Are Anthropic’s AI Economics Finally Working?

Speaker A: Are AI economics finally starting to make sense? What we've learned recently with anthropic public filing, or S1 filing, is that we're starting to see numbers that actually add up instead of like what we've assumed. Because let me be clear, we haven't seen any real numbers. We've had assumed numbers and leak numbers, but we've never seen a public one of these massive companies go public with their revenue numbers that we can trust. This is a public filing that has to be vetted, that has to be audited, because it's allowing them to be listed on the stock exchange as a public company and we can buy shares in the public company. Right. So this is a legit offering. So they have to go through these numbers pretty intensely. These must be legit, otherwise they could be, you know, sued for fraud. And what we're seeing with the latest release is that there is revenue, and revenue is strictly outpacing compute spending. Now, preface that with there is a ton of debt. I'm not going to get into specific numbers because I'm going to bore you with the numbers. And I don't understand all the numbers either. I just know the correlations between the numbers because I read the summaries. All I know is that the 2026 revenue for Anthropic is 14x what it was a year earlier, the first half of 2026, I should be clear. And compute and infrastructure expenses obviously also rose, but they only rose by 3.8x, which actually fell. The amount of increase fell from 201% the year before to 55% the 2026 first year. So that means that expenses are still rising, but they're rising a lot slower and revenue is rising exponentially faster. So we're seeing this correlation of like, hey, they're profiting from inference with the revenue, and they're able to get more efficiency out of their current hardware and the hardware that they're making. Right. They're, they're, they're starting to optimize. We talked about this many times on the show where I'm like, for the past six years, all the AI companies cared about was intelligence. That's all they cared about. All of the money, all the research, all the R and D went into how to make the models more intelligent. Well, I think over the last maybe year, year and a half M, they're starting to shift that where they're spending a significant amount of money on compression, optimization, hardware acceleration, et cetera, et cetera. There were so many knobs to turn to make it cheaper. That I was almost positive that they would be able to figure it out, because they had, they had, they had done nothing. They literally were just like 50 90s. Oh, yeah, let's get to 50 90s and just throw compute at them with no consideration or very minimal consideration for how to actually, like, optimize them. They were like. I listened to a podcast on, uh, like the, the new gigafactories that Elon was creating or the new giga data centers, these massive data centers that he was creating. And they were just finding buildings, like, just the old construction, old, uh, warehouses. And they were just literally rolling racks of GPUs into them. Just like, they weren't like retrofitting them or anything. It's just racks with wires freaking everywhere, just trying to get them up. Like, there's no efficiency there. They're burning. They're just trying to get compute up. There was no time for efficiency. It was an intelligence war. But now we're seeing this first steps and the first shots fired in the efficiency wars. And with this IPO filing, there is hope and clear evidence that they are able to profit from inference. So there is a healthy margin, like, we're paying a lot more, like API costs specifically, and potentially even subscription costs. I haven't actually done that in depth research, because this came out really recently, uh, to see if the subscription is also maybe covered to a certain degree by these costs, by, by the revenues, because they're making margin. They're not. They're not operating at 0% margins anymore. They are making a healthy margin. And that poses a lot of questions that I want to throw at you, Matt, and we can discuss the first one. Is, is the bubble not popping really? Like, does this change the argument that AI companies cannot make money because inference is too expensive?

Speaker B: I don't necessarily think that, that, that this is going to stop the bubble. I think it's positive news for the economics of AI companies, and I think it proves that they could potentially be profitable. But we also have to remember the amount, like you just said, of, of inefficiencies that were put in place in order to build things to this amount. And I also recently listened to a, uh, Diary CEO episode with Mark Cuban. And I don't want to put words in his mouth, but his idea behind AI and some of his ideas are really interesting to me. And one of them is that the AIs themselves are not getting smarter the way we make them smarter. The way that we make them do more is we throw more compute at them. And that doesn't really reflect intelligence. Again, I'm paraphrasing what he said or how I understood it. I'm going to link to that episode inside of this, the show notes. You can listen to the episode. I enjoyed it myself. But I think that that's really interesting. Is I exactly what you were describing? They're going to, going into these warehouses, these construction zones, whatever, and they're throwing, they're throwing compute at these things. Meanwhile, a human can go from having the exact same organs and parts on board, if you will, and can learn and get better at multiple things, can get better at doing exercise, can get better at reading, can get better at biking around, can get better at all these things. Meanwhile, I want, need my AI to be faster. Give me another $10 million in GPUs. Give me another, you know, 2 billion doll RAM. Give me another $5 million in, in all these other computing things. Give me another $2 million in networking infrastructure. More, more, more. And the actual AIs are not getting more and more intelligent. So I think that it, maybe there, maybe it strengthens the, the wall of the bubble, if there is one. I'm not an economic expert, but I think that there's a lot more to this story obviously than what we are going to be tackling in just a web news episode here. Because there's a lot of debt that's been taken on. There's a lot of public questions, a lot of public protests against these AI data centers. There's a lot of public protests against the use of AI in general. There's a lot of questions as to what the regulations will do. And my whole point there is, is that it doesn't just take good economics for a bubble to not pop but go away. It can be popped by bad regulation that comes in bad in the, to the actual AI companies where it blocks their training or it, it hurts how they do things or it hurts how they buy hardware. And now all of a sudden, maybe the debt collectors come out and they say, well, you were training at this pace. You're not training at that pace anymore. Where's my money? And pop goes to the bubble. Who knows? Who knows?

