We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.
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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 02 August 2026:
1. Cyprus – “weird” opportunities galore – Swen Lorenz
In 1999, the main index of the Cyprus Stock Exchange rose nearly tenfold, making it the world’s best-performing stock market.
It was one of history’s greatest investment manias:
- Brokers had such a backlog of orders that it took them up to three weeks to clear a trade.
- Some Cypriot farmers reportedly sold their sheep to invest the proceeds in the stock market.
- Hastily arranged IPOs were oversubscribed by a factor of 50-100x.
- One IPO by a small cruise company attracted subscriptions equivalent to 10% of Cyprus’ GDP.
- A small shopping mall suddenly reached a valuation of EUR 2bn, roughly equal to the entire market cap of the Cyprus stock market before the boom began.
The business section of Britain’s The Guardian reported at the time:
“Everyone, housewives, cleaning ladies, ministers and businessmen are in on the act … The mania has reached such heights that from Cyprus’ taverna-terraced beaches to its remote mountain villages few now talk of anything else.”
It ended much like almost every investment mania ends: in tears.
After breaking records on the way up, the Cypriot stock market broke records on the way down, too. The market index ultimately lost 99%, which, according to some, remains the largest decline ever suffered by a national stock market index. By comparison, Greece “only” lost 92.5% during its sovereign debt crisis, while Germany’s hyperinflation between 1918-1922 saw the market fall by 97%.
2. You just hired a million bad employees – George Sivulka
For the first time in history, humans are cheaper than software.
And AI is creating more jobs than it eliminates…
…Managing AI is harder than managing people, because AI scales dysfunction instantly. Fortunately, we can learn from the past:
Agent workforces and human workforces fail in the same way.
Understanding the 7 major parallels between the two will unlock the next trillion dollars of AI value creation…
…1. Tokenmaxxing is throwing bodies at the problem…
…People are spending so much on tokens because they don’t know how to use them.
Maybe 1 in 100 employees knows how to give AI context. It’s a rare breed of person that can articulate a process clearly, that has the patience to empathize with a polluted context window, or even understands what that means.
Give an agent harness to the other 99 people and they will produce “loops”.
2. Loops are meetings about meetings…
…3. Wasted tokens are the new headcount bloat…
…Just like 80% of employees do nothing, 80% of tokens today do nothing.
People create more people. Tokens create more tokens. Looping is the new empire building.
4. 100X tokens are the new 10X engineers…
…In the same way a handful of employees make others 10X as productive, for any given job some amount of token context can cut AI effort down by orders of magnitude. There exist tokens that will give you 100X as much leverage.
Humans are cheaper than tokens on average, but good tokens are cheaper at scale…
…5. Context hoarding is the latest job security tactic.
There’s a massive political problem with AI inside the firm, and it will only get worse.
Employees don’t want to teach AI systems their secret sauce….
…6. Evals are the new OKRs.
The best way to manage a token workforce is the same as the best way to manage humans: by defining what good looks like.
The one breakout AI use case that escaped politics is coding. It expanded the pie and made every engineer better.
The mechanism is evals. 99% of AI revenue today is coding because coding has built-in evals. Code runs or it doesn’t…
…7. The next trillion-dollar opportunity is the transformation company.
Enterprises have been buying foundation model commits, the application layer, and internal builds for years now. All of it conceals a brutal truth about the economics:
Nobody has AI working reliably yet…
…In fact, the next biggest businesses won’t be eating existing services spend. They will sell a net-new type of service to existing players:
“AI transformation companies” will be 10X larger than any neofirm.
Transformation sounds like a one-off project. But there’s a Jevons paradox at work: every use case an organization adopts surfaces ten more. The more AI-enabled a firm becomes, the more transformation it consumes, while the frontier of what’s possible advances daily. Ongoing AI transformation efforts will become the only way to compete.
3. Data-Center Builders Are Racing to Offload Stakes Worth Billions – Anissa Gardizy
Data-center builders and operators across the U.S. are working with bankers to sell majority equity stakes worth tens of billions of dollars in their companies this summer, according to people familiar with the efforts…
…Sales of data-center operators are on the rise as owners of these firms seek exits and investor interest in owning the physical infrastructure behind advanced artificial intelligence grows. A massive backlog of demand for server capacity pushed companies to pursue novel strategies to secure more of it, from renting chips from direct competitors to launching data centers into orbit…
…Whether there are enough buyers with the means to absorb so many large deals at once this summer remains an open question. Ravi Purohit, the co-head of infrastructure at Paul Weiss, said that while plenty of investors want exposure to data centers, only a handful of firms can afford multibillion-dollar deals…
…But as these megadeals scale up, developers are increasingly running into fierce local opposition, driven by residents’ anxieties over rising utility bills, noise and advanced AI services in general. In some cases, it has pushed developers to pause or walk away from projects. This all makes investing in data centers riskier than it was in the past, investors said.
