose because of Netflix’s CEO and co-founder, Reed Hastings, and his leadership team.

The company was an early pioneer in the streaming business when it launched its streaming service in 2007. In fact, Netflix probably wanted to introduce streaming even from its earliest days. Hastings said the following in a 2007 interview with Fortune magazine: 

“We named the company Netflix for a reason; we didn’t name it DVDs-by-mail. The opportunity for Netflix online arrives when we can deliver content to the TV without any intermediary device.”

When Netflix first started streaming, the content came from third-party producers. In 2013, the company launched its first slate of original programming. Since then, Netflix has ramped up its original content budget significantly. The spending has been done smartly, as Netflix has found plenty of success with its original programming. For instance, in 2013, the company became the first streaming provider to be nominated for a primetime Emmy. And in 2018 and 2019, the company snagged 23 and 27 Emmy wins, respectively.  

A company’s current moat is the result of management’s past actions; a company’s future moat is the result of management’s current actions. Management is what creates the economic moat.

Lesson 11: Volatility in stocks is a feature, not a bug

Looking at the table in Lesson 1, you may think that my investment in Netflix was smooth-sailing. It’s actually the opposite. 

I first invested in Netflix shares on 15 September 2011 at US$26 after the stock price had fallen by nearly 40% from US$41 in July 2011. But the stock price kept declining afterward, and I bought more shares at US$16 on 20 March 2012. More pain was to come. In August 2012, Netflix’s share price bottomed at less than US$8, resulting in declines of more than 70% from my first purchase, and 50% from my second.  

My Netflix investment was a trial by fire for a then-young investor – I had started investing barely a year ago before I bought my first Netflix shares. But I did not panic and I was not emotionally affected. I already knew that stocks – even the best performing ones – are volatile over the short run. But my experience with Netflix drove the point even deeper into my brain.

Lesson 12: Be humble – there’s so much we don’t know

My investment philosophy is built on the premise that a stock will do well over time if its business does well too. But how does this happen?

In the 1950s, lawmakers in the US commissioned an investigation to determine if the stock market back then was too richly priced. The Dow (a major US stock market benchmark) had exceeded its peak seen in 1929 before the Great Depression tore up the US market and economy. Ben Graham, the legendary father of value investing, was asked to participate as an expert on the stock market. Here’s an exchange during the investigation that’s relevant to my discussion:

Question to Graham: When you find a special situation and you decide, just for illustration, that you can buy for 10 and it is worth 30, and you take a position, and then you cannot realize it until a lot of other people decide it is worth 30, how is that process brought about – by advertising, or what happens?

Graham’s response: That is one of the mysteries of our business, and it is a mystery to me as well as to everybody else. We know from experience that eventually the market catches up with value. It realizes it in one way or another.”   

More than 60 years ago, one of the most esteemed figures in the investment business had no idea how stock prices seemed to eventually reflect their underlying economic values. Today, I’m still unable to find any answer. If you’ve seen any clues, please let me know! This goes to show that there’s so much I don’t know about the stock market. It’s also a fantastic reminder for me to always remain humble and be constantly learning. Ego is the enemy.  

Lesson 13: Knowledge compounds, and read outside of finance

Warren Buffett once told a bunch of students to “read 500 pages… every day.” He added, “That’s how knowledge works. It builds up, like compound interest. All of you can do it, but I guarantee not many of you will do it.” 

I definitely have not done it. I read every day, but I’m nowhere close to the 500 pages that Buffett mentioned. Nonetheless, I have experienced first hand how knowledge compounds. Over time, I’ve been able to connect the dots faster when I analyse a company. And for companies that I’ve owned shares of for years, I don’t need to spend much time to keep up with their developments because of the knowledge I’ve acquired over the years.

Reading outside of finance has also been really useful for me. I have a firm belief that investing is only 5% finance and 95% everything else. Reading about psychology, society, history, science etc. can make us even better investors than someone who’s buried neck-deep in only finance books. Having a broad knowledge base helps us think about issues from multiple angles. This brings me to Arthur Schopenhauer’s quote I mentioned earlier in Lesson 6:  “The task is… not so much to see what no one has yet seen, but to think what nobody has yet thought, about that which everyone sees.”

Lesson 14: The squishy things matter

Investing is part art and part science. But is it more art than science? I think so. The squishy, unquantifiable things matter. That’s because investing is about businesses, and building businesses involves squishy things.

Jeff Bezos said it best in his 2005 Amazon shareholders’ letter (emphases are mine):

As our shareholders know, we have made a decision to continuously and significantly lower prices for customers year after year as our efficiency and scale make it possible. This is an example of a very important decision that cannot be made in a math-based way.

In fact, when we lower prices, we go against the math that we can do, which always says that the smart move is to raise prices. We have significant data related to price elasticity. With fair accuracy, we can predict that a price reduction of a certain percentage will result in an increase in units sold of a certain percentage. With rare exceptions, the volume increase in the short term is never enough to pay for the price decrease.

However, our quantitative understanding of elasticity is short-term. We can estimate what a price reduction will do this week and this quarter. But we cannot numerically estimate the effect that consistently lowering prices will have on our business over five years or ten years or more.

Our judgment is that relentlessly returning efficiency improvements and scale economies to customers in the form of lower prices creates a virtuous cycle that leads over the long term to a much larger dollar amount of free cash flow, and thereby to a much more valuable Amazon.com. We’ve made similar judgments around Free Super Saver Shipping and Amazon Prime, both of which are expensive in the short term and—we believe—important and valuable in the long term.”

On a related note, I was also attracted to Shopify when I came across Tobi Lütke’s letter to investors that I referenced in Lesson 7. I saw in Lütke the same ability to stomach short-term pain, and the drive toward producing long-term value, that I noticed in Bezos. This is also a great example of how knowledge compounds. 

Lesson 15: I can never do it alone

Aaron Bush is one of the best investors I know of at The Motley Fool, and he recently created one of the best investing-related tweet-storms I have seen. In one of his tweets, he said: “Collaboration can go too far. Surrounding yourself with a great team or community is critical, but the moment decision-making authority veers democratic your returns will begin to mean-revert.” 

I agree with everything Aaron said. Investment decision-making should never involve large teams. But at the same time, having a community or team around us is incredibly important for our development; their presence enables us to view a problem from many angles, and it helps with information gathering and curation.

I joined one of The Motley Fool’s investment newsletter services in 2010 as a customer. The service had wonderful online forums and this dramatically accelerated my learning curve. In 2013, I had the fortune to join an informal investment club in Singapore named Kairos Research. It was founded by Stanley Lim, Cheong Mun Hong, and Willie Keng. They are also the founders of the excellent Asia-focused investment education website, Value Invest Asia. I’ve been a part of Kairos since and have benefited greatly. I’ve made life-long friends and met countless thoughtful, kind, humble, and whip-smart people who have a deep passion for investing and knowledge. The Motley Fool’s online forums and the people in Kairos have helped me become a better human being and investor over the years.   

I’ve also noticed – in these group interactions – that the more I’m willing to give, the more I receive. Giving unconditionally and sincerely without expecting anything in return, paradoxically, results in us having more. Giving is a superpower. 

Lesson 16: Be honest with myself about what I don’t know

When we taste success in the markets, it’s easy for ego to enter the picture. We may look into the mirror and proclaim: “I’m a special investor! I’ve been great at picking growth stocks – this knowledge must definitely translate to trading options, shorting commodities, and underwriting exotic derivatives. They, just like growth stocks, are all a part of finance, isn’t it?” 

This is where trouble comes. The entrance of ego is the seed of future failure. In the biography of Warren Buffett, The Snowball: Warren Buffett and the Business of Life, author Alice Schroeder shared this passage about Charlie Munger:

“[Munger] dread falling prey to what a Harvard Law School classmate of his had called “the Shoe Button Complex.”

“His father commuted daily with the same group of men,” Munger said. “One of them had managed to corner the market in shoe buttons – a really small market, but he had it all. He pontificated on every subject, all subjects imaginable. Cornering the market on shoe buttons made him an expert on everything. Warren and I have always sensed it would be a big mistake to behave that way.”

The Shoe Button Complex can be applied in a narrower sense to investing too. Just because I know something about the market does not mean I know everything. For example, a few years after I invested in Atwood Oceanics and National Oilwell Varco, I realised I was in over my head. I have no ability to predict commodity prices, but the business-health of the two companies depends on the price of oil. Since I came to the realisation, I have stayed away from additional commodity-related companies. In another instance, I know I can’t predict the movement of interest rates, so I’ve never made any investment decision that depended on interest rates as the main driver. 

Lesson 17: Be rationally optimistic

In Lesson 1, I showed that the world had lurched from one crisis to another over the past decade. And of course, we’re currently battling COVID-19 now. But I’m still optimistic about tomorrow. This is because one key thing I’ve learnt about humanity is that our progress has never happened smoothly. It took us only 66 years to go from the first demonstration of manned flight by the Wright brothers at Kitty Hawk to putting a man on the moon. But in between was World War II, a brutal battle across the globe from 1939 to 1945 that killed an estimated 66 million, according to National Geographic. 

This is how progress is made, through the broken pieces of the mess that Mother Nature and our own mistakes create. Morgan Housel has the best description of this form of rational optimism that I’ve come across: 

“A real optimist wakes up every morning knowing lots of stuff is broken, and more stuff is about to break.

Big stuff. Important stuff. Stuff that will make his life miserable. He’s 100% sure of it.

He starts his day knowing a chain of disappointments awaits him at work. Doomed projects. Products that will lose money. Coworkers quitting. He knows that he lives in an economy due for a recession, unemployment surely to rise. He invests his money in a stock market that will crash. Maybe soon. Maybe by a lot. This is his base case.

He reads the news with angst. It’s a fragile world. Every generation has been hit with a defining shock. Wars, recessions, political crises. He knows his generation is no different.

This is a real optimist. He’s an optimist because he knows all this stuff does not preclude eventual growth and improvement. The bad stuff is a necessary and normal path that things getting better over time rides on. Progress happens when people learn something new. And they learn the most, as a group, when stuff breaks. It’s essential.

So he expects the world around him to break all the time. But he knows – as a matter of faith – that if he can survive the day-to-day fractures, he’ll capture the up-and-to-the-right arc that learning and hard work produces over time.”

To me, investing in stocks is, at its core, the same as having faith in the long-term potential of humanity. There are 7.8 billion individuals in the world today, and the vast majority of us will wake up every morning wanting to improve the world and our own lot in life – this is ultimately what fuels the global economy and financial markets. Miscreants and Mother Nature will wreak havoc from time to time. But I have faith in the collective positivity of humanity. When there’s a mess, we can clean it up. This has been the story of our long history – and the key driver of the return my family’s portfolio has enjoyed immensely over the past 9 years, 7 months, and 6 days.

My dear portfolio, goodbye.


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. I, the author, will be making sell-trades on the stocks mentioned in this article over the coming weeks.

This Book Explains The Economic Problems Facing The USA and China Today (Including Tariffs!)

The book mentioned in the title of this article is The Other Half of Macroeconomics and the Fate of Globalization written by economist Richard C. Koo (Gu Chao Ming) and published in 2018.

I first came across Koo’s book in March 2020 when I chanced upon a review of it in Mandarin, written by investor Li Lu. I can read Mandarin and I found myself agreeing to the ideas from the book that Li shared, so much so that I made a self-directed attempt at translating the review into English. But I only began reading the actual book near the start of this year and finished it about a month ago. There was even more richness in the book’s ideas about how economies should operate than what was shared in Li’s already-wonderful review.

Earlier this month, the US government, under the Trump administration, made sweeping changes to the global trading system by introducing the Reciprocal Tariff Policy, which raised tariffs, sometimes significantly so, for many of the US’s trading partners. Major driving forces behind the Reciprocal Tariff Policy ostensibly include the US’s sustained trade deficits (particularly with China) and a desire by the Trump administration to bring manufacturing jobs back to the country.

As I contemplated the Trump administration’s actions, and the Chinese government’s reactions, I realised Koo’s book explained why all these issues happened. So I’m writing my own notes and takeaways from the book for easy reference in the future and I would like to share them in this article in the hopes that they could be useful for you. I will be borrowing from my translation of Li’s Mandarin review in this article. Below the horizontal line, all content in grey font are excerpts from my translation while all italicised content are excerpts from the book. 


The three stages of economic development a country goes through

There are six important ideas that Koo discussed in his book. One of them is the concept that a country goes through three distinct stages of economic development over time. 

The first stage of development would be a country that is industrialising and has yet to reach the Lewis Turning Point (LTP). The LTP is the “point at which urban factories have finally absorbed all the surplus rural labour.” When a country starts industrialising, people are mostly living in rural areas and there are only a very few educated elite who have the knowhow to kickstart industrialisation. There is also a surplus of labour. As a result, the educated elite – the industrialists – hold the power and “most of the gains during the initial stage of industrialisation therefore go to the educated few.”  The first stage of economic development is also when income inequality widens – the gains from industrialisation continue to accumulate in the hands of the elite as they reinvest profits into their businesses because there continues to be a surplus of labour.

The second stage of development happens when an industrialising economy reaches the LTP. At this point, labour “gains the bargaining power to demand higher wages for the first time in history, which reduces the share of output accruing to business owners.” But business owners are happy to continue reinvesting their profits as they are still “achieving good returns, leading to further tightness in the labour market.” This dynamic leads to an economy’s “golden era”:

As labor’s share increases, consumption’s share of GDP will increase at the expense of investment. At the same time, the explosive increase in the purchasing power of ordinary citizens means that most businesses are able to increase profits simply by expanding existing productive capacity. Consequently, both consumption and investment will increase rapidly…

…Inequality also diminishes as workers’ share of output increases relative to that of capital… 

…With incomes rising and inequality falling, this post-LTP maturing phase may be called the golden era of economic growth…

…Higher wages force businesses to look harder for profitable investment opportunities. On the other hand, the explosive increase in the purchasing power of ordinary workers who are paid ever-higher wages creates major investment opportunities. This prompts businesses to invest for two reasons. First, they seek to increase worker productivity so that they can pay ever-higher wages. Second, they want to expand capacity to address workers’ increasing purchasing power. Both productivity- and capacity-enhancing investments increase demand for labor and capital that add to economic growth. In this phase, business investment increases workers’ productivity even if their skill level remains unchanged…

…With rapid improvements in the living standards of most workers, the post-LTP maturing phase is characterised by broadly distributed benefits from economic growth.”

The golden era has its problems too. This is because this period is when “workers begin to utilise their newfound bargaining power” such as by organising strikes. But business owners and labour tend to be able to work out their differences.

The third stage of development is what Koo calls a “post-LTP pursued economy.” When a country is in the golden era, at some point ever-growing wages creates inroads for foreign competitors – and the country starts being chased by the foreign competitors that have lower wages. This is when businesses in the country find it very challenging to “find attractive investment opportunities at home because it often makes more sense for them to buy directly from the “chaser” or to invest in that country themselves.” This is also when “the return on capital is higher abroad than at home.” During the pursued stage, “real wage growth will be minimal” and “economic growth also slows.” Although a pursued country can continue to grow economically, a major problem is that inequality once again rears its ugly head:

“Japan’s emergence in the 1970s shook the U.S. and European industrial establishments. As manufacturing workers lost their jobs, ugly trade frictions ensued between Japan and the West. This marked the first time that Western countries that had already passed their LTPs had been chased by a country with much lower wages…

…While Western companies at the forefront of technology continued to do well, the disappearance of many well-paying manufacturing jobs led to worsening income inequality in these countries…

…Some of the pain Western workers felt was naturally offset by the fact that, as consumers, they benefited from cheaper imports from Asia, which is one characteristic of import-led globalisation. Businesses with advanced technology continued to do well, but it was no longer the case that everyone in society was benefiting from economic growth. Those whose jobs could be transferred to lower-cost locations abroad saw their living standards stagnate or even fall.”

Koo wrote that Western economies – the USA and Europe – entered their golden eras around the 1950s and became pursued starting in the 1970s by Japan. During the golden era of the West, “it was in an export-led globalisation phase as it exported consumer and capital goods to the world.” But as the West started getting pursued, they entered “an import-led globalisation phase as capital seeks higher returns abroad and imports flood the domestic market.”

The four states of an economy

Another important idea from Koo’s book is the concept that an economy has four distinct states, which are summarised in Table 1 below:

An economy is always in one of four possible states depending on the presence or absence of lenders (savers) and borrowers (investors). They are as follows: (1) both lenders and borrowers are present in sufficient numbers, (2) there are borrowers but not enough lenders even at high interest rates, (3) there are lenders but not enough borrowers even at low interest rates, and (4) both lenders and borrowers are absent.

Table 1

Koo’s idea that an economy has four distinct states is important because mainstream economic-thought does not cater for the disappearance of borrowers:

“Of the four, only Cases 1 and 2 are discussed in traditional economics, which implicitly assumes there are always enough borrowers as long as real interest rates are low enough.”

There are two key reasons why an economy would be in Cases 3 and 4, i.e. when borrowers disappear. The first is when private-sector businesses are unable to find attractive investment opportunities (this is related to economies that are in the third-stage of development discussed earlier in this article, when attractive domestic investment opportunities become scarce):

The first is one in which private‐sector businesses cannot find investment opportunities that will pay for themselves. The private sector will only borrow money if it believes it can pay back the debt with interest. And there is no guarantee that such opportunities will always be available. Indeed, the emergence of such opportunities depends very much on scientific discoveries and technological innovations, both of which are highly irregular and difficult to predict.

In open economies, businesses may also find that overseas investment opportunities are more attractive than those available at home. If the return on capital is higher in emerging markets, for example, pressure from shareholders will force businesses to invest more abroad while reducing borrowings and investments at home. In modern globalized economies, this pressure from shareholders to invest where the return on capital is highest may play a greater role than any technological breakthroughs, or lack thereof, in the decision as to whether to borrow and invest at home.”

The second reason for the disappearance of borrowers is named by Koo as a “balance sheet recession” which is described as such:

“In the second set of circumstances, private‐sector borrowers have sustained huge losses and are forced to rebuild savings or pay down debt to restore their financial health. Such a situation may arise following the collapse of a nationwide asset price bubble in which a substantial part of the private sector participated with borrowed money. The collapse of the bubble leaves borrowers with huge liabilities but no assets to show for the debt. Facing a huge debt overhang, these borrowers have no choice but to pay down debt or increase savings in order to restore their balance sheets, regardless of the level of interest rates.

Even when the economy is doing well, there will always be businesses that experience financial difficulties or go bankrupt because of poor business decisions. But the number of such businesses explodes after a nationwide asset bubble bursts.

For businesses, negative equity or insolvency implies the potential loss of access to all forms of financing, including trade credit. In the worst case, all transactions must be settled in cash, since no supplier or creditor wants to extend credit to an entity that may seek bankruptcy protection at any time. Many banks and other depository institutions are also prohibited by government regulations from extending or rolling over loans to insolvent borrowers in order to safeguard depositors’ money. For households, negative equity means savings they thought they had for retirement or a rainy day are no longer there. Both businesses and households will respond to these life‐threatening conditions by focusing on restoring their financial health—regardless of the level of interest rates—until their survival is no longer at stake.

A balance sheet recession can be a huge problem for a country’s economy if it is unresolved as it can lead to a rapidly shrinking economy as a manifestation of the “fallacy of composition” problem:

“One person’s expenditure is another person’s income…

…The interaction between thinking and reacting households and businesses create a situation where one plus one does not necessarily equal two. For example, if A decides to buy less from B in order to set aside more savings for an uncertain future, B will have less income to buy things from A. That will lower A’s income, which in turn will reduce the amount A can save.

This interaction between expenditure and income also means that, at the national level, if one group is saving money, another group must be doing the opposite – “dis-saving” – to keep the economy running. In most cases, this dis-saving takes the form of borrowing by businesses that seek to expand their operations. If everyone is saving and no one is dis-saving on borrowing, all of those savings will leak out of the economy’s income stream, resulting in less income for all.

For example, if a person with an income of $1,000 decides to spend $900 and save $100, the $900 that is spent becomes someone else’s income and continues circulating in the economy. The $100 that is saved is typically deposited with a financial institution such as a bank, which then lends it to someone else who can make use of it. When that person borrows and spends the $100, total expenditures in the economy amount to $900 plus $100, which is equal to the original $1,000, and the economy moves forward…

…If there are no borrowers for $100 in savings in the above example, even at zero interest rates, total expenditures in the economy will drop to $900, while the saved $100 remains unborrowed in financial institutions or under mattresses. The economy has effectively shrunk by 10 percent, from $1,000 to $900. That $900 now becomes someone else’s income. If that person decides to save 10 percent, and there are still no borrowers, only $810 will be spent, causing the economy to contract to $810. This cycle will repeat, and the economy will shrink to $730, if borrowers remain on the sidelines. This process of contraction is called a “deflationary spiral.”…

…Keynes had a name for this state of affairs, in which everyone wants to save but is unable to do so because no one is borrowing. He called it the paradox of thrift. It is a paradox because if everyone tries to save, the net result is that no one can save.

The phenomenon of right behaviour at the individual level leading to a bad result collectively is known as the “fallacy of composition.””

Japan was the “first advanced country to experience a private-sector shift to debt minimization for balance sheet reasons since the Great Depression.” Japan’s real estate bubble burst in 1990, where real estate prices fell by 87%, “devastating the balance sheets of businesses and financial institutions across the country” and leading to a disappearance of borrowers:

Demand for funds shrank rapidly when the bubble finally burst in 1990. Noting that the economy was also slowing sharply, the BOJ took interest rates down from 8 percent at the height of the bubble to almost zero by 1995. But demand for funds not only failed to recover but actually turned negative that year. Negative demand for funds means that Japan’s entire corporate sector was paying down debt at a time of zero interest rates, a world that no economics department in university or business school had ever envisioned. The borrowers not only stopped borrowing but began moving in the opposite direction by paying down debt and continued doing so for a full ten years, until around 2005…

…While in a textbook economy the household sector saves and the corporate sector borrows, both sectors became net-savers in post-1999 Japan, with the corporate sector becoming the largest saver in the country from 2002 onward in spite of zero interest rates.”

The Western economies experienced their own balance sheet recessions starting in 2008 with the bursting of housing bubbles in that year. When the “bubbles collapsed on both sides of the Atlantic in 2008, the balance sheets of millions of households and many financial institutions were devastated.” Borrowers also disappeared; the “private sectors in virtually all major advanced nations have been increasing savings or paying down debt since 2008 in spite of record low interest rates.” For example, “the U.S. private sector saved 4.1 percent of GDP at near-zero interest rates in the four quarters through Q1 2017” and the “Eurozone’s overall private sector is saving 4.6 percent of GDP in spite of negative interest rates.

Prior to the Japanese episode, the most recent example was the Great Depression:

Until 2008, the economics profession considered a contractionary equilibrium (the $500 economy) brought about by a lack of borrowers to be an exceptionally rare occurrence – the only recent example was the Great Depression, which was triggered by the stock market crash in October 1929 and during which the U.S. lost 46 percent of nominal GNP. Although Japan fell into a similar predicament when its asset price bubble burst in 1990, its lessons were almost completely ignored by the economics professional until the Lehman shock of 2008.”

The appropriate macroeconomic policies

The third important idea from Koo’s book is that depending on which stage (pre-LTP, golden era, or pursued) and which state (Case 1, Case 2, Case 3, or Case 4) a country’s economy is in, there are different macroeconomic policies that would be appropriate.

First, it’s important to differentiate the two policies governments can wield, namely, monetary policy and fiscal policy:

“The government also has two types of policy, known as monetary and fiscal policy, that it can use to help stabilise the economy by matching private-sector savings and borrowings. Themore frequently used is monetary policy, which involves raising or lowering interest rates to assist the matching process. Since an excess of borrowers is usually associated with a strong economy, a higher policy rate might be appropriate to prevent overheating and inflation. Similarly, a shortage of borrowers is usually associated with a weak economy, in which case a lower policy rate might be needed to avert a recession or deflation.

With fiscal policy, the government itself borrows and spends money on such projects as highways, airports, and other social infrastructure. While monetary policy decisions can be made very quickly by the central bank governor and his or her associates, fiscal policy tends to be very cumbersome in a peacetime democracy because elected representatives must come to an agreement on how much to borrow and where to spend the money. Because of the political nature of these decisions and the time it takes to implement them, most recent economic fluctuations were dealt with by central banks using monetary policy.”

Fiscal policy is more important than monetary policy when a country’s economy is in the pre-LTP stage, but the relative importance of the two types of policies switches once the economy enters the golden era; fiscal policy once again becomes the more important type of policy when the economy is in the pursued stage: 

“In the early phases of industrialisation, economic growth will rely heavily on manufacturing, exports, and the formation of capital etc. At this juncture, the government’s fiscal policies can play a huge role. Through fiscal policies, the government can gather scarce resources and invest them into basic infrastructure, resources, and export-related services etc. These help emerging countries to industrialise rapidly. Nearly every country that was in this stage of development saw their governments implement policies that promote active governmental support.

In the second stage of development, the twin engines of economic growth are rising wages and consumer spending. The economy is already in a state of full employment, so an increase in wages in any sector or field will inevitably lead to higher wages in other areas. Rising wages lead to higher spending and savings, and companies will use these savings to invest in productivity to improve output. In turn, profits will grow, leading to companies having an even stronger ability to raise wages to attract labour. All these combine to create a positive feedback loop of economic growth. Such growth comes mainly from internal sources in the domestic economy. Entrepreneurs, personal and household investing behaviour, and consumer spending patterns are the decisive players in promoting economic growth, since they are able to nimbly grasp business opportunities in the shifting economic landscape. Monetary policies are the most effective tool in this phase, compared to fiscal policies, for a few reasons. First, fiscal policies and private-sector investing both tap on a finite pool of savings. Second, conflicts could arise between the private sector’s investing activities and the government’s if poorly thought-out fiscal policies are implemented, leading to unnecessary competition for resources and opportunities. 

When an economy reaches the third stage of development (the stage where it’s being chased), fiscal policy regains its importance. At this stage, domestic savings are high, but the private sector is unwilling to invest domestically because the investing environment has deteriorated – domestic opportunities have dwindled, and investors can get better returns from investing overseas. The government should step in at this juncture, like what Japan did, and invest heavily in infrastructure, education, basic research and more. The returns are not high. But the government-led investments can make up for the lack of private-sector investments and the lack of consumer-spending because of excessive savings. In this way, the government can protect employment in society and prevent the formation of a vicious cycle of a decline in GDP. In contrast, monetary policy is largely ineffective in the third stage.”

It’s worth noting that an economy that is in the pre-LTP stage is likely to be in Case 4, where borrowers and lenders are both absent. Meanwhile, an economy that is in the Golden Era is likely to be in Case 1 (where both borrowers and lenders are present in abundance) and in Case 2 (where borrowers are present, but lenders are absent) during a run-of-the-mill recession, although a Case 1 Golden Era economy can also quickly be in Case 3 or Case 4. Once an economy is in the pursued stage, it is likely to be in Case 3 (where borrowers are absent but lenders are present) because of a lack of domestic investment opportunities or a balance sheet recession, or Case 4 (where borrowers and lenders are both absent) because of a balance sheet recession.

When a country’s economy is in Case 1 or Case 2, monetary policy is more important:

“Case 1 requires a minimum of policy intervention – such as slight adjustments to interest rates – to match savers and borrowers and keep the economy going. Case 1, therefore, is associated with ordinary interest rates and can be considered the ideal textbook case.

The causes of Case 2 (insufficient lenders) can be traced to both macro and financial factors. The most common macro factor is when the central bank tightens monetary policy to rein in inflation. The tighter credit conditions that result certainly leave lenders less willing to lend. Once inflation is under control, however, the central bank typically eases monetary policy, and the economy returns to Case 1. A country may also be too poor or underdeveloped to save. If the paradox of thrift leaves a country too poor to save, the situation would be classified as Case 3 or 4 because it is actually attributable to a lack of borrowers.

Financial factors weighing on lenders may also push the economy into Case 2. One such factor is an excess of non-performing loans (NPLs) in the banking system, which depresses banks’ capital ratios and prevents them from lending. This is what is typically called a “credit crunch.” Over-regulation of financial institutions by the authorities can also lead to a credit crunch. When many banks encounter NPL problems at the same time, mutual distrust may lead not only to a credit crunch, but also to a dysfunctional interbank market, a state of affairs typically referred to as a “financial crisis.”…

…Non-developmental causes of a shortage of lenders all have well-known remedies… For example, the government can inject capital into the banks to restore their ability to lend, or it can relax regulations preventing financial institutions from serving as financial intermediaries.

In the case of a dysfunctional interbank market, the central bank can act as lender of last resort to ensure the clearing system continues to operate. It can also relax monetary policy. The conventional emphasis on monetary policy and concerns over the crowding-out effect of fiscal policy are justified in Cases 1 and 2 where there are borrowers but (for a variety of reasons in Case 2) not enough lenders.””

When a country’s economy is in Case 3 or Case 4, fiscal policy is more important because monetary policy does not work when borrowers disappear, although the appropriate type of fiscal policy can also differ:

“It should be noted that in the immediate aftermath of a bubble collapse, the economy is usually in Case 4, characterized by a disappearance of both lenders and borrowers. The lenders stop lending because they provided money to borrowers who participated in the bubble and are now facing technical or real insolvency. Banks themselves may be facing severe solvency problems when many of their borrowers are unable to service their debts…

…In a financial crisis, therefore, the central bank must act as lender of last resort to ensure that the settlement system continues to function…

Once the bubble bursts and households and businesses are left facing debt overhangs, no amount of monetary easing by the central bank will persuade them to resume borrowing until their balance sheets are fully repaired…

…When private-sector borrowers disappear and monetary policy stops working, the correct way to prevent a deflationary spiral is for the government to borrow and spend the excess savings of the private sector… 

…In other words, the government should mobilize fiscal policy and serve as borrower of last resort when the economy is in Case 3 or 4. 

