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Exit Liquidity

6

I’m taking a week off of premium as I’ve had a family situation that has absorbed a lot of my time this week, but I’ll be back with a barnburner next Friday (11/6).

In the interim, I’m running a week-long sale — 10% off of the $70-a-year subscription for life (click here!) — for new subscribers. It’s a great way to support my work, and you get an absolute ton of value at a lower price than basically every competing newsletter.

Over the past few months, I’ve published a two part guide to the world of AI debt, an analysis of the (dubious) impact of generative AI on the global economy, deep analyses of the biggest players in the AI infrastructure space like NVIDIA (part one and two) and Oracle (part one and two), how OpenAI will eventually kill Oracle, and how venture capital is killing itself.

If you want to get in touch — and especially if you have any juicy information about Anthropic, OpenAI, Blackstone 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.

Last week, I opened my newsletter with a quote from Apollo Chief Economist Torsten Slok, and forgive me, I’m going to have to do so again, emphases his:

Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech. Revenue per worker is rising for the Mag 7 but is flat for the S&P 493, see the first chart below. Profit margins are rising for the Mag 7 but are flat for the S&P 493, see the second chart below. And there are still no signs of AI boosting productivity growth, see the third chart below. With no impact on the bottom line, mainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center that weighs on margins.

I’ve included the first two charts below, because they’re important and, well, damning.

In the grand scheme of things, the whole sales pitch for AI is that it’s an enhancer or a job replacer, by which I mean it makes your current resources more efficient and/or productive or allows you to replace said resources, with “resources” meaning cash, people, software, or other things that you use to run your business.

The reason I’m speaking in such Fisher Price-esque terms is that the AI bubble has been inflated by intentionally escaping the terminology that you’d use to measure the health of a business. Four years into the bubble, AI should, at least in theory, be doing something to the world of business — something measurable, especially given that just about everybody is talking about installing it everywhere and using it all the time.

Yet profit margins appear to have gotten worse across the S&P 500 since the beginning of the AI bubble, with ChatGPT’s November 2022 launch appearing to do sweet fuck all for anybody not called Google, Amazon, Meta, Microsoft, or NVIDIA, with Tesla and Apple having very little to do with the AI bubble as we understand it.

AI boosters and malcontents have spent the best part of four years trying to get everybody to talk about any imaginable statistic other than the ones that matter, mostly because they universally look like this:

The counterpoint they’re going to give is that “organizations have yet to fully install AI in their workflows” or some such business, not so much moving the goalposts but constantly changing the rules of the game to the point that it’s unclear what it is we’re playing. It isn’t making companies more money, more profits, or improving them in a manner that can be measured by modern science.

And, per Slok last week, it isn’t even improving the ROIC (return on invested capital) for hyperscalers, and that was before Meta announced its plans to raise nearly $100 billion through ongoing equity sales:

It appears that AI does not appear to be increasing revenue or margin growth across the S&P 500, other than in the magnificent seven, who in return for over a trillion dollars of capital expenditures have seen their return on invested capital drop on a quarterly basis.

Yet every single company building anything AI related will tell you that it’s changing everything and that you have to get on board today, even if the product doesn’t really work the way they say it does, even if there isn’t really tangible evidence that it’s a good investment, and even if it’s clear the companies running the services have deeply questionable economics.

And that’s because this entire industry is sold with a genuine contempt for the end customer or investor.

Including, I should add, the biggest IPO in Silicon Valley history.

This Is The Best Anthropic Will Ever Look, And Its IPO Timing Is Intentional

To quote economist Paul Kedrosky on the Prof G Markets podcast, “...this [S-1] is as good as it looks from the standpoint of the business as currently structured. And now you go through this inflection that makes it much more capex intensive."

I’m going to be a little more brutal, as I believe that Anthropic is intentionally misleading investors at a scale unseen in the history of IPOs. Whatever excitement anyone might have about cashflows or the stretched definition of “profitability” is irrelevant, as Anthropic is, by its own admission and its unbelievable obligations, a completely different company to the one it was in the second quarter of this year.

Anthropic’s S-1 — And Q2 2026 — Tells The Story Of A Very Different Company To The One That Will Go Public, With Over $430 Billion In Non-Cancellable Obligations

So, as you’ve likely read, Anthropic finally dropped its S-1 earlier in the week, a 300+ page megalith of different risk factors and disclosures that also carefully avoided including things that might have been useful to fully analyze it, specifically leaving out anything to do with its third quarter numbers that were disclosed during its investor day.

Sidenote: It seems as though Anthropic’s aligning its financial year with the calendar year. In that case, its third quarter would have ended on September 30.

