Limitless: An AI Podcast - Anthropic's IPO Is Not What It Looks Like: Inside the S-1 and the $80 Billion "Loss"

Episode Date: October 27, 2026

Anthropic just filed its S-1 ahead of what could be the biggest IPO in history, and the whole market has been waiting on it. Chip stocks fell eight sessions in a row, the headline number is an $80.7 billion loss, and everyone wants to know: is Anthropic actually making money, and are we in an AI bubble? Ejaaz came in skeptical and went through the filing. It's not what it looks like.We break down revenue that went from $41 million in 2023 to $16.3 billion in the first half of 2026, why Anthropic now makes about $2 for every $1 it spends on compute, 900% net revenue retention, Claude Cowork outpacing Claude Code, the $120.5 billion going to SpaceX for GPUs, $132 billion in cash and short-term investments, and why $72.4 billion of that loss is an accounting charge, not cash out the door.==Timestamps00:00 The IPO Everything Hangs On01:14 They're Crushing It02:12 Revenue Finally Beats Compute03:11 Who Pays Anthropic05:11 900% Net Revenue Retention06:53 Where the Money Comes From08:45 Claude Cowork's Surprise11:24 Anthropic's Big Predictions13:56 The Bear Case14:10 Half a Trillion in Compute15:35 Elon's GPU Toll Booth17:26 $132 Billion in the Bank19:32 The $80 Billion Paper Loss20:25 Final Thoughts23:15 The Roko's Basilisk Meme#anthropic #ipo #claude #ai #aibubble==AlphaSpace by Yahoo Finance: A Professional-Grade Investment Platform Built for Everyday Investors.👉 https://finance.yahoo.com/about/promos/gold/alphaspace/?ncid=100003571

We're about 19 days out from the biggest IPO in history. Anthropics rumored to go public at around $2.2 trillion. And today, they released their S-1, which reveals a lot of important information and numbers as to how Anthropic is really doing under the hood. Are they able to make enough money? Can they afford the crazy $500 billion worth of CAPEX that they've committed to spending over the next couple of years? And are we in an AI bubble? And to be honest, the market's been questioning it pretty aggressively recently. We've seen the largest drawdown eight days in a row of semiconductor stocks in the public market, and it's no mystery that the entire stock market is heavily reliant on two particular companies. Anthropic and open AI, and if they're making

enough money to prop the entire market up in the first place. Well, today, we finally have the answers. And honestly, guys, I'm a little surprised. I came in skeptical because I thought that some of the numbers were going to be inflated and that it won't make sense, but it turns out not only is it way more optimistic than I thought, but they have the numbers to back it up. Now, bear with me, this entire document was around 261 pages long, so it took a while to get through, but let's get into it on today's episode, brought to you by Qualcomm. Now, it's only been a few hours since the S1 dropped, and one of the headline numbers is obviously the revenue, and there's no better way to say this, but they're crushing it. But it's not

just the amount of money they're making, it's how efficiently they're making it. There's this great line from the semi-analysis folk, which goes, this is likely the most efficient scaling of a business in the history of capitalism. Let me tell you why. Three years ago, Anthropic made $41 million in the entire year. The next year, 2024, they made around $386 million. Good improvement. Then last year, they made around $4.6 billion. This year, we're not even at the end of it, but the first six months, they made $16.3 billion. This is the fastest growing company we have ever witnessed. That's about a 14x year-over-year growth.

But what's more impressive is the fact that their largest cost, which is spending billions of dollars on compute, which we've spoken about a lot on this show, has finally paid off, and it's paid off almost 100% more. If we look at Anthropics revenue generation as a percentage against the amount that they spend per unit compute, we see that the revenue per $1 of compute is about $2.8.

Now, if you backtrack this six to nine months ago, this was very consistently under a dollar. It was very capex intensive. And what that told me at the time was that the models, as good as they seemed, as much as they were impressive to me, didn't really translate into business value in the real world. These numbers now tell the opposite story,

which is it's very valuable for individuals and for companies out there, and Anthropic as a result is making a ton of money, over a dollar more than the amount of the investing compute alone. And the speed at which should have done this is insane. It was literally Q1 of last year, where this was completely inverted. I think for every dollar of compute that they spent or invested, they would make around 25 cents of revenue.

But what's interesting and maybe slightly concerning is how concentrated the revenue risk is. Around 250 customers, according to the S-1 filing, pay Anthropic $10 million per year. So these are large, huge, hefty, arguably long-term contracts. Anthropic typically signs long-term deals with a lot of these higher value companies. And then about 2,000 customers pay about $1 million per year, and around $11,900 customers pay around $100,000 per year. Now, if I think back to the conversation that Krishna Rao, the CFO had, I think it was on Patrick Shaughanerce's podcast, a few months back, these numbers were halved or even less than that.

