Anthropic targeting a $2 trillion IPO. According to the Financial Times, this would obviously break the record setting $1.75 trillion IPO by SpaceX. FT reported Wednesday night that investors expect the company to go public in October which is like six to eight weeks away. annualized run rate. We talked about this sax a bunch will end the year between a hundred and $120 billion dollars. This is an extraordinary ramp up of revenue that we have never seen in Silicon Valley.

Sets the stage for understanding the unprecedented scale of Anthropic's revenue growth and the significance of its potential IPO.

probably on the margin, Anthropic is losing share to OpenAI, to open source, and to Grock. and they're still growing so fast. The numbers are still exceptional. So I think you know that speaks to the... the pie is getting ginormous. So even if on a percentage basis Anthropic is losing on a percentage basis the real number and we talked about open source being dark tokens that aren't tracked anywhere. You know this is a major major pie growing moment.

Illustrates how a rapidly expanding total market can mask share losses, a crucial lens for evaluating AI company health.

if you're ending the year at, let's say, a hundred billion run rate up 10x plus year-over-year. And by the way, they've grown 10x year-over-year for the last 3 years. So it's growing exponentially. If that rate of growth were to continue, they'd hit a trillion dollars of ARR by the end of next year. And then the question you have to ask is, well, is the TAM big enough for that? But also, is there enough compute? Is there enough energy? I think you start to get into physical constraints.

Frames the fundamental tension between exponential demand for AI and the hard physical limits of energy and compute infrastructure.

Daario has said that Anthropic might be the only private company in the world at some point. Think about that. And you know in this vision an anthropic maximalist vision there's anthropic and then there are governments and that's it. So there's a lot of confidence. I'm sure they have more advanced checkpoints than Fable up their sleeve. I would probably take the under on them being the only private company in the world.

Reveals the extraordinarily ambitious — and arguably hubristic — internal culture at Anthropic, raising questions about mission versus commercial ambition.

depending on how you count it, there's, you know, 25 to, you know, 65 trillion in in knowledge work. Um 25 is is kind of a number I've used. I was told by um you know, the head of the AI institute at at one of the three largest investment banks that it was way low. And then it's a question of is it labor substitution or accelerating growth? Thus far, it really does look like it's accelerating growth. There are, you know, there are more job openings for software coders today than there were a year ago.

The labor-substitution-versus-acceleration debate is the central economic question of the AI era, and early data points here are surprisingly optimistic.

right now the narrative on AI is not good. It's that a data center takes all the water because someone made a mistake in a book three years ago and they're off by I think a factor of a 100,000 in the amount of water a data center uses. So it's just wrong. They raise your cost of electricity which is just wrong. They lower your cost of electricity. The Wall Street Journal just read a written a story about a town called Ellenale where like it was a dying town. A data center got built. It's revitalized the town. Tax revenue is 10xed.

Challenges widely repeated media narratives about data center harms with concrete counter-evidence, relevant to anyone following AI infrastructure policy debates.

you just look at the pricing here of GLM2 versus Claude Opus. And you know, it is 90% cheaper to use these products. I'm using them. the founders I invest in are using them and increasingly corporate America is going to embrace these solutions. It's just a little bit harder to set them up and it's coming folks. And if you think it's not that corporate America is not going to embrace open source, you have not been paying attention to the last 20 years when they did exactly that.

The 90% price gap between open-source and frontier models is a concrete signal that commoditization pressure on closed AI providers is real and accelerating.

He has picked up the abundance crown which Sam Waltman dropped when he went for the private company and he says super intelligence is invention not automation and that AI safety should be based on the balance of power no singular centralized intelligence.

Succinctly captures Zuckerberg's strategic repositioning as the optimistic, pro-distribution voice in AI — a direct contrast to both OpenAI and Anthropic.

the notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic. Historically, hoping that an absolute power will benevolently provide for humanity, if sufficiently enlightened, has not led to safe or positive outcomes. So I think the point he's getting at here is that a major frame on the whole AI debate is not just about open or closed. It's also about centralized versus decentralized.

Reframes the AI safety debate from a technical question to a political philosophy question with deep historical precedent.

anthropic and people in the effect of altruism movement believe that this technology is too dangerous to distribute. And what Mark Zuckerberg and I think Elon and Jensen believe is that this technology is too dangerous to centralize. and history has spoken and when given the choice it is always better to distribute and decentralize there is there's really no counter example that I can think of.

Offers the sharpest possible formulation of the two opposing camps in AI governance, making it easy to map any policy position onto one of these two worldviews.

their whole right to charge this massive premium for tokens which Jal that's the point you were making before is you're wondering how sustainable that is because of all these open models that are coming up and are offering tokens for much less their whole pricing power that premium they're able to charge is because they're 6 months ahead of those open models and that 6 months be eaten up in the blink of an eye if they were subject to regulatory approval.