If we hold Anthropic to the same expectations as publicly-traded companies, there’s nothing inherently dodgy (bear with me) with it failing to disclose its latest figures. The SEC gives public companies 45 days to publish their results after the close of each fiscal quarter.

That said, if we hold Anthropic to the same expectations set by large publicly-traded companies (bear in mind it’s targeting a $1.5 trillion valuation, though investors have reportedly told investors that their target has shifted to potentially as low as $1.4 trillion), it’s a bit lousy. Companies of this size can (and do) publish their audited numbers within a few weeks of the close of their fiscal quarters. SpaceX, for example, published its Q3 results on October 20, with Meta following one day later.

Both of these companies are larger, more diversified, and therefore considerably more complex. And so, it’s hard to ignore or rationalize away this glaring omission.

And despite all the hubbub and booster-cope, the vast majority of the numbers were already known, and many of the new ones make things much, much harder to stomach.

We Already Knew Anthropic’s Q2 Numbers — And The Company This S-1 Describes No Longer Exists

This means that the latest quarter we have — Q2 2026 — is “profitable” (as I discussed back in May) due to the discounts given to it by SpaceX for two out of the three months of the quarter:

Hence Anthropic’s profitable quarter — a $974 million profit, to be specific — which was largely a result of events that will likely never be repeated.

Sidenote: I should also add that you can see this is an anomaly when you use Anthropic’s own “dollar of revenue per compute” number. For Q2 2026, it brought in $2 of revenue per $1 of compute spend, up from $1.39 in Q1 2026. This number dropped to $1.70 in Q3. I think it’s a stupid number as it doesn’t really say very much about the business, but even based on Amodeiconomics, this quarter feels like the exception rather than the rule.

In fact, the literal opposite is going to take place over the next few quarters, as Anthropic’s massive non-cancellable burdens start weighing on its balance sheet regardless of how well the company does.

You see, this was an opportunistically-timed S-1, as the vast majority of Anthropic’s big compute contracts only got started in or around Q2 2026, with $224.5 billion in non-cancellable agreements with Amazon and Google starting in April and May.

  • “...In March 2026, we entered into an agreement with Google, which was subsequently amended between May and August 2026, and pursuant to which we committed to spend at least approximately $114.5 billion between April 2026 and July 2033, regardless of actual usage.”
  • “...In April 2026, we entered into an agreement with Amazon, pursuant to which we committed to spend an aggregate of at least $110.0 billion between May 2026 and April 2036, regardless of actual usage.”

In SpaceX’s case, the compute bill is much, much larger than we thought, going from the $1.25 billion a month that had previously been reported to, as of December 2026, $3.1 billion a month, or around $37.2 billion a year.

  • “Under the SpaceXAI Arrangements, we agreed to spend an aggregate of up to $120.5 billion over terms extending into 2029, consisting of approximately $3.1 billion in the aggregate per month once all capacity has been delivered, which we expect in December 2026, with different fees during capacity ramping periods.”

In Microsoft’s case, Anthropic is due to start paying it as of November 2026.

  • “...in November 2025, we entered into an agreement with Microsoft, which was subsequently amended in February and October 2026, pursuant to which we committed to spend an aggregate of at least $44.9 billion between November 2026 and May 2033, regardless of actual usage.”

That’s around $269.4 billion in non-cancellable compute commitments, the majority of which are yet to be realized on Anthropic’s actual books.

There’s also another curious note:

  • “The Company also entered into certain agreements that are short term in nature with minimum non-cancelable payments under such contracts of approximately $21 billion.”

Who are those with? Who knows! No need to tell us what those are, when they might amortize, the terms of those contracts, or really anything at all. What’s $21 billion between friends?

Anyway, there’s also Broadcom, which builds Google’s TPU chips and has $161.2 billion in non-cancellable leases with Anthropic, with the only out being an outright default. While Anthropic notes that “a portion of” the chips “began to come online in 2026…additional capacity [is] expected to come online starting in 2027.”

Sidenote: You’ll notice I haven’t brought up Anthropic’s obligations with Nscale or Lambda, and that’s because neither of them feel very real to me despite being “worth tens of billions of dollars.” Anthropic signed those deals to help boost the neoclouds’ IPOs, the capacity doesn’t currently exist, and building it will require debt from a market that, if you believe Elon Musk, has stopped lending money.

Anthropic Left The Numbers That Matter Blank, Focusing On A Quarter That Doesn’t Represent The Future Of A Company With Slowing Growth And Skyrocketing Obligations

In other words, Anthropic’s numbers tell the story of a completely different company to the one that will actually go public, and lean heavily on a quarter with discounted compute costs and yet-to-fully-commence agreements that will weigh on the company regardless of its revenue growth.

