Latest / In the Loop AI / Anthropic's IPO Is Not What It Looks Like: Inside the S-1 and the $80 Billion "Loss"

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Anthropic's IPO Is Not What It Looks Like: Inside the S-1 and the $80 Billion "Loss" · In the Loop AI

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We're about 19 days out from the biggest IPO in history. Anthropix rumored to
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go public at around $2.2 trillion.
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And today they released their S1, which reveals a lot of important information
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and numbers as to how Anthropix is really doing under the hood.
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Are they able to make enough money? Can they afford the crazy $500 billion worth
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of capex that they've committed to spending over the next couple of years?
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And are we in an AI bubble? And to be honest, the market's been questioning
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it pretty aggressively recently.
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We've seen the largest drawdown eight days in a row
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of semiconductor stocks in the public market, and it's no mystery that the entire
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stock market is heavily reliant on two particular companies,
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Anthropic and OpenAI, and if they're making enough money to prop the entire
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market up in the first place.
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Well, today we finally have the answers, and honestly, guys, I'm a little surprised.
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I came in skeptical because I thought that some of the numbers were going to
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be inflated and that it won't make sense.
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But it turns out not only is it way more optimistic than I thought,
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but they have the numbers to back it up. Now, bear with me, this entire document
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was around 261 pages long, so it took a while to get through,
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but let's get into it on today's episode brought to you by Qualcomm.
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Now, it's only been a few hours since the S1 dropped. And one of the headline
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numbers is obviously the revenue. And there's no better way to say this,
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but they're crushing it. But it's not just the amount of money they're making.
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It's how efficiently they're making it. There's this great line from the semi-analysis
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folk, which goes, this is likely the most efficient scaling of a business in
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the history of capitalism.
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Let me tell you why. Three years ago, Anthropic made $41 million in the entire year.
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The next year, 2024, they made around $386 million.
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Good improvement. Then last year, they made around $4.6 billion.
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This year, we're not even at the end of it, but the first six months,
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they made $16.3 billion.
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This is the fastest growing company we have ever witnessed.
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That's about a 14x year over year growth. But what's more impressive is the
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fact that their largest cost, which is spending billions of dollars on compute,
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which we've spoken about a lot on this show, has finally paid off.
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And it's paid off almost 100% more. If we look at Anthropics revenue generation
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as a percentage against the amount that they spend per unit compute,
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we see that the revenue per $1 of compute
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is about $2.08.
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Now, if you backtrack this six to nine months ago this was very consistently
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under a dollar it was very capex intensive and what that told me at the time
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was that the models as good as they seemed as much as they were impressive to
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me didn't really translate into business value in the real world these numbers
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now tell the opposite story which is.
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It's very valuable for individuals and for companies out there.
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And Anthropic as a result is making a ton of money, over a dollar more than
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the amount that they invest in compute alone.
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And the speed at which they've done this is insane. It was literally Q1 of last
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year where this was completely inverted.
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I think for every dollar of compute that they spent or invested,
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they would make around 25 cents of revenue.
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But what's interesting and maybe slightly concerning is how concentrated the revenue risk is.
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Around 250 customers according to the s1 filing pay anthropic 10 million dollars
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per year so these are large huge hefty
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arguably long-term contracts anthropic typically signs long-term deals with a lot of these higher
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value companies and then around 2 000 customers pay about a million dollars
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per year and around 11 900 customers pay around 100 000 per year
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now if i think back to the conversation that Krishna Rao, the CFO,
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had, I think it was on Patrick Shornish's podcast, a few months back,
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these numbers were halved or even less than that.
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So we're seeing increasing concentration and increased profitability for a set
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number of customers, very high value customers that seem to be doubling,
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tripling, and quadrupling down on Anthropic and their models.
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And the data from OpenRouter, which is basically a public platform that routes
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people's requests across any most popular demanded model platform.
