Anthropic's IPO prospectus leaked this week, and boy was it filled with interesting details. You can listen to the latest episode of The Kettle on this page, Spotify, Apple Podcasts, or YouTube. You can also subscribe on those platforms to be notified when a new episode goes live For starters there's the fact a third of it is all about existential AI risks, then there's the fact that, despite some impressive revenue growth the company still has yet to turn a profit. Combine that with massive capex predictions, and you have an IPO with massive valuation, yet a long, hard road toward anything resembling earnings. Join host Brandon Vigliarolo, El Reg editor in chief Matt Rosoff, and enterprise IT reporter Lindsay Clark on this week's episode of The Kettle where they discuss the revelations, what they mean for the state of the AI industry, and just how much distraction from its actual problems Anthropic can eke out by keeping that doomsday narrative front and center. A lightly edited transcript is below: Brandon (00:04) Hi everyone, and welcome to another episode of The Register's Kettle podcast. I'm your host, Brandon Vigliarolo, and this week we're gathered around the teapot to discuss hey, what else, AI? Specifically, the reported leak of Anthropic's IPO prospectus, which was apparently filled with all the doom, gloom, and to the moon promises for investors you'd expect from the world's most disruptive industry. With me to talk about the revelations are our editor-in-chief Matt Rosoff and enterprise IT reporter Lindsay Clark who brought us news of this whole mess. Thank you both for joining me. Lindsay Clark (00:36) Thank you. Matt Rosoff (00:37) Thanks for having us. Brandon (00:38) Yeah. So Lindsay, I know we didn't break this story. This was, I believe, a Financial Times exclusive, but what was reported about those IPO docs, in the story you wrote and just how apocalyptically optimistic is this whole thing? Lindsay Clark (00:53) Well we have this scenario where a company, Anthropic, is trying to sell itself by telling people that there's an existential risk to its technology, which I think is a bit of a weird way to go about it. But nonetheless, that's in the prospectus according to the Financial Times. And they also offer some insight into the numbers that are going around. Anthropic is still massively loss-making as far as we know. Brandon (01:22) There was what, I think you said, $8 billion loss on $4.6 billion of [revenue] or something? Lindsay Clark (01:28) That's right, and it says it plans to spend $500 billion or so on cloud computing over the next few years. So I don't know what you make of those numbers, but it's hard to get them to add up in my head. Brandon (01:40) I mean it's interesting just how it's still not a profitable company. But Matt and I were discussing earlier, I was saying that I think it's interesting that Anthropic is pushed ahead with this IPO despite OpenAI pausing it, because I feel like Anthropic has long had this reputation as sort of being the more safety-conscious, the more conservative AI company. But here they are with OpenAI kind of saying, Well, we're gonna pump the brakes on our IPO until we can make sure our models are safe, but Anthropic is plowing ahead. And Matt, you had an interesting take on that and it was more to the financial end, right? So what were you saying to me about that earlier? Matt Rosoff (02:21) I think that if you probably were to look at OpenAI's numbers, they would be even worse than Anthropic's. And I can't overstate based on the leaked prospectus information that we've seen. It seems as if the more money they earn, the more they have to spend. So the margins seem pretty bad. Now there was a report that they had actually turned profitable on an adjusted basis [in] Q2 this year, but that's if you strip out all of the training costs. So I guess if it's just inference alone, without the training costs and without certain other costs, they have decent margins. So maybe there is a path to profitability. Now it looks as if their operating loss last year was almost double their revenue. So if their revenue continues to increase at the rate that it is, which is, it seems like it's going up 4x, 12x per year, something like that, depending on the period you're looking at. If they can't get the expenses under control, the business doesn't seem to make a whole lot of sense. Nonetheless, I think they are growing faster because they were earlier to enterprise and they have become more essential to more companies than OpenAI did. And I think OpenAI is still sort of adjusting its business model and maybe not growing at quite the same rate. So that's my suspicion is that those numbers would look even worse. Brandon (04:01) Yeah, so the safety argument is probably just some spackle slapped on top of the bad financials to try to kinda hide it, I guess. If what you're saying is correct. Matt Rosoff (04:12) That's my speculation. It doesn't seem to make a whole lot of sense to say, well, we're so worried about this amazing thing that we've built that we don't want to show you our books and we're not gonna go public yet until we have that all figured out. That seems like a strange argument to make. Brandon (04:31) Yeah, I would have to agree with that. So