Reveals that Anthropic's business model is entirely dependent on maintaining a narrow capability lead — and that the regulation Dario advocates would destroy that lead.

Open source makes Frontier tokens more valuable. So like let's just say that, you know, Enthropic, OpenAI, and Grock, they're at like a 250 IQ or 200 IQ. Well, if you have a 200 or 250 IQ intellect that can orchestrate these open-source 150 IQ intellects, like that that's actually more that makes the 250 IQ intellect more valuable is because it can farm out past.

Provides an intuitive mental model for why frontier and open-source AI are complementary rather than purely competitive — with direct investment implications.

Just think about how energy efficient we are. all of our brains. To approximate our brains, you need to have a data center that consumes the power of a million American homes running for probably 6 to n months. And then you get our brains and then every time you want to answer a question, you need the power of like a thousand American homes, okay, to operate at the level of our minds.

Puts AI energy consumption in visceral perspective, making the case that human cognitive efficiency remains a massive and underappreciated competitive advantage.

Nvidia is being a matchmaker. And what they're basically saying is, hey, our compute, because it's so flexible, is going to have a long enough life that you can finance it at lower rates than other um kinds of compute. And I think that's smart. That's good for everyone. And it is interesting if you look at the underlying architectures of the three what I call big Chinese open source models and maybe even throw a few or four you know if we have Quinn if we have Kimmy if we have DeepSync um and then we have GLM they're actually evolving in very different ways and that architectural variation works in Nvidia's favor and in GPU's favor um because it means that you do need this more flexible compute to be able to finance it to be able to think that you can have a long life.

Framing Nvidia as a 'matchmaker' using architectural diversity in Chinese open-source models as a strategic argument for GPU longevity is a novel and counterintuitive investment thesis.

hey um Blackstone Goldman Sachs KKR Apollo Black Rock um I'm leaving someone out and I'm so sorry there are six of them come to us if you have a deal you can bring it to us and we will give a residual value guarantee and I think the way that that residual which will further lower the cost of financing these and that residual value guarantee can then be incorporated into those companies underwriting and what that basically means is they're saying that after 3 years four years we guarantee that these GPUs can be rented at a certain rate and then the risk that they are bearing is the risk between that that value um and wherever the market rate is and right now everything's going straight up Nvidia has better telemetry than almost anyone and to the supply and demand of compute so they can put that at a very very smart place

Nvidia's residual value guarantee to major financial institutions is a structural financial innovation that could unlock massive new capital flows into AI infrastructure.

Corweave said that they are renting ampiers at economically profitable rates today for 2029. So an amp year that came out in 2020 is going to have a 9year life. And I think that's what Nvidia sees. You know, it's like old American cars, they get sent overseas.

A concrete data point — 9-year GPU economic life — dramatically changes the math on GPU-backed financing and undermines the bear case on compute obsolescence.

The biggest risk is that you get a glut of compute and you get an overbuild. And in the same way that we had dark fiber after the dotcom crash, if you had dark GPUs, that'd be a disaster for everyone. Especially if you built out your compute infrastructure expecting a spot price of $30 to $50 a watt as you know Elon said that they were expecting right so if all of a sudden there are too many people racing to provide this compute and now there's an over supply and the market crashes that'd be the risk factor in a weird way all the political headwinds I think insure against that outcome because it is so hard to build data centers for all the reason we said there's a whole moral panic/ SL hysteria/hoax going on that actually it's those political headwinds I think will almost guarantee that there's not an overupp relative to the exponentially growing demand.

The 'dark fiber' analogy is the clearest articulation of the AI infrastructure bear case, and the counterintuitive argument that political resistance to data centers is actually a market stabilizer is worth examining seriously.

the numbers are getting so big that the TAM is getting constrained by the ability to finance this buildout. And what he's doing is alleviating that finance constraint so that he can grow uh as big as the the the TAM actually is right is removing that constraint. So for just to take one example Elon wants to add somewhere around 6 to8 gawatt next year. We know that that would cost 3 to400 billion of capex. The company just raised 100 billion in its equity and debt offerings. So obviously they would have to go out and finance that somehow. And as we talked about in our previous episode, the simplest way to finance it would be to get seller financing from Nvidia, especially given that the payback period could be as quick as one year. So now Jensen is creating the you could say the line of credit using these big banks, using these big private equity shops, and he's making that available, and that's going to now benefit all of these downstream purchasers. I don't think it's circular. This is not a a circular situation like Gurley's worried about. This is I think Wall Street banks and private equity firms providing financing based on the expected cash flows that will be delivered from these GPUs. In some ways, Nvidia is kind of becoming the central bank of AI, the Federal Reserve of AI.

