We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.
Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!
But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.
Here are the articles for the week ending 17 May 2026:
1. A Government Debt Crisis? – Ben Carlson
One of my favorites is the 1972 Time Magazine cover story:
This sounds like it could have been written today:
Debt service is now the third highest public expense, exceeded only by spending for defense and education; most of the money goes to banks, which are the major buyers of bonds that governments at all levels sell to cover their deficits. Moreover, debt functions as a wrong-way income redistribution device, channeling tax money that is paid in large part by the poor and the middle class into the pockets of wealthy holders of trust accounts or stock in banks.
When this cover was published, government debt was roughly $430 billion.
Today it’s fast approaching $40 trillion in total…
…The Wall Street Journal shows that publicly held debt to GDP is now 100% for the first time since WWII..
…Here’s the trillion dollar question — why have none of the government debt crisis predictions come to fruition?…
There are two big mistakes people make when they predict a catastrophe from U.S. government debt levles:
1. Conflating U.S. government debt with household debt. Government debt is not like a mortgage that needs to be paid back. As long as the economy keep growing, debt levels will likely keep rising.1 Plus, the U.S. government has the ability to print the global reserve currency. You can’t print more dollar bills in your basement.
2. The government’s liabilities are someone else’s assets. Treasuries are bonds owned by pensions, insurance companies, fund managers, and households. It’s the largest, most liquid bond in the world and there isn’t an alternative…
…So what would make me worry about government debt levels?
The biggest risk of large deficits and government spending is inflation…
…Continuously rising interest rates would also be cause for concern…
…Another concern is the fact that interest expenses are becoming a larger share of the government’s budget…
…Interest expenses now exceed the defense budget.
The good news is that interest expense as a percentage of GDP is at 1980s levels.
The bad news is that it has risen like a rocket and rates were a lot higher back then…
…Is there a line in the sand where a government debt crisis automatically kicks in?
No one knows.
2. China’s $3 Trillion of Hidden Bad Debt Prolongs Economic Pain – Bloomberg News
By any measure, Tom Hu should be in default on a $730,000 bank loan for his plastics business in China. He barely brings in enough revenue to pay expenses and can’t cover the debt costs.
Yet rather than calling in the loan, his bank lets him defer payments — keeping him afloat, while avoiding another past-due loan on its books…
…Stories like Hu’s are playing out across China as banks grapple with a growing pile of bad debt. It’s impossible to quantify the true extent of the problem, though most economists say the ratio of bad loans is significantly higher than the 1.5% official rate. One analyst at Absolute Strategy Research in London pegs it at about 10%, which would mean a staggering $3 trillion in loans that should be classified as past due are not. Others say it could be double that amount…
…The apparent stability of the official bad loan rate is all the more surprising given that the economy has experienced a major property collapse and posted the slowest nominal growth outside Covid since the 1970s. In March, China lowered its 2026 growth target to between 4.5% and 5% — its least ambitious goal since 1991.
Regulators have taken note. Despite seemingly strong capital buffers and stable NPL ratios, officials have moved to bolster the nation’s six biggest banks with more than $100 billion in fresh capital…
…The primary culprit for the surge in bad loans is a mountain of credit extended to companies whose earnings are insufficient to cover interest payments. About 10% of listed non-financial firms have failed to cover interest payments from their earnings before interest and tax for three consecutive years, according to Absolute Strategy Research. As a result, the non-performing loan ratio is probably closer to 10% than 1.5%, according to Adam Wolfe, an emerging markets economist at the firm…
…China’s official NPL ratio has always been a bit of a mystery. In good times and bad, it’s rarely wavered much from 1.5%, and most economists say it greatly understates the true stress in the system. The figure captures only loans officially classified as “substandard,” “doubtful,” or “loss.”
In reality, the classification is often a subjective assessment and banks have different internal criteria. A much larger pool of troubled credit remains in the “special mention” — those that may have already become overdue but yet to be categorized as nonperforming — or “normal” categories, thanks to an aggressive use of leniency known as forbearance.
Existing rules stipulate that when repayment on a loan is overdue by more than 90 days and the borrower can’t fully repay the amount, it should be marked as nonperforming.
Economists including Wolfe estimate that about 40% of loans are either eligible or already in some sort of forbearance program, where banks are strongly discouraged from seeking repayment or recognizing losses…
…In other words, rather than cracking down on deadbeat borrowers, China’s banks are encouraged to cut them some slack. Regulators have for years urged the big banks to keep their reported bad loan ratio under 2%, according to people familiar with the guidance.
With the forbearance policy — a legacy of Covid support programs that’s been extended to property developers and other firms — Beijing is signaling its desire to maintain financial stability. It wants to avoid a rash of bank failures that would follow a surge in reported bad credits and company defaults.