Speaker A: I, uh, I definitely agree with you. I, I don't think this is a direct line to this being a bubble pop. I think if anything, this proves that a company with infinite resources is able to figure shit out. But the reality is that there's a lot of smaller companies that won't be able to figure this out and they're solely relying on the Invested money that they have. That might not be enough to figure it out. The amount of money these companies like OpenAI and Anthropic are burning is astronomical. Like H1. We still had massive losses in the first half of 2026. 80, $80.74 billion in losses in the first half of 2026. The ridiculous numbers. Absolutely ridiculous numbers. Right. So the only thing that I see this staving off is this is a push to be like, to show investors and the public, because this is a public offering. So the public is going to be investing money. They are going to net a big chunk of change from the public offering. Let me be clear. They're going to make tons of money or not make, but like get tons of money for their shares. It's a, uh, it's a way for them to show that, hey, we've got, we, we have a path, right? Like this is a path forward. There is money to be made here. We don't have. I don't think they have a direct answer to like their astronomic evaluation yet. I think all of their answers is like super intelligence. And that's not really. Like, what does that mean? Like, what, how does that, how does that actually make money? No one knows that answer, right? Like, no one, no one has a very direct line for that. And I think that is a very high risk factor for the bubble popping is we don't have a direct line to the valuation making sense. I think the valuation they're trying to get to is 2 trillion, which would make it the biggest IPO offering ever. Public IPO, like first public IPO offering ever. I don't know if they're going to get to trillion, but that's what they're trying to. It's going to be probably somewhere between 1.5 and 2 ridiculous, like absolutely crazy amounts of money. But this is like a, uh, hey, we're on a track now. Like, there's something to be said about the fact that they have figured out a way to make money from a product that didn't exist even like two or three years ago. You know, like from an investment point of view, you're like, okay, maybe I trust these guys a little bit more. Maybe I'm willing to invest a little bit more money because I see the outcomes that they're, that they're getting to, even though I don't see the potent, like, I don't see the direct line to the potential outcome like, uh, of the evaluation. Like, I see that they are able to figure it out, but These are, these big companies like OpenAI is probably going to have something similar, if not worse, potentially. I, I have a feeling that they're delaying their public offering because they're trying to make their numbers make sense like Anthropic has. Um, but regardless, it's going to be probably similar, but the other smaller companies, it's going to be tough. And the bubble popping doesn't mean that all the companies go down. It probably means that majority of companies go down. So I still think there's a high risk of a bubble pop. It's not going to be a complete bubble pop like we've talked about. It's going to be contraction, whatever you want to call it. It's probably going to happen in a more contained sense. Probably not on uh, probably not Anthropic and OpenAI or at least both of them. For sure they're going to be around. We can see their economics now. Now another question for you, Matt. Do you think they would ever pass the savings that they're getting onto us? Do you think the cost will like, for us will always be rising? Like we've seen

Speaker B: the costs of, in terms of like the plans to the

Speaker A: plans, the, the tokens, like the, the straight API costs. Like, do you think we'll ever, they'll ever go down now that we've seen that they can make money on it? Initially our assumption was that they were, they were even, even with us paying them. They were burning the money on the, for that compute. That was what everyone was saying. You know, three, four months ago, everyone was saying that, but now we see that that's not the case. So could they pass the cost back down to us? OpenAI just released a $500 subscription. That seems like a lot. Um, would we ever be, would they ever be like, oh, we're removing it back down to just the $200. We're giving you more usage.

Speaker B: I could see it due to other people innovating in the space.