And because this is a draft and Anthropic knows it doesn’t really have to give this information, the breakdown of its contractual obligations is left…completely blank!

The gaps in this S-1 filing are seemingly custom-built to obfuscate any ability to try and work out anything about its future.

Despite filing more than three hundred pages of information, Anthropic chose to leave out:

  • Its Q3 revenues.
  • The amount of payments due on a yearly basis.
    • This would allow us to model out exactly how much money it needs through 2030.
  • The amount of payments due in the next 12 months — arguably the most important number to disclose.
    • This would allow us to compare its current burn with its future costs.
  • Its cash position as of September 30, 2026 (the end of Q3).
    • This would allow us to see how much money it actually had on hand past June 30 2026, which feels pretty material for an IPO happening before Thanksgiving.
    • I also imagine its cash position changed since then given its increased payments to SpaceX, Google, Amazon and other counterparties.
  • Anything about IPO pricing or the use of proceeds outside of the most general statements.
  • Its run-rate, which it leaves blank on page 194.

I’ll give Anthropic some leniency — this is a draft filing, and thus it’s possible that it adds these numbers before the actual IPO, but nevertheless, this is extremely valuable information given that its revenue growth, per Reuters, slowed to (a still very high) 45% quarter-over-quarter in Q3, growing from $11.5 billion to $16.8 billion. Per TickerTrends, even the bastardized “run rate” metric shows that things have begun to slow down:

The era of token-maxxing — when companies like Meta incentivized their employees to burn as many tokens as possible, only to pull back after costs skyrocketed — ended somewhere in Q2 or Q3 2026, which is why Anthropic is so keen to push this company out the door, ideally before you learn too much about its latest quarter or how much its ongoing expenses might be.

Nevertheless, Anthropic had a profitable quarter, which proves that it has a more efficient business than OpenAI, even if said efficiency came from contractual shenanigans. The fact that it left out Q3 — a month we already know about — suggests that this is no longer the case, especially given that every article I read has it being profitable “on an adjusted basis,” which means removing stock based compensation (which was $1.261 billion in Q2 2026, and had grown by 36.5% quarter-over-quarter).

What’s also interesting — and frustrating! — is that, as of June 30 ,2026, Anthropic had around $112 billion in cash and cash equivalents, giving us little insight into its current financial position or whether any prepayments have had to go out the door. What’s wrong, Anthropic? Afraid you might tell us something about your liquidity?

Nevertheless, the majority of it — $110.4 billion — came from two funding rounds, one of which was larger than reported:

I’ll admit that Anthropic’s cash position surprised me, especially given what appears to be a drastically lower compute spend than I (and others) had expected…which makes the lack of any payment schedule all the more frustrating.

There’re two reasons I can imagine, and both can be true at once!

  1. Anthropic was smart enough to realize that post-IPO fundraising would be difficult, and chose to fill its boots at the height of its hype, with $65 billion or so coming in at the height of its valuation without any of the messiness of a public at-the-market offering.
  2. Anthropic knew that the contracts it was signing — its massive deals with Google, Broadcom and Amazon (both signed in April, before the close of its Series H which included investments from both Amazon and Google), for example — would require massive prepayments starting in the latter half of 2026, and took action to capitalize itself before purse strings tightened.

Either way, the Anthropic described in this S-1 isn’t really the one that’s hitting the market.

In fact, Anthropic warns investors of exactly that, and has an entire risk factor dedicated to it aptly titled (emphasis theirs) We are at an early stage of our revenue growth, we have experienced rapid growth in recent periods, and our historical growth rates are not indicative of future performance or our ability to sustain or forecast future revenue growth.

We do not expect our revenue will continue to grow at comparable rates, and we cannot assure you that it will continue to grow at all. Our recent growth may reflect early-stage adoption dynamics, the nascency of the AI market, and rapid initial customer expansion that may not be sustainable over time, and it may decline significantly and more rapidly than we anticipate, as our revenue base increases, as the market matures, and as a result of the other factors described below. We expect our revenue growth rate to decline over time. In addition, because the AI industry is very nascent, we have struggled to accurately forecast our revenue in the past and may struggle to do so in the future.

It also names a number of factors that could slow growth, including a slowing or shifting demand for models, an ability to secure sufficient compute or to direct it efficiently, failures or performance limitations on models (including unexpected behavior), increasing competition, safety risks, and my personal favourite…

insufficient growth in the number of users and paying customers of our models, platform, and applications or the failure to increase sales of our models, platform, and applications to existing customers

“Customers” could mean many things, given that 48% of Anthropic’s first half 2026 revenues came from selling its models through Amazon and Google.

