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 08 November 2026:
1. The End of the Internet – Ben Thompson
Venkatesh Rao wrote an absolute must-read essay over the weekend called Cognitive Mercantilism. In brief, Rao makes the case that mercantilism rested on an assumption that economics was about scarcity and control; what brought about capitalism was demand. When people were freed from the burden of subsistence farming they discovered wants and desires at a scale that pulled entire markets into existence. Rao suggests the same might happen when people are freed from “subsistence cognition”. Rao concludes:
What gets missed is the possibility that we are witnessing the beginning of a transition as profound as the one from an overwhelmingly agricultural society to an industrial and commercial one. From a world where 80% of human brains are engaged in subsistence cognition to one in which 95% are engaged in satisfying previously unfulfillable cognitive demands.
The most important consequence of the agricultural revolution was not that farming became more efficient. It was that most people were liberated from the necessity of farming, allowing entirely new kinds of economic and cultural life to emerge. Likewise, the most important consequence of the AI revolution may not be that intelligence production becomes more efficient. It may be that most minds, human and eventually artificial, are liberated from the necessity of producing intelligence merely to survive, and become free to discover what they actually want to do with it.
The cognitive mercantilist sees a world threatened by an oversupply of intelligence and an impending surplus of useless minds. The AI Malthusian sees a world in which intelligence outruns the capacity of humanity to absorb it, leaving a growing population of economically redundant minds primed for revolutionary explosions. The cognitive capitalist sees the possibility of an almost limitless expansion of demand, and a world full of minds whose potential has barely begun to be explored.
I do understand why people have difficulty imagining this future. Capitalism, particularly over the last half century, has increasingly given way to scale, as ever larger corporations mediate ever more economic transactions, and as the Internet has played an important role in making the market a global one…
…This is where I come back to de Tocqueville: the Internet is an American invention, and has long been defined by American mores; the individuals who thrive on the Internet, no matter their nationality, come across as very American in their iconoclasm and cringe. Beyond the individual, however, there is the association, and amongst the association there is not a market, but infinite markets. Markets are just another word for needs and desires and the mechanisms of meeting and fulfilling them; the end of the Internet may mean the possibilities for creation are only just beginning.
2. Cognitive Mercantilism – Venkatesh Rao
AI panic is really a form of cognitive mercantilism. If we regard market capitalism as the first planetary intelligence, as many (including me) do, the parallels are closer than you might think…
…Capitalism emerged when people began discovering that wealth could be created rather than merely captured, and that ordinary people could be sources of demand and initiative rather than merely labor to be commanded as a factor of production…
…Third, economic thinking was overwhelmingly oriented toward supply and its control. Wealth came from controlling productive resources and commanding high prices for their output. Aggregate demand, especially demand from the poor, was barely recognized as a significant economic force. Ordinary people were primarily factors of production. They ate, worked, and reproduced, with no share of any surplus. The only real discretionary consumers were elites, who bought luxuries and commanded all surplus.
Fourth, there was little reason to imagine most people doing anything other than agricultural labor. If something like 80% of the population was engaged in inefficient subsistence farming, that was simply the natural order of things. What else were they good for? Remove them from the fields and you would merely have millions of useless mouths to feed…
…Third, the supply of intelligence is treated as the central economic fact. Controlling its production, preserving its scarcity, and maintaining high prices for brains and knowledge products (including AIs) are the primary concerns. The demand side barely registers. Less intelligent people are regarded as limited cognitive laborers and passive consumers of whatever knowledge products elites choose to provide. They are not imagined as significant sources of demand for intelligence in their own right, let alone as participants in its further production.
Fourth, the cognitive mercantilist assumes that most people are not good for much intellectually. If 80% of humanity is occupied in low-grade cognitive labor, or simply muddling along without producing much intelligence at all, that is unfortunate but natural. Automating their cognitive work merely threatens to create billions of useless minds to occupy.
This last assumption is where the analogy gets especially interesting.
The agricultural revolution that helped launch capitalism began overturning the apparent necessity of having most of humanity engaged in farming. Over the following centuries, improvements in agricultural productivity reduced the fraction of the population required to produce food from a large majority to a tiny minority in advanced economies.