“I think people are downplaying the significance of Nimbyism in this country right now,” Purohit said, adding that companies looking to sell this summer will be scrutinized for how they plan to handle it.
“The more they can demonstrate to buyers that they have a constructive relationship with these communities…that actually goes a really long way,” he said.
4. How Terrorist Groups Are Using A.I. to Gain an Edge in Battle – Dustin Volz and Eric Schmitt
When a gang of motorcycle-riding members of Boko Haram attacked a military base in eastern Nigeria a couple of years ago, they were stymied by a defensive trench surrounding the complex.The extremists regrouped. Before launching another assault, they asked A.I. for help.
“We saw in a movie how motorcycles can jump over bridges,” a former Boko Haram commander told Antonia Juelich, a terrorism and technology researcher at Cambridge University. “We used A.I. to learn how to do this. We gave it information, like what motorcycles we use and the distance we need to jump and so on, and it gave us steps on what we have to do.”
Using tips from chatbots, mechanics modified the motorcycles to allow for faster acceleration and top speed. The riders dug their own holes, filled them with broken glass and fire, and practiced jumps — sometimes with fatal outcomes — until they achieved enough aerial liftoff to mount a successful attack, defectors said…
…Until recently, the Islamic State, Al Qaeda and other extremists primarily used A.I. in the information-operations realm — propaganda production, translation, recruitment and security tradecraft. But that has evolved as jihadists have turned to A.I. for tactical on-the-ground advantages, according to current and former U.S. military and counterterrorism officials and independent researchers…
…Daniel Byman, a terrorism expert at Georgetown University and co-author of a report about A.I. and the future of terrorism released on Friday by the Center for Strategic and International Studies, said terrorist groups were “mixing and matching” from different A.I. systems, seeking to avoid technical guardrails established by the A.I. companies. Dr. Juelich’s research also found that Boko Haram was platform agnostic, interchangeably working with OpenAI’s ChatGPT, Anthropic’s Claude, Google’s Gemini and xAI’s Grok, as well as the Chinese firm DeepSeek…
…Defectors recounted attending organized training sessions focused on how to best leverage the powers of generative A.I. models to inform or enhance their uses of the technology.
The trainings, in which laptops were equipped with virtual private networks and encryption software, were delivered via transnational jihadist networks often led by members of the Islamic State, interviewees said. Common topics included managing an account on an A.I. platform, suggestions on generating useful answers and tips on evading safety restrictions.
5. Are We Repeating the Biggest Mistake of 1873? (Transcript here) – Merryn Somerset Webb and Liaquat Ahamed
Liaquat Ahamed: What started it was the gold rush. Europe, which was the centre of the world, had gone through a terrible depression in the 1840s, fuelled by bad harvests and by revolution. They actually thought every government in Europe was going to fall and that we’d have the equivalent of the Russian Revolution across Europe. That didn’t happen — but at the same time, they discovered gold in the United States, and that provided the fuel to get the global economy going.
You had bankers like the Rothschilds, who had made a ton of money in the early part of the 19th century lending to governments, jumping on the bandwagon and starting to lend for infrastructure — particularly the railroads — but to the private sector. You got a massive boom in lending, and it was a boom based on the bond market. Everyone thinks the bond market is a sleepy place where people who don’t want to take risk put their money, but it was essentially the bond market that provided the impetus to growth. It grew by five times in the two decades from 1850 to 1870…
…Merryn Somerset Webb: That’s interesting, and we’ll come on to it — whether economies are incredibly resilient and whether the best thing to do is just leave them alone. Because when we get to 1873, we find out that everyone decided not to leave it alone. They succumbed to what we’d call “something must be done”-ism, and that’s when things started to get nasty.
But the pivotal moment is this war between Prussia and France that starts in 1870. It’s a short war, but it has enormous repercussions, because France is obliged to pay enormous reparations to Germany — to the tune of how much?
Liaquat Ahamed: Around a billion dollars.
