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What The USA’s Largest Bank Thinks About The State Of The Country’s Economy In Q1 2026

Insights from JPMorgan Chase’s management on the health of American consumers and businesses in the first quarter of 2026.

JPMorgan Chase (NYSE: JPM) is currently the largest bank in the USA by total assets. Because of this status, it is naturally able to feel the pulse of the country’s economy. The bank’s latest earnings conference call – for the first quarter of 2026 – was held earlier this week and contained useful insights on the state of American consumers and businesses. The bottom-line is this: the US economy remains resilient, but the risks are growing in complexity.

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 remained resilient in 2026 Q1; consumers and businesses continue to spend; there are multiple tailwinds supporting the economy’s resilience, but the risks to the economy are growing in complexity; consumer spending growth in 2026 Q1 is faster compared to a year ago; energy is just 3% of the typical consumer’s expenditure, so they are not significantly affected by higher energy prices; the strength of the American consumer is the result of a strong labour market, so if the labour market were to weaken for any reason, the American consumer will also weaken

The U.S. economy remained resilient in the quarter, with consumers still earning and spending and businesses still healthy. Several tailwinds are supporting this resiliency, including increased fiscal stimulus, the benefits of deregulation, AI-driven capital investment and the Fed’s asset purchases. At the same time, there is an increasingly complex set of risks— such as geopolitical tensions and wars, energy price volatility, trade uncertainty, large global fiscal deficits and elevated asset prices. While we cannot predict how these risks and uncertainties will ultimately play out, they are significant and they reinforce why we prepare the Firm for a wide range of environments…

…Notwithstanding the recent volatility in market and gas prices based on our data, consumers and small businesses remain resilient with consumer spend growth continuing above last year’s pace…

…[Question] How resilient is consumer spend and credit if energy prices remain high? And are there any signs of cracks that you’re seeing at all?

[Answer] There really is not anything new or interesting to say this quarter. We’ve looked at it through every angle. Early roll rates, delinquency rates, cash buffer, spend, discretionary spend, non-discretionary spend, it all looks consistent with prior trends and fundamentally, healthy. So let me add maybe just a little bit of nuance in the context of energy prices and what’s going on this quarter. So I think gas or energy cost is something like 3% of the typical consumer’s expenditure, at least in our portfolio. So it’s not nothing, but it’s not overwhelming. We’ve looked to see if there’s kind of evidence in there of people trading, decreasing other discretionary spending to adjust for higher gas prices, but it’s just kind of not enough yet to be visible.

I would caution, though, I think it remains fundamentally the case that the biggest single reason that the consumer credit performance is healthy is that the labor market is strong. And if you get bad outcomes in the Middle East, much higher energy prices or other problems that sort of do eventually track what has been, I think, from many people’s perspective, a surprisingly resilient American economy and a very resilient U.S. consumer, and that winds up having knock-on effects on the labor market, then you will see that come through, clearly. But right now, in the end, the story remains the same, which is resilient consumer that’s doing fine despite higher gas prices.

2. Net charge-offs for the whole bank (effectively bad loans that JPMorgan can’t recover) was flat at US$2.3 billion compared to a year ago

Credit costs of $2.5 billion with net charge-offs of $2.3 billion and a net reserve build of $191 million.

3. Management thinks there has been no recent changes in real-world systemic risk

It’s important to understand that under the current rule, the surcharges for almost all of the G-SIB banks are scheduled to increase meaningfully over the next 2 years, simply as a result of recent growth in the system despite, in our view, no change in real-world systemic risk.

4. Mortgage loan originations had strong growth in 2026 Q1, driven by refinancing of mortgages 

In Home Lending, originations of $13.7 billion increased 46% year-on-year predominantly driven by refi performance.

5. JPMorgan’s investment banking fees were up 28% in 2026 Q1 from a year ago because of strong performance in mergers & acquisitions (M&A) and equity underwriting; management sees a strong pipeline for capital markets activities, barring significant deterioration in the ongoing Middle Eastern conflict; the sentiment of companies for capital markets activities has been surprisingly resilient

IB fees were up 28% year-on-year, driven by strong performance across M&A and equity underwriting, partially offset by lower debt underwriting. Looking ahead, client engagement and pipelines remain healthy, but of course, developments in the Middle East could have an impact on deal execution and timing…

…On the question of overall sentiment on the pipeline, I would describe it as resilient, maybe surprisingly resilient, given everything that’s going on. But I also think the time lines in the Middle East are kind of quite short. There are deadlines or negotiations. I think it’s reasonable for people to kind of proceed with their plans in the hope or maybe expectation that we get relatively quick resolutions. But if things start getting derailed, I would be surprised if you don’t see some impact on sentiment and on deal decision-making. But for right now, it seems quite resilient.

6. Management continues to expect credit card net charge-offs for 2026 to be 3.4% (was around 3.3% in 2025); management expects JPMorgan’s credit card loans to grow 6% in 2026

The adjusted expense outlook continues to be about $105 billion and the Card net charge-off rate continues to be approximately 3.4%…

…What we said about Card loan growth expectations at Company Update, which is that we said we expected 6% or maybe a little bit more, and that hasn’t really changed. That’s still kind of our core expectation. 

7. Management thinks that there will not be systemic issues for banks even if the private credit industry experiences a default cycle because the private credit industry is still relatively small compared to the overall loans market banks are participating in; the credit quality within private credit portfolios has not gotten much worse

[Question] do you think that if we do have a default cycle in private credit, that it will be systemic?

[Answer] Private credit leverage lending is like $1.7 trillion, high-yield bonds are something like $1.7 trillion, bank syndicated leveraged loans are like $1.7 trillion, investment-grade debt is $13 trillion, mortgage debt is like $13 trillion, and there’s a lot of other stuff out there. And I pointed out that I think there’s been some weakening in underwriting and not just by private credit elsewhere. And there will be a credit cycle one day. And I think when there’s a credit cycle, losses will be worse than people expect relative to the scenario. I don’t think it’s systemic. It almost can’t be systemic at that size relative to anything else. But when recessions happen and values go down and people refi at higher rates, there will be stress and strain in the system. Are people prepared for that? I can’t speak for other banks, but these are — most of these things are on top of — you have to have very large losses in private credit before at least it looks like banks are going to get hit or something like that. So it doesn’t mean you won’t feel some stress and strain, and that you might have to do something about it, but I’m not particularly worried about it…

…We always had what we call marking rights to look at the underlying collateral, and that’s just a right that protects you and gives you certain rights, things like that. Obviously, if you ever see credit getting worse, and it’s gotten not terribly worse, the actual credit which a lot of these private equity — private credit guys are pointing out, the actual credit hasn’t gotten that much worse. There are pockets where it has. And credit spreads themselves haven’t gotten much worse in general, but there are pockets where it has. So we’ll be watching it closely. We think we’re okay on all of that.

8. Management thinks corporate and consumer debt are not too high, whereas government debt is high

Corporations in general, the debt is not too high. Consumers, in general, the debt is not too high. Most of the excess debt is in government debt at this point. 


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 12 April 2026)

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 12 April 2026:

1. America’s AI Build-Out Hinges on Chinese Electrical Parts – Emily Forgash and Akshat Rathi

Almost half of the US data centers planned for this year are expected to be delayed or canceled. One big reason is the shortage of electrical equipment, such as transformers, switchgear and batteries. They are needed not just for powering AI, but also for building out the grid that is seeing increased consumption from electric cars and heat pumps. US manufacturing capacity for these devices cannot keep up with demand, and the scarcity has caused data center builders to rely on imports…

…Data centers consuming as much as 12 gigawatts of power are supposed to come online in 2026 in the US, according to analysts at market intelligence firm Sightline Climate, who will be releasing a new report in the coming weeks. However, only a third of that is currently under construction, Sightline estimates…

…Electrical infrastructure adds up to less than 10% of the total cost of the data center, but it’s impossible to build the operation without it. “If one piece of your supply chain is delayed, then your whole project can’t deliver,” says Andrew Likens, Crusoe’s energy and infrastructure lead. “It is a pretty wild puzzle at the moment.”…

…Though few companies are eager to talk about it, the US has been outsourcing its manufacturing to other countries, primarily China, for decades. That has contributed to a significant shortage of electrical components in the US, says WoodMac’s Boucher…

…While most of the US’s transformers come from Canada, Mexico and South Korea, US utilities imported more than 8,000 high-power transformers in 2025 through October from China, up from fewer than 1,500 imported in all of 2022, estimates WoodMac’s Boucher. This build-out “is going to be highly dependent on the import market,” he says.

Once transformers lower the voltage of electricity so it can be used in data centers, it then needs to be distributed across the data center safely. That’s done through switchgear, which includes circuit breakers and fuses. There too, data center developers are seeing delivery delays – though not as extreme as the timelines for transformers.

Equinix Inc.’s solution is to commit at least $350 million to support Hanley Energy’s new manufacturing facility in Ireland, which will make switchgear and other data center components. Equinix expects to achieve 10% to 15% faster lead times as a result.

Crusoe’s answer to that shortfall has been to pre-order lots of the equipment. That means spending many millions of dollars on supplies before the company even knows it has an order to fill, but it’s proved a winning strategy. Recently, Crusoe also began manufacturing their own switchgear…

…The share of US imports of transformers and switchgear from China has declined steadily in recent years – although for specific types of equipment that share is still hovering around 30%. The Chinese share of battery import volumes remains stubbornly above 40%.

China dominates the supply of electrical equipment because it controls so many parts of the supply chain, from materials to processing to manufacturing, and the gulf between China and the US is set to widen. In its new five-year plan, the Asian giant revealed last month that it will double down on building out its grid with renewables, while the Trump administration has dismantled policies to deploy solar and wind power.

2. “Founder Mode” Complacency – Abdullah Al-Rezwan

When DeepMind was plotting to extricate themselves from Alphabet almost a decade ago, Pichai was prescient enough to foresee AI’s paramount importance in their core business…

…As these negotiations became more tense over time, all the big guns of Alphabet planned to meet to resolve the issue at hand. Alas, some big guns didn’t seem to appreciate what was at stake. From the book:

When the two sides met again, the conversation underscored the gulf between them. Hassabis and Suleyman argued that DeepMind did not fit under Google’s umbrella: Its mission was AGI, not consumer‑internet products. Pichai objected that AI was central to his vision for Google, and that he would not allow his scientific bench to be depleted. Hassabis had hoped that Larry Page would weigh in on his side and push the Alphabet plan to a conclusion. But Page showed up for the meeting two hours late, and Sergey Brin was even later. Their version of what later came to be known as “founder mode” was that they were nowhere to be found, disproving the Silicon Valley mantra that founders deserve the right to control their companies indefinitely. With Page and Brin effectively checked out, Pichai was the man DeepMind had to deal with.

I have been thinking about the aforementioned excerpt for the last couple of days. If you glanced at my portfolio, it’s not difficult to see that I drank my fair share of kool-aid of “founder mode”. Perhaps fittingly the “founder mode” propaganda originated from a founder himself: Brian Chesky. The more I ruminated over “founder mode”, the more I came to the conclusion that there is a glaring missing aspect in “founder mode” mantra: Complacency.

It is telling that Chesky proudly recalls every chance he gets about how he figured out during Covid that Airbnb doesn’t need to do search advertising; as an investor I was actually a bit alarmed that he was running Airbnb pre-pandemic without paying close attention whether his advertising dollars was being deployed with appropriate ROAS guardrail. I can guarantee you that despite operating in “Manager Mode”, Glenn Fogel at Booking was looking at advertising ROI with a microscope and he certainly didn’t need a global pandemic to remind him how to deploy his precious advertising dollars at Booking.

3. A token is not a fixed unit of cost – Anjali Shrivastava

We only consider token count as the static linear meter because we inherited the logic from inference APIs. But, a token does not represent a fixed unit of work.

This is obvious to anyone who works in inference, but if you’re used to calculating compute budgets based on linear API rates, it takes a second to sink in.

The intuition is grounded in the autoregressive nature of the transformer: Attention is quadratic with respect to current context size…

…In layman’s terms, the language model is looking at every previous token in the context window before generating a new token, which means inference APIs are linearly pricing fresh tokens whose compute cost scales quadratically.

The scaling law for compute is likely not purely quadratic, given optimizations like caching and compacting context. But no matter what, the underlying compute cost per token grows with context length. The Nth token in a conversation is an order of magnitude more expensive than the first.

There’s signs that per-token pricing breaks down at scale: both Anthropic and Google charge different rates based on prompt length…

…Traditional SaaS has variable costs too (like hosting, customer support and third-party service costs). But these costs follow the law of large numbers, and are normally distributed at scale. You can set a single subscription price that covers this average cost, plus a comfortable margin to absorb tail risk.

In the case of AI software, it is likely that these variable costs are fat tailed. The law of large numbers assumes finite mean and i.i.d. samples, but AI software has at least one dimension with infinite first moment and non-stationary tails. The sample mean keeps wandering instead of converging…

…Margin collapse is the first and most obvious symptom of the problem. Cursor’s repricing exposed poor margins, and we also learned that Replit’s margins are volatile. And there is ample evidence that Anthropic is losing money on its subscriptions.

Each layer of the aggregate cost curve is highly variable, and the more you scale, the higher the probability that these tail risks can compound…

…Subscriptions misprice intelligence, and much of the industry recognizes this, but now we can rigorously explain why.

Traditional SaaS pricing mirrors the physics of stable software, but AI introduces high variance that breaks each of these laws…

…High variance in costs necessarily constrains demand; today, the constraints are reactive.

To safely cushion from unbounded costs, a business model must price in the variance or be well above the true cost on average. Ideally by anchoring price to value delivered instead of token cost; but value delivered also happens to be highly variable and subjective. At the same time, there’s structure to value: reliability, relevance, actionability.

The key insight is that margin squeeze and resource misallocation are two sides of the same problem. Solving one side of the equation should solve the other. If you can measure the value delivered, you can price that instead of raw compute. And if you can price outcomes in terms of value delivered, you can budget the exact amount of compute and data that maximizes profit on each task.

So the layer that owns the meter also decides how much compute and data to deploy and keeps the spread between cost and price. Today that meter sits inside the model; tomorrow it could sit inside an orchestrator that plans the whole workflow.

4. Why You Should Wait Out AI’s Super-Spending False Start – Merryn Somerset Webb

The second part, the data on which all LLMs are trained, is not. Its supply is limited. Up to ChatGPT4, the internet provided enough data for each new iteration to be better. But that version was completed a few years ago, trained on the lot. There is little more for new models to train on.

The data on the internet might have expanded over the last few years, but not in a particularly helpful way. Much of it has been produced by other LLMs: train your new model on that and you might end up degrading it. Why? Because LLMs are horribly prone to errors (confabulations or hallucinations), which means they can’t give us what we most need from them: accuracy.

An LLM is not a continuous learning machine. Its knowledge stops with its training. It also isn’t deterministic (like, say, a calculator), says AI expert Janusz Marecki (who I interviewed for a podcast this week). It knows nothing with certainty. It simply “rolls the dice” on what the next word in a series should be, giving you its best guess. The answer you get is an approximation, not a series of facts. Worse, the more complicated the task in hand, the more the errors compound. Possibly even worse, the LLM can’t tell you how likely it is that there are errors. How would it know?

These problems aren’t going to go away. They are irredeemable systemic flaws in the product.

5. Switzerland – Europe’s overlooked activist opportunity – Swen Lorenz

Switzerland is famously conservative and generally averse to outsiders telling it what to do.

This is also reflected in its corporate landscape.

Even though the country is broadly open to foreign investment, there have long been numerous mechanisms allowing companies to keep outside influence under tight control.

Some Swiss companies require shareholders to be registered by name, with board approval needed for new registrations. This has led to cases where outsiders were refused registration – and “outsiders” can even include Swiss citizens from a different region.

Other companies cap voting rights per shareholder or maintain super-voting shares that remain tightly held by local incumbents…

…The 2023 reform of Swiss corporate law wasn’t widely noticed, not least because attention was focused on events in Ukraine and the aftermath of the pandemic.

Until then, a shareholder needed to represent 10% of share capital to add an agenda item for a vote at the annual general meeting.

For publicly listed companies, this threshold has now been reduced to just 0.5% – a far more attainable level.

Similarly, a shareholder with 5% can now requisition a shareholders’ meeting, compared to 10% previously.

Just as importantly, the broader acceptance of active shareholders has evolved…

…Finanz und Wirtschaft, Switzerland’s leading German-language business daily, carries significant influence among corporate executives. In an article published on 18 September 2025, the paper noted how “activist investors are transforming from bogeyman to catalyst”…

…Patrick Fournier is an active investor based in Zug. We met several years ago at his family home to discuss our shared interest in frontier markets.

Today, his focus has shifted closer to home.

He allowed me to share the following:

“We have progressively sold all our portfolio of foreign shares and are now focusing on Swiss small & mid cap. We see huge value opportunities on this segment. We intend to become a little ‘activist’ as it is now possible with only 0.5% of capital in a listed company (far lower than the previous 10%) to add some proposition at the agenda of the annual general meeting of shareholders. This will wake up the Board of several companies, including regarding the dividend (payout) policy. As a result, we are in front of a ‘rerating’ (multiple expansion) of this segment.”…

…BVZ held its annual general meeting on 8 April 2026, and the results were telling.

Some 287 shareholders attended, representing 110,328 out of 197,278 shares outstanding (with one shareholder alone holding 56,000 shares). Alarick’s proposal to increase the dividend from CHF 18 to CHF 50 received 14.5% support and was rejected by 83.8%. As a result, the board’s proposal to raise the dividend from CHF 16 to CHF 18 was approved. With earnings per share of CHF 151, this implies a payout ratio below 20%. The proposal to initiate a share buyback programme received 16.67% support and was rejected by 82%, and therefore did not pass.

What may sound like a defeat is, in fact, the equivalent of an earthquake. In Switzerland’s highly consensus-driven corporate culture, such a level of shareholder dissent represents a clear wake-up call for management.

The market agreed. On the day of the meeting, the share price closed at an all-time high of CHF 1,550, up 67% over the past 12 months.

As the recent share price performance suggests, even raising one’s voice in a constructive manner can create value for shareholders in Swiss companies.


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. Holdings are subject to change at any time.

What The CEO of The USA’s Largest Bank Thinks About The World Today

Jamie Dimon’s latest excellent letter.

JPMorgan Chase (NYSE: JPM) is currently the largest bank in the USA by total assets. Its CEO, Jamie Dimon, is known for writing lengthy annual shareholder letters in which he pontificates about the state of the world and the banking industry. 

His latest letter was released earlier this week. I read it in earnest, taking extensive notes that I thought will be useful to share. So here they are! (The italicised passages between the two horizontal lines below are direct quotes from Dimon’s letter.)


1. Asset prices look fully valued

And we also continue to buy back enough stock so as not to increase total excess capital, though we have a number of options on how to deploy our capital and are clear-eyed that many asset prices, including bank stocks, are fully valued.

2. Current banking regulations have had some good effects, but have also made the banking system weaker by creating risks, including the creation of conditions that led to the Silicon Valley Bank crisis in 2023, and the risk of moral hazard in bank runs

A properly regulated banking system helps reduce risk to the financial system, protect customers, and maximize productive use of capital and lending. The Dodd-Frank Wall Street Reform and Consumer Protection Act and some of the rules that followed that legislation accomplished some good things. At the same time, they also created a fragmented, slow-moving system with expensive, overlapping and excessive rules and regulations — some of which made the financial system weaker and reduced productive lending…

…Here are some of the negative consequences partially due to poor bank regulations.

  • Because capital requirements on banks are much higher than the market gives to private entities, insurance companies or even foreign banks, huge arbitrage is created. This is often a sign of potential risk.
  • Regulators wrongly incorporated an accounting concept called “held to maturity” (HTM) into the capital rules, thereby giving Treasury and mortgage securities better capital treatment because the holder has promised not to sell them. This had many negative consequences — it allowed banks to not recognize mark-to-market losses on those securities in their regulatory capital, and in some cases, it falsely increased returns on those securities (because the amount of regulatory capital needed to be held against them was significantly smaller). This inadvertently encouraged banks to take on more interest rate risk, which was the ultimate trigger for the failure of Silicon Valley Bank (SVB) and First Republic Bank (FRB).
  • The Fed’s Comprehensive Capital Analysis and Review (CCAR) stress test, as currently constructed, produces results that are far worse, in our strongly held opinion, than what our actual results would be under those severely adverse conditions. The process is flawed, including reliance on inaccurate models and assumptions and the fact that it tests only one type of crisis, so other scenarios are overlooked (e.g., rapid rises in interest rates, as in the case of SVB and FRB). Testing should use accurate numbers and assumptions — then the results are what they are — rather than being driven by predetermined “what-ifs.” More transparency and sound methodology would lead to continuous improvement, not gaming the system. Essentially, we do not use CCAR to manage risk — we look at far more scenarios and need to be prepared for all of them. We also look at these risks every week, not just once a year…

…One of the huge risks for a bank has always been a “run on the bank,” which occurs when people think that their uninsured deposits are at risk. The FDIC only covers insured deposits, and the run risk is driven by uninsured deposits, particularly nonoperating uninsured deposits. In recent bank failures, regulators have had to invoke the systemic risk exception (SRE) to protect uninsured deposits at the point of failure. That is a problem — no one should want this as an emergency mechanism. It creates moral hazard, and the process to invoke the SRE is chaotic and involves multiple agencies, including approval by the Treasury Secretary in consultation with the President. Bank runs can happen quickly, and relying on that type of action to avoid contagion is simply not a good idea.

3. Real banking risks are always about credit, liquidity, interest rate, and operations

The real risks almost always end up being credit, liquidity, interest rate or operational risk.

4. Ideas to reduce actual risks in the banking industry through regulations include placing limits on the amount of HTM (held-to-maturity) assets banks can hold, requiring banks to have more liquidity to pay off uninsured deposits, and putting limits on the percentage loss on uninsured depots in the event of a bank failure

Here are some ideas that I believe would not only significantly reduce the chances that the SRE would need to be invoked but would also make the system safer and avoid moral hazard.

  • I would limit the amount of HTM securities in a way that links to the total long-term debt that the bank must have available to absorb losses upon its failure. And while this is a judgment call, banks need to realize that when available-for-sale and HTM security losses start to exceed 50% of tangible equity, investors will get worried…
  • …Prior to failure — between the Fed window and the rather quick sale or financing of securities or other assets — banks should be in a position where they have enough liquidity to pay off more than 50% of uninsured, nonoperating deposits. Regulators floated a similar idea in 2024, and I agree with them. This plan, plus the fact that equity and long-term debt will absorb losses before uninsured deposits are at risk, would give customers far greater peace of mind.
  • We should also consider simply setting, upfront, a statutory cap on the percentage loss on uninsured deposits in the event of failure — say, at 5%. This would reduce moral hazard and create an additional buffer for the FDIC to achieve a smooth resolution without using the SRE. With this plan, a small portion of the uninsured deposits would be immediately available to cover losses and communicated to depositors in “peacetime” while the bulk of uninsured deposits would be protected in a resolution. Although some might argue that a mechanism like this might increase the risk of a bank run, I think if the percentage is well-chosen, it might actually be stabilizing by eliminating the uninsured depositor’s nightmare scenario of losing all their money. In the end, all debates about the best way to proceed revolve around how much shareholders, creditors and uninsured depositors of the failing bank should pay and how much healthy banks should pay. As I already said, it has never been the taxpayer. And perhaps capping the maximum loss on uninsured deposits upfront would put an end to ad hoc involvement by the government once and for all.

5. AI is transformational, will have tremendous positive impacts on society, and is not a speculative bubble, but AI will also create serious new risks, including job displacement; AI will also have second- and third-order effects

The importance of AI is real — and while I hesitate to use the word transformational — it is. The pace of adoption will likely be far faster than prior technological transformations, like electricity or the internet. Those took decades to roll out, but this implementation looks likely to accelerate over the next few years. Our Chief Operating Officer describes our efforts in more detail, but I want to make some key points here.

  • We will not put our heads in the sand. We will deploy AI, as we deploy all technology, to do a better job for our customers (and employees).
  • AI will affect virtually every function, application and process in the company. And in the long run, it will have a huge positive impact on productivity. I do not think it is an exaggeration to say that AI will cure some cancers, create new composites and reduce accidental deaths, among other positive outcomes. It will eventually reduce the workweek in the developed world. And people will live longer and safer.
  • We do not yet know exactly how AI will unfold. The landscape will change rapidly, with shifting assumptions about power consumption, costs, chip technologies and the speed at which data centers are deployed. There will be a wide variety of AI models — open and closed, large and small — and no single tool will dominate. Overall, the investment in AI is not a speculative bubble; rather, it will deliver significant benefits. However, at this time, we cannot predict the ultimate winners and losers in AI- related industries.
  • AI is a genuine technological shift that will impact many sectors, including physical industries and scientific research. AI is only beginning to be applied broadly in science, and its influence will continue to expand.
  • AI will also introduce serious new risks — from deepfakes and misinformation to cybersecurity vulnerabilities. These risks are real, but they are manageable if companies, regulators and governments prepare. The worst mistakes we can make are predictable: overreact at the first serious incident and regulate out important innovation or underreact and fail to learn from what went wrong. The right approach requires rigorous preparation in advance, an honest assessment when things go wrong — and they will — and discipline to fix what’s broken without destroying what works.
  • AI will definitely eliminate some jobs, while it enhances others. Our firm will have definitive plans on how we can support and redeploy our affected workforce.
  • AI will create many jobs — some we can see today in cybersecurity and AI itself, and some we can’t see. But we do know that there is a huge workforce shortage for many well-paying white- and blue-collar jobs.
  • There is a possibility that AI deployment will move faster than workforce adaptation to new job creation. In prior technological transformations, labor had time to adjust and retrain. We do believe that business and government can do many things to properly incent retraining, income assistance, reskilling, early retirement and relocation for those whose job might be adversely impacted by AI (I talk about some of these ideas in Section IV around work skills training and the Earned Income Tax Credit).

