Concentration Risk

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This week's premium will be The Hater’s Guide To Broadcom, a company that has long ceased to innovate, and whose existence centers on buying successful companies and jacking up prices, and now, building chips for Anthropic and OpenAI, while also taking on (and backstopping) insane amounts of debt. In short, Broadcom is the unholy lovechild of NVIDIA and Oracle. If you want to get in touch — and especially if you have any juicy information about Anthropic, OpenAI, or any other companies in the AI bubble — hit me up on Signal at ezitron.76. I’m also on IB on your Bloomberg Terminal. Jensen Huang, CEO of NVIDIA, the largest company on the stock market, has declared that “AGI has arrived” in a response to the CEO of Crusoe congratulating OpenAI on the launch of its GPT-6 Astra model, who said that this “made Abilene the birthplace of AGI.”Per sources with direct knowledge of the current progress of Stargate Abilene, the AI data center being built by Crusoe for Oracle to lease to OpenAI, there are at most four out of eight buildings functional at the Abilene campus, which started construction some time in 2024. Huang at no point defines what “AGI” is, other than to say that we’ve reached it, and that “400k GPUs coming online” was what was next, I assume referring to somewhere else on Earth, because Abilene only has space for a total of 400,000 Blackwell GPUs, of which (as I’ve noted) at best half of which are actually installed and functional.The reason that everybody is talking about AGI is that TIME magazine, bereft of any journalistic standards or shame, quoted OpenAI Chief Research Officer Mark Chen as saying that OpenAI was “80% of the way” to AGI,” only for Chief Operating Officer Greg Brockman to say a few days later that we had entered the “AGI era, whether you view it as this model, the last one or the next one,” which the Wall Street Journal agrees with, even though it cannot define exactly what AGI means, but this is the AI bubble and those most-responsible for telling the truth are mostly incapable or unwilling to bother.These companies are treating everybody like they’re stupid, in large part because everybody, including the largest media outlets in the world, appears to fall for just about anything. Neither NVIDIA nor Crusoe have actually done anything — we have not reached “AGI,” nor has “the birthplace of AGI” been completed, nor does anybody seem to bring up these facts in any of the pieces I’ve read outside of saying “hmm, well AGI isn’t really well-defined,” humouring what these companies are saying without a single thought entering their minds. If anything, the far-more-interesting way to look at this is why all of these people are suddenly jerking their shit from first principles over a term that is meant to mean “an artificial intelligence that can handle tasks beyond its original training” but now means basically anything the companies want it to, and how that times with the rush for both Anthropic and OpenAI to go public. The answer is pretty simple: these people want to stop you thinking about what’s actually happening — that the underlying financials and demand do not make sense, and their cloud software does not remotely justify its alarming costs.Today I’m going to talk to you about why I think there’s a Silicon Valley Financial Crisis brewing, and the concentration risks involved. Let’s Talk About Concentration RiskSo, today we’re going to talk about a term you may or may not have heard of before: concentration risk.It’s a term that refers to having all your eggs in one or a few baskets, becoming overly reliant on a few investments, customers or particular business lines to the point that without them your business or portfolio would suffer massive harms. In banking specifically, to quote the National Credit Union Administration, it refers to any single exposure or group of exposures with the potential to produce losses large enough (relative to capital, total assets, or overall risk level) to threaten a financial institution’s health or ability to maintain its core operations.I bring this all up because you’re going to hear this term, or variations of this term, a lot in the next few months and years as the AI bubble unravels, because just about every part of the industry involves its own flavor of concentration risk.80% Of OpenAI And Anthropic’s Enterprise Revenues Come From 1% Of Its Customers, Which Skew Heavily Toward AI Startups Subsidized By Venture CapitalLet’s start at the top. Per data from fintech firm Ramp, 80% of OpenAI and Anthropic's enterprise revenues come from 1% of their customers, a number that hasn’t improved over the last three years. Ramp’s lead economist Ara Kharazian notes that the top 1% skews heavily toward the tech sector and AI products and services, and that this was a level of concentration risk unseen in any other software category they tracked.Oh, and it hasn’t gotten better over time.This dataset, which likely includes big companies like Visa and Cursor as well as a great deal of startups and regular-sized companies, is indicative of the overall spend of the AI industry, with the caveat that it doesn’t include massive players like Microsoft or major banks, and customers can opt out of being included in research.I also want to be clear that when Ramp says “AI products and services,” that includes AI startups that sell subscriptions with subsidized token spend, meaning that users can burn far more than their subscription price in tokens. This means that the money made by Anthropic or OpenAI from an AI startup in that 1% spend is contingent on their continued ability to raise venture capital. This means that the vast majority of enterprises — which is where the real money is in software — just don’t spend that much money on AI. Those that do spend the most on it are heavily-concentrated in either AI companies that either use a lot of tokens internally because they’re bankrolled by venture capital, AI companies that allow their users to blow unsustainable amounts of money on tokens bankrolled by venture capital, tech companies that are currently under heavy peer pressure to spend money on AI tokens, and I assume a few whale customers of some sort.Concentration Risk 1: AI Startups Are The NINJA Borrowers Of AI During the Great Financial Crisis, millions of people took on debt they never had any hope of paying, with one of the most egregious examples being “NINJA” loans — No Income No Job Applicants. Per Pew, “...in the years before the Great Recession, almost 38% of new mortgages required little or no documentation.” To be specific, 36.5% of 2005 and 37.9% of American home purchases in 2006 were from buyers with little-to-no income documentation, which meant that, for the most part, these subprime mortgage payments were only made possible by a system that was desperate to create more demand for loans rather than creating a lending agreement with a stable customer who would be able to make regular payments. Sidenote: Before we go any further, I want you to also know that “subprime” doesn’t refer to the borrower but the loan itself. Plenty of “well off” people got mortgages they couldn’t afford in the time leading up to the Great Financial Crisis.A “homeowner” in 2005 and 2006 could easily be somebody who could not, in any real sense, afford the home they were buying.I sure hope that nobody is making that same mis-OH MY GOD!Anthropic and OpenAI Are Dependent On Artificial Revenue Driven By Unprofitable Venture-Backed AI Startups For Billions Of Dollars Of Revenue This means that 80% of OpenAI and Anthropic’s enterprise revenues — which make up the vast majority of their total revenues — are dependent on what are likely hundreds of customers spending outsized amounts of money on AI tokens, with an indeterminately-large chunk of them being AI startups that can only do so as long as venture capital supports them. Let me break down exactly what this means:AI startups, when they run their services, connect to models provided by OpenAI and Anthropic and pay on a per-million token basis.In virtually every case I’ve found, the AI startup “subsidizes” the AI use of their customers, allowing them to burn way more than their monthly subscription in tokens, with the AI startup paying for the tokens at either full or a slightly-discounted price.This is only made possible through endless venture capital. For example, legal AI startup Harvey has raised over $1 billion and is trying to raise another $500 million, all while only having $350 million in ‘annualized’ revenue, meaning (assuming a straight-line month x 12 calculation) it makes only around $29 million a month. Harvey, like many AI startups, is sending hundreds of millions of dollars to Anthropic and OpenAI.This means that these AI startup customers will, at some point, run out of money to keep feeding to OpenAI and Anthropic, because running their services is economically unviable by the very nature of connecting to AI models.AI startups are an artificial source of revenue. They are not paying Anthropic and OpenAI out of cashflow,