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It shows that Opus 5.5, since it released, Anthropic's token consumption has
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almost 3.5 to 4x, which is very impressive because prior to that,
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the trend showed that OpenAI's models were winning.
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So Anthropic's pulled something really special off with Opus 5.5.
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But it's important to point out that this doesn't necessarily mean that Anthropic
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is profitable. They had a humongous loss on their balance sheet, $80.6 billion.
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That's not actually strictly true, and I'll get into that in a second.
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But the idea is if you remove that and you actually look at the operating losses
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that they have, it's between $7 to $9 billion.
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And again, there's a lot of other hidden expenses. I question Anthropik's revenue
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calculation quite a bit, and we'll get into that in a second.
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But the idea here is they're generating a lot of money. And if you do a fund
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calculation of like dividing their profit or the revenue that they're generating
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across each of their employees, that's roughly around $6.6 million per employee.
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The most highly monetized company in the world. But what's also so interesting
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is how loyal the customers seem to be.
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They reported a net revenue retention, NRR, of 9x, 900%.
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What that basically means is, if you're a company that starts the year,
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January 1st, using Anthropics models, and you're spending a million dollars
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a year, by the end of the year, you're spending $9 million.
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Because you see so much value being reaped from your investment in anthropic models.
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So obviously that customer concentration risk that I mentioned earlier on,
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is actually showing up quite positively for Anthropic.
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Their models are providing these customers with a net difference from the likes
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of OpenAI, SpaceX AI, or Meta's models, or Google Gemini's models themselves.
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So the idea that's being implied here is Anthropic's models offers something
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very net new and useful. And listen, I'll speak from my own experience.
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I have access to all the Frontier models.
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And I would say that a large bulk of my work is still spent on Claude models,
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despite me using codecs from ChatGPT for multiple other things.
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So I can kind of like see the resemblance and pattern that is forming here.
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They have a huge customer loyalty. And what's interesting about this is,
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again, on Christian Rao's conversation three months ago, he said that the net
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RR back then was around 300%.
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And I remember that that blew my mind. I remember speaking about it on an earlier
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episode a few months back and saying how impressive that was.
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And back then it was the fastest growing net rr for any other company and we
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just see that 3x in a matter of months it's unprecedented the demand for these
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models has just skyrocketed.
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But what's also interesting is where Anthropic is making this money.
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You would think that these companies are just signing up to Anthropic.com or
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making the deals directly with the lab, but that is not the case at all.
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In fact, 48% of their customer revenue comes from cloud providers,
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the likes of AWS, Google Cloud Platform, as well as Microsoft Azure.
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So Anthropic is very heavily dependent on these legacy cloud systems where enterprises
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already have their sort of home.
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And I wanted to point this out because there's a lesson here.
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Even if you are a startup founder or just a regular enterprise trying to eat
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into this moat, it helps to be where these enterprise companies,
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these Fortune 500 companies already are because they're comfortable with their setup.
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They have these customer relationships with the likes of Amazon,
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Google, and Microsoft because they have such a sticky moat and relationship
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with their enterprise customers.
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If you're a startup and you're trying to break into replacing an existing product
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that an enterprise already has, and you go directly to the source,
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you're going to have a hard time because those customer relationships that they've
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built up with these cloud providers are already huge.
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Now, that means that Anthropic has a heavy dependency on these companies.
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Which aren't just cloud service providers.
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In some cases, they're also competitors. You kind of see Google,
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they train their own models.
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Gemini, they have their TPUs, which is their own version of their GPU.
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Arguably, they're going to be using their compute to train their models and
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to learn from all these other models that are being inferenced through their
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own cloud platform. Now, what's interesting is Google is kind of playing both sides for a while.
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Amazon is doing the same, but they're largely more of a cloud provider.
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And Microsoft, in my opinion, is largely more of a cloud provider.
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I don't see them as an AI lab. But Google is the distinction here. And they also have a.
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Own around 17 to 21% of Anthropic. They've invested billions of dollars.