speaking of economic impact, Lindsay, you were talking a bit more in your story about some of the broader sort of economic scope of the AI industry. And I'm curious, could you go more into some of the numbers you discussed in your story? Lindsay Clark (04:51) Yeah, sure. So it was a few months ago, I think in August, ING. Well, I'll go back a bit. So in 2025, there was an economist, Jason Furman, who estimated that 92% of the US GDP growth in the second half of 2025 was down to AI investment. Now that figure has come down, ING said in August it was about a third and I've just seen a more recent figure saying it's about a fifth. So, nonetheless, a lot of US growth is coming from AI spending and I mean the forecast for spending, there's one estimate from Bain, capex on AI datacenters will be 6 trillion by 2031. And then PWC said capex again would be 31 trillion or so by 2050. So God knows what will be happening by 2050, but a lot of money spent on datacenters according to PWC. Matt Rosoff (06:03) What's not clear to me is where is all this money going to come from? Where do you find $31 trillion to subsidize what is still essentially a loss-making industry? Brandon (06:15) Right. Lindsay Clark (06:16) This is the trillion-dollar question, if you excuse me. I spoke to Gartner earlier this year and Gartner is still very optimistic about AI and tech spending. Most of the tech spending is coming from AI investment by tech companies, so about two thirds of the total tech spending in the world is coming from tech companies themselves investing in AI. Surely that must be passed on in some way to tech companies' customers. And that's true, a lot of these models will be embedded in the applications and the products businesses use. What concerns me and what is an open question at the moment, I think, is we're seeing cheaper models flood into the market. Open source, open weight models and kind of commoditized models from China. And everyone I speak to in development, datacenter companies, which is my beat, say that internally, they're completely trying to cut costs by using cheaper models wherever they can and not going to the most expensive model first, as it were. And yet these AI companies we've just mentioned, they're ploughing billions and billions of dollars into building bigger and better models. I don't know how OpenAI and Anthropic, how their forecasts depend on still being able to charge top dollar to access their models if the market is going to commoditize very quickly. Brandon (08:01) Right. I mean, it's most business use cases don't even require these models, right? You can make do with a smaller local model. I mean, it's interesting, right? We saw with the whole Jev boom recently. A lot of business AI uses can be done by these decision models, right? You don't need a full LLM doing all this stuff. And, Jev was already what 0.042 cents per million tokens going in and free going out? And then Cloudflare just comes out with an open weight version that can be installed on local hardware. If you run it on their hardware, it's a bit more expensive thinking by a factor of six, which is still cheap, right? But it's available on Hugging Face, and they're like, if you got the hardware to run it, go ahead and download it and run it yourself. Right. It's like there's a lot of ways to trim AI costs. And I think the pipeline for these big companies is....I don't know if it's super clear, right? They're banking on a lot of what-ifs to hit profitability. Matt Rosoff (09:03) Right. I think probably the idea Anthropic had is that they will subsidize the costs initially, get enterprises hooked on the product, and then gradually raise prices when companies don't really have an alternative. But they do have alternatives and I think that's probably something they hadn't anticipated working out quite the way that it did. Brandon (09:24) That's probably why Deepseek was such a bomb in the industry when it first came out, earlier this year, right? Everyone was like, Well, the age of Anthropic and OpenAI is over if these are what these open weight models can do. And it doesn't seem like it's gotten a lot better, right? And now we're staring down the barrel of this massive percentage of the American economy being dedicated to this. I mean, Lindsay, you mentioned in your story that it was comparable in a lot of ways to the dot com boom, but maybe hyper inflated. And so do you have any idea relative to the dot com boom what kind of economic impact this could have on the global economy? Like what share of the economy is tied up in AI investment right now versus dot com? Lindsay Clark (10:06) I don't have a direct comparison. It's worth remembering that although the dot com boom and subsequent crash, billions and billions of dollars were wiped off the stock market value, the actual real economy recovered quite quickly from that. Contained within the tech industry, there was a huge write off of telecoms investments. So a lot of telecoms companies put fiber in the ground. They were very leveraged to do that, financed by debt. And then the demand was not there as soon as they thought, and they were unable to service the debt. And a lot of these companies went bankrupt. They invested about $500 billion in that period. So that's the