Speaker A: Um, I

Speaker B: think that I, I don't know what's going to happen with this whole super intelligence idea or how intelligent they're going to be able to make these things realistically. Because at the end of the day, I mean, we could, we could order more graphics cards today than have ever been made in the history of mankind. We could, we could do that and it would be very detrimental to the economy and there'd be a whole bunch of other different things, but we could, we could technically do it and slowly but surely produce those and then throw it all in a model and it could still not be a super intelligence. It could still not be all that impressive. I think personally, I think one of the things that is going to absolutely disrupt them is innovation. Meaning random, random agents that just come out at the consumer level. Something like Muse, uh, there's even the Muse pendant and things. I'm not saying that those are the end all, be alls. My point is, is those are innovations that are coming in in different ways, using the technology in different ways. Having Muse just have a Linux box in the cloud for anyone who just signs up currently. Like whether that's profitable or not profitable or whatever, you know, remains to be seen though. My point is, is that I think we're going to see a lot of different innovations come in. There's been some AI accessories, some AI little PDA handheld things. There's been AI pins earlier and some of these places have not done well. Some of them have gone bankrupt, some of them are whatever. But there's, the point is that there's a ton of different ways that these companies are quote unquote being attacked from a competitive standpoint where it's possible that we might start seeing, hey man, everyone has this, this like not a smart speaker. Actually there's a perfect example. Back in the day smart speakers weren't anywhere. Now they're kind of in a lot of people's houses, uh, quite a bit. Maybe you're going to have like a little smart document that has a little local model that runs just over your WiFi and does a lot of your local AI computing and then only calls upon the cloud, calls upon the big amount, the big powerful data centers when it needs that, if, and it intelligently decides when to do that. We saw something similar at a very rudimentary level. We saw something similar when might have been iOS 15 or something when Siri, a lot of Siri's computing went on device. Now obviously Siri is not an LLM or uh, I know that they have Apple intelligence

Speaker A: now and that.

Speaker B: But I'm talking back in the day. Siri was not in the same idea that it was not. Siri was not an LLM. It is not an AI in the current definition of what we're talking about today. My point is though is they brought that on device. It's entirely possible that there, it'll become a thing where uh, if you want this AI, here's a little smart speaker looking thing, you put it near your router and this thing will, will do a lot of your compute for you. Because even Sam Altman said There might be almost a utility charge for AI where it's pay as you go and it's kind of like your electrical bill or your water bill where it's like a uh, thing that we actually use as a utility. Well this would be a way that people would say okay, I'm just going to try to save some money here. And people do this already with standard utilities, low flow toilets and more energy efficient light bulbs, more energy efficient appliances. The list goes on and on. And so I can see them being hit in varying ways which will then to go back to your question, which will then naturally cause them to have to rethink how they price things.

Speaker A: Yeah, competition, you're 100% right. Any sort of competition is going to make it so that the prices have to go down. And uh, now that we know that they're able to get the compute down, I think it's, I think it's inevitable that they're going to have to compete with the deep seats of the world when they figure stuff out. If they figure stuff out, the GLMs, the open source models that come out that are able to compete with them on a direct level. Right. Because right now they are able to compete. But there's certain things that like just. It's not the same. It's not the same. I can't replicate an opus, especially the latest opus with any of these older open source models. At some point they might get to the point where they we can and that will change things quite a bit. And that, that in my opinion is also another huge risk for the bubble popping is if they aren't able to innovate. For example, like they aren't able to create these new devices that they could sell or the new workflows or the utility capabilities of AI and the open source cheaper models catch up, their margins are going to go down significantly and quickly. Right. On device models I think are still, I mean uh, there are some decent ones, let me be clear, like Quinn has a couple decent ones out there right now that are able to maybe compete with like a lower level Luna model or something like that. So there's certain things that you could definitely already pass off to those models but on the grand scale they're not there. And due to hardware, due to the current hardware situation where like the worldwide shortages of RAM and stuff like that, I think that almost moats the capabilities of local AI models for a little while because we're just not able to get significant enough hardware into consumers hands to create a local um, a good local Experience.