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But let's put numbers aside for a second and look at the actual products.
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How's Claude Code doing? And do they have any other diversity across any of
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the other products? Or are they just reliant on Claude Code?
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Well, according to the S1, Claude Cowork, which is basically like the layman's
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version of Claude Code, if you aren't a software engineer,
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and you want to use it for multiple other things, but have that Claude Code-like
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experience without understanding or being technical, you would use Claude Cowork.
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And they launched this, I was about to say last year, but they've launched this
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literally earlier this year.
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And I remember it being launched. And listen, I was impressed by it,
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but I wasn't that impressed by it.
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I think some of the more personal agents that we're seeing today from the likes
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of Metamuse, GrokBot, ChatGPTDots, and now Anthropic's own Claude Duet,
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which we did an episode on, you should definitely go check that out yesterday,
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are much better instantiations or versions of this.
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Well, apparently I'm wrong. Claude Cowork is currently growing a lot faster
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than Claude Code itself.
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And that's a very distinctive sentence for me to say because Claude Code...
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Is by all means the bread and butter of Anthropic. That's how they make the
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majority of their money, token consumption through Cloud Code.
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So the fact that we're starting to see Cloud Cowork increase,
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it hasn't beaten the number of users that Cloud Code has, but is increasing
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at a quicker rate of adoption than Cloud Code right now,
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suggests that Anthropic might have finally hit the actual goldmine of products.
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Because remember, Cloud Code is very specific. It applies to software engineers
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and the technical know-how, there's a very limited population of the world that
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that applies to. But 99.9% of the rest of the world doesn't know how to code,
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but would like to have a similar magical experience to Claude Code.
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And Claude Cowork is that instantiation. So if you can imagine,
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we have the same sort of effect that Claude Code had,
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but on the rest of the world, on knowledge work, on any other profession that
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includes administrative roles, customer support, or whatever that might be,
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people will end up being not only a lot more productive, but Anthropik is going
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to end up making a hell of a lot more money.
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And this is just me extrapolating. I have no idea if that's actually going to
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happen, but it's a useful stat to see.
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Now, if I were to highlight a red flag about this is typically if you wanted
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to access Cloud Cowork, you would need to select a different tab,
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I believe, in the desktop.
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Now what they've done is they've sort of combined it with the homepage.
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So whenever you're using regular Claude on the LLM chatbot interface,
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it directs your prompt to Claude Cowork if it thinks that it's a work-related task.
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So it's a bit of UX and financial engineering, but it's not just Anthropic specifically.
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OpenAO is doing the same thing with ChatGPT work.
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I don't know how I feel about this. I actually think I'm fine by it.
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Let's see the numbers after they've actually gone public and they've done their
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first quarterly earnings. And of course, it wouldn't be Anthropic if they didn't
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have some very high-level, long-standing thesis predictions.
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Two of my favorite were expert-level autonomous systems within a few years.
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So Anthropic basically expects AI to match or exceed leading human experts across
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most professional and scientific disciplines.
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This isn't a surprise to me at all because over the recent few
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weeks and months, we've seen the likes of maths chemistry and physics make very
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meaningful progress due to these llms if i had to guess what anthropics models
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are going to solve first it's going to be in the medical and biological
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related field that's where anthropic has kind of designed and focused their moat on when it comes to.
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Real world application and to be honest i'm all for it as a former biologist
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and scientist i would love to see some of the biggest diseases get cured soon
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It's not going to be as easy as I'm saying it, but it's nice to see the focus on that.
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The other high level takeaway I liked was AI is already accelerating the development
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of its successes. Clawed helps run experiments, generate and process training
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data, automate evaluations and safety audits.
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Now, of course, with this, we're talking about RSI, recursive self-improvement.
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The idea of an AI model being so smart that it can build the next version of itself.
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Which seems very meta, but the reason behind this is you'll end up having AI
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that is self-improving.
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And so you will not need as many humans to try and figure out the complex research
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problems or tasks or way to improve itself.