One last but important point: We have focused on some of the “known and predictable” and some of the “known unknown” events. But huge technological shifts like AI always have second- and third-order effects as well that can deeply impact society. Some of these are, for example, cars bringing about the development of suburbs and shopping malls; agriculture enabling cities; and the original internet (invented back in 1969) leading to mobile phones, apps and social media. We should be monitoring for this kind of transformation, too.

6. Small teams are required to execute with speed

It’s essential to organize in small teams for super speed.

The real competitive battles are fought at the detailed segment level: It’s not just investment banking or the investment banking healthcare sector; it’s having the right team to win in healthcare pharma or medical devices. It’s not just credit card or even affluent brands; it’s the Chase Sapphire® card. It’s not small business clients in branches; it’s restaurateurs or law firms. It’s not digital payments; it’s 24/7 digital payments with automatic currency conversions. It’s hundreds of small teams (including technology, AI, marketing, subject matter experts and others) attacking specific problems. The teams needed to tackle these challenges should be small and authorized with the decision-making ability to move and act like Navy SEALs or the Army’s Delta Force. Finally, they need to be dedicated to the task at hand. Very often when a management team wants to accomplish something new, like create a digital account opening process that cuts across virtually every area, everyone on the team says, “We’ll get it done,” meaning they will add it to the long list of tasks already on their plate. But when efforts are 1% of a lot of people’s jobs, it will never get done. You need a team 100% dedicated to the mission — and everyone else supports them.

7. The global and US economy is very different today compared to 20 years ago in terms of (1) the importance of energy, (2) the size of the financial markets, (3) the composition of the players in the financial markets, (4) the size of investment portfolios, (5) the composition of holders of US Treasuries, and (6) central bank activity

It’s helpful to recognize that the world’s economy is far larger and more diversified and far less reliant on energy as an input versus 20 years ago. Global energy consumption to the global gross domestic product (GDP) is only about 40% of what it was around 45 years ago, say in the early 1980s, and the United States, instead of being a major importer on a net basis, is now a major exporter…

…If you look at the tables below, there are a few items that are truly different now from what they were in 2010, and these may well lead to different and unexpected outcomes. To name a few: The global debt and equity markets are far bigger than before (as are global deficits). Many nonbank financial institutions and investors are dramatically bigger than they were in the past (think hedge funds, private equity funds, sovereign wealth funds, among others). Global foreign portfolio investments are far bigger than before, and a large stock of U.S. Treasuries owned by foreigners is not held by central banks (central banks are less likely to make dramatic changes in their holdings of U.S. Treasuries). In addition, global QE is far bigger than it ever was before. A change in sentiment could easily affect the global flow of investments into securities, including U.S. Treasuries. You can also see that brokerage inventories are far smaller as a percentage of investments than ever before and, as a result, market makers are less able to intermediate in extremely volatile markets.

8. The US remains the world’s best investment destination; the US must continue to be the premier military force globally, maintain its economic position, and manage its foreign economic affairs, in order to remain strong

It is also good to remember that the United States remains the world’s best investment destination, particularly when things are going badly…

…There are three critical issues that will ultimately determine the health and safety of the United States and possibly determine the future direction and strength of the free and democratic world. JPMorganChase and its employees — like all other businesses and individuals — will be deeply affected over time by how the United States succeeds in these areas:

  1. The United States must maintain the premier military force in the world.
  2. The United States must maintain its preeminent economic position in the world, which also requires reigniting the American Dream.
  3. The United States must manage its foreign economic affairs to strengthen the U.S. economy and that of our critical allies so that the first two points remain true.

9. Inflation is a risk to the US and global economy in 2026; other large risks to watch include (1) Russia’s ongoing war with Ukraine, and the US and Israel’s ongoing war with Iran, (2) high sovereign deficits and debt, (3) high asset prices and low credit spreads, (4) new trade arrangements, (5) the relationship between the US and China, (6) private credit, (7) lengthy holding periods of private equity investments, and (8) cybersecurity; losses on leveraged lending could be higher than most expect when a credit cycle happens

The skunk at the party — and it could happen in 2026 — would be inflation slowly going up, as opposed to slowly going down. This alone could cause interest rates to rise and asset prices to drop. Interest rates are like gravity to almost all asset prices. And falling asset prices at one point can change sentiment rapidly and cause a flight to cash…

…I think some of the larger risks are much like tectonic plates, always moving and periodically causing earthquakes and volcanoes when they crash into each other. Some of the larger risks we should keep our eyes on are:

  • First and foremost, geopolitics. Russia’s war in Ukraine and its ongoing sabotage in Europe and now the war in Iran and its potential effects on energy prices can cause events that are unpredictable. We all hope these wars get properly resolved. But war is the realm of uncertainty, as each side in a war determines what it wants to do (as is often said, “the enemy gets a vote”), and these conflicts involve many countries. Not only do they have a major impact on the nations at war, but they also have an impact on countries and economies across the globe that are not directly involved in war. Nations that are heavily dependent upon imported energy are already seeing the effects. And it’s not just energy, it’s commodity products that are byproducts of oil and gas, like fertilizer and helium. And given our complex global supply chains, countries are experiencing disruptions in shipbuilding, food and farming, among others. The outcome of current geopolitical events may very well be the defining factor in how the future global economic order unfolds — then again, it may not.
  • High global sovereign deficits and debt. Global deficits are significantly elevated, particularly during what has been a relatively healthy global economy and, until recently, a time of peace — the deficit globally is at an extremely high 5%, while global sovereign debt is at all-time highs. The current forecast from the Congressional Budget Office has our debt-to-GDP ratio going from 100% today to 120% in 2036. High government debt is somewhat offset by low consumer debt, which was nearly 100% of GDP in 2007 and is now below 70%. Similarly, corporate debt is at a fairly normal healthy level of 45%. High and increasing government debt will eventually have to be dealt with — the right way would be to deal with it now before it becomes a problem; the wrong way would be to let it become a crisis, which, in my opinion, is probably the likely outcome. Importantly, almost 60% of government spending is for entitlements and is not discretionary. This makes the job that much harder. A crucial note on the importance of growth: If interest rates went down 100 basis points and GDP grew at 3%, the debt-to-GDP ratio could actually start to go down instead of going up.
  • High asset prices and very low credit spreads. In and of itself, this is not a bad thing. Household net worth as a percentage of GDP is now 560%. The high during the housing peak in 2006 was 460%. But this also means that anything less than positive outcomes could have a dramatic impact on global markets. Rapidly decreasing asset prices can sometimes create a self-reinforcing loop. It’s always good to remember that prices are set by the marginal buyers and sellers — which, on the average day, is only a small fraction of asset owners. And it’s also good to remember that foreigners own almost $30 trillion of U.S. equities and bonds. While U.S. investments and the U.S. dollar are generally havens of security in a troubled world, that didn’t stop recessions and bad markets in prior times.
  • Trade 2.0. The U.S. tariffs themselves had only minor effects on inflation or growth, and were only one straw on the camel’s back. But the trade battles are clearly not over, and it should be expected that many nations are analyzing how and with whom they should create trade arrangements. This is causing a realignment of economic relations in the world. While some of this is necessary for national security and resiliency, which are paramount, it is hard to figure out what the long-term effects will be.
  • U.S. and China relations. This relationship is critical to the whole world and is also impacted by the events mentioned above. The United States and China clearly have different systems, values, goals and objectives, and while both sides are currently engaging, we have to expect that there will be some bumps in the road — maybe even some large ones. We should all hope that ongoing proper engagement continues to lead to what may be a competitive but peaceful future.
  • Private credit and credit in general. The leveraged private credit market totals $1.8 trillion. As a comparison, the U.S. high yield bond market totals $1.5 trillion, and the bank syndicated leveraged loan market totals $1.7 trillion. Taking a wider view, the total market size of investment grade bonds is $13 trillion. And the total market value of all residential mortgage securities and loans is also $13 trillion. In the great scheme of things, private credit probably does not present a systemic risk.

    I do believe that when we have a credit cycle, which will happen one day, losses on all leveraged lending in general will be higher than expected, relative to the environment. This is because credit standards have been modestly weakening pretty much across the board; i.e., more aggressive and positive assumptions about future performance (called add-backs), weaker covenants, more use of PIK (payment-in-kind; not paying interest in cash but accruing it), more aggressive private ratings (particularly in insurance companies) and more arbitrage (not always a great sign). Also, by and large, private credit does not tend to have great transparency or rigorous valuation “marks” of their loans — this increases the chance that people will sell if they think the environment will get worse — even if actual realized losses barely change. Additionally, actual losses right now are already a little higher than they should be, relative to the environment. Finally, if rates or credit spreads ever go up, the companies that borrowed will have to borrow at even higher rates, putting them under even greater stress. However this plays out, it should be expected that at some point insurance regulators will insist on more rigorous ratings or markdowns, which will likely lead to demands for more capital.

    It has always been true that not everyone providing credit is necessarily good at it. There are many players who are late to this game, and it should be expected that some credit providers will do a far worse job than others. We have not had a credit recession in a long time, and it seems that some people assume it will never happen.

    Additionally, anything that gets sold to retail investors as opposed to institutional investors requires greater transparency, higher standards and fewer potential conflicts. If anything ever goes wrong, you should assume that retail investors, even though they were told about some of the risks, will seek remedy in the courts. Also, some of these loans go into various funds run by the asset management company. Generally, each of these funds has its own objectives and its own fiduciary responsibility to make sure that the loans are suitable for that specific fund. Those who do not do this properly are likely to get into trouble.
  • Private markets. With stock markets at all-time highs in recent months, it is a little surprising that private equity firms, which own close to 13,000 companies, have not taken greater advantage of healthy markets to take their companies public. Private equity investments are now held for an average of seven years — this is virtually double what it used to be. And some are sold, not to another company or taken public, and put in a new fund called a continuation fund. We have generally had nothing but a bull market since the great financial crisis — it’s hard to imagine what will happen if and when we have an extended bear market.
  • Cyber risk. I have to mention this because it remains one of our biggest risks, and this is probably true for many other major industries and corporations. AI will almost surely make this risk worse. We invest significantly to protect ourselves and stay vigilant.

10. There are a number of things that will have a positive impact on the US economy in 2026, and they are (1) the One Big Beautiful Bill, (2) purchases of securities by the Federal Reserve, (3) less restrictive regulations, and (4) AI-related capital spending

While there are many larger risks, as discussed in the next section, that may or may not impact the economy in 2026, we do know several things that will have a positive impact on the economy in the remainder of this year. They are:

  • Increasing fiscal stimulus from the One Big Beautiful Bill. Our economists believe this will inject another $300 billion (effectively 1% of GDP) into the economy. This has to be very modestly inflationary this year.
  • Benefits from the Fed’s purchase of $40 billion of additional securities each month, which is supposed to be reduced to $20 billion–$25 billion this April. At a minimum, this supports asset prices and helps ensure there is no liquidity squeeze in the financial system.
  • Positive effects of comprehensive deregulatory policies. This was badly needed and long overdue. Change is clearly evident in bank regulations that will free up capital and liquidity, which can be lent out (and we already see this happening), and in deregulation across many other industries, from energy to home building. It is fair to say that actions taken have clearly increased confidence and animal spirits. This should add to productivity and be modestly deflationary this year.
  • Huge increase in AI-driven capital spending and construction by the five hyperscalers. In 2025, this number was $450 billion, and in 2026, it will be approximately $725 billion. While AI will clearly drive productivity, which is generally good for inflation in the long run, all of this spending is probably inflationary in the short run.

Some of the items above have mild inflationary effects, while others probably have some deflationary effects.

11. The US has come together before to overcome incredible challenges

We have met big challenges before. At one point in 1940, only one nation, the United Kingdom, stood against the Nazi war machine, which had already conquered most of Western Europe. The United States was unprepared for what was going to happen but rose to the challenge. You may find it uplifting to read the book Freedom’s Forge, which shows how the United States came together to build the arsenal of freedom and to keep the world safe for democracy.

12. The US has become too dependent on unreliable sources for its national security needs

The United States has also allowed itself to become too dependent on unreliable sources for items that are essential to our national security, such as critical minerals, semiconductors and advanced manufacturing output, among others. We have maintained insufficient productive capabilities to be ready to quickly increase production if necessary. And our military needs to be able to rapidly develop new and often cheaper weapons, like drones.

13. The US could have grown even faster over the past 20 years than what it actually did

Over the last 20 years or so, U.S. GDP has averaged about 2% annually — I believe we could have easily achieved at least 3% growth. The reason we were able to grow 2% is that America’s businesses and entrepreneurial spirit allowed us to overcome a lot of the roadblocks mentioned later in this section. That 1% difference would have had an enormous impact, providing Americans with an extra $20,000 GDP per person annually, giving us resources to take care of nearly all our problems and jump-starting deficit reduction. Growth is part of the solution to almost all of our problems…

…I am going to mention a few damaging policies, not in detail because I’ve written about them in the past, but if they aren’t corrected, real progress may be impossible.

  • Fraud, waste and abuse…
  • …Inefficiencies within the federal government (and within state and local governments, too)…
  • …Mortgage and regulatory policies and local housing requirements….
  • …Red and “blue” tape, permitting reforms and a little litigation reform… 
  • …Policy uncertainty…
  • …Unreliable R&D policies…
  • …Failure to recognize that capital formation drives growth.

14. Supportive policies for capital formation in Sweden and Australia have led to great results

In Sweden, an investment savings account is available that simplifies the investing process with favorable tax treatment. Account holders can deposit and withdraw funds at any time, and there is no capital gains tax — just an annual tax of 1% on the balance. This has dramatically increased investment by retail investors into the Swedish stock market. It may surprise some of our readers that Sweden’s policies have created a growing and innovative stock market and that Sweden has more unicorns and billionaires per person than America does. Another example is Australia, which has a wonderful retirement policy based on superannuation, a savings account funded by both employer and employee contributions.

15. The private sector should be the one allocating capital, not the government

Industrial policy mechanisms, when used, should be as targeted and as simple as possible. They come in many guises: grants, cheap loans, equity investing, purchase agreements and others. The cleanest of these is tax credits in various forms. Whatever the policy, two rules should not be violated: (1) there should be no social engineering — this is not a jobs program (the Jones Act meant to preserve jobs in the Merchant Marine has basically destroyed our Merchant Marine and merchant ship building business) and (2) for the most part, the market should allocate capital, not the government. Industrial policy can easily devolve into a buffet where corporate America gorges at the expense of the taxpayer. While there are certain circumstances that require the government to allocate capital (think infrastructure and national security), generally the government is simply not good at allocating capital in a free market. America does best not with central planning but with consistent and clear policies that are conducive to growth.

16. Europe is currently on a very bad path of decline and fragmentation; Europe’s defense industrial base is not in good shape

I believe we are staring one in the face: the slow but constant decline and fragmentation of Europe. Europe is entering a decisive decade, and it is unable to act. The EU was an extraordinary accomplishment —nations coming together and using political and peaceful means to settle differences. And this after a millennium of terrible wars. It worked, but it only went halfway. Europe never finished the economic union (see the Draghi report), which meant that European countries constantly underperformed economically. This has led to their GDP relative to the United States going from 90% in the year 2000 to approximately 70% today. This fragmentation remains a structural drag on competitiveness. As former European Central Bank President Mario Draghi has noted, internal EU market barriers function like “hard tariffs” of approximately 45% for manufacturing and 110% for services. Those barriers reflect not a failure of ambition but rather a failure of integration. This has led to a lack of scale for their major businesses and a lack of mobility for both capital and people.

EU nations also created whole new layers of bureaucracy that reduced innovation, growth and investment among other things. This will continue unless European leaders dramatically change course. If they don’t, they will eventually be unable to afford their social safety nets, restrengthen their nations’ militaries and grow their economies. The EU is currently home to world-class companies, deep pools of savings and a talented workforce. But without new EU direction, their major global companies will weaken, faced with very strong American and Chinese competition. The ultimate loser in all this will be Europe and all its citizens — and it will hurt the United States as well.

Europe and America are each other’s largest trade partners at $2 trillion a year…

…Yet Europe’s defense industrial base is still not fit for purpose. This is as much an economic and industrial challenge as a military one. The continent needs enduring production capacity, coordinated procurement and dual-use manufacturing that serves both commercial and defense sectors.

17. Strong leadership by the US is still required for global prosperity

Strong American leadership is required – there is no real alternative.

Some political leaders have said that there is a “rupture” between America and the Western world — that the red lines have been crossed and there is no return to the prior system. I completely disagree. There is no practical replacement to the prior system. It has not ruptured, but it needs reform. The middle-sized nations do not have real alternatives in terms of building a unified military or a unified economy that can compete effectively with the United States and China. If these middle nations did, the result would look a lot like what Europe is today: dysfunctional. The only practical alternative is to fix the current situation.

The United States and Europe have an extraordinary number of commonalities, including values deeply held. For more than 75 years since the end of World War II, the United States and Europe have worked together to resolve most major global economic or military challenges and in fighting terrorism and nuclear proliferation. We need this cooperation for the next 75 years.

I do not want to contemplate the opposite. Without American leadership, there would be a huge vacuum. If not us, who? We are the only country that has the capability to do it. Fragmented relationships with and among our extensive allies could lead to an “every nation for themselves” mentality. America would become more isolated, the U.S. dollar would no longer be the world’s reserve currency and autocratic nations would rejoice. Need I say more?


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 05 April 2026)

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 05 April 2026:

1. Energy’s Moment – Abdullah Al-Rezwan

I had this naive assumption that since the US has now become a net oil exporter and China remains heavily dependent on imported oil, any oil shock would be net negative for China far more than it would affect the US.

So, it was surprising for me when I noticed that China was actually ahead of the US in terms of “total insulation factor” when it comes to global oil & gas shocks. The “total insulation factor” indicates the share of a country’s useful final energy that is less exposed to global oil and gas shocks. JPM calculated it by adding together a country’s reliance on four specific energy sources: domestically produced gas, domestically produced coal, nuclear power, renewables (such as biofuel, hydro, wind, solar, and biomass). China has a total insulation factor of 76%, while the US has a total insulation factor of 70%. China scores higher primarily because of its massive reliance on domestic coal (54% of useful final energy), which accounts for a larger share of its energy mix than the US’s primary domestic buffer: natural gas (44.5% of useful final energy).

Even though China is the world’s largest oil importer nation, oil imports make up 13% of China’s primary energy consumption. When you combine all oil consumption and imported gas, it only accounts for 20% of China’s primary energy. 

2. A Sinister Raise, a Bitter Press Release, and Five Other Weird SEC Filings – Andrew Walker

EMPD is a digital treasury company focused on Bitcoin. Like most digital treasury companies, they’ve traded for a discount to NAV basically this entire year; for most of the past month, they’ve been trading around 80-90% of NAV (you can see a real time NAV calc here).

Towards the end of March, the company announced a $25m equity raise. The raise was priced at a premium to both NAV (it priced at 103% of NAV) and the market price (again, the company trades for <90% of NAV); on top of that premium raise, the company noted they’d continued to buy back stock at a discount to NAV. Read that sentence again: a company trading at a discount is buying back shares and somehow raising capital at a premium to NAV? Nirvana for shareholders, right!?!?!

Au contraire, mon frère!

EMPD didn’t just issue stock in the equity raise; for every share they issued, they gave the buyer a four year warrant struck at $6.27/share (~20% above NAV). Those warrants have enormous value; BTC currently trades with ~50 vol. EMPD is a levered BTC treasury company, so it should have even more volatility than BTC (EMPD’s option chain is extremely thin but points to volatility well over 100). ChatGPT tells me that a four year warrant that’s 40% out of the money with 100 vol is worth ~65% of the spot price…. for EMPD, that means each warrant was worth ~$2.90/share. So, yes, the headline number EMPD raised at was $5.39/share, but if you adjust for the value of the warrant EMPD raised money at an effective price of ~$2.50/share while the stock was trading at ~$4.50/share. An absolutely awful trade.

Why would EMPD raise money like this? Well, I’m not in the board room, so I can’t tell you with absolutely certainty…. but I’d suggest it’s likely a board entrenchment maneuver. EMPD is currently in a rarely seen double proxy fight where two separate shareholder groups3 are trying to replace the board with a more shareholder friendly group4. EMPD’s press release announcing the raise notes the raise was bought by a “current institutional investor” in EMPD; my guess is EMPD went to a big shareholder and said “hey, agree to keep the current board in place, and we’ll give you a big slug of stock to vote and toss in a ton of warrants to make the whole thing worth your while.” …

…Today, BNTX has just shy of $20B in net cash, and while the COVID franchise is obviously dwindling the company has a ton of promising other drugs / readouts coming over the next few years….

Perhaps those readouts work, perhaps they don’t. I have no idea! But it’s a pretty promising set up…. which is why it’s so wild that BNTX announced that their co-Founders / top executives were leaving BNTX to start a “next-generation mRNA innovations” company. What’s even crazier is that BNTX will be contributing their mRNA assets to the new company!

Why is this so crazy? It’s absolutely ripe for conflicts of interest! BNTX could have spun out the mRNA assets to all their shareholders and put their founders / exec team in control of the new company. That would have been a fair and equitable way to do a start up. Instead, it seems BNTX will contribute the mRNA assets to the new company in exchange for a piece of that company. How are the mRNA assets going to get valued in that transaction? Given the founders / CEOs are going to the new company, it’s not hard to see how they might want to give the new company a boost by paying BNTX far under market value for the mRNA assets.

3. 2023 – Dean W. Ball

Intelligence is a tremendously useful capability, but it is not the bottleneck on all human progress, and, crucially, an extreme amount of intelligence does not equate to omniscience. Intelligence is not knowledge. Aristotle was surely more intelligent than I am, but he was not more knowledgeable, including even about many of the topics to which he devoted his treatises. This is why I am confident I would score better on a standardized test in biology or physics than Aristotle, despite him being one of the West’s originators of those fields of inquiry.

In a similar vein, imagine a newborn baby that was guaranteed to grow into an adult with an astoundingly high IQ (say, an IQ of 300, or 500, or 1000), but raised by Aristotle in Ancient Greece. Do you expect that the baby would mature into an adult that invents all modern science within the span of a few years or decades? Eliezer Yudkowsky does. Indeed, he describes contemporary humans trying to grapple with superintelligent AI as equivalent to “the 11th century trying to fight the 21st century.” I, on the other hand, strongly doubt that our imaginary high-IQ baby would invent all modern science from first principles. First principles do not have unbounded explanatory power.

In the end, most interesting things about the universe cannot be inferred from first principles. Imagine, for example, that you came upon a dry planet with mountain ranges but no bodies of water. But imagine that you knew, magically, that the planet would soon gain an atmosphere and thus precipitation, seasons, and the like. Suppose you have a superintelligent AI with you, and you show it the map of the planet as it is, and ask it to predict where all the planet’s rivers, lakes, and oceans will lie 50 years hence, after the planet gains regular precipitation. You don’t ask it to predict “generally speaking, where the bodies of water might end up,” but instead to predict exactly where they will be.

I would submit that there is no computational process which can arrive at the end of this natural process faster than nature itself. In other words, there is no pattern or abstraction you can create that allows you to speed ahead to the end of the process, and thus there is no amount of intelligence that gets you to the correct solution faster than nature on its own. You just have to wait the 50 years to find out. This is what the scientist Stephen Wolfram describes as “computational irreducibility.” Understanding this notion deeply is key, I think, to understanding the limits of intelligence. It should therefore come as no surprise that the best debate I’ve ever heard about AI existential risk was between Wolfram and Eliezer Yudkowsky.

Computational irreducibility comes into play anytime you are interacting with a complex system (though this is not to say that computational irreducibility is intrinsic to all interactions with a complex system). Every natural ecosystem, cell, animal, and economy is a complex system. While we have all manner of methods to predict what will happen when a complex system is perturbed (we call these things “physics,” “biology,” “chemistry,” “economics,” and the like), none of those methods is perfect, and often they are far from it.

The way we build better models of the world does not usually resemble “thinking about the problem really hard.” Generally it involves testing ideas and seeing if they work in the real world. In science these are generally called “experiments,” and in business sometimes we call these “startups.” Both take time and often money (sometimes considerable amounts of both); in the limit, neither of these things can be abstracted away with intelligence, no matter how much of it you have on tap. This is the central reason that I have written so much about, and even written into public policy, automated scientific labs that could run thousands of experiments in parallel; AI will increase the number of good predictions, but these are worth little without the ability to verify those predictions with experiments at massive scale.

There is one further observation that follows from the disentanglement of knowledge and intelligence. This is that knowledge itself is distributed throughout the world in highly uneven and imperfect ways. Anyone who thinks that “all the world’s knowledge” is on the internet is deeply mistaken. There is information that exists within a firm like Taiwan Semiconductor Manufacturing Corporation that is, first of all, not only unavailable on the internet but literally against Taiwanese law to make public. Even more importantly, though, there is knowledge within that firm that cannot be written down and is only held collectively. No single employee knows it all; it is the network—the meta-organism of TSMC itself—that holds this knowledge. It cannot be replicated so easily. This is all merely a restatement of the knowledge problem most memorably elucidated by the economist Friedrich Hayek.

The implicit, and sometimes even explicit, argument of “the doomers” is that intelligence is the sole bottleneck on capability (because any other bottlenecks can be resolved with more intelligence), and that everything else follows instantly once that bottleneck is removed. I believe this is just flatly untrue, and thus I doubt many “AI doom” scenarios. Intelligence is neither omniscience nor omnipotence.

What all of this means is that I am doubtful about the ability of an AI system—no matter how smart—to eradicate or enslave humanity in the ways imagined by the doomers. Note that this is not a claim about alignment or any other technical safeguard, even if a “misaligned” AI system wanted to take over the world and had no developer- or government-imposed, AI-specific safeguards to hinder it, I contend it would still fail. “Taking over the world” involves too many steps that require capital, interfacing with hard-to-predict complex systems (yes, hard to predict even for a superintelligence), ascertaining esoteric and deliberately hidden knowledge (knowledge that cannot be deduced from first principles), and running into too many other systems and procedures with in-built human oversight. It is not any one of these things, but the combination of them, that gives me high confidence that AI existential risk is highly unlikely and thus not worth extreme policy mitigations such as bans on AI development enforced by threats to bomb civilian infrastructure like data centers. “If anyone builds it, everyone dies” is false.