A leniency policy for small businesses that was introduced during the pandemic was extended in 2024 to encourage banks to roll over loans for companies enduring temporary difficulties. This policy is effective until late next year, and applies to 9.4 trillion yuan ($1.38 trillion) worth of loans, according to officials.
As a result, banks routinely roll over maturing loans, extend repayment periods, or allow interest to be capitalized to avoid triggering NPL recognition. Local governments also exert pressure on lenders to maintain stability by avoiding cuts to risk classifications on loans tied to sensitive sectors. Those include property developers, local government debt and small businesses in weaker regions, according to a dozen bankers interviewed by Bloomberg News…
…All this leniency comes at a cost. Financial resources are trapped in unprofitable and even inactive firms, hindering banks’ ability to promote growth in healthy businesses. Overall loan growth is slowing significantly after fixed-asset investment experienced an unprecedented contraction last year…
…Chinese banks are also accelerating write-offs and transfers of bad assets. Lenders have disposed of more than 3 trillion yuan of non-performing assets a year since 2020, with the total rising to roughly 3.8 trillion yuan in 2024, the highest on record.
Banks have stepped up transfers of NPL portfolios to asset management companies, which typically hoover up bad assets in China. Still, these firms entrust collection back to the originating banks in many cases, according to people familiar with the matter. The funds used to purchase bad loans largely come from the banks, meaning the risks aren’t fully removed from the financial system.
3. The Inference Shift – Ben Thompson
Specifically, coding with LLMs requires a human in the loop. It’s the human that defines what is to be coded, checks the work, commits the pull request, etc.; it’s not hard to envision a future, however, where all of this is completely handled by machines. This will apply to agentic work broadly: the true power of agents will not be that they do work for humans, but rather that they do work without human involvement at all.
This, by extension, will mean that the likely best approach to solving agentic inference will look a lot different than answer inference. The most important aspect for answer inference is token speed; the most important aspect for agentic inference, however, is memory. Agents need context, state, and history. Some of that will live as active KV cache; some will live in host memory or SSDs; much of it will live in databases, logs, embeddings, and object stores. The important point is that agentic inference will be less about GPUs answering a question and more about the memory hierarchy wrapped around a model.
Critically, this articulation of an agentic-specific memory hierarchy implies a necessary trade-off of speed for capacity. Here’s the thing, though: lower speed isn’t nearly as important a consideration if there isn’t a human in the loop. If an agent is waiting around for a job that is being run overnight, the agent doesn’t know or care about the user experience impact; what is most important is being able to accomplish a task, and if entirely new approaches to memory make that possible, then delays are fine.
Meanwhile, if delays are fine, then all of the focus on pure compute power and high-bandwidth memory seems out of place: if latency isn’t the top priority, then slower and cheaper memory — like traditional DRAM, for example — makes a lot more sense. And if the entire system is mostly waiting on memory, then chips don’t need to be as fast as the cutting edge either. This represents a profound shift in future architectures, but it also doesn’t mean that current architectures are going away:
- Training will continue to matter, and Nvidia’s current architecture, including high-speed compute, large amounts of high-bandwidth memory, and high-speed networking, will likely continue to dominate.
- Answer inference will be a meaningful market, albeit a relatively small one, and speed from chips like Cerebras or Groq (I explained how Nvidia is deploying Groq’s LPUs here) will be very useful.
- Agentic inference will gradually unbundle the GPU, which alternates between stranding high-bandwidth memory (during the prefill process) and stranding compute (during the decode process), in favor of increasingly sophisticated memory hierarchies dominated by high capacity and relatively lower cost memory types, with “good enough” compute; indeed, if anything it will be the speed of CPUs for things like tool use that will matter more than the speed of GPUs…
…To date the invocation of “scaling with compute” has implicitly meant Nvidia bullishness. However, much of Nvidia’s relative advantage to date has been a function of latency: Nvidia chips have fast compute, but keeping that compute busy has required big investments in ever-expanding HBM memory and networking. If latency isn’t the key constraint, however, then Nvidia’s approach seems less worth paying a premium for…
…China, meanwhile, for all of its lack of leading edge compute, has everything it needs for agentic inference: fast-enough (but not leading-edge) GPUs, fast-enough (but not leading-edge) CPUs, DRAM, hard drives, etc. The challenge, of course, is compute for training; it’s also possible that answer inference is more important for national security, at least when it comes to military applications.
4. 50 Learnings from the War in Iran – Tomas Pueyo
Missile and drone launching can be dramatically curtailed, because you can track where they’re launched from and destroy that.