There’s also this fascinating note included in discussion of run-rates:

Our recent Run-Rate Revenue growth has also been driven in part by rapid initial customer adoption and expansion often characteristic of an early-adoption period and the nascency of the AI market that may not be sustainable, and we expect our Run-Rate Revenue growth rate to decline over time, and it may decline significantly and more rapidly than we anticipate, as our revenue base increases, as the market matures, and as a result of other factors.

In addition, our Run-Rate Revenue has included, and we expect will continue to include, amounts from customers that we subsequently determine are using our models, platform, and applications in violation of our usage policy or commercial terms.

Which leads me to another problem…

Anthropic Has A Customer Concentration Problem, With 5-7% Of 2026 Revenues To Date ($1.65 Billion to $2.31 billion) Coming From Competitors Using Its Inputs To Train Their Models

On page 145, Anthropic reveals that 5% to 7% of its revenues came from what appear to be distillation attacks, meaning other model providers using its models or accounts to train theirs:

In addition, our revenue has included, and we expect will continue to include, amounts from customers that we subsequently determine are using our models, platform, and applications in violation of our usage policy or commercial terms. We believe this dynamic is common in our industry. Because detection, investigation, and enforcement take time, we recognize revenue from such customers when the related services are provided, before restricting or terminating their access. Based on our detection and review process, we estimate that revenue from such customers represented approximately 5% to 7% of our revenue for the nine months ended September 30, 2026.

When we factor in that Anthropic’s revenue to date — including the $16.8 billion reported for Q3 2026 — is around $33.08 billion, that means that as much as $2.31 billion of its revenues (7%) has come from other companies distilling its models. Anthropic expects the percentage of revenue from this part of its “business model” to decline, adding that it will have “an uncertain adverse effect on revenue and revenue growth.”

Its five largest customers also accounted for 25% of its revenues through the end of Q3 2026 — you know, the one it didn’t include! — with Anthropic adding that “many of its top customers are not subject to long-term contracts or have contracts with near-term expiration dates and are able to reduce or in some cases cease spending at any time for any reason.”

While it’s unclear who these large customers are, they undoubtedly include Meta and Microsoft, both of whom are reported to reduce their use of the platform, with Microsoft AI CEO Mustafa Suleyman saying back in June that he wanted to eliminate the spend entirely.

Then there’s the rest of them — and these three bullet points that I’ve seen multiple media outlets attempt to frame as a positive for the company.

Let’s play around with this.

  • So, let’s suppose that $1.19bn of its revenue came from 11,900 users (assuming each paid $100,000 — although the spread was between $0.1 and $1m. I’m going with the lowest possible number here, for the sake of argument).
  • Again, let’s suppose further $1.9bn of its revenue comes from 1,900 customers (assuming, again they’re spending the least amount of money in that range, namely $1m).
  • Finally, let’s imagine that $2.5bn came from 250 customers (assuming, again, they all spent exactly $10m)
  • That gives us $4.59 billion.

These figures are on a TTM (trailing twelve month) basis, meaning the previous twelve months before the end of the reporting period — namely, the end of June. If we do the math, Anthropic had revenues of $19.708bn over the period (with H2 2025 bringing in $3,422bn), meaning that, in our most generous (and therefore guaranteed to be wrong) nearly one-quarter of its revenue from that period came from a relatively small group of whales.

If we make those assumptions less generous, even marginally so, then the revenue concentration becomes a lot more bleak. If the lowest possible estimate is wrong by 50%, then nearly one-third of Anthropic’s revenue comes from that small group of whales. If the lowest-possible amount is half the real number, then, in turn, just under half of Anthropic’s revenues from that period came from the same small group.

Again, the most generous estimate is guaranteed to be a fraction of the real number, not least because two customers alone accounted for 23% of Anthropic’s accounts receivable in H1 2026. The above exercise assumed that each whale uniformly spent the least amount possible in their respective bracket — an unrealistic proposition, but one that illustrated a point.

And then there’s the other problem: a large share of these supposed “diverse” customers are, in fact, unprofitable and unsustainable AI startups.

Both Anthropic and OpenAI Are Dependent On Venture-Backed Startups For 80% Of Their Enterprise Revenues — And Anthropic Used Discounts To Pump Revenues In The Short Term

Anthropic also quietly mentions what I believe is its second-largest — behind its compute agreements — existential risk:

…our customers, particularly early-stage and high-growth companies, may depend on venture capital or other external financing to fund their operations, and may reduce or cease spending with us if such funding is delayed, reduced, or unavailable or if their access to capital becomes more costly.