4. Beware of Simple Narratives – Alfred Lin

Consider a few narratives that shaped and misshaped technology investing:

  • Winner takes all. In some markets, such as search and social networking, this proved largely correct, but enterprise software proved stubbornly multi-vendor. E-commerce never consolidated the way the narrative predicted. Even in cloud infrastructure, the oligopoly of AWS, Azure, and GCP defied the single-winner thesis. The narrative was a useful heuristic. Founders and investors who treated it as a law made expensive mistakes.
  • First mover advantage. Google was not the first search engine. Facebook was not the first social network. The iPhone was not the first smartphone. The company that finds product-market fit in the right window wins. But “timing and execution matter more than sequence” is a harder story to tell than “be first.”
  • AI will replace [x]. Today’s dominant narrative is directionally correct but operationally misleading. The simple version, that AI replaces humans in a neat, linear substitution, misses the more investable reality. Augmentation, new workflows, and entirely new categories of work tend to emerge alongside displacement. The companies building for the nuanced version of this future look very different from those building for the simple version…

…In 1997, I declared that Amazon would kill Walmart. Today, Walmart is 30 times larger than it was 30 years ago. With each quarter of declining mall traffic and each confirmed brick-and-mortar bankruptcy, the thesis held true. This was confirmation bias at work. The world was messier than the story. E-commerce companies also failed. Customer acquisition costs online kept rising. Certain categories had persistent try-before-you-buy dynamics. Physical presence created brand equity that digital alone could not. Those who treated the simple narrative as a settled truth missed the omnichannel reality that ultimately prevailed.

5. Javier Blas on Why Oil Could Go Much, Much Higher (Transcript here) – Tracy Alloway, Joe Weisenthal, and Javier Blas

Javier: You are absolutely right that what is really cushioning the market right now is a number of buffers that we are going through. One is regular inventories that every country, every refinery has to normal functioning. Then is also the strategic inventories that some countries own, particularly industrialized countries like the United States, Europe, Japan, and also China. Those have been mobilized, in most places have been released. And also we entered the crisis with a market that was over-supplied. There was even floating storage – that is when an oil tanker has been loaded, it’s on the high seas but it cannot find a buyer and just basically sits on the high seas looking for someone who will take the oil. We have quite a lot of that just going into the crisis. So there was quite an element of buffer through the system and probably a larger buffer than in normal circumstances because the market was over-supplied. That is helping to cushion or to mitigate the crisis.

Where we are seeing some actions by government is where countries are closer to the crisis, which is the Strait of Hormuz. So the closer that you are to that location, the more action you need to take because you typically depend more of that flow of oil coming from the Middle East and also because you are impacted earlier. If you are moving oil from say Saudi Arabia into India, that’s only a few days, at most a week, of sailing time. If you are moving that to say the Philippines, that’s about 15 days. It’s longer if you are moving that oil into Europe, probably around three weeks. And it’s even longer if you are moving that oil into say the United States where Saudi oil takes about 40 days. All of that means that the crisis is felt in some places quicker than in other places.

Also is how the global oil market works. And to put it in quite simple terms, I’m afraid that I have to go with colonial vocabulary. The oil market is divided in two large chunks. East of Suez and west of Suez. This is like the British Empire was still around and everything was east or west of the Suez Canal. Countries that are east of Suez, mostly Asia, rely a lot on Middle East oil these days and therefore they are impacted earlier on by the crisis. West of Suez, Europe, Western Europe, and the whole American continent, is a bit detached from that market and therefore the crisis will hit them much later…

…Javier: But if I may suggest, forget about the price of a barrel of oil. No one cares about the price of oil unless you are someone producing oil in Texas or Saudi Arabia, or you are someone who owns a refinery. Those are the people that care about the price of a barrel of crude. The rest of us, you and I, we care about the price of a refined product because that’s what we consume. We consume gasoline, we consume diesel, or we consume other refined products that they embed into a service that we are buying. Think about an airfare ticket, where inside that ticket there’s a big proportion of it that is jet fuel, or you are buying a cup made of plastic. You are buying effectively some kind of transformed naphtha and obviously the transformation and the retail margin and so on, but what matters really is the price of refined products, and there actually we are beginning to see, particularly in the Southeast Asian markets, some very extreme prices.

If you look at the price of crude or Brent or WTI or Oman, things look relatively contained. We are trading around $110 a barrel, that is well below the all-time high. If you look at the cost of diesel in Singapore, which is a benchmark for the Southeast Asian market, the price there is approaching $200 a barrel, which is something that we have never seen. The refined product is where really we are seeing the real tension.

Tracy: This is exactly what I wanted to ask you. If you look at the benchmark prices for crude oil, we’ve seen higher prices before, and relatively recently in 2022. But if you look at the refined products, we’re getting to places that we haven’t seen. What explains that disconnect? Back in 2022, why didn’t we see the higher cost of crude feed into refined products the way that we seem to be seeing now?

Javier: For two reasons. One is because we have lost not only a lot of crude oil production, but we have lost a significant chunk of refined production. The Middle East also has a lot of refineries which are export refineries. They are just devoted to the export market and the global trade of refined products is a lot smaller than the global trade of crude oil. So even a small reduction in supply could have a much larger impact. You think about the global market for crude oil which is 100 million barrels, around 60 million are traded globally. But if you look at the market for say jet fuel, that market is a lot smaller and we have lost a significant proportion of the refineries who are serving that international market for jet fuel and therefore prices are reacting much more stronger than we saw in previous crises.

There’s also the way that the world of refining works. Some refineries are slowing down intake of crude oil because there is not enough crude oil in the market but we have not really seen yet the consumers reacting the same way. So what is happening is the refining world is acting as a buffer between crude oil that is not there, and consumers that have not yet realized that the crude oil is not there. The refined market is trying to basically get those two together. The way that it can only do it is by extreme pricing and indicating to the consumers, “I don’t have enough crude to make these refined products, so please can you stop demanding the refined products?” The please is basically $200 a barrel diesel…

…Tracy: What’s going on with US natural gas? If you look there – we’re talking about muted market moves in the oil market, even though those have risen – if you look at nat gas, nat gas has actually come down.

Javier: Nat gas in the United States is trading almost at a six-month low, which considering what is happening in the global energy market, is almost incredible. The reason there is US shale. And the reason is that you cannot export gas easily. For exporting gas, you first need to cool it down, liquefy. That basically means having an enormous fridge that cools gas from room temperature to -160 celsius, then it liquefies and then you can put it on a tanker and send it to the rest of the market. Because we have limited liquefaction capacity, and it does increase quite quickly, that creates a bottleneck. That means that the US and Canadian gas is effectively trapped inside North America and that’s keeping prices completely detached from the global market. That is a huge difference from previous episodes of high energy prices. Even in 2022, the price of US natural gas went from around $3.50-$4 to almost $10 per British Thermal Unit. This time it’s staying at actually below $3 per MBTU.

That is incredible because it means that the heavy US industry, electricity generators, chemical companies, fertilizer companies, there is no crisis while everyone else in the world is suffering. The US is completely insulated…

…Javier: 2022 was a huge shock to the global food market because it affected a bread basket region of the world. If you look at Russia and Ukraine, at the time combined, they accounted for around a quarter of global exports of wheat and barley, around 15% of global exports of corn, and even much higher percentage for some vegetable oil like rapeseed and sunflower. The Russian invasion of Ukraine, the battleground was some of the richest fertile farmland in the planet. The battleground of the crisis in the Middle East is deserts and a piece of sea that we call the Strait of Hormuz. It doesn’t have the same impact in terms of global supply.

It does have an impact on fertilizer prices. It did also, the 2022 war between Russia and Ukraine which is still ongoing. But fertilizer prices require time to have an impact on food production. Also, while yes the numbers are very scary and you look at the global fertilizer market, just focusing on urea, you look at that market and say, “Oh boy it’s going up a lot, we are approaching the 2022 record high.” But that is a problem in many markets, it’s a problem that is not a food problem. It will be a fiscal problem and the reason is that urea fertilizer in particular is massively subsidized in the developing world, particularly in places like India and Pakistan. So the problem there is going to be for the Indian government – can it afford to spend billions of dollars extra subsidizing fertilizer? Less so is it going to be a food crisis in India because the fertilizer I think is going to be there. You are the finance minister in India, you have a big problem there. That’s how I’m seeing the problem.

Also the global food market is in a better position than almost anytime in the last two or three decades. Inventories of wheat are very high. Inventories of rice in particular at an all-time high. You mentioned rice, while we are worried about fertilizer prices, etc., etc., if you look at the most important benchmark for rice prices in Asia, it is about to hit at 19-year low…

…Javier: Oh boy, if we we didn’t have enough with the Middle East, here is Ukraine. You cannot blame Ukraine, it is fighting for survival. They are hitting Russia as hard as they can, wherever they can. And that means hitting their oil terminals. In the past, they were hitting the terminals in the south of the country. That’s the Black Sea. But they have found a corridor to send long-distance drones into the north, into the Baltic. I think the Russians were caught completely offguard. They didn’t think that Ukraine will be able to hit the terminals in the far north of Russian territory. So they were not very well protected, or you say Ukrainians were extremely good at it. But the terminals have been damaged significantly. We don’t know for sure the extent of the damage, but looking at the satellite pictures, it looks bad enough. So we may be also losing potentially 1 million barrels a day of Russian oil. Again you cannot blame Ukraine, but it’s not really the time when you want to be losing more oil…

…Tracy: Okay, one thing that people have talked about for I’m pretty sure the duration of all of our careers, are attempts to move away from pricing oil in dollars. If you think about the current situation, there’s something very perverse about seeing the dollar go up because there’s a scramble for barrels of oil because of an action taken by the United States. From your context in the oil market, is anyone talking about actual currency pricing for barrels at the moment? Is this something that is going to get renewed traction?

Javier: No, I don’t hear anyone. Certainly Iran may be happy to take other currencies. It has been relatively happy to take Chinese yuan, and also other currencies which has problems on convertibility. Everyone else will still want the dollar. The way that it was put to me by a leading producing country in the Middle East, and I was talking to the head of the central bank, I’m going to not name the country. But they said to me, “If I switch from the dollar to say the yuan, I move from a relatively high interest rate, to a low interest rate. I move from full convertibility to a lot of problems to convert. And I move from maximum liquidity to no liquidity whatsoever.” And then this central bank governor is like, “Why I would like to do that? Why I would like to really take a step back on my currency?” I think that the yuan is not there yet for oil producers. Everyone that is using other currencies than the dollar to price their oil or to invoice their oil, they are doing it because they are under American sanctions. They’re not doing it because they want to do it. They’re doing it because they have no other option than to do it. Just because they are on the naughty corner of the US Treasury.


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 GCP), Amazon (parent of AWS), Microsoft (parent of Azure), and TSMC. Holdings are subject to change at any time.

What Warren Buffett Thinks About The Stock Market And Global Economy Now

The Oracle of Omaha was interviewed by CNBC recently.

Warren Buffett stepped down as CEO of Berkshire Hathaway at the end of 2025. Together with this change in his professional life, he would also no longer hold court during Berkshire’s AGM (annual general meeting) that has traditionally been held in early-May each year. This means there’s less opportunity for the public to hear his thoughts about the financial markets and the world writ large. 

So I was excited when he appeared for an hour-long interview session hosted by CNBC earlier this week. Here are my takeaways from the interview (passages in italics below are from the official transcript of the event):

1. The US stock market has not fallen much so far

QUICK: Well, let’s talk about that. The market has come down substantially.

BUFFETT: Not substantially.

QUICK: Well, you’ve got both the Dow and the Nasdaq in correction territory. It’s the worst performance on a quarterly basis for stocks in about four years. Do things look cheaper to you?

BUFFETT: No. Three times since I’ve taken over Berkshire, it’s gone down more than 50%. I mean, if you look at the markets, of the worst, probably was the 2007, 08′ period, although it was that one Monday, when you had 21% in a day. I mean, this is nothing. I mean—

QUICK: This is nothing to make you get excited and think there’s huge valuation—

BUFFETT: Well if they’re 5 or 6% cheaper, that doesn’t, we aren’t in it to make 5 or 6%…

2. Buffett’s happy to deploy capital for long-term investments if there’s a big decline, but he does not know what the market will do

QUICK: Are you waiting for the next big drop in the market to deploy that cash, and if so, when do you see that coming?

BUFFETT: Yeah, if there is a big decline, we will deploy, I mean, but we won’t, we will deploy it because stocks are attractive or businesses are attractive to us, and we are not planning to sell them next week or next month, so we want to be right on them. And we’ve had our American Express stock 30 years without having a — close to 40 years, 35 years. And on the other hand, there’s things I change my mind on fairly quickly, but, but the goal is own the owned businesses, and when we buy Occidental Chemical, we expect all of that 50 years from now. You know, the world can change in some way, but that we do not, we do not buy that with a thought of resale…

…BUFFETT: No, no, I don’t have any ability to predict what stocks will do next week or next month and I will buy them if they’re cheap. I’ll buy a whole lot of them if they’re cheap and I think I really understand the business, and Apple is still our largest single investment…

…BUFFETT: I mean, the idea that people think they know what the market’s going to do is just crazy. I mean, the idea that they would shout out to the world, you know, that something they really knew, I mean, that’s like saying if they had gold — found gold in their backyard, they’d come on television and say, here’s where the gold is in my backyard, you know? I mean, they’re selling something.

3. Railroads are more likely to be around 50-100 years from now than smartphones, but Apple is the company that earns the higher on capital

BUFFETT: Yeah, well, if I didn’t like it, I could sell it. Yeah, I can,  I think it’s a remark — it’s better than any business we own outright. Now, we own a railroad that’s worth more money than our Apple position, for example, they’re both looked at the same way. I mean, they’re both, they’re both businesses. I expect the, I think it’s more predictable in a certain sense, that the railroad will be around 50 or 100 years from now, but it doesn’t earn the rate remotely on capital than Apple does. I mean, Apple is a business that you’ve got one, probably and your kids have got them, and—

QUICK: Not one, we’ve got like 20 of them.

BUFFET: Yeah, devices. Actually, the Bell Telephone Company was that way at one point, but they were regulated.

4. Buffett thinks US technology companies are too well-liked by consumers for them to face heavy regulation; Apple is a consumer company in Buffett’s eyes

QUICK: Well, do you worry about regulation coming for some of these big tech companies, in particular Apple?

BUFFETT: I think the consumers are in love with them too much. I don’t, I don’t think Washington will do anything that really destroys something that every one of their voters likes and they’re using themselves. I mean, it’s a remarkable product that way. Just think of something as useful as the Apple is…

…QUICK: You don’t necessarily follow tech companies and Apple, people look at as a tech company, but you always looked at as a consumer company.

BUFFET: It’s a consumer.

QUICK: Yeah.

BUFFETT: Company. 

5. Buffett thinks the Federal Reserve’s biggest worry should be about the status of the US dollar as the world’s reserve currency

QUICK: Warren, let me ask you about the economy because the Fed is in a bit of a quandary right now, just trying to figure out which one of its mandates it’s more worried about. Is it worried about inflation potentially rising more. Is it worried about the jobs market and, you know, potential decline in economic output? What, what of those two issues would worry you most if you were at the Fed right now?

BUFFETT: Well, if I were at the Fed, the thing I’d worry about always is, you know, you’re the reserve currency of the world. I mean, so you’ve got very smart people, very sophisticated people, the American dollar looks like nothing could happen to it. I don’t feel anything could happen to it. But if it does happen to it, I would, I would, I wouldn’t want the responsibility of running the Fed.

6. Buffett would prefer the Federal Reserve to have a 0% inflation target instead of 2%; Buffett is concerned about inflation

QUICK: Did they keep rates low for too long? I mean, I think that’s, as they didn’t worry about inflation, as they said it was going to be transitory? Because I think even Powell himself said that he might wish he’d turned it sooner.

BUFFETT: Well, I wish they had a zero inflation target.

QUICK: Right.

BUFFETT: But, I mean, once you start saying you’re going to tolerate 2 percent, that compounds pretty dramatically over time. And you’re saying to people, if you’re getting less than 2 percent on your money, you’re going backwards. And, actually, if you pay tax, you may pay tax on the 2 percent. You know, I mean, I don’t like that particular goal. But—

QUICK: So, inflation is maybe what you’d be more concerned about? I mean, that’s what Greenspan, Alan Greenspan always said.

BUFFETT: Yes. I would be, I would care about inflation.

7. Buffett is concerned about the stability of banks, in particular, the inter-connectedness of the financial system; Buffett does not know enough about the private credit industry to opine on its effects on the banking system

BUFFETT: Yes. I would be, I would care about inflation. I would compare what I really would care about is the stability of the banks.

QUICK: Yes.

BUFFETT: I mean, the banking system, in some sense is very strong, in other sense, is very fragile. I mean, JPMorgan in the last couple annual reports reported doing $10 trillion of business per day. Now, that’s an unsecured policy. Now, they know what they’re doing. Believe me. I mean, there’s nobody smarter than JP– but I don’t want — I didn’t want — during the 2008 period, I didn’t want anything unsecured, you know, out there for a day. I mean, who knew? Nobody was any good. You know, I mean, it, the world is very interconnected and everybody panics. I mean, it, you know, they may say they don’t, but you can call the biggest investment banking firms and they say, well, they don’t answer the phone even if things get bad enough. And if they do answer the phone, you know, they say 10 bid, 20 offered subject.

QUICK: Yes. I mean, Joe will talk about that day that you mentioned in where the Dow was down 21 percent. I think he was, at that point, he said it himself. He was hiding under his desk for the calls that were coming in.

BUFFETT: Yes. And—

QUICK:  Because when liquidity disappears, it disappears—

BUFFETT: 21 percent and that was some day, and it just kept coming. And most of the specialist firms, which then counted for more in terms of the stability of the markets. They were broke. I mean, as I remember, they went around to their banks and said, just don’t pull the loans, you know, but they, people, they were supposed to keep making markets, but people just kept hitting the bid and can widen the spread out. You got circuit breakers now, all kinds of things. But when people are scared, they’re scared. And people, if you yell fire in a crowded theater, everybody runs. Still, it still pays to beat people to the door, you know, and I can get trampled, you know, so, I will stand back there and say everybody to stay calm, you know? But that’s because I can’t run fast. On the other hand, when people come back into the theater, they come in one at a time. They know they don’t have to get into it. But when people panic, they panic.

QUICK: But is it the banking system we should be concerned about right now, or is it the shadow banking system, the private credit at this point?

BUFFETT: Well, it’s all parts of the banking system because they all affect each other and the troubles from one can spread over to another. And, well, you saw what happened, I mean, in 2008.

QUICK: But at risk of potentially, I don’t want people to say that you are commenting on what’s happening in the private credit situation right now. What do you think of the private credit situation right now? Are there enough concerning issues there that you worry that it could cause a contagion—

BUFFETT: I don’t think I know.

8. Buffett is always prepared for a wide range of outcomes by holding significant amounts of treasury bills, but he’s not thinking that there’s something on the horizon

BUFFETT: I don’t, I do not think I know what, but, therefore, I want to be prepared for anything, and, therefore, we will always have, we’ll always have cash around and we’ll have treasury bills. We won’t have money market funds. We didn’t have them in 2008. We won’t have commercial paper in 2008. There’s just one thing that’s legal tender. And, you know, if you own treasury bills, and we have known, we don’t own treasury bonds way out. I mean, but every Monday, the treasury has to sell bills. And as long as they got to sell, you know, X billions worth of bills, I mean, they kind of a, they can print some money to do it, and they’ll do it.

QUICK:  But just to put a fine point on it, you don’t think you know what’s happening out there. You’ve had this huge cash forward north of $350 billion. It’s just there waiting for any time. It’s not that you necessarily think that there’s something on the horizon. It’s just the longer time goes—

BUFFETT: Oh, sure. No, I always want to have—

QUICK: Yes.

BUFFETT: Yes. And I never want to buy anything just because people think the market is going up.

9. Buffett’s worried about the possession of nuclear weapons by certain countries

BUFFETT: I took that pretty philosophically. I mean, I could handle that. And now, you’ve got nine countries, including, you know, a guy in North Korea. I mean, and there will be, something will happen. And we worried enormously about it when there were two. And we had perfectly, we had really pretty sane leaders in Kennedy and Khrushchev. You know, I mean, you were not dealing with unstable people or anything like that. And. You know, the ships turned around, but people were hiding under their desks with two. I mean, just think how you feel with North Korea having it and Iran wanting to get it. I mean, it — it is — and I don’t have an answer for that. I mean, we did the right thing in 1938 even or 1939. You can go look at it. It’s all over the Internet. The most important letter ever written. And Leo Szilard could not get the message to. He was a famous nuclear physicist. Terrific one. Very funny too. And he couldn’t get the message to Roosevelt, but he knew if Einstein signed the letter, that it would get there, and he finally got Einstein to sign the letter. And that letter was a month before the Germans started rolling into Poland. And I don’t think Roosevelt understood U-235 any better than I do. I mean, you know, but he knew if Einstein signed it, he better do something. And the funny thing is, of course, he was doing it because he was worried about the Germans getting it. And it was actually used on the Japanese. But it, we, we haven’t learned to live with it. Now, we’ve been — we’ve gone 80 years since then. We’ve had a lot of close calls. I mean, we’ve had training tapes put in there that that almost got the president to do something. They’ve had them. I mean, there is no way that the planet has an expectancy of 500 years now when it was 4.5 billion when I was a kid and we had to do it. I’m not faulting anybody. My dad was in Congress. He would have voted for it. I mean, everybody rejoiced on VJ day. You know, I mean, it — it — but there was no way we could undo it…

…QUICK: Yeah. So if you were the president today or if you were advising the president today, what would you say about going after the enriched uranium in Iran?

BUFFETT: I would say that one way or another. In the next 100 years, maybe it’s 200 years, who knows? But one way or another, something will happen that cause it to be used. And we can’t take what’s out there now. And if you thought it was dangerous with the Soviets and us with Khrushchev, who was perfectly rational guy, probably Kennedy, just wait until we, wait until we’re dealing with, you know, the guy in North Korea that criticizes haircut or something, I mean, or, or I would say the most dangerous thing is actually somebody that’s got their hand on the switch who is dying themselves or is facing enormous embarrassment if he figures if I go ever—

QUICK: If you’re cornered, yeah, if you’re cornered.

BUFFETT: Yeah.

QUICK: So that’s still rises to the level of one of the most important and—

BUFFETT: It is.

QUICK: Yeah.

BUFFETT: It’s just that I don’t know the answer for it. But I do know that the — it’ll be more difficult if Iran has the bomb than if they don’t.


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 a vested interest in Apple. Holdings are subject to change at any time.

What We’re Reading (Week Ending 29 March 2026)

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 29 March 2026:

1. What the closure of the Strait of Hormuz means for the global economy – Lutz Kilian, Michael Plante and Alexander W. Richter

From the point of view of the rest of the world, a disruption of oil exports from the Persian Gulf is equivalent to a disruption of oil production in the Gulf. From the point of view of oil producers in the Gulf, the difference is largely academic because as soon as local oil storage fills up, oil producers have no choice but to shut in their oil wells if the oil cannot be stored or exported. This is why many oil producers, starting with Iraq and Kuwait, started curtailing their production in early March 2026.

A complete cessation of oil exports from the Gulf region amounts to removing close to 20 percent of global oil supplies from the market, about 80 percent of which is shipped to Asia. Oil importers unable to access oil from the Persian Gulf have to turn to other oil suppliers, putting upward pressure on oil prices worldwide…

…Major oil supply shortfalls driven by geopolitical events such as wars or revolutions previously occurred following the Yom Kippur War in 1973, the Iranian Revolution in 1979, the outbreak of the Iraq–Iran War in 1980 and the Persian Gulf War in 1990. What makes the closure of the Strait of Hormuz different from these earlier oil supply shortfalls is first and foremost its magnitude. For example, in 1973 and 1990 only a little more than 6 percent of global oil supplies was removed from the market and in 1979 and 1980 only about 4 percent. Today, we are concerned with a shortfall close to 20 percent, making this geopolitical event three to five times larger.

This is the first time the Strait has been closed. While some observers in 1990 grew concerned that Iraq would take over Saudi Arabia and control of the Persian Gulf, these concerns never materialized…

…Regardless of the likelihood of the Strait reopening in the future, the model implies that a closure of the Strait of Hormuz that removes close to 20 percent of global oil supplies from the market during second quarter 2026 is expected to raise the average West Texas Intermediate (WTI) price of oil to $98 per barrel and lower global real GDP growth by an annualized 2.9 percentage points in second quarter 2026 (Chart 2).

The subsequent effects depend on when oil shipments resume. For example, if the Strait reopens after one quarter, the oil price drops to $68 per barrel and growth increases 2.2 percentage points in third quarter 2026. While the oil price drop causes growth to recover, the level of real GDP remains 0.2 percent below its pre-closure level even by year-end 2026 and 0.1 percent below its initial level by year-end 2027. The positive growth response in third quarter 2026 reflects the increased availability of oil and the resulting decline in the price of oil.