But they’re very hard to fully eliminate. This is the beginning of aerial drone warfare. It suggests it will be super important in the future as an asymmetric weapon: Countries can produce drones in a decentralized way and launch them from many different, constantly changing places.
The other way in which drones and missiles can be intercepted is at the destination. Israel has proven that this can work quite well: Iran has been unable to cause critical damage in the country despite trying over and over again…
…Iran’s entire fleet was destroyed in a matter of days (Ukraine did something similar over the last few years, virtually wiping out Russia’s fleet in the Black Sea).
This marks the end of naval warfare as we know it. Few countries will invest in a full traditional naval force anymore…
…Israel and the US blew up a lot of the command chain, but they couldn’t have done that just with airplanes. They needed intelligence, satellites, cyber penetration, AI, amazing communications, and fast command decisions. Doing all of these steps well and integrating them seamlessly is beyond the capability of most countries today…
…For the first time in history, Israel deployed an Iron Dome system in a foreign country—the UAE—manned by Israeli soldiers. This is unprecedented: Israel defending Arabs against other Muslims!…
…Iran finally executed their biggest threat, which gave them lots of leverage in negotiations: They closed the Strait of Hormuz.
It wasn’t clear that this was a threat they could actually follow through with. But it is. They closed it.
They did so even without air supremacy or a naval force. This is very counterintuitive! It turns out you can use small boats and drones to close a big international highway…
…Although US opponents have more incentives to de-dollarize, one thing is to want it and the other to succeed. The dollar has actually risen during the war, and its position as a reserve currency hasn’t changed.
5. An Ode to Restraint: Lessons from the Tim Cook Legacy! – Aswath Damodaran
If you were to create a profile of Tim Cook, the manager, based upon the choices that he has made at Apple during his tenure as CEO, two very divergent views emerge. To his admirers, his actions on some fronts (initiating dividends, massive stock buybacks, borrowing money) and inaction on other fronts (no big acquisitions, diffidence on AI investments), represent an exercise in discipline and restraint, preserving the company’s crown jewel (the iPhone) and fending off the bankers and consultants, with their false promises. To his critics, and there are quite a few, Cook’s caution has cost Apple its disruptor status, when it could have used its ample cash reserves to buy its way or invest in into almost every new business that has bloomed in the last fifteen years. In fact, they point to chances that Apple has had to buy some of the biggest stars in the market, from Tesla and Netflix more than a decade ago to Anthropic, Mistral and Perplexity in more recent years.
It is impossible to argue that one side is right and the other side wrong, but it is undeniable that both pathways (the restrained pathway that Apple adopted and the more aggressive pathway that it could have taken) include trade offs. It is true that Apple’s restraint has led it to miss out on some of the biggest trends in technology over the last decade, but it has also avoided the overpayment that is so common with high profile acquisitions of big companies. The argument that Apple would be worth a lot more today if it had bought Netflix or Tesla a decade ago falls flat for two reasons. The first is the selection bias in picking two companies that, in hindsight, have emerged as winners, when in fact there were at least a dozen other worse-performing companies that were also on Apple’s radar. The second is the presumption that companies like Tesla or Netflix would have been just as successful, owned by Apple, as they were as stand alone enterprises. The clash of corporate cultures that would have ensued if Apple had bought either Tesla, a company that reinvents its business narrative every few hours, or Netflix, an entity that makes content in quantity with the hope that some it sticks, would have been epic, with the risk that both Apple and its acquired target would have gone down in flames.
More generally, though, the question of whether you want a visionary or a disciplined business builder at the top of a firm is not one that has an easy answer, since it depends on the firm in question. In my work on corporate life cycles, I focus on the management skills that are needed most in a company, based upon where it is the life cycle, and that may help address the choice between vision and restraint:…
…With young companies, vision dominates, as managers work to sway investors, employees and nascent customers that their product or service will find a market. As the vision takes hold, converting it into commercial products and services requires trading off some portions of vision for pragmatism, in the interest of getting the business going. As products and services find demand among customers, business building becomes a key difference-maker, with the grunt work of marketing, production facilities and supply chains coming into play. Assuming that you have made it through these three stages, the trade offs of scaling up come into focus, and as you hit market limits, success depends on being opportunistic in finding new products and markets, but only if they exist. In corporate middle age, pathways to easy growth, especially at scale, become difficult to find, and to the extent that value comes from moats and core products, playing defense against competitors takes priority. Finally, in decline, a phase that no company ever wants to enter, but is inevitable at some point, you need to be willing to shrink a firm, shutting down businesses that no longer deliver value and selling other assets to high bidders.
Given these very divergent management functions, it should come as no surprise that there is no prototype for the perfect CEO, McKinsey and Harvard Business School blueprints notwithstanding.
Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Apple and Netflix. Holdings are subject to change at any time.