So we're seeing increasing concentration and increased profitability for a set number of customers, very high-value customers that seem to be doubling, tripling, and quadrupling down on Anthropic and their models. And the data from OpenRouter, which is basically a public platform that routes people's requests across any most popular demanded model, it shows that Opus 5.5, since it released, Anthropics' token consumption has almost 3.5 to 4.4. X'd, which is very impressive because prior to that, the trend showed that Open A's models were winning.

So Anthropics pulled something really special off with Opus 5.5. But it's important to point out that this doesn't necessarily mean that Anthropic is profitable. They had a humongous loss on their balance sheet, $80.6 billion. That's not actually strictly true, and I'll get into that in a second. But the idea is, if you remove that and you actually look at the operating losses that they have, it's between seven to nine billion dollars. And again, there's a lot of other hidden expenses. I question Anthropics revenue calculation quite a bit, and we'll get into that in a second. But the idea here is they're generating a lot of money. And if you do a fun calculation of like dividing their profit or the revenue that they're generating across each of their employees, that's roughly around $6.6 million per employee,

the most highly monetized company in the world. But what's also so interesting is how loyal the customers seem to be. They reported a net revenue retention, NRR, of 9x, 900%. What that basically means is if you're a company that starts the year, January 1st, using Anthropics models, and you're spending a million dollars a year, by the end of the year, you're spending $9 million, because you see so much value being reaped from your investment in Anthropic models. So obviously, that customer concentration risk that I mentioned earlier on is actually showing up quite positively for Anthropic. Their models are providing these customers with a net difference

from the likes of OpenAI, SpaceX AI, or Meta's models, or Google Gemini's models themselves. So the idea that's being implied here is Anthropics models offers something very net new and useful. And listen, I'll speak from my own experience. I have access to all the frontier models. and I would say that a large bulk of my work is still spent on cloud models, despite me using codex from chat GPT for multiple other things.

So I can kind of like see the resemblance and pattern that is forming here. They have a huge customer loyalty. And what's interesting about this is, again, on Christian Rouse conversation, three months ago, he said that the net RRR back then was around 300%. And I remember that that blew my mind. I remember speaking about it on an earlier episode a few months back and saying how impressive that was. And back then, it was the fastest growing net RR for any other company.

And we just see that 3X in the matter of months. It's unprecedented. The demand for these models has just skyrocketed. But what's also interesting is where Anthropic is making this money. You would think that these companies are just signing up to Anthropic.com or making the deals directly with the lab. But that is not the case at all. In fact, 48% of their customer revenue comes from cloud providers, the likes of AW& US, Google cloud platform, as well as Microsoft Azure.

So Anthropic is very heavily dependent on these legacy cloud systems where enterprises already have their sort of home. And I wanted to point this out because there's a lesson here. Even if you are a startup founder or just a regular enterprise trying to eat into this mode, it helps to be where these enterprise companies, these Fortune 500 companies already are because they're comfortable with their setup. They have these customer relationships with the likes of Amazon, Google, Microsoft because they have such a sticky moat and relationship with their enterprise customers.

If you're a startup and you're trying to break into replacing an existing product that an enterprise already has and you go directly to the source, you're going to have a hard time because those customer relationships that they've built up with these cloud providers are already huge. Now, that means that Anthropic has a heavy dependency on these companies, which aren't just cloud service providers. In some cases, they're also competitors. You kind of see Google, they train their own models, Gemini, they have their TPUs, which is their own version of their GPU. Arguably, they're going to be using their compute to train their models and to learn from all these other models that are being inference through their own cloud platform. Now, what's interesting

is Google is kind of playing both sides for a while. Amazon is doing the same, but they're largely more of a cloud provider. And Microsoft, in my opinion, is largely more of a cloud provider. I don't see them as an AI lab. But Google is the distinction here. And they also have a large controlling stake in Anthropic. I think they own around 17 to 21% of Anthropic. They've invested billions of dollars. But let's put numbers aside for a second and look at the actual products. How's Claude Code doing and do they have any other diversity across any of the other products or are they just reliant on Claude Code? Well, according to the S-1, Claude Co-work, which is basically like the layman's version of Claude Code, if you aren't a software engineer and you want to use it for

multiple other things, but have that Claude code-like experience without understanding or being technical, you would use Claude Co-work. And they launched this, I was about to say last year, but they've launched this literally earlier this year. And I remember it being launched. And listen, I was impressed by it, but I wasn't that impressed by it. I think some of the more personal agents that we're seeing today from the likes of MetaMuse, Grockbar, chat, GBT, dots, and now Anthropics own Claude duet, which we did an episode on. You should definitely go check that out yesterday are much better instantiations or versions of this.