Merryn Somerset Webb: A billion dollars, which would be the equivalent of $1.2 to $1.3 trillion today. And Prussia thought this was fine, because so much money would take France forever to pay off. This would keep them down and out of the way — the enemy dealt with indefinitely. Instead, France somehow managed to go out and get the bond markets to give them a billion bucks over two years. And it was the Rothschilds who were at the centre of that, because they had incredible reach.
Liaquat Ahamed: They raised two bond issues which together raised a billion dollars. But the most important thing was that in one case the issue was three times oversubscribed, and in the other, twelve times…
…Merryn Somerset Webb: And the London Stock Exchange went crazy.
Liaquat Ahamed: Because everyone who didn’t get into that bond issue still had their money.
Merryn Somerset Webb: Exactly.
Liaquat Ahamed: And in the US, the railroads had been a perfectly rational boom until then — and then suddenly railroad bond issues doubled. We went up to $500 million a year in an economy where that was roughly 5% of GDP.
Merryn Somerset Webb: Which today would be $1.5 trillion in the US. So that $1.5 trillion — the sort of money that goes into a SpaceX today — is what went into the railroads then. Fascinating. And then of course that billion dollars went to Germany over a two-year period.
Liaquat Ahamed: Yes, and they then had 25% of GDP to play with in cash.
Merryn Somerset Webb: And that was totally mismanaged.
Liaquat Ahamed: They could have fed it into the economy at a slower pace. But injecting 25% of GDP in liquid cash into an economy that was relatively unsophisticated — where everyone who owned government bonds suddenly found their bonds paid off —
Merryn Somerset Webb: Paid off meaning redeemed.
Liaquat Ahamed: Yes. They looked around and said, “What do I do with this money?” and started hunting for opportunities. And lo and behold, a whole lot of charlatans appeared on the scene to relieve them of it. It was not only a stock market boom but a giant IPO boom. The stock market, which had maybe 30 or 40 companies listed, suddenly ballooned to 500 or 600. A lot of them were banks, a lot were real estate, a lot were railroad companies — but there were also all sorts of things, like companies set up to explore the northern regions of Europe, or to look for banana plantations in West Africa. It was a crazy time…
…Merryn Somerset Webb: So the crash starts in Vienna. But because there had been a global boom and a global bubble, it spreads. There’s contagion across the world.
Liaquat Ahamed: Yes. You actually get a false period of calm. It crashes in Vienna, everyone says there’s going to be a global disaster — and then nothing happens for three or four months. So people said, maybe Vienna was just overpriced. It was a local incident. Everywhere else, earnings will rise to match prices and it’ll be fine.
But meanwhile, Jay Cooke — the premier investment banker, who had raised $2 billion for the Union government during the Civil War — suddenly found that because of the disruption in Europe he couldn’t raise capital. He ran out of money in the middle of constructing the second transcontinental railroad. It was a little like the Lehman Brothers story: he started injecting his own bank’s money into the project, and still couldn’t complete it. When he announced that he couldn’t raise the capital, there was total panic — the same sort of psychological panic that happened after Lehman. People said, “If Jay Cooke, a friend of the president and the most well-connected banker in the United States, can’t raise $100 million, what hope do we have?”
Every railroad stopped construction. There were 500 railroad companies in the United States; by the end of the year a third of them had stopped paying dividends, and within five years half of them had defaulted.
Merryn Somerset Webb: Everything comes crashing down.
Liaquat Ahamed: Everything comes crashing down.
Merryn Somerset Webb: And at the same time everything’s still going horribly in Europe — 70% of the banks in Vienna have gone bust. It’s global carnage…
…Liaquat Ahamed: What caused the boom to end? I think two things. One is that everyone tried to build railroads at the same time, so they started competing against each other and railroad profitability began to decline. The equivalent today is all of the hyperscalers trying to build AI infrastructure at once, and the price of tokens starting to collapse — which, by the way, has already started.
Merryn Somerset Webb: It’s already happening.
Liaquat Ahamed: It changes the economics of their investment. And at the same time, because of the disruption in Europe and the war, the price of capital started rising — and there are some signs of that happening now. Until recently we reassured ourselves that we could finance this boom out of the profits of the giant technology companies. But even that has proved inadequate, and they’re now going out and borrowing.
So the combination of declining profitability and a rising cost of capital at some point causes a crunch. In the US case, when Jay Cooke announced he couldn’t complete his railroad — the equivalent today would be OpenAI declaring, “Actually, we think we’ve miscalculated, we’re not going to be able to complete a whole model, and we’re going to have to sell to Microsoft.” Can you imagine the panic that would occur in the market for AI infrastructure?
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