As I’ve discussed previously, per Ramp, 80% of OpenAI and Anthropic’s enterprise revenues — the vast majority of what they make — come from 1% of their customers, with the vast majority of those being venture-backed startups that as I’ve also discussed allow their customers to burn anywhere from $3 to $10 for every dollar of subscription revenue.

Per my last newsletter:

For example, into the amount of tokens you could burn on the various different AI subscriptions out there, finding that you could burn anywhere from $83 to $118 a month for $20 and from $1,264 to $1,331 a month for $200 on Cognition, dropping to $46 on a $20-a-month plan and $507 for $200-a-month on Cursor when using Anthropic’s models.

This means that a large chunk of both companies’ revenues are dependent on their customers being able to continually raise capital, which is why companies like Harvey have to raise hundreds of millions of dollars every few months to keep up with their costs.

And it’s clear that Anthropic offered temporary discounts to pump its revenues through IPO, only to discontinue them unless the startup committed to spending more on the platform through tactics I’d describe as a little brutal:

Per The Information, on September 2026:

While both Anthropic and archrival OpenAI provide discounts to customers that commit to spending millions of dollars a year on their products, Anthropic has taken the unusual step of ending customers’ discounts once they hit the usage limits in their contracts, according to managers from three software firms that buy AI from both companies. Customers that reach the cap must negotiate a new agreement or face higher prices, these people said.

“The second you hit the cap, you get phone calls and emails from Anthropic sales teams, saying ‘Hey, we noticed you hit your cap—if we address this today with a new agreement, you can avoid overages,’” one of these people said. “Otherwise you’re on your own.”

Somewhere between a mobster and a drug-pusher, Anthropic assumed its customers would simply capitulate, assuming (incorrectly) that OpenAI wouldn’t compete on cost:

Per The Information last week:

Replit, a coding app, in recent months switched the majority of its AI spending to OpenAI from Anthropic after OpenAI offered a discount of more than 30% on its model prices as part of a contract worth more than $100 million annually, according to a person familiar with the situation. The startup had planned to stick with Anthropic, but Anthropic wouldn’t extend a discount it had previously provided to Replit unless the startup committed to a higher spending level, this person said. (Replit has publicly discussed shifting toward OpenAI but hasn’t disclosed the discount it is receiving nor the size of the contract.)

“In recent months,” eh? Replit had mentioned a few weeks ago that it was no longer working with Anthropic, which makes me wonder if the effect of the dropoff will be realized in, say, Q4 2026, you know, the quarter after it goes public.

Anthropic is playing a dangerous game where it either chooses to alienate some of its largest customers or drain them of what remains of their venture capital by demanding they guarantee a minimum spend on tokens.

And I imagine the reason Anthropic is doing so is that it realizes it’s bitten off more than it can chew with its compute commitments.

Anthropic’s Compute Costs Are Now Growing Faster Than Its Revenues

Eager beavers reading stories about Anthropic’s Q3 2026 numbers will note that it boasts about generating “$1.70 in revenue for every dollar spent on computing power,” which works out to approximately $9.88 billion in compute spend for $16.8 billion in revenue.

This is likely one of the main reasons that Anthropic didn’t include its Q3 numbers — because Q3 2026 is when its compute spend grew faster than its revenues on a quarter-over-quarter basis, where revenues grew a (still impressive) 45% (from $11.5bn to $16.8bn), but compute costs grew 76.3% (from $5.5bn to $9.88bn).

It’s also interesting that Anthropic fell back on that “dollar of revenue per compute” figure, especially considering that said number declined from $2 (Q2 2026) to $1.70 quarter-over-quarter. I imagine it assumed nobody would bother to think about it for two minutes.

In any case, while we don’t know much about Anthropic past Q3 2026, we do know that it has hundreds of billions of compute costs due in the next few years, and that they’re going to increase dramatically:

  • If we assume that SpaceX makes good on delivering its compute, that means that Anthropic will be spending $37.2 billion a year just with Elon Musk.
  • Broadcom’s deal is $161.2 billion “excluding interest” for multiple five-year-long leases, though it’s unclear when the capacity will come online. Nevertheless, that’s at least $5 billion next year, if not more like $10 billion, growing to as much as $30 billion a year.
  • Anthropic’s Microsoft deal kicks off in November, requiring it to spend $44.9 billion through July 2033, or around $6.8 billion a year.
  • Anthropic’s $110 billion Amazon deal kicked off in May 2026 and goes through 2036, working out to about $11 billion a year.
  • Google’s $114.5 billion deal, which runs from April 2026 through July 2033, works out to about $15.6 billion a year.