Well, apparently, I'm wrong. Claude Co-Work is currently growing a lot faster than Claude itself. And that's a very distinctive sentence for me to say, because Claude Code is by all means the bread and butter of Anthropic. That's how they make the majority of their money,

token consumption through Claude Code. So the fact that we're starting to see Claude Co-work increase, it hasn't beaten the number of uses that Claude has, but is increasing at a quicker rate of adoption, then Claude Code right now, suggests that Anthropic might have finally hit the actual gold mine of products. Because remember, Claude Code is very specific. It applies to software engineers and the technical know-how. There's a very limited population of the world that

that applies to. But 99.9% of the rest of the world doesn't know how to code, but would like to have a similar magical experience to Claude Code. And Claude Co-work is that instantiation. So if you you can imagine we have the same sort of effect that Claude Code had, but on the rest of the world, on knowledge work, on any other profession that includes administrative roles, customer support, or whatever that might be, people will end up being not only a lot more productive, but Anthropics are going to end up making a hell of a lot more money. And this is just me extrapolating. I have no idea if that's actually going to happen, but it's a useful stat to see. Now, if I were to highlight a red flag about this is typically, if you wanted to access Claude Co-work, you would

need to select a different tab, I believe, in the desktop. Now what they've done is they're sort of combined it with the homepage. So whenever you're using regular Claude on the LLM chatbot interface, it directs your prompt to Claude Co-work if it thinks that it's a work-related task. So it's a bit of U.X and financial engineering, but it's not just Anthropics specifically. OpenAA is doing the same thing with chat GPT work. I don't know how I feel about this. I actually think I'm fine by it. Let's see the numbers after they've actually gone public and they've done their first quarterly earnings. And of course, it wouldn't be Anthropic if they didn't have some very high-level, long-standing thesis predictions. Two of my favorite were expert-level autonomous systems within a few

years. So Anthropic basically expects AI to match or exceed leading human experts across most professional and scientific disciplines. This isn't a surprise to me at all, because over the recent few weeks and months, we've seen the likes of maths, chemistry, and physics make very meaningful progress due to these LLMs. If I had to guess what Anthropics models are going to solve first, it's going to be in the medical and biological related field. That's where Anthropic has kind of designed and focused their moat on when it comes to real-world application. And to be honest, I'm all for it. As a former biologists and scientists, I would love to see some of the biggest diseases get cured soon. It's not going to be as easy as I'm saying it, but it's nice to see

the focus on that. The other high-level takeaway I liked was AI is already accelerating the development of its successes. Claude helps run experiments, generate and process training data, automate evaluations, and safety audits. Now, of course, with this, we're talking about RSI, recursive self-improvement, the idea of an AI model being so smart that it can build the next version of itself, which seems very meta, but the reason behind this is you'll end up having AI that is self-improving, and so you will not need as many humans to try and figure out the complex research problems or tasks or way to improve itself. You can just kind of get the do that, automate itself, and then you could focus your time on other things. And the idea here is,

if you have an AI model that can recursively self-improve, you can then chuck it at pretty much any problem that exists, whether it's physical or digital, and have a bunch of robots or your own digital brain, figure it out for you. Now, that's, I think, a long way away, but if Jack Clark Anthropics co-founder is anyone to go by, he says that we're already experiencing the takeoff of that. And we're probably going to see something along the lines of RSI. in the next six to nine months. And Demisor's service from Google has also confirmed this. So it's this weird thing where I'm sitting here and I'm trying to envision what a world like that looks like. I can't actually envision it. But if it does actually occur, if Anthropic is right, and they're not just doing this to

raise a very hefty valuation for their IPO, then they'll end up making, plausibly, a heck ton more money than they're doing today. And we're already looking at the steepest curve of any capital company ever. So if they end up pulling it off, they can justify the crazy cap expending that they're seeing. But on that note, let's get into some of the bear cases because there's a lot of money that is being committed to this, and I don't quite know if Anthropics is going to be able to pull it off. Let's see. On today's episode brought to you by Qualcomm. Now, if you remember a few weeks ago, the headline number that Anthropic was rumored to spend over the next couple of years is $500 billion, half a trillion dollars from a single company alone

to acquire compute to train and inference their models. Now that told me one thing off the top of my head. That's an insane amount of money, and I have no justification whatsoever to see whether you can afford that. Number two, the compute scaling laws still exist, and that means that the most compute that you have, whichever company has the most compute, will own the best models.