Speaker B: Yeah. But we are also burning the candle at both ends, though, because you have to think how many users are giving prompts that actually require a lot of computing power. Probably not a lot. Many of them are asking for help in daily things. They're. Or they're asking for things that are. That could have been asked to Google search even five or 10 years ago. Because people are not all in the tech space, they're not all engineering the next greatest app. They're. They're asking questions like, find me the best burger joint and organize it by entering a metric here. Uh, find me the best burger joint and compare all the Yelp and the Google Map reviews and give me a PDF. That's not a super difficult thing for it to do. My point is, is that if that's using, let's say, 10 compute units right now in a gear, that might use five compute units, and then in 10 years, it might use one compute unit. So then we're going to be using less computing to begin with, and that will. How much? How big of a percentage? I think it's a lot. How big of a percentage of the everyday users prompts, how much are the. Are going to fall under that what I'll call a mundane level. I've mentioned on this podcast before that computing has become mundane. Meaning back in the day, we had to have a video conference. We got to go to the conference room, we got to get WebEx fired up, we got to have all this stuff. They got to have a WebEx set up. It's going to be a whole thing. Now I could be driving down the highway and the person sitting beside me in the passenger seat could be doing a video conference from their phone. They're conferenced into four different countries. They're. They're doing stuff OTA, they're doing. They're using the 5G. They don't have a big boardroom. They don't need all that stuff. Look how mundane in terms of computing. Look how mundane it's become. Look how quick we can communicate now. Look how quick we can send photos and video and things like that. Now, my point there is, even when you and I are going to college, Mike, which realistically, wasn't that long ago, we used a lot of USB sticks. No, but it wasn't that long ago. In the end of the day here, we were using a lot of USB sticks. Cloud computing, cloud storage just kind of took over suddenly, and now it's just a part of everything. Oh, yeah, there's Steam cloud storage. Oh, there's Xbox cloud storage, there's Nintendo game saves, cloud storage, everything's in the cloud, don't worry about it. And then that's just mundane and we just move on.

Speaker A: I think it's been over 10 years since we've been, since we graduated college.

Speaker B: Right. But we're talking about this AI thing and it's only been a couple of years since it's really hit the mainstream is

Speaker A: my point.

Speaker B: And that's 20% of the time frame that you're talking about. Look how quickly, look how quickly the conversation changed. If there was no AI stuff right now we'd be talking about how to frigging code in PHP or something right now.

Speaker A: Yeah, I think if they could survive 10 years, they'll figure, they'll probably figure it out. I, I like my worry is that the bubble pops or the bubble could start popping within like a year and a half or two years, which is, I don't know, I feel like the timelines have now changed completely of how I evaluate anything lately. Because of

Speaker B: this, because of this initial offering?

Speaker A: No, no, not because of that. Just in general because of AI, like how AIs come onto the scene, how it's disrupted the economies and different perspectives like you know, the, the, the shortages of RAM and all that like all of that kind of contributes to me just like, I don't know, I can't predict anything in the next year, let alone two, let alone five. Like 10 years seems like a lifetime away at this point in terms of progress from all these different sectors. And I, I think I almost, I, I would 100% agree with you that in 10 years time they will have probably reduced the 10 to 1 compute units. I,

Speaker B: it's

Speaker A: going to become, it's

Speaker B: going to become mundane

Speaker A: as hell

Speaker B: to look up Google Maps stuff. It's going to be become.

Speaker A: Yeah,

Speaker B: look, look at even how we ingest media when we were in college. There were video stores on every corner from the beginning of college. It was approximately a four year period from the beginning of college to the end of college. The entire VHS video industry basically collapsed. Even the large, the large chains largely collapsed. People stopped renting and started streaming.

Speaker A: Uh,

Speaker B: and we had streaming years and years and years prior even. Right. But this is on the forefront. Money's being poured into this. Like back then streaming was held back by people not having five speed Internet and yada yada yada. Infrastructure gets better. And it's not just the infrastructure that gets better because people always want the infrastructure in, in the case of Internet to become more reliable. And faster, uh, and cheaper, of course. Right, of course. So that happened to some extent. Uh, at the very least, it's. I don't know if it's cheaper, but it's definitely more reliable and it's definitely faster. So therefore it's more accessible because it, uh, there are decent plans out there, even at slower speeds. And those slower speeds are way faster than what they were 10 years ago. The point of that being is no one thinks, oh, but, uh, I have faster Internet, so now I'm going to stream Netflix, which was new at the time. They think, I'm going to go do this, use the same websites that I did before, but they're going to be faster than ever. That's what the consumer thinks. But then the entrepreneurs think, oh, my God, I have this streaming platform. I can now get this into more homes than ever. And that completely tanks the industry. There's, it's too, there's too many parts to an economy and there's too much innovation. There's too many mistakes in order to reliably predict this stuff. But there are patterns, like things that were hard to compute yesterday are easier to compute today. That's something that, that almost always, if not, has always happened.