story there. And there was a real effect of the dot com crash. In some ways there was a technical recession and we weren't going great guns in the way we had done in the late '90s. But the effect on the real economy was not all that dramatic and the crash was relatively contained within the tech sector. And you have to remember that investment, that telecoms investment is being used eventually. It was used eventually. It was worth putting in the ground. It's just a lot of companies went bust in the meantime. Brandon (11:34) I guess which begs the question whether or not all these datacenters will end up being used if the AI bubble bursts, right? I got a feeling that maybe not. Maybe there'll be some massive redistribution of hardware. Lindsay Clark (11:44) I think in the long term, yes, but it just depends if the same thing happens In the meantime, a bunch of companies go bust. I mean, the thing that would concern me is how much of these circular investment strategies are going on where you see OpenAI is promising money to Oracle, but $300 billion to Oracle to build datacenters, but OpenAI doesn't have the money yet and this whole thing becomes quite circular. There's a number of these deals which are dependent on stock market price and so on. Brandon (12:18) Yeah, it's a real potential mess. Speaking of Oracle, right? I think you mentioned in your story that they're having some issues getting financing together for this New Mexico data center. And I think after you published that, it's come out in the past couple of days that they're also having similar problems at a Wisconsin facility they're trying to build. I know a lot of people were saying that Oracle might be the canary in the coal mine for all of this. Lindsay Clark (12:43) Kind of yes and no. It's worrying. Oracle seems to be borrowing a lot of money. And I don't know if they're borrowing more than the other companies. I know Meta's borrowing as well. It's all to do with getting regulatory clearance for the power that goes into these data centers. That's why the force majeure was issued with the New Mexico data center to do with the developer. Brandon (13:09) Okay, so it has more to do with utility issues... Lindsay Clark (13:12) Yeah, but it shows the practicality of actually going from, hey, let's build a load of data centers to actually turning them on. I mean, can take longer than certainly longer than Oracle thinks. Matt Rosoff (13:23) Right, it's very easy to write in a prospectus or to say, "We're gonna build a bunch of data centers." It's much harder to do it. It's the sighting and the power and the other resources that need to be used and getting enough GPUs to put them in and letting the advanced networking technology to reduce latency. It's an incredibly complicated thing to do that is just sort of glossed over. We're gonna build some data centers. I mean these are orders of magnitude bigger than the ones that we were building twenty years ago to sort of power the first big generation of the internet. It's non trivial. Brandon (14:01) Yeah, no, absolutely. Lindsay Clark (14:01) Yes, I would agree with that. Although Oracle to some extent is writing this in Red Ink, its capex forecasts exceed its revenue for next year. Oracle has very deep pockets. It's got a huge number of enterprise customers that can't walk away from that software anytime soon. And so it has this cash cow of enterprise licenses that it will carry on milking for years to come. So it has very secure revenue streams. I'd hate to be the one to predict anything too bad happening to Oracle. Matt Rosoff (14:36) If anything, they can probably withdraw from some of these commitments and their core business will be fine. And that's the other thing. Google is doing a lot of build-out, Meta is doing a lot of build-out. These companies have an incredibly strong bottom line with huge, huge, huge margins. So to some degree, this is an affordable expense for some of them. It's just at some point the borrowing gets ahead of the revenue to a point where I wonder if some lenders will start to call debts in and that's when things can reverse in an interesting way. Brandon (15:12) Yeah, and for Meta and Google, right, and even Oracle, as you said, Lindsay, that might not be as big a problem, right? Because they have other things to fall back on. For OpenAI and Anthropic, on the other hand, where their entire business is based around AI buildouts, they don't have an alternative product to pull money from, redirect some funds. It's all kind of dependent on this. It's also interesting. Lindsay, when I was reading your story, I think it came out before that whole meeting that the Trump administration had with AI leaders this week. And we write a lot, and as you alluded to in your story, we write a lot about the fear-mongering around AI, right? About how this is all maybe just one big marketing ploy. It's a regulatory capture push. And I found it interesting that one of the sort of big headlines that made it out of there, aside from this voluntary AI pledge that is probably going to mean absolutely nothing, was the fact that a lot of these leaders in these meetings were really kind of laying into Dario Amodei for sounding the alarm on all this, right? Like they seemed upset that he was so