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You can just kind of get the AI to do that, automate itself,
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and then you could focus your time on other things.
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And the idea here is if you have an AI model that can recursively self-improve,
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you can then chuck it at pretty much any problem that exists,
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whether it's physical or digital, and have a bunch of robots or your own digital
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brain figure it out for you.
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Now, that's, I think, a long way away. But if Jack Clark, Anthropics co-founder,
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is anyone to go by, he says that we're already experiencing the takeoff of that.
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And we're probably going to see something along the lines of RSI in the next six to nine months.
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And Demis Civis from Google has also confirmed this. So it's this weird thing
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where I'm sitting here and I'm trying to envision what a world like that looks like.
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I can't actually envision it. But if it does actually occur,
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if Anthropic is right, and they're not just doing this to, you know,
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raise a very hefty valuation for their IPO, then they'll end up making plausibly
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a heck ton more money than they're doing today.
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And we're already looking at the steepest curve of any capital company ever.
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So if they end up pulling it off, they can justify the crazy capex spending that they're seeing.
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But on that note, Let's get into some of the bear cases because there's a lot
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of money that is being committed to this and I don't quite know if Anthropic
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is going to be able to pull it off.
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Let's see. On today's episode brought to you by Qualcomm.
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Now, if you remember a few weeks ago, the headline number that Anthropic was
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rumored to spend over the next couple of years is $500 billion.
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Half a trillion dollars from a single company alone to acquire compute to train
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and inference their models.
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Now, that told me one thing off the top of my head. That's an insane amount
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of money and I have no justification whatsoever to see whether you can afford that. Number two,
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the compute scaling laws still exist. And that means that the most compute that
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you have, whichever company has the most compute, will own the best models.
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But the question is, can Anthropic afford it?
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Now, if you look at the breakdown of who they're spending this money on,
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it's quite interesting.
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$120.5 billion of that $500 billion is going to Elon Musk, SpaceX,
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who have recently pivoted in the most successful way to become one of the leading
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or number one neoclouds in the world. That is a company that would provide compute to others.
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And Elon has been able to pull this off because he's been a master scaler of
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GPUs. He built the best relationship with Jensen Huang, and he committed the
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longest and most expensive premiums to acquire Jensen's GPUs.
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And now he's sitting on the largest arsenal of GPUs ever. He's bringing on around
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200,000 to 300,000 GPUs online every month. That's around $13.1 billion worth of compute.
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And no other company has been able to achieve this feat. He is the master scaler.
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We made an episode on this last week.
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Elon Musk and SpaceX has sort of become a toll booth to some of the biggest,
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most important AI labs of which valuation relies on getting access to these
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GPUs. So they can't go directly to Jensen Huang or NVIDIA because he'll just tell you he's sold out.
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So they need to go through this third party or this intermediary who has gathered this arsenal.
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And Elon Musk is sitting there and thinking, cool, I'll charge you a hefty premium
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on that to the tune of around $3.1 billion per month.
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That's what Anthropic is going to be paying Elon Musk. So he mentioned several
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times that this is a temporary measure whilst we figure out the training of Grok.
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And remember, these contracts are non-cancelable. So Elon Musk at any time can
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just shut Anthropic off from this and be like, well, I don't care anymore.
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Now, another $115 billion Anthropic is spending on Google to acquire their TPUs,
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to diversify their GPU stack from NVIDIA's GPUs. And this is a smart move,
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in my opinion, because too much reliance on a singular.
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Type of GPU or metal block means that you are just heavily reliant on that company, NVIDIA.
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Diversifying to DPUs, to ASICs, which is what Anthropic and OpenAI,
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fair enough, is also doing is a smart move.
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What's also cool here is I guess Google's investing stake in Anthropic,
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which roughly sits around 17 to 20% of Anthropic.