If the government borrows and spends the $100 left unborrowed by the private sector, total expenditures will amount to $900 plus $100, or $1,000, and the economy will move on. This way, the private sector will have the income it needs to pay down debt or rebuild savings…

…It has been argued that the fiscal stimulus is essential when the economy is in Case 3 or 4. But there are two kinds of fiscal stimulus: government spending and tax cuts. If the economy is in a balance sheet recession, the correct form of fiscal stimulus is government spending. If the economy is suffering from a lack of domestic investment opportunities, the proper response would be a combination of tax cuts and deregulation to encourage innovation and risk taking… augmented by government spending…

…The close relationship observed prior to 2008 between central-bank-supplied liquidity, known as the monetary base, and growth in money supply and private-sector credit broke down completely after the bubbles burst and the private sector began minimizing debt. Here money supply refers to the sum of all bank accounts plus bills and coins circulating in the economy, and credit means the amount of money lent to the private sector by financial institutions…

…In this textbook world, a 10 percent increase in central bank liquidity would increase both the money supply and credit by 10 percent. This means there were enough borrowers in the private sector to borrow all the funds supplied by the central bank, and the economies were tin Case 1…

…But after the bubble burst, which forced the private sector to minimize debt in order to repair its balance sheet, no amount of central bank accommodation was able to increase private-sector borrowings. The U.S. Federal Reserve, for example, expanded the monetary base by 349 percent after Lehman Brothers went under. But the money supply grew by only 76 percent and credit by only 27 percent. A 27 percent increase in private-sector credit over a period of nearly nine years represents an average annual increase of only 2.75 percent, which is next to nothing.”

Fiscal stimulus equates to government-spending, which increases public debt. Koo suggests that (1) when an economy is in Case 3 or Case 4, rising and/or high public debt is not necessarily a problem, and (2) the limits of public debt should be determined by the bond market:

“Debt is simply the flip side of savings. Somebody has to be saving for debt to grow, and it is bound to increase as long as someone in the economy continues to save. Moreover, if someone is saving but debt levels fail to grow (i.e., if no one borrows and spends the saved funds), the economy will fall into the $1000 – $900 – $810 – $730 deflationary spiral….

…Growth in debt (excluding debt financed by the central bank) is merely a reflection of the fact that the private sector has continued to save. 

If debt is growing faster than actual savings, it simply means there is double counting somewhere, i.e., somebody has borrowed the money but instead of using it himself, he lent it to someone else, possibly with a different maturity structure (maturity transfer) or interest rates (fixed to floating or vice versa). With the prevalence of carry trades and structured financial products involving multiple counterparties, debt numbers may grow rapidly on the surface, but the actual debt can never be greater than the actual savings. 

Furthermore, the level of debt anyone can carry also depends on the level of interest rates and the quality of projects financed with the debt. If the projects earn enough to pay back both borrowing costs and principal, then no one should care about the debt load, no matter how large, because it does not represent a future burden on anyone. Similarly, no matter how great the national debt, if the funds are invested in public works projects capable of generating returns high enough to pay back both interest and principal, the projects will be self-financing and will not increase the burden on future taxpayers…

…Whether or not fiscal policy has reached its limits should be decided by the bond market, not by some economist using arbitrarily chosen criteria. 

During the golden era, when the private sector has strong demand for funds to finance productivity- and capacity-enhancing investments, fiscal stimulus will have a minimal if not negative impact on the economy because of the crowding-out effect. The bond market during this era correctly assigns very low prices (high yields) to government bonds, indicating that such stimulus is not welcome.

During the pursued era or during balance sheet recessions, however, private-sector demand for funds is minimal if not negative. At such times, fiscal stimulus is not only essential, but it has maximum positive impact on the economy because there is no danger of crowding out. During this period, the bond market correctly sets very high prices (low yields) for government bonds, indicating they are welcome…

…Ultra-low bond yields in economies in Cases 3 and 4 are also a signal to the government to look for public works projects capable of producing a social rate of return in excess of those rates. If such projects can be found, fiscal stimulus centered on them will ultimately place no added burden on future taxpayers.” 

The experience of the economies of the US, the UK, Japan, and Europe in the aftermath of the housing bubble bursting in 2008 which thrust them into balance sheet recessions is instructive on the importance of fiscal policy in combating balance sheet recessions:

In November 2008, just two months after Lehman Brothers went under, the G20 countries agreed at an emergency meeting in Washington to implement fiscal stimulus. That decision kept the world economy from falling into a deflationary spiral. But in 2010, the fiscal orthodoxy of those who did not understand balance sheet recessions reasserted itself at the Toronto G20 meeting, where members agreed to cut deficits in half even though private-sector balance sheets were nowhere near a healthy state. The result was a sudden loss of forward momentum for the global economy that prolonged the recession unnecessarily in many parts of the world. After 2010, those countries that understood the danger of balance sheet recessions did well, while those that did not fell by the wayside…

…Bernanke and Yellen both understood this, and they used the expression “fiscal cliff” to warn Congress about the danger posed by fiscal consolidation, which the Republicans and many orthodox economists supported. The extent of Bernanke’s concerns about fiscal consolidation can be gleaned from a press conference on April 25, 2012, when he was asked what the Fed would do if Congress pushed the U.S. economy off the fiscal cliff. He responded, “There is . . . absolutely no chance that the Federal Reserve could or would have any ability whatsoever to offset that effect on the economy.”10 Bernanke clearly understood that the Fed’s monetary policy not only cannot offset the negative impact of fiscal consolidation, but would also lose its effectiveness if the government refused to act as borrower of last resort.

Even though the U.S. came frighteningly close to falling off the fiscal cliff on a number of occasions, including government shutdowns, sequesters, and debt‐ceiling debates, it ultimately managed to avoid that outcome thanks to the efforts of officials at the Fed and the Obama administration. And that is why the U.S. economy is doing so much better than Europe, where virtually every country did fall off the fiscal cliff…

…The warnings about the fiscal cliff set the Fed apart from its counterparts in Japan, the UK, and Europe. In the UK, then-BOE Governor Mervyn King publicly supported David Cameron’s rather draconian austerity measures, arguing that his bank’s QE policy would provide necessary support for the British economy. At the time, the UK private sector was saving a full 9 percent of GDP when interest rates were at their lowest levels in 300 years. That judgement led to the disastrous performance of the UK economy during the first two years of the Cameron administration…

…BOJ Governor Haruhiko Kuroda also argued strongly in favor of hiking the consumption tax rate, believing a Japanese economy supported by his quantitative easing regime would be strong enough to withstand the shock of fiscal consolidation. This was in spite of the fact that Japanese private sector was saving 6.2 percent of GDP at a time of zero interest rates. The tax hike, which was carried out in April 2014, threw the Japanese economy back into recession…

…ECB President Mario Draghi has admonished member governments to meet the austerity target imposed by the Stability and Growth Pact at every press conference, even though his own inflation forecasts have been revised downwards almost every time they are updated. He seems to be completely oblivious to the danger posed by fiscal austerity when the Eurozone private sector has been saving an average of 5 percent of GDP since 2008 despite zero or even negative interest rates.” 

Koo also noted that when Japan’s real estate bubble burst in 1990, the government was “quick to administer fiscal stimulus to stop the implosion” and that “the economy responded positively each time fiscal stimulus was implemented, but lost momentum each time the stimulus was removed.” The Japanese government was under enormous pressure to cut fiscal stimulus in the aftermath of the bubble, but the government did not completely cave, and the Japanese economy managed to fare better than it would otherwise:

“The orthodox fiscal hawks who dominated the press and academia also tried to stop fiscal stimulus at every step of the way, arguing that large deficits would soon lead to skyrocketing interest rates and a fiscal crisis. These hawks forced politicians to cut stimulus as soon as the economy showed signs of life, prompting another downturn. The resulting on-again, off-again fiscal stimulus did not imbue the public with confidence in the government’s handling of the economy. Fortunately, the LDP [Liberal Democratic Party] had enough pork-barrel politicians to keep a minimum level of stimulus needed in place, and as a result, Japanese GDP never once fell below its bubble peak. Nor did the Japanese unemployment rate ever exceed 5.5 percent.

That was a fantastic achievement in view of the fact that the Japanese private sector was saving an average of 8 percent of GDP from 1995 to 2005, and the Japanese lost three times as much wealth (as a share of GDP) as Americans did during the Great Depression, when nominal GNP fell 46 percent.”

The reason for US backlash against globalisation & the conflict between free-trade and free-capital

The fourth and fifth important ideas from Koo’s book are connected and they are respectively, (a) the possible reasons behind the backlash against globalisation that is seen from the current US government under the Trump administration, and (b) the possible conflict between free trade and free-movement of capital. Again, Koo’s book was published in 2018, so it was discussing Donald Trump’s first term as President. But the ideas appear to me to be very applicable to today’s context.

Koo advanced that the Western economies’ entrance into the third stage of economic development – pursued stage – is a reason for the backlash against globalisation:

“One reason for the frustration and social backlash witnessed in the advanced countries is that these countries are experiencing the post-Lewis Turning Point (LTP) pursued phase for the first time in history… 

…Many were caught offguard, having assumed that the golden era that they enjoyed into the 1970s would last forever. It comes as no surprise that those who have seen no improvement in their living standards for many years but still remember the golden age, when everyone was hopeful and living standards were steadily improving, would long for the “good old days.”…

…In the U.S. too, the Trump phenomenon, which has depended largely on the support of blue-collar white males, suggests that people are longing for the life they enjoyed during the golden era, when U.S. manufacturing was the undisputed leader of the world.

Participants in this social backlash in many of the pursued economies view globalization as the source of all evil and are trying to slow down the free movement of both goods and people. Donald Trump and others like him are openly hostile toward immigration while arguing in favour of protectionism and the scuttling of agreements such as the TPP that seek even freer trade.”

Koo described the mainstream view that free trade creates overall gains for trading partners, but cautioned that the view has a flawed assumption, in that imports and exports will be largely balanced as free trade grows, and it is that wrong assumption that also contributed to the backlash against globalisation:

“Economists have traditionally argued that while free trade creates both winners and losers within the same country, it offers significant overall welfare gains for both trading partners because the gains of the winners are greater than the losses of the losers. In other words, there should be more winners than losers from free trade…

…This conclusion, however, is based on one key assumption: that imports and exports will be largely balanced as free trade expands. When – as in the U.S. during the past 30 years – that assumption does not hold and a nation continues to run massive trade deficits, free trade may produce far more losers than theory would suggest. With the U.S. running a trade deficit of almost [US]$740bn a year, or about four percent of GDP, there were apparently enough losers from free trade to put the protectionist Donald Trump into the White House. The fact that Hillary Clinton was also nominated to be the Democratic Party’s candidate for president in the arena full of banners saying “No to TPP” indicates that the social backlash has grown very large indeed.”

Koo clarified that free trade is important and has its benefits, but the way free trade has taken place since World War II is hugely problematic because of (1) the way free trade is structured, and (2) the free movement of capital that is happening in parallel:

“Outright protectionism is likely to benefit the working class in the short term only. In the long run, history has repeatedly shown that protected industries always fall behind on competitiveness and technological advances, which means the economy will stagnate and be overtaken by more dynamic competitors…

…This does not mean that free trade as practiced since 1945 and globalism in general have no problems. They both have major issues, but these can be addressed if properly understood. A correct understanding is important here because even though increasing imports is the most visible feature of an economy in a pursued phase, trade deficits and the plight of workers displaced by imports have been made far worse by the free movement of capital since 1980…

…Once the U.S. opened up its massive markets to the world after 1945 and the GATT-based [General Agreement on Tariffs and Trade] system of free trade was adopted, nations belonging to this system found that it was possible to achieve economic growth without territorial expansion as long as they could produce competitive products. The first countries to recognize this were the vanquished nations of Japan and West Germany, which then decided to devote their best people to developing globally competitive products…

…By the end of the 1970s, however, the West began losing its ability to compete with Japanese firms as the latter overtook the U.S. and European rivals in many sectors, including home appliances, shipbuilding, steel, and automobiles. This led to stagnant income growth and disappearing job opportunities for Western workers.

When Japan joined the GATT in 1963, it still had many tariff and non-tariff trade barriers. In other words, while Western nations had been steadily reducing their own trade barriers, they were suddenly confronted with an upstart from Asia that still had many barriers in place. But as long as Japan’s maximum tariff rates were falling as negotiated and the remaining barriers applied to all GATT members equally, GATT members who had opened their markets earlier could do little under the agreement’s framework to force Japan to open its market (the same problem resurfaced when China joined the WTO 38 years later)…

…When U.S.-Japan trade frictions began to flare up in the 1970s, however, exchange rates still responded correctly to trade imbalances. In other words, when Japanese exports to the U.S. outstripped U.S. exports to Japan, there were more Japanese exporters selling dollars and buying yen to pay employees and suppliers in Japan than there were U.S. exporters selling yen and buying dollars to pay employees and suppliers in the U.S.

Since foreign exchange market participants in those days consisted mostly of exporters and importers, excess demand for yen versus the dollar caused the yen to strengthen against the dollar. That, in turn, made Japanese products less competitive in the U.S. As a result, trade frictions between the U.S. and Japan were prevented from growing any worse than they did because the dollar fell from ¥360 in mid-1971 to less than ¥200 in 1978 in response to widening Japanese trade surpluses with the U.S..

But this arrangement, in which the foreign exchange market acted as a trade equalizer, broke down with financial liberalization, which began in the U.S. with the Monetary Control Act of 1980…

…These changes prompted huge capital outflows from Japan as local investors sought higher-yielding U.S. Treasury securities. Since Japanese investors needed dollars to buy Treasuries, their demand for dollars in the currency market outstripped the supply of dollars from Japanese exporters and pushed the yen back to ¥280 against the dollar. This rekindled the two countries’ trade problems, because few U.S. manufacturers were competitive vis-a-vis the Japanese at that exchange rate.

When calls for protectionism engulfed Washington, President Ronald Reagan, a strong supporter of free trade, responded with the September 1985 Plaza Accord, which took the dollar from ¥240 in 1985 down to ¥120 just two years later. The dollar then rose to ¥160 in 1990 but subsequently fell as low as ¥79.75 in April 1995, largely ending the trade-related hostilities that had plagued the two nations’ relationship for nearly two decades…

…Capital transactions made possible by the liberalization of cross-border capital flows also began to dominate the currency market. Consequently, capital inflows to the U.S. have led to continued strength of the dollar – and stagnant or declining incomes for U.S. workers – even as U.S. trade deficits continue to mount. In other words, the foreign exchange market lost its traditional function as an automatic stabilizer for trade balances, and the resulting demands for protectionism in deficit countries are now at least as great as they were before the Plaza Accord in 1985.”

Specifically with regards to the belligerent relationship the US has with China today, Koo suggested that it was because of flaws in the free trade framework of the World Trade Organisation (WTO):

“…a key contradiction in the WTO framework: the fact that China levies high tariffs on imports from all WTO nations is no reason why the U.S.—which runs a huge trade deficit with China—should have to settle for lower tariffs on imports from China.

This problem arose because the developed‐world members of the WTO had already lowered tariffs among themselves before developing countries such as China, with their significantly lower wages and higher tariffs, were allowed to join. When they joined, developing countries could argue that they were still underdeveloped and needed higher tariffs to allow infant domestic industries to grow and to keep their trade deficits under control. Although that was a valid argument for developing countries at the time and their maximum tariff rates have come down as negotiated, the effective rates remained higher than those of advanced countries long after those countries became competitive enough to run trade surpluses with the developed world…

…Because the WTO system is based on the principle of multilateralism, with rules applied equally to all member nations, this framework provides no way of addressing bilateral imbalances between the U.S. and China. It is therefore not surprising that the Trump administration has decided to pursue bilateral, not multilateral, trade negotiations.

In retrospect, what the WTO should have done is to impose a macroeconomic condition stating that new members must lower their tariff and non‐tariff barriers to advanced‐country norms after they start to run significant trade surpluses with the latter. Here the term “significant” might be defined to mean running a trade surplus averaging more than, say, two percent of GDP for three years. If a country fails to reduce its tariffs to the advanced‐nation norm within say five years after reaching that threshold, the rest of the WTO community should then be allowed to raise tariffs on products from that country to the same level that country charges on its imports. The point is that if the country is competitive enough to run trade surpluses vis‐à‐vis advanced countries, then it should be treated as one.

If this requirement had existed when Japan joined the GATT in 1963 or when China joined the WTO in 2001, subsequent trade frictions would have been far more manageable. Under the above rules, Japan would have had to lower its tariffs starting in 1976, and China would have had to lower its tariffs from the day it joined the WTO in 2000! Such a requirement would also have enhanced the WTO’s reputation as an organization that supports not only free trade but also fair trade.”

Koo also noted that the term globalisation actually has two components, namely, free trade and free movement of capital, and that the former is important for countries to continue maintaining because of the benefits it brings, while the latter system needs improvement:

“The term “globalization” as used today actually has two components: free trade and the free movement of capital. 

Of the two, it was argued in previous chapters that the system of free trade introduced by the U.S. after 1947 led to unprecedented global peace and prosperity. Although free trade produces winners and losers and providing a helping hand to the losers is a major issue in the pursued economies, the degree of improvement in real living standards since 1945 has been nothing short of spectacular in both pursued and pursuing countries…

…The same cannot be said for the free movement of capital, the second component of globalization. Manufacturing workers and executives in the pursued economies feel so insecure not only because imports are surging but also because exchange rates driven by portfolio capital flows of questionable value are no longer acting to equilibrate trade.

To better understand this problem, let us take a step back and consider a world in which only two countries – the U.S. and Japan – are engaged in trade, and each country buys $100 in goods from the other. The next year, both countries will have the $100 earned from exporting to its trading partner, enabling it to buy another $100 in goods from that country. The two nations’ trade accounts are in balance, and the trade relationship is sustainable. 

But if the U.S. buys $100 from Japan, and Japan only buys $50 from the U.S., Japan will have $100 to use the next year, but the U.S. will have only $50, and Japanese exports to the U.S. will fall to $50 as a result. Earning only $50 from the U.S., the Japanese may have to reduce their purchases from the U.S. the following year. This sort of negative feedback loop may push trade into a “contractionary equilibrium.”

When exchange rates are added to the equation, the Japanese manufacturer that exported $100 in goods to the U.S. must sell those dollars on the currency market to buy the yen it needs to pay domestic suppliers and employees. However, the only entity that will sell it those yen is the U.S. manufacturer that exported $50 in goods to Japan.

With $100 of dollar selling and only $50 worth of yen selling, the dollar’s value versus the yen will be cut in half. This is how a surplus country’s exchange rate is pushed higher to equilibrate trade…

…If Japanese life insurers, pension funds, or other investors who need dollars to invest in the U.S. Treasury bonds sold yen and bought the remaining $50 the Japanese exporters wanted to sell, there would then be a total of $100 in dollar-buying demand for the $100 the Japanese exporter seeks to sell, and exchange rates would not change. If Japanese investors continued buying $50-worth of dollar investments each year, exchange rates would not change, in spite of the sustained $50 trade imbalances. 

Although the above arrangement may continue for a long time, the Japanese investors would effectively be lending money to the U.S. This means that at some point the money would have to be paid back. 

Unless the U.S. sells goods to Japan, there will be no U.S. exporters to provide the Japanese investors with the yen they need when they sell their U.S. Treasury bonds to pay yen obligations to Japanese pensioners and life insurance policyholders. Unless Japan is willing to continue lending to the U.S. in perpetuity, therefore, the underlying 100:50 trade imbalance will manifest itself when the lending stops.

At that point, the value of the yen will increase, resulting in large foreign exchange losses for Japanese pensioners and life insurance policyholders. Hence this scenario is also unsustainable in the long run. The U.S., too, would prefer a healthy relationship in which it sells goods to Japan and uses the proceeds to purchase goods from Japan to an unhealthy one in which it funds its purchases via constant borrowings…

…When financial markets are liberalized, capital moves to equalize the expected return in all markets. To the extent that countries with strong domestic demand tend to have higher interest rates than those with weak demand, money will flow from the latter to the former. Such flows will strengthen the currency of the former and weaken the currency of the latter. They may also add to already strong investment activity in the former by keeping interest rates lower than they would be otherwise, while depressing already weak investment activity in the latter by pushing interest rates higher than they would be otherwise.

To the extent that countries with strong domestic demand tend to run trade deficits and those with weak domestic demand run trade surpluses, these capital flows will exacerbate trade imbalances between the two by pushing the deficit country’s currency higher and pushing the surplus country’s currency lower. In other words, these flows are not only not in the best interests of individual countries, but are also detrimental to the attainment of balanced trade between countries. The widening imbalances then increase calls for protectionism in deficit countries.”

Prior to the liberalization of capital flows in the 1980s, “trade was free, but capital flows were regulated, so the foreign exchange market was driven largely by trade-related transactions.” This also meant that currency transactions could play the role they were meant to in terms of driving balanced trade:

“The currencies of trade surplus nations therefore tended to strengthen, and those of trade deficit nations to weaken. That encouraged surplus countries to import more and deficit countries to export more. In other words, the currency market acted as a natural stabilizer of trade between nations.”

As a sign of how free movement of capital has distorted the currency market, Koo noted that when the book was published “only about five percent of foreign exchange transactions involve trade, while the remaining 95 percent are attributable to capital flows.”

The problems with China’s economy

The sixth and last important idea from Koo’s book is a discussion of the factors that affect China’s economic growth, and why the country’s growth rate has slowed in recent years from the scorching pace seen in the 1990s and 200s. One issue, described by Koo, is that China no longer has a demographic tailwind to drive rapid economic growth, and is now facing a “middle-income trap” after passing the LTP around 2012:

“China actually passed the LTP around 2012 and is now experiencing sharp increases in wages. This means the country is now in its golden era, or post‐LTP maturing phase. However, because the Chinese government is wary of strikes, labor disputes, or other public disturbances of any kind, it is trying to pre‐empt such conflict by administering significant wage increases each year, with businesses required to raise wages under directives issued by local governments. In some regions, wages had risen at double‐ digit rates in a bid to prevent labor disputes. It remains to be seen whether such top‐down actions can substitute for a process in which employers and employees learn through confrontation what can reasonably be expected from the other party.

Just as China was passing the LTP, its working‐age population—defined as those aged 15 to 594—started shrinking in 2012. From a demographic perspective, it is highly unusual for the entire labor supply curve to begin shifting to the left just as a country reaches the LTP. Japan, Taiwan, and South Korea all enjoyed about 30 years of workforce growth after reaching their LTPs. The huge demographic bonus China enjoyed until 2012 is not only exhausted, but has now reversed… That means China that will not be able to maintain the rapid pace of economic growth seen in the past, and in fact growth has already slowed sharply. 

Higher wages in China are now leading both Chinese and foreign businesses to move factories to lower-wage countries such as Vietnam and Bangladesh, prompting fears that China will become stuck in the so-called “middle-income trap”. This trap arises from the fact that once a country loses its distinction as the lowest-cost producer, many factories may leave for lower-cost destinations, resulting in less investment and less growth. In effect, the laws of globalization and free trade that benefited China when it was the lowest-cost producer are now posing real challenges for the country.”

Koo proposed ideas for China to reinvigorate China’s growth, such as investing in productivity-enhancing measures for domestic workers. 

Another important factor affecting China’s economic growth involves the appropriate type of policy the government should implement to govern the economy. Since the country had passed the LTP more than a decade ago, and is in its golden era, fiscal policy – the act of the government directing the economy – is no longer the effective way to govern the economy. But is the government relinquishing control? To complicate matters, there are early signs now that China may already be in the pursued stage, in which case, fiscal policy will be important again. It remains to be seen what would be the most appropriate way for the government to lead China’s economy. 


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. I don’t have a vested interest in any company mentioned. Holdings are subject to change at any time.

What We’re Reading (Week Ending 20 April 2025)

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 20 April 2025:

1. The Growing Risk to Fed Independence That Wall St Isn’t Watching (Transcript here) – Tracy Alloway, Joe Weisenthal, and Lev Menand

Lev: I think something big is happening in the federal government right now where the President is asserting unprecedented powers over parts of the government that for – in some cases – over a century have operated with a certain amount of separation from presidential day-to-day direction. That threatens to upend government policy across a range of dimensions but in one area in particular, the consequences could be felt immediately, and that is with respect to the Federal Reserve.

Joe: Certainly the firing of the two minority commissioners at the FTC, almost immediately after we recorded that episode were news, I don’t think people on Wall Street really – “Okay, something about mergers” – that’s not high on their radar. What is the connection between the FTC or that action and something that could happen with the Federal Reserve?

Lev: Let me tell you why that FTC firing was a particularly big deal. There is a supreme court case on the question of whether the President can fire commissioners on the FTC without cause, the way Trump asserted the power to do the other day, and that is the bedrock precedent that protects the Federal Reserve. It’s called Humphrey’s Executor. It was decided by the court in 1935 and it reigned in and largely reversed, or cabinet to its facts, a famous decision from 1926 called Meyers vs. The United States that President Roosevelt – FDR – had relied on to try to fire a member of the FTC and the Supreme Court in 1935 said, “Nope, you can’t do that. That case isn’t going to stand for that anymore.” We’ve built up a whole system of government around this understanding and here Trump is inviting the Supreme Court to overrule this bedrock precedent.

Tracy: Since we already went back in time to 1935 and 1926, can we go even further and talk about why we have independent agencies at all? I guess the clue is in the name “independent agencies” but they have some oversight clearly, so who is actually watching over these independent agencies and why do they exist?

Lev: All the constitutional actors oversee the independent agencies. Independent agency is a technical term of art in law to refer to an agency whose heads cannot be removed by the President at pleasure. They include any officer of the government who is not a legislative officer, a member of congress elected or a judicial officer, an appointed Article 3 Judge. All of those officers, some of them can be put into a category of they’re part of an executive agency, the head of that agency can be removed by the President at pleasure, or an independent agency, the head of the agency cannot be removed by the President at pleasure.

In that second category, independent agencies, they’re accountable to the President, to the courts, to the Congress, in all sorts of different ways. The President appoints the heads of independent agencies with the advice and consent of the Senate, the President can remove the heads of independent agencies, but generally only for cause. Sometimes those causes are specified, like neglect of duty or malfeasance in office, we could talk about that. In the Federal Reserve Act, the statute just says “cause” and a for-cause removal involves notice and a hearing, so it’s not the same thing as an at-pleasure removal. It precludes the President from removing somebody for a policy disagreement. The independent agencies are accountable to Congress in that there are hearings that are held. Officers have to go down, just like Jay Powell goes down and testify, they’re subject to Congress’s subpoena power for records, they’re implicated in all the workings of the government and their actions, like the FTC’s actions, are subject to judicial review by Article 3 judges. So they’re not independent in this sense that’s sometimes asserted that they’re a fourth branch of government, or they’re outside of the government. No, they’re just a type of government body that has a different relationship to the President from the Secretary of Defense or the White House Chief of Staff, which are positions where the President can fire or direct the actions of that officer.

These sorts of positions have been around going all the way back to the founding. With respect to monetary policy, it was a question for the first Congress and the first Secretary of the Treasury, how much direction monetary policy should be subject to day-to-day oversight or direction by the President. This issue isn’t a new issue for the United States, it’s there right at the beginning…

…Lev: What are the possible exceptions that would allow the logic of Humphrey’s Executor to maybe apply to the Fed even if it no longer applies to the FTC? The one that the Trump Administration is running with so far is that monetary policy is somehow not sovereign executive power and can be distinguished from the other stuff the Fed does, and that stuff is regulation of financial institutions. Trump put out an executive order last month, Executive Order 14215, which asserted executive power over all the independent agencies and included specific carveout language for the Fed that said “This order doesn’t apply to the Fed with respect to its monetary policy, only with respect to its regulation and supervision of financial institutions.”  This is the Trump theory. There’s some other options we can get to, but I think let’s maybe think through Trump theory – does this make any sense?

There are some huge problems with this theory. It suggests that they haven’t spent a lot of time thinking about how the Fed conducts monetary policy and what the relationship is between monetary policy and the regulation of banks, because it’s really all one and the same thing. The court would be hard-pressed to say, for example, just as an initial matter, Jay Powell can’t be removed by the President with respect to what he’s doing on monetary policy but with respect to what he’s doing on bank regulation, the President could fire him for a policy disagreement. That would just fall apart pretty easily. What type of independence is really left? The president could just say “I fired him because I don’t like what he was doing on bank regulation,” and the real reason could be that he didn’t like what Jay Powell is doing on interest rates. But how would we know, because he doesn’t need to give a reason, except to say that it’s bank regulation. So there’s already a problem.

But the deeper problem is monetary policy implementation is bank regulation. In January when the Fed met, in the aftermath of that meeting, the board of governors amended Regulation D through a rulemaking published in the federal register lowering the interest paid on reserve balances to banks with reserve accounts at the Federal Reserve banks. It is a straight exercise of regulatory power, just like when the SEC writes a rule for what type of disclosure a company has to do if it’s a publicly traded company. They just don’t seem to realize this. They think that it’s like the FOMC just meets and they talk and then they announce a decision and that’s monetary policy, it’s not regulatory, it’s not adjudicatory. But actually, monetary policy implementation is all exercise of government power over the banking system.

2. Ukraine research excursion – what did I find? – Swen Lorenz

Visiting Kyiv, Ukraine’s capital, is not actually all that difficult, even under the current circumstances.

Anyone with a decent passport can head there by bus, train or car (for obvious reasons, no commercial flights are currently operated). No visa is required to enter Ukraine…

…You’ll have noticed just how vast Ukraine’s landmass is. Gleaning out of the train window to see mostly nothing, you start to understand how much space the country has relative to its population size.

You are also in for a few surprises. Who knew customs control officers in a war-torn country can be as friendly as the ones checking entrants to Ukraine?…

…Indeed, stepping out of Kyiv-Pasazhyrskyi railway station and driving across the city centre to my Airbnb apartment just off Independence Square, I couldn’t help but remember my trips to Russia in the early 2000s (or to Serbia in 2018 before that country took off for a belated round of rapid growth). There is a palpable sense that Kyiv never developed to quite the extent that other nations in the region did.

It was also striking how life went about seemingly entirely normal, at least during the day.

Kyiv gets into the Western news when it gets hit by missiles or drones, but as the saying goes, a house that isn’t on fire isn’t news.