When the oil supply shortfall lasts longer than one quarter, richer dynamics arise. Extending the closure to two quarters causes the oil price to rise further to $115 per barrel in third quarter 2026 before falling to $76 per barrel in fourth quarter 2026 (Tables 1, 2). The impact on real GDP growth only turns positive in fourth quarter 2026. If shipping resumes after three quarters, the oil price will rise even further before declining, reaching as high as $132 per barrel by year-end. The impact on growth will remain negative through year-end 2026…

…While the model underlying these scenarios is global, the case can be made that the effects of higher oil prices on U.S. GDP growth will be of similar magnitude to the global effects. Although the U.S. economy for many decades was heavily dependent on imported petroleum, since the shale oil boom the U.S. petroleum trade balance has been close to balanced. This makes the U.S. economy not so different from a global economy model in which there is no trade in oil by construction…

…One way the oil supply shortfall could potentially be reduced is by Saudi Arabia increasing the flow of oil on the East-West pipeline from the Persian Gulf to the Red Sea. The capacity of the Yanbu port would allow Saudi Arabia to redirect about 4 million barrels of oil per day from the Persian Gulf for transport by oil tankers from the Red Sea, corresponding to about one-fifth of the global supply shortfall.

One obvious concern with this approach is the port in question is within range of both Iranian and Houthi missiles from Yemen, as are the waterways in the Red Sea. The other concern is that shipping this oil south past the Bab el-Mandeb Strait to Asia exposes oil tankers to attacks by the Houthis, while shipping it north through the Suez Canal limits the tanker size and requires redirecting the oil toward Europe rather than Asia where it is most needed.

There is also a short pipeline in the United Arab Emirates bypassing the Strait of Hormuz to the port of Fujairah on the Gulf of Oman. That pipeline as well as the port, however, have already come under Iranian attack, making it difficult for the existing flows to be maintained, never mind increased.

2. Warren Buffett Case Study – Dirtcheapstocks

J. Paul Getty was the richest man in America in 1957.

Five years later, you could buy a piece of his oil company for 63 cents on the dollar.

Warren Buffett took notice…

…Buffett’s Getty shares were marked at $18 at year end…

…On the surface Getty didn’t look especially cheap. Sure, it traded at a large discount to book, but the ROE was low and the stock was selling for 17x earnings.

But there was a larger issue at play.

Getty owned large stakes in three publicly traded, related party companies: Mission Corporation, Mission Development Corp., and Tidewater.

Without going into too much detail, the nature of these businesses was to produce, refine and market oil and manage other assets of the “Getty Empire”…

…Getty’s market cap was only $287mm.

Getty’s share of these three assets alone was $259mm.

Buyers at $18 were paying almost nothing for Getty Oil.

And it’s not like Getty had a bad business. It was earning $14mm of net income and had a pristine balance sheet. This excludes its share of income from Mission, Mission Development and Tidewater.

Getty had $398mm of total assets and only $50mm of total liabilities…

…Buffett was actually paying 1.7x earnings and 30% of book for Getty.

On a look through earnings basis (Getty earnings plus share of minority-owned earnings), Buffett paid ~7.5x for his Getty investment. It was cheap any way you slice it.

Getty had a steady history of growth…

…That’s an 11% CAGR over 11 years in BVPS.

Companies compounding book value at double digits should not trade at a discount to book…

…In 1949, J. Paul Getty ignored his advisors and bought a barren strip of desert in Saudi Arabia.

That piece of land produced 15,000 barrels per day in 1956.

By 1962 it was up to 100,000 barrels per day.

Getty’s agreement with Saudi Arabia called for a fixed royalty structure, allowing Getty to capture the vast majority of the field’s value.

In 1962, Getty produced 10x the oil volume of a decade prior…

…I don’t know how long Buffett held his shares, but he probably made money.

Shares traded up to $27.50 in 1963 and $32 in 1964.

Getty Oil was bought by Texaco in 1984 for $10.1 billion.

Adjusting for splits, the shares Buffett owned at $18 in 1962, would have grown to $625 in 1984.

Excluding dividends, the stock compounded at 17.5% for 22 years.

3. Meta’s Agentic AI Ambitions – Abdullah Al-Rezwan

One of the interesting bits from the blog post is that Meta mentioned for long-horizon workflow autonomy, Meta built REA on an internal AI agent framework called “Confucius” which they elaborated further on this paper back in February 2026. Often, when tech companies try to improve AI coders, they focus on making the underlying AI models (like GPT or Claude) smarter. However, the paper argued that the “scaffolding” i.e. the software environment, memory systems, and tools built around the AI is just as important. When working on big codebases, AI agents frequently get overwhelmed by reading too much code, forget their original plan during long tasks, or repeat the same mistakes.

The most interesting takeaway from the paper is that a great setup can compensate for a less powerful AI. The researchers proved that a weaker model (Claude 4.5 Sonnet) using the Confucius scaffolding successfully fixed more bugs (52.7%) than a stronger, more expensive model (Claude 4.5 Opus) using Anthropic’s standard setup (52.0%). When powered by the GPT-5.2 model, Confucius Code Agent successfully resolved 59% of the real-world bugs on the SWE-Bench-Pro test, beating both prior academic research and the official corporate systems built by OpenAI and Anthropic under identical conditions. If such scaffolding itself can consistently beat the more expensive SOTA models, it can provide a ceiling on SOTA model developers’ ability to exercise pricing power. It remains to be seen whether such scaffolding can outperform more expensive SOTA models in a wide range of scenarios. Nonetheless, the key takeaway is quite encouraging for all the tech companies that will not have a SOTA model and those tech companies may still be able to capture value from better scaffolding.

4. The AI Supply Chain Runs Through a War Zone. Nobody in Silicon Valley Is Paying Attention – Veron Wickramasinghe

The physical supply chain that powers every artificial intelligence system on earth passes through a single chokepoint that has been effectively closed since early March. Not a data bottleneck. Not a software constraint. A 21-mile strait between Iran and Oman through which 30 percent of the world’s LNG and 20 percent of its oil once flowed…

…Helium is the second most abundant element in the universe and one of the rarest on Earth’s surface. It is produced by the radioactive decay of uranium and thorium deep in the planet’s crust. It migrates upward through rock over billions of years and accumulates in the same geological traps that hold natural gas. You do not manufacture helium. You extract it as a byproduct of natural gas processing, or you do not have it.

Qatar’s three helium plants at Ras Laffan produce approximately 2.3 billion standard cubic feet per year: Helium 1 (660 million scf, online 2005), Helium 2 (1.3 billion scf, the world’s largest, online 2013), and Helium 3 (400 million scf, online approximately 2021). That is roughly one-third of total global helium supply, according to the US Geological Survey’s 2026 Mineral Commodity Summaries, which puts Qatar at 33.2 percent of world production.

All three plants have been offline since March 2, when Qatar halted LNG production following the outbreak of hostilities. The helium plants cannot operate independently of the LNG facility because helium is extracted from the natural gas stream during cryogenic liquefaction. When the gas stops flowing, the helium stops flowing.

QatarEnergy CEO Saad al-Kaabi confirmed on March 24 that the missile strikes reduced helium output capacity by 14 percent, with repairs expected to take three to five years. The planned Helium 4 plant, targeting 1.5 billion standard cubic feet per year and over 50 percent engineered before the crisis, has no confirmed restart timeline…

…The bottom line: helium is genuinely critical for specific, high-value fabrication steps, particularly plasma etching, where no substitute exists. It is not equally irreplaceable across all semiconductor applications. But the applications where it is irreplaceable happen to be the ones that define whether a chip gets made or does not…

…South Korea imports 64.7 percent of its helium from Qatar, according to Korea International Trade Association data for 2025.

South Korea is home to Samsung Electronics and SK Hynix, which together dominate global memory production. SK Hynix commands 62 percent of the High Bandwidth Memory market by shipment volume as of Q2 2025, per Counterpoint Research. Samsung holds 33 percent of global DRAM market share. Combined, these two companies produce the majority of the memory chips that go into every AI training system, every data centre GPU, and every high-performance computing cluster on earth.

HBM is the single most critical constraint in the AI hardware supply chain…

…South Korea imports approximately 70 percent of its crude oil from the Middle East. The Strait of Hormuz has been effectively closed to commercial shipping since early March, when war risk insurance premiums made transit economically unviable. Seoul implemented mandatory fuel rationing on March 25: a one-day-per-week vehicle ban for 1.5 million government vehicles, enforced by licence plate number.

QatarEnergy declared force majeure on long-term LNG contracts with South Korea on March 24. Gas generates approximately 26 percent of South Korea’s electricity. Those contracted molecules, which were supposed to flow reliably for decades, now carry a force majeure notice that could last five years.

South Korea is losing three supply lines simultaneously. Oil. Gas. Helium. All from the same chokepoint…

…SK Hynix has publicly stated it has diversified supplies and secured sufficient inventory. Samsung has not issued a public reassurance but is understood to hold approximately six months of stockpile and has deployed its Helium Reuse System, which reduces consumption by approximately 18 percent. TSMC says it does not currently anticipate notable impact and maintains helium from multiple suppliers with over two months of stock on hand. The Korea Semiconductor Industry Association says short-term supplies are sufficient.

There are reasons to take these reassurances seriously. Major fabs are not naive about supply chain risk. Over 70 percent of fabs in Taiwan and Japan already operate helium recycling systems. Six months of Korean stockpile buys time…

…The United States produces 42 percent of global helium but cannot rapidly scale. The former Federal Helium Reserve in Amarillo was privatised in June 2024 and can no longer serve as a government strategic buffer. Russia’s Amur Gas Processing Plant has design capacity roughly equal to Qatar’s entire output but faces Western sanctions. Algeria produces only 5 to 10 percent of global supply. Tanzania’s emerging helium projects are years from commercial production.

Phil Kornbluth estimates a minimum three-month disruption to helium supply chains, plus two months for logistics normalisation. If the conflict extends beyond six months, the structural deficit has no easy solution…

…South Korea does not just make chips. It builds the ships that carry the gas that the rest of the world needs to replace Qatar’s output.

South Korean shipyards, HD Hyundai Heavy Industries, Samsung Heavy Industries, and Hanwha Ocean, delivered 248 LNG carriers between 2021 and 2025, versus 48 from China. That is an 83.8 percent share of LNG carrier deliveries over the past five years, per BusinessKorea. Korean yards currently hold approximately two-thirds of the global LNG carrier orderbook by value, with LNG vessels accounting for 52 percent of their total backlog at $71.3 billion, per VesselsValue.

A single 174,000-cubic-metre LNG carrier costs $220 to 260 million at current pricing. Construction takes 30 to 36 months from steel cutting to delivery. Korean yards have orderbooks extending through 2028. New orders placed today face delivery in late 2028 or 2029.

Korean vessel exports hit $31.8 billion in 2025. Gas carriers make up over 60 percent of order composition… 

…South Korea’s energy crisis, caused by the Hormuz closure and Qatar’s force majeure, puts pressure on the industrial base that builds the LNG carriers the world needs to transport replacement gas. If Korean industry faces sustained energy disruption, supply chain delays, or cost inflation, carrier construction timelines could slip. If carrier construction slips, the global LNG fleet grows more slowly at precisely the moment the world needs more ships. If there are not enough ships, the global gas shortage deepens. If the gas shortage deepens, energy prices rise further. If energy prices rise further, Korean industry takes a harder hit.

I want to be precise about the limitations of this argument. There are circuit breakers. South Korea is restarting five nuclear reactors and easing coal restrictions. Shipbuilding is moderately energy-intensive, far less than steelmaking or semiconductor fabrication. There is currently an oversupply of LNG carriers, with approximately 60 idle ships providing buffer. Any disruption to shipyard output today would only affect deliveries in 2028 to 2029, given build timelines.

5. Notes from the SaaS Funeral – Reid Hoffman

Just two weeks ago, a single tweet about Claude Code was enough to wipe five percent off SaaS stocks. I understand the instinct. But I think the inference most people are drawing is wrong, and it’s worth being precise about exactly where the logic breaks down…

…Most of the arguments here fundamentally misunderstand software businesses as just lines of code you generate once. They are living systems that require maintenance, verification, security, compliance, and ongoing refinement…

… A CRM company that ships a deeply intelligent set of agents that iteratively refine your sales workflow, that understands your pipeline more comprehensively than any human analyst, that comes with powerful backend libraries purpose-built for that domain has an extremely well-crafted moat…

…The business model will shift, too. We may see more models where customers prepay token budgets much like a utility. For example, a CRM company that reimagines its economic model around compute consumption and scale. We’ve experienced business model transitions like this before. We went from on-premises software to cloud SaaS and the world didn’t end; it expanded. We’re making a similar transition now, from cloud to AI-native…

…And Jevons’ Paradox will do what it always does… as the cost of building software drops dramatically, the demand for software will expand dramatically.


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 and TSMC. Holdings are subject to change at any time.

Company Notes Series (#14): The Central and Eastern Europe Fund


Editor’s note
: This is the latest edition in the “Company Notes Series”, where we periodically share our notes on companies we’ve studied in the recent past but currently have no vested interest in (we may invest in or sell shares in the companies mentioned at any time). The notes are raw and not updated, and the “as of” date for the data is given at the start of the notes. The first 13 editions in the series can be found hereherehereherehereherehere,  here,  herehere,  here, here, and here. Please share your thoughts on the series through the “Contact Us” page; your feedback will determine if we continue with it. Thanks in advance!

Start of notes for The Central and Eastern Europe Fund

  • Data as of 2024-11-09
  • Ticker: CEE
  • Exchange: NYSE
  • CEE is a closed-end fund that invests in equities and equity-linked securities in Central and Eastern Europe. It is managed by DWS, which has €933 billion in assets under management as of 30 September 2024.
  • CEE’s NAV per share as of 30 September 2024 is US$11.40, with total net assets of US$73 million, giving rise to about 6.4 million shares outstanding in the fund. Share price on 2024-11-09 is US$13.14.
  • CEE’s Russian holdings have been valued at zero since 14 March 2022. The manager of the fund has observed occasional privately negotiated transactions in depositary receipts of non-sanctioned Russian issuers taking place (at prices that are deeply discounted from those taking place through the facilities of the Moscow Stock Exchange). In May 2024, CEE was successful in selling depositary receipts of one non-sanctioned Russian issuer in such a privately negotiated transaction, resulting in positive impact to the fund’s net asset value. DWS will continue to monitor developments in this area and may make further opportunistic sales of depositary receipts for Russian securities. Three of CEE’s remaining 16 positions in Russian securities are “local shares” which cannot currently be sold. In addition, four positions are in securities of issuers that are subject to US sanctions that bar CEE from selling, unless special permissions are granted by the US. So CEE continues to value certain Russian securities at zero, unless it has received a recent bid for the security and the sale of the security would be permissible under the applicable sanctions and other laws and regulations. 
  • CEE’s Russian stocks as of 30 April 2024 are shown in Table 1. Unsure which stock was sold in May 2024, but it was a depository receipt. 
Table 1
  • Valuation on 2024-11-09:
    • 6.4 million shares outstanding
    • NAV of the Russian portfolio in Table 1 equates to US$9.88 per share for CEE (US$63.27 million divided by 6.4 million shares), so total NAV for CEE is US$21.28 (US$11.40 + US$9.88)
    • If we remove the value of the most valuable depository receipt (Novatek PSJC) to account for the sale of a depository receipt in May 2024, the NAV of the Russian portfolio in Table 1 equates to US$9.32 (US$59.64 million divided by 6.4 million shares), so total NAV for CEE is US$20.72
    • Stock price of US$13.14, so there’s a prospective return of around 60% if Russian stocks are no longer barred from being traded globally
  • CEE’s portfolio characteristics are shown in Figure 1 below:
Figure 1
  • A quick look at the current valuations of CEE’s 2024-09-30 top 10 holdings is shown in Table 2. It’s clear that most of the top 10 holdings carry very low valuations. The top 10 holdings account for 60% of CEE’s NAV. So CEE at its current state, even with the Russian holdings held at effectively zero, looks like a low-risk investment.
Table 2

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

What We’re Reading (Week Ending 22 March 2026)

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

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

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

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

Here are the articles for the week ending 22 March 2026:

1. Why Walmart and OpenAI Are Shaking Up Their Agentic Shopping Deal – Paresh Dave

Last year, OpenAI made a bet that it could boost revenue by charging a commission on purchases made through ChatGPT. It partnered with Walmart, Etsy, and other shops on an “agentic commerce” feature called Instant Checkout.

Walmart has made about 200,000 products available directly in chat responses, allowing consumers to provide their shipping and payment details to OpenAI and place their order within ChatGPT. For products like TVs, shoppers still have to open Walmart’s website to make a purchase the old-fashioned online way. Conversion rates—the percentage of users following through with a purchase of an item shown to them by ChatGPT—have been three times lower for the selection sold directly inside the chatbot than those that require clicking out…

…The approach solves what Danker says he believes is the biggest problem with Instant Checkout: It forces people to buy items individually. “They fear that when checkout happens automatically after every single item that they’re going to receive five boxes when they actually just want it all in one,” Danker says. “They generally don’t want to split the checkout experience, where it buys the one item, even though they had other items in their Walmart cart already.”…

…In the new experience, Walmart users log into Sparky the first time they encounter it in ChatGPT. Their basket from Walmart’s website or app and within ChatGPT will sync with another in the hopes of better reflecting people’s actual shopping habits. Consumers add peanut butter one day on the Walmart app, foil the next, and a birthday gift at the last second on the website before checking out…

…Walmart has good reason to want to get the experience in ChatGPT correct. The chatbot is now bringing in about twice the rate of new customers as search engines, Danker says. He suspects that’s because the power users of ChatGPT are not typical Walmart customers. But the retailer’s price, selection, and broad geographic footprint mean that its products are showing up in many ChatGPT responses.

Sparky was developed by Walmart, Danker says. But it relies on open source generative AI models combined with some retail-specific ones trained on decades of Walmart data. “We’re able to route certain questions to one model and certain questions to another because we find that the quality of answers differs,” Danker says. “It’s never stuck in any one.”…

…Sparky has been criticized by people purporting to work for Walmart on Reddit, and testimonials for the chatbot are difficult to find on social media. But half of Walmart app users have engaged with it, according to the company. While people typically use the app to search for staples such as milk and bananas, they ask Sparky about exotic items or for solutions to more complicated problems. Walmart US CEO David Guggina recently said Sparky users spend about 35 percent more per order than other shoppers.

Danker acknowledges that Sparky is slow and generates weak responses often enough that some consumers might dismiss it as unreliable. Danker says the priority this year is training Sparky to be more proactive, getting it to learn more about individual shoppers, and making it helpful across more of Walmart’s many departments, such as the pharmacy.

2. Uzbekistan is gathering pace – what to look at now – Swen Lorenz

Uzbekistan has recently been attracting growing attention from investors.

One reason is the country’s remarkable demographics. With a fertility rate of 3.5 children per woman – far above the replacement level of 2.1 – Uzbekistan has one of the fastest-growing populations outside Africa.

When the people of a nation with a 100% literacy rate decide to have many children, it’s usually a sign that they are optimistic about the future of their country…

…In 2019, I was part of one of the first organised investor trips to Uzbekistan. The country had only just begun to move beyond the legacy of the Soviet Union and its late dictator, Islam Karimov. As I described at the time in an extensive three-part article, there were strong indications that Uzbekistan would embark on a programme of capital market reforms and privatisations.

However, the process proved slower than expected. It’s difficult to say whether Covid, domestic policies, or a combination of both slowed the reform momentum…

…Recently, however, circumstances have begun to change, both for frontier markets in general and for Uzbekistan in particular. The country’s demographics have also attracted growing attention from investors, amid the global debate about low birth rates and their knock-on effects on economies and asset prices. Over the past four years, Uzbekistan’s population has grown by an average of 700,000 people per year – more than the population of the country’s second-largest city, Samarkand…

…In Uzbekistan, Uzum may do just that.

The company began as an e-commerce marketplace but has since expanded into financial services, consumer lending, and express food delivery. Its integrated ecosystem could eventually resemble the “super app” model that has delivered spectacular investment successes elsewhere.

Today, Uzum’s ecosystem reaches about 20 million users – more than half of Uzbekistan’s adult population.

Early investors in the company will be delighted.

Founded less than five years ago, Uzum is already valued at USD 2.3bn. On 10 March 2026, it announced a new funding round at a valuation 53% higher than the one completed just seven months earlier.

Still described as a “startup” in media reports, Uzum generated revenue of USD 691m in 2025, up from USD 505m the previous year. Net income reached USD 176m.

3. Agents Over Bubbles – Ben Thompson

You need agency to use agents, and yes, the number of people who will have that agency are probably far fewer than those who might use a chatbot. Of course you can make the (almost certainly accurate) case that chatbots will become agent managers in their own right, but the more critical observation is that by abstracting humans away from direct model management any one single human can control multiple agents.

What this means in terms of compute — and by extension, economic impact — is that it actually won’t require that many people with agency to drastically increase the amount of compute that is actively utilized to create products with meaningful economic impact. In other words, the rise of agents doesn’t just mean a dramatic increase in compute, but also a narrowing of the need for widescale adoption by humans for that demand to manifest. Yes, AI still needs agency; it just doesn’t need agency from that many people for its impact to be profound…

… Most consumers mostly do just want to consume content (which, I would add, means he should be more worried about the Neo, not less). This is why your favorite productivity application always ends up pivoting to the enterprise: it is companies who are willing to pay for productivity, because they are the ones actually paying for the workers who they want to be more productive.

It’s reasonable to expect this to apply to AI as well: the most compelling consumer applications of AI, at least in the near term, are Google and Meta’s advertising businesses, which sit alongside content. By the same token, it was always unrealistic for OpenAI to think that it could convert more than a small percentage of consumers into subscribers; that’s both why an ad model is essential, and also why that won’t be enough to pay the bills. It’s definitely the case that most people don’t want to pay for AI; it remains to be seen if they want to use it enough to make the ad model work.

That is another way of saying that Anthropic got it right by focusing almost entirely on the enterprise market: companies have a demonstrated willingness to pay for software that makes their employees more productive, and AI certainly fits the bill in that regard. What makes enterprise executives truly salivate, however, is the prospect of AI not simply eliminating jobs, but doing so precisely because that makes the company as a whole more productive.

It’s always been the case, even in large companies, that a relatively small number of people actually move the needle and drive the company forward in meaningful ways. That drive, however, has been filtered through a huge apparatus, filled with humans, who accelerate the effort in some vectors, and retard it in others. That apparatus makes broad impact possible, but it carries massive coordination costs.

Agents, however, will tilt much more heavily towards pure acceleration, making those drivers of value much more impactful. I’m sympathetic to the argument that the best companies will want to use AI to do more, not simply save money; the reality of large organizations, however, is that the positive impact of AI will not be in eliminating jobs, but rather replacing hard-to-manage-and-motivate human cogs in the organizational machine with agents that not only do what they are told but do so tirelessly and continuously until the job is done.

This only makes the argument that we are not in a bubble that much more compelling:

  • First, all of the weaknesses of LLMs are being addressed by exponential increases in compute.
  • Second, the number of people who need to wield AI effectively for demand to skyrocket is decreasing.
  • Third, the economic returns from using agents aren’t just impactful on the bottom line, but the top line as well.

In this context, is it any wonder that every single hyperscaler says that demand for compute exceeds supply, and that every single hyperscaler is, in the face of stock market skepticism, announcing capex plans that blow away expectations?…

… I noted above that what made Opus 4.5 compelling was not the model release itself, but changes to the Claude Code harness that made it suddenly dramatically more useful. What this means is that model performance isn’t the only thing that matters: the integration between model and harness is where true agent differentiation is found.

This is a very big deal when it comes to figuring out the future structure of the AI industry and where profits will flow, because profits flow away from modular parts of the value chain — which are commoditized — and flow towards integrated parts of the value chain, which are differentiated. Apple is of course the ultimate example of this: its hardware is not commoditized because it is integrated with their software, which is why Apple can charge sustainably higher prices and capture nearly the entirety of the PC and smartphone sector profits.

It follows, then, that if agents require integration between model and harness, that the companies building that integration — specifically Anthropic and OpenAI (Gemini is a strong model, but Google hasn’t yet shipped a compelling harness) — are actually poised to be significantly more profitable than it might have seemed as recently as late last year. And, by the same token, companies who were betting on model commoditization may struggle to deliver competitive products…

…What matters in terms of this Article, however, is that if agents are making Anthropic and OpenAI the point of integration in the value chain, then the bubble argument that these companies are overvalued, or that the massive investments other companies are making on their behalf in data centers is unwarranted, may not be correct.

I must, in the end, address my opening parenthetical: I’ve long maintained that there is no need to be worried about a bubble as long as everyone is worried about a bubble; it’s the moment when caution is flung to the wind and assurances are made that this is definitely not a bubble that we might actually be in one. And, well, I think the rise of agents means we are not in a bubble. The capex is warranted, and Anthropic and OpenAI look more durable than ever. If my declaring there is no bubble means there is one, then so be it!

4. The “secret” share that allows you to invest in North Korea right now (part 2) – Swen Lorenz

Chung Ju-young was the founder of Hyundai, THE South Korean conglomerate (“chaebol”) in the decades after the Korean War. Today, it’s Samsung that takes the crown among South Korean companies. But back in the 1970s and 1980s, Hyundai was the country’s biggest and most powerful corporation.

Hyundai suffered mightily under the 1997-98 Asian debt crisis and a seemingly never-ending family feud. However, this never dented Chairman Chung Ju-young’s passion for helping to make amends between the two Koreas.

In 1998, he led a herd of 500 cows over a North/South Korean border crossing as a symbol of future economic collaboration between two countries…

…That same year, Chung Ju-young and one of his sons, Chung Mong-hun, started offering tours to North Korea’s famous iconic Kungmangsan Mountain. With special permission from North Korea’s regime, their tourist groups initially traveled to the country’s mountain area by sea. Later, they even got permission to take South Korean visitors across the infamous Demilitarized Zone (DMZ).

The crowning glory of the Hyundai family’s efforts to bring both countries together, though, was the construction of the Kaesong Industrial Region, a special administrative region that was carved out as a place where South Korean companies could operate using cheap North Korean labor. The industrial park attracted 124 companies and grew to employ over 50,000 North Korean workers. It is located ten kilometers (six miles) to the North of the DMZ…

…In 2008, a South Korean tourist got shot and killed by a North Korean soldier. The tragic incident led to all further tours getting canceled until further notice.