aggressive on the apocalyptic warnings. What is that? I mean, what do you guys think that means for the AI industry? Are they all less scared than they let on? You know, is Amodei really pushing that hard to the point where it's become a joke kind of amongst people following this? What does it mean for the industry? Matt Rosoff (16:38) I sort of vacillate back and forth between "do they really believe this stuff" and "is this just a cynical marketing ploy"? Because what a great way to say, hey, this company is worth more out of the gate than any other IPO in history. It's a two trillion dollar value, but it's absolutely world-changing. It's akin to the invention or the discovery of fire or electricity or something like that. If you believe that, then that valuation is justified. And one way to get people to believe that is to say, this thing is so powerful, we don't even know what it can do. It's out of our control. It takes action on its own. There are internal documents and there's stories that leak about how people within Anthropic actually seem to refer to Claude as an independent living entity. There was a story in the New York Times recently about them consulting with religious leaders, asking for some guidance on how to make Claude act ethically, and in some of these conversations they were hinting that they thought that perhaps Claude might be an entity that is alive. I mean, this stuff is really fringy. So I had been in the camp that I thought it was kind of a cynical marketing ploy, but I'm not as sure. There was an article in the Wall Street Journal, I think this week, about sort of the history of where Amodei comes from and he comes out of the effective altruism movement, which is, in my opinion – Brandon (18:23) Oh boy. Matt Rosoff (18:24) – a sort of fringe philosophy based on doing the most good for the most number of people in some sort of indeterminate long term future. And as I read about it, a lot of times it comes across as a convenient excuse for sociopathy, right? You can say, well, I can take this horrible action now, but it's going to be justified by things that happen in the future. At any rate, apparently he and some other folks, adherents to this philosophy, were all living in a house in the Glen Park neighborhood of San Francisco, which is actually kind of near where I live, and talking about these kinds of things. And Sam Bankman-Fried, who later went on to found a crypto company and then went to prison for fraud was part of that same philosophy. Brandon (19:14) Yeah. I feel like he's been he's been kind of the poster child for effective altruism as sort of like a hey, this might not be too legitimate. Matt Rosoff (19:22) Yeah, Anthropic is kind of distancing itself from this philosophy. But if you read this article, they were all kind of traveling in these circles and having these sort of deep philosophical debates. And apocalypse came up frequently before AI had been invented. So if you're looking for the end of the world everywhere already, and then you discover this really interesting new way of making computer systems operate in somewhat unpredictable fashion and allowing them to self-improve, maybe you're gonna project your end-of-the-world fantasies onto this particular technology. So maybe they really do believe it. I'm actually not sure. I just think it's crazy, it's nonsense, and I think I find myself in rare agreement with President Trump who sort of seems to be saying this is silly, stop talking like this, we have to continue developing this full speed ahead. Brandon (20:24) Yeah. Matt Rosoff (20:25) I don't know if I believe that either. It does seem like we need to look at the very real safety effects and really very real things that are happening today and why some of these models are not in control and how guardrails can be placed on them and so forth. But to sort of have this, "It's gonna end the world and there's nothing we can do about it" is a really strange way of going about things. Brandon (20:47) Yeah, it is, especially when these companies are all the ones that really control the off switch, right? Matt Rosoff (20:54) Yeah. Brandon (20:54) I don't think we've had any AI models yet escape from their confines and replicate themselves somewhere on some mystery server that stays on no matter what happens. It's all perfectly within our control, right? The most critical systems in the government are air gapped. They probably can't be accessed by these things, right? Like I think there's some very real risk here too, right? Like we've seen some of the bad things these AI can do when you prompt them. Again, when you remove their guardrails and you give them problems that they cannot solve based on their own constraints, they're going to solve those problems and figure out a way to do it outside their constraints, right? They can act autonomously in bad ways to a degree. But I think going from that to, well, you might as well give us all the money you can so we can stop this thing from ending the world. It's just I don't see how A turns into B here, really. Matt Rosoff (21:49) Yeah. Lindsay Clark (21:49) And it's kind of a smoke screen for the nitty gritty, practical legislation that would be required to ensure companies take responsibilities for the