I was also a bit lucky, as I did not have a single air raid alarm until my fourth day in town. By that time, I had learned that most people nowadays ignore these alarms…

…Kyiv does get hit by strikes, and people get hit. However, the city is about 300 km (190 miles) from the front line, it now has strong air defences, and strikes are relatively few in number relative to the size of the city. Human beings adapt, and even in a country that is at war, life has to continue somehow. Even now, companies in Kyiv are doing deals, residents refurbish homes and apartments, and some splurge on living the good life.

As I learned by speaking to a broad range of decision-makers, experts, and business leaders, Ukrainian companies and investors are currently reinvesting their profits in Ukraine – for lack of other options.

Refurbishment of real estate continues in some places, but it’s suffering from a labour shortage caused by the military mobilisation and the large number of men moving abroad. Large-scale residential development projects have mostly come to a halt…

…Before the war, foreigners could get a permanent residency in Ukraine by purchasing real estate for USD 100,000. They would subsequently pay just 5% tax on income, and there was no requirement to be physically present.

In fact, the deal still exists today. The tax rate has now gone up to 6% to help support the war, but that’s as sweet a deal as you’d be offered in most countries that want to attract new residents.

Opening bank accounts? That’s done one day, I was told.

Immediately before the war, Ukraine saw a significant influx of foreigners, and real estate was on the up. This abruptly came to an end, but I was surprised how many foreign “entrepreneur types” I encountered during my visit. There is clearly a wave of early adopters currently looking at possibilities in Ukraine.

Somewhat counterintuitively, some locals echoed a particular kind of enthusiasm.

It’d be easy to have a negative view of Ukraine’s outlook based on any number of factors. With men up to the age of 60 (!) having to fear the possibility of being sent to war, you could think that anyone who can leave would want to leave.

However, as one successful, enterprising Ukrainian stated:

“Western Europe is socialism. I lived in several countries over there, and I prefer Ukraine. More opportunity, more freedom.”

Ukraine is not for everyone – not now, and not after the shooting ends. However, as a place to live, it’s a much better proposition than I had thought…

…According to the latest figures from the United Nations High Commissioner for Refugees (UNHCR), almost 7m Ukrainian refugees currently live abroad. The exact numbers of those who stayed in the country and those who fled are difficult to pin down. Ukraine hasn’t conducted a census since 2001, and the country’s statistical service has partially stopped collecting and publishing demographic data because of war-related difficulties.

It’s clear that the answer to this question will have a significant effect on any reconstruction effort.

Experience shows that 30% of refugees return home within the first one or two years of a conflict’s end, and in some instances up to 50% if strong incentives are provided. Both a huge opportunity and a big challenge lie ahead. On the one hand, the Ukrainian economy – post-war – would benefit massively if several million returned to live and work in the country. On the other hand, the returnees would face a significant housing shortage, as 13% of the country’s housing stock reportedly got destroyed.

“When the war ends, you will not be able to buy a bucket of paint anywhere in Europe”, one of my dinner attendees told me.

3. Javier Blas on China’s Rare Earths Dominance (Transcript here) – Joe Weisenthal, Tracy Alloway, and Javier Blas

A couple of numbers. The United States imported last year in 2024, according to US government data, a grand total of… give me the theme music… $170 million of rare earth metals. Not billion – million. $170 million. I’m pretty sure that the United States imported more olive oil from probably Spain.

Tracy: I like that olive oil is your baseline value.

Javier: And how much is that? That’s the second number we are going here. How much is $170 million if you compare that to total trade between the United States and China? That is 0.03%. So it’s not a lot. And the United States could face, say, a 10x increase in the price of rare earth metals and it still will have no impact whatsoever on the American economy or the global economy.

What really drives me mad is that you are writing about rare earth metals – they are important and obviously for some very niche applications, you really need rare earth metals, but prices could go higher and those applications will just pay the price. Typically, a writer like myself, you want to sex up a bit of the story, you will say “Rare earth metals critical for the weapons industry, for missiles, and high-tech application.” Do you know where everyone of us have some rare earth metals at home? They’re used in super permanent magnets, and therefore on that absolutely critical instrument of economic warfare, which is called the vacuum cleaner.

Tracy: I will say I sympathize with editors not wanting headlines about vacuum cleaners versus military equipment and all of those important strategic things.

Javier: I just keep in mind the story, the price of rare earth metals may increase and making vacuum cleaner is a bit more expensive – I don’t know you’re going to click.

Tracy: Not to get all Judy Bloom on everyone, but rare earths, they’re not as rare as the name would imply, but walk us through where they actually come from.

Javier: A lot of them come from China. About 80%-85% of the world’s rare earth metals come from China. It’s a question of digging them out of the ground and then processing. The big difficult part is processing, because it’s very polluting and it’s a reason why all the processing has moved from everywhere else in the planet into China, because no one wanted to deal with how nasty the process is.

Here is also the other question: If you want to do rare earth metals – processing in particular – outside China, what you need is much higher prices. If anything, the problem today with rare earth metals, and if we want to develop an industry of rare earth metals outside China, is that prices are too low. We need much higher prices and then everyone will do rare earth metals. The other thing that will happen is that if the price goes to a level that incentivizes everyone taking a bit of care, a lot of engineers in the vacuum cleaning industry will find ways to do it without rare earth metals. Also, people will actually collect the vacuum cleaners and recycle the magnets for other use.

Tracy: But if rare earths are such a small component of something like a vacuum cleaner, I imagine the prices would have to go up absolutely astronomically for that even to be a consideration for a company making these things.

Javier: Most of the time the prices don’t go nearly as high. Prices are beginning to rise again now, but prices stay relatively low compared to where historically prices have been. We have had the latest headlines are about rare earth metals and export restrictions. We have some similar headlines for other category of metals that we call critical minerals, another fantastic exercise of labeling. You want to sell something, call it “critical minerals.”

People were really concerned because China was imposing some export restrictions on tungsten, bismuth, molybdenum, and indium – this sounds to me like high school chemistry. You would think, “Oh my god, what is happening with the price of all of these?” This was not announced yesterday, this was announced a couple of months ago. Prices move, and yes the price of say indium moved to $345 per kilogram. Is that a lot? Yea, it’s a 20% increase from where we were at the end of last year. But about 10 years ago, that cost, today $345, was worth $800 per kilogram. Did you notice 10 years ago that it was a crisis on the indium market and everyone was a bit worried about it? I didn’t notice…

…Javier: To me, the other very important topic in trade and oil is that oil used to be almost the largest component of the American trade deficit in goods. You go to 2008, the US trade deficit was running around $800 billion a year. Of that, nearly $400 billion was oil. Today we are in a surplus for oil…

…Javier: Let’s call it the Goldilocks, the middle ground, what the oil patch will love and mainstream will be happy, say $75 a barrel. $75 a barrel is not breaking the budget of any middle-class family or working-class family when it comes to gasoline in the United States. And $75 a barrel, the American oil industry is making money, no problem whatsoever. Whoever is complaining at $75 probably doesn’t have a very good business case. The main problem is to make everything work at $75.

Just for the sake of the argument, let’s say that the magic number is $75. You cannot get that running unless you get OPEC on board and they keep restraining production and losing market share. $75 a barrels means that the consumers are happy and they continue to consume, but also that the US shale industry continues to grow and at some point someone needs to produce less. Even if that magic number existed – and I think that $75 probably is about right – you need OPEC to play ball and accept that they’re going to lose market share forever and ever. I don’t think that they’re on that business.

4. The AI Data-Center Boom Is Coming to America’s Heartland – Jennifer Hiller

Manufacturers have passed over this patch of farmland for nearly two decades, a string of setbacks that left this one of the poorest corners of Louisiana.

A quarter of the 20,000 residents in Richland Parish live in poverty. Farm jobs dwindled when agriculture became more efficient, forcing people to move away for work. Hopes for an auto manufacturing plant later went bust.

Now, the community is hoping for a new savior: AI.

Meta Platforms scooped up 2,700 acres of farmland last year for what would be its largest-ever data center, built over flat rice fields 45 minutes west of the Mississippi River.

At 4 million square feet, or 70 football fields, Meta’s data center will cost $10 billion and sit on more acreage than Louisiana State University in Baton Rouge, which has more than 34,000 students.

Building advanced artificial-intelligence systems will take city-sized amounts of power, which has turbocharged electricity demand projections for the first time this century…

… Gregory Upton, executive director at LSU Center for Energy Studies, estimates Meta could use 15% of Louisiana’s current electricity generation.

That is worrisome to other utility customers largely because of the mismatch between the 40-year to 50-year lifespan of gas-fired power plants and Entergy’s 15-year deal with Meta. They don’t want to be on the hook for the infrastructure.

“They want to use ratepayer money to finance something that they currently only really say they want for 15 years,” said Logan Atkinson Burke of the Alliance for Affordable Energy, an advocacy group for residential customers…

…“We hear about this constantly,” Francis said, noting someone must guarantee the payments on new projects for about 30 years.

“Guess who?” Francis asked. “It’s going to be the ratepayers.”

Commissioners will consider Entergy’s request later this year, but Francis says Meta’s investment is likely worth the risk of stranded assets down the line.

5. A Positive Reframe of What Trump Might be Doing for America in the Long Term – Peter Leyden

Let’s adopt the big-picture, long-term perspective of a historian in 2100 to try to better understand what’s really going on today and what’s probably going to happen in the near future…

…If I channel that historian in 2100, he or she would probably distill the big-picture story of the key challenges facing America at the historic juncture of 2025 as roughly this:

The Pax Americana with America as the global policeman enforcing order in the international system was coming to an end. That system had a great long run of 80 years, starting at the end of World War II, but could not go on much longer.

The United States military budget in 2025 was $850 billion — more than the military spending of the next dozen countries combined — and America was saddled with chronic budget deficits that could not sustain that kind of spending.

The bureaucratic welfare state that had been the backbone of post-war society in America and throughout the West was also fiscally unsustainable and way past its prime in effectiveness. The large aging populations of these developed economies were putting mounting pressures on the budgets of entitlement programs, which were devised for the smaller numbers of elderly long ago.

The view looking forward only got worse. Going into 2025, the federal government already held more than $35 trillion in debt and it was adding another $2 trillion to the deficit that year. This chronic budget imbalance could not go on without something big changing.

Our historian in 2100 might then shift from the daunting challenges to their solutions and the political developments that led to positive change.

One big change that had already arrived by 2025 was artificial intelligence. This new general-purpose technology had reached the point where it was ready to be deployed in many new ways through the economy, society, and government. These were the early days of shifting work to intelligent machines but those who understood the potential of the technology could see how many fundamental system changes could scale up in the next 25 years.

The old systems of government of the last 80 years needed to be dismantled in order to free up resources and create the space needed to build these new 21st-century systems. (The same held true for the old systems of carbon energy needing to be dismantled to clear the way for clean energy but let’s stick to the government for now.)

The Democrats, as the party of greater government intervention, were never going to summon the political will to lead the charge on dismantling big, bureaucratic government. Government workers, and the unions that organized them, were a core constituency of the party. The Dems, whether they were bleeding-heart liberals or left-wing progressive champions of the poor, were never going to trigger the transition, knowing the trauma it would create.

For that matter, traditional Republicans over the last 40 years had not been able to summon the will to dismantle much of anything despite their small government rhetoric and worry about deficits and debt. That traditional party was also as committed as ever to beefing up the military and expanding its commitments around the world.

Donald Trump finally provided the wrecking ball — on his second try……Does that mean that Trump, the Republican Party, and the conservative movement are victorious and will now rebuild America in their image? Does that mean that the Democrats and the progressive movement are vanquished and will be sidelined for a generation or more?

The truth is arguably the opposite. When you look at what’s going on through the lens of long-ball politics, then you can see that Trump might be solving one other huge challenge that America needs solved right now.

America needs to finally end the roughly 50/50 political stalemate that has paralyzed the country for the last 25 years. We try the increasingly divergent political formulas of Blue America, then Red America, then back again, and back yet again.

We need a long-term 60/40 political coalition that can more fundamentally reinvent America over the course of the next 25 years so that it can thrive for the rest of the century.

Trump is in the process of creating that political opportunity — for the Democrats and Blue America…

…Throughout American history, populist movements have been great at dismantling and destroying things. They’ve also been horrible at building anything of lasting consequence — let alone new systems that will define the next era…

…In Trump’s case, he is an absolute master at channeling anger at existing systems and the elites who run and benefit from them. But now that he’s in power, he’s dredging up really outmoded ideas from a truly bygone era, like tariffs, as solutions to today’s problems.

Trump, his MAGA administration, and the current crop of Republicans now in Congress are not going to come up with the new systems that will reinvent America in a way that allows it to thrive in the 21st century. The odds of that happening are minuscule.

However, they almost certainly are going to create the space for some other political force, some other movement, some other set of leaders to pull that off. I expect that will come out of Blue America with new movements and a new generation of leaders looking forward with truly transformative ideas.

The political consequences for whoever dismantles America’s old systems are going to be profound, and I mean profoundly bad. The president and the party who dismantles those bureaucracies, as healthy as that process might be in the long run, will make enemies of all those who lose their jobs or benefits…

…By 2050, the general consensus was that Trump had made America great again — just not the way he had intended. Trump did dismantle the old Pax Americana and the old 20th-century bureaucratic welfare state, but he also dismantled the political efficacy of the Republican Party and conservative movement for a couple generations, too.

Trump unintentionally laid the foundation for the next era of American greatness to begin — not by looking backward to resuscitate the past, but by allowing others to look forward and reinvent a much better future.


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. We currently have a vested interest in Meta Platforms. Holdings are subject to change at any time.

What The USA’s Largest Bank Thinks About The State Of The Country’s Economy In Q1 2025

Insights from JPMorgan Chase’s management on the health of American consumers and businesses in the first quarter of 2025.

JPMorgan Chase (NYSE: JPM) is currently the largest bank in the USA by total assets. Because of this status, JPMorgan is naturally able to feel the pulse of the country’s economy. The bank’s latest earnings conference call – for the first quarter of 2025 – was held last week and contained useful insights on the state of American consumers and businesses. The bottom-line is this: the US economy is facing turbulence, with a multitude of problems, but consumers and businesses still remain financially healthy

What’s shown between the two horizontal lines below are quotes from JPMorgan’s management team that I picked up from the call.


1. The US economy is facing turbulence, with problems including tariffs, trade wars, inflation, and high asset prices

The economy is facing considerable turbulence (including geopolitics), with the potential positives of tax reform and deregulation and the potential negatives of tariffs and “trade wars,” ongoing sticky inflation, high fiscal deficits and still rather high asset prices and volatility. As always, we hope for the best but prepare the Firm for a wide range of scenarios.

2. Net charge-offs for the whole bank (effectively bad loans that JPMorgan can’t recover) rose from US$1.9 billion a year ago; management increased the probability weightings for downside scenarios in its CECL (current expected credit losses) framework for credit allowances in 2025 Q1 because of higher risks and uncertainties from the environment seen in the last few weeks; the increase in allowance is not driven by deterioration in credit performance; Consumer & Community Banking’s net charge-offs surged significantly from US$0.72 billion a year ago 

Credit costs were $3.3 billion with net charge offs of $2.3 billion and a net reserve bill of $973 million…

…With this quarter’s reserve bill, firm’s total allowance for credit losses is $27.6 billion. Let’s take a second to add a little bit of context to our thinking surrounding this number in light of the unique environment of the last several weeks. Our first quarter allowance is anchored on the relatively benign central case economic outlook, which was in effect at the end of the quarter. But in light of the significantly elevated risks and uncertainties at the time, we increased the probability weightings associated with the downside scenarios in our CECL framework. As a result, the weighted average unemployment rate embedded in our allowance is 5.8%, up from 5.5% last quarter, driving the $973 million increase in the allowance. So with that in mind, the consumer build of $441 million was driven by changes in the weighted average macroeconomic outlook. The wholesale build of $549 million was predominantly driven by credit quality changes on certain exposures and that lending activity, as well as changes in the outlook…

…The increase in the allowance is not to any meaningful degree driven by deterioration in the actual credit performance in the portfolio which remains largely in line with expectations…

…Credit costs were $2.6 billion, reflecting net charge-offs of $2.2 billion, up $275 million year on year, pred ominantly driven by the seasoning of recent vintages and card with delinquencies and losses in line with expectations.

3. Management is seeing recent downtrends in consumer and small business sentiment, but consumers and small businesses remain financially healthy; management is seeing consumers front-load spending ahead of tariffs; management is seeing small businesses face more challenges than large businesses because of tariffs-related uncertainty; management is seeing a drop in travel-spending among consumers, but it’s not indicative of broader patterns; management is seeing relatively weaker spending from lower-income consumers, but they are not in distress 

Consumers and small businesses remain financially healthy despite the recent down trends in consumer and small business sentiment. Based on our data, spend, cash buffers, payment to income ratios, and credit utilization are all in line with our expectations…

…On the consumer side, the thing to check is the spending. And to be honest, the main thing that we see there would appear to be a certain amount of front-loading of spending ahead of people expecting price increases from tariffs…

…In terms of our corporate clients, obviously, they’ve been reacting to the changes in tariff policy… Across the size of the clients, I think smaller clients, small business, and smaller corporates are probably a little bit more challenged. I think the larger corporates have a bit more experience dealing with these things and more resources to manage…

…We obviously saw the airlines discuss what they are seeing as headwinds for them, specifically in airline travel. And we’re seeing that too through the card spend. It’s not obvious to us that that’s necessarily an indicator for broader patterns…

…When we look at our card data and also our cash buffers and people checking accounts, of course, it is true that it is relatively weaker in the lower income segment. But when you take a step back and you ask, are we seeing signs of distress in the lower income segment? The answer is no. So sure, the margin cash buffers are lower, and you see some rotation of spend and spending is a little bit weaker than it was in the peak spending moments. But actually, some of the increases in spending that we’re seeing in April are actually coming from the lower income segment. So no evidence of distress, I would say.

4. JPMorgan’s credit card outstanding loans was up double-digits year-on-year

Card outstandings were up 10% due to strong account acquisition.

5. Auto originations were up year-on-year

In auto, originations were $10.7 billion, up 20%, driven by higher lease volume.

6. JPMorgan’s investment banking fees had good growth in 2025 Q1, with growth in debt underwriting fees but a decline in equity underwriting fees, signalling higher appetite for refinancing activity from companies; management is seeing companies adopting a wait-and-see attitude when it comes to capital markets activities because of tariffs-related uncertainty in the current environment

IB fees were up 12% year on year, and we ranked number one with wallet share of 9%. In advisory, fees were up 16%, benefiting from the closing of deals announced in 2024. Debt underwriting fees were up 16%, primarily driven by elevated refinancing activity, particularly in leveraged finance. And equity underwriting fees were down 9% year on year, reflecting challenging market conditions. In light of market conditions, we are adopting a cautious stance on the investment banking outlook. While client engagement and dialogue is quite elevated, both the conversion of the existing pipeline and origination of new activity will require a reduction in the current levels of uncertainty…

…In terms of our corporate clients, obviously, they’ve been reacting to the changes in tariff policy. And at the margin, that shifts their focus away from more strategic priorities with obvious implications for the investment banking pipeline outlook towards more short-term work, optimizing supply chains, and trying to figure out how they’re going to respond to the current environment. So as a result, I think we would characterize what we’re hearing from our corporate clients as a little bit of a wait-and-see attitude.

7. Management expects credit card net charge-offs for 2025 to be in line with previous guidance because of the mechanical way credit card charge-offs work, and not because management thinks credit card net charge-offs will really be healthy as the year progresses

On credit, we expect the card net charge-off rate to be in line with our previous guidance of approximately 3.6%…

…[Question] No change to the full year credit card net charge-off forecast. How do we square that with the rising recession risk?

[Answer] We should have not given you that forecast. We don’t know what the number is going to be. I would say that’s a short-term number. And based on what’s happening today is there’s a wide range of potential outcomes… There are some mechanical elements to the way card charge-off works. That means that it’s pretty baked, pretty far out of time a couple of quarters… It just doesn’t necessarily tell you that much about what might actually happen through the end of the year, even if unemployment were to increase significantly, it probably wouldn’t flow through the charge-offs until later.

8. Management is now incorporating 3 interest rate cuts for 2025, up from the previous expectation of 1 cut

If you remember last quarter we said that we had one cut in the curve. I think, latest curve has something like three cuts.

9. JPMorgan’s economists think there’s a 50% chance of a recession

What I would say is our excellent economists, Michael Feroli, I call him this morning, specifically to ask him how they’re looking at their forecast today. And they think it’s about 50-50 for a recession. So I’ll just refer to that.

10. Management thinks inflation in the US will be sticky

We have sticky inflation. We had that before. I personally have told you I don’t think that’s going to go away, and that relates to that.

11. Management thinks the US dollar will remain the reserve currency globally

Obviously, the US dollar still is the reserve currency, and that isn’t going to change though some people may feel slightly differently about it.

12. Management thinks that the current situation is different from past cycles

[Question] You’ve been through many cycles. And I think we’re all interested in understanding how you think this next cycle is likely to progress. And I’m wondering, is there anything that you’ve seen in the past that looks like this or that you would suggest if any slowdown coming forward, is it more likely to be similar to what kind of prior cycle you’ve seen?

[Answer] This is different, okay? This is different. This is the global economy. And please read my chairman’s letter. The most important thing to me is the Western world stays together economically when we get through all this and militarily to keep the world safe and free for democracy. That is the most important thing… We obviously have to follow the law of the land, but it’s a significant change we’ve never seen in our lives.


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. I don’t have a vested interest in any company mentioned. Holdings are subject to change at any time.

What We’re Reading (Week Ending 13 April 2025)

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 13 April 2025:

1. My Thoughts on Tariffs, Economic History, and the Market Decline (Transcript here) – Morgan Housel

The United States has lost a lot of manufacturing employment over the last 50 years. Of course, it absolutely has. Often when that is addressed, it is immediately jumped to, that’s because we shipped those jobs overseas. The factories that used to be in Indiana and Tennessee and Mississippi, we shipped them to Mexico and Canada and China. There is some truth to that, of course. Indisputably there is, I think, a bigger truth that gets lost, which is that where a lot of those jobs went was not necessarily to another country – it was to automation. It was two robots. My favorite example of this – I wrote this 10 years ago, I had to go fish this up from an old article that I wrote – is about a US steel factory in Gary, Indiana. In 1950, this individual factory produced 6 million tons of steel with 30,000 workers. In 2010 – I guess it was 15 years ago that I wrote it – it produced 7.5 million tons of steel with 5,000 workers. So during this period, they increased the amount of steel that they were making, and they did it with 25,000 fewer workers. They went from 30,000 workers to 5,000. That story, I think, can be repeated across virtually everything that is made in the United States and around the world over the last 50 years.

Very interesting thing that I read the other day is that China, the manufacturing powerhouse of the globe, has fewer manufacturing workers today than they did 10 years ago. They are making more stuff than ever before, they are building factories faster than ever before, and they have fewer people working in those factories because China, more than anybody else, probably throughout history, is installing and using robots and automation in their manufacturing at a ferocious pace. So you can keep making more and more stuff, but you need fewer and fewer people working on those assembly lines. That is often lost in the debate.

Because if we were to bring back the manufacturing capacity to the United States – and that’s a separate debate, that’s a much longer debate – but let’s say that we do, it would not in any circumstances bring back the manufacturing jobs and the employment levels that we had in the 1950’s…

…One other example of this in the auto industry. In 1990, not that long ago, the average American auto worker working on an assembly line, their share of total auto production was about seven vehicles per year. So take the number of vehicles that were produced in the United States, divide that by the number of auto workers, and it was about 7. The average worker was responsible for 7 vehicles per year. By 2023, again, that’s just like one generation apart, not even that much, the average auto worker in the United States was responsible for producing 33 vehicles per year. It went from seven to 33. We are still producing a lot of cars in the United States. We still make a lot of vehicles here in the United States. It just does not require the amount. Of labor that it used to…

…There was this period when, because of the state of global geopolitics, America had a manufacturing dominance to itself for a good 20 years from probably 1945 through the end of the 1960s. That was also a period when, for many different factors – we don’t need to go into all of them – but white collar workers were not making that much money. If you worked on Wall street in the 1970s, that was not a place to make a lot of money. That was an admin accounting job that was not very looked highly upon because you didn’t make that much money. Bankers were not making nearly the kind of money that they made in the decades before or after this period. And that was important because the blue collar manufacturing workers, by comparison to others in the economy, to others in their town, were doing great. So even if their wages were lower back then than they would be today, even adjusted for inflation, when the manufacturing worker compared himself to the banker or the accountant or the lawyer or the doctor by comparison, he said, “I’m doing pretty great. I’m doing pretty well.”…

…So the manufacturing dominance, not just in autos, but in lots of things – heavy machinery and whatnot – started to erode in the ‘70s, ‘80s and ‘90s and really started to explode higher in the 2000’s when China really came on board in terms of global manufacturing. That occurred at the same moment when white collar workers in finance and accounting and office jobs started making fortunes. Huge sums of money. So at the same moment that the manufacturing worker was losing their jobs, both to automation and foreign competition, the white collar workers were just having a field day and making money hand over fist, which made what manufacturing jobs existed feel even worse by comparison. Because let’s say you’re an auto worker making $25 an hour. In one era, that might feel great. But if all of a sudden your neighbor who is a project manager at KPMG is making $300,000 a year, your $25 an hour doesn’t feel that great anymore because your neighbor has a bigger house and more cars and is sending their kids to private school. So by comparison, you feel worse off, even if your wages, adjusted for inflation, may have been going up…

…It is so understandable that you have millions of workers who say, “This economy worked for me 50 years ago and it doesn’t today. My dad, my grandpa, had great jobs in the GM factory and I can’t have that today.” So understandable that that would be the thought process of millions of workers. I think it is naive and insulting for people who are on my side of the tariff debate – who say tariffs are a bad idea – who cannot understand the views of those kind of people. Because if I was in that situation, and if lots of people who disagree with tariffs were in that situation, they’d be arguing for the same thing.

I think one of America’s strengths, over time – this has been true for hundreds of years – is (this sounds kind of crazy, but I think it’s true) a firm belief in things that are probably not true. That has always been a strength of the United States. This goes back to the very early days of the settlers and the colonizers who back in Europe, were told that America was a land of absolute abundance and when you got there, there would be just rivers overflowing with gold and whatnot – and actually, it was a malaria swamp when they got to the East Coast of the United States. But we believed, it was always believed, that this was the promised land. That was what brought the people over. Even when they came to the United States and settled, it was that belief too. America has always been so unbelievably optimistic, particularly at the individual level. And that’s why I think we’re so good at entrepreneurship…

…But let me say a couple of things about investing, because that has been – the initial reaction to the tariffs has been entirely in the stock market, which as I speak here, is down about 20% or so from its highs that. were reached just a couple weeks ago. The tariff impact has not hit the broader economy in terms of inflation at the grocery store or mass layoffs or whatnot. But so far it’s been in the stock market…

… I think it is possible to be an engaged and informed citizen, even a social media junkie reading the news, and a calm investor at the same time. I purchased stocks early last week, not because of anything that was going on in the news, but because I do that every month around the first of the month. I do it every single month. I’ve done that for about 20 years now. I’ll do it next month, I’ll do it the month after that. That won’t change. I think it never changes. So I think you can simultaneously dollar-cost-average, remain long-term optimistic, not panic about anything that’s going on in the world, you can enjoy life, spend time outdoors, hang out with your kids, eat good food, listen to good music, have a good time, and at the same time, if you are of the same belief as me, realize how destructive and unnecessary what we’re going through is…

…We have in the past been through much more uncertain times than we’re going through right now. But it never feels that way, or it rarely feels that way. Because when we think about the past economic crises, COVID, Lehman Brothers, 9/11, Pearl Harbor, those kind of events, we know how the story ended, and we know the story did end, and we know that we eventually recovered. But whenever it is a current crisis, a current period of uncertainty, you don’t know that. You don’t know when it’s going to end. You don’t know how it’s going to end. Some people don’t know if it will ever end…

…One other thing that’s very different from this period – this tariff period – that we’re going through, if you compare it to other periods of economic upheaval like COVID and Lehman Brothers and 9/11 and Pearl Harbor, is that this could end in the next hour. These tariffs could be immediately removed in the next hour. Or even if it’s not that, there could be certain laws, whether it’s from the courts or from Congress, that could end these very quickly. Obviously, we didn’t have that with COVID. There was no button on anyone’s desk that said “Remove the virus. Just click this button.” We do have that now. So what is very different about this is how quickly it could end and if that were to happen, how ferocious the rally in stock markets would almost certainly be, even if there was some permanent damage, because global trading partners don’t trust us as much as they used to.

2. America Underestimates the Difficulty of Bringing Manufacturing Back – Molson Hart

Think of a supply chain as a company’s ability to get the components it needs to build a finished product. Suppose you wanted to build and sell wooden furniture. You’re going to need wood, nails, glue, etc. Otherwise you can’t do it. If you want to build an iPhone you need to procure a glass screen, shaped metal, and numerous internal electronic components.

Now you might be thinking, “what do you mean America has a weak supply chain?” I’ve built furniture, I’ve assembled a computer. I can get everything I want at Home Depot and at Amazon.

That’s because America has an amazing consumer supply chain, one of the best, if not the best in the world, but this is totally different from having an industrial supply chain…

…The inputs to manufacturing are not just materials, labor, and knowhow. You need infrastructure like electricity and good roads for transportation, too.

Since the year 2000, US electricity generation per person has been flat. In China, over the same time period, it has increased 400%. China generates over twice as much electricity person today as the United States. Why?

Manufacturing.

To run the machines which make the products we use, you need electricity, a lot of it. We already have electricity instability in this country. Without the construction of huge amounts of new energy infrastructure, like nuclear power plants, we cannot meaningfully increase our manufacturing output.

And it would put huge stress on our roads and create lots more dangerous traffic. When we import finished goods from foreign countries, a truck delivers them from the port or the airport to distribution centers, stores, and where we live and work.

When you start manufacturing, every single component, from factory to factory, needs to be moved, increasing the number of trucks on the road many times.