Kaesong is currently closed, too. North Korea’s ballistic missile tests in 2016 made the South Korean government ask all companies to shut down operations. The site was professionally mothballed, i.e., it’s maintained but not currently open.

Tragedy struck in the family, too. Not only did Hyundai Group’s founder die of old age in 2001. His son, Chung Mong-hun, committed suicide in 2003 after it was revealed that he had used company funds to pay bribes in North Korea.

Thus ended the drive for economic reunification that Chung Ju-young had mostly focused under the umbrella of one of the family companies, Hyundai Asan…

…Back in the days of the late founder and his late son, Hyundai Asan negotiated agreements that went way further than merely operating tour groups and the Kaesong Industrial Park.

Hyundai Asan also has “exclusive business rights” to the following areas of the North Korean economy:

Electricity: Construction of power plants and expansion of existing ones.

Communication: Establishing and operating wireless services.

Rail: Reconnecting railroads between specific regions of both countries.

Airport: Construction of an airport in the tourist region of Kumgangsan.

Dam building: Construction of a dam near the Imjin River.

Water resources: Supply of water from the Kumgangsan Dam to the South.

Tourism: Development of tourism at specific, significant historic sites.

These are precisely the kind of large-scale infrastructure projects that the leaders of both Koreas have identified as priority areas for the potential future economic development of North Korea. Actually, the reopening of the Kaesong Industrial Complex and the construction of railway lines were a high priority part of the agenda of this week’s bilateral summit.

These contracts were all signed between Hyundai Asan and the North Korean government, which makes them both compelling and questionable. The North Korean government could decide not to honor the contracts. However, a country that is seemingly getting ready to welcome international investment back into the fold would be ill-advised to start the process by screwing one of its longest-standing allies in economic development.

It’s highly likely that there are still close contacts between the Hyundai family and North Korea’s dictator, Kim Jong-un. The widow of Chung Mong-hun is chairing Hyundai Asan, and she has made a point of keeping the vision of the company becoming a trailblazing investor in North Korea alive.

5. Rory Johnston on How Oil Could Surge to Over $200 a Barrel | Odd Lots (Transcript here) – Tracy Alloway, Joe Weisenthal, and Rory Johnston

Rory: What we talk about when we talk about the blowout in the product market is we’re talking about – so crude oil has a supply and demand curve as you see in econ 101. Then each individual product – gasoline, jet fuel, diesel, naphtha, petrochemical feed, everything else, shipping fuel – they all have their own specific supply and demand curves which this market becomes fractally complicated very quickly.

But to simplify what we’re talking about, it’s a refinery taking let’s say a barrel of oil for $100 which is roughly where we’re trading right now in Brent. We’re kind of jumping to another side of $100. They take a barrel of oil of $100 and they refine into a bunch of different products. The premiums they get for those products are what we typically call the crack spread, or the difference between crude and a refined product that is yielded from a refinery. And the refinery margin is essentially the weighted average blend of all those crack spreads, plus other costs and everything else.

But what’s happening right now, and the reason that we’re actually seeing the refined product market jump ahead of the consequences in the crude oil market, is that the worst thing for a refinery is literally running out of crude feed stock. And actually full credit to June Goh of Sparta Commodities for educating me more on this because I would have thought, “Wow, product markets are going insane. Refiners must be chasing as hard as they can, running as fast as they can, to capture those exceptionally high margins.” But the issue is that for them, shutting down a facility is the worst case scenario. This is basically a giant flowing chemistry set that if you turn it off, it’s really really hard to turn back on properly and it takes a lot of time and money and downtime and then you’re not capturing any of those margins.

So what the refiners are doing – these are the refineries in Asia that basically have a massive 20 million barrel a day gap coming towards them in the market in terms of feed stock – they’re preemptively reducing activity, reducing the rate of runs so they can extend their runway basically for how long they can remain in the market at all. So this means that with crude oil 2 weeks ago, we still had crude flowing out of the Gulf. It takes a month or two for those cargos to get to where they’re going. It’s only then that we’ll really start to feel the consequence and the supply loss and the inventory drain down. But with the refiners in Asia in particular, preemptively adjusting down their run rates, we’re seeing the impacts in Asian product markets immediately…

…Joe: Talk to us a little bit more about the sort of relationship between the duration of the war and the ability to flip the switch back. Because the president’s communication does seem to be like, we’re paying a price right now, but it’s going to be worth it and then prices are going to come down. As this goes on longer and longer, to what degree does everything compound and make it more difficult to go back to normal?

Rory: I was listening to actually your podcast on the Strait of Hormuz flow with the shipping experts exactly on this topic. I think you guys nailed it there, that this gets worse every single day it goes on. But let’s talk through the ways it gets worse.

When we talk about the Strait of Hormuz, you could think of it very simply as the world’s largest pipeline, or a big giant garden hose through which 20 million barrels of petroleum flows. When the Strait was closed initially for the first day, 2, 3 days, it’s like a kink in the garden hose. If the conflict had ended then, which is honestly when I expected it to end, you would unkink the garden hose and things would get back to normal pretty quickly. No harm, no foul. Some issues, but you can make that up pretty quickly.

But now, 10-plus days into this, we now have the equivalent of a 200 million barrel air gap in the global flow of petroleum. First of all – not to mention that in addition to this kind of kink in the garden hose – that pressure has built up because these countries can’t export out of this region anymore. Countries like Iraq and Kuwait in particular, both of which lack sufficient domestic storage capacity because they just export the stuff all the time for decades and decades, they have been forced to shut in production. Iraq as of yesterday shut in over 3 million barrels a day of production from its southern Basra fields. That is just Iraq alone so far. That is the same size as the feared loss of Russian supply in April of 2022 that sent the market ripping higher above $120 Brent. Just for perspective – and we didn’t end up losing that supply in the Russia case – we only lost one briefly and it came back. But in Iraq we’ve already lost, Kuwait we’ve already lost it, in the Emirates and Saudi Arabia, they have more storage capacity and a bit more optionality. There’s a pipeline to the west coast in the Red Sea in Saudi Arabia that can divert some of the flow. Similarly with the United Arab Emirates, you can divert some flow out the port of Fujairah. The pipeline to the west coast of Saudi Arabia can get bombed, if we get to an existential battle, this keeps grinding. Same with the ports of Fujairah, I think. These systems can all be broken. So you’ve lost that. You’ve lost supply structurally at least for weeks, potentially a month, even if the thing resumed, even if flow resumed tomorrow. That’s on the exporter, the supply side.

On the demand side, on the importers in Asia. Like I said, you’ve already begun to lose refining runs. Jet fuel is very particular, I think rightfully so. You don’t store as much of it typically. I think part of that giant spike in fuel prices, in jet fuel in particular, was this sudden loss of supply, not a lot of inventory cover and all of a sudden, you had all of these airlines all across Asia like, “Wow, I’m not hedged for this. I need to get every barrel I can right now.” So I think even if this resolved, which it doesn’t look like it’s going to, but even if it did, now we have a big air gap in the system that’s going to need to work itself out. And all of these different supply chains will probably end up taking 2-3 months minimum to get back to something resembling normal. And it doesn’t look like we’re about to resume flow through the Strait of Hormuz right now, despite what the White House says.

Tracy: I have what is perhaps a silly question, but does demand destruction actually exist when it comes to higher oil prices? I know that airlines will go bankrupt eventually because of high oil prices. But it feels like it is one of those things that you want to keep using for as long as you are physically or financially capable of doing so.

Rory: I’ll talk about three different angles here. The first is the difference between the elasticity of price versus the elasticity of income. When we typically think about demand destruction, we think primarily through the lens of “Prices got too high, so I’m not going to drive to work today.” There’s also the angle of prices got so high, they crashed the economy and you lost your job so you no longer have to drive to work. That is one angle if this goes on for much longer. We’re talking serious recession, if not outright global depressionary conditions if the Strait remains closed for a month-plus, two months.

I agree. I’m not going to stop driving my kid to school. I have a fairly high tolerance for high prices. But we live in wealthy advanced societies. I think what you saw for instance in 2022 I think is illustrative of this in the LG market when there was a very, very high-profile event when a contracted LG tanker that was supposed to land in Pakistan got diverted and ended up in Europe because the Europeans were willing to pay way way more and basically the LG supplier broke the contract to service that, which economics dictated. But I think the human cost was very real. Pakistan just couldn’t afford it.

So what you’re going to see here, let’s say in this horrible scenario where the Strait of Hormuz remains closed until 2027, this is what the world would look like. What you would end up seeing is massive demand destruction from lower income countries that can no longer afford to get those barrels and attract them to their shores in the first place. You and I would see this as massively surging prices at the pump and we would grumble and it would it would sap our consumer-spending-energy, etc., etc. But the barrels would likely be there. We are in the countries that will attract the most supplies because we’re willing to pay the highest prices. But other lower income countries in the world, it’s not going to be a price issue for them. It’s going to be an outright shortage. And that I think is how demand destruction in this particular instance would work…

…Tracy: I don’t think we’ve mentioned OPEC once in this conversation, which probably says something about OPEC’s relevance today. But to what extent can OPEC respond with a big supply increase and maybe shift some production away from the Gulf and start firing up output elsewhere?

Rory: It’s a great question and unfortunately the Strait of Hormuz is a risk concept, shortcircuits the OPEC’s normal reaction. When you’re talking about spare capacity, virtually all the spare capacity in OPEC is on the wrong side of the Strait of Hormuz. It’s in Iraq, Kuwait, Saudi Arabia, and the UAE. All of that is currently caught up in this. I think that’s part of the challenge and why the Strait of Hormuz was always the boogeyman scenario. There’s no real normal way that the market can get around it.

The one major producer that’s within OPEC that is likely the single greatest beneficiary of this is actually Moscow. The Trump administration has put a lot of pressure on what I call the Big Sanctioned Three. You’ve got Iran, Venezuela, and Russia. Venezuela we have a regime change. Iran was in the process of doing so or trying to. And then in Russia, they said that they were prioritizing the war in Ukraine and they were at various points. But now they had actually been putting a lot of pressure on the Russian oil trade. India, which was one of the largest importers of Russian crude, largest seaboard importer of Russian crude after the invasion with the price cap and everything else, they got under increasing pressure on two fronts. One, the Trump administration issued blocking sanctions, really really tough sanctions that were on Iran, issued those on Roseneft and Lukoil, which are Russia’s two largest crude oil exporting companies. The Indians didn’t like that and they started pulling back purchases there because they’re afraid of the sanctions risk. But in addition, Trump actually imposed a specific punitive 25% tariff on India for being such large importers of Russian oil. So between October and say January, we saw Indian imports of Russian crude drop from over 2 million barrels a day to about 1 million barrels a day. That Russian oil, a little bit was going to China, but it wasn’t finding many other buyers. So Tracy mentioned that we were building up lots and lots of oil and water. That’s where a lot of this was ending up. So the prices for these, the discounts that were suffered by Russian barrels were exploding, they were building up on water. The oil industry was on its back foot and probably going to start contracting pretty meaningfully if that continued.

Now what are you seeing? All of a sudden one of the major places that has any incremental supply at all to share around the world is Russia. India’s back in the market for Russian crude and the White House actually explicitly gave them a waiver for those sanctions that I mentioned previously. So they’re going to start importing a lot more Russian crude because they need to. Even the Europeans have started clamoring about easing sanctions or reopening flow on the Druzbha pipeline to Eastern Europe and into Germany. It’s a mess. It’s a mess that overwhelmingly serves the interests of the Kremlin above any other single national actor in this oil market…

… Rory: Let’s use an example of the US Gulf Coast which is the major refining hub of the United States where you have all of the outlet from the Permian and all the rest of the oil fields and directly into that refining hub, much of which is exported. You see a lot of diesel exports, about a million, million and a half barrels a day of diesel exports out of the region, largely going to Mexico, Latin America and other areas. If you banned exports, let’s say across the board, what you would do is you would start building those inventories at that pace in the US Gulf Coast. You would start overflowing your tanks of diesel. Diesel prices would crash. That would be great briefly for your drivers of big diesel trucks and shipping etc. That’s great.

But eventually you reach the stage where it’s the same kind of thing as you’re seeing from the Gulf exporters. You run out of storage space and all of a sudden you can’t produce any more diesel. You can’t put it anywhere. That begins to overflow your tanks. You need to cut runs. That’s when things get bad because then you’re starting to lose gasoline supply. You’re starting to lose everything else as well. And all of a sudden you’re going to get turned into an importer of various fuels.


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 no vested interest in any companies mentioned. Holdings are subject to change at any time.

Still More Of The Latest Thoughts From American Technology Companies On AI (2025 Q4)

A collection of quotes on artificial intelligence, or AI, from the management teams of US-listed technology companies in the 2025 Q4 earnings season.

A few weeks ago, I published Even More Of The Latest Thoughts From American Technology Companies On AI (2025 Q4). In it, I shared commentary in earnings conference calls for the fourth quarter of 2025, 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 2025’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:

With that, here are the latest commentary, in no particular order:

Adobe (NASDAQ: ADBE)

Adobe’s AI-first ARR (annual recurring revenue) in 2025 Q4 (FY2026 Q1) tripled year-on-year; management thinks Adobe’s AI-first business will be the company’s next $1 billion business

Our new AI-first offerings ending ARR more than tripled year-over-year, reflecting progress against this opportunity with individuals and enterprises alike…

…What we had identified as the AI first sort of book of business. That tripled, but that should be our next $1 billion business.

Adobe’s management thinks the company’s success in AI will be underpinned by its deep understanding of the creativity domains, its access to vast data, its delivery of complex workflows, and its great brand; enterprises are increasingly asking Adobe for help on their AI strategy in their customer experience orchestration; management thinks agentic AI will further enable outcome-focused enterprise workflows, and Adobe is uniquely able to meet the needs of enterprises in these areas; emerging new platforms have always been additive to Adobe’s market opportunity; management intends to integrate Adobe with leading AI platforms including Anthropic, Google, and OpenAI; management is collaborating with global system integrators (GSIs) such as Accenture and Deloitte to drive technological transformation 

Adobe’s continued success in AI will be underpinned by our deep understanding of creativity domains, the vast amount of data to which we have access, delivery of complex workflows driving business outcomes, and a great brand across individuals, small and medium businesses and enterprises…

…, Adobe has always been a trusted partner for enterprises and we’re increasingly being asked to help them drive their AI strategy across customer experience orchestration (CXO) globally. Enterprises are looking to the combination of employees and automation to deliver on the demands of content and marketing at scale. Agentic AI will further enable outcome-focused enterprise workflows as customers look beyond speed to elevate creative differentiation, brand governance, and personalized experiences across channels. Adobe’s end-to-end solutions are uniquely designed to meet these needs at scale…

…Emerging new platforms have always been additive to our market opportunity. In addition to Windows, MAC, iOS, Android, Chrome and EDGE, we intend to integrate with leading AI platforms such as Anthropic, Google, Microsoft, NVIDIA and OpenAI— providing customers with access, choice, and flexibility. We’re jointly driving enterprise transformation at scale in collaboration with global leaders such as Accenture, Cognizant, Deloitte, dentsu, EY, IBM, Infosys, Omnicom, Publicis, PWC, Stagwell, TCS and WPP.

Adobe’s management’s approach with AI is to expand access to AI in Creative Cloud and Acrobat, reach new audiences with Firefly and Express, and automate content production in Firefly Enterprise; AI usage at Adobe is growing quickly, with record generative credit consumption; Adobe’s content automation solutions are seeing record number of API (application programming interface) calls

Our approach is to expand access to AI across our existing audiences in products like Creative Cloud and Acrobat, reach new audiences with products like Firefly and Express, and help automate content production in enterprises with Firefly Enterprise…

…AI usage continues to grow quickly, as measured through record levels of generative credit consumption…

… Our content automation solutions continue to see strong enterprise adoption, as measured through record numbers of API calls.  These metrics highlight that we are executing against our strategy to empower individuals and businesses to create content in new ways in the era of AI.

Adobe’s management’s approach with AI across Business Professionals & Consumers is to deliver AI-powered applications that reinvent how users comprehend, create and share content; AI Assistant MAU doubled year-on-year in 2025 Q4 (FY2026 Q1) and Express MAU tripled; Express is now used in 99% of US Fortune 500 companies; Adobe Acrobat Studio, introduced recently, brings all of Adobe’s AI and creative capabilities into PDF tools, is off to a strong start

Our vision for Business Professionals & Consumers is to deliver AI-powered applications that reinvent how users comprehend, create and share content…

…PDF Spaces transforms collections of files and links into dynamic knowledge hubs that allow you to easily collaborate with others. Acrobat AI Assistant provides users conversational experiences that help them comprehend information faster and more accurately with an individual PDF or across documents in a PDF Space. Our Acrobat and Express integrations empower users to turn content they are consuming into generated presentations, infographics, audio summaries and more. It’s clear that these AI-based capabilities are resonating with users, as AI Assistant MAU doubled year over year and Express MAU tripled year over year. Express is now used in 99% of U.S. Fortune 500 companies.

In Q3, we introduced Adobe Acrobat Studio, a single offering that brings together all these AI and creative capabilities with the PDF tools users know and rely on. Subscription upgrades to offerings that include Acrobat Studio value are off to a strong start across routes to market, including Adobe.com and enterprise license renewals.

Adobe’s management is embedding Adobe products directly into chatbots; management launched Acrobat and Express for ChatGPT in 2025 Q4 (FY2026 Q1); management will soon launch similar integrations into Copilot, Claude, and Gemini; management recently launched a Photoshop conversational editing experience in ChatGPT; brands can now create ads for ChatGPT with Adobe’s tools

We are embedding Adobe’s capabilities directly into new conversational platforms. In Q1, we launched both Acrobat and Express for ChatGPT, significantly expanding the reach of our creativity and productivity workflows. You can expect to see similar integrations into Copilot, Claude and Gemini as those platforms support integrated application experiences…

…Photoshop launched a conversational editing experience in ChatGPT…

…Partnership in the OpenAI initiative to enable brands to create ads for ChatGPT

Adobe’s management’s approach with AI across Creators and Creative Professionals is to empower everyone to create, with Firefly, Adobe’s all-in-one creative AI studio, as the centerpiece; enterprises are increasingly turning to Firefly Enterprise to unlock content automation; Firefly users can access over 30 industry-leading models from both Adobe and leading AI labs; Firefly users can edit and assemble images, videos and audio with prompts and in an integrated way with Photoshop and Express; Firefly’s generative credit consumption was up 45% sequentially in 2025 Q4 (FY2026 Q1); Firefly’s generative credit consumption is skewing toward higher-value modalities, with video generative actions up 8x from a year ago and audio generative actions up 2x; Firefly subscription and credit pack ending ARR was up 75% sequentially in 2025 Q4 (FY2026 Q1); Adobe’s management has continued to add new AI capabilities into Creative Cloud applications, which has led to higher AI usage and in turn, a nice ramp in purchases of Firefly credit packs; Adobe’s Creators & Creative Professionals segment saw the traditional Stock business decline faster than management expected; the entire Firefly ecosystem’s ending ARR exceeded $250 million in 2025 Q4 (FY2026 Q1)

Our strategy for Creators & Creative Professionals is to empower everyone to create – from first-time creators to seasoned professionals to large enterprises seeking to scale content production. Firefly, an all-in-one creative AI studio, is the right tool for the next generation of creators and creative professionals…

…Enterprises are increasingly turning to Firefly Enterprise to unlock a new era of content automation.

Firefly is quickly becoming the go-to destination for content generation, ideation and assembly. Users can generate with over 30 industry-leading models, including Adobe, Google and OpenAI. They can collaboratively ideate with stakeholders in Adobe Firefly Boards. They can edit and assemble image, video and audio using Firefly’s prompt-based editing capabilities with integrated Photoshop and Express web journeys. Firefly momentum is strong, with generative credit consumption growing over 45% quarter over quarter. While that growth is broad-based, generations are skewing toward higher-value modalities, with video generative actions growing more than 8x year over year and audio generative actions doubling year over year, reflecting customers moving deeper into AI-assisted creation across the full creative process. As a result, Firefly subscription and credit pack ending ARR grew 75% quarter over quarter.

Creative Cloud applications continue to embed new AI capabilities, making users far more productive. Photoshop added new partner models and support for higher resolution image generation and editing. Illustrator expanded its generative design capabilities with models from OpenAI, Ideogram, and Google to support frequent vector workflows. Premiere added AI Object Mask, which quickly became one of the most used AI features in the application. As Creative Cloud users increase AI usage, we are seeing purchases of Firefly credit packs ramp nicely…

…While Q1 had many highlights, our traditional Stock business saw a steeper decline than we expected. This shift is playing out more quickly than we had planned for and our focus remains on giving customers meaningful choice between stock and generative AI as they build their creative and marketing workflows…

Firefly ending ARR, across Firefly App, Firefly credit packs, and Firefly Enterprise exceeded $250 million

Firefly Enterprise combines Firefly Services and Firefly Foundry; Firefly Services provides APIs for automated content production workflows, including 3D digital twin workflows, image and video resizing across every social and digital channel, campaign variant generation, and more; Firefly Foundry allows enterprises to build private, deeply tuned AI models trained on their own IP (intellectual property), and gives enterprises a commercially safe model that is able to accurately generate their branded assets; Firefly Enterprise’s new customer acquisition was up 50% in 2025 Q4 (FY2026 Q1) from a year ago; Firefly Foundry recently signed new partnerships in the media & entertainment vertical

Firefly Enterprise, the combination of Firefly Services and Firefly Foundry, is empowering the world’s largest brands to scale content production to unprecedented levels. Firefly Services provide enterprise-grade APIs, giving businesses more than 30 content production capabilities which can be run in automated workflows. These include 3D digital twin workflows for showcasing physical products, image and video resizing across every social and digital channel, and campaign variant generation and assembly for personalized marketing content. Firefly Foundry enables the world’s largest marketing teams and media companies to build private, deeply tuned AI models trained on their own IP. Unlike generic AI models, Firefly Foundry gives enterprises a commercially safe model that understands and is able to accurately generate their branded assets. Together, these products are driving measurable business outcomes, by increasing production scale, accelerating velocity and reducing costs. Firefly Enterprise new customer acquisition grew 50% year over year…

…Firefly Foundry continues to build momentum in the media & entertainment vertical, with partnerships including B5 Studios, Cantina Creative, Creative Artists Agency, United Talent Agency and WME. 

Adobe’s management sees Adobe as the  trusted partner for AI-powered Customer Experience Orchestration (CXO) for enterprises; management recently introduced new agents in Adobe Experience Platform (AEP); management recently expanded AEP’s Agent Orchestrator capabilities; AEP now handles 35 trillion segment evaluations and 70 billion profile activations daily; subscription revenue for AEP and native apps grew 30% year-on-year in 2025 Q4 (FY2026 Q1); traffic to retail sites from LLMs (large language models) was up 7x during the 2025 holiday season; traffic from LLMs to retail sites convert 31% higher and generate 254% more revenue per visit; Adobe has products that help brands engage consumers across their owned properties, search, social media, LLMs and agentic channels; Adobe LLM Optimiser helps enterprises improve their websites’ discoverability by LLMs; Adobe Brand Concierge helps enterprises configure and manage agentic AI experiences on their websites and mobile apps; Adobe is in the process of acquiring Semrush and management expects Semrush to help Adobe provide a comprehensive solution for enterprises to shape brand-image across their own websites, LLMs, and traditional search; 650 customer trials for  Adobe LLM Optimizer, Sites Optimizer, and Brand Concierge are underway; AEP AI Assistant is now used by 70% of all AEP customers;   

Adobe has become the trusted partner for AI-powered Customer Experience Orchestration (CXO) through our thought leadership, rapid innovation, and omnichannel capabilities, while providing the security, reliability, data governance, global scale, and partner ecosystem that enterprises require. 

Adobe’s unified CXO platform provides solutions for brand visibility, content supply chain and customer engagement. Adobe Experience Platform (AEP) is a leading platform for digital customer engagement and brings together new AI-powered apps and agents to transform how businesses build, deliver and optimize marketing campaigns and customer experiences, as well as reduce costs. In Q1, we introduced new AEP Agents along with expanded Agent Orchestrator capabilities, now available to all AEP customers, via a Try and Buy program. The scale of our platform has grown to over 35 trillion segment evaluations and more than 70 billion profile activations per day. Subscription revenue for AEP and native apps grew over 30% year over year, demonstrating continued momentum and value realization…

…According to Adobe Digital Insights, during the 2025 holiday season, traffic to retail sites from LLMs increased nearly 7x, bringing qualified referrals that convert 31% higher and generate 254% more revenue per visit. Adobe’s brand visibility solution, which includes Adobe Experience Manager, Adobe LLM Optimizer and Adobe Brand Concierge, empowers brands to engage consumers across their owned properties, search, social media, LLMs and agentic channels. Adobe LLM Optimizer enables enterprises to enhance the discoverability of their websites by LLMs and significantly increase their organic traffic. Adobe Brand Concierge is an AI-first application enabling businesses to configure and manage agentic AI experiences on their websites and mobile apps to guide consumers from exploration to purchase decisions, using immersive and conversational experiences. We expect our pending acquisition of Semrush will expand our offering to provide marketers with a comprehensive solution to shape how their brands appear across their own websites, LLMs, traditional search and the wider web…

…Strong customer demand for our agentic web offerings with over 650 customer trials underway for Adobe LLM Optimizer, Sites Optimizer, and Brand Concierge…

…Continued adoption and momentum for AEP AI Assistant with 70% of all AEP customers using the agentic capabilities;

Adobe’s management recently delivered innovation that enabled GenStudio-created content assets to flow directly into activation workflows across Adobe’s stack and some of the largest 3rd-party advertising platforms; Adobe GenStudio’s family of products saw ending ARR grow 30% year-on-year in 2025 Q4 (FY2026 Q1)

GenStudio is our comprehensive content supply chain offering, spanning content ideation, creation, production, and activation…

… In Q1, we delivered breakthrough innovations enabling GenStudiocreated assets to flow directly into activation workflows across the Adobe stack and a broad ecosystem of advertising platforms including Amazon Ads, Google, LinkedIn, and Meta. Ending ARR for the Adobe GenStudio family of products grew over 30% year over year as the world’s leading brands and agencies increasingly turn to Adobe to power their content supply chain.