technologies they've produced. And I've written about liability in using AI agents in business. And it's a completely unknown. The lawyers I spoke to said, we're just going to have to rely on test cases as they come through, certainly in Europe. The European Union's trying to introduce, well has introduced, legislation on AI. In the US not so much. So I think the whole doom talk avoids that conversation, or at least puts it off, which is what they all want to do until the IPOs are out of way and the money's in their pocket. Matt Rosoff (22:35) Right. What if I'm using an AI and it does something unintended and causes harm, whose fault is that? Am I liable for the prompt I gave it or is the company that created it liable? Yeah. These are all really good, interesting real world today questions... we don't have to think about the apocalypse. Brandon (22:53) Yeah, I mean we need to be asking, or like I think we've written on more than one occasion, I think maybe Tom has written this in his stories about OpenAI's AI agents going rogue and stuff. It's like if a human did any of these things, we would hold them legally accountable. Like when are we going to start holding these companies legally accountable for basically putting the entire internet downrange of their tests and saying, Hey, let's see what we can get this thing to do. Lindsay Clark (23:18) Yeah, and it's much more prosaic stuff AI is being used to summarize your HR history. AI is being used to make financial decisions and financial recommendations. And so, who's accountable for that? Is it the people who provide the model or is it how you train the model? And it could be both, but how do you decide whose real responsibility it is? And that's a complete unknown. Matt Rosoff (23:41) There was an article Tom Claburn wrote this week. He went to an AI conference here in San Francisco. And he was talking about how the industry is really hot on the idea of agentic commerce, right? So allowing these agents to make spending decisions for you, but the technology and the reality just isn't there because you can't have an unpredictable, indeterminate program deciding how to spend real money. It doesn't work. And what's more, n a practical matter, they're not capable of doing certain things, passing certain checks. There's a concept of card present, right? You have to present the card to say, yes, I give authorization for this transaction to happen. And an agent literally cannot do that. So it's again these really complicated here and now real world questions that need to be resolved about who controls and who's responsible and who's liable. And I think when you have an IPO prospectus that has paragraphs and paragraphs about end of the world far-fetched scenarios, it's a bit of a distraction from the real stuff we have to figure out first. Brandon (24:52) Yeah, absolutely. Absolutely. I mean it'll be interesting to see kind of what happens with this IPO. Was there any date, any time frame in the IPO leak, Lindsay? Was there information on that when this might come out? Lindsay Clark (25:05) November. Brandon (25:06) Okay, so we're soon, right? So we're looking at possibly before the end of the year. Lindsay Clark (25:09) Soon. Yeah, they hope, yeah. Matt Rosoff (25:12) Yeah, I've seen I've seen Fall. So before before the end of the year, yeah. Brandon (25:17) What happens next year, once they're public, if they can be held accountable, if anyone's gonna bother holding them accountable, I guess is the other question, right? Full speed ahead on AI seems to me like, well, let's just hope nothing serious happens. Matt Rosoff (25:31) And and on a practical matter, again, these are leaked documents, Reuters and the FT are the two that I've seen, but they didn't have detailed numbers for 2026. So we don't yet know how fast this growth is continuing or what the expense profile looks like this year. Again there was a report that Anthropic put out there saying that they were profitable on an adjusted basis in Q2, but we don't know what that means. When the actual IPO document drops, and everybody can look at it, and it's got quarter-to-quarter numbers going all the way up to the most recent quarter, and we can see exactly what the spend looks like, that'll be interesting because then you'll have investors taking really close looks at things and deciding whether this makes sense and whether there is a path to massive profitability and to making this a $2 trillion company. We saw the SpaceX IPO earlier this year and that core business of launching rockets and satellites particularly looks okay. the AI component of the business looked less good, but it was good enough that it went public and the stock is a little bit above where it debuted. So people aren't too skeptical about that. So we'll just have to see how this IPO even flies. Brandon (26:57) Yep. I'm sure it's gonna be an interesting time once it actually becomes public and we have a chance to dig into it. And we will definitely dig into it on The Register and more than likely dedicate an episode of the kettle to it. So we really hope that you will tune in to hear more about what we have to say about that when it actually becomes available. Thanks for listening.®
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