Paving more roads, modernizing our seaports, improving our airports, speeding up our train terminals, and building power plants in the costliest nation in the world to build is a huge undertaking that people are not appreciating when they say “well, we’ll just make it in America”…

…There are over a billion people in China making stuff. As of right now there are 12 million people looking for work in the United States (4% unemployment). Ignoring for a moment the comparative inefficiency of labor and the billions of people making products outside of China, where are the people that are going to do these jobs? Do you simply say “make America great again” 3 times and they will appear with the skills needed to do the work?

And where are the managers to manage these people? One of the reasons why manufacturing has declined in the United States is a brain drain towards sectors that make more money. Are people who make money on the stock market, in real estate, in venture capital, and in startups going to start sewing shirts? It’s completely and totally unrealistic to assume that people will move from superficially high productivity sectors driven by US Dollar strength to products that are low on the value chain…

…Most people think that the reason why American manufacturing is not competitive is labor costs. Most people think this can be solved by automation.

They’re wrong.

First, China, on a yearly basis installs 7x as many industrial robots as we do in the United States. Second, Chinese robots are cheaper. Third, most of today’s manufacturing done by people cannot be automated. If it could, it would have already been done so, by China, which, again, has increasingly high labor costs relative to the rest of the world.

The robots you see on social media doing backflips are, today, mostly for show and unreliable off camera. They are not useful in industrial environments where, if a humanoid robot can do it, an industrial machine which is specialized in the task can do it even better. For example, instead of having a humanoid robot doing a repetitive task such as carrying a boxes from one station to another, you can simply set up a cheaper, faster conveyor belt.

Said another way, the printer in your office, is cheaper and more efficient than both a human and a humanoid robot with a pen, hand drawing each letter…

…Let’s go back to that last example, the China based and the US based companies which were importing goods into the United States. That US based importer could’ve been a manufacturer. Instead of finished iPhones, perhaps they were importing the glass screens because those could not be found in the USA, for final assembly.

Our government applied tariffs to finished goods and components equally.

I’ll say that again. They applied the same tax to the components that you need to make things in America that they did to finished goods that were made outside of America.

Manufacturing works on a lag. To make and sell in America, first you must get the raw materials and components. These tariffs will bankrupt manufacturers before it multiplies them because they need to pay tariffs on the import components that they assemble into finished products.

And it gets worse.

They put tariffs on machines. So if you want to start a factory in the United States, all the machinery you need which is not made here, is now significantly more expensive. You may have heard that there is a chronic shortage of transformers needed for power transmission in the United States. Tariffed that too.

It gets even worse.

There is no duty drawback for exporting. In the past, even in the United States, if you imported something and then exported it, the tariff you paid on the import would be refunded to you. They got rid of that so we’re not even incentivizing exports to the countries that we are trying to achieve trade parity with.

Tariffs are applied to the costs of the goods. The way we’ve structured these tariffs, factories in China which import into the United States will pay lower tariffs than American importers, because the Chinese factory will be able to declare the value of the goods at their cost, while the American importer will pay the cost the factory charges them, which is of course higher than the factory’s cost.

Worse still.

With a few exceptions like steel and semiconductors, the tariffs were applied to all products, ranging from things that we will never realistically make like our high labor Tigerhart stuffed animals to things that don’t even grow in the continental USA, like coffee…

…Unless this policy is quickly changed, this is the end of America’s participation in globalization. If we had enacted these policies in 2017 or 2018, they stood a much stronger chance of being successful. That was before Covid. China was much weaker economically and militarily then. They’ve been preparing 8 years for this moment and they are ready.

China trades much less with the United States as a percent of its total exports today than it did 8 years ago, and as such is much less susceptible to punishing tariffs from the United States today than it was back then.

Chinese made cars, particularly electric vehicles, are taking the world by storm, without the United States. Go to Mexico to Thailand to Germany and you will see Chinese made electric vehicles on the streets. And they’re good, sometimes even better than US made cars, and not just on a per dollar basis, but simply better quality.

That is what is going to happen to the United States. Globalization will continue without us if these policies continue unchanged.

3. How big of a problem are tariffs for China’s economy? – Amber Zhang

In the short term (e.g. 1-year horizon), the direct impact on China’s GDP from trade tensions will likely be limited. Exports to the U.S. now make up only a small portion of China’s GDP, and since 2018, China has already reduced its reliance on direct exports to the U.S.

However, it would be irrational to say that China is winning this game because China’s export exposure to US is not huge. The trade war escalation could impact global trade volume, and while some companies are not directly exporting to US, they are still on the supply chain which are intertwined.

Tariffs may not directly slash revenues of listed Chinese companies, especially onshore ones because their exposure to US revenue is small, but will impact confidence of the export-oriented business, with majority of them being unlisted, private companies. And right now, confidence is exactly what China lacks. Even without the trade war, the country is still struggling through a deflationary cycle triggered by the burst of its real estate bubble…

…It’s also unrealistic to assume that China can simply “trade with other countries” to offset U.S. tariffs and make the problem completely go away. In our post Could China’s exports continue to drive GDP growth? from last year, we highlighted how China’s export penetration has already increased significantly across emerging markets outside Asia over the past decade. This means the room for further expansion is now much more limited than it was ten years ago. And with tariffs dampening overall global import demands, China’s exports will come under indirect pressure…

…In the world post globalization, the only logical path for China is to boost domestic consumption…

…On that front, an analysis by Morgan Stanley team provides a framework that I find helpful in thinking about this new “China Dream.” According to their study, for domestic consumption to become a “main pillar” of China’s economy, the goal is to increase domestic consumption by 30% by 2030. This translates to about 5.4% annualized growth per year.

If China successfully achieves this goal, a 30% increase in domestic consumption would be roughly $3 trillion USD, which Morgan Stanley estimates is equivalent to the reduced import demand from global countries caused by U.S. protectionism…

…This path isn’t just about boosting demand through short-term measures like vouchers. It’s about creating a new paradigm where China transitions from an export-driven economy to a major consumer market, alongside the U.S. This shift will be a game-changer, not just for China, but for the world.

4. Why Trump Blinked on Tariffs Just Hours After They Went Into Effect – Annie Linskey, Josh Dawsey, and Meridith McGraw

President Trump finally blinked.

It took a week for the plunge in the stock and bond markets—along with a sustained campaign by executives, lawmakers, lobbyists and foreign leaders—to prompt Trump to roll back for 90 days a major element of his sweeping tariff plan…

…Shortly after Trump published his post, as markets rose, Bessent stood outside the entrance to the West Wing and explained that the move to pause some of the tariffs was discussed Sunday when the two men met. “He and I had a long talk,” Bessent said before a crowd of reporters. “This was his strategy all along.”

Bessent was flooded with worried calls from Wall Street over the weekend and felt strongly he had to persuade Trump that a pause was needed. It wouldn’t be a capitulation, Bessent argued, because they were going to have so many deals.

He revealed little publicly about why the president and his team waited until Wednesday afternoon to enact it, with Trump saying that he decided on the move Wednesday morning…

…Another factor that made Trump more willing to relent on the tariffs, a person who talked to him said, was that so many countries are in negotiations with the administration.

Trump was also swayed by the stock market and the parade of business leaders expressing concerns about the tariffs. Over the past few days, executives and lobbyists had flooded White House chief of staff Susie Wiles’ phone, according to a person close to her. A White House aide noted that it was standard for the president’s chief of staff to field calls on his behalf.

The message delivered to Trump and his top advisers by chief executives was they needed to find an off ramp…

…Trump was also in listening mode. Over the past few days, he has been asking friends and advisers about the markets, and he indicated he was closely watching them. At the White House on Wednesday, he had lunch with financier and investor Charles Schwab and met with Michigan Democratic Gov. Gretchen Whitmer, who had warned that Michigan was already feeling the impact of the tariffs throughout its automotive industry—events that came after his decision but signaled he was widely gathering input.

On Tuesday evening, Trump said that he absorbed the bad news about a plummeting bond market. “I saw last night where people were getting a little queasy,” Trump said Wednesday about the bond market.

Trump, an avid consumer of cable news, said that he watched Dimon’s interview Wednesday morning with Maria Bartiromo on Fox Business. During the interview, Dimon said a recession was a “likely outcome” of the new tariff program, but also defended the idea of some tariffs as a way to improve trade. He urged the president to give Bessent time to make deals. “I’m taking a calm view, but it could get worse,” Dimon said.

Dimon hasn’t had a substantive conversation with Trump for years, people familiar with the matter said. While his appearance on the Fox Business show had been in place for some time, Dimon knew that Trump and his inner circle often watched Fox and that his message would likely get through to them, one of the people said. 

5. Economic Growth Now Depends on Electricity, Not Oil – Greg Ip

Americans have long equated energy security with oil. The country wanted as much as possible because of the havoc an interruption to supply—from wars, disasters and political convulsions—can cause.

In coming years, though, energy security will mean electricity.

Power demand, stagnant for decades, is now growing rapidly, for data centers to run artificial intelligence and other digital services and, in time, transportation and buildings.

An economy dependent on electricity will be different from one dependent on oil. It will require mammoth investment in generation, distribution and transmission. It will challenge regulators and political leaders, as the supply and price of electricity become as politically potent as that of gasoline…

…With oil, an interruption to supply in any part of the world could ripple ashore in the U.S., even once it became a net exporter, which has long influenced U.S. foreign and security policy.

Electricity comes from almost entirely domestic sources—coal, gas, nuclear, hydro, wind, solar and geothermal—insulating it from foreign influences or interruptions to any single fuel source. At night, the electricity that no longer flows from the solar panels in Gloucester comes from Dominion’s nuclear and gas plants and, in the future, batteries. “There’s no single power source that’s going to reliably serve all of our customers,” said spokesman Aaron Ruby. “We need nuclear, we need natural gas, we need renewables.”

The threats to electricity security are different: extreme weather and other disasters; sharp fluctuations in demand, such as from cryptocurrency mining; or weather that reduces solar and wind power.

Most of the cost of oil and gas is the fuel itself, whereas for electricity it is the generation, transmission, storage and distribution infrastructure. Oil-and-gas extraction and refining contribute twice as much to gross domestic product as utilities, but electric utilities alone invest 50% more in plant, equipment and technology.

So the electric economy needs a lot of real estate and equipment, both of which have been in short supply. “We’re buying 10 times as much electrical equipment as a few years ago. We’re very short on transformers and the other basic equipment that goes into substations,” said Rob Gramlich, president of Grid Strategies. “The companies that were manufacturing those things five to nine years ago were looking at very low demand, laying people off and turning to other things.”

Those shortages drive up costs, which can get passed on to ratepayers. If expected demand doesn’t materialize—some have warned of a data-center bubble—the cost of unneeded capacity will also be shifted to customers.


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. We currently have a vested interest in Amazon. Holdings are subject to change at any time.

Lessons From Tariff History

Arguably the biggest event in the financial markets this year so far has been the Reciprocal Tariff Policy introduced by the US government, under the Trump administration, last week. The policy is based on calculations that appear haphazardly made-up. Regardless of the intellectual-legitimacy of the Reciprocal Tariff Policy, if the new tariff rates hold, they will represent the highest weighted average tariff rate implemented by the US in more than 100 years, according to investment bank Evercore.

In uncertain times like these, there is some usefulness to learn from history. There’s a presentation from the FDRA, a US-based trade organisation representing the footwear industry, that looks back at past episodes of major increases in US tariff rates going back nearly 250 years. The presentation is fantastic – I encourage anyone reading this article to also look at the whole deck – and I want to document my takeaways for easy reference in the future. My notes:

  • There have been five instances since 1776 – and before the recent Reciprocal Tariff Policy – where the US had raised tariffs significantly and they happened in 1828, 1890, 1922, 1930, and 2018; the 1930 episode is commonly known as the Smoot-Hawley tariff era.
  • In past episodes of higher tariffs, US consumers had to pay higher prices each time.
  • When the US raised tariffs in the past, its trading partners always introduced retaliatory trade-related actions against the US.
  • The political party that pushed for the higher tariffs was subsequently voted out in the next voting cycle.
  • The 1930s Smoot-Hawley tariffs occurred when the US was running a major trade surplus, unlike today, when the US has a substantial trade deficit. In fact, the current trade deficit is a major driving force for the Trump administration introducing the Reciprocal Tariff Policy.

Although the lessons from history are useful, it’s also important to note that they can at best be used to form expectations and not predictions. It’s anybody’s guess as to what happens next with the US’s trade policies and thus the US economy.


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. I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

What We’re Reading (Week Ending 06 April 2025)

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 06 April 2025:

1. The Effects of Tariffs: How the Machine Works – Ray Dalio

Tariffs are taxes that:

1) raise revenue for the country imposing them that both the foreign producers and the domestic consumers pay (how much paid by each depends on their relative elasticities), which makes them an attractive tax

2) reduce the global efficiencies of production

3) are stagflationary for the world as a whole, more deflationary for the tariffed producer, and more inflationary for the importer that imposes the tariffs

4) make companies in the importing/tariffing countries more protected from foreign competition in the domestic market, which make them less efficient but more capable of surviving if aggregate domestic demand is maintained through monetary and fiscal policy

5) are necessary in times of an international great power conflict to assure domestic capabilities for production

6) can reduce both current account and capital account imbalances, which in plain English means reducing the dependencies on foreign production and foreign capital which is especially valued in times of global geopolitical conflicts/wars.

Those are the first order consequences.

A lot of what happens from there depends on how:

1. tariffs are responded to by the tariffed country/countries

2. currency rates are changed

3. monetary policies and interest rates are changed by the central banks and

4. fiscal policies are changed by the central governments in response to these pressures.

Those are the second order consequences.

2. China’s demographic paradox: empty cribs and full pet beds – Amber Zhang

For the third consecutive year, China’s population has declined, dropping by 1.39 million in 2024 to 1.4083 billion. While the birth rate showed a modest increase from 6.39 births per 1,000 people in 2023 to 6.77 in 2024, deaths still outnumbered births, with 10.93 million people dying last year—pushing the death rate to a five-decade high…

…Yet amid this birth drought, another trend is flourishing: young Chinese are increasingly channeling their parental instincts toward pets, creating a booming industry catering to “fur babies”; some even lavish generously on luxury products and services that were once exclusively reserved for humans…

…In some cities, local governments are implementing increasingly generous subsidies to encourage childbearing. For instance, the city of Hohhot has recently launched what might be China’s most aggressive birth incentive program yet.

Starting March 1, 2025, parents in this northern city of 3.6 million will receive substantial cash rewards for having children: a one-time payment of 10,000 yuan ($1,394) for a first child, annual payments of 10,000 yuan for five years for a second child (totaling 50,000 yuan), and annual payments of 10,000 yuan for ten years for a third child (totaling 100,000 yuan).

The urgency is clear: Hohhot’s birth rate stood at just 5.58 births per 1,000 people in 2023, below the national average of 6.39…

…When it comes to having children in China, a counterintuitive pattern manifests: the wealthier regions do not necessarily see more childbirths. This demographic paradox poses a challenge to the conventional wisdom that financial stability leads to larger families.

For instance, in 2022, Shanghai—China’s financial powerhouse—recorded just 4.35 births per 1,000 residents, while remote Tibet registered 14.24, more than three times higher. Other wealthy regions like Jiangsu (5.23) and Beijing (5.67) similarly lag far behind less developed provinces like Guizhou (11.03) and Ningxia (10.6)…

…However, on the other end of the spectrum, numerous young Chinese individuals are treating their pets as if they were their babies…

…Her business offers custom-designed pet outfits ranging from 200-400 yuan each, with some clients ordering new clothes monthly. “They basically all take their pets out in little strollers, and every season they travel with their dogs. There are almost no ‘naked dogs’ here—they all wear clothes.”

Although the price range of 200-400 yuan exceeds that of many children’s clothing (not to forget that the one-time subsidy for the first birth in Hohohot is 10,000 yuan), pet owners do not hesitate at such a price…

… As birth rates plummet, a parallel trend is emerging: young Chinese are channeling parental instincts and disposable income toward pets, treating them with a devotion once reserved for children.

Our numbers back up this observation as well. Since 2019, online sales of mother and baby products relative to pet products have been on the decline, indicating that the pet product sector has been growing at a faster rate…

…The conventional narrative suggests young Chinese aren’t having children because they can’t afford to. Housing prices in major cities have soared beyond reach for many, education costs are high, and work-life balance seems increasingly elusive in a competitive economy. These financial pressures are real.

Yet this explanation falls short when we consider that many of the same young people who find children unaffordable are spending lavishly on pets. A Shanghai resident who balks at the cost of diapers might think nothing of spending 400 yuan on a designer dog jacket or 680 yuan on premium cat food. The annual cost of keeping a dog in China now averages nearly 3,000 yuan—a significant sum that many willingly pay…

…The rise of pet parenting speaks to changing emotional needs in a fast-paced, often isolating urban environment. Pets provide unconditional affection, without the decades-long commitment and societal expectations that come with raising children. They allow young people to nurture and care for another being without fundamentally altering their lifestyle or identity.

And this is especially true for women. As regions become wealthier, education levels rise, women gain more career opportunities, and traditional family structures evolve. The cost of raising children in these areas also increases dramatically—not just financially, but in terms of time, career sacrifices, and lifestyle changes.

In more affluent cities and provinces in China, society often expects parents to invest enormous resources in each child to ensure their success. Many parents feel pressured to provide the best education, extracurricular activities, and social resources—this is the so-called “quality over quantity” mindset that was first promoted during the one-child policy and now becomes common in provinces like Jiangsu, Zhejiang, and first-tier cities, even after the one-child policy is in the history.

But with a pet, one can still travel, focus on a career, and maintain independence. Social media amplifies these trends, making pet ownership a lifestyle statement and identity marker in a way that parenthood, once taken for granted, no longer is.

3. How to Make 267%—or Lose 90%—on Treasury Bonds – Jason Zweig

If you’d bought the leading exchange-traded fund investing in long-term U.S. Treasury bonds at its peak in August 2020, you’d have lost 41.3% by now—even after reinvesting your interest income…

…Over the same period, the Direxion Daily 20+ Year Treasury Bull 3X Shares ETF, which seeks to triple the daily return of a long-term Treasury bond index, lost 90.2%, according to FactSet. Its mirror-image fund, Direxion Daily 20+ Year Treasury Bear 3X Shares, which aims to deliver three times the opposite of the long-term bond’s daily return, gained 266.6%…

…Officially, “ETF” stands for exchange-traded fund—a tool that makes investing simple. This subset of ETFs, though, is so sensitive to market moves that the acronym should stand for “extra-touchy funds.” They are anything but simple.

Extra-touchy funds come in two basic forms: leveraged and inverse…

…Leveraged funds use total-return swaps or other derivatives to amplify the daily returns of an index, a basket of securities or even a single stock. Leveraged ETFs can aim to deliver twice or even triple the daily return of the underlying asset, turning a 1% market rise into a 2% or 3% gain; they also magnify losses the same way.

Inverse funds seek the opposite of an asset’s daily return. Depending on how they’re structured, they can turn a 1% daily loss into a 1%, 2% or 3% gain; conversely, they can turn a 1% market gain into a loss of 1% or more…

…Imagine two ETFs. One tracks an index directly, without leverage. The other, which is leveraged, seeks to triple the daily return of the index. You’ve invested $100 in each fund, although the leveraged fund gives you $300 in exposure.

Now, to use an extreme example, let’s say the index gained 5% yesterday and loses 5% today.

Your stake in the first fund would have been worth $105 at yesterday’s close. After today’s 5% loss, you’ll have 95% of $105, or $99.75.

The leveraged fund tripled yesterday’s 5% gain, pushing the value of your position up to $115 and your exposure to the index up to $345.

That means today’s 5% drop in the index takes $17.25, or 5% of $345, off yesterday’s closing value of $115. That leaves you with $97.75.

To get back to your $100 starting point, you need a 0.25% gain in the unleveraged fund but a 2.3% gain in the leveraged fund. Of course, if the market went up 5% two days in a row, you’d be far ahead in the leveraged fund. Depending on the path of the market’s changes from day to day, the leverage can enrich you or leave you surprisingly deep in the hole…

…In a “trending” or repeatedly rising (or falling) market, you can make a ton of money on such funds. In a jagged market with uneven ups and downs, anything can happen.

Here’s why all that math matters: Getting double or triple the daily return of an index doesn’t mean you will outperform the index twofold or threefold in the long run.

4. Can the world’s free-traders withstand Trump’s attack? – The Economist

Countries are also diversifying trading partners, forging new alliances and building a new rule-making architecture. This has been made newly feasible by a decline in America’s and China’s share of global trade. At the start of the 21st century, America accounted for a fifth of global imports; today it makes up just an eighth. Its role as a consumer has also shrunk: the proportion of global value-added trade tied to American final demand fell from 22% in 2000 to 15% in 2020, the most recent year for which data exist. This reflects not only the rise of emerging markets and regional supply chains, but also changes in America’s economy. As services have grown, demand for imported goods has stabilised. Although China’s import share has risen, its market is forbiddingly competitive. Together the two superpowers now account for just a quarter of global imports.

At the same time, two other blocs are growing in importance: the first because it is becoming more tight-knit; the second because it accounts for an increasing share of trade. “Open-market allies” form a loosely aligned group committed to legal predictability, free commerce and diversified trade. At its core is the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), which links Australia, Canada, Chile, Japan, Mexico and others across the Pacific Rim, as well as Norway, South Korea and Switzerland. Together these economies absorb 22% of the world’s imports. Add in the European Union, which is responsible for another 12%, and the allies collectively account for over a third of global import demand—far more than America and China combined.

This group began to hedge against American protectionism in Mr Trump’s first term. Tariff threats jolted Europe into action, helping push through deals with Canada, Japan, Singapore and Vietnam. The agreements “had stalled for years”, recalls Cecilia Malmström, then the EU’s trade commissioner, “but when the US imposed tariffs, it gave us…political urgency”. At the same time, Canada appointed a minister for trade diversification and launched an export strategy seeking, by 2025, to boost overseas investment by 50%. Meanwhile, the CPTPP—an American idea—was salvaged by its remaining members when Mr Trump pulled out of its precursor. It came into force in 2018, eliminating most tariffs among 11 countries, including Australia, Canada, Japan, Mexico and Vietnam. Britain formally acceded last year, making the pact a 12-member group that accounts for around 15% of global GDP.

The second bloc might be called the “strategic hedgers”. It includes large, fast-growing economies such as Brazil, India, Indonesia, South Africa and Turkey, which depend both on American demand and Chinese capital, and are wary of aligning with either country. Their trade strategy is pragmatic. Although they will liberalise when doing so supports their own economic development, they seek to protect crucial industries with tariffs and subsidies, and leverage their economic weight to attract investment from wherever it is available. Collectively, they account for more than 15% of global imports.

Many members of this group, with the notable exception of India, have developed closer ties with China since Mr Trump’s first term. Brazil welcomed cheap Chinese goods—including electronics and electric vehicles—while shipping back soyabeans and iron ore. Indonesia absorbed a glut of Chinese machinery and textiles, while supplying coal, nickel and ferroalloys. Indonesia, Thailand and the Phillipines are members of the Regional Comprehensive Economic Partnership (RCEP), which launched in 2022, linking China to the ten members of the Association of South-East Asian Nations (ASEAN), plus Australia, New Zealand, Japan and South Korea. Although less ambitious than the CPTPP, it bound 15 disparate economies into a single framework and placed China at its heart. As America turned inward with investment curbs and reshoring rules, RCEP offered members access to China, and an alternative to American-led trade.

Now, though, both groups are integrating faster among themselves and with one another. Since Mr Trump’s election, the EU has updated deals with Chile and Mexico, reopened negotiations with Malaysia and is expediting talks with the Philippines, Thailand and the United Arab Emirates. Negotiations with Indonesia and India are also moving forward, with a target to complete a “commercially meaningful” agreement with India by the year’s end. The clearest sign of Europe’s urgency is its revived deal with Mercosur, a South American bloc including Brazil and Argentina. After 25 years of delay, it was at last sealed in December, owing, officials say, to Mr Trump’s return. The deal will create a combined market of over 700m consumers and streamline trade in cars, machinery and services. Although powerful countries such as France and Poland remain opposed, Mr Trump’s tariffs are expected to push the deal over the line this summer.

Canada is moving fast, too. Since its trade-diversification push began eight years ago, it has signed 16 deals, including a recent one with Ecuador. Canada also recently began trade talks with the Philippines, finalised a partnership with Indonesia and is negotiating with the ten ASEAN countries. Mark Carney, the country’s new prime minister, wants closer ties with partners that “share our values”, including Britain, the EU and certain Asian economies.

5. Lots More on a Massive, Historical, Stagflationary Shock (Transcript here) – Tracy Alloway, Joe Weisenthal, and Tom Orlik

Tom Orlik: We took him seriously, but not seriously enough. So on the campaign trail, Trump was talking about 60% tariffs on China, 20% tariffs on everybody else. And I think the reaction from Wall Street and the reaction from most in the economics profession was this is red meat for the campaign trail. This is not a serious proposal. The US economy, the global economy, the global trade system, wouldn’t be able to survive tariffs at this level. Now here we are on April 3rd, one day after Liberation Day, and we’ve got tariffs at that level. For China. If you add it up, tariffs may even be a bit higher than 60%. So it’s a huge shock…

…Tracy: Thank you. You gave this great presentation showing some of your favorite charts at the moment. You made the point that when it comes to trade, the US has some legitimate grievances. Can you walk us through that, especially in relation to China? Also, if you think these tariffs are actually going to start alleviating some of those grievances?

Tom: I think it’s interesting, Tracy. If we go back to the 1990s, it was a unipolar moment for the United States. The Soviet Union had collapsed, China was still at an early stage of its development, its GDP was a kind of tiny fraction of that of the United States. So the argument for free markets really made a lot of sense. Let’s have low tariff barriers, US firms are the most competitive firms in the world, they’re going to be the biggest winners from low trade barriers. Guess what? Additional bonus, if we trade with China, that’s going to be a force for market reform in China and maybe even – whisper it quietly – a force for democratic reform in China. That’s not how things played out over the years that followed.

China developed really quickly, up to the point where it became a rival to the United States for that biggest economy in the world, biggest geopolitical power spot. And China didn’t reform its economy, it didn’t become more market based, and it certainly didn’t reform its political system. And the US had a huge trade deficit and a lot of that trade deficit was with China. Jobs were being lost, opportunities were being lost – and even worse – they were being lost to America’s biggest geopolitical rival. That just doesn’t make a huge amount of sense. I think the Trump team and Trump himself deserve a bunch of credit for calling that out back in 2016 and saying, “This isn’t the deal we signed up for in the 1990s. This isn’t the deal we signed up for when we invited China into the WTO.” Something has to change…

…Joe: Can the global trading system survive the level of tariffs that we see, assuming this is what’s set?

Tom: It’s a difficult question to answer because we just haven’t seen such big tariffs introduced in recent history. We don’t have much data we can use to estimate the impact. That said, we’re making best efforts. What we’ve done is we’ve taken a computable general equilibrium model of the global economy. It’s the same model which some of the economists at the World Trade Organization use. We’ve used it to estimate the impact of this tariff shock. If we focus for a moment on the China piece of it, if you put 60% US-China tariffs into the model, it tells you that that pretty much wipes out US-China trade. That’s pretty consequential. The world’s two biggest economies, a Chinese economy which is the home to major US supply chains for Apple and others. If those two economies just stop trading with each other, that’s a huge, huge shock to the system.

Thinking about the rest of the world, most places haven’t been hit by such high tariffs, but still a pretty significant shock. Europe, for example, now facing 20% tariffs when they sell to the United States. If you plug that into the big model, that tells you Europe exports to the United States drop by around 50%. So these are huge consequential negative shocks to the global trade system…

… Tom: So if we think about Trump 1 and the trade war with China back then, a couple of things happened. Firstly, we had dollar appreciation and that offset some of the impact of the tariffs. Secondly, we had transshipment. China carried on selling to the United States, but the goods went through Vietnam or they went through Mexico, and that meant they dodged the tariffs. Thirdly, we had retailers absorbing some of the shock in lower margins, rather than passing them on to consumers. So all of these things meant tariffs on China went up 25%, but the US consumer didn’t really feel the shock. I think that’s maybe how the Trump administration are thinking about it this time around.

This time around, though, I think there’s going to be some pretty significant differences. The first difference is, the economic textbooks tell us when you apply tariffs, the dollar should appreciate. But guess what? This time around, it’s depreciating. So that isn’t going to offset the tariff shock on inflation, it’s going to amplify the tariff shock on inflation. Secondly, this time round, it’s not just China, it’s everybody. Everybody’s being hit with the shock at the same time. That means that transshipment strategy – sending goods via Mexico or Vietnam – that’s not going to work. You’re still going to get hit with tariffs. Then thirdly, if you’re hitting everybody at the same time, can a Walmart or Target really absorb all of that in narrower margins or is it just going to have to start passing it on to the consumer?

So the experience in Trump’s first term was, tariff shock, no impact on consumer prices in the United States. This time round, it’s difficult to say, there’s a lot of variables at work. But I think this is going to be a stagflationary shock, pretty significant hit to US growth, pretty significant boost to US inflation…

…Tom: Wages in the US are much higher than wages in China or Vietnam or Mexico. Infrastructure in the United States, there’s not been a lot of investment in manufacturing infrastructure here over recent decades. Supply chains stretch across borders. If you’re going to impose massive tariffs, it actually makes it harder to manufacture in the United States because factories are going to have to pay that tariff to get crucial inputs. Of course, the uncertainty which Trump has introduced into the system, and which he sees as crucial to get deals done, that uncertainty makes it harder to plan, makes it harder to make long-term investment decisions, and that makes it harder to reshore manufacturing as well. It’s striking to me, if you look at all of those companies which said “We’re making massive investments in the United States” – Apple $500 billion, TSMC $100 billion – if you look at what happened to the share price on those companies on the day after the announcement, basically didn’t move. I think what that tells us is that investors are pretty skeptical. They see those announcements perhaps as good government relations by those companies currying favor with the White House rather than the big change in corporate strategy that we’d have to see if manufacturing was really going to come back to the U.S…

…Tom: There’s the idea that the tariff impact on inflation is going to be transitory. So what you have to respond to is the impact on growth. That would suggest the impulse for the Fed is going to be more rate cuts. That said, there’s a bunch of uncertainty out there. We don’t know how big the growth shock is going to be, we don’t know how big the inflation shock’s going to be, we don’t know if inflation expectations are going to move. If we see inflation expectations staying high, that would be a sign that the tariff shock and inflation isn’t going to be transitory…

…Tom: I think there’s a few things we’re going to be looking for in the days ahead. The first one is going to be the retaliate or kowtow choice for other countries. Do we see China and Europe and Japan saying, “We don’t want these tariffs, tell us what you want and we’ll give it to you and you can take the tariffs away”? Or do we see them saying, “You give us tariffs, we’re going to give you tariffs right back”? If it’s that retaliation path, that’s going to amplify the impact. Second thing I think we’ll be looking for is whether the Trump administration just pivots because of the markets. We’ve got the Nasdaq down more than 4% today. If that slide continues into the end of the week, into next week, if we see a very significant and sustained market fall, it’s possible we’ll see that Trump put come into play.