Adobe’s management thinks that only 2-3 really large LLMs (large language models) will succeed because people are not interested in the model but the workflows; management thinks it’s the right strategic move for Adobe to provide a choice of models because customers can then use the right models for the right use cases; management thinks it’s a win-win for Adobe and the model providers for Adobe to be providing different models because the model providers want access to customers while Adobe wants different model-capabilities

My take on the model side would be as follows, which is they’re going to be 2 or 3 really large language models that actually succeed. All of these individual models that exist, small model companies in 1 part of a media ecosystem, I just don’t see how long term they survive because people aren’t interested in just the model, they’re interested in the workflow. And so for us, offering customers with that choice was actually very strategic because we can actually then provide for all of our creative customers the right model for the right case because these all have different brands…

…As it relates to the support of all these models, I think it’s a win-win. They would like access to customers, which Adobe has, and we would like access to these different models because they have different brand attributes. And I think if you look at the larger companies like Google, we’re actually with them and with Nano banana. It’s been a great partnership because we are providing them with a lot of customers and they’re providing us with great technology.

Okta (NASDAQ: OKTA)

Okta’s management thinks the market for securing AI agents is still early; management thinks that Okta is well positioned to help companies secure their AI agents; 91% of organisations surveyed by Okta are using AI, but only 10% have a governance strategy for their use of AI; when management is speaking to customers, they are asking how Okta can help them manage agents securely; management thinks that the surface area for threat actors increases as AI becomes embedded in more workflows and automations; management sees AI agents as a new identity type, and securing identities is Okta’s expertise; Okta can secure the entire agentic lifecycle and gives customers the freedom to deploy agents without any ecosystem lock-in; Okta’s solutions for securing AI agents, Auth0 for AI Agents and Okta for AI agents, treats AI agents similarly as human users; management believes that AI agents are the future of software; Okta for AI Agents became available in early access only in January 2026; Okta’s solutions can enable organisations to observe, govern, and secure the entire life cycle of an AI agent; management thinks identity is even more important in the agentic world than before; management thinks Okta for AI Agents is more unique and differentiated than Auth0 for AI Agents; Okta for AI Agents can help customers understand what different agents are doing;

I mentioned that our portfolio of new products now includes our AI products, Auth0 for AI Agents and Okta for AI Agents. It is still early for this developing market, but as the leading modern identity solution for workforce and customer identity, Okta is uniquely positioned to help organizations combat the growing security threat that AI agents represent. The reality is that the AI revolution has moved faster than today’s security frameworks. According to Okta’s AI at Work report, 91% of surveyed organizations are already using AI but only 10% have a governance strategy in place.

In meetings that I have had with customers and prospects over the past six months, the vast majority of the conversations revolve around their AI initiatives and how Okta can help them build and manage agents securely. As AI becomes embedded in more workflows and automations, the growing number of exploitable entry points—from nonhuman identities to unsecured integrations—expands the attack surface for threat actors. It is clear that in order to get AI right, you have to get identity right. Okta was built to meet this challenge…

…AI agents are simply a new identity type, and protecting them is a natural extension of what we do best. Okta’s neutral and independent identity solution is uniquely positioned to secure and govern the entire agentic lifecycle and gives customers the freedom to deploy on any agent without ecosystem lock-in, all while strengthening their security posture. Our two-pronged solution with Auth0 and Okta for AI Agents treats AI agents with the same importance as humans and gives customers everything they need to secure this powerful new technology. 

We are still in the early stages, but we believe that in a few years, agents and agentic systems will not be the exception to how enterprise software is built and operated. They will be the rule. We believe that AI agents represent nothing less than the future of software…

…Okta for AI Agents, which became available in early access in January…

…With our solutions, developers, administrators and IT teams can ensure that the entire life cycle of an AI agent from initial design through active deployment is observable, governable and secure…

…Identity is at the center of — traditionally, in legacy technology, it was always at the center. And in this agentic world going forward, it’s becoming clear to everyone, it’s even a bigger deal than it was before…

…[Question] It seems like you’ve got a real competitive advantage on the Auth0 side. Could you maybe compare, and contrast initial takes for sales cycles, competitive dynamics and velocity of each? I know it’s still early stages, but is Okta for AI Agents in a more competitive market?

[Answer] I think Okta for AI Agents is more unique and more differentiated than maybe we would have expected. I think Auth0 for AI Agents is unique and differentiated as well. But I think maybe the sentiment you’re expressing is it’s different than what we’re seeing. Customers need a solution that’s pre-integrated to all these agentic systems. I mean there’s no good way for customers to even understand what all these vendors are doing in agentic. There’s no catalog of systems that says, Salesforce is doing this. ServiceNow is doing this, AgentCore is this, Google is doing this, Microsoft is doing this. And that’s what Okta for AI Agents does. And then on top of that, models connections and has policy for connections that connects users to different agents, agents to systems.

A financial services platform company is an existing Auth0 customer and it picked Auth0 for AI Agents to build AI agents; the financial services platform found Auth0 for AI Agents offered enterprise-grade identity for humans and agents, and secure access to 3rd-party MCP (model context protocol) servers

An existing Auth0 customer is building AI agents as part of their leading financial services platform. These agents will help the firm’s advisers make better and faster decisions, but to do so, the agents need access to sensitive customer information, which must be least-privileged. And they need to work with existing systems and third-party services inside the financial institution. The customer picked Auth0 for AI Agents as it met their stringent requirements for a secure, extensible platform to build and deploy agentic systems. They needed a solution that offered enterprise-grade identity for humans and agents while providing secure access to third-party MCP servers, all while acting as a single source of truth.

A global business and technology services provider is rolling out AI agents across multiple agent platforms and chose Okta for AI Agents to manage identities for its growing sprawl of agents; Okta is an independent agent-agnostic platform

Another notable deal that included Okta for AI Agents, which became available in early access in January was with a top global business and technology services provider. They chose Okta for AI Agents to help them discover, control and govern identities for their growing sprawl of agents. Rolling out AI agents across multiple agent platforms is key to their ongoing transformation and centralizing agentic identities in an independent agent-agnostic platform like Okta will strengthen their cybersecurity posture.

Okta for AI Agents and Auth0 for AI Agents contribute very little revenue at the moment because they are still very young products, but management thinks they can be a huge source of upside in the coming years; Okta for AI Agents and Auth0 for AI Agents will lead to higher growth in current RPO before it flows down to revenue

Okta for AI Agents is not even generally available yet, and Auth0 for AI Agents is — just was generally available at the beginning of the quarter. So it’s off to a huge start. Now the relative number is small compared to our $3 billion revenue run rate. But looking forward to next year, we’re very, very excited about the potential of these products…

…Because the agentic products are so new, it’s tough to pour too much into our assumptions about growth in terms of guidance. But I think those things could be a huge source of upside over and above the guidance in the years ahead…

…We’re not thinking about this as an opportunity just for FY ’27. This is an opportunity to be accretive to growth for FY ’28, ’29. And we’ll see the results, as you guys know, in current RPO first before we see it in revenue…

There is some confusion that Okta’s customers have between identity infrastructure and identity security; identity infrastructure and identity security are separate things, and Okta is the only company that does both; management sees both identity infrastructure and identity security as being really important for the agentic market; management is not seeing any big change in the competitive landscape for Okta in the agentic market for identity infrastructure and identity security

I think the biggest confusion people have is the distinction between identity infrastructure and identity security. And they hear the word identity, and they think if you’re sitting on top of identity and detecting threats and blocking threats, you’re also identity infrastructure. So that’s one of the big confusions. And when you look at the agentic market, they’re both really important. It’s the identity security, making sure the agents are monitored and checked that they can’t go out of bounds. But just the infrastructure, just the ability for the agents to connect and just for tracking and visibility, that’s an infrastructure play. And we’re the only company that really does both. It’s at the security layer and the infrastructure layer. So I think that is maybe a little bit of a confusion and something that we’re working hard to make sure everyone understands the advantage of that position as well…

…From an Okta standpoint, we’re not seeing any material change in the competitive behavior in our transactions yet. Of course, we’re keeping our eye on the landscape.

Okta’s management has been speaking to customers, and they think there are 2 ways to charge for agents, (1) a multiplier on a person who uses agents, and (2) a fee that is based on the number of connections a non-human-connected agent has; it’s still early days for the pricing model Okta will adopt, but management sees the pricing as a nice step up for the company

We have these conversations with our 20,000 customers, we get really rapid feedback on how we can capture value, what would be most valuable for them, easy for them to consume. So it’s really a strategic advantage. We have this feedback loop, and we’ve actually structured the go-to-market team for AI agents to capture that feedback rapidly and feed it right back into the product teams. And what we’re seeing is that there’s really 2 ways that we charge for agents. One is like a multiplier on a person. So in the model where a human identity uses a number of agents to augment their work, there’s a multiplier on that agent or on that — what they pay for a person to what they pay for agents. And then also, there’s a — if the agent is not coupled to a person, there’s a — we sell it based on the number of connections the agent makes because that’s really the value. They want to secure those connections and filter on fine-grain access to all the back-end systems and the SaaS applications and the custom applications and data warehouses the agent connects to as they get more — the agent is more valuable as it has more fine-grained access to different things and it’s more secure. So there’s a multiple based on that. The pricing we’re working with these customers on is pretty early. So we’re — it’s a nice step up.

From a hypothetical point of view, Okta’s management thinks it’s really difficult and costly to vibe code a competing product to what Okta has built over the years because the vibe coder (1) needs to ensure there are no vulnerabilities and the product can scale, (2) is likely to incur significant inference costs, and (3) will suffer major costs if things wrong; Okta’s management is hearing customers share similar views as what they have when it comes to vibe coding; management is paranoid about competition from vibe coding and Okta is using LLMs and coding tools to build in the as fast possible; customers are telling Okta that they do not want to use startups for securing AI agents and they do not want to use just one provider for agents

[Question] When you look at what you’ve built over the years and the data that you’re sitting on, can you talk about sort of the structural advantages that you see over maybe some upstarts or some vibe coding alternatives?

[Answer] I think if you want to build what any SaaS company has done or what Okta has done, it’s years and years of hardening and making sure there’s no vulnerabilities and making sure it scales and it’s reliable. And it’s — if you — I don’t know what the inference cost to build that would be, but it would be pretty significant inference cost. And then if you flip it around, you just think about what’s the price of getting it wrong. And if getting it wrong, it’s hard to validate. It’s hard to prove you have it right. And if it’s wrong, you have a major security breach or you’re down and none of your agents or none of your people can access systems. So the cost of getting it wrong hypothetically and actually just the cost to do it theoretically, if it was even possible theoretically with an LLM or a tool would be pretty high. And that cost could change over time. We don’t know… But when you talk to customers and you hear their challenges and their opportunities, they — a lot of the same things are echoed. They want to identify key infrastructure pillars, and they want to standardize on them. And they see that as the unlock to hundreds of other decisions and hundreds of other builds versus buy decisions they have to make. And they’re putting foundational security, foundational identity in this bucket of things that they want to partner with a leader and trust it and go on top of that and figure everything else out. That’s what they’re telling me. And it kind of matches up with what I would think about hypothetically…

…We are paranoid. And we’re making sure that we are using all the latest technologies, LLMs, coding tools to make sure we have not only something that’s resilient and secure but has the best features and the best capabilities. And so we’re making sure that we build things internally as fast as anyone could build them because we — make no mistakes, the prize here that the whole industry is going after, which is this agentic future where digital labor is part of the TAM is a massive prize. And everyone is at some level; big picture is going to be going after this prize. And it’s exciting because it’s greatly expanded the TAM of what Okta could be…

…They’re reticent to trust a start-up with this critical piece of foundation because they know there’s going to be M&A, and they know there’s going to be start-ups going away. There are so many start-ups playing in this space that there’s bound to be a lot of failure, and they don’t want to build their whole foundation around something and have it be pulled out from under them. And the other factor that is in their minds is that they don’t want to be locked in. Think about — what’s happening at agentic and what’s happening in this world, these foundational models are moving incredibly fast. And its Anthropic foundational model that has the leap ahead and then it’s OpenAI and then it’s an open-source model and then it’s — and that’s going to continue for many years. And they don’t want to be locked into a certain stack and a certain set of tools. So they’re reticent to trust their foundational security with one provider, one platform. And back to the start-ups, they know that a bunch of these start-ups are going to get bought by the big players, so they’re thinking, even if I go with a start-up now, it’s going to get sold and then we’d be locked into Microsoft, and they don’t really want that.

Okta’s management thinks the proliferation of AI agents could massively expand Okta’s total addressable market (TAM); management thinks the SIEM (Security Information and Event Management) market is changing because of AI agents

Think about identity and what it’s been in the past. It’s roughly $20 billion TAM right now in terms of what people spend on the vendor data. We talk about an $80 billion TAM. I mean this could be bigger than — this could be the biggest part of cyber in a few years for sure. And it could be even bigger than that if you really think about the infrastructure that stitches together the entire agentic enterprise and is the plumbing that makes it run…

…The SIEM market is transitioning to be not just a platform for logging in and doing authentication authorization, but it’s a platform for customers building agentic interfaces to their customers and to agents coming into their systems. So Auth0 for AI Agents, that’s what it is. It’s a token vault. It helps agentic login. It helps customers hook other AI tools up to their customer login. And so I think over time, that market is evolving into something that’s hugely impactful and value delivering for our customers.

Okta’s management is working with standards bodies in building solutions for securing AI agents, but they do not think that there will be only one set of standards that will dominate

They’re all trying to do a ton of things and make their services more agentic and more compelling and security and the ability to have them be more enterprise-ready is on their list, but we have to convince them to get it higher on their list. So it’s not like a competing standard is like a prioritization thing. But remember, we are — we want to provide this identity infrastructure and make sure that we give people this solid foundation to build upon. And that’s going to require standardization just because it’s not going to — you can’t use a standard piece of foundation if everyone is doing their own things in a different way, which is why we’re working with standards bodies in general. It’s not just Cross App Access, but it’s an important part of the equation. But I wouldn’t say like the whole war rests on one specific standards body or standards battle. I think it will be an evolutionary thing over the next several years.

Sea Ltd (NYSE: SE)

Monee’s credit business grew in 2025 because of its AI-driven improvements in risk underwriting capabilities; management is experimenting with transformer-based AI models to assess credit risks and the experiments are showing very good performance

Our credit business expansion in 2025 was made possible by improvement in our risk underwriting capabilities. This improvement tapped on our rich ecosystem data and advancement in AI. Over the year, we made good progress training our risk models to better understand and map how user behavior evolves over time. We are better able to access individual repayment capacity alongside evolving market risk and dynamically adjust the credit limits as needed. Enhancing our models precision and performance enabled us to scale rapidly in 2025, while still maintaining a stable risk profile…

…We’re experimenting with the new AI — new risk model with the transformer structure as well to do a sort of a long sequence data training fit into our model to utilize many of the e-commerce data that we are not able to use in the traditional risk modeling, and it has been showing us very good performance.

Sea’s management has directed a lot of investments into AI for the Shopee business; for each AI investment in Shopee, management looks at the ROI (return on investment); Sea has used AI to improve the take rate on its advertising business; management recently rolled out multi-modal search for Shopee and the roll-out has delivered clear ROI; management is using AI to help sellers on Shopee; customers are able to talk to Shopee’s sellers with the help of AI and this helps sellers upsell and reduce manpower costs; Shopee has AI-powered tools for sellers to create pictures, videos, and descriptions of their products, and the tools have a fairly positive ROI

I think if you look at the e-commerce side, we do spend quite a lot of effort on the AI. I think you mentioned about AI investment there. For every — for the investment on the e-commerce for AI, we also look at the positive return of investment across the initiatives.

For example, if you look at one of the area we spend on AI is our search recommendation and also ad systems. The uplift on our ad take rate is a consequence of many of our AI efforts. For example, how do we actually expand the description for our products, we can understand the product better. For example, how can we expand the queries from the users, we can understand user intention better. Recently, we also rolled out a multimodal search in our platform as well. So user can search a picture plus a long description, and we are able to serve that just similar to how Gemini or ChatGPT would do. I think all those AI investment has a clear ROI.

We also spent quite a lot of effort using AI to help our sellers. For example, if you go to many of our countries, you can talk to the sellers with the help of AI already. So we built an AI chatbot for our sellers. Our sellers can customize it for their own purposes. This will help the seller to reduce their manpower and also make it not only reduce cost, but also have the better upsell for the buyers. And we also have tools for the seller to create videos and picture descriptions for their products, et cetera. All those typically come with a fairly positive return on investment for our ecosystems.

Tencent (OTC: TCEHY)

AI is benefitting Tencent’s game content development, user engagement, and marketing efficiency; management believes that Tencent’s business has a high degree of resilience in the age of AI because of (1) network effects, (2) a connection between the digital and physical world, (3) licensing requirements, (4) unique resources, (5) low take rates, and (6) proprietary data; AI can enable faster game development, but the gaming industry is already in a state of oversupply and it will be game-quality, which depends on human creativity, that will be the key success factor; management thinks games will benefit from AI as people will have more time on hand; 

AI contributes meaningfully to game content development, user engagement, and marketing efficiency. Video Accounts total time spent increased over 20% on upgraded recommendation algorithms and enriched content ecosystem. Our marketing services revenue growth outperforms the industry, benefiting from our upgraded ad tech model and newly introduced automatic campaign solution, AiM Plus…

…AI will affect every part of the technology industry, but some products and services are inherently more resilient than others. We believe that some of the characteristics of resilience would include network effects arising from consumer to consumer to content creator, and consumer to business interactions in descending order of strength. That’s number one. Number two, deep supply chain integration linking the worlds of bits with the world of atoms. Number three, stringent regulatory and licensing requirements. Number four, scarce or unique resources, including physical and intellectual properties. Number five, tick rates that are low compared to value provided or cost of switching. And number six, private data that is closed and interactive in nature. Using these criteria, we look across our major existing businesses. Our conclusion, which is supported by usage trends, is that each one of them has got a high degree of inherent resistance.

In particular, for our communication services, including Weixin, QQ, and Tencent Meeting, people use them to connect and interact with other people, largely their families, friends, and colleagues, and business partners. We believe this need for human interaction, together with the network effects and closed nature of the data arising from these interactions, have resulted in communication services being extremely sticky in the face of competing non-AI services in the past and will continue to be resilient versus AI-based services in the future.

Moving on to our games. They are also very resilient as our multiplayer games, especially PVP games, also enjoy network effects. Similar to sports, they are team-based in nature, and players play with and against other players. Just as people prefer to participate themselves or watch the teams they support compete in sports rather than watching AI sports, game players continue to enjoy the interaction with other humans that our games provide…

…While AI will enable more games to be made faster, the game industry is already in a position of excess supply, with 200,000 new games on mobile and 18,000 new games released on Steam every year. The limiting factor is that new games need to be high quality and more innovative than the best existing games, which in turn requires human creativity on top of cutting-edge technology. Game is a natural beneficiary of AI proliferation, also when people have more time at hand.

Our fintech services are also resilient as they depend on difficult to secure and retain licenses which are limited in nature and also set the boundary on how innovations can be introduced in an industry. We have also invested decades building a payment network of difficult to replicate rails into partner banks, merchants, and connecting them with more than 1 billion consumers, which brings its own network effects. Our mobile payment take rates are already among the lowest in the world, which we believe makes competing with us on price highly uneconomical.

Tencent’s management is deploying AI to strengthen the company’s core businesses; management thinks Tencent is at the forefront in China and globally in strengthening its core businesses with AI; Tencent is using generative AI in its games business to speed up content production, acquire new users, retain existing users, and improve the gameplay experience; Tencent is using generative AI in its marketing services to improve ad conversions and user experiences, allow advertisers to create more ads, and provide the AiM Plus automated advertising campaign solution; Tencent is using AI to enhance content recommendation for Video Accounts; Tencent is using AI to improve content production efficiency for digital content; Tencent is providing AI agents within its enterprise software products; Tencent is using AI in the Fintech business to improve credit scoring and fraud detection; management has integrated AI into Weixin to enhance the user experience in a wide range of areas; the improved user experience in Weixin include AI agents which autonomously interact on behalf of users within Weixin functionalities (see Point 3 for more on using Hunyuan to build AI agents in Weixin); management thinks the trend of AI agents, such as OpenClaw, being controlled through users’ existing communication apps, mean that Weixin and QQ, will be the most efficient place for users to interact with AI agents; management thinks Tencent is already seeing vey good ROI (return on investment) when applying AI to the company’s existing businesses

We believe that in each of our core businesses, we are now at the forefront of their respective industries in China and often globally in utilizing AI with positive initial results demonstrated by user engagement and revenue trends.

In games, we are deploying generative AI to accelerate in-game content production, enabling us to produce more content within our big games. We’re using generative AI to facilitate new user acquisition and existing user retention through measures such as targeted ads and personalized daily highlight reels. We’re enriching the core gameplay experience with AI features such as virtual teammates in PVP games and realistic non-player characters in PVE games. These initiatives are one reason why Tencent’s games are more and more evergreen, and our revenue growth of 22% in 2025 outperformed the 7% growth of the global games industry.

For marketing services, we scaled up our advertising foundation model to provide more relevant ads to more targeted users, boosting ad conversions for advertisers and providing better user experiences at the same time. We provide generative AI-powered ad creative solutions, enabling advertisers to create more ads which are more relevant to smaller set of users and more efficiently. We introduced our automated ad campaign solution, AiM Plus, under which advertisers can automate targeting, bidding, and placement, improving their return on marketing investments and increasing their budget allocation to us. These initiatives contributed substantially to Tencent’s marketing services revenue growth of 19% in 2025, outstripping the overall China ad industry growth of 14%.

For Video Accounts, deploying a longer sequence AI model which captures more of a user’s signals to enhance content recommendation is boosting user growth, engagement, and content distribution. Total time spent on Video Accounts increased more than 20% in 2025, and Video Accounts is now the second-largest short video service by DAU in China.

For digital contents, we utilize AI in content production, improving production workflow efficiency, and providing visually compelling special effects. AI also helps in content distribution through more intelligent content recommendations across music, videos, and literature.

We’re using AI in enterprise software to provide features such as AI agents that can take notes on and summarize concurrent meetings for users, and AI agents that generate intelligent summaries of customer service history for merchants. Our enterprise software products, WeCom and Tencent Meeting, are leaders in their categories in China in terms of usage and revenue.

For Fintech, we utilize lightweight AI models to enhance credit scoring processes and facilitate fraud detection, contributing to us sustaining better than industry non-performing loan rates…

…We have also integrated AI to enhance a range of existing user experiences within Weixin, including content consumption, information retrieval, and merchandise recommendation and customer service. We’re building AI agents which autonomously interact on behalf of users within Weixin functionalities, especially Mini Programs. The excitement around OpenClaw illustrates that people recognize AI can unlock computer use capabilities to improve their daily lives but also illustrate the risks around unleashing unsupervised AI. We want AI agents in Weixin to deliver AI productivity that’s beneficial to the general public as well as early adopters, and which will boost ecosystem activity and naturally generate revenue…

…OpenClaw is upgrading AI from thinking to doing via autonomous workflows and continuous task execution. Users control this new generation of AI tools through command line interfaces in their existing communication apps, which generally means Weixin and QQ in China, as it’s the most efficient for users to interact with digital agents in a place and format where they are already interacting with human contacts…

…We have already seen very good ROIs when we apply AI into our existing businesses, right? You know, so if you look at the breakdown of our financials, you know, if you look at the financials on a combined basis and then sort of we break it out and saying, oh, you know, these are the financials with existing businesses plus the investment into AI for supporting these businesses, right? You know, the growth is actually quite strong and if you exclude the investment in new AI products, then you know, the operating leverage is clearly there.

Tencent’s management sees substantial opportunities from configuring a strong foundational model for the company’s core customer-facing use cases; management thinks Tencent is not at the forefront when developing frontier models, but the company has revamped its AI-building capabilities; version 3 of Tencent’s foundation model, Hunyuan, is now in testing and it is a step-improvement compared to version 2; management thinks Tencent’s 3D text-to-image and world models are early category leaders; management believes that users of AI agents will have access to multiple foundation models, but integrating Hunyuan with Weixin will enable Weixin to have unique agentic capabilities; management spent RMB 7 billion on HunYuan and Yuanbao in 2025 Q4 alone, and RMB 18 billion in 2025, and expects to double the investment in 2026; management is confident that the investments in HunYuan and Yuanbao will lead to monetisation; management thinks the AI race is not just one race of model-building, but there are many different races taking place, so they are not worried about Tencent being relatively late; management believes that HunYuan will eventually be a SOTA (state of the art) model in the future

At the foundation model layer, we see substantial opportunities from combining a strong foundation model with configuration for core user cases such as chatbot, coding, multimodal, and agentic applications. 

Although we’re not the first mover in large language models, having already revamped our team, improved our data quality, and rebuilt our AI infrastructure for pre-training and reinforcement learning, we’re now iterating more intelligent models at a faster pace. HunYuan 3.0 is in internal testing and currently represents a bigger step in capabilities versus HunYuan 2.0 than HunYuan 2.0 was versus HunYuan 1.0.