Then there’s this curious note at the bottom of page 170 following its disclosure of its deal with Google to rent TPUs:

In addition, we also committed to procure additional TPU compute from TPU providers, including Google, to be delivered between 2028 and 2031. The payment obligations for such additional compute are determined by the capacity made available, the manner in which it is deployed, the pricing mechanics, and the satisfaction of certain deployment conditions. We estimate the aggregate future payments for such additional compute to be approximately $125.0 billion to $150.0 billion, which are not included in the contractual commitments table above.

So yeah, just another $125 billion or $150 billion in commitments. No big deal! Don’t worry about it.

As far as its non-cancellable commitments go, this all works out to around $75.6 billion in annual compute commitments, with each deal having the crucial phrase “at least.” The fact that Anthropic doesn’t include the exact breakdowns is an insult to basically every investor putting money in this IPO.

Yet if we (sigh) annualize Anthropic’s Q3 2026 compute spend, this means that Anthropic is likely on the hook to nearly double how much it’s spending on chip rentals at precisely the moment it’s slowing down.

Anthropic Is Saying In No Uncertain Terms That The Company In Its S-1 Is Not The One You’re Investing In

Anthropic is telling us in no uncertain terms that the company you see before you is not the one that will actually go public. This is not my personal opinion, but an objective explanation of the S-1.

In its S-1, Anthropic is telling you that “...historical growth rates are not indicative of future performance or our ability to sustain or forecast future revenue growth” (page 16), and specifically that “...results for the six months ended June 30, 2026 are not necessarily indicative of the results that may be expected for the full year ending December 31, 2026 or any other period” (page 22). It reminds us again on page 62 that it does “...not expect [its] revenue will continue to grow at comparable rates,” that it can “not assure you that it will continue to grow at all,” and that "recent growth may reflect early-stage adoption dynamics, the nascency of the AI market, and rapid initial customer expansion that may not be sustainable over time, and may decline significantly.”

On page 64, it tells you that Anthropic “...expects [its] costs will increase over time and [its] losses will continue as we expect to invest significant resources towards growing our business and operating as a public company.”

On page 67, Anthropic explicitly states that its run-rate revenue growth was driven by “expansion often characteristic of early adoption periods” and “may decline more rapidly than it anticipates”:

On page 133, Anthropic says that its margins will get worse as compute comes online:

As significant incremental compute is brought online in future periods, the associated expense will be recognized in advance of the full revenue that the compute will ultimately support, and we expect operating margin and Adjusted Operating Margin may compress in those periods.

…and that’s before factoring in short term compute costs (page 134).

In addition, the majority of our compute is contracted under multi-year commitments that we typically procure 12 to 18 months in advance of availability. When customer demand or research needs exceed this long-term capacity, we procure short-term compute, which typically carries a higher cost per unit of compute. We expect our use of short-term compute to increase in the near term and to in turn compress our operating margin and Adjusted Operating Margin as a result.

On page 161, Anthropic explicitly states that its “increasing efforts to build out our compute and infrastructure require substantial capital expenditures and are changing the cash flow profile of [its] business, and that the underlying economics of its compute payments are set to change, including larger prepayments and “substantial” capex:

Our increasing efforts to build out our compute and infrastructure require substantial capital expenditures and are changing the cash flow profile of our business. Whereas the compute purchased through our CSP arrangements is generally paid as the compute becomes available to us, we expect an increasing portion of our compute and infrastructure investment to take the form of capital expenditures and other commitments, including lease obligations, that require significant upfront payments well in advance of the related compute becoming operational. We expect our capital expenditures to increase significantly as we expand our build-out, and we expect these investments to result in significant net cash used in operating and investing activities for the foreseeable future. Our net cash used in these activities may increase regardless of whether our financial performance improves.

In other words, the Anthropic of Q2 2026 — the so-called “profitable,” compute-light firm that’s got boosters hot under the collar — is a moment in time specifically chosen so that people come away with a vision of a very, very different company to the one they’d be investing in.

Anthropic is guaranteed — in its own words! — to have slower growth, worse margins and higher costs going forward, and by putting out just the Q2 numbers, it’s engaged in a truly offensive bait-and-switch with an investor class buoyed by a media ecosystem incapable of seeing when it’s being duped.

What makes this all the more offensive is that Anthropic shared some of its Q3 numbers with investors only a couple of weeks ago! It clearly has them, and considering its other 2026 numbers are unaudited, I see no excuse to not include at least its cash position and operating expenses outside of “we don’t want investors to compare them to Q2.”