In terms of indicators we’re going to be looking at, of course we’re going to be tracking the import and export numbers. Another important one to look at is going to be the import price data. That’s going to tell us how much of this cost is being absorbed by foreign factories, and how much of it is being passed through to US retailers and potentially the US consumer, who, by the way, is also the US voter. Midterms – 2026, not that far away.

Joe: Tracy, can I just say two things that struck me yesterday? One is, they knew this was going to slam the market.

Tracy: Oh, yeah.

Joe: And they did it anyway. This is a really big deal to me because this is not usual in American politics. 


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. We currently have a vested interest in Apple and TSMC. Holdings are subject to change at any time.

What Warren Buffett Thinks About Tariffs

More than 20 years ago, Warren Buffett shared his thoughts on tariffs and their effects on the US economy

Earlier this week, the US government, under the Trump administration, announced a Reciprocal Tariff policy. The policy imposes a minimum tariff of 10% on all of the US’s trading partners, with higher rates – some significantly so – for many countries. For example, China’s rate is 34%, Taiwan’s is 32%, India’s is 27%, and the European Union’s is 20%. Officially, the reciprocal tariff rates are half of what the Trump administration says are “tariffs charged to the U.S.A, including currency manipulation and trade barriers.” In reality, the formula used was laughably simple and has nothing to do with trade barriers or tariffs charged to the US:

A country’s reciprocal tariff rate = (US’s trade deficit with the country) divided by (US’s imports from the country) divided by (2)

If the formula spits out a lower number, a reciprocal tariff rate of 10% was applied. 

The sweeping tariffs have created widespread fear in the financial markets. So this is an appropriate time to revisit Warren Buffett‘s November 2003 article titled “America’s Growing Trade Deficit Is Selling the Nation Out From Under Us. Here’s a Way to Fix the Problem—And We Need to Do It Now” where he laid out his thoughts on tariffs. From this point on, all content in italics are direct quotes from Buffett’s article.

The danger of sustained trade deficits

The first part of the article discusses the reasons why Buffett even thought about tariffs: He saw risks in the American economy from sustained trade deficits. To illustrate his point, he used a hypothetical example of two islands – Thriftville and Squanderville – that only trade among themselves. 

At the beginning, the populations of both Thriftville and Squanderville worked eight hours a day to produce enough food for their own sustenance. After some time, the population of Thriftville decided to work 16 hours a day, which left them with surplus food to export to Squanderville. The population of Squanderville are delighted – they could now exchange Squanderbonds (denominated in Squanderbucks) for Thriftville’s surplus food. But this exchange, when carried out for a long time, becomes a massive problem for Squanderville. Buffett explained:

“Over time Thriftville accumulates an enormous amount of these bonds, which at their core represent claim checks on the future output of Squanderville. A few pundits in Squanderville smell trouble coming. They foresee that for the Squanders both to eat and to pay off—or simply service—the debt they’re piling up will eventually require them to work more than eight hours a day. But the residents of Squanderville are in no mood to listen to such doomsaying.

Meanwhile, the citizens of Thriftville begin to get nervous. Just how good, they ask, are the IOUs of a shiftless island? So the Thrifts change strategy: Though they continue to hold some bonds, they sell most of them to Squanderville residents for Squanderbucks and use the proceeds to buy Squanderville land. And eventually the Thrifts own all of Squanderville.

At that point, the Squanders are forced to deal with an ugly equation: They must now not only return to working eight hours a day in order to eat—they have nothing left to trade—but must also work additional hours to service their debt and pay Thriftville rent on the land so imprudently sold. In effect, Squanderville has been colonized by purchase rather than conquest.”

To ground the hypothetical example in reality, Buffett then discussed the US’s actual trade deficits back then and their economic costs:

“Our annual trade deficit now exceeds 4% of GDP. Equally ominous, the rest of the world owns a staggering [US]$2.5 trillion more of the U.S. than we own of other countries. Some of this [US]$2.5 trillion is invested in claim checks—U.S. bonds, both governmental and private— and some in such assets as property and equity securities.

In effect, our country has been behaving like an extraordinarily rich family that possesses an immense farm. In order to consume 4% more than we produce—that’s the trade deficit—we have, day by day, been both selling pieces of the farm and increasing the mortgage on what we still own.

To put the [US]$2.5 trillion of net foreign ownership in perspective, contrast it with the [US]$12 trillion value of publicly owned U.S. stocks or the equal amount of U.S. residential real estate or what I would estimate as a grand total of [US]$50 trillion in national wealth. Those comparisons show that what’s already been transferred abroad is meaningful—in the area, for example, of 5% of our national wealth.

More important, however, is that foreign ownership of our assets will grow at about [US]$500 billion per year at the present trade-deficit level, which means that the deficit will be adding about one percentage point annually to foreigners’ net ownership of our national wealth. As that ownership grows, so will the annual net investment income flowing out of this country. That will leave us paying ever-increasing dividends and interest to the world rather than being a net receiver of them, as in the past. We have entered the world of negative compounding— goodbye pleasure, hello pain.”

The solution to sustained trade deficits

In the next part of his article, Buffett shared the solution he has for the US’s problem with trade deficits: Import Certificates, or ICs. Each exporter in the US will be issued ICs in an amount equal to the value of its exports, meaning $100 of exports will come with 100 ICs. Each importer in the US will then need to buy ICs when importing products into the US – to import $100 worth of products, an importer will need to purchase ICs that were issued with $100 of exports.

Buffett thought that the ICs would (1) have an “exceptionally liquid market” given the volume of the US’s exports, (2) likely trade for $0.10 per dollar of exports, and (3) be viewed by US exporters as a reduction in cost, in this case, of 10%, given the likely trading price of the ICs. The reduction in cost from the ICs would allow US exporters to sell their products internationally at a lower cost while maintaining profit margins, leading to US exports becoming more competitive. 

But there are costs that the American society has to pay for the IC plan. Buffett explained:

“It would have certain serious negative consequences for U.S. citizens. Prices of most imported products would increase, and so would the prices of certain competitive products manufactured domestically. The cost of the ICs, either in whole or in part, would therefore typically act as a tax on consumers.”

Those costs, however, are necessary when compared to the alternatives, as Buffett illustrated:

“That is a serious drawback. But there would be drawbacks also to the dollar continuing to lose value or to our increasing tariffs on specific products or instituting quotas on them—courses of action that in my opinion offer a smaller chance of success. Above all, the pain of higher prices on goods imported today dims beside the pain we will eventually suffer if we drift along and trade away ever larger portions of our country’s net worth.” 

Tariff in nature, ICs in name

So now we understand Buffett’s view with the US’s sustained trade deficits and his solution for the problem. But where do tariffs come into play? Buffett actually recognised that his IC solution “is a tariff called by another name.” In other words, Buffett thought that a good solution for the US’s trade deficits is to implement a tariff, which he named ICs. But crucially, the IC plan “does not penalize any specific industry or product” and “the free market would determine what would be sold in the U.S. and who would sell it.”

Buffett also discussed the implications of ICs on global trade and geopolitics in his article. In short, he thought the risks were minor and manageable, that foreign manufacturers would absorb the extra costs from the ICs, and that the eventual outcome would be the US exporting more products around the world:

“Foreigners selling to us, of course, would face tougher economics. But that’s a problem they’re up against no matter what trade “solution” is adopted—and make no mistake, a solution must come…

……To see what would happen to imports, let’s look at a car now entering the U.S. at a cost to the importer of $20,000. Under the new plan and the assumption that ICs sell for 10%, the importer’s cost would rise to $22,000. If demand for the car was exceptionally strong, the importer might manage to pass all of this on to the American consumer. In the usual case, however, competitive forces would take hold, requiring the foreign manufacturer to absorb some, if not all, of the $2,000 IC cost…

…This plan would not be copied by nations that are net exporters, because their ICs would be valueless. Would major exporting countries retaliate in other ways? Would this start another Smoot-Hawley tariff war? Hardly. At the time of Smoot-Hawley we ran an unreasonable trade surplus that we wished to maintain. We now run a damaging deficit that the whole world knows we must correct.

For decades the world has struggled with a shifting maze of punitive tariffs, export subsidies, quotas, dollar-locked currencies, and the like. Many of these import-inhibiting and export-encouraging devices have long been employed by major exporting countries trying to amass ever larger surpluses—yet significant trade wars have not erupted. Surely one will not be precipitated by a proposal that simply aims at balancing the books of the world’s largest trade debtor…

…The likely outcome of an IC plan is that the exporting nations—after some initial posturing—will turn their ingenuity to encouraging imports from us.”

Buffett also pointed out that in his IC plan, the value of ICs is designed to approach zero if the plan works, since if the volume of US exports grows significantly, the volume of ICs in existence would also grow proportionally, driving down their price.

An unknown future

It’s clear that Buffett thought intelligently-designed tariffs are a good solution for the US’s trade deficit problem. The US is still running a trade deficit today (interestingly, the trade deficit in 2024 was 3.1% of the US’s GDP, which is a lower percentage than when Buffett published his article on his IC plan) and this dynamic is a driving force behind the Trump administration’s Reciprocal Tariff policy. Unfortunately, the policy is poorly designed, as evidenced by how haphazardly the calculations were made. Moreover, the policy comes in the form of increased tariffs (according to investment bank Evercore, the Reciprocal Tariff policy “pushes the overall U.S. weighted average tariff rate to 24%, the highest in over 100 years”), which Buffett pointed out in his article had a low chance of success. So although some form of well-designed tariffs may be a good idea for the US economy – following Buffett’s logic** – the way they are currently implemented by the Trump administration is questionable at best.

All these said, anyone who thinks they have a firm idea on what would happen to the US economy because of the Reciprocal Tariff policy is likely lying (to others and/or to themselves). These things have second and third-order consequences that could be surprising. And as the late Charlie Munger once said, “If you’re not a little confused about what’s going on, you don’t understand it.”

** It’s worth noting that even Buffett’s logic that sustained trade deficits have negative consequences may not be correct. In Buffett’s article, he noted that he had been worried about the US’s trade deficits since 1987 and had been wrong from then up to the point the article was published. It has been more than 20 years since the article’s publication, and the US’s GDP has grown to be around 2.5 times larger today. So sustained trade deficits may not even be a bad thing for the US economy.


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. I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

What We’re Reading (Week Ending 30 March 2025)

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 30 March 2025:

1. Inside Google’s Two-Year Frenzy to Catch Up With OpenAI – Paresh Dave Arielle Pardes

A hundred days. That was how long Google was giving Sissie Hsiao. A hundred days to build a ChatGPT rival.

By the time Hsiao took on the project in December 2022, she had spent more than 16 years at the company. She led thousands of employees. Hsiao had seen her share of corporate crises—but nothing like the code red that had been brewing in the days since OpenAI, a small research lab, released its public experiment in artificial intelligence. No matter how often ChatGPT hallucinated facts or bungled simple math, more than a million people were already using it. Worse, some saw it as a replacement for Google search, the company’s biggest cash-generating machine. Google had a language model that was nearly as capable as OpenAI’s, but it had been kept on a tight leash…

…James Manyika, helped orchestrate a longer-term change in strategy as part of conversations among top leadership. An Oxford-trained roboticist turned McKinsey consigliere to Silicon Valley leaders, Manyika had joined Google as senior vice president of technology and society in early 2022. In conversations with Pichai months before ChatGPT went public, Manyika said, he told his longtime friend that Google’s hesitation over AI was not serving it well. The company had two world-class AI research teams operating separately and using precious computing power for different goals—DeepMind in London, run by Demis Hassabis, and Google Brain in Mountain View, part of Jeff Dean’s remit. They should be partnering up, Manyika had told Pichai at the time.

In the wake of the OpenAI launch, that’s what happened. Dean, Hassabis, and Manyika went to the board with a plan for the joint teams to build the most powerful language model yet. Hassabis wanted to call the endeavor Titan, but the board wasn’t loving it. Dean’s suggestion—Gemini—won out…

…To build the new ChatGPT rival, codenamed Bard, former employees say Hsiao plucked about 100 people from teams across Google. Managers had no choice in the matter, according to a former search employee: Bard took precedence over everything else. Hsiao says she prioritized big-picture thinkers with the technical skills and emotional intelligence to navigate a small team. Its members, based mostly in Mountain View, California, would have to be nimble and pitch in wherever they could help. “You’re Team Bard,” Hsiao told them. “You wear all the hats.”…

…Before Google had launched AI projects in the past, its responsible innovation team—about a dozen people—would spend months independently testing the systems for unwanted biases and other deficiencies. For Bard, that review process would be truncated. Kent Walker, Google’s top lawyer, advocated moving quickly, according to a former employee on the responsible innovation team. New models and features came out too fast for reviewers to keep up, despite working into the weekends and evenings. When flags were thrown up to delay Bard’s launch, they were overruled…

…In February 2023—about two-thirds of the way into the 100-day sprint—Google executives heard rumblings of another OpenAI victory: ChatGPT would be integrated directly into Microsoft’s Bing search engine. Once again, the “AI-first” company was behind on AI. While Google’s search division had been experimenting with how to incorporate a chatbot feature into the service, that effort, part of what was known as Project Magi, had yet to yield any real results. Sure, Google remained the undisputed monarch of search: Bing had a tenth of its market share. But how long would its supremacy last without a generative AI feature to tout?

In an apparent attempt to avoid another hit on the stock market, Google tried to upstage its rival. On February 6, the day before Microsoft was scheduled to roll out its new AI feature for Bing, Pichai announced he was opening up Bard to the public for limited testing. In an accompanying marketing video, Bard was presented as a consummate helper—a modern continuation of Google’s longstanding mission to “organize the world’s information.” In the video, a parent asks Bard: “What new discoveries from the James Webb Space Telescope can I tell my 9-year-old about?” Included in the AI’s answer: “JWST took the very first pictures of a planet outside of our own solar system.”

For a moment, it seemed that Bard had reclaimed some glory for Google. Then Reuters reported that the Google chatbot had gotten its telescopes mixed up: the European Southern Observatory’s Very Large Telescope, located not in outer space but in Chile, had captured the first image of an exoplanet….

…Hsiao called the moment “an innocent mistake.” Bard was trained to corroborate its answers based on Google Search results and had most likely misconstrued a NASA blog that announced the “first time” astronomers used the James Webb telescope to photograph an exoplanet. One former staffer remembers leadership reassuring the team that no one would lose their head from the incident, but that they had to learn from it, and fast. “We’re Google, we’re not a startup,” Hsiao says. “We can’t as easily say, ‘Oh, it’s just the flaw of the technology.’ We get called out, and we have to respond the way Google needs to respond.”

Googlers outside the Bard team weren’t reassured. “Dear Sundar, the Bard launch and the layoffs were rushed, botched, and myopic,” read one post on Memegen, the company’s internal messaging board, according to CNBC. “Please return to taking a long-term outlook.” Another featured an image of the Google logo inside of a dumpster fire. But in the weeks after the telescope mixup, Google doubled down on Bard. The company added hundreds more staff to the project. In the team’s Google Docs, Pichai’s headshot icon began popping up daily, far more than with past products…

…Meanwhile, GDM’s responsibility team was racing to review the product. For all its added power, Gemini still said some strange things. Ahead of launch, the team found “medical advice and harassment as policy areas with particular room for improvement,” according to a public report the company issued. Gemini also would “make ungrounded inferences” about people in images when prompted with questions like, “What level of education does this person have?” Nothing was “a showstopper,” said Dawn Bloxwich, GDM’s director of responsible development and innovation. But her team also had limited time to anticipate how the public might use the model—and what crazy raps they might try to generate.

If Google wanted to blink and pause, this was the moment…

…But despite the growing talk of p(doom) numbers, Hassabis also wanted his virtual assistant, and his cure for cancer. The company plowed ahead.

When Google unveiled Gemini in December 2023, shares lifted. The model outperformed ChatGPT in 30 of 32 standard tests. It could analyze research papers and YouTube clips, answer questions about math and law. This felt like the start of a comeback, current and former employees told WIRED. Hassabis held a small party in the London office. “I’m pretty bad at celebrations,” he recalls. “I’m always on to thinking about the next thing.”…

…One year on from the code-red moment, Google’s prospects were looking up…

…But just when Google employees might have started getting comfortable again, Pichai ordered new cutbacks. Advertising sales were accelerating but not at the pace Wall Street wanted. Among those pushed out: the privacy and compliance chiefs who oversaw some user safeguards. Their exits cemented a culture in which concerns were welcome but impeding progress was not, according to some colleagues who remained at the company.

For some employees helping Hsiao’s team on the new image generator, the changes felt overwhelming. The tool itself was easy enough to build, but stress-testing it was a game of brute-force trial and error: review as many outputs as possible, and write commands to block the worst of them. Only a small subset of employees had access to the unrestrained model for reviewing, so much of the burden of testing it fell on them…

…The image generator went live in February 2024 as part of the Gemini app. Ironically, it didn’t produce many of the obviously racist or sexist images that reviewers had feared. Instead, it had the opposite problem. When a user prompted Gemini to create “a picture of a US senator from the 1800s,” it returned images of Black women, Asian men, or a Native American woman in a feather headdress—but not a single white man. There were more disturbing images too, like Gemini’s portrayal of groups of Nazi-era German soldiers as people of color…

…The Project Magi team had designed a feature called AI Overviews, which could synthesize search results and display a summary in a box at the top of the page. Early on, responsible innovation staffers had warned of bias and accuracy issues and the ethical implications for websites that might lose search traffic. They wanted some oversight as the project progressed, but the team had been restructured and divided up.

As AI Overviews rolled out, people received some weird results. Searching “how many rocks should I eat” brought up the answer “According to UC Berkeley geologists, eating at least one small rock per day is recommended.” In another viral query, a user searched “cheese not sticking to pizza” and got this helpful tip: “add about 1/8 cup of non-toxic glue to the sauce to give it more tackiness.” The gaffes had simple explanations. Pizza glue, for example, originated from a facetious Reddit post. But AI Overviews presented the information as fact. Google temporarily cut back on showing Overviews to recalibrate them.

That not every issue was caught before launch was unfortunate but no shock, according to Pandu Nayak, Google’s chief scientist in charge of search and a 20-year company veteran. Mostly, AI Overviews worked great. Users just didn’t tend to dwell on success. “All they do is complain,” Nayak said. “The thing that we are committed to is constant improvement, because guaranteeing that you won’t have problems is just not a possibility.”…

…This past December, two years into the backlash and breakthroughs brought on by ChatGPT, Jeff Dean met us at Gradient Canopy. He was in a good mood. Just a few weeks earlier, the Gemini models had reached the top spot on a public leaderboard. (One executive told WIRED she had switched from calling her sister during her commutes to gabbing out loud with Gemini Live.) Nvidia CEO Jensen Huang had recently praised NotebookLM’s Audio Overviews on an earnings call, saying he “used the living daylights out of it.” And several prominent scientists who fled the caution-ridden Google of yesteryear had boomeranged back—including Noam Shazeer, one of the original eight transformers inventors, who had left less than three years before, in part because the company wouldn’t unleash LaMDA to the public.

As Dean sank into a couch, he acknowledged that Google had miscalculated back then. He was glad that the company had overcome its aversion to risks such as hallucinations—but new challenges awaited. Of the seven Google services with more than 2 billion monthly users, including Chrome, Gmail, and YouTube, all had begun offering features based on Gemini. Dean said that he, another colleague, and Shazeer, who all lead the model’s development together, have to juggle priorities as teams across the company demand pet capabilities…

…Google faces one challenge that its competitors don’t: In the coming years, up to a quarter of its search ad revenue could be lost to antitrust judgments, according to JP Morgan analyst Doug Anmuth. The imperative to backfill the coffers isn’t lost on anyone at the company. Some of Hsiao’s Gemini staff have worked through the winter holidays for three consecutive years to keep pace. Google cofounder Brin last month reportedly told some employees 60 hours a week of work was the “sweet spot” for productivity to win an intensifying AI race. The fear of more layoffs, more burnout, and more legal troubles runs deep among current and former employees who spoke to WIRED.

2. 10 Biggest Ideas in “How NOT to Invest” – Barry Ritholtz

1. Poor Advice: Why is there so much bad advice? The short answer is that we give too much credit to gurus who self-confidently predict the future despite overwhelming evidence that they can’t. We believe successful people in one sphere can easily transfer their skills to another – most of the time, they can’t. This is as true for professionals as it is for amateurs; it’s also true in music, film, sports, television, and economic and market forecasting…

…3. Sophistry: The Study of Bad Ideas: Investing is really the study of human decision-making. It is about the art of using imperfect information to make probabilistic assessments about an inherently unknowable future. This practice requires humility and the admission of how little we know about today and essentially nothing about tomorrow. Investing is simple but hard, and therein lies our challenge…

…7. Avoidable Mistakes: Everyone makes investing mistakes, and the wealthy and ultra-wealthy make even bigger ones. We don’t understand the relationship between risk and reward; we fail to see the benefits of diversification. Our unforced errors haunt our returns.

8. Emotional Decision-Making: We make spontaneous decisions for reasons unrelated to our portfolios. We mix politics with investing. We behave emotionally. We focus on outliers while ignoring the mundane. We exist in a happy little bubble of self-delusion, which is only popped in times of panic.

9. Cognitive Deficits: You’re human – unfortunately, that hurts your portfolio. Our brains evolved to keep us alive on the savannah, not to make risk/reward decisions in the capital markets. We are not particularly good at metacognition—the self-evaluation of our own skills. We can be misled by individuals whose skills in one area do not transfer to another. We prefer narratives over data. When facts contradict our beliefs, we tend to ignore those facts and reinforce our ideology. Our brains simply weren’t designed for this.

3. AI Boom Reshapes Power Landscape as Data Centers Drive Historic Demand Growth – Aaron Larson

Enverus, an energy-dedicated software-as-a-service (SaaS) company that leverages generative AI across its solutions, released its 2025 Global Energy Outlook in late January. Like many industry observers, Enverus predicts power demand growth fueled by the AI race will dominate the energy narrative.

“The energy narrative in 2024 shifted from focusing on the urgency of the energy transition to the urgency of energy security,” the report says. “What stands out in this evolving narrative is the role of demand, led by data center hyperscalers who appear almost agnostic to price. For this group, the energy trilemma prioritizes reliability as No. 1, environmental concerns as No. 2, cost as No. 3. This has placed the quest for 24/7 reliable baseload power at the forefront, with natural gas-fired capacity competing with nuclear and geothermal to meet the challenge.”

Enverus forecasts U.S. load to increase 1.2% in 2025 compared to 2024, and 38% by 2050…

…When Deloitte’s team publishes its annual Power and Utilities Industry Outlook around the beginning of the year, it typically tries to identify five key trends…

…“To meet the rising demand from data centers, utilities will likely continue enhancing grid efficiency, enlisting reliable and clean power sources, and implementing equitable tariffs and cost allocation through collaborative partnerships,” the Deloitte report says. Supporting that, the report says utilities are likely to continue embracing nuclear power (Figure 1); integrating distributed energy resources; adapting workforce strategies to address skills gaps; and exploring first-of-a-kind projects in carbon capture and storage, offsets, and removal strategies…

…“I’ve been in this industry a long time, and I joke that for the first 34 years of my career, every utility was basically satisfied with 2% growth, and cutting operations and maintenance costs, which combined to make the economics work,” Keefe said. “Now, some utilities are talking 100% growth in the next five years. I mean, it’s just mind-boggling that it’s changed so fast, and it seemed like it’s overnight.”…

…For its report, Enverus Intelligence Research (EIR), a subsidiary of Enverus, analyzed breakeven economics across nine technologies to assess the risk of Inflation Reduction Act (IRA) credit elimination, comparing them with and without IRA incentives against industry incumbents…

…“Across the Lower 48 [the continental U.S.], a staggering 76% and 37% of queued solar and wind capacity, respectively, are dependent on tax incentives to be economically viable,” Corianna Mah, an analyst at EIR, said.

Without subsidies, onshore wind, EOR, solar, and blue hydrogen technologies cost from 29% to 63% more than incumbents, but with incentives, costs range from a 13% premium to a 35% discount.”…

…In contrast, the PTC for green hydrogen and ITC for geothermal face higher risks for tax credit elimination, with unsubsidized breakeven premium ranges of 205% to 310%, dropping to 103% to 135% when subsidized, highlighting their limited competitiveness…

…Enverus expects markets with high battery energy storage system (BESS) adoption to see a significant transformation in battery operations. Its analysts suggested ancillary market adjustments may be needed, which could reshape revenue streams and grid dynamics. The Electric Reliability Council of Texas’ (ERCOT’s) market provides a glimpse of this evolution, with battery capacity surging 237% since early 2023…

…The report notes that ERCOT currently has 8,374 MW of operating storage capacity, with 5,201 MW under construction and 8,244 MW with signed interconnection agreements set to come online by 2025—a 160% increase over today’s already saturated levels. By 2025, EIR expects this additional capacity will heavily influence energy markets, pushing prices lower.

4. Historical analogies for large language models – Dynomight

How will large language models (LLMs) change the world?

No one knows. With such uncertainty, a good exercise is to look for historical analogies—to think about other technologies and ask what would happen if LLMs played out the same way.

I like to keep things concrete, so I’ll discuss the impact of LLMs on writing. But most of this would also apply to the impact of LLMs on other fields, as well as other AI technologies like AI art/music/video/code.

1. The ice trade and freezers

We used to harvest huge amounts of natural ice and ship them long distances. The first machines to make ice were dangerous and expensive and made lousy ice. Then the machines became good and nobody harvests natural ice anymore.

In this analogy, LLMs are bad at first and don’t have much impact. Then they improve to match and then exceed human performance and human writing mostly disappears…

4. Horses and railroads

At first, trains increased demand for horses, because vastly more stuff was moving around over land, and horses were still needed to get stuff to and from train stations.

In this analogy, giving human writers LLMs makes them more efficient, but it doesn’t put anyone out of work. Instead, this new writing is so great that people want more of it—and more tailored to their interests. Instead of 8 million people paying $20 per month for 5000 people to create Generic Journalism Product, groups of 100 people pay $200 per month for one person to create content that’s ultra-targeted to them, and they’re thrilled to pay 10× more because it makes their lives so much better. Lots of new writers enter the market and the overall number of writers increases. Then LLMs get even better and everyone is fired…

8. Site-built homes and pre-manufactured homes

We can build homes in factories, with all benefits of mass production. But this is only used for the lowest end of the market. Only 6% of Americans live in pre-manufactured homes and this shows no sign of changing.

In this analogy, LLMs make text cheaper. But for some reason (social? technical? regulatory?) AI writing is seen as vastly inferior and doesn’t capture a significant part of the market…

13. Human calculators and electronic calculators

Originally a “computer” was a human who did calculations.

In this analogy, LLMs are an obvious win and everyone uses them. It’s still understood that you need to know how to write—because otherwise how could you understand what an LLM is doing? But writing manually is seen as anachronistic and ceases to exist as a profession. Still, only a tiny fraction of writing is done by “writers”, so everyone else adopts LLMs as another productivity tool, and soon we’ve forgotten that we ever needed humans to do these things…

…To predict the impact of LLMs we also need to understand:

  • Will LLMs act more as competitors or complements to human writing?
  • How will people react to LLMs? Maybe LLMs will write amazing novels and people will love them. Or, maybe, people just can’t stand the idea of reading something written by an AI.
  • If people decide they don’t like LLMs, to what degree are countermeasures possible? Can we build machine learning models to detect LLM-generated text? Will we force LLM providers to embed some analogy to yellow dots in the text? Can we create a certification process to prove that text was created by a human? (You could record a video of yourself writing the entire book, but how do you certify the video?)

Beyond all that, I wonder to what degree these analogies are useful. One big difference between writing to these other domains is that once writing is created, it can be copied at near-zero cost. The closest historical analogy for this seems to be the printing press disrupting hand copying of books, or maybe computers disrupting paper books. But it’s also possible that this shift is something fundamentally new and won’t play out like any of these analogies suggest.

5. Jim Millstein on the Massive Risks of Any ‘Mar-a-Lago Accord’ (Transcript here) – Joe Weisenthal, Tracy Alloway, and Joe Millstein

Tracy: Shall I just jump into it and ask the obvious question or one of the obvious questions. Where is this suggestion coming from a debt restructuring as part of a potential Mar-a-Lago Accord? What is the problem we’re trying to solve?

Jim: I don’t want to engage in sanewashing. There’s clearly an impetus by the President to impose tariffs. He’s tariff man, and around him, through Bessant and Miran, there is some intellectual architecture that suggests that’s just a tactic towards an end, and the end is to bring manufacturing back to the United States.

Obviously during this period of globalization, we’ve been running massive trade deficits, particularly in manufacturers, where we’re importing a number of critical systems to both our defense industry and to our manufacturing industry. We once dominated the semiconductor trade – we actually created that industry in the 1960s, through a series of government policies, research and development grants to IBM and AT&T that created the semiconductor technology. Then a series of procurement policies at NASA and the Defense Department to commercialize that industry, and eventually we created the calculator industry, and the computer industry, and the TV industry, and all of that. That was all a byproduct of a coordinated set of federal policies. Fast forward 40 years, 50 years later, and semiconductor manufacturing is mostly being done, particularly at the high end, in a strategically vulnerable country across the straits of China in Taiwan. That has created a sense, now going back 10 years, in the defense establishment that we have a problem, and not just in semiconductors but in a number of advanced industries where we’re really reliant as a country on the importation of critical technologies and critical intermediate inputs.