For multimodal capabilities, our 3D text-to-image and world models are early category leaders and will increasingly benefit from leveraging our proprietary data and abundant use cases…

…AI agents are currently powered by a multiplicity of foundation models, and we expect that users at the application level will continue to have access to a range of models. However, improving the performance of HunYuan will enable us to offer new, unique to Weixin agentic capabilities. The Weixin and HunYuan teams will work increasingly closely together going forward…

…Our spending on our two biggest new AI products, HunYuan and Yuanbao, was CNY 7 billion in the Q4 of 2025 and CNY 18 billion for the full year. These figures are only for HunYuan and Yuanbao and exclude AI initiatives supporting our existing products and services, as well as exclude costs arising from providing GPUs to external customers via Tencent Cloud. We expect to more than double these investments in HunYuan, Yuanbao, and other new AI products in 2026, which we intend to fund from increasing earnings from our core businesses…

…Over time, we’re confident that monetization will follow usage for these new AI products…

…[Question] I have one question regarding the comment quite a few times that we mentioned that we are not a first mover or we are even a latecomer in AI. In the U.S., we have also observed that it’s becoming very difficult for some of the latecomers to catch up, even for those that have very high resources in terms of compute, talents, and data. How does management get comfortable and confident that we won’t be following the same path in terms of, you know, lagging behind, not able to catch up and around areas on compute modeled applications?

[Answer] If you are playing just one game, then basically it’s hard to sort of, you know, catch up on one game, right? You know, if you view AI as sort of, you know, a multiple of different games, then, you know, there are new opportunities, new frontier that’s opened all the time… All these elements can be packaged together, you know, in the new race of AI. It’s not sort of, you know, one race. It’s actually sort of, you know, a world of many, many races… I think, you know, that will, you know, increasingly manifest itself and as a result, there will be a lot of opportunities for different players to come up and innovate from behind. I’m not sort of, you know, very worried about, you know, being late, but I’d be worried about, you know, if we’re not innovating fast enough…

…Our HunYuan 3.0 is gonna be much better than HunYuan 2.0, and that’s actually just the starting point. I think, you know, over time, we’ll be able to iterate the training of our model faster and, you know, I’m very confident that, you know, if we focus on that, you know, we’ll reach SOTA at some point in time.

Tencent’s management thinks building AI chatbots is not the best way to use AI to help people; management thinks AI chatbots are competing with internet search; management is still finding product-market-fit for Tencent’s chatbot, Yuanbao; management will be deploying HunYuan 3.0 in Yuanbao in the near future and they think this will improve Yuanbao’s user experience; Tencent’s management is seeing that consumers in China are not willing to pay for AI subscriptions, unlike in the USA; management thinks Tencent’s consumer AI products, when introduced to Chinese consumers, will have to be seen as investments upfront because the company can’t charge for them at the moment, but management still thinks the AI products will generate a very attractive return over time; see Some observers in Chinese tech are single-mindedly focused on AI chatbots as the only means for bringing AI to users. We believe this mindset is overly simplistic because AI can help people in a multitude of ways beyond powering an information advice app. We believe that AI chatbot applications are largely competing with search applications rather than with every other application. For Yuanbao, our own AI chatbot app, we’re focused on finding product market fit and use cases which belong in chatbot AI app. We’re rapidly iterating Yuanbao to enhance its user experience by providing better search integration, improved speech recognition, easier access to multimodal capabilities, and exploration around group chat, which we believe will increase usage and user retention of the app. In the coming months, as we deploy HunYuan 3.0 in Yuanbao, we believe the core user experience will step up further…

…You know, we would be seeing new investments first, right? You know, there’s not that much of a revenue, especially in the context of China. Unlike in the U.S. where you can actually get consumers to pay subscriptions and you can get companies to pay for, you know, coding agents at a very high cost. In China, those are not sort of that available. I think these will present themselves as investments upfront. Over time, we believe, you know, we’ll be able to generate revenue from these new AI products and they would generate, you know, very attractive return for us over time.

Tencent’s management has introduced productivity-enhancing AI tools for OpenClaw; management sees OpenClaw as a decentralised model for how AI works, beyond just having two major chatbots; management thinks that users of OpenClaw will want OpenClaw to work with multiple models

Speaking of OpenClaw, we have introduced a number of AI tools for enhancing productivity, including WorkBuddy, QClaw, and Tencent Cloud Lighthouse. We provide downloadable skills to easily put these tools to use from our SkillHub…

…I think OpenClaw is actually a very exciting concept, right? You know, it actually sort of presents a decentralized model or a decentralized regime for, you know, how AI works in this world…

…For some time, right, AI seems to be sort of, you know, everybody is trying to fight to become the AI, AGI hegemon or monopoly. You know, there seems to be a point in it which like people said, “Oh, if there’s one model which is AGI, then, you know, it would rule over everybody,” right? You know, the reality is it’s not, right? You know, you have multiple models becoming, you know, very strong and, you know, they specialize in different kinds of activities, right? One in chatbot, the other one in coding, and the other one in multimodal. You also have open source, which are, you know, pretty good. You have a lot of other models which sort of, you know, fast followers too. Then there was a time in which, you know, in the two C world [referring to ChatGPT and Claude], there seems to be, the chatbot being sort of, you know, the single entry point. Now with Claw, you can see, you know, it opens up a completely decentralized regime where, you know, many companies can have their own Claw, and the Claw can be using all kinds of different models…

…If you use these OpenClaws, then you know you go into them, and you have a choice. Do you want to use, you know, model A, which is, you know, very high performance and high price per token, or, you know, model Z that’s medium performance and very low price per token, or models, you know, B through Y in the middle? You know, that’s part of the appeal of OpenClaw. You know, HunYuan is, you know, one of those models that is available. You know, we believe with the capabilities of the HunYuan team now in place, that going forward, HunYuan will get better faster, and therefore consumers will naturally increasingly opt to use HunYuan. I don’t think it will be a monopoly situation.

Tencent’s management thinks the company’s investments in AI will follow a similar experience with Tencent Cloud; Tencent Cloud was a late entrant into cloud services in China, but management was patient and knew that Tencent Cloud had scale right from the start; Tencent Cloud focused on high-quality services starting in 2022 which pressured revenue growth for some time, but Tencent Cloud ended up achieving operating profit breakeven in 2024; Tencent Cloud faced revenue headwinds in 2025 because of GPU-supply constraints, but it still grew revenue and earnings; Tencent Cloud is facing a better pricing environment in recent party because of AI demand; management has ordered a substantially higher volume of compute for Tencent Cloud in 2026, which would facilitate revenue growth; cloud services providers in China were suffering for years because the supply of infrastructure was ample, but the supply is now constrained; management will be passing Tencent Cloud’s higher supply costs to customers

I would like to present a case study on Tencent Cloud as the latest example on how we develop our services into market leaders with economic returns over time. That would follow games, payments, and long-form video. We expect it will be the same for our new AI products. Tencent Cloud was a relative late entrant in cloud services. However, we committed to a patient and long-term investment strategy, believing that it had scale from the start due to Tencent itself being the biggest single end user for a range of technology infrastructure in China, and that it could provide differentiated services arising from Tencent’s unique insights, ecosystem, and capabilities. For example, we believe that we were the first cloud service provider in China to fully recognize the stepped-up capabilities of AMD’s recent generations of CPUs, becoming AMD’s largest partner in the country, and that our cloud video streaming service is the industry leader in terms of streaming quality. 

After a period where Tencent Cloud prioritized the revenue growth somewhat misguided by other industry participants, in 2022, we aggressively restructured Tencent Cloud to focus on high-quality services rather than chasing high revenue but low-value-added activities such as reselling and customizing projects. This pivot cost us several quarters of revenue growth, but it enabled Tencent Cloud to achieve operating profit breakeven in 2024, up from significant losses in prior years. During 2025, although Tencent Cloud continued to face revenue headwinds due to limited availability of GPU for external customers as we prioritize our internal needs, it grew revenue and sharply improved earnings, achieving CNY 5 billion adjusted operating profit. In recent months, we’re seeing a better pricing environment, especially for memory and CPU, which, along with robust AI demand and overseas expansion, allowing Tencent Cloud to grow revenue at a faster rate. Moving through the year, we have ordered a substantially higher volume of compute, which should also facilitate revenue growth…

…For years the industry has suffered because the cloud services providers in China were operating at very low margins. One of the reasons they operated at very low margins was because, you know, if there was a new entrant or if the customers wanted to source infrastructure directly, they were able to telephone the supplier and, you know, order the infrastructure that they wanted from the supplier of, you know, CPU or GPU or DRAM. You know, that’s no longer the case. You know, now, the supply is booked out months, quarters, in some cases, years in advance. You know, the supplier is prioritizing the biggest, most regular customers, which are the hyperscalers such as ourselves. Therefore, you know, the smaller cloud providers no longer have certainty that they can source supply, and they need to come to the hyperscalers. You know, the hyperscalers have been operating at low margins and so, you know, when the demand picks up, then, you know, we almost sort of as an industry have no choice but to pass through higher prices. You have seen a number of price increases in China cloud in the last 24 hours as a result…

…We seek to deliver, you know, more value through, you know, enrichment. Enrichment means that, you know, at a minimum, if you have, you know, compute, you can rent it out bare metal and you get a certain low price and low margin. You know, preferably you rent it out. You subdivide it and virtualize it into tokens, and then you get a higher price and higher margin per unit of compute. Ideally, you bundle it into a platform as a service or software as a service. Then you can get, you know, the best pricing and the best margins. That’s part of the journey that we’ve been on, and that’s part of, you know, how Tencent Cloud has moved from a very substantial losses four years ago to pretty substantial profits last year.

Tencent’s management added Tencent CodeBuddy to Weixin’s developer toolkit, enabling developers to create mini-programs using natural language; management provided developers of AI native mini-programs with free compute resources

For Mini Programs, total user time spent increased over 20% year-on-year, driven by workplace productivity tools, mini-games, and novels. We added Tencent CodeBuddy to our developer toolkit, enabling developers to create mini-programs using natural language input, and we provided developers of AI native mini-programs with free compute resources.

Tencent’s management is using AI in Delta Force to improve user engagement and development efficiency

Delta Force leverages AI coding for development efficiency and deploys AI-powered companions to enhance user engagement. 

The Marketing Services segment’s revenue was up 17% year-on-year in 2025 Q4, driven by improved ad targeting, expansion of closed-loop marketing services, and tailoring of ad formats for specific advertiser use cases; management will be deepening collaboration of Marketing Services with e-commerce platforms; management has increased the inventory for video ads and Video Accounts; Weixin Search’s overall query volume grew rapidly in 2025 Q4 because of AI enhancements to search results, driving commercial query volume

For marketing services, revenue increased 17% year-on-year to CNY 41 billion. We experienced rapid growth from the internet services and local services categories, partially offset by slower growth from the e-commerce category due to platforms temporarily shifting budget from marketing to subsidies, and also from the financial services category due to the impact of policy changes affecting online lending during the quarter. Growth drivers included improved ad targeting, expanding our closed loop marketing services, and tailoring ad formats for specific advertiser use cases, such as ads that are playable previews of the mini games being advertised.

Entering 2026, we have deepened collaboration with e-commerce platforms, facilitating their merchants advertising within Tencent, and we’ve increased the inventory for rewarded video ads and Video Accounts, which have contributed to faster year-on-year marketing services revenue growth in the Q1 to date versus in the Q4 of last year.

At a product level, Video Accounts total time spent increased due to upgrades to the content recommendation algorithm, enabling faster growth in ad impressions while our ad load remained lower than peers. Better conversion rates contributed to more marketing spending for Mini Shops merchants. For Mini Programs, consumers engaging more with mini-games and mini-dramas attracted more marketing spend from the mini-game and mini-drama studios. Weixin Search overall query volume grew at a rapid rate due to AI enhancements to search results, driving growth in commercial query volume, while search pricing also increased.

Tencent’s management has obtained additional AI compute through leasing, through purchasing imported GPUs (likely referring to NVIDIA’s GPUs), and through purchasing domestic GPUs; the priority use-cases for Tencent’s AI compute is for HunYuan and the company’s new AI products; management currently does not want Tencent to design its own AI chips; management thinks there are many options for AI inference chips in China, and this has brought down the cost of inference chips; management wants Tencent to leverage the best training chips to build models

In terms of GPU constraints then, we’ve been quite actively provisioning, more compute, and that will be coming on stream, progressively, and increasingly quickly through this year, especially the H2 of the year. You know, that additional compute comes from leasing capacity. It comes from us purchasing, higher-end imported GPUs which are now becoming available again, and it comes from us purchasing, the increasing quantity of, domestically China-designed, GPUs. In terms of utilizing those, the compute for different use cases, you know, the priority right now is, you know, HunYuan and our new AI products more generally…

…[Question] We’re seeing a growing number of your tech peers are prioritizing the development of in-house chip design capabilities. I’m just curious where in-house chip development fits into Tencent’s own AI priorities.

[Answer] I think at this point of time, it’s not the most critical thing that we’ll be focused on. So if you look at the chip, you know, there is, you know, a difference between training chip and inference chip, right? You know, and for training chip, it’s actually very, very difficult to design and you manufacture, and you actually want to have access to the most state-of-the-art, you know, training chips to the extent possible and in the most flexible way so that, you know, you can actually sort of keep training for the best model. 

And then, you know, if you’re talking about inference, right, you know, I think inference, it’s mostly for cost. I think for cost at this point in time, there’s actually a lot of different suppliers in China, which is actually very different from, let’s say, in the training space, right, where there’s essentially one player or two players who can actually command a very, very high margin, right? You know, in the inference world, people basically sort of, you know, are earning much lower margin, and there are many more solutions and, you know, options. So, I think, you know, the key for us is actually sort of leverage the best training chips to train the best model at this point in time, and there’s a lot of value in being focused.

Tencent’s management thinks it’s really difficult right now to tell which layer of the AI technology stack will be commodities

[Question] If we think about the AI stack between, you know, the models, the orchestration layer, the application layer and so on, which parts would you say are most critical for Tencent to be best in breed versus, you know, areas where we think these will be commoditized?

[Answer] I think at this point in time, it’s actually very dynamic, right? You know, you’re in a fast-moving market. I think, you know, it’s very difficult for someone to say sort of, you know, oh, you know, there will be one layer more important than the others, right? You know, I think, you know, we have the resources, we have the people, we have the team to actually invest in all these layers.

It’s currently not possible to use AI to build games completely from scratch

There is not yet the capability to create games, you know, completely from scratch using AI for a number of reasons that we can get into.

Tencent’s management is seeing AI create demand for memory chips in two ways, namely, (1) GPUs requiring high memory capacity, and (2) AI creating software that requires memory to execute

You know, when people utilize the agentic tools that we’ve been discussing, they’re using them and they create software. You know, that software, you know, then primarily, it needs to be executed. When it executes, most of it is not executing on a GPU. It’s executing on CPU, and then as it executes, it creates, you know, memory demands. It’s not just, you know, GPU, DRAM, HBM where we’re seeing demand picking up. It’s also, you know, CPU. It’s, you know, regular RAM. It’s SSD. It’s hard disk drive.

Veeva Systems (NYSE: VEEV)

Veeva’s management thinks core systems of record such as Veeva will incorporate and work seamlessly with AI and not be replaced by it; Anthropic’s recent launch of Claude for Life Sciences has Veeva as a launch partner; management thinks LLM (large language model) providers’ launches of life sciences products will not cannibalise Veeva’s products; management thinks AI is a very positive thing for Veeva because it helps Veeva create and improve its software faster; management thinks core systems of records will be used by both agents and humans; management thinks it’s still early days of AI and it will play out over 10-20 years; management thinks the LLM providers and Veeva will have a symbiotic relationship; management thinks the LLM providers will not be interested in industry-specific software

There’s a lot of hype and fear that AI will replace today’s software systems. The reality is, not all software

is the same. Core systems of record like Veeva, SAP, and Workday are essential and will incorporate and

work seamlessly with AI, not be replaced by…

…[Question] Anthropic made a lot of noise when they launched Claude for Life Sciences and signed up a lot of deals and maybe lost in that was Veeva is an enabling and launch partner of Claude for Life Sciences. So Peter, how should we be thinking about the opportunity for Veeva to work with Anthropic, OpenAI, all the different kind of model providers out there, provide your domain expertise, provide the workflow expertise and kind of have a rising tide lifts all boats situation rather than obviously the current market view of it being more cannibalistic?

[Answer] I certainly don’t view it being cannibalistic for Veeva, absolutely not. I mean let me state that clearly. AI is a very positive thing..

…And these core systems are going to be used by agents as well as human users. Yes, that’s new. But these systems are essential, and they’re not going away…

…So we’re really in these early days of AI and people get a lot of hyper and they think it’s going to play out over 1 or 2 months. It’s not. It’s going to play out over 10 or 20 years…

…Specifically for Veeva, AI, that’s going to help us create and improve our core systems faster than before. So that’s where it will help our software development but not at the expense of quality, predictability, regulatory compliance and the real value that customers depend on…

…Anthropic or OpenAI and others, that’s an engine, and their engine will be used for a lot of things. They will be used by the Veeva applications or by custom applications that customers develop. So yes, it’s good for those large model providers. Now they have to watch their profitability, et cetera, but they’re an engine in the new wave of cloud computing. So that’s the new AWS, et cetera. So it’s a good business there. But just as AWS itself and also Microsoft Azure, Google Cloud, et cetera, that was very good business for those hyperscalers. But I think what sometimes gets lost, that actually enabled Veeva. You couldn’t have built the industry Claude for Life Sciences. You couldn’t have built those long tail of applications without those cloud infrastructure providers. And it’s the same way here with these large language models. Veeva could not build the AI applications that we’re going to build without these foundational LLMs. So I don’t know if I’ll use this word correctly. I think the word is symbiotic. I think so…

…I don’t think the AI vendors are really making industry-specific software applications, right? It takes a lot of dedication and effort to do that. So I think it’s a very symbiotic relationship. Just like the cloud area, yes, Amazon didn’t make industry-specific applications either. I don’t really see — why would somebody like Anthropic do that, right? They’re going to make broad applications and applications for coding itself, et cetera. That’s what I feel would happen.

Veeva’s management thinks the agentic layer will provide far broader value than LLMs (large language models); management thinks AI agents is a substantial opportunity for Veeva; Veeva has Vault CRM Free Text Agent that captures rich, compliant call notes; Veeva has PromoMats agents that deliver approved content faster; management will be introducing regulatory and safety agents in 2026 (FY2027); management thinks building industry-specific AI is difficult and requires proprietary data, sophisticated logic, domain expertise, and more; management thinks Veeva’s agents, if built well, can provide a lot of value to customers; management thinks Veeva is in a great position to lead in industry-AI for the life sciences industry; management is making great progress on Veeva’s first two AI agents for safety, and they will be launched in April 2026; management is pleased with the progress of PromoMats agents; there are early adopters who are live with PromoMats agents; management thinks their approach to data is resonating with the life sciences industry when building AI use cases; customers are excited about the PromoMats (Promotional Materials) agents because the agents really work and the customers have been burnt by failed AI experiments; management is seeing PromoMats agents delivering very clear ROI (return on investment) for customers; the two AI agents for safety that will be launched in April 2026 provides clear value for customers because they automate workflows that would require expensive labour; management thinks it’s still early to nail down the right pricing model, but Veeva will be going with a token-based pricing model; management is seeing most customers go with Veeva’s agents instead of them building their own agents with Veeva AI

While the major large language models are the catalyst for this shift, the agentic layer provides far broader and more diverse value. The agentic transformation underway represents a substantial opportunity for Veeva and life sciences. With our core systems of record spanning the industry’s most critical functions and unique datasets, we can deliver industry-specific AI deeply integrated into our core applications. 

For example, Vault CRM Free Text Agent captures rich, compliant call notes for deeper customer insights. PromoMats agents help deliver approved content faster. Regulatory and safety agents coming this year can streamline health authority interactions and safety case processing. And this is just the beginning.

Building reliable industry-specific AI across a wide range of use cases for a highly regulated industry is hard. It takes time, focus, and the right skills. It integrates proprietary datasets, sophisticated logic, validated processes, and depends on specialized domain expertise and safeguards to maintain compliance and data integrity. If done well, our agents will provide significant value for customers and Veeva.  

It’s early days for industry AI, and we are in a great position to lead. We have a well-established life sciences cloud that’s expanding to connect the industry, strong momentum with Veeva AI, and much more innovation on the way…

…We are also making great progress on our first two Veeva AI Agents in safety, Case Intake and Case Narrative coming in April. Customer interest is high as the industry looks to AI to drive efficiency in safety case processing…

…I am also pleased with the progress of Veeva AI for PromoMats. A number of early adopters are now live, more projects are underway, and the success of these agents is generating a lot of interest…

…Our unique and modern approach to data is resonating with the industry, providing a harmonized data foundation that fits seamlessly with our commercial software. High quality, standardized and connected data is critical for speed and efficiency and is a required foundation for AI…

…For example, in the promotional materials management area, and they’re pretty excited like that I can have a winning AI application that really works and is really durable and is from Veeva because they’ve been — a lot of them have been burned on a lot of experiments, but it’s not easy for customers to admit failed experiments because that’s just the dynamics. You don’t like to admit that. And failed is too hard of a word. Sometimes the experiment doesn’t work out, but it’s not a failure. You got a lot of learnings. But the experiments that can actually scale, they’re rare so far, and they know Veeva’s — we won’t do things unless we can scale them…

…[Question] Can you maybe speak to early proof points that you’re seeing on AI agents that, I guess, you’re planning to roll out over the course of the year? Are there any sort of ROI or tidbits from clients that you’re hearing that you can kind of comment on ahead of these releases?

[Answer] The one that’s farthest along, and we have multiple projects underway, is the commercial content area. And that — the ROI is just very clear. It’s faster content, lower cost to create that content, and that’s what it’s all about. Lower cost to create that content, I won’t quote specific numbers, but that’s pretty clear to quantify. Faster content just means better launches. That means that drives the top line before the patent on that product expires. So I get asked by that — by customers all the time. They know in the age of really omni-channel experience for their customers, which are patients and health care providers, omni-channel experience that includes AI doctors and large language models, the speed that you can get your content out there in a compliant way is just going to be critical. So the old way of approving content is just not going to suffice anymore…

…In terms of AI, it’s pretty clear there in — there’s a lot of human processing of case intake and case narrative generation that’s done by people. That’s not necessarily that high risk, but it has to be done well. And it’s expensive to hire those people, and it’s not easy. So in safety, it’s just very clear. It’s about replacing that type of labor with automation, with AI software…

…It is, as you said, still quite early. As we’re starting this year, we’re really expecting to be using a token-based pricing model, and so that gives us a little bit of predictability around the margin profile. But that may evolve over time…

…[Question] Within Veeva AI, what is the mix of customer adoption you’re seeing right now between prepackaged agents that you’ve built and custom agents that they’re building using Veeva AI?

[Answer] The bulk of it is with our agents that we’re designing. So part of it is our — I guess, our agents are probably a little more robust than our custom tooling right now. But if you look at our agents, there’s detailed work in the agents, right? There’s detailed data curation. There’s detailed testing pipelines. There’s a lot of logic in the agents, right? When we talk about AI agents, there’s a lot of logic, specific logic written in our Java code that’s hard that needs great product management. So in general, customers would rather get that solution rather than build that themselves.

Veeva’s management is not seeing AI-considerations being a major theme with the company’s customer-wins in 2025 Q4 (FY2026 Q4)

[Question] I wanted to ask if Veeva is starting to see some programs funded maybe in the name of AI readiness. I would imagine for a top 20 to commit to Veeva in any of the R&D areas, RTSM, quality, safety, it would seem you’re going eyes wide open into really viewing Veeva as a future foundation for everything AI related that is to come. And so I’m wondering if there’s an AI influence that you’re starting to see that’s contributing to the strong demand here at year-end.

[Answer] I wouldn’t say that’s a broad theme. There are cases, and it varies by area. More of the theme is, hey, we need core systems that will scale, either their existing systems are aging. So we talked about a top 20 safety win. There, their existing systems, because they were doing other things over the past years and just lots of deferred maintenance and that was going to become a critical risk for the company, so they have to get that in. There are sometimes where it will help our data business. They’re trying to clean up their clean reference data because they know AI is not going to work because, okay, garbage in, garbage out. So there’s a little bit of that, but more it’s just modernizing, getting rid of legacy and looking for increased automation. AI is — really, the goal there is automation, right? That’s the goal. But AI is not the only way you do automation. Part of it is you do automation through a system to have clean workflow. So it’s a driver, but I wouldn’t say it’s a major driver.

Veeva’s management is seeing life sciences companies group AI players into 4 buckets, namely, (1) the LLM providers, (2) the point solution providers, (3) their own in-house development teams, and (4) core application providers such as Veeva; when life science companies talk to Veeva about AI, they want Veeva to provide more AI solutions that are tightly integrated with their core systems because they trust the company; Veeva’s management thinks the company’s customers really want it to win in AI applications

They bucket into 3 — maybe 4 types of people that might be able to help them. One is the infrastructure providers, the LLM providers themselves, Anthropic, OpenAI, Microsoft in that camp, Amazon, NVIDIA, those types of things, what — how can they be leveraged there? And then they would look for point solution providers. There’s a specialized group of people in the specialized department, and they can do this proof of concept or maybe you scale it for me here. And then there’s their own employees doing custom software, and then there’s system integrators. And then you get the core application people like Veeva, like Workday, like SAP…

…When they’re generally talking to us, they want us to provide more AI solutions that are tightly integrated with their core systems because they trust Veeva, and they know we deliver quality and really know when we say something is going to work, it’s going to work, right, because our reputation is on the line versus a small start-up can just say whatever they want…

…Our customers really want us to win in AI applications. And so we have a right to win, and we just have to execute.

Veeva’s management thinks the real bottlenecks in life sciences is not the pace of drug discovery, but finding patients for clinical trials, and the pace of a patient getting the right drug for treatment; management thinks these bottlenecks are where AI can play the biggest role, and where Veeva can help; management thinks AI cannot really speed up clinical trials

[Question] Given how mission-critical this is and maybe how much it can be tied not just to better revenue outcomes but more importantly, better patient and better health care outcomes and better societal outcomes, do you see an opportunity to not just automate and drive faster time to value and efficiency but even leveraging AI within the Veeva platform to allow for better drug development, safer drugs out of the market, basically better outcomes rather than just faster time to value?