The 'Nvidia as central bank of AI' framing captures a genuinely new economic structure where a chip company controls credit creation for an entire industry.

One point that really stuck with me was when the private equity guys said that this was a little bit like what they do for plane financing where when an airline buys airplanes, they're able to finance it not just based on the creditworthiness of the airline, but rather because the airplanes themselves have value. And that makes it much easier to finance because you know that even if the airline gets in trouble, you're protected, right? you have assetbacked financing and that's what they're basically doing here with GPUs. Now, in order for that to happen, Nvidia has to standardize. They have to create essentially reference designs and so forth and so on so that it can all be standardized enough for these Wall Street guys now package it up and securitize it, turn it into securities.

The airplane financing analogy clarifies the precise financial mechanism — asset-backed securitization — and highlights the standardization requirement that makes or breaks the whole structure.

there's a dead man switch on this which is you know the switch that you have to hold down to run the train but if you have a heart attack your hand comes off the switch which is anthropic and open AI. These are the two biggest customers. One of them has scaled back open AAI their ambitions in this regard of their buildout from like 1.4 4 trillion to like butt 600 billion. And um then there's anthropic which we just said okay they're going to go to 400 billion in revenue next year something like that or they'll end the year at that run rate. If they don't need the compute or compute gets so efficient or open- source models create a headwind whatever it is they're going to take their hand off the buy button and that dead man switch will then slow everything down so we don't get a mortgage back security. Well, that could lead to a car crash. But actually, this is why I think it's the anthropic IPO is really important for the market is getting those quarterly earnings and be able to see their numbers every quarter. I think it'll become probably the most important signal that the entire industry has.

Identifying Anthropic's quarterly earnings as the primary real-time signal for the entire AI investment thesis — the 'pace car' — is a framework every investor in the sector should internalize.

The overwhelming majority of tokens are profitable for everyone in the chain. everyone and I think the anthropic S1 is kind of going to make that clear. But when I listen to these macro and value investors talk about AI, it's a little bit about me saying, you know, I'm very bearish on the world economy because oil is at $500 a barrel. And you know what? If oil was at $500 a barrel, that'd be a good reason to be bearish. It's just not like they're just wrong. Like the simple fact is wrong. to be they're they're paid in some ways to be doom scrollers and merchants of doom. I I can tell you, you know, one framing of this that I've been working on, which is the number of people employed in the United States, like 150 million, 160 million, what their collective salaries are, 10 trillion, 12 trillion, whatever it winds up being. There is no world in which I don't see corporations and people in the economy spending five or 10% of the salaries of their employees on the equivalent in tokens. In other words, somebody makes $80,000 a year on average. They're going to you you you will spend $8,000 10% of their salary or a minimum of $4,000 to make them more efficient. We have an analogy for this. It's SAS software and compute computers on their desktop, mobile phones, etc. Just their general use of technology. If you put those numbers together, you're looking at a trillion dollars in AI spend just in the United States.

The '$8,000 per worker in tokens' framework — anchored to the SaaS/desktop compute precedent — provides a ground-up, intuitive sizing of AI's total addressable market.

Yeah, I think it is. I mean, I think it's Can can we show up show that graph of the prao frontier? This is pretty wild. Now on the left, what this shows is kind of like quality or intelligence on the um y-axis and cost on the on the x- axis. So you want to be in the upper right quadrant. And you can see here you just want to be on the outside of this and you can just see like how disruptive Grock 4.6 is pricing right? So as you sorry just as you move as if you move right on the x-axis it's getting cheaper and the y ais is the capability and it's getting more and more cable as you move up but they they invert the x-axis so that as you move to the top right it's better right exactly and I mean this is now and this is on cursor bench and xai you know SpaceX is you know almost certain you know they have a right to acquire cursor they're working with cursor so maybe this is grading your own homework well right here on the right, this is from Data Bricks, which just raised money at $190 billion. Um, this is a very real company that is very sophisticated. And you can see like even on this, you're well ahead of um, Fable 5

The Pareto frontier benchmarking framework — quality vs. cost — is the right analytical lens for evaluating model competitiveness, and Grok 4.6's position on it is a concrete claim worth verifying.

Very few of these investors talk about Grock at all. And it is parto dominant on a lot of measures. And we have an existence proof that anthropic went from whatever it is a billion to 50 billion really fast. And if anthropic is worth, you know, with two two trillion per the FT, you know, three or four trillion, you know, maybe settles on a previous settle out. Um I said I thought that was a market clearing price. I didn't say that's where I thought it was worth. Um, you know, maybe people should start to consider Grock when they think about SpaceX. SpaceX has so many ways to win and I think that's the the higher bit here is and it's and we're obviously all talking our book here.

The argument that institutional investors systematically overlook Grok when valuing SpaceX — despite its Pareto-dominant benchmark position — points to a potential mispricing in private markets.