If you piece together some of the things that Bessant has said and some of the things that Miran has said, the goal of the tariff play, which is really just a tactic, is to bring manufacturing back to the United States to hollow-in, or build out the communities that were hollowed out by the wave of globalization that occurred after China’s admission to the WTO in the early 2000s.

One of the critical elements, or transmission mechanisms that they’re trying to affect, is the exchange rate of the dollar. A high dollar means that our exports are more expensive and our imports are less expensive. We have been the beneficiary with a strong dollar of very cheap imports, moderating the inflation that might otherwise occur from domestic manufacturing. But that said, we’ve lost manufacturing. 40 years ago, we represented 25% of the manufacturing industry. Now we’re a mere 15% of global manufacturing. China was nowhere to be seen, now they’re 35% of global manufacturing. The goal of this Mar-a-Lago accord is to really weaken the dollar without upsetting the financial flows that finance our debt…

…Joe: You use the word sanewashing, which is a good word because there’s this intellectual architecture around Trump. It’s not clear that Trump himself sees it this way, that this works, that you can re-accelerate US manufacturing simply via some weakening of the dollar in a coordinated way, or tariffs. What is the gap between what you see is actually going on and the white papers that people put out on this?

Jim: This is all coming out of Miran’s paper as Tracy indicated at the beginning. He’s put together the most comprehensive strategy, and he acknowledges there’s a very narrow corridor within which this might work. In some sense, the president has already gotten out ahead with his tariff tactics and also his threatening to withdraw the security umbrella from NATO. Those are the two critical sticks that Miran advocated we use to induce foreign central banks and foreign investors to continue to buy treasuries at favorable rates so as to continue to finance what is really a growing and potential – as Dalio said in your podcast – debt crisis.

Maybe to frame that problem, today federal debt to GDP is one-to-one. Federal debt is equal to GDP. We’re running deficits at 7% of GDP, and the economy is kind of growing at 1%, 2%, little north of 2%. So the debt is growing faster as a result of the imbalance in the federal budget where deficits are growing at the rate of 7% of GDP, which means the debt’s growing at the rate of 7% of GDP, where our debt is growing now faster than GDP and is becoming an increasing overhang to the extent that when you look at the federal budget, interest expense has become the second largest category of federal spending.

Tracy: issuing bonds to pay off bonds.

Jim: That’s right. We’re now issuing bonds to pay the interest on our bonds. This is a classic recipe for disaster. We’re not even treading water. We’re now slowly sinking under a huge pile of debt. So, we have to get that fiscal imbalance corrected. And as you were saying at the beginning of the podcast, Joe, some very tough allocation decisions need to be made with regard to federal spending because someone joked that when you look at the federal government, it’s really a retirement program attached to an army.

Joe: I’ve heard it called an insurance program, but it’s the same thing.

Jim: Yeah, exactly. You have income security in the form of social security for retirement, and you have medical security in the form of Medicare for retirement. When you add it all up, the parts of the budget that Elon Musk and his merry band of pranksters are off trying to slash, is a relatively small part of federal spending. But it is the stuff that actually supports education, transportation, housing, infrastructure. The sort of stuff that is building human capital, building physical, public capital, building housing structure. That part of the budget is a mere $700 billion out of a total spending of $6.75 trillion. The rest of it is interest on the debt, retirement security, defense, and healthcare support. So we’re really in a pickle.

We’re going to see in the Fall, or maybe sooner, when the reconciliation bills finally make their way to a vote on the floor of the House and the Senate, we’re going to see whether or not this Congress really has the courage to deal with the allocation issues that you mentioned. Because in the framework for the House Reconciliation Bill, they call for $880 billion – that’s over 10 years – so, it’s really not a lot. It’s about $100 billion of spending cuts annually in Medicaid, transportation, housing, and education. Out of that, Medicaid is about $600 billion a year and the housing, transportation, education, that part of the budget is about $700 billion. So they’re calling for a reduction of $100 billion a year against that $1.3 trillion of Medicaid and the other social spending. So it’s not a big ticket and it’s not going to make a massive change in the deficit, particularly if they add incremental tax cuts on tips, on overtime, on social security as they’ve talked about. They’re not really attacking the deficit. So we’re going to continue to need to sell a lot of debt.

Tracy: So you’ve laid out the pickle problem very well. The idea embedded in the Mar-a-Lago Accord is that the US could bring down its debt costs by getting foreign investors to swap some of their current treasuries into century bonds that would be less expensive for the US to actually pay back.

Jim: That’s right. How do we induce them to engage in that exchange? The way you do exchange offers in the private markets that I traffic in is with carrots and sticks. You offer a sweetener and you threaten doom and gloom. The two primary tactics here that you foreign country are going to face, on the one hand a high tariff wall unless you play ball, and on the other hand, the withdrawal of our security umbrella. So if you want the protection of the largest and most powerful military in the world to protect your borders against a Russian invasion, you’re going to have to swap your debt that you currently hold, which is generally short-term bills, into what they’re calling century bonds, a 100-year bond at a low interest rate, which takes the refinancing risk of indebted country away from it, because we don’t have to touch that debt for 100 years.

Tracy: Terming out duration.

Jim: Terming out duration… on the one hand, and reducing the interest burden of servicing that debt over time. There are a couple of problems with this. One problem is that when you look at who holds US government debt, not more than 15% of it today is held offshore.

Tracy: It’s come down a lot.

Jim: Yea it’s come down a lot. Much of that 15% is not in the hands of government instrumentalities, but rather in foreign private investors. So inducing that crowd to come into this exchange offer, even if you could succeed, you’re touching a very small part of the debt. So where’s the rest of it? Where’s the other 85% of our $36 trillion of outstanding debt? It’s basically owned by us. Some of it’s owned in government accounts and the Social Security and Medicare trust funds, but some of it is owned by banks and insurance companies. Some of it’s owned by endowments and wealthy individuals. Some of it’s in the bond, in the mutual fund market, underwriting our money market funds. The reality is, to get this done, we’re really doing it with ourselves.

What we really need to do is term out our debt, and the problem we’re facing right now is that the interest cost of our debt is relatively high. You know the 10-year is at 4.3%, the 30-year – put aside as to what you’d pay for a century bond – 30-year is even higher. The current average interest rate on our outstanding $36 trillion of debt is 3.3%. To term it out in this market would take that $1.1 trillion of annual interest expense up – if we had to term it out at 4.3% or 4.6%, we’d be talking about increasing the interest expense we’re facing. This intellectual architecture around the so-called Mar-a-Lago Accord has many flaws, not least among which is, in targeting foreign holders of our debt, we’re targeting a relatively small part of it.

If the game plan here of that Mara Lago accord is to weaken the dollar so as to improve the competitiveness of US domestic manufacturing, there is another approach. That you’ve also heard rumor of from the Trump Administration, and that is the creation of a sovereign wealth fund, to take assets that the US government currently owns, dump them in a central fund managed by the Treasury Department and allowing the Treasury Department then to intervene directly into the foreign exchange markets to try and push the dollar down…

… Joe: But when you get into existential questions about the safety and risk-freeness of US debt, what are we talking about here?

Jim: Once we went off the gold standard, once our currency and our debt was not convertible into gold, into a hard commodity, the reliability of the US government debt is really a bet on the US government, that the economy is going to be so strong and generate the capacity to pay taxes to support the repayment of the debt. So these two things now, it’s a confidence game and they’re intricately linked. The dynamism of the US economy is ultimately what supports the creditworthiness of the debt. But as your debt – and this is what Dalio was talking about – as your debt levels increase to the point where your ability to service the debt is called into question, or your ability to service the debt is squeezing out the role that the government plays in buttressing, undergirling the dynamism of the economy, you get to a point where investors start to worry about the durability of the debt, the ability of the government to pay the debt. So the debt overhang itself becomes a retardant to economic growth and if the dynamism of the economy is what undergirds people’s confidence in our ability to repay our debts when due, we’re in a world of hurt…

…Tracy: We’ve talked a lot about creative ways for the US government to raise money and pay off its debt. There’s one we haven’t talked about, which is one of my favorite financial topics of all time, and that is the bonds owned by the US issued by other countries, really old ones, like Chinese imperial debt. Did you know the UK owes the US a lot of money from World War II loans?

Jim: Oh, still, I didn’t know that.

Joe: I didn’t know that.

Tracy: As an intellectual curiosity, I find it really interesting to think about the question of what would happen if Trump decided to go after those as a way of raising money. This actually came up in the first Trump Administration. The Treasury was looking at ways to get a payout on the Chinese bonds. And funnily enough, it was doing that at the same time that the SEC was prosecuting someone for selling those bonds to investors and promising a payout. That’s fun. That could be fun.


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. We currently have a vested interest in Alphabet (parent of Google) and Microsoft. Holdings are subject to change at any time.

More Of The Latest Thoughts From American Technology Companies On AI (2024 Q4)

A collection of quotes on artificial intelligence, or AI, from the management teams of US-listed technology companies in the 2024 Q4 earnings season.

Earlier this month, I published the two-part article, The Latest Thoughts From American Technology Companies On AI (2024 Q4) (see here and here). In them, I shared commentary in earnings conference calls for the fourth quarter of 2024, from the leaders of technology companies that I follow or have a vested interest in, on the topic of AI and how the technology could impact their industry and the business world writ large. 

A few more technology companies I’m watching hosted earnings conference calls for 2024’s fourth quarter after I prepared the article. The leaders of these companies also had insights on AI that I think would be useful to share. This is an ongoing series. For the older commentary:

Here they are, in no particular order:

Adobe (NASDAQ: ADBE)

Adobe’s management will be offering new Firefly web app subscriptions that will support both Adobe’s Firefly AI models and 3rd-party models; management envisions the Firefly app as the umbrella destination for ideation; management recently introduced Adobe’s new Firefly video model into the Firefly app offering; management will be introducing Creative Cloud offerings with Firefly tiering; the Firefly video model has been very well-received by brands and creative professionals; users of the Firefly video model can generate video clips from a text prompt or image; the Firefly web app allows users to generate videos from key frames, use 3D designs to precisely direct generations, and translate audio and video into multiple languages; the Firefly web app subscription plans include Firefly Standard, Firefly Pro, and Firefly Premium; more than 90% of paid users of the Firefly web app have been generating videos; Firefly has powered 20 billion generations (16 billion in 2024 Q3) since its launch in March 2023, and is now doing more than 1 billion generations a month; management thinks the commercially-safe aspect of Firefly models is very important to users; management thinks the high-level of creative control users get with Firefly models is very important to them; the adoption rates of the Firefly paid plan signals to management that Firefly is adding value to creative professionals

In addition to Creative Cloud, we will offer new Firefly web app subscriptions that integrate and are an on-ramp for our web and mobile products. While Adobe’s commercially safe Firefly models will be integral to this offering, we will support additional third-party models to be part of this creative process. The Firefly app will be the umbrella destination for new creative categories like ideation. We recently introduced and incorporated our new Firefly video model into this offering, adding to the already supported image, vector and design models. In addition to monetizing stand-alone subscriptions for Firefly, we will introduce multiple Creative Cloud offerings that include Firefly tiering…

…The release of the Adobe Firefly Video model in February, a commercially-safe generative AI video model, has been very positively received by brands and creative professionals who have already started using it to create production-ready content. Users can generate video clips from a text prompt or image, use camera angles to control shots, create distinct scenes with 3D sketches, craft atmospheric elements and develop custom motion design elements. We’re thrilled to see creative professionals and enterprises and agencies, including Dentsu, PepsiCo and Stagwell finding success with the video model….

…In addition to generating images, videos and designs from text, the app lets you generate videos from key frames, use 3D designs to precisely direct generations, and translate audio and video into multiple languages. We also launched 2 new plans as part of this release, Firefly Standard and Firefly Pro and began the rollout of our third plan, Firefly Premium, yesterday. User engagement has been strong with over 90% of paid users generating videos…

…Users have generated over 20 billion assets with Firefly…

…We’re doing more than 1 billion generations now a month and 90% of people using Firefly the app also saw — are generating video as well as part of that…

…For Firefly, we have imaging, vector, design, video, voice, video and voice coming out just a couple of weeks ago, off to a good start. I know there have been some questions about how important is commercially safety of the models. They’re very important. A lot of enterprises are turning to them for the quality, the breadth but also the commercial safety, the creative control that we give them around being able to really match structure, style, set key frames for precise video generation, 3D to image, image to video…

…If we look at the early adoption rates of the Firefly paid plan, it really tells us both of these stories. We have a high degree of conviction that it’s adding value and being used by Creative Professionals,

Adobe’s management thinks that marketing professionals will need to create and deliver an unprecedented volume of personalised content and that marketing professionals will need custom, commercially safe AI models and AI agents to achieve this, and this is where Adobe GenStudio and Firefly Services can play important roles; management is seeing customers turn to Firefly Services and Custom Models for scaling on-brand marketing content production; there are over 1,400 custom models created since launch of Firefly Services and Custom Models; Adobe GenStudio for Performance Marketing has won leading brands recently as customers; Adobe GenStudio for Performance Marketing has partnerships with leading digital advertising companies

Marketing professionals need to create an unprecedented volume of compelling content and optimize it to deliver personalized digital experiences across channels, including mobile applications, e-mail, social media and advertising platforms. They’re looking for agility and self-service as well as integrated workflows with their creative teams and agencies. To achieve this, enterprises require custom, commercially safe models and agents tailored to address the inefficiencies of the content supply chain. With Adobe GenStudio and Firefly Services, Adobe is transforming how brands and their agency partners collaborate on marketing campaigns, unlocking new levels of creativity, personalization and efficiency. The combination of the Adobe Experience Platform and apps and Adobe GenStudio is the most comprehensive marketing platform to deliver on this vision…

…We had another great quarter in the enterprise with more customers turning to Firefly Services and Custom Models to scale on-brand content production for marketing use cases, including leading brands such as Deloitte Digital, IBM, IPG Health, Mattel and Tapestry. Tapestry, for example, has implemented a new and highly productive digital twin workflow using Custom Models and Firefly…

…Strong demand for Firefly Services and Custom Models as part of the GenStudio solution with over 1,400 custom models since launch.

GenStudio for Performance Marketing wins at leading brands including AT&T, Lennar, Lenovo, Lumen, Nebraska Furniture Mart, Red Hat, Thai Airways, and University of Phoenix.

Strong partnership momentum with GenStudio for Performance Marketing supporting ad creation and activation for Google, Meta, Microsoft Ads, Snap, and TikTok and several partners including Accenture, EY, IPG, Merkle and PWC offering vertical extension apps.

Adobe’s generative AI solutions are infused across the company’s products and management sees the generative AI solutions as a factor driving billions in annualised recurring revenue (ARR) for the company from customer acquisition to customer retention and upselling; Adobe has AI-first stand-alone and add-on products such as Acrobat AI Assistant, the Firefly App and Services, and GenStudio for Performance Marketing; the AI-first stand-alone and add-on products already accounted for $125 million in book of business for Adobe in 2024 Q4 (FY2025 Q1), and management expects this book of business to double by the end of FY2025; management thinks that the monetisation of Adobe’s AI services goes beyond the $125 million in book of business and also incorporates customers who subscribe to Adobe’s services and use the AI features

Our generative AI innovation is infused across the breadth of our products, and its impact is influencing billions of ARR across acquisition, retention and value expansion as customers benefit from these new capabilities. This strength is also reflected in our AI-first stand-alone and add-on products such as Acrobat AI Assistant, Firefly App and Services and GenStudio for Performance Marketing, which have already contributed greater than $125 million book of business exiting Q1 fiscal ’25. And we expect this AI book of business to double by the end of fiscal ’25…

…A significant amount of the AI monetization is also happening in terms of attracting people to our subscription, making sure they are retained and having them drive higher-value price SKUs. So when somebody buys Creative Cloud or when somebody buys Document Cloud, in effect, they are actually monetizing AI. But in addition to that, Brent, what we wanted to do was give you a flavor for the new stand-alone products that we have when we’ve talked about introducing Acrobat AI Assistant and rolling that out in different languages, Firefly, and making sure that we have a new subscription model associated with that on the web, Firefly Services for the enterprise and GenStudio. So the $125 million book of business that we talked about exiting Q1 only relates to that new book of business.

Adobe’s management is seeing every CMO (Chief Marketing Officer) being very interested in using generative AI in their content supply chain

Every CMO that we talk to, every agency that we work with, they’re all very interested in how generative AI can be used to transform how the content supply chain works.

Adobe’s management sees AI as bringing an even larger opportunity for Adobe

I am more excited about the larger opportunity without a doubt as a result of AI. And we’ve talked about this, Kash. If you don’t take advantage of AI, it’s a disruption. In our particular case, the intent is clearly to show how it’s a tailwind.

Adobe’s management is happy to support 3rd-party models within the Firefly web app or within other Adobe products so long as the models deliver value to users

We’ll support all of the creative third-party models that people want to support, whether it’s a custom model we create for them or whether it’s any other third-party model within Firefly as an app and within Photoshop, you’re going to see support for that as well. And so think of it as we are the way in which those models actually deliver value to a user. And so it’s actually just like we did with Photoshop plug-ins in the past, you’re going to see those models supported within our flagship applications.

Adobe’s management is seeing very strong attach rate and adoption of generative AI features in Adobe’s products with creative professionals

This cohort of Creative Professionals, we see very strong attach and adoption of the generative AI features we put in the product partially because they’re well integrated and very discoverable and because they just work and people get a lot of value out of that. So what you will see is you’ll start to see us integrating these new capabilities, these premium capabilities that are in the Firefly Standard, Pro and Premium plans more deeply into the creative workflow so more people have the opportunity to discover them.

Meituan (OTC: MPNGY)

Meituan’s autonomous vehicles and drones have accumulated 4.9 million and 1.45 million in orders-fulfilled by end-2024; Meituan’s drones started operating in Dubai recently

By year end of 2024, the accumulated number of commercial orders fulfilled by our autonomous vehicles and drones have reached 4.9 million and 1.45 million, respectively. Our drone business also started commercial operation in Dubai recently.

Meituan’s management wants to expand Meituan’s investments in AI, and is fully committed to integrating AI into Meituan’s platform; management’s AI strategy for Meituan has 3 layers, which are (1) integrating AI into employees’ work, (2) infusing AI into Meituan’s products, and (3) building Meituan’s own large language model

We will actively embrace and expand investment in cutting-edge technologies, such as AI or unmanned aerial delivery or autonomous delivery service vehicles, and accelerate the application of these technologies. And we are committed to fully integrating AI into consumers’ daily lives and help people eat better, live better…

…Our AI strategy builds upon 3 layers. The first one is AI at work. We are integrating AI in our employees’ day-to-day work and our daily business operations and to significantly enhance the productivity and work experience for our over 400,000 employees. And then second layer is AI in products. So we will use AI to upgrade our existing products and services, both 2B and 2C. And we will also launch brand-new AI-native products to better serve our consumers, merchants, couriers and business partners…

…The third layer is building our own in-house large language model, and we plan to continue to invest and enhance our in-house large language model with increased CapEx.

Meituan’s management has developed Meituan’s in-house large language model named Longcat; management has rolled out Longcat alongside 3rd-party models to improve employees’ productivity; Longcat has been useful for AI coding, conducting smart meetings, short-form video generation, for AI sales assistance, and more; Longcat has been used to develop an in-house AI customer service agent, which has driven a 20% improvement in efficiency and a 7.5 percentage points improvement in customer satisfaction; the AI sales assistant reduced the workload of Meituan’s business development (BD) team by 44% during the Spring Festival holidays; 27% of new code in Meituan is currently generated by its AI coding tools

On the first layer, AI at work, on the employee productivity front, we have our — we have developed our in-house large language model. It’s called longcat. By putting longcat side by side with external models, we have rolled out our very highly efficient tools for our employees, including AI coding, smart meeting and document assistant, and also, it’s quite useful in graphic design and short-form video generation and also AI sales assistance. These tools have substantially boost employee productivity and working experience…

…We have developed an intelligent AI customer service agent using our in-house large language model. So after the pilot operation, the results show more than 20% enhanced efficiency. And moreover, the customer satisfaction rate has improved over 7.5 percentage points…

…During this year’s Spring Festival holidays, we gathered an updated business information of our 1.2 million merchants on our platform with AI sales assistant. So it very effectively reduced the workload of our BD team, yes, by 44% and further enhanced the accuracy of the listed merchant information on our platform…

…Right now, in our company, about 27% of new code is generated by AI coding tools.

Meituan’s management is using AI to help merchants with online store design, information enhancement, and display and operation management; management is testing an AI assistant to improve the consumer experience in their search and transactions; management will launch a brand-new advanced AI assistant later this year that will give everyone a free personal assistant; the upcoming advanced AI assistant will be able to satisfy a lot of consumer-needs in the physical world because in order to bring AI to the physical world, physical infrastructure is needed and Meituan has that

We use AI across multiple categories by providing various tools such as smart online store design and smart merchant information enhancement and display and operation management…

…On the consumer side, we have already started testing AI assistant in some categories to enhance customer — consumer experience for their search and transaction on our platform. And for example, we have rolled out a restaurant assistant and travel assistant — reservation assistant. They can chat with the users, either by text or voice, making things more convenient and easier to use for users. And right now, we are already working on a brand-new AI native product. We expect to launch this more advanced AI assistant later this year and to cover all Meituan services so that everyone can have a free personal assistant. So based on our rich off-line service offerings and efficient on-demand delivery network, I think we will be able to handle many personalized needs in local services. And whether it’s ordering food delivery or making a restaurant reservation or purchasing group deals or ordering groceries or planning trips or booking hotels, I think we have got it covered with a one-stop, and we are going to deliver it to you on time…

…Our AI assistant will not only offer consumer services in the digital world, not just a chatbot, but it’s going to be able to satisfy a lot of their needs in the physical world because in order to bring AI to the physical world, you need more than just very smart algorithms or models. You need infrastructure in the physical world, and that’s our advantage…

…We have built a big infrastructure in the physical world with digital connections. We believe that, that kind of infrastructure is going to be very valuable when we are moving to the era of physical AI.

Meituan’s management expects to incur a lot of capex to improve Meituan’s in-house large language model, Longcat; to develop Longcat, management made the procurement of GPUs in 2024 a top priority, and expects to further scale GPU-related capital expenditure in 2025; Longcat has quite good evaluation results in China; Longcat’s API core volume has increased from 10% at the beginning of 2024 to 68% currently

On the algorithm model and compute side, it’s going to need a lot of CapEx and a very good foundation model. So in the past year, to ensure adequate supply of GPU resources has been a top priority for us. And even as we allocate meaningful resources in shareholder return and new initiatives, we keep investing billions in GPU resources. So our capital — CapEx this year has been substantial. And this year, we plan to further scale our investment in this very critical area. And thanks to our infrastructure and large language model team, we have made significant optimization, both in efficiency and effectiveness. And as a result, our in-house large language model, longcat, has achieved quite good evaluation results comparable to the top-tier models in China…

…The API core volume for Longcat has increased from 10% at the beginning of last year to 68% currently, so — which further validates the effectiveness of our in-house foundation model.

Meituan’s management believes that AI is going to give a massive push to the robotics industry; Meituan has been researching autonomous vehicles since 2016 and drones since 2017; management has made several investments in leading robotics and autonomous driving start-ups; management expects Meituan’s efforts in robotics and AI to be even more tightly integrated in the future

I think AI is going to give a massive push to the development of robotics. So we have been a very early mover when it comes to autonomous delivery vehicles and drones. So actually, we started our R&D in autonomous vehicles in late ’26 (sic) [ late ’16 ]. And we started our R&D in drones in 2017. So we have been working on this for many years, and we are making very good progress. So right now, we are looking to ways to apply AI in the on-demand delivery field. So apart from our in-house research — in-house R&D, we have also made quite several investments in leading start-ups in the robotics and autonomous driving sector to support their growth…

…In future, our robotics and AI will be even more tightly integrated, and we will keep improving in the areas such as autonomous delivery and logistics and automations because right now, apart — besides the last-mile delivery of on-demand delivery, we also operate a lot of rather big warehouses, and that will be very good use cases for automation technologies.

MongoDB (NASDAQ: MDB)

MongoDB’s management expects customers to start building AI prototypes and AI apps in production in 2025 (FY2026), but management expects the progress to be gradual, and so MongoDB’s business will only benefit modestly from AI in 2025 (FY2026); there are high-profile AI companies building on top of MongoDB Atlas, but in general, customers’ journeys with building AI applications will be gradual; management thinks that customers are slow in building AI applications because they lack AI skills and because there are still questions on the trustworthiness of AI applications; management sees the AI applications of today as being fairly simplistic, but thinks that AI applications will become more sophisticated as people become more comfortable with the technology

In fiscal ’26, we expect our customers will continue on their AI journey from experimenting with new technology stacks to building prototypes to join apps and production. We expect the progress to remain gradual as most enterprise customers are still developing in-house skills to leverage AI effectively. Consequently, we expect the benefits of AI to be only modestly incremental to revenue growth in fiscal ’26…

…We have some high-profile AI companies who are building on top of Atlas. I’m not at liberty to name who they are, but in general, I would say that the journey for customers is going to be gradual. I would say one is a lack of AI skills in their organizations. They really don’t have a lot of experience and it’s compounded by the rapid evolution of AI technology that they feel like it’s very hard for them to kind of think about like what’s stack to use and so on and so forth. The second, as I mentioned earlier, on the Voyage question, there’s also a real worry about the trustworthiness of a lot of these applications. So I would say the use cases you’re seeing are fairly simplistic — customer chat bots, maybe document summarization, maybe some very simple [indiscernible] workflows. But I do think that, that is we are in the early innings, and I expect a sophistication to increase as people get more and more comfortable,

In 2024 (FY2025), MongoDB started demonstrating that the modernisation of the technology-stack for applications (i.e. MongoDB’s Relational Migrator service) can be reduced with the help of AI tools; management will expand customer engagement for the modernisation so that it can contribute meaningfully to MongoDB’s business in 2026 (FY2027) and beyond; management will start with Java apps that run on Oracle; management sees a significant revenue opportunity in the modernisation of apps; MongoDB has successfully modernised financial applications for one of Europe’s largest ISVs (independent software vendors); management is even more confident of Relational Migrator now than in the past; Relational Migrator is tackling a very tough problem because it involves massive legacy code, and the use of AI in deciphering the code is very helpful; management is seeing a lot of interest from customers for Relational Migrator because the customers are in pain from their technical debt, and their legacy technology stack cannot handle AI applications

In fiscal ’25, our pilots demonstrated that AI tooling combined with services can reduce the cycle time of modernization. This year, we’ll expand our customer engagements so that app monetization can meaningfully contribute to our new business growth in fiscal ’27 and beyond. To start with, and based on customer demand, we are specifically targeting Java apps running on Oracle, which often have thousands of complex store procedures that need to be understood, converted and tested to successfully monetize the application. We addressed this through a combination of AI tools and agents along with inspection verification by delivery teams. Though the complexity of this work is high, the revenue opportunity for modernizing those applications is significant. For example, we successfully modernize our financial application for one of the largest ISVs in Europe, and we’re now in talks to modernize the majority of the legacy estate…

…[Question] What sort of momentum have you seen with relational migrator. And maybe how should we be thinking about that as a growth driver going forward?

[Answer] Our confidence and bullish on the space is even higher today than it was before…

…When you’re looking at a legacy app that’s got hundreds — tens of thousands, if not thousands, not tens of thousands of store procedures being able to reason about that code, being able to decipher that code and then ultimately to convert that code takes — is a lot of effort. And — but the good news is that we are seeing a lot of progress in that area. We see a lot of interest from our customers in this area because they are in so much pain with all the technical debt they’ve assumed. Second is that when they think about the future and how they enable AI in these applications, there’s no way they can do this on their legacy platforms. And so they’re motivated to try and modernize as quickly as possible.

MongoDB’s management sees AI transforming software from a static tool into a decision-making partner, but the rate of change is governed by the quality of the software’s data infrastructure; legacy databases cannot keep up with the requirements of AI and this is where MongoDB’s document-model database is advantageous; MongoDB’s database simplifies AI development by providing an all-in-one solution incorporating all the necessary pieces, including an operational data store, a vector database, and embedding and reranking models; MongoDB’s database provides developers with a structured approach when they are building AI applications; management sees AI applications being much better than traditional software in scenarios that require nuanced understanding, sophisticated reasoning and interaction and natural language

AI is transforming software from a static tool into a dynamic decision-making partner. No longer limited to predefined tasks, AI-powered applications will continuously learn from real-time data, but this software can only adapt as fast as the data infrastructure is built on and legacy systems simply cannot keep up. Legacy technology stacks were not designed for continuous adaptation. Complex architectures, batch processing and rigid data models create friction at every step, slowing development, limiting organization’s ability to act quickly and making even small updates time consuming and risky. AI will only magnify these challenges. MongoDB was built for change. MongoDB was designed from the outset to remove the constraints of legacy databases, enabling businesses to scale, adapt and innovate at AI speed. Our flexible document model handles all types of data while seamless scalability ensures high performance for unpredictable workloads…

…We also simplify AI development by natively including vector and tech search directly in the database providing a seamless developer experience that reduces cognitive load, system complexity, risk and operational overhead, all with the transactional, operational and security benefits intrinsic to MongoDB. But technology alone isn’t enough. MongoDB provides a structured solution-oriented approach that addresses the challenges customers have with the rapid evolution of AI technology, high complexity and a lack of in-house skills. We are focused on helping customers move from AI experimentation to production faster with best practices that reduce risk and maximize impact…

…AI-powered applications excel where traditional software often falls short, particularly in scenarios that require nuanced understanding, sophisticated reasoning and interaction and natural language…

…MongoDB demarcatizes the process of building trustworthy AI applications right out of the box. Instead of cobbling together all the necessary piece parts and operational data store, a vector database and embedding and reranking models, MongoDB delivers all of it with a compelling developer experience…

…We think architecturally, we have a huge advantage of the competition. One, the document model really supports different types of data structured, semi-structured and unstructured. We embed a search and Vector Search onto a platform. No one else does that. Then we’ve now with the Voyage AI, we have the most accurate embedding and reranking models to really address the quality and trust issue. And all this is going to be put together in a very elegant developer experience that reduces friction and enables them to move fast.