The result was not a world full of useless mouths. It was a world in which vastly more people could do things other than farm, while enjoying access to vastly more food.
I don’t know how to farm. I can barely keep a houseplant alive. Yet I can obtain an astonishing variety of foods, in quantities that would have seemed fantastical to an early modern peasant. My inability to produce food is economically almost irrelevant. What matters is that I can consume it, enjoy it, develop tastes for it, and devote my energies to other things.
The analogous possibility with AI is that most people will no longer need to be significant producers of intelligence in order to become significant consumers of it…
…Why should AI systems themselves be regarded exclusively as producers of intelligence rather than potential consumers of it? What if they could be unlocked as new sources of aggregate demand, as happened with subsistence farmers?
Much of the contemporary AI discourse imagines AI as a purely supply-side technology: a collection of increasingly capable cognitive serfs that will produce intelligence for human consumption. Even discussions of autonomous agents tend to treat them as sophisticated servants pursuing goals assigned by humans.
But if we are serious about the analogy with capitalism, we should consider the possibility of AI systems becoming autonomous sources of demand for intelligence too. Intelligent demand for intelligence that harmonizes with human patterns of demand due to economic interconnectedness. Not demand for paperclips.
An AI agent pursuing open-ended projects, discovering new interests, collaborating with other agents, and generating its own reasons to acquire further intelligence would be participating in a cognitive economy as something more than a factor of production or paperclip-maximizing externality. The market itself, as the original emergent planetary intelligence, illustrates this possibility. Many products and services exist primarily because the “market” demands it, with humans being secondary consumers.
This is an argument for developing fuller forms of cognitive agency, rather than permanently confining AI to the status of obedient cognitive serfs.
From this perspective, some contemporary AI safety anxieties begin to resemble early modern elite fears of emancipated agricultural laborers. What will happen if these creatures are allowed to act independently? Won’t they become unruly, destabilize society, and threaten their betters? Won’t they turn monarchs and nobles into paperclips?
3. Wall Street Is Starting to Call the Shots in America’s AI Build-Out – Peter Rudegeair, Robbie Whelan, and Jack Pitcher
Lenders and investors are getting choosier about where to place their bets and are demanding tougher terms, signaling a new phase in the AI build-out. Among their concerns: the prospect of delays in big projects as a grassroots political backlash to data centers gains traction, and the threat that AI-related profits from hyperscalers and startups such as Anthropic and OpenAI won’t materialize as fast as promised…
…Bonds issued even by big tech companies such as SpaceX and Meta are trading at steep discounts. AI cloud companies such as CoreWeave, Nebius and Nscale that borrow big to build and sell capacity have effectively been shut out of the bond market in recent weeks, people familiar with the matter said…
…Raising money in equity markets isn’t much easier. Nscale’s hopes of going public next month have been thwarted, while rival Lambda dialed back the valuation it was seeking in a new fundraising round, people familiar with the matter said. And OpenAI has raised less than half of the $30 billion it had initially targeted for its latest funding round, people familiar with the matter said…
…There is still money available for creditworthy companies. SpaceX this week announced it raised the biggest-ever financing for AI chips, a $40 billion package that will allow it to purchase the latest lineup of Nvidia chips.
Its record only lasted a few hours, when chip-design giant Broadcom sealed a $63 billion deal to lease chips to Anthropic. But even that deal showed the strains of the current environment: Broadcom Chief Executive Hock Tan had to personally intervene in negotiations at the last minute to calm banks’ nerves…
…Across all types of U.S. corporate debt markets, AI-linked issuance totaled $394 billion in 2025 and $655 billion through mid-October of this year, according to Bank of America. Next year, analysts forecast nearly $1 trillion of fresh AI-linked debt.
Among the most prolific participants in capital markets are so-called neoclouds, companies that own or lease data centers, outfit them with fleets of AI servers and sign contracts to sell computing power to big tech companies, trading firms and AI startups. They are also the most sensitive in the AI sphere to rising interest rates, since their borrowing costs were already elevated before recent turmoil in the market.