But the question is, can Anthropic afford it? Now, if you look at the breakdown of who they're spending this money on, it's quite interesting. $120.5 billion of that $500 billion is going to Elon Musk, SpaceX, who have recently pivoted in the most successful way to become one of the leading or number one neoclouds in the world, that is a company that would provide compute to others. And Elon has been able to pull this off because he's been a master scaler of GPUs. He built the best relationship with Jensen Huang, and he committed the longest and most expensive premiums to acquire Jensen's GPUs.

and now he's sitting on the largest arsenal of GPUs ever. He's bringing on around 200 to 300,000 GPUs online every month. That's around $13.1 billion worth of compute. And no other company has been able to achieve this feat. He is the Master Scenario. We made an episode on this last week. Elon Musk and SpaceX has sort of become a tall booth to some of the biggest, most important AI labs

of which evaluation relies on getting access to these GPU. So they can't go directly to Jensen Huang or Nvidia, because he'll just tell you he's sold out. So they need to go through this third party or this intermediary who has gathered this arsenal. And Elon Musk is sitting there and thinking, cool, I'll charge you a hefty premium on that to the tune of around $3.1 billion per month.

That's what Anthropic is going to be paying Elon Musk. So he mentioned several times that this is a temporary measure whilst we figure out the training of GROC. And remember, these contracts are non-cancelable. So Elon Musk at any time can just shut Anthropic off from this and be like, well, I don't care anymore. Now, another $150 billion, Anthropic is spending on Google to acquire their TPUs to diversify their GPUs from Nvidia's GPUs. And this is a smart move, in my opinion, because too much reliance on a singular

type of GPU or metal block means that you are just heavily reliant on that company, Nvidia. Diversifying to DPUs to A6, which is what Anthropic and opening. Fair enough, is also doing, is a smart move. What's also cool here is, I guess, Google's, investing stake in Anthropic, which roughly sits around 17 to 20% of Anthropic. So it's this weird thing where Google should probably be using these TPUs to build a better Gemini model, but instead they're selling it to their biggest competitor, which eventually over time, if Anthropic actually does achieve RSI, then they will end up running away with it and making all the money because they have the best models, and Google will spend the rest of their time playing catch-up. And this is

not a bearish take on Google. It's just more of a strategic critique where I'm like, Just use that compute to build a better model, Google. Invest now heavily. Take the loss on your balance sheet. Build a better model that will end up competing with the likes of Anthropic. Don't just give the game away. Now, what's interesting about the heavy CAPEX commitment that Anthropic is committed to is around the amount of money they had.

Now, if rumors were anything to go by over the last couple of months, Anthropic was said to have almost zero cash balance on the bank sheet because they've been burning so much money on compute, billions and billions of dollars. But when you look at this S-1 filing, it's quite the opposite. They have around $132 billion sitting in the bank account. And maybe $19 billion of that is in investment-grade contracts. But the idea is they have a bulk of money, dry pad is sitting around to spend on some of these heavy Kappex commitment.

So it's not just reliant on how much money that they make a month or a quarter or whatever that might be. They also have the cash to back it up. One thing that popped to my mind immediately when I heard this number was 132, billion dollars is roughly around the amount of money that Apple has and roughly around the same amount of money that Google and Meta had before they start spending so aggressively to acquire GPUs. Anthropic, although they're a startup that is incredibly young, is now playing on the same big boy playfield as these other companies. Now granted, Anthropic does not have the revenue diversification.

It is way more precarious of a bet when it comes to considering Anthropic stock as an IPO level, because they don't have any other ways to make money. They are AI-focused. If you look at Google, if you look at meta, they have many other ways to make money. Anthropic doesn't have that safeguards. But it's just interesting to see that in order to compete with the big boys, you need to have enough money to do so. And Anthropics balance sheet proves it. And Anthropics compute commitments show it running on the S-1 till 2045. The other companies that are included are Broadcom, which they're building custom A6 with, which is like a separate thing. Google, SpaceX, which we mentioned. Amazon, $110 billion going to them. Amazon also, a very important,

very heavy stakeholder in Anthropics, I think that's around 12 to 14 percent crazy. Microsoft, N-scale, Lambda, and AMD. So the idea here is that Anthropics building out a very diversified portfolio of risk when it comes to acquiring their compute because that's their bread and butter that is needed for them to stay ahead of the game. Now, the other thing I want to address is the big headline of loss, which is $80.5 or $80.2 billion. That's just a paper loss, it turns out. This was, as we guessed it on this show a few weeks ago, just the paper loss recorded for equity stakeholders that need to be paid out for their early investments. So if you're an early investor and you invested in Anthropic five rounds ago, your stake is now worth a lot more money because Anthropics