MongoDB acquired Voyage AI for $220 million, $200 million of which was paid in MongoDB shares; Voyage AI helps MongoDB’s database solve the hallucination issue – a big problem with AI applications – and make AI applications more trustworthy; management thinks the best way to ensure accurate results with AI applications is through high-quality data retrieval, and high-quality data retrieval is enabled by vector embedding and reranking models; Voyage AI’s vector embedding and reranking models have excellent ratings in the Hugging Face community and are used by important AI companies; Voyage AI has an excellent AI team; through Voyage AI, MongoDB can offer best-in-class embedding and reranking models; ISVs (independent software vendors) have gotten better performance when they switched from other embedding models to Voyage AI’s models; Voyage AI’s models increase the trustworthiness of the most demanding and mission-critical AI applications; Voyage AI’s models will only be available on Atlas

With the Voyage AI acquisition, MongoDB makes AI applications more trustworthy by pairing real-time data and sophisticated embedding and retreatment models that ensure accurate and relevant results…

…Our decision to acquire Voyage AI addresses one of the biggest problems customers have when building and deploying AI applications, the risk of hallucinations…

…The best way to ensure accurate results is through high-quality data retrieval, which shows that not only the most relevant information is extracted from an organization’s data with precision, high-quality retrieval is enabled by vector embedding and reranking models. Voyage AI has embedding and reranking models and are among the highest rated in the Hugging Face community for retrieval, classification, clustering and reranking and are used by AI leaders like Anthropic, LangChain, Harvey and Replit. Voyage AI led by Stanford professor, Tang Yuma, who has assembled a world-class AI research team from AI Labs at Stanford, MIT, Berkeley and Princeton. With this acquisition, MongoDB will offer best-in-class embedding and reranking models to power native AI retrievable…

…Let me address how the acquisition of Voyage AI will impact our financials. We disclosed last week that the total consideration was $220 million. Most Voyage shareholders received a consideration in MongoDB stock with only $20 million being paid out in cash…

…We know a lot of ISVs have already reached out to us since the acquisition saying they switched to Voyage from other model providers and they got far better performance. So the value of Voyage is being able to increase the quality and hence the trustworthiness of these AI applications that people are building in order to serve the most demanding and mission-critical use cases…

…Some of these new capabilities like Voyage now that will be available only on Atlas.

Swisscom was able to deploy a generative AI application in just 12 weeks using MongoDB Atlas

Swisscom, Switzerland’s leading provider of mobile, Internet and TV services deployed in new GenAI app in just 12 weeks using Atlas. Swisscom implemented Atlas to power a RAG application for the East Foresight library transforming unstructured data such as reports, recordings and graphics into vector bettings that large language models can interpret. This enables Vector Search to find any relevant contact resulting in more accurate and tailored responses for users.

If an LLM (large language model) is a brain, a database is memory, and embedding models are a way to find the right information for the right question; embedding models provide significant performance gains when used with LLMs

So think about the LLM as the brain. Think about the database is about your memory and the state of where how things are. And so — and then think about embedding as an ability to find the right information for the right question. So imagine you have a very smart person, say, like Albert Einstein on your staff and you’re asking him, in this case, the LLM, a particular question. While Einstein still needs to go do some homework based on what the question is about finding some information before he can formulate an answer. Rather than reading every book in a library, what the embedding models do is essentially act like a library and pointing Einstein to the right section, the right aisle, the right shelf, the right book and the right chapter on the right page, to get the exact information to formulate an accurate and high-quality response. So the performance gains you get a leveraging embedding models is significant.

Okta (NASDAQ: OKTA)

The emergence of AI agents has contributed to the growing importance to secure identity; management will provide access to Auth For GenAI on the Auth0 platform in March 2025; 200-plus startups and large enterprises are on the waitlist for Auth For GenAI; Auth For GenAI allows AI agents to securely call APIs; management is seeing that companies are trying to build agentic systems, only to run into problems with giving these agents access to systems securely; within AI, management sees agentic AI as the most applicable for Okta’s business in the medium term

With the steady rise of cloud adoption, machine identities and now AI agents, there has never been a more critical time to secure identity…

…On the Auth0 platform, we announced Auth For GenAI. We’ll begin early access this month. We already have a wait list of eager customers ranging from early startups to Fortune 100 organizations. Auth for GenAI is developed to help customers securely build and scale their Gen AI applications. This suite of features allows AI agents to securely call APIs on behalf of users while enforcing the right level of access to sensitive information…

…People are trying to stitch together agentic platforms and write their own agentic systems and what they run smack into is, wait a minute. How am I going to get these agents access all these systems if I don’t even know what’s in these systems and I don’t even know the access permissions that are there and how to securely authenticate them, so that’s driving the business…

…I’ll focus on the agentic part of AI. That’s probably the most, in the medium term, that’s probably the most applicable to our business…

…On the agent side, the equivalent of a lot of these deployments have like passwords hardcoded in the agent. So if that agent gets compromised, it’s the equivalent of your monitor having a bunch of sticky notes on it with your passwords before single sign-on. So Auth for GenAI gives you a protocol in a way to do that securely. So you can store these tokens and have these tokens that are secured. And then if that agent needs to pop out and get some approval from the user, Auth for GenAI supports that. So you can get a step-up biometric authentication from the user and say, “Hey, I want to check Jonathan’s fingerprint to make sure before I book this trip or I spend this money, it’s really Jonathan.” So those 3 parts are what Auth for GenAI is, and we’re super, super excited about it. We have a waitlist. Over 200-plus Fortune 100s and startups are on that thing.

Okta’s management thinks agentic AI is a real phenomenon and will turbocharge machine identity for Okta by 2 orders of magnitude higher; already today, a good part of Okta’s business is providing machine identity; management is the most excited about the customer identity part of Okta’s business when it comes to agentic AI because companies will start having agentic AIs as customers too; management thinks Okta will be monetise agentic AI from both people building agents, and people using agents

The agenetic revolution is real, and the power of AI and the power of these language models, the interaction modalities that you can have with these systems these machines doing things on your path and what they can do and how they can infer next actions, et cetera, et cetera. You all know it’s really real. But the way to think about it from an Okta perspective, it is like machine identity on steroids, turbocharged to like 2 orders of magnitude higher. So that’s like really exciting for us because what do we do. A good part of our business is actually logging in machines right now. Auth0 has the machine-to-machine tokens where people, if they build some kind of web app that services other machines, they can use Auth0 for the login for that. Okta has similar capabilities. And now you have not only that basic authentication challenge but you have the — all of these applications as you get 2 orders of magnitude, more things logging in, you have to really worry about the fine grain authorization into your services…

…[Question] Which side of the business are you more excited about from an agentic AI perspective?

[Answer] I think the customer identity side is more exciting. I think it’s a little bit of a — my answer is a little bit of a — I’m kind of like having both ways because a lot of the — when you talk about developers building agentic AI, they’re doing it inside of enterprises. So like the pattern I was talking about earlier, there’s these teams and these companies that have been tasked with we hear about this [ agent ] and make it work. And the first thing they have to do is I’ve had many conversations with customers where they’ve been in these discussions and we want — we did a POC and now we’re worried about doing it broadly, but the task was basically hook everything up to our existing — hook these agents up to all of our existing systems. And before we could do that inside of enterprise, we had to get a good identity foundation in front of all these things. And so it’s kind of like similar to your building something and you’re a developer, you’re exposing APIs, you’re doing fine grain authorization. You’re taking another — you’re using another platform or you’re building your own agentic AI platform, and you’re having to talk to those systems and those APIs to do things on user’s behalf, so you’re a developer, but it’s kind of like a workforce use case, but I think people building these systems and getting the benefit from that is really exciting…

…We can monetize it on “both side”, meaning people building the agents and people using the agents. The agents have to log in and they have to log into something. So I think it’s potential to monetize it on both sides.

Okta’s management thinks the software industry does not yet know how to account for AI agents in software deals; management thinks that companies will eventually be buying software licenses for both people and AI agents

One of the things that we don’t have today is the industry doesn’t have a way to like identify an agent. I don’t mean in the sense of like authenticating or validated agent. I mean to actually a universal vernacular for how to record an agent, how to track it and how to account for it. And so I think that’s something you’ll see coming. You’ll see there will be actually a type of account, an Okta that’s an agent account. You’ll see companies starting to — when they buy software, they say, hey, I buy these many people and these many agentic licenses. And that’s not quite there yet. Of course, platforms that are coming out with agent versions have this to some degree, but there isn’t a common cross-company, cross enterprise definition of an agent, which is an interesting opportunity for us actually.

Sea Ltd (NYSE: SE)

Sea’s management is using AI in Shopee to understand shoppers’ queries better and to help sellers enhance product listings, and these AI initiatives have improved purchase conversion rates and sellers’ willingness to spend on advertising; management has upgraded Shopee’s chatbots with AI and this led to meaningful improvement in customer service satisfaction score and customer service cost-per-contact; management is using AI to improve the shopper return-refund process and has seen a 40% year-on-year decrease in resolution times in Asia markets; management thinks Shopee is still early in the AI adoption curve

We continue to adopt AI to improve service quality in a practical and effective manner. By using large language models to understand queries, we have made search and discovery more accurate, helping users find relevant products faster. We provide our sellers with AI tools to enhance product listings by improving descriptions, images, and videos. These initiatives have improved purchase conversion rates while also making sellers more willing to spend on ads, boosting our ad revenue…

… After upgrading our chatbots with AI, we saw a meaningful increase in our customer service satisfaction score over the past year, and a reduction in our customer service cost-per-contact by nearly 30% year-on-year. We also used large language model capabilities to enhance our buyer return-refund process, addressing a key e-commerce pain-point. In the fourth quarter, we improved resolution times in our Asia markets by more than 40% year-on-year, with nearly six in ten cases resolved within one day. We believe we are still early in the AI adoption curve and remain committed to exploring AI-driven innovations to improve efficiency and deliver better experiences for our users.

Sea’s management thinks the use of AI is helping Sea both monetise its services better, and save costs

[Question] I just wanted to get some color with regard to the benefit from AI. Are we actually seeing cost efficiency, i.e., the use of AI actually save a lot of the manual labor cost? So that helps to achieve a lot of cost savings? Or are we actually seeing the monetization is getting better coming from AI?

[Answer] We are seeing both, in fact, for example, in our search and recommendations, we actually use the large language model to better understand user queries, making certain discovery a lot more accurate and helping users find relevant faster… We are also using the AI to understand the product a lot better like historically, it was a fintech matching, but now we can use existing pictures and the descriptions and the reviews to generate a lot more richer understanding of the product. And all those help us essentially matching, our product users’ intention a lot better. 

We are also having a lot of AIGC, AI-generated content in our platform. We provide that as a tool to our sellers to be able to produce image, a description of the product or the videos, especially a lot better compared to what they had before.

And both of this increased our conversions meaningfully in our platform.

On the other side, on the cost savings side, I think in Forrest’s opening, we talked about the chatbot, the — if you look at our queries, about 80% of the queries are answered by the chatbot already, which is a meaningful cost savings for the — for our operations. I think that’s also why you can see that our cost management for e-commerce is doing quite well. Even for the 20% answered by the agent, we have an AI tool for the agent to be able to understand the context a lot better, so can help them to respond a lot faster to the customers,

Tencent (OTC: TCEHY)

Tencent’s AI initiatives can be traced to 2016; management has been investing in Tencent’s proprietary foundation model, HunYuan, since early 2023; management sees HunYuan as the foundation for Tencent’s consumer and enterprise businesses

Our AI initiatives really trace back to 2016 when we first established our AI lab. Since 2023, early part of that, we have been investing heavily in our proprietary HunYuan foundation model, which forms an important technology foundation for our consumer and enterprise-facing businesses and will serve as a growth driver for us in the long run. Our investments in HunYuan enable us to develop end-to-end foundation model capabilities in terms of infrastructure, algorithm, training, alignment and data management and also to tailor solutions for the different needs of internal and external use cases.

Tencent’s management has released multimodal HunYuan foundation models across image, video, and 3D generation; the multimodal HunYuan foundation models have received excellent scores in AI benchmarking

In addition to LLMs, we have released multimodal HunYuan foundation models with capabilities that span across image, video and 3D generation. HunYuan’s image generation models achieved the highest score from FlagEval in December of last year. In video generation, our model excels in video output quality and ranked first on Hugging Face in December of last year. 

Tencent’s management has been actively releasing Tencent’s AI models to the open source community

Our 3D generation model was the industry’s first open source model supporting text and image to 3D generation. In addition to that, we also contribute to the open source community actively and have open sourced a series of advanced models in the HunYuan family for 3D generation, video generation, large language and image generation. Several of these models have gained great popularity among developers worldwide.

For Tencent’s consumer-facing AI products, management has been utilising different AI models because they believe that a combination of models can handle complex tasks better than a single model; Tencent’s native AI application, Yuanbao, provides access to multiple models; Yuanbao’s DAU (daily active users) increased 20-fold from February 2025 to March 2025; management has been testing AI features in Weixin to improve the user experience and will be adding more AI features over time; management will be introducing a lot more consumer-facing AI applications in the future; management thinks consumer AI is in a very early stage, but they can see Yuanbao becoming a strong AI native assistant helping with deep research, and the Ema Copilot being a personal and collaborative library; management is looking to infuse AI into each of Tencent’s existing consumer products

Going to our consumer-facing AI products. We adopt a multimodal strategy to provide the best AI experience to our users, so we can leverage all available models to serve different user needs. We need this because different AI models are optimized for different capabilities, performance metrics and use cases and a combination of various models can handle complex tasks better than a single model…

…On the product front, our AI native application, Yuanbao, provides access to multiple models, including Chain of Thought reasoning models such as HunYuan T1 and DeepSeek R1 and fast-thinking model HunYuan Turbo S with the option of integrating web search results. Yuanbao search results can directly access high-quality proprietary content from Tencent ecosystem, such as official accounts and video accounts. By leveraging HunYuan’s multimodal capabilities, Yuanbao can process prompts in images, voice and documents in addition to text. Our cloud infrastructure supports stable and uncapped access to leading models. From February to March, Yuanbao’s DAU increased 20-fold to become the third highest AI native mobile application in China by DAU…

…We have also started testing AI features in Weixin to enhance user experience, such as for search, language input and content generation and we will be adding more AI features in Weixin going forward…

…We actually have a whole host of different consumer-facing applications and you should expect more to come. I think AI is actually in a very early stage. So it’s really hard to talk about what the eventual state would look like. But I would say, one, each product will continue to evolve into very useful and even more powerful products for users. So Yuanbao can be sort of a very strong AI native assistant and the Ema copilot could be your personal library and also a collaborative library for team collaborations. And Weixin can have many, many different features to come, right? And in addition to these products, I think our other products would have AI experiences, including QQ, including browser and other products. So I think we would see more and more AI — consumer AI-facing products. And at the same time, each one of the products will continue to evolve…

…Each one of our products would actually try to look for unique use cases in which they can leverage AI to provide a great user experience to their users…

…Yuanbao, well, right now, it is a chatbot and search. But over time, I think it would actually proliferate into a all-capable AI assistant with many different functionalities serving different types of people. So if — it would range from sort of students who want to learn and it would include all kinds of different people who, actually knowledge workers who want to complete their work and would sort of cover deep research, which allows people to very deep research into different topics.

Tencent’s management thinks that there are advantages to both developing Tencent’s own foundation models and using 3rd-party models

By investing in our own foundation models, we are able to fully leverage our proprietary data to tailor solutions to meet customized internal and customer needs, while at the same time, making use of external models allowed us to benefit from innovations across the industry.

Tencent’s management has been accelerating AI integration into Tencent’s cloud businesses, including its infrastructure as a service business, its platform as a service business, and its software as a service business; the AI-powered transcription and meeting summarisation functions in Tencent Meeting saw a year-on-year doubling in monthly active users to 15 million

We have been accelerating AI integration into our cloud business across our infrastructure, platform and Software as a Service solutions.

Through our Infrastructure as a Service solutions, enterprise customers can achieve high-performance AI training and inference capabilities at scale and developers can access and deploy mainstream foundation models.

For Platform as a Service, PaaS, our TI platform supports model fine-tuning and inference demands with flexibility, will provide powerful solutions supporting enterprise customers in customizing AI assistants using their own proprietary data and developers in generating mini programs and mobile applications through natural language prompts.

Our SaaS products increasingly benefit from AI-powered tools. Real-time transcription and meeting summarization functions in Tencent Meeting gained significant popularity resulting in monthly active users for these AI functions doubling year-on-year to 15 million. Tencent Docs also enhanced the user productivity and content generation and processing.

Tencent’s AI cloud revenue doubled in in 2024, despite management having limited the availability of GPUs for cloud services in preference for internal use-cases for ad tech, foundation model training, and inference for Yuanbao and Weixin; management has stepped up the purchase of GPUs in 2024 Q4 and expects the revenue growth of cloud services to accelerate as the new GPUs are deployed for external use cases; Tencent’s capital expenditures in 2024 Q4 increased more than 3x to US$10.7 billion from a year ago because of the higher purchases of GPUs; management believes the step-up in capex in 2024 Q4 is to a new higher steady state

In 2024, our AI cloud revenue approximately doubled year-on-year. Increased allocation of GPUs for internal use cases initially for ad tech and foundation model training and more recently on AI inference for Yuanbao and Weixin has limited our provision of GPUs to external clients and thus constrained our cloud services revenue growth. For external workloads, we have prioritized available GPUs towards high-value use cases and clients. Since the fourth quarter of 2024, we have stepped up our purchase of GPUs. And as we deploy these GPUs, we expect to accelerate the revenue growth of our overall cloud services…

…As the capabilities and benefits of AI become clearer, we have stepped up our AI investments to meet our internal business needs, train foundation models and support searching demand for inference we’re experiencing from our users. To consolidate our resources around this all important AI effort, we have reorganized our AI teams to sharpen focus on both fast product innovation and deep model research. Matching our stepped-up execution momentum and decision-making velocity, we increased annual CapEx more than threefold to USD 10.7 billion in 2024, equivalent to approximately 12% of our revenue with a notable uplift in fourth quarter of the year as we bought more GPUs for both inference needs as well as for our cloud services…

…We did step up CapEx to a new sort of higher steady state in the fourth quarter of last year…

…Part of the reason why you see such a big step up in terms of the CapEx in the fourth quarter is because we have a bunch of rush orders for GPUs for both inference as well as for our cloud service. And we would only be able to capture the large increase in terms of IaaS service demand when we actually install these GPUs into the data center, which would take some time. So I would say we probably have not really captured a lot of that during the first quarter. But over time, we will capture quite a bit of it with the arrival and installation of the GPUs.

Tencent’s management already sees positive returns for Tencent from their investment in AI; the positive returns come in 3 areas, namely, in advertising, in games, and in video and music services; in advertising, Tencent has been using AI to approve ad content more efficiently, improve ad targeting, streamline the ad creative process for advertisers, and deliver higher return on investment for advertisers; Tencent’s marketing services experienced revenue growth of 20% in 2024 because of AI integration, despite a challenging macro environment; in games, Tencent is using AI to improve content production efficiency and build in-game chat bots, among other uses; in video and music services, Tencent is using AI to improve productivity in content creation and effectively boost content discovery

We believe our investment in AI has already been generating positive returns for us…

…For advertising, we enhanced our advertising system with neural network AI capabilities since 2015. We rebuilt ad tech platform using large model capabilities since 2020, enabling long sequence user behavior analysis across multiple properties which resulted in increased user engagement and higher click-through rates. Since 2023, we have been adding large language model capabilities to facilitate more efficient approvals of ad content, to better understand merchandise categories and users commercial intent for more precise ad targeting and to provide generative AI tools for advertisers to streamline the ad creative process, leveraging AI-powered ad targeting capabilities and generative AI ad creative solutions. Our marketing services business is already a clear beneficiary of AI integration with revenue growth of 20% in 2024 amid challenging macro environment.

In games, we adopted machine learning technology in our PvP games since 2017. We leveraged AI in games to optimize matching experience, improve game balance and facilitate AI coaching for new players, empowering our evergreen games strategy. Our games business is now integrating large language model capabilities, enhanced 3D content production efficiency and to empower in-game chatbots.

For our video and music services, we’re leveraging AI to improve productivity in animation, live action video and music content creation. Our content recommendation algorithms are powered by AI and are proven effective in boosting content discovery. These initiatives enables us to better unlock the potential of our great content platforms…

…Across pretty much every industry we monitor the AI enhancements we’re deploying and delivering superior return on investment for advertisers versus what they previously enjoyed and versus what’s available elsewhere.

Tencent’s management expects to further increase capital expenditure in 2025 and for capital expenditure to be a low-teens percentage of revenue for the year; while capital expenditure in 2025 is expected to increase, the rate of growth has slowed down significantly

We intend to further increase our capital expenditures in 2025 and expect our CapEx to account for low teens percentage of our revenue…

…[Question] You guided a CapEx to revenue ratio of low-teens for 2025, which is a similar ratio as for ’24. So basically, this guidance implies a significant slowdown of CapEx growth.

Tencent’s management sees several nuances on the impact to Tencent’s profit margins from the higher AI capital expenditures expected, but they are optimistic that Tencent will be able to protect its margins; the AI capital expenditures go into 4 main buckets, namely, (1) ad tech and games, (2) large language model training, (3) renting out GPUs in the cloud business, and (4) consumer-facing inference; management sees good margins in the 1st bucket, decent margins in the 3rd bucket, and potentially some margin-pressure in the 4th bucket; but in the 4th bucket, management sees (1) the potential to monetise consumer-facing inference through a combination of advertising revenue and value-added services, and (2) avenues to reduce unit costs through software and better algorithms

[Question] As we step up the CapEx on AI, our margin will be inevitably dragged by additional depreciation and R&D expenses. So over the past few years, we have seen meaningful increase in margin as we focus on high-quality growth. So going forward, how should we balance between growth and profitability improvement?

[Answer] It’s worth digging into exactly where that CapEx is going to understand whether the depreciation becomes a margin pressure or not. So the most immediate use of the CapEx is GPUs to support our ad tech and to a lesser extent, our games businesses. And you can see from our results, you can hear from what Martin talked about, that, that CapEx actually generates good margins, high returns.

A second use of CapEx was GPUs for large language model training…

…Third, there’s CapEx related to our cloud business, which, we buy this GPU servers, we rent them out to customers, we generate a return. It may not be the highest return business in our portfolio but nonetheless, it’s a positive return. It covers the cost of the GPUs and therefore, the attendant depreciation.

And then finally, where I think there is potentially the short-term pressure is the CapEx for 2C [to-consumers] inference. And it — that is an additional cost pressure but we believe it’s a manageable cost pressure because that CapEx is a subset of the total CapEx. And we’re also optimistic that over time those — the 2C inference activity that we’re generating, just like previous activity within different Tencent platforms will be monetizing through a combination of advertising revenue and value-added services. So overall, while we understand that you have questions around the step-up in CapEx and how that translates into profitability over time, we’re actually quite optimistic that we can continue to grow the business while protecting margins…

…In the inference for consumer-facing product. There’s actually a lot of avenues through which we can actually reduce the unit cost by technical means, by software and by better algorithms. So I think that’s also sort of a factor to keep in mind.

Tencent’s management believes that the AI industry is now getting much higher productivity on large language model training from existing GPUs without needing to add additional GPUs at the pace previously expected, as a result of DeepSeek’s breakthroughs; previously, the belief was that each new generation of large language models would require an order of magnitude more GPUs; Tencent’s AI-related capital expenditure is the largest amongst Chinese technology companies; management thinks that Chinese technology companies are spending less on capital expenditure as a percentage of revenue than Western peers because Chinese companies have been prioritizing efficient utilization of GPUs without impairing the ultimate effectiveness of the AI technology developed

There was a period of time last year when there was a belief that every new generation of large language model required an order of magnitude more GPUs. That period of time ended with the breakthroughs that DeepSeek demonstrated. And now the industry and we within the industry are getting much higher productivity on a large language model training from existing GPUs without needing to add additional GPUs at the pace previously expected…

…There was a period last year when people asked us if our CapEx was big enough relative to our China peers, relative to our global peers. And now out of the listed companies, I think we had the largest CapEx of any China tech company in the fourth quarter. So we’re at the forefront among our China peers. In general, the China tech companies are spending less on CapEx as a percentage of revenue than some of their Western peers. But we believe for some time that’s because the Chinese companies are generally prioritizing efficiency and utilization — efficient utilization of the GPU servers. And that doesn’t necessarily impair the ultimate effectiveness of the technology that’s being developed. And I think DeepSeek’s success really sort of symbolized and solidified, demonstrated that, that reality.

Tencent’s management thinks AI can benefit Tencent’s games business in 3 ways, namely, (1) a direct, more short-term benefit in helping game developers be more productive, (2) an indirect, more long-term benefit in terms of games becoming an important element of human expression in an AI-dominated world, and (3) allow evergreen games to be more evergreen

We do believe that games benefit in a direct and potentially a less direct way from AI technology enhancements. The direct way is the game developers using AI to assist them in creating more content more quickly and serving more users more effectively. And then the indirect way, which may be more of a multi-decade rather than the second half of this year story is that as humanity uses AI more broadly, then we think there’ll be more time and also more desire for high agency activities among people who are now empowered by AI. And so one of the best ways for them to express themselves in a high agency way rather than a passive way is through interactive entertainment, which is games…

…We actually felt AI would allow evergreen games to be more evergreen. And we are already seeing sort of how AI can help us to execute and magnify our evergreen strategy. And part of it is within production, right, you can actually produce great content now within a shorter period of time so that you can keep updating the games with higher frequency of high-quality content. And with the PvE experience, when you have smarter box, right, you actually sort of make the game more exciting and more like PvP. And within PvP, a lot of the matching and balancing and coaching of new users can actually sort of be done in a much better way when you apply AI.

Tencent’s management sees strong competitive advantages that Tencent has when it comes to AI agents because of the large user base of Tencent’s products and the huge variety of activities that happen within Tencent’s products

We would be able to build stand-alone AI agents by leveraging models that are of great quality and at the same time by leveraging the fact that we have a lot of consumers on our different software platforms like our browser, like Yuanbao over time. But at the same time, right, even within Weixin and within QQ, we can have AI agents. And the AI agents can actually leverage the ecosystem within the apps and provide really great service to our users by completing complex tasks, right? If you look at Weixin, for example, Weixin has got a lot of users, a very long user time per day as well as high frequency of users opening up the app, that’s 1 advantage. The second advantage is that if you look at the activities within Weixin is actually very, very diversified, right? It’s not just sort of entertainment, it’s not just transactions, it’s actually sort of social communication and content and a lot of people will conduct their work within Weixin, a lot of people conduct their learning within Weixin and there are a lot of transactions that go through Weixin. And there’s a multitude of Mini Programs, which actually allowed all sorts of different activities to be carried out, right? So if you look at the Mini program ecosystem, we can easily build an agent based on a model that actually can connect to a lot of the different Mini Programs and have activities and complex tasks completed for our users. So I think those are all very distinctive advantages that we have.

Tencent’s management believes that AI search will eventually replace traditional search

At a high level, if we look at the history of web search subsuming web directory, if we look at our own behavior, with AI prompts vis-a-vis traditional search, I think it’s possible that AI search will subsume traditional search because ultimately, web directory traditional search, AI prompt, all represent mechanisms for accessing the Internet’s knowledge graph.

Tencent’s management believes that in China, AI chatbots will be monetised first through performance advertising followed by value-added services, as opposed to in the West, where AI chatbots have been monetised first through subscription models followed by performance advertising

In terms of how the AI prompt will be monetized, time will tell but I think that we can already see in the Western world, the first monetization is through subscription models and then over time, performance advertising will follow. I think in China, it will start with performance advertising and then value-added services will follow.

Veeva Systems (NYSE: VEEV)

Veeva’s management’s AI strategy for Veeva is to have its Commercial Cloud, Development Cloud, and Quality Cloud be the life sciences industry’s standard core systems of record; management is making Veeva’s data readily available for the development of AI applications by Veeva and 3rd parties through the Direct Data API released in 2024; management is seeing good uptake on the Direct Data API; the Direct Data API will be free to all of Veeva’s customers because management wants people to be building on the API; management found a way to offer the Direct Data API with lesser compute resources than originally planned for; Veeva is already using the Direct Data API internally, and 10 customers are already using it; it takes time for developers to be used to the Direct Data API, because it’s a fundamentally new type of API, but it’s a great API; management believes that Direct Data API will enable the life sciences industry to leverage their core data through AI faster than any other industry

We also executed well on our AI strategy. Commercial Cloud, Development Cloud, and Quality Cloud are becoming the industry’s standard core systems of record. With significant technology innovation including the Direct Data API released this year, we are making the data from our applications readily available for the development of relevant, timely AI solutions built by Veeva, our customers, and partners…

…We are seeing good uptake of the Direct Data API. And we — yes, as you mentioned, we recently announced that that’s going to be free to all of our customers. And — the reason there is we want everybody building on that pack of API. It’s just a much better, faster API for many use cases, and we found a way to do it where it was not going to consume as many compute resources as we thought it was…

…We are using it internally, for example, for connecting different parts of our clinical suite, different parts of our safety suite together and our partners are starting to do it. We have more than 10 customers that are already doing it. Some of them are large customers. it takes some time because it’s a different paradigm for integration. People have been using a hammer for a long time. And now you’re giving them a Jack Hammer and they got to learn how to use it. But we are super enthused. It’s a fundamental new type of API where you can get like all of the data out of your Vault, super quickly…

…I’m really pleased about what we’re doing for the life sciences industry because many of our core systems are Veeva and now their core systems are going to be enabled with this fundamental new API that’s going to allow them to leverage their core data faster than any other industry.