Speaker A: Yeah. So if we're, if we're looking at the patterns, then realistically what's going to happen is costs have gone up. Now as the competitors come into space, come into the space more, and stuff gets more commoditized. The cost will have to go down. As the competitors start buying each other up, similar to what we've seen with the streaming space and the TV space, they're going to start price fixing and setting costs higher. And so the costs will start going back up. So we're going to see this, like, wave of costs will go down. It'll get commoditized, and then they'll try to figure out ways, whether it be through, you know, conglomerates or whatever they want to do, to bring the costs back up, to get their margins higher, et cetera, et cetera, et cetera. That's, I mean, if we're looking historically probably the case, the of. Of how this is going to go, maybe we can take advantage of the time when the costs are down. Great. Now, you know, but we don't know you're right. Like, it's impossible to predict. I, uh, think tldr, probably the cost will go down at some point. Well,

Speaker B: you also have to consider the fact that if there is a bubble that pops, we have to look at the, the value to life that these Things have. But you also have to look at the goal that these, like we're talking largely is this a normal ipo? Maybe legally speaking. But think about

Speaker A: the company offering. It's not completely normal.

Speaker B: Is this company trying to just make m, you know, the greatest app ever and is trying to make the greatest app ever and get as many users as possible and yada yada. That's part of it. That's part of it for sure. They obviously they offer this to the, to the consumer, but there's also almost a research angle to these companies where they're trying to get to this super intelligence. They're trying to push the margin, they're trying to get to these different goals. And there's been tons of talk in those areas about what are they trying to do. They're trying to automate themselves. They're trying to push into this area. They're trying to push into that area. They're trying to. It's not all about profit. Maybe at the end of the day when the dust settles and it, maybe it will be all about profit, but right now it's about, I need to get the smartest model out there because my competitors are chasing me and you know, smarter, more capable, faster, etc. Etc. Etc. Is what's selling it currently.

Speaker A: I think that's it. Yeah. And I think there's so much unknown in that space that no matter how much you predict, they just don't know. Right. Like they don't know what the super intelligence would even bring. Like they're betting super intelligence is going to make the money. Will it?

Speaker B: Is it even going to happen?

Speaker A: Yeah. Is it even going to happen? Like they don't know. What if they, what if

Speaker B: they crack the code of the singularity?

Speaker A: Yeah,

Speaker B: if they crack the code of the singularity. Now the, now the business changes. Do we really care about silly little prompts?

Speaker A: Nope. Or maybe we do. It's a completely new thing and they don't have the answers to it. Neither do we. And like, it's a very different. I, I agree that this is a very different offering than a regular ipo. It's not

Speaker B: an ipo. On the, on the. This is the best movie app. Yeah. You know,

Speaker A: it's

Speaker B: like, okay, well,

Speaker A: and you're, you're. The, the difference here is that, like, there could be legislation that comes out that significantly destroys the value of the ipo. Let me be very clear. So I'm not. This is not financial advice. Don't go investing your money into anthropic just from listening to this episode. Do your own research. But like there's a lot of ex. External factors that can happen or even internal. They're retaining over 50% ownership even through the IPO. So there's no way for a, A board, I mean like to be formed from the IPO or like a uh, you know, an Elon Peter Thiel conglomerate try to take ownership of the company. Hostile

Speaker B: takeover is not possible due to them owning the majority of the company.

Speaker A: Correct? Yeah, they're, they've, they've established it so that the seven co founders own 50.5%.

Speaker B: Unless they somehow turn one of the people that are within that 50 some odd percent or what have you. There's

Speaker A: obviously, I understand they have, they have um, they have a fight. Like uh, they have a way to stop that anyway. So regardless, they're, they, they've made sure that there's no way for a hostile takeover to happen, at least in the legal terms. But that doesn't mean that the government can't take over. That doesn't mean that the legislation can't happen. That doesn't mean that internally they can be like, we've made super intelligence and it's evil. We're going to shut it down. Like that's part of why they're doing this. So that they can't be forced by customers, by shareholders to push out a model that has the potential to destroy everyone. At least that's what they're saying. But. And I kind of believe them to a certain degree. So like there's a lot of external factors, uh, other than just profits that are happening here. You're right, Matt. And it's, it's a very complicated process. At the very least it's very interesting. And I will have a link, we will have a link in the show notes to the S1, the filing that you can go look through yourself or prompt an AI to explain it to you in whatever way you want. And uh, yeah, it's, yeah, it's, it's, it's something that's out there now and we know that there is profit to be made. It's not all just rainbows and unicorns.

Speaker B: All right, well, I think that that is this edition of the web News. Unless you had anything else to add. Mike, I think you faded out there. I think it'll be corrected in the edited version, but you like disappeared a little bit. I think your Internet cut out. So I'm not sure if you were finished or hopefully I didn't cut you off there, but

Speaker A: I was absolutely finished. That was a natural fade out, but, yeah, uh, that's it for the web news, then.

Speaker B: It's a good cover up. I like that. A natural fade out.

Speaker A: Natural fade out. Thank you for listening to the web news. Uh, we'll see you next week. Goodbye.

Speaker B: Goodbye.