Is there a version of Anthropic that could be truly economically viable? It’s unlikely given that so much of its revenue is dependent on venture capital. With the vast majority of its revenue coming from venture backed startups, it’s reasonable to question whether there’s fundamental demand for AI writ large — and while boosters may respond that “it’s just the early days,” I think that’s fucking laughable when you’ve made nearly half a trillion in commitments and are claiming a total addressable market of $30 trillion.

Anthropic — And The Greater AI Industry — Sees You As Exit Liquidity

You can do whatever mental gymnastics you want — “oh, it could just stop training and be profitable” — but all that matters is what Anthropic is actually doing, which is making $430 billion in non-cancellable commitments and explicitly stating that its economics will get worse.

Anthropic’s largest customers are also explicitly building competitors and/or actively discussing dropping their services. SpaceX (which owns Cursor) has Grok and just took on $40 billion in debt to buy more GPUs to train it (and will potentially kick Anthropic off of its infrastructure to do so), Meta has Muse, and both Meta and Microsoft have explicitly discussed dropping their Anthropic use.

Then there’s the threat from open source LLMs, which appeal naturally to Anthropic’s largest customers. While it might be impractical for an AI startup to spend tens or hundreds of millions training its own models when its users demand access to the latest from Anthropic and OpenAI, a large, established business with any real interest in AI would see far more value in — and have the resources to execute on — training their own off of one of the many open source options, like Meta’s open weight Muse model.

I should also be clear, as I discussed two weeks ago in my premium newsletter, that the only objective of this IPO is to dump Anthropic onto the public markets.

At a $1.4 trillion to $1.75 trillion valuation, Anthropic is long past the point at which there’s really any room for this to grow like, say, investing in Amazon (which went public at $438 million), Microsoft ($777 million or so), Google ($23 billion), or Meta ($104 billion).

Sidenote: Should Anthropic debut at $1.4 trillion, it would no doubt be a massive disappointment for those that invested when the company was targeting a paper valuation of $960 billion.

For some context, Meta’s current market capitalization as of writing this sentence is about $1.6 trillion, and that’s for a company with an effective monopoly on social media. How, exactly, does Anthropic warrant such a high valuation? And if it actually lists — which it sadly might, given how brainless everybody is — how does it retain that valuation?

In any case, all the proof you need that this is about dumping shares comes from Anthropic’s lock-up schedule, which allows non-founder insiders to dump 10% of their shares on the first day of trading, and a total of 45% of their shares the second trading day after Anthropic’s Fiscal Year 2026 earnings results.

Approximately 180 days — or earlier, if it reports its Q1 2027 earnings before then — after it goes public, Anthropic’s non-founder insiders can sell all of their shares, and founders can sell 29% of their shares. On the second trading day after its Q3 2027 earnings (or 365 days after its final IPO prospectus date, whichever happens first), everyone can sell everything, assuming their agreements don’t preclude them from doing so.

Those holders subject to a 180 day lockup period (which does not actually mean they have to wait 180 days) are allowed to sell 6% of their shares 27 days after the prospectus is filed, 6% more after 48 days, and by the second full trading day after its Fiscal Year 2026 earnings, can sell up to 38.5% of them. 69 days after those earnings, that jumps to 86%.

While some of this is fairly standard, the sheer speed at which insiders and shareholders can exit this company is remarkable, purpose-built to allow insiders to use retail investors to financialize their early bets in a company that’s been drained of any opportunity or value.

To quote Peter B. Parker in Spiderman: Into The Spiderverse, don’t watch the mouth, watch the hands.

If CoreWeave believed it would actually grow to meet its $100 billion in revenue backlogs — something that would undoubtedly send its share price to the moon — its three co-founders wouldn’t have sold $3.3 billion in shares since it went public in March 2025. If former Oracle CEO Safra Catz believed that Oracle would actually make anything out of its $300 billion, five-year-long deal with OpenAI, she wouldn’t have sold $1.8 billion in shares in the second quarter of 2025,let alone step down as CEO two weeks after the deal was announced. The same goes for , who sold $1 billion of his shares by October 2025 in a plan put in action in March 2025 — the month that DeepSeek panicked the markets about the threat of open source — and board member Mark Stevens, who sold $946 million in share sales in Q2 2026.

To quote Bloomberg in July 2026, US executives are selling shares at the second-fastest pace in more than 20 years, beaten only by the opulence of 2021. Meanwhile, corporate buying sat at $6.9 billion, a little above the seven-year-low of $6.7 billion, per Bloomberg.

In other words, while everybody in tech and AI is telling you to buy now and get in on the ground floor, their actual actions suggest an unwillingness to stick around and find out what might happen next.