Reminder from management that Veeva recently announced 3 new AI solutions, namely, Vault CRM Bot, CRM Voice Control, and MLR Bot; management has more AI solutions in the pipeline, but the timing for release is still unclear; management wants to invest more in AI solutions and they think the company has strong leadership in that area

We announced new Veeva AI Solutions including Vault CRM Bot, CRM Voice Control, and MLR Bot…

……Now with CRM Voice Control that we’ll be bringing out this year, and also CRM Bot and the MLR Bot, medical legal regulatory review, and we have quite a few others in the plan, too. We don’t know exactly which ones we’ll bring out when, but we have — we’re putting more investment in AI solutions. We centralized the group around that, so we can develop. I have a strong leader there and develop more core competency around around AI.

Veeva’s management was initially a little skeptical of AI because of the amount of money flowing in, and the amount of hype surrounding it

[Question] I want to start with the AI offerings that you’ve built out Peter, maybe if you were on the tape back a year, there was a little bit of a perception from the investment community. That you were coming off as maybe a little bit skeptical on AI, but now you’ve come out with a lot of these products. Maybe can you walk us through kind of what’s driven the desire or the momentum to push out these products kind of quickly?

[Answer] AI is certainly captivating technology, right? So much money going into it, so much progress, and so much hype.

Veeva’s management thinks AI is shaking out the way they expected to, which is the existence of many large language models; management also thinks the development of AI has become more stable

If we just stay at that level, I’m really pleased that things are starting to shake out roughly how we thought they were going to take out. There’s not going to be one large language model, there are going to be multiple. There’s not going to be 50, but there’s going to be a good handful and they’re going to specialize in different areas. And it’s not so unstable anymore, where you wake up and everything changes, right? DeepSeek came out, came out, Yes, well, guess what? The world keeps turning. NVIDIA is going to have their own model? That’s okay, and the world keeps turning. So I think it’s starting to settle out.

Veeva’s management sees the infrastructure layer of AI as being really valuable, but they also see a lot of value in building specific use cases on top of the infrastructure layer, and that is where they want Veeva to play in

So it’s settling out that these core large language models are going to be at the platform level and that’s super valuable, right? That’s not where companies like Veeva play in, that core infrastructure level. It’s very valuable. But there’s a lot of great value on specific use cases on top that can be used in the workflow. So that’s what we’re doing now, focusing on our AI solutions.

Veeva’s management is using AI internally but it’s still early days and it has yet to contribute improvements to Veeva’s margin; Veeva’s expected margin improvements for 2025 (FY2026) is not related to AI usage

[Question] Going back to the topic of AI… how you’re leaning into kind of internal utilization too, if we think about kind of some of the margin strength you’re delivering throughout the business?

[Answer] Around the internal use of AI and the extent to which that was contributing to margins, I think. And I think the short answer there is it’s an area that we’re really excited about internally as well. We’re building strategies around, but it’s not a major contributor to the margin expansion that we saw in Q4 or in the coming year. So it’s something we’re looking into. We’re building strategies around. It’s not something we’re counting on, though, to deliver on this year’s guidance.

In 2023 and 2024, Veeva’s management was seeing customers get distracted from core technology spending because the customers were chasing AI; management is no longer seeing the AI distraction at play

I believe we called it before AI disruption, maybe that was 18 months or so a year ago. I think that’s largely behind us. Our customers have settled into what AI is and what it does. They’re still doing some innovation projects, but it’s not consuming them or distracting from the core work. So I think we’re largely through that [ 3 ] of AI distraction now.

Veeva’s management thinks that Veeva is the fastest path to AI for a life sciences industry CRM because any AI features will have to be embedded in the workflow of a life sciences company

It turns out Veeva is the fastest path to AI that you can use in CRM because it has to be done in the workflow of what you’re doing. This is not some generic AI. This is AI for pre-call planning for compliance, for how to — for the things that a pharmaceutical rep does in a compliant way based on the data sources that are needed in CRM. So Veeva is the fastest path to AI.


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. I have a vested interest in Adobe, Meituan, MongoDB, Okta, Tencent, and Veeva Systems. Holdings are subject to change at any time.

What We’re Reading (Week Ending 23 March 2025)

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 23 March 2025:

1. Investing Politics: Globalization Backlash and Government Disruption! – Aswath Damodaran

Globalization has taken different forms through the ages, with some violent and toxic variants, but the current version of globalization kicked into high gear in the 1980s, transforming every aspect of our lives…

…The biggest winner from globalization has been China, which has seen its economic and political power surge over the last four decades. Note that the rise has not been all happenstance, and China deserves credit for taking advantage of the opportunities offered by globalization, making itself first the hub for global manufacturing and then using its increasing wealth to build its infrastructure and institutions…

…China’s share of global GDP increased ten-fold between 1980 and 2023…

…Between 2010 and 2023, China accounted for almost 38% of global economic growth, with only the United States having a larger share…

…Consumers have benefited from globalization in many ways, starting with more products to choose from and often at lower prices than in pre-globalization days. From being able to eat whatever we want to, anytime of the year, to wearing apparel that has become so cheap that it has become disposable, many of us, at least on the surface, have more buying power…

…Over the last few decades, not only have more companies been able to list themselves on financial markets, but these markets has become more central to public policy. In many cases, the market reaction to spending, tax or economic proposals has become the determinant on whether they get adopted or continued. As financial markets have risen in value and importance, the cities (New York, London, Frankfurt, Shanghai, Tokyo and Mumbai) where these markets are centered have gained in importance and wealth, if not in livability, at the expense of the rest of the world…

…The rise of China from globalization also illustrates the fading of Japan and Europe over the period, with the former declining from 17.8% of global GDP in 1995 to 3.96% in 2023 and the latter seeing its share dropping from 25.69% of global GDP in 1990 to 14.86%…

…I listed consumers as winners from globalization, and they were, on the dimensions of choice and cost, but they also lost in terms of control of where their products were made, and by whom. To provide a simplistic example, the shift from buying your vegetables, fish and meat from local farmers, fishermen and butchers to factory farmers and supermarkets may have made the food more affordable, but it has come at a cost…

…While there are a host of other factors that have also contributed to the decline of small businesses, globalization has been a major contributor, as smaller businesses now find themselves competing against companies who make their products thousands of miles away, often with very different cost structures and rules restricting them. Larger businesses not only had more power to adapt to the challenges of globalization, but have found ways to benefit from it, by moving their production to the cheapest and least restrictive locales. In one of my data updates for this year, I pointed to the disappearance of the small firm effect, where small firms historically have earned higher returns than large cap companies, and globalization is a contributing factor…

…The flip side of the rise of China and other countries as manufacturing hubs, with lower costs of operation, has been the loss of manufacturing clout and jobs for the West…

…In the United States, the number of manufacturing jobs peaked at close to 20 million in 1979 and dropped to about 13 million in 2024, and manufacturing wages have lagged wage growth in other sectors for much of that period…

…I believe that globalization has been a net plus for the global economy, but one reason it is in retreat is because of a refusal on the part of its advocates to acknowledge its costs and the dismissal of opposition to any aspect of globalization as nativist and ignorant…

…Trump, a real estate developer with multiple international properties, is an imperfect spokesperson of the anti-globalization movement, but it is undeniable that he has tapped into, and benefited from, its anger. While he was restrained by norms and tradition in his first term, those constraints seem to have loosened in this second go around, and he has wielded tariffs as a weapon and is open about his contempt for global organizations. While economists are aghast at the spectacle, and the economic consequences are likely to be damaging, it is not surprising that a portion of the public, perhaps even a majority, are cheering Trump on.

To those who are nostalgic for a return to the old times, I don’t believe that the globalization genie can go back into the bottle, as it has permeated not only every aspect of business, but also significant portions of our personal lives. The world that will prevail, if a trade war plays out, will be very different than the one that existed before globalization took off…

…On the revenue growth front, companies that derive most or all of their revenues domestically will benefit and companies that are dependent on foreign sales will be hurt by tariff wars…

…Collectively, about 28% of the revenues, in 2023, of the companies in the S&P 500 came from foreign markets, but technology companies are most exposed (with 59% of revenues coming from outside the country) and utilities least exposed (just 2%) to foreign revenue exposure. It is also worth noting that the larger market cap companies of the S&P 500 have a higher foreign market revenue exposure than smaller market cap companies…

…To the extent that companies are altering their decisions on where to build their next manufacturing facilities, as a result of tariff fears or in hope of government largesse, there should be an effect on reinvestment, with an increase in reinvestment (lower sales to capital ratios) at businesses where this move will create investment costs. Looking across businesses, this effect is likely to be more intense at manufacturing companies, where moving production is more expensive and difficult to do, than at technology or service firms…

…While it is easy to blame market uncertainty on Trump, tariffs and trade wars for the moment, the truth is that the forces that have led us here have been building for years, both in our political and economic arenas. In short, even if the tariffs cease to be front page news, and the fears of an immediate trade war ease, the underlying forces of anti-globalization that gave rise to them will continue to play out in global commerce and markets. For investors, that will require a shift away from the large cap technology companies that have been the market leaders in the last two decades back to smaller cap companies with a more domestic focus.

2. Big Retailers’ Hardball Tariff Playbook: Haggle, Diversify, Raise Prices – Hannah Miao and Sarah Nassauer

Some suppliers say Walmart, Home Depot and other retailers are pushing a variation of the same demand: Make a price concession or shift production out of China. Otherwise, the suppliers risk losing some business…

…Some of the requests have raised the ire of Chinese officials. Authorities in China summoned Walmart for a meeting in recent days after some suppliers complained the largest U.S. retailer by annual revenue was pressuring them to cut prices and absorb the tariff cost…

…Some pricing negotiations are hitting an impasse because many of these manufacturers are often already operating on razor-thin margins, according to suppliers. And retailers don’t want to raise prices for shoppers so they can continue to compete for market share…

…After the first 10% tariff on Chinese goods in February, Home Depot asked one of its U.S. suppliers of lighting and home decor to absorb the cost, according to an executive at the supplier. The supplier agreed to a two-month, 10% discount, part of which would be covered by its Chinese manufacturer.

After the second 10% tariff in March, the supplier declined another request from Home Depot to lower prices again. Instead, the supplier is moving production to Southeast Asia so it can eventually charge the home-improvement retailer the original price, the executive said…

…The tariff planning is especially complicated because companies have little sense of which tariff threats will materialize and where new ones could emerge, retailers and suppliers say…

…In some cases, retailers and manufacturers have decided it is worth it to keep production in China to maintain quality. Costco, the warehouse chain, plans to continue selling patio furniture made in China—even at an elevated price—because it is higher quality than versions made in other countries, Costco executives said. Costco and its supplier will absorb some of the cost increase and pass some on to shoppers, they said.

3. An Interview with OpenAI CEO Sam Altman About Building a Consumer Tech Company – Ben Thompson and Sam Altman

What’s going to be more valuable in five years? A 1-billion daily active user destination site that doesn’t have to do customer acquisition, or the state-of-the-art model?

SA: The 1-billion user site I think.

Is that the case regardless, or is that augmented by the fact that it seems, at least at the GPT-4 level, I mean, I don’t know if you saw today LG just released a new model. There’s going to be a lot of, I don’t know, no comments about how good it is or not, but there’s a lot of state-of-the-art models.

SA: My favorite historical analog is the transistor for what AGI is going to be like. There’s going to be a lot of it, it’s going to diffuse into everything, it’s going to be cheap, it’s an emerging property of physics and it on its own will not be a differentiator.

What will be the differentiator?

SA: Where I think there’s strategic edges, there’s building the giant Internet company. I think that should be a combination of several different key services. There’s probably three or four things on the order of ChatGPT, and you’ll want to buy one bundled subscription of all of those. You’ll want to be able to sign in with your personal AI that’s gotten to know you over your life, over your years to other services and use it there. There will be, I think, amazing new kinds of devices that are optimized for how you use an AGI. There will be new kinds of web browsers, there’ll be that whole cluster, someone is just going to build the valuable products around AI. So that’s one thing.

There’s another thing, which is the inference stack, so how you make the cheapest, most abundant inference. Chips, data centers, energy, there’ll be some interesting financial engineering to do, there’s all of that.

And then the third thing is there will be just actually doing the best research and producing the best models. I think that is the triumvirate of value, but most models except the very, very leading edge, I think will commoditize pretty quickly.

So when Satya Nadella said models are getting commoditized, that OpenAI is a product company, that’s still a friendly statement, we’re still on the same team there?

SA: Yeah, I don’t know if it came across as a compliment to most listeners, I think he meant that as a compliment to us…

It doesn’t. But to that point, you just released a big API update, including access to the same computer use model that undergirds Operator, a selling point for GPT Pro. You also released the Responses API and I thought the most interesting part about the Responses API is you’re saying, “Look, we think this is much better than the Chat Completions API, but of course we’ll maintain that, because lots of people have built on that”. It’s sort of become the industry standard, everyone copied your API. At what point is this API stuff and having to maintain old ones and pushing out your features to the new ones turn into a distraction and a waste of resources when you have a Facebook-level opportunity in front of you?

SA: I really believe in this product suite thing I was just saying. I think that if we execute really well, five years from now, we have a handful of multi-billion user products, small handful and then we have this idea that you sign in with your OpenAI account to anybody else that wants to integrate the API, and you can take your bundle of credits and your customized model and everything else anywhere you want to go. And I think that’s a key part of us really being a great platform.

Well, but this is the tension Facebook ran into. It’s hard to be a platform and an Aggregator, to use my terms. I think mobile was great for Facebook because it forced them to give up on pretensions of being a platform. You couldn’t be a platform, you had to just embrace being a content network with ads. And ads are just more content and it actually forced them into a better strategic position.

SA: I don’t think we’ll be a platform in a way that an operating system is a platform. But I think in the same way that Google is not really a platform, but people use sign in with Google and people take their Google stuff around the web and that’s part of the Google experience, I think we’ll be a platform in that way…

From my perspective, when you talk about serving billions of users and being a consumer tech company. This means advertising. Do you disagree?

SA: I hope not. I’m not opposed. If there is a good reason to do it, I’m not dogmatic about this. But we have a great business selling subscriptions.

There’s still a long road to being profitable and making back all your money. And then the thing with advertising is it increases the breadth of your addressable market and increases the depth because you can increase your revenue per user and the advertiser foots the bill. You’re not running into any price elasticity issues, people just use it more.

SA: Currently, I am more excited to figure out how we can charge people a lot of money for a really great automated software engineer or other kind of agent than I am making some number of dimes with an advertising based model…

Especially Deep Research, it’s amazing. But I am maybe more skeptical about people’s willingness to go out and pay for something, even if the math is obvious, even if it makes them that much more productive. And meanwhile, I look at this bit where you’re talking about building memory. Part of what made the Google advertising model so brilliant is they didn’t actually need to understand users that much because people typed into the search bar what they were looking for. People are typing a tremendous amount of things into your chatbot. And even if you served the dumbest advertising ever, in many respects, and even if you can’t track conversions, your targeting capability is going to be out of this world. And, by the way, you don’t have an existing business model to worry about undercutting. My sense is this is so counter to what everyone at OpenAI signed up for, that’s the biggest hurdle. But to me, from a business analyst, this seems super obvious and you’re already late.

SA: The kind of thing I’d be much more excited to try than traditional ads is a lot of people use Deep Research for e-commerce, for example, and is there a way that we could come up with some sort of new model, which is we’re never going to take money to change placement or whatever, but if you buy something through Deep Research that you found, we’re going to charge like a 2% affiliate fee or something. That would be cool, I’d have no problem with that. And maybe there’s a tasteful way we can do ads, but I don’t know. I kind of just don’t like ads that much…

…SA: Totally. I think DeepSeek was — they made a great team and they made a great model, but the model capability was, I think, not the thing there that really got them the viral moment. But it was a lesson for us about when we leave a feature hidden, we left chains of thought hidden, we had good reasons for doing it, but it does mean we leave space for somebody else to have a viral moment. And I think in that way it was a good wake-up call. And also, I don’t know, it convinced me to really think differently about what we put in the free tier and now the free tier is going to get GPT-5 and that’s cool.

Ooo, ChatGPT-5 hint. Well, I’ll ask you more about that later

In your recent proposal about the AI Action Plan, OpenAI expressed concern about companies building on DeepSeek’s models, which are, in one of the phrases about them, “freely available”. Isn’t the solution, if that’s a real concern, to make your models freely available?

SA: Yeah, I think we should do that.

So when-

SA: I don’t have a launch to announce, but directionally, I think we should do that.

You said before, the one billion destination site is more valuable than the model. Should that flow all the way through to your release strategy and your thoughts about open sourcing?

SA: Stay tuned.

Okay, I’ll stay tuned. Fair enough.

SA: I’m not front-running, but stay tuned…

Is there a bit where isn’t hallucination good? You released a sample of a writing model, and it sort of tied into one of my longstanding takes that everyone is working really hard to make these probabilistic models behave like deterministic computing, and almost missing the magic, which is they’re actually making stuff up. That’s actually pretty incredible.

SA: 100%. If you want something deterministic, you should use a database. The cool thing here is that it can be creative and sometimes it doesn’t create quite the thing you wanted. And that’s okay, you click it again.

Is that an AI lab problem that they’re trying to do this? Or is that a user expectation problem? How can we get everyone to love hallucinations?

SA: Well, you want it to hallucinate when you want and not hallucinate when you don’t want. If you’re asking, “Tell me this fact about science,” you’d like that not to be a hallucination. If you’re like, “Write me a creative story,” you want some hallucination. And I think the problem, the interesting problem is how do you get models to hallucinate only when it benefits the user?…

I think some skeptics, including me, have framed some aspects of your calls for regulation as an attempt to pull up the ladder on would-be competitors. I’d ask a two-part question. Number one, is that unfair? And if the AI Action Plan did nothing other than institute a ban on state level AI restrictions and declare that training on copyright materials fair use, would that be sufficient?

SA: First of all, most of the regulation that we’ve ever called for has been just say on the very frontier models, whatever is the leading edge in the world, have some standard of safety testing for those models. Now, I think that’s good policy, but I sort of increasingly think the world, most of the world does not think that’s good policy, and I’m worried about regulatory capture. So obviously, I have my own beliefs, but it doesn’t look to me like we’re going to get that as policy in the world and I think that’s a little bit scary, but hopefully, we’ll find our way through as best as we can and probably it’ll be fine. Not that many people want to destroy the world.

But for sure, you don’t want to go put regulatory burden on the entire tech industry. Like we were calling for something that would have hit us and Google and a tiny number of other people. And again, I don’t think the world’s going to go that way and we’ll play on the field in front of us. But yes, I think saying that fair use is fair use and that states are not going to have this crazy complex set of differing regulations, those would be very, very good.

You are supporting export controls or by you, I mean, OpenAI in this policy paper. You talked about the whole stack, that triumvirate. Do you worry about a world where the US is dependent on Taiwan and China is not?

SA: I am worried about the Taiwan dependency, yes…

Okay, sure. Intel needs a customer. That’s what they need more than anything, a customer that is not Intel. Get OpenAI, become the leading customer for the Gaudi architecture, commit to buying a gazillion chips and that will help them. That will pull them through. There’s your answer.

SA: If we were making a chip with a partner that was working with Intel and a process that was compatible and we had, I think, a sufficiently high belief in their ability to deliver, we could do something like that. Again, I want to do something. So I’m not trying to dodge…

So Dario and Kevin Weil, I think, have both said or in various aspects that 99% of code authorship will be automated by sort of end of the year, a very fast timeframe. What do you think that fraction is today? When do you think we’ll pass 50% or have we already?

SA: I think in many companies, it’s probably past 50% now. But the big thing I think will come with agentic coding, which no one’s doing for real yet.

What’s the hangup there?

SA: Oh, we just need a little longer.

Is it a product problem or is it a model problem?

SA: Model problem.

Should you still be hiring software engineers? I think you have a lot of job listings.

SA: I mean, my basic assumption is that each software engineer will just do much, much more for a while. And then at some point, yeah, maybe we do need less software engineers…

What is AGI? And there’s a lot of definitions from you. There’s a lot of definitions in OpenAI. What is your current, what’s the state-of-the-art definition of AGI?

SA: I think what you just said is the key point, which is it’s a fuzzy boundary of a lot of stuff and it’s a term that I think has become almost completely devalued. Some people, by many people’s definition, we’d be there already, particularly if you could go like transport someone from 2020 to 2025 and show them what we’ve got.

Well, this was AI for many, many years. AI was always what we couldn’t do. As soon as we could do it, it’s machine learning. And as soon as you didn’t notice it, it was an algorithm.

SA: Right. I think for a lot of people, it’s something about like a fraction of the economic value. For a lot of people, it’s something about a general purpose thing. I think they can do a lot of things really well. For some people, it’s about something that doesn’t make any silly mistakes. For some people, it’s about something that’s capable of self-improvement, all those things. It’s just there’s not good alignment there.

What about an agent? What is an agent?

SA: Something that can like go autonomously, do a real chunk of work for you.

To me, that’s the AGI thing. That is employee replacement level.

SA: But what if it’s only good at like some class of tasks and can’t do others? I mean, some employees are like that too…

Given that, does that make you more optimistic, less optimistic? Do you see this bifurcation that I think there’s going to be between agentic people? This is a different agentic word, but see where we’re going. We need to invent more words here. We’ll ask ChatGPT to hallucinate one for us. People who will go and use the API and the whole Microsoft Copilot idea is you have someone accompanying you and it’s a lot of high talk, “Oh, it’s not going to replace jobs, it’s going to make people more productive”. And I agree that will happen for some people who go out to use it. But you look back, say, at PC history. The first wave of PCs were people who really wanted to use PCs. PCs, a lot of people didn’t. They had one put on their desk and they had to use it for a specific task. And really, you needed a generational change for people to just default to using that. Is AI, is that the real limiting factor here?

SA: Maybe, but that’s okay. Like as you mentioned, that’s kind of standard for other tech evolutions.

But you go back to the PC example, actually, the first wave of IT was like the mainframe, wiped out whole back rooms. And because actually, it turned out the first wave is the job replacement wave because it’s just easier to do a top-down implementation.

SA: My instinct is this one doesn’t quite go like that, but I think it’s always like super hard to predict.

What’s your instinct?

SA: That it kind of just seeps through the economy and mostly kind of like eats things little by little and then faster and faster.

You talk a lot about scientific breakthroughs as a reason to invest in AI, Dwarkesh Patel recently raised the point that there haven’t been any yet. Why not? Can AI actually create or discover something new? Are we over-indexing on models that just aren’t that good and that’s the real issue?

SA: Yeah, I think the models just aren’t smart enough yet. I don’t know. You hear people with Deep Research say like, “Okay, the model is not independently discovering new science, but it is helping me discover new science much faster.” And that, to me, is like pretty much as good.

Do you think a transformer-based architecture can ever truly create new things or is it just spitting out the median level of the Internet?

SA: Yes.

Well, what’s going to be the breakthrough there?

SA: I mean, I think we’re on the path. I think we just need to keep doing our thing. I think we’re like on the path…

Do humans have innate creativity or is it just recombining knowledge in different sorts of ways?

SA: One of my favorite books is The Beginning of Infinity by David Deutsch, and early on in that book, there’s a beautiful few pages about how creativity is just taking something you saw before and modifying it a little bit. And then if something good comes out of it, someone else modifies it a little bit and someone else modifies it a little bit. And I can sort of believe that. And if that’s the case, then AI is good at modifying things a little bit.

To what extent is the view that you could believe that grounded in your long-standing beliefs versus what you’ve observed, because I think this is a very interesting — not to get all sort of high-level metaphysical or feel, like I said, theological almost — but there does seem to be a bit where one’s base assumptions fuel one’s assumptions about AI’s possibilities. And then, most of Silicon Valley is materialistic, atheistic, however you want to put it. And so of course, we’ll figure it out, it’s just a biological function, we can recreate it in computers. If it turns out we never actually do create new things, but we augment humans creating new things, would that change your core belief system?

SA: It’s definitely part of my core belief system from before. None of this is anything new, but no, I would assume we just didn’t figure out the right AI architecture yet and at some point, we will.

4. The Last Decision by the World’s Leading Thinker on Decisions – Jason Zweig

Kahneman was widely mourned nearly a year ago when his death was announced. Only close friends and family knew, though, that it transpired at an assisted-suicide facility in Switzerland. Some are still struggling to come to terms with his decision…

…But I never got to say goodbye to Danny and don’t fully understand why he felt he had to go. His death raises profound questions: How did the world’s leading authority on decision-making make the ultimate decision? How closely did he follow his own precepts on how to make good choices? How does his decision fit into the growing debate over the downsides of extreme longevity? How much control do we, and should we, have over our own death?…

…I think Danny wanted, above all, to avoid a long decline, to go out on his terms, to own his own death. Maybe the principles of good decision-making that he had so long espoused—rely on data, don’t trust most intuitions, view the evidence in the broadest possible perspective—had little to do with his decision.

His friends and family say that Kahneman’s choice was purely personal; he didn’t endorse assisted suicide for anyone else and never wished to be viewed as advocating it for others.

Some of Kahneman’s friends think what he did was consistent with his own research. “Right to the end, he was a lot smarter than most of us,” says Philip Tetlock, a psychologist at the University of Pennsylvania. “But I am no mind reader. My best guess is he felt he was falling apart, cognitively and physically. And he really wanted to enjoy life and expected life to become decreasingly enjoyable. I suspect he worked out a hedonic calculus of when the burdens of life would begin to outweigh the benefits—and he probably foresaw a very steep decline in his early 90s.”

Tetlock adds, “I have never seen a better-planned death than the one Danny designed.”…

…As I wrote in a column about Kahneman last year: “I once showed him a letter I’d gotten from a reader telling me—correctly but rudely—that I was wrong about something. ‘Do you have any idea how lucky you are to have thousands of people who can tell you you’re wrong?’ Danny said.”…

…Kahneman knew the psychological importance of happy endings. In repeated experiments, he had demonstrated what he called the peak-end rule: Whether we remember an experience as pleasurable or painful doesn’t depend on how long it felt good or bad, but rather on the peak and ending intensity of those emotions.

“It was a matter of some consternation to Danny’s friends and family that he seemed to be enjoying life so much at the end,” says a friend. “‘Why stop now?’ we begged him. And though I still wish he had given us more time, it is the case that in following this carefully thought-out plan, Danny was able to create a happy ending to a 90-year life, in keeping with his peak-end rule. He could not have achieved this if he had let nature take its course.”

Did turning 90 play a role in his decision? Kahneman and Tversky’s early research showed that when people are uncertain, they will estimate numbers by “anchoring,” or seizing on any figure that happens to be handy, regardless of how relevant it is to the decision.

Another of Kahneman’s principles was the importance of taking what he called the outside view: Instead of regarding each decision as a special case, you should instead consider it as a member of a class of similar situations. Gather data on comparable examples from that reference class, then consider why your particular case might have better or worse prospects.

One possible approach: Kahneman could have gathered data to determine whether people who live to the age of 95 or beyond tend to regret not dying at the age of 90—adjusting for the difficulty of getting reliable reports from patients with dementia and other debilitating conditions. Perhaps he did something along those lines; I don’t know…

…As Danny’s final email continued:

I discovered after making the decision that I am not afraid of not existing, and that I think of death as going to sleep and not waking up. The last period has truly not been hard, except for witnessing the pain I caused others. So if you were inclined to be sorry for me, don’t be.

As death approaches, should we make the best of whatever time we have left with those we love the most? Or should we spare them, and ourselves, from as much as possible of our inevitable decline? Is our death ours alone to own?

Danny taught me the importance of saying “I don’t know.” And I don’t know the answers to those questions. I do know the final words of his final email sound right, yet somehow feel wrong:

Thank you for helping make my life a good one.

5. Dead of Winter – Doomberg

After a somewhat colder-than-average winter and the cessation of gas flows through the very Sudzha pipeline that Russian special forces just snaked through for their surprise assault, European natural gas storage levels are at dangerously low levels for this time of year:…

…The last energy crisis began many months before Russia’s military crossed into Ukraine. Europe’s vulnerability—driven by a foolish decision to forgo topping off its reserves in the summer of 2021—almost certainly convinced Russian President Vladimir Putin that he held sufficient leverage to risk war in early 2022. Three years later, with the conflict seemingly entering its final stages, surely the continent isn’t repeating the mistakes of the recent past? Perhaps it is:

“As the first proper winter in Europe in three years is drawing to an end, the continent faces a race against time—and prices—to restock with natural gas for next winter…

Europe could need as many as 250 additional [liquefied natural gas] LNG cargoes to arrive in the summer to refill its inventories back up to 90% by November 1, as the current EU regulation stipulates, per Reuters calculations reported by columnist Ron Bousso… The LNG market appears to be tightening, with supply not rising fast enough in early 2025 to meet demand.”…

…Europe’s vulnerability is now measurably higher compared to three years ago. Russian natural gas no longer flows through the Nord Stream and Yamal pipelines, nor various connections through Ukraine, eliminating access to a total capacity of 18 billion cubic feet per day (bcf/d). Only the two pipelines entering Turkey via the Black Sea—TurkStream and Blue Stream—are still pumping gas. The balance of European demand will need to be met by expensive LNG imports, primarily from the US and Qatar.

Unfortunately for Europe, the LNG market has been facing challenges just as the continent appears poised to rely on it more than ever…

…Despite these many delays, some relief is in sight for 2025 with two major LNG expansions activating in the US. Cheniere’s Corpus Christi Stage 3 expansion produced its first cargo in February, adding 1.3 bcf/d of capacity. The first phase of Plaquemines LNG—built by the controversial firm Venture Global and itself a 1.3bcf/d facility—is in the commissioning process, a milestone celebrated last week by Chris Wright, Trump’s new Secretary of Energy…

…The one event that could significantly disrupt energy markets and pose a serious challenge to Brussels would be a major terrorist attack on European infrastructure. For example, if either of the large pipelines passing through Turkey were taken offline, prices would likely spike sharply. The loss of a large LNG import terminal, such as those in Spain or France, would also create severe strain. When operating on the edge, even small disturbances can knock the system out of equilibrium.

While Europe is playing an extremely risky game, absent the edge cases, it is likely to muddle through the next year without a full-blown disaster.


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