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So it's this weird thing where Google should probably be using these TPUs to
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build a better Gemini model, but instead they're selling it to their biggest
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competitor, which eventually over time, if Anthropic actually does achieve RSI, then
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they will end up running away with it and making all the money because they have the best models.
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And Google will spend the rest of their time playing catch up.
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And this is not a bearish take on Google. It's just more of a strategic critique
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where I'm like, just use that compute to build a better model,
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Google. Invest now heavily, take the loss on your balance sheet,
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build a better model that will end up competing with the likes of Anthropic.
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Don't just give the game away.
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Now, what's interesting about the heavy capex commitment that Anthropic is committed
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to is around the amount of money they had.
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Now, if rumors were anything to go by over the last couple of months,
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Anthropic was said to have almost zero cash balance on the bank sheet because
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they've been burning so much money on compute, billions and billions of dollars.
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But when you look at this S-1 filing, it's quite the opposite.
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They have around $132 billion sitting in the bank account And maybe $19 billion
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of that is in investment-grade contracts.
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But the idea is they have a bulk of money dry powder sitting around to spend
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on some of these heavy capex commitments. So it's not just reliant on how much
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money that they make a month or a quarter or whatever that might be.
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They also have the cash to back it up.
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One thing that popped into my mind immediately when I heard this number was,
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$132 billion is roughly around the amount of money that Apple has and roughly
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around the same amount of money that Google and Meta had before they started
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spending so aggressively to acquire GPUs.
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Anthropic, although they're a startup that is incredibly young,
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is now playing on the same big boy play field as these other companies.
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Now, granted, Anthropic does not have the revenue diversification.
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It is way more precarious of a bet when it comes to considering Anthropic stock
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as an IPO level, because they don't have any other ways to make money.
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They are AI focused. If you look at Google, if you look at Meta,
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they have many other ways to make money.
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Anthropic doesn't have that safeguards. But it's just interesting to see that
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in order to compete with the big boys, you need to have enough money to do so.
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And Anthropic's balance sheet proves it. And Anthropic's compute commitments
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show it running on the S1 till 2045. The other companies These are included
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are Broadcom, which they're building custom ASICs with, which is like a separate thing.
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Google, SpaceX Air, which we mentioned, Amazon, $110 billion going to them.
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Amazon also a very heavy stakeholder in Anthropoc. I think that's around 12 to 14%. Crazy.
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Microsoft, NScale, Lambda and AMD. So the idea here is that Anthropoc is building
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out a very diversified portfolio of risk when it comes to acquiring their compute
19:29
because that's their bread and butter that is needed for them to stay ahead of the game.
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Now, the other thing I want to address is the big headline of loss,
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which is $80.5 or $80.2 billion.
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That's just a paper loss, it turns out. This was, as we guessed it on this show
19:44
a few weeks ago, just the paper loss recorded for equity stakeholders that need
19:49
to be paid out for their early investments.
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So if you're an early investor and you invested in Anthropic five rounds ago,
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your stake is now worth a lot more money because Anthropic's valuation has increased.
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So Anthropic legally needs to record that as a loss on their balance sheet.
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I do not know why that's what the law mandates, but that's what that paper loss is.
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$72 billion to be specific. So the real loss is actually around $8 billion.
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$72 billion paper loss will not exist in the next quarterly earnings or public
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report that they eventually end up releasing.
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So again, a bit more fear mongering and a bit more of a nothing bug.
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I just wanted to, you know, debunk that myth. And so to round this up,
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I feel a lot more optimistic about the IPO.
20:33
That's not to say I'm concerned and I justify the valuation or the price that it's going to be.
20:38
I still think it's going to be quite overvalued. I still think there are an
20:42
immeasurable number of factors that could influence the way this market swings.
20:46
When it comes down to CapEx, bringing all those GPUs online,
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the $500 billion that they're spending, that's all well and good.
20:52
But if you can't bring those GPUs online because you're constrained by power
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or the electrical grid or whatever that might be, war, political conflicts,
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anything that are outside of the purview of just AI.