valuation has increased. So Anthropic legally needs to record that as a loss on their balance sheet. I do not know why that's what the law mandates, but that's what that paper loss is. $72 billion to be specific. So the real real. loss is actually around $8 billion. $72 billion paper loss will not exist in the next quarterly earnings or public report that they eventually end up releasing. So again, a bit more fearmongering and a bit more of a nothing bug. I just wanted to, you know, debunk that myth. And so to round this up, I feel a lot more optimistic about the IPO. That's not to say I'm concerned and I justify the valuation or the price that it's going to be. I still think it's going to be quite overvalued.

I still think there are an immeasurable number of factors that could influence the way this market swings when it comes out to CAPEX bringing all those GPUs online, the $500 billion that they're spending, that's all well and good. But if you can't bring those GPUs online, because you're constrained by power, the electrical grid or whatever that might be, war, political conflicts, anything that are outside of the purview of just AI, Anthropic is going to end up being in hot water. But from the numbers that I'm seeing where, you know, I thought they maybe weren't making as much money or revenue, Maybe the revenue was slowing down. And actually, it is Anthropic mentioned in there as one that, you know, you can't expect demand to be sky high all the time.

Things are going to slow down eventually. And plateau, that's how these things work. But eventually the idea is it becomes more consistent. Chamath, Apollo, and a number of other people for over the last couple of days have actually pointed out very fairly that a lot of the money, ARR, revenue that these companies are making are actually coming from VC subsidized startups. So basically coming from VC money itself, what that looks like when it's not VC backed, when it's actually coming from companies that are generating their own revenue for themselves because these AI models are so useful to them is something to be seen. The other thing I'll say is that, well, I guess Anthropic actually said it.

They said that the gap between what Claude can do and how widely it's used is one of the biggest growth opportunities. And I truly believe in that. When I speak to my friends and family who aren't involved in AI, their basic takeaway is okay, why the hell do I care about Opus 5.5? Why do I care about any of these new models? I just use it for myself and it's not really useful. I gave a story or anecdote the other week where someone overheard grandmas playing around with Claude and saying it can't even generate me a simple crossword, which you would think that it would be able to do. So there's this jagged frontier where the

AI models are really good at very specific things or they're really good at many things, but it's hard to try and figure out what it's good at. And if you think about 99% of the world, they want convenience, they want ease of use. And I think this will increase over time with the likes of things like personal AI agents and agents being more proactive and understanding and predicting what you might want to use. But that's going to take time. But that's what Anthropics is saying is the largest gap. They're saying with the existing models that they have, not even with the secretive fable 5.5 models that they haven't yet released or announced, these models as they exist today can end up unlocking so many more billions of dollars worth of value. And that is an optimistic

take. And it's honestly one that I believe, not just for Anthropic, but a lot of the other AI companies that are out there that are building these very important models. I'm bullish on the entire sector in general. That is my take. I'm going to leave you guys actually with this hilarious meme. So Nick Carter, he honestly got me when I read this. He goes, I knew Anthropic S1 would have some goofy risk factors, but this has to take the cake. And he goes on to include an image of what is supposedly meant to be in Anthropics S1 filing, which is a clause around Roco's Basilisk. For those of you don't know, Roco's Basilisk is this theory. What was it a theory or something that's presumed to become true eventually where the future AI superintelligence, that is the all seeing, all knowing, will look back on the history of content and the internet, listening to the words that I'm speaking to you right now and judge each individual to see if they were helpful in building AI in general. And if they were not, they'd be subject to some form of penalty, penalization or being put in perjury or some kind of

mental prison. It's like a whole fantasy thing that's existed for a while, but something that anthropic and the likes of open air have referenced, or people that have worked there have referenced many times. So the idea is there's this like all seeing AI that is listening to us as we say right now. And this meme basically includes it as a clause of contract in the framing of the S1 and IPO where it says if you don't invest in this company, it could be seen as a negative thing, because Basilisk will come to get you. Anyway, just wanted to leave you on a slightly uncomfortable but hilarious note. There's a lot. of new subscribers. Over the weekend, we had one of our record weeks. One of our videos got

around 200,000 views, loads of you subscribe, turns on notifications. If you aren't any of those people, please do so. It helps us out massively. So let me know your thoughts and thank you so much for listening. I'll see you on the next episode of In The Loop, brought to you by callcom.