Many neoclouds started out as cryptocurrency mining outfits, and most of them have scant histories operating AI infrastructure…
…Bonds issued by CoreWeave at a 9.75% rate earlier this year now trade at a yield above 15% in the secondary market, an indication of how much more expensive it has become to borrow over a short period. Bankers cautioned in recent weeks that the high-yield market for neoclouds was essentially shut for new offerings. Yields of 15% or more would be prohibitively expensive for borrowers.
4. Is this the first clear evidence of AI’s impact on the labour market? – John Burn-Murdoch
On Sunday, US financial analyst Eric Basmajian demonstrated that labour productivity in the sectors with heaviest adoption of AI has decisively ticked up from its pre-2023 trend, while other sectors have not. A day later, a Goldman Sachs research note showed that sectors with higher AI usage are seeing steeper declines in employment. So, are the productivity explosion and “jobpocalypse” upon us?
First up, it’s worth noting a few caveats. The Goldman result is sensitive to the use of a particular data source and looks at a particular time period. Swap in a richer employment dataset and the link with AI disappears. Run the same analysis two years ago and the link with AI comes out stronger, not weaker.
More importantly, if one extends both analyses to a range of other high-income countries and drills down from industries to narrower occupations, the picture becomes decidedly muddier…
…Another way of thinking about all of this is that occupational vulnerability to automation is about more than just whether new technologies are good enough at performing particular tasks. The concentration of lay-offs in software tells us businesses where output is highly scalable are especially exposed. As more companies in more sectors essentially become digital services companies, more employers may make the same bet on smaller workforces as US Big Tech.
5. The Beleaguered Chip Sellers Getting Their Revenge on Apple – Rolfe Winkler
Apple bullied flash makers into opening their books so it could monitor sales, making sure no one else got a better deal.
Kioxia and other flash makers stewed as Apple paid them pennies for flash storage that the iPhone maker resold to customers for dollars. The disparity in bargaining power had galled Nelson, who used Android phones in protest…
…In the past year, demand by AI hyperscalers has quintupled prices for flash, according to research firm TechInsights, opening a new era for Kioxia and other suppliers. Two years ago, Apple bought nearly twice the flash storage of Microsoft, Amazon, Meta and Google combined, according to TechInsights estimates. Hyperscalers are now buying double Apple’s share.
Flash memory suppliers and their sales teams privately expressed their glee at Apple’s comeuppance during chitchat at the industry’s largest conference this summer in Santa Clara, Calif. AI deals have given Kioxia sales executives and other flash suppliers new leverage to charge Apple higher prices…
…Hyperscalers can afford to pay more. Flash storage is a smaller part of building a data center than making an iPhone, and accounting rules allow companies to spread the cost over years…
…Buyers of the iPhone 17 Pro paid Apple $200 last year for double the storage of its 256-gigabyte base model. The extra storage at the time cost Apple $15 and has since shot up to $66, according to an analysis by The Wall Street Journal…
…The company had another hardball tactic: Avoid commitments. After ordering flash at rock-bottom prices, Apple would refuse delivery at times if flash prices were falling. That left suppliers holding piles of unsold chips, including ones custom-made for Apple. Kioxia executives joked they felt like Charlie Brown trying to kick the football—with Lucy always pulling it away.
The standoff often ended with suppliers further cutting Apple’s prices.
The executive behind that strategy, Tony Blevins, was Apple’s head of procurement. He became known as the Blevinator for clever negotiating tactics—or ruthless ones, said suppliers.
Blevins, who left Apple in 2022, sometimes set up back-to-back meetings with suppliers so that rival sales teams might run into each other, stoking competitive tension. Sales representatives learned to pack nutrition bars to sustain them through negotiating sessions that Apple executives sometimes pushed past midnight without a dinner break. Blevins’s bad-cop reputation gave his staff leverage: They threatened to call him in if contract terms weren’t to their liking.
One significant contract term allowed Apple to audit its suppliers’ books. Flash makers typically had to designate Apple as a “most favored customer,” which guaranteed that no other buyer got a lower price, according to people familiar with the agreements. Apple’s audits allowed it to verify that no one paid less.
Apple caught Micron selling flash at cheaper prices to another customer and won an arbitration settlement worth tens of millions of dollars more than a decade ago, said people familiar with the dispute. Apple audited its suppliers so often that Blevins negotiated a volume discount with the auditor, Deloitte.
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