The same goes for the massive, rushed AI debt deals you’re starting to see happen. Broadcom’s Hock Tan reportedly held (per the WSJ) “11th-hour talks with bank executives over the weekend” to finalize their $40 billion contribution to a $63 billion chip deal for Anthropic to lease back TPUs from the company, or put another way, for bankers to buy $63 billion in TPUs from Broadcom.

While Tan had to pay an indeterminately-higher interest rate on the deal, his urgency tells me that he’s well aware that the party is winding down and he needs to get as much money out of the system as possible. The same goes for Musk and his $40 billion chips deal (which is expected to close by year-end, per Bloomberg), with Semafor reporting that some parts of the debt could have as much as an 8.75% interest rate.

That’s an abominable interest rate you take only when you’re convinced that the money is running out.

Per the Washington Post, the AI industry is already admitting it behind closed doors:

How to summarize the sentiment among AI firms right now? “Take it when you can,” Matt Orton, chief market strategist of investment firm Raymond James Investment Management, said about the AI companies’ cash grabs. “Everyone is going to need more.”

Per MarketWatch, RBC’s Head of Fixed Income Andrzej Skiba thinks that “the funding market is about - or close to - shutting [the door on AI investments].”

Yet the worst of all of these strange attempts to absorb the world’s liquidity — other than Anthropic’s IPO, which I believe is an egregious swindle of retail investors — is Meta’s $97.5 billion at-the-market stock dump, where a company with little or no AI strategy dilutes its shareholders and cons retail by claiming it’s funding “futuristic AI” based on the brief yet collapsing growth of its Muse assistant.

That $97.5 billion number rivals the $50 billion to $100 billion Anthropic wants to raise in its IPO, and in both cases investors will be left holding the bag for two companies with little tangible proof that they can live up to their egregious promises.

And in the end, everybody else suffers.

We’re In A Bubble, And The Longer It Goes On, The Worse It Gets

Organizations are questioning the ROI. Apollo’s Chief Economist says there’s no payoff. Data centers are not getting built, and are requiring endless high-interest debt to fund them.

The two biggest companies — OpenAI and Anthropic — have over $1.3 trillion in obligations, many of them non-cancellable, and are looking to take their companies public before most of them kick in, tricking retail investors into believing they’re in a much better place just before the anvil drops on their head.

Anthropic is so confident in its growth trajectory that it left out the majority of its third quarter 2026 numbers from its S-1, reporting a second quarter before over $430 billion in non-cancellable compute commitments begin to kick in and its growth begins to slow.

46.5% of the NASDAQ 100 is wrapped in AI chipmakers like NVIDIA, AMD and Broadcom, hyperscalers Google, Amazon, Meta, and Microsoft, the memory company Micron, and the debt-ridden “neocloud” CoreWeave. The value of these stocks is tied to a very simple idea — that AI will grow in perpetuity, creating trillions of dollars a year in new revenues for both hardware and software companies alike. Per Gartner, data center owners will need to generate $8.5 trillion dollars in new AI revenues by 2030 to justify their planned expenditures, and they’re at least five trillion dollars short.

More than 37% of all US household wealth is tied up in a US stock market pumped full of hot air, and if you try and point this out, you’re often framed as a skeptic, a cynic or somehow ignorant of the bigger picture.

And to make matters worse, pension and insurance funds are increasingly being used to fund the buildout, per Jen Harris writing in the New York Times:

Take annuities, which are often relied on by retirees. Because many Americans rely on such insurance products, their policies are usually guaranteed by the state should an insurer go bankrupt. Right now, private creditors like Apollo are funding the debt boom in part by tapping the money sitting in companies like Athene, the $470 billion insurer Apollo controls. Should the A.I. boom go bad and Athene go under, Apollo knows the state (i.e. taxpayers) will be on the hook for much of what it owes policyholders. (Athene’s opaque disclosures make it hard to know how much of its assets are in data centers.)

Private-capital-backed firms now own nearly 20 percent of the entire U.S. life insurance industry, with assets of nearly $1.5 trillion.

There is something very, very wrong here, both in the events taking place and the coordinated efforts to attack anyone who would suggest otherwise.

At some point the money runs out — the funds behind the venture-backed customers of OpenAI and Anthropic, the debt underlying AI data centers, and the willingness of investors to tolerate endless quarters of eleven-digit capital expenditures — and once it does, everything I’ve been saying will become consensus.

And if we’re all being honest, it kind of already has — just not to the scale that can stop Anthropic using retail investors as exit liquidity.

If you liked this piece, you should subscribe to my premium newsletter. Right now I’m running a week-long sale — 10% off of the $70-a-year subscription for life (click here!) — for new subscribers. It’s a great way to support my work, and you get an absolute ton of value at a lower price than basically every competing newsletter.

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 The Terminal.

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