[Answer] Drug discovery is one thing, and there’s a lot of focus on that. And yes, that will get faster, but that’s not the real bottleneck. The real bottleneck is the clinical trial, the experiment that’s done in the human. And we’re always going to have to do those experiments in the human, and the human biology runs at the same speed. So that always has to be done, and the bottleneck now is finding the patients around the world that can get in those trials. So that’s one.

But the biggest bottleneck by far is there’s a patient somewhere out there in the world. They’re diagnosed with something by a doctor. How long did it take them to get diagnosed? And when did they get the right medicine that will best treat them? That’s where 90% of the value in life sciences is lost, because of that impediment, the basics of is the patient informed. Can they get to the right doctor? Is the right doctor informed? Is the payer informed? It’s — that’s where 90% of the value is lost. And I said value is lost, but on the other side, there’s a lot of people who don’t get treated correctly or timely around the world. And that affects productivity. That affects their family…

…So this is really important for us, and AI can definitely, definitely, definitely bridge that gap. AI doctors and large language models can help bridge that gap between doctors and patients, so maybe that 90% inefficiency goes down to 50%, and that will be a tremendous boom. And yes, Veeva will definitely play a part in that by connecting our customers, the industry to its external ecosystem. And its external ecosystems are clinical researchers, patients and doctors and regulators. And the industry is not well connected, and AI is going to provide a better method to do that…

…About AI speeding up clinical trials, I think AI can speed up some maybe in the start-up and in the close down but not that much really. It’s still based on the clinical protocol of the medicine, which is based on the time of the human body it takes to deal with that medicine and to prove it out and then the patient recruitment, which I don’t think is actually an AI problem, the patient recruitment. So speed it up some but not so much in clinical trials.

Veeva’s broad product suite is an advantage for customers when they are trying to implement AI

Let’s say they’re doing something with us in safety and they start doing an AI solution with us in safety. And 2 years from now, they go with us in clinical data management, and a year later, they put in an AI solution for clinical data management. Well, that AI solution is going to work with their safety solution pretty much out of the box. And that’s a benefit they never planned for they’re going to get. So I think customers start to see that it kind of fits together with Veeva.

Veeva’s management thinks customers are starting to realise that Veeva is the only company that can provide AI solutions that are also connected to all their other systems; management thinks customers are also starting to realise it’s not so easy to build and maintain their own AI solutions

But I think they’re starting to realize if you if you want to have a potential future where you have a great core safety system that has safety AI on top of it and is connected to your other systems in your company, Veeva is the only place you’re going to do that unless you’re going to build it yourself. I think most people are starting also to realize now that it’s not that easy to build and maintain these things themselves. So that’s kind of what’s leaning into our favor on the AI.

Wix (NASDAQ: WIX)

Wix’s management thinks AI and the acquisition of Base44 has dramatically expanded Wix’s market opportunity; the addition of Base44 has allowed users to build applications, content, and websites that are much more powerful and sophisticated than before

What started as a simple do-it-yourself website builder has grown into the leading online presence creation platform serving not just self creators, but also businesses of all sizes as well as professional designers and developers. In recent years, the web has undoubtedly become much more AI-first. That shift is redefining how and what people build online. AI has dramatically expanded the world of what is possible and created new dimensions that had not existed before. As a result, Wix.com Ltd.’s market opportunity today is exponentially larger than in 2025, primarily driven by our expansion into the application space facilitated by our acquisition of Base44…

…With the addition of Base44 to our platform, users can now build tailored software applications, smart mobile applications, pro-level visual content, and, of course, websites, but so much more powerful and sophisticated than ever before. These are all things you can create on Wix.com Ltd. today, which is incredible, but the possibilities ahead are much, much bigger.

Wix Harmony is a first-of-its kind website builder that blends visual editing with vibe coding; Wix Harmony is an AI layer that spans the entire Wix experience; Wix Harmony was launched in English in January 2026 and management will expand Wix Harmony globally in other languages; management is very pleased with the early conversion and monetisation of Wix Harmony; management intends to make Wix Harmony the default Wix experience for new and existing users over time; management expects negligible AI inference costs associated with Wix Harmony in 2026; management is not seeing Wix Harmony and Base44 cannibalise each other’s customer base; management built Wix Harmony for the self-creator market; users of Wix Harmony are using it for the same purposes as the old Wix; Wix Harmony currently does not support a database, but will soon do so; early users of Wix Harmony have better conversion, faster monetization, and higher ARPU (average revenue per user)

Wix Harmony is the first-of-its-kind website creation platform that blends intuitive visual editing with the flexibility and power of Vibe coding. Wix Harmony provides a unified AI layer that spans across the full Wix.com Ltd. experience, allowing for a real AI partner to be with you every step of the way as you create, manage, and grow an online presence or business. After launching in English in January, we are now expanding Wix Harmony globally in other languages, and I am very pleased with the early performance we are seeing, particularly across conversion and monetization metrics. We believe Wix Harmony has the potential to fundamentally reshape how individuals and small businesses build and scale online, not just on Wix.com Ltd., but across the Internet as it becomes increasingly AI-driven. Over time, we plan to gradually make Harmony the default experience for new and existing users, an evolution we anticipate will drive meaningful long-term impact across conversion, engagement, retention, and monetization…

…Negligible AI inference costs associated with Wix Harmony as a result of proactive infrastructure optimization completed last year…

…[Question] Just stepping back, what types of businesses or applications are you seeing users set up with Base 44? And how much crossover is there with what you see on Wix.com Ltd.’s core platform?

[Answer] We do not see any kind of competition, and you can see that they are very mostly different usage also, as you can see now. Clearly, Harmony is accelerating, Base 44 is accelerating. So, obviously, we do not think they take from each other…

…Harmony is a product we built for the self creators…

…We are pretty much seeing everybody using Harmony that was using Wix.com Ltd. before. So it is everything from personal websites to the hair salon website to large company and enterprises, so pretty much everybody. At this stage, Harmony does not support a database, but that will be added soon…

…[Question] On Harmony, just curious what the early cohort KPIs that you are seeing there in terms of conversion, ARPU, attach rate, churn, relative to the traditional cohorts and how durable you see these KPIs across your geos?

[Answer] We see a very good performance of the new cohorts. We actually see a better conversion, faster monetization, and also higher ARPU. So we believe, we hope that this strong trend will continue. Again, I think that it is too early, but we feel very positive about the first reaction and performance of this product.

Base44 expands Wix’s reach into vibe coding; Base44’s user base is scaling rapidly, with the number of new Base44 users today nearly 2/3 of the number of new Wix users; Base44 has reached $100 million of ARR (annualised recurring revenue) just 1 year after its founding and 9 months after Wix’s acquisition (Base44’s ARR was just a few million dollars when Wix acquired it); management is starting to see Base44 being used by enterprises from different industries to build their own software solutions; Base44’s current growth is completely organic as Base44 has no sales team; management believes the potential for vibe coding still lies ahead as the technology reaches the broader online population; 1/3 of Base44’s AI inference costs today are for free users; Base44 has positive non-GAAP gross margin today; management thinks Base44 has a tROI (time return on investment) of less than one year; management thinks there is a great opportunity for partners to use Base44 in the future; Base44 is driving users who joined Wix 10-15 years ago to become paid users

The second new pillar of our strategy is Base44, our leading Vibe coding platform that expands our reach into the vast world of software creation and significantly grows our TAM…

…Base44’s user base is scaling rapidly. Today, the number of new users joining Base44 is nearly two-thirds of the number of new users joining Wix.com Ltd…

…Just one year after Moar founded the company and nine months after our acquisition, Base44 recently reached approximately $100,000,000 of ARR, placing it among the fastest growing software platforms in history. While Base44 is already emerging as a top platform to build lightweight personal projects, we are seeing adoption from a growing community of businesses and enterprise-sized organizations too. Companies in the tech, banking, and healthcare industries, as well as government organizations and nonprofits, are using Base44 to build customized software solutions. We are seeing users develop their own CRM capabilities, product and project management tools, ERP systems, workflow automation frameworks, and financial reporting applications.

Importantly, this momentum and growth is completely organic. With no sales team at Base 44 today, self-propelled adoption by enterprise-size organizations demonstrates the strength of the platform as well as our successful marketing execution…

…I believe the real potential still lies ahead as Vibe coding permeates beyond early tech-forward adopters to the broad online population…

…Base44 finished the year with approximately $59 million of ARR, above our expectations at the time of acquisition. Excitingly, Base44 recently reached approximately $100 million in ARR, a major milestone that underscores our rapid growth and growing market leadership. Strong ARR growth was driven by product innovation that has resonated, a rapidly expanding user base, improving conversion and consistent upgrade and renewal trends…

…Approximately one third of Base44’s AI inference costs today is attributed to token consumption of free users…

….Even after incorporating AI-related costs associated with free users into cost of revenue, Base44’s non-GAAP gross margin is positive today and is expected to improve as the year progresses…

…Base is a very young company, very young product. And, by the way, this is why we are very also conservative about the guidance. But right now, based on the information that we have, based on the history that we already have, we are looking at less than one year of tROI and this is how we manage the acquisition cost…

…Base44 has a ton of interesting things for our partners that they can actually use for their customers, and it is more revenue stream for them. So we believe that although right now most of it is self creator-led, we believe that it is a great opportunity also for partners to use Base44 in the future…

…Base 44 is a very young product, on the Wix.com Ltd. cohorts, we are seeing people who are converting who joined us ten or fifteen years ago. That is amazing

Wix’s partnership with OpenAI is not built on APIs in the standard way, but rather, it’s built on two AIs that are collaborating

[Question] In addition to the apps partnership with OpenAI, do you see potential opportunities in terms of how Wix.com Ltd. websites are navigated and searched by OpenAI in the future, particularly ChatGPT?

[Answer] It is not APIs in the standard way, it is essentially two intelligences that are discussing and working together to give you a website. And that is a fantastic pattern that can be grown a lot.

Wix’s management has given Wix users the ability to open their websites for LLMs to crawl and read if they want to; Wix users can even give LLMs more content than what is offered over a website

As for how OpenAI or any other LLM can read Wix.com Ltd. sites, we support pretty much everything. We support, of course, make text. If our customers choose so, we can make the text visible and easy to crawl and built in a way that is very easy for the LLMs to process. And we also have ways so we can give the LLMs more than just the content that we normally offer over the website, because LLMs like to read a lot of content, when humans tend to want to read less.


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, Alphabet (parent of Google), Amazon, Meta Platforms, Microsoft, Okta, Salesforce, Sea, Tencent, Veeva Systems, and Wix. Holdings are subject to change at any time.

What We’re Reading (Week Ending 15 March 2026)

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 15 March 2026:

1. The subtle art of not selling stocks – Chin Hui Leong

My co-founder, David Kuo, has an investing rule that some of you may find peculiar: He never sells any stock he buys…

…Before you dismiss this idea as reckless, consider what this commitment actually demands.

If you know you will never sell a stock, every purchase becomes a permanent decision. You can’t afford to be casual. You can’t buy on a whim and figure it out later…

…David treats his stock purchases the same way. By removing the option to sell, he raises the bar for every stock that enters his portfolio. The result is a collection of businesses he knows deeply and trusts completely…

..Most selling decisions are driven by emotion, not analysis. When a stock drops, fear kicks in…

…Daniel Kahneman, the Nobel laureate and father of behavioural finance, would recognise this pattern. In his parlance, your reflexive brain (called System 1), built for snap decisions and danger avoidance, often overwhelms your analytical (System 2) brain you before you have a chance to think things through…

…Back in January 2007, I bought shares of Netflix at a split-adjusted US$0.33 per share. Over the past two decades or so, the stock has soared, crashed and soared again.

Along the way, I sold half my position. At the time, it felt like the prudent thing to do. Lock in the gains; reduce risk; be sensible.

But here’s what “sensible” cost me: I estimate that the shares I sold would have gained over 14,000 percent had I held on. That’s the equivalent of holding 140 stocks that went to zero.

And the chances of finding another Netflix are slim. My remaining shares are up over 300 times my original investment. The half I kept is doing the heavy lifting: the half I sold become my most expensive lesson.

For David, his eyes are on the dividend stream his shares produce, not the stock price…

…You don’t have to adopt David’s rule as a rigid requirement. There are legitimate reasons to sell: A business may suffer permanent deterioration. Your original thesis may be proven wrong. Management may stray in ways that betray your trust…

…The art of not selling isn’t really about not selling. It’s about becoming the kind of investor who doesn’t need to react to every bit of news.

2. Ergodicity and Investing – Eugene Ng

The average investor made money. The average investor also does not exist. There is no average investor. There is only you, your portfolio, your decisions, and your one path through time. Finance forgot that. Ergodicity remembers it…

…A system is ergodic if the average outcome over many people (ensemble average) equals the average outcome of a single person over time (time average). When those two diverge, the system is non-ergodic, because you are not the group.

Imagine 100 people each play Russian Roulette once. One bullet, six chambers in a pistol, spin the chamber, and fire the pistol. Survivors get a huge prize. The group average survival rate looks seemingly acceptable (83% = 1 – 1/6). That is the ensemble average. The expected value is 0.833 (5/6 x 1 + 1/6 x 0). A classical economist would say, positive expected value, rational to play. If the prize is $1 mil, $10 mil, or $100 mil, does the size of the prize matter? Would you still play such a game?

Now, imagine that one person can only play 100 rounds of Russian Roulette sequentially. They are dead with near certainty (~99.999999%). While in round 1, the probability of death is 16.7% (i.e., 1/6), which rapidly increases as more rounds are played. Probabilities grow rapidly to 60%, 84%, 97%, 99% after 5, 10, 20, 30 rounds, respectively. This is the time average.

It’s the same game, but over time results in a completely different outcome…

…Maximize growth that first conserves survival. Game-overs cause non-ergodicity. Do not maximise growth over survival. When permanent game-overs are possible, don’t rely on averages. Focus on not being wiped out permanently first.

Avoid a total loss and irreversibility at all costs. Never allow a single negative event to maximise short-term returns, rendering long-term maximisation irrelevant. If you are going to play a game where, after many rounds, you are almost certainly going to be dead. Avoid playing all games that are not repeatable at infinity…

…Survival beats performance. Performance is always subordinate to survival. The longer the time horizon, the more true this becomes. To be among the best over time, you need to keep playing the game, rather than being kicked out.

Focus on being antifragile, not fragile. To determine whether something is fragile or antifragile, expose it to volatility and see how it responds. Fragile things are harmed by volatility, and antifragile things benefit from volatility. Fragility is non-ergodic. Antifragility is ergodic. Fragility has limited upside and unlimited downside. Antifragility has a limited downside and unlimited upside…

…We avoid margin/leverage at all costs. Brokers can offer up to 100x leverage, but never take it. A 1% move against you could wipe you out. A Monte Carlo simulation of 20 sequential scenarios with 20X leverage, using 8% p.a. returns and 18% annualized volatility, shows that ~90-100% of the time, one will eventually be permanently wiped out (with a cumulative loss of -5%)…

…Don’t agree with redistribution, particularly for investing. Trimming your winners to feed your losers is incorrect, as it assumes the same likelihood of returns. Winners tend to keep winning, and losers tend to keep losing. Persistence tends to be more likely at both the right tails (winners) and left tails (losers). As long as the risk is overly significant, one should first let your winners run high, second, don’t trim them, and third, add to them.

3. Good news: AI Will Eat Application Software – Alex Immerman and Santiago Rodriguez

Yes, AI is a big deal. But the conclusion that AI is going to kill the vertical and functional software business model simply makes no sense. The truth is that AI simply isn’t going to kill software companies: after all this panic has passed, we’ll see that AI is the best thing that ever happened to the software industry…

..The bear case rests on a basic misunderstanding of what software companies actually sell. The market is treating “software” as though it were a commodity input—as if the value of a software company resided in its code, and cheaper code meant more competition and therefore cheaper companies. But code is never where the value has lived: if code is where the value was, these companies would have never gotten so big in the first place. They would have been killed years ago by open-source software or by competition from cheap software engineering labor in developing countries…

…AI might increase competition; but it’ll also dramatically expand what software companies can do, how fast they can do it, and how large the markets they serve can become. The end result won’t be margin compression to zero. Software will be a much bigger industry, with durable competitive advantages for the companies that earn them…

…The classic contemporary book on business moats is Hamilton Helmer’s Seven Powers. He lists seven distinct ways in which companies develop robust competitive advantages: Scale, network effects, counterpositioning, switching costs, brand, cornered resources, and process power…

…Switching costs are perhaps the one moat that really is going to change. It’s definitely true that AI is changing the friction and the cost-benefit analysis associated with switching vendors: agents can assist with a lot of migration work that used to be a headache…

…Network effects are a classic moat. And they aren’t going away…

…On the surface, Salesforce is a CRM database; but anyone who has worked in an enterprise setting knows that Salesforce is also an ecosystem. When everyone uses one platform, the network becomes self-reinforcing: you use Salesforce because everyone uses Salesforce. And the more companies use Salesforce, the more valuable the ecosystem of third party applications built on top of Salesforce and platform administrators experts in Salesforce…

…Scale was never the defining moat in software—it’s just not as important for Salesforce as it is for a cloud provider or for an industrial company. But to some extent, it may matter more for AI applications where compute spend exceeds labor costs, driving a unit cost advantage to the larger consumers of tokens. In addition, there are places where scale will still help: it’s a straightforward economy of scale to concentrate that maintenance burden in one place, since productivity gains from specialization don’t go away in an AI world…

…Cornered resources, like high-quality proprietary data, aren’t going to stop mattering either. If friction goes to zero, simply consolidating publicly available data into a usable interface becomes less valuable, because anyone can do it. But if AI enables doing much more with high-quality data than you could before, then the stuff that you can’t get easily becomes extremely valuable…

…And perhaps the strongest moat of all in this new era is process power—or as George Sivulka of Hebbia calls it, “process engineering.” Application software can be thought of as a stored process—it encodes opinions about how the function of an organization should operate, and those opinions calcify over years and decades of use into something that is inseparable from the organization itself. Successful app software companies are the ones that co-evolve with their clients around these workflows. As those workflows penetrate ever-deeper into an organization, process engineering only becomes more important. And more difficult for challengers to replicate…

…Counterpositioning is a kind of power that can be summoned and wielded by new entrants to a market. It’s when the new company has a business model which, for whatever reason, is unattractive for the incumbent company to compete against. Disruption theory from Clay Christensen is a classic type of counterpositioning, but it doesn’t always have to be “low cost” as the differentiated counterposition. In software, a new technology stack could create the opening for a startup to create new kinds of products and business models that are difficult for incumbents to replicate – like Databricks and their “Lakehouse” model.

The “agent” model of doing work and replacing tasks is certainly going to create some counterposition opportunities for new startups to challenge incumbents. There’s been a lot of ink spilled on the disruption of “per seat pricing” at the hands of agentic upstarts with value-based pricing. Let’s take customer service as an example. Decagon prices its customer support product per conversation handled, not per agent seat, and will eventually price per resolution achieved: that’s fundamentally a better alignment of incentives between vendor and buyer. An incumbent like Zendesk can’t easily make that same move without cannibalizing its own seat-based revenue. Just as Blockbuster couldn’t match Netflix’s subscription model without destroying its existing economics or Peoplesoft couldn’t match Workday’s SaaS model without upending its monetization. Companies that start with the new business model don’t face that dilemma, and it’s the core reason why platform shifts so reliably produce new winners.

But guess what? The total amount of “end state pricing power” in the market didn’t necessarily decrease; it just means customers now have a choice of business models they’d like to subscribe to, and the better one will win. That’s how competitive markets have always worked! AI is not the first time that a wave of creative destruction has rearranged markets and shifted the playing field. But here’s the thing: the business models that result almost always dwarf the old ones in the scale of the total opportunity…

…AI isn’t going to destroy the software industry; it’s going to split it into two parts. There really will be some categories of software companies that face genuine pressure. Frontend tools that serve primarily as thin wrappers around commodity functionality and do relatively little beyond presenting data in a slightly more convenient format are vulnerable. Incumbent systems of record that still operate on archaic interfaces but raise prices every year should be worried. So should software companies that have an outdated pricing model and value proposition that’s just inferior to what AI-native competitors can offer. The companies that win in this environment will be the ones delivering genuine value, not the ones that built the highest walls around their customer base.

4. THE NDFI BOMB – Dirt Cheap Banks

Here is a sentence that should terrify you: the single fastest-growing loan category in American banking is one that most investors have never heard of, most analysts don’t understand, and most banks can’t fully explain.

That category is loans to Non-Depository Financial Institutions, or NDFIs.

An NDFI is any financial company that lends money but doesn’t take deposits. Think mortgage companies, private equity funds, hedge funds, subprime auto lenders, fintech lenders, insurance companies, business development companies (BDCs), and the sprawling private credit universe. These are the shadow banks. The firms that exist in the regulatory gray zone between Wall Street and Main Street.

Here’s where it gets dangerous: traditional banks are funding the shadow banks. When Bank of America extends a $500 million credit line to a private credit fund, or when a regional bank in Indiana provides warehouse lines to a dozen mortgage companies, those are NDFI loans. The bank is one step removed from the actual borrower, lending to the lender, and often has limited visibility into what’s happening with the money downstream.

As of Q1 2025, U.S. banks held $1.14 trillion in outstanding NDFI loans, according to the Federal Reserve Bank of St. Louis. But that’s only the money that’s already been lent. The International Monetary Fund estimates banks have an additional $900+ billion in undrawn credit commitments to NDFIs. That’s money NDFIs can draw down at any time, for any reason. In a crisis, they will.

Total potential exposure: north of $2 trillion.

And it’s growing at a pace that should make every risk manager in America lose sleep. NDFI lending has grown at approximately 26% annually since 2012, according to the St. Louis Fed. In 2025, it surged more than 50% year-over-year according to Federal Reserve data, the largest jump in records going back to 2016.

To put that in context: total bank loans grew roughly 4% annually over the same period. NDFI lending has been growing at six times the rate of everything else…

…The FDIC now requires banks with over $10 billion in assets to break their NDFI lending into five categories. Here is where the $1.14 trillion actually goes, based on Q4 2024 call report data:

Mortgage Credit Intermediaries (23% of all NDFI loans, roughly $219 billion): These are loans to non-bank mortgage companies. The bank provides a “warehouse line” that the mortgage company uses to fund home loans. Once the mortgage is originated, the mortgage company sells it to Fannie Mae, Freddie Mac, or Ginnie Mae and pays back the warehouse line. The end-borrower is a homebuyer. The risk to the bank is that the mortgage company goes bust before it can sell the loans, or that the loans don’t qualify for agency purchase and the collateral is worth less than the advance. This is generally considered the lowest-risk form of NDFI lending because the collateral is agency-eligible mortgages with a ready secondary market.

Private Credit Intermediaries (23%, roughly $202 billion in private equity fund loans plus additional business credit intermediary exposure): These are loans to private credit funds, business development companies, and leveraged lending vehicles. The bank provides subscription lines (backed by investor capital commitments), NAV facilities (backed by the fund’s loan portfolio), or direct credit lines. The end-borrowers are mid-market and lower-middle-market companies, often highly leveraged, that couldn’t get financing from traditional bank channels. These companies typically carry 4x to 6x debt-to-EBITDA, and in some cases higher. The bank’s collateral is ultimately the fund’s portfolio of leveraged loans to these companies.

Business Credit Intermediaries (21%): Loans to companies that in turn provide business financing. This includes BDCs, equipment leasing companies, specialty finance firms, and factoring companies. The end-borrowers are small and medium businesses.

Consumer Credit Intermediaries (9%): Loans to non-bank consumer lenders. This is where subprime auto lending lives. Tricolor Holdings, the company whose collapse kicked off the NDFI panic in September 2025, was a consumer credit intermediary. It sold cars and provided financing largely to borrowers with little credit history. JPMorgan, Fifth Third, and Barclays all had warehouse-style exposure. The end-borrowers are consumers who can’t qualify for traditional bank financing.

Other NDFIs (24%, roughly $395 billion): A catch-all category that includes insurance companies, pension funds, broker-dealers, investment banks, bank holding companies, and securitization vehicles. JPMorgan classified its entire $133 billion NDFI book as “other”, declining to break out subcategories, citing “organizational risk” associated with reporting different values to the FDIC and the Fed, according to the Financial Times.

The bottom line: 46% of all bank NDFI loans fund mortgage origination and private credit lending. The end-borrowers are homebuyers on one side and highly leveraged companies on the other. The remaining 54% funds everything from subprime auto loans to hedge fund margin lending to insurance company investment portfolios. 

5. All of the Jobs That No Longer Exist – Ben Carlson

Heading into the 19th century, about 70-80% of all jobs in the industrial world were in agriculture.

Most people were farmers.

By 1870, more than half of all men owned or performed labor on farms.

Today less than 1% of the U.S. population works in agriculture…

…There are plenty of jobs over the years that have been taken out by technology…

…There used to be people who would light all of the gas lanterns on the street by hand. They were replaced by electricity.

Before alarm clocks, people called knocker-ups used to go around tapping windows to wake people up…

…Before computers were around, NASA used human computers who literally did calculations by hand…

…It used to be someone’s job to set up the bowling pins by hand…

…There used to be video store clerks who would be forced to rewind the videos you forgot to rewind (and charge you for their troubles).

I could continue.

All of this job displacement and more has occurred yet the unemployment rate over the past 80 years or so has averaged less than 6%…

…There will certainly be a painful transition for many white-collar roles as AI is integrated into the workflow. I’m sure there are jobs out there that will be impacted by AI that we’re not even considering right now.

But new roles will also be created. AI will make so many people better at their current roles. That’s going to lead to more opportunities.

For many workers and businesses, AI will lead to more customers. Lawyers will be able to file more lawsuits. Tax accountants will be able to file more taxes. Financial advisors will be able to handle more clients. When bottlenecks are removed, output increases.


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 Netflix and Salesforce. Holdings are subject to change at any time.