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Anthropic is going to end up being in hot water. But from the numbers that I'm
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seeing where I thought they maybe weren't making as much money or revenue,
21:10
maybe the revenue was slowing down.
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And actually, it is. Anthropic mentioned in the S1 that you can't expect demand
21:16
to be sky high all the time. Things are going to slow down eventually and plateau.
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That's how these things work.
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But eventually, the idea is it becomes more consistent. Chamath,
21:25
Apollo, and a number of other people for over the last
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couple of days have actually pointed out very fairly that a lot of the money,
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ARR, revenue that these companies are making are actually coming from VC-subsidized startups.
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So basically coming from VC money itself.
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What that looks like when it's not VC-backed, when it's actually coming from
21:45
companies that are generating their own revenue for themselves because these
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AR models are so useful to them, is something to be seen.
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The other thing I'll say is that, well, I guess Anthropic actually said it.
21:56
They said that the gap between what Claude can do and how widely it's used is
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one of the biggest growth opportunities. And I truly believe in that.
22:03
When I speak to my friends and family who aren't involved in AI,
22:07
their basic takeaway is, okay, why the hell do I care about Opus 5.5?
22:11
Why do I care about any of these new models?
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I just use it for myself and it's not really useful.
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You know, I gave a story or anecdote.
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The other week where someone overheard grandmas playing around with Claude and
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saying, it can't even generate me a simple crossword, which you would think
22:26
that it would be able to do.
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So there's this jagged frontier where the AI models are really good at very
22:31
specific things, or they're really good at many things, but it's hard to try
22:35
and figure out what it's good at.
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And if you think about 99% of the world, they want convenience, they want ease of use.
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And I think this will increase over time with the likes of things like personal
22:44
AI agents and agents being more proactive and understanding and predicting what
22:48
you might want to use, but that's going to take time.
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But that's what Anthropic is saying is the largest gap. They're saying with
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the existing models that they have, not even with the secretive Fable 5.5 models
22:57
that they haven't yet released or announced, these models as they exist today
23:01
can end up unlocking so many more billions of dollars worth of value.
23:04
And that is an optimistic take. And it's honestly one that I believe not just
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for Anthropic, but a lot of the other AI companies that are out there that are
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building these very important models.
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I'm bullish on the entire sector in general. That is my take.
23:15
I'm going to leave you guys actually with this hilarious meme so nick carter
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he honestly got me when i read this
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he goes i knew anthropic s1 would have some goofy risk factors but this has
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to take the cake and he goes on to include an image of what is supposedly meant
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to be in anthropics s1 filing which is a clause around roco's basilisk for those
23:32
of you who don't know roco's basilisk
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is this theory that.
23:36
What was a theory or something that's presumed to become true eventually, where,
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the future AI superintelligence, that is the all-seeing, all-knowing,
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will look back on the history of content and the internet, listening to the
23:49
words that I'm speaking to you right now, and judge each individual to see if they were,
23:55
helpful in building AI in general.
23:58
And if they were not, they'd be subject to some form of penalty,
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penalization, or being put in perjury, or some kind of mental prison.
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It's like a whole fantasy thing that's existed for a while, but something that
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Anthropik and the likes of OpenAI have referenced or people that have worked
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there have referenced many times.
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So the idea is there's this like all seeing AI that is listening to us as we say right now.
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And this meme basically includes it as a clause of contract in the framing of
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the S1 and IPO, where it says if you don't invest in this company,
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it could be seen as a negative thing because Basilisk will come to get you.
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But anyway, just wanted to leave you on a slightly uncomfortable but hilarious
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note there's a lot of new subscribers over the weekend we had one of our record
24:39
weeks one of our videos got around 200 000 views
24:42
loads of you subscribe turns on notifications if you aren't any of those people
24:45
please do so it helps us out massively so let me know your thoughts and thank
24:49
you so much for listening i'll see you on the next episode of in the loop brought to you by Qualcomm.