Decoder with Nilay Patel
00:01:32 · S1, Nilay Patel
[00:01:32] S1: Support for the show comes from CrowdStrike. It's not a huge stretch to say that AI is the next major computing platform. Every platform shift changes the way we build software, and it changes security too. CrowdStrike is defining cybersecurity in the AI era with AI Detection and Response, or AIDR, a solution for seeing, monitoring, and securing AI across the enterprise. Learn more about how leading companies are turning to CrowdStrike to secure AI and secure their business at crowdstrike.com/decoder. [00:02:09] S2: Hello and welcome to Decoder. I'm Nilay Patel, editor in chief of The Verge and Decoder is my show about big ideas and other problems. Today I'm joined by Joey Brookhart, an analyst at the chip and AI research firm SemiAnalysis. Helped me dig into the story inside the numbers of the Anthropic IPO filing, a document known as an s one. Anthropic just filed its s one to go public on the Nasdaq stock exchange and it could start trading as soon as next month at a valuation of anywhere between 1.5 to $2,000,000,000,000 immediately making it one of the most valuable companies on the planet. But the price tag really isn't the whole story here. The S1 published earlier this week is hundreds upon hundreds of pages filled with details that finally paint a picture of the economics of a front year AI lab. And as you might imagine, that picture is both really complicated and built on a series of very, very ambitious assumptions about the future and what AI will do to it. So I wanted to have Joey on the show to help break down
00:02:09 · Nilay Patel, S3
[00:02:09] S2: Hello and welcome to Decoder. I'm Nilay Patel, editor in chief of The Verge and Decoder is my show about big ideas and other problems. Today I'm joined by Joey Brookhart, an analyst at the chip and AI research firm SemiAnalysis. Helped me dig into the story inside the numbers of the Anthropic IPO filing, a document known as an s one. Anthropic just filed its s one to go public on the Nasdaq stock exchange and it could start trading as soon as next month at a valuation of anywhere between 1.5 to $2,000,000,000,000 immediately making it one of the most valuable companies on the planet. But the price tag really isn't the whole story here. The S1 published earlier this week is hundreds upon hundreds of pages filled with details that finally paint a picture of the economics of a front year AI lab. And as you might imagine, that picture is both really complicated and built on a series of very, very ambitious assumptions about the future and what AI will do to it. So I wanted to have Joey on the show to help break down [00:02:57] S3: what this document really tells us,
00:02:57 · S3, Nilay Patel, Joey Brookhart
[00:02:57] S3: what this document really tells us, [00:02:59] S2: both about Anthropic's finances and the broader AI economy. Joey and his colleagues at SemiAnalysis actually built a model of Anthropic's finances from the outside back in July. So he's been waiting for the s one about as eagerly as anyone. And I was excited to hear his take on what we've learned and importantly, what we still don't know. Before we get going, do me a favor and subscribe to Decoder on YouTube where we put out new episodes every Monday and Thursday. Okay. SemiAnalysis Joey Brookhart on the Anthropic s one and the costs and risks of building Frontier AI. Here we go. Joey Brookhart, you're an analyst at SemiAnalysis. You're also co lead the tokenomics model, which is gonna come up a lot in this episode. Welcome to Decoder. [00:03:32] S4: Yeah. Thanks so much, Nilay. [00:03:33] S2: I am very excited to talk to you. We're talking just a couple days after the big Anthropic s one was filed. It's our first look inside of the finances of one of the leading frontier models. What's your take? What's your what's your read into it?
00:03:33 · Nilay Patel, Joey Brookhart
[00:03:33] S2: I am very excited to talk to you. We're talking just a couple days after the big Anthropic s one was filed. It's our first look inside of the finances of one of the leading frontier models. What's your take? What's your what's your read into it? [00:03:44] S4: It was an awesome S1. I think, you know, it's been a rough three weeks since the Investor Day. I think, you know, some people were somewhat disappointed in the September ARR numbers, but what we saw here was a company that has capital efficiently scaled to an amazing level, trillion plus valuation, know, 70,000,000,000 plus of ARR in very short amount of time. And gross margins, compute margins, free cash flow, everything is what you'd want to see. So I don't think there was much to nitpick in this filing. It's the reason you've seen in the last two days. I think a lot of the Semi Connector Complex and Neo Clouds and compute stocks really rally again. [00:04:19] S2: I'm actually... It's funny, I don't think I can nitpick the S1 itself. I want to get into some of the details because there's a lot of numbers in there that are worth thinking about. I actually just want to start a really big picture. I look at Anthropic and where it could go. I look at Dario saying that he can see his way to a trillion dollars in revenue. Where does that money come from? Because so much of these businesses are about eating every other business and it feels like somewhere someone else has to make some money to pay Anthropic to generate these revenues and I haven't actually seen that laid out very clearly.
00:04:51 · Joey Brookhart
[00:04:51] S4: It's so interesting I think today because even though the scale were at you know 120,000,000,000 of ARR between the two leading labs, it's still an extremely narrow market. The top 1% of customers are the one that are spending you know 100,050 thousand per employee. Your broader Fortune 500 Global two thousand, who typically has a lot of IT spend, isn't spending much, and then two, lot of the spending, especially at Anthropic, is coding specific. So we're kind of in, it's almost a single vertical company, and then we look in the future in a '27, you think of just this broader adoption in white collar work. This typical enterprise Q4 budgeting season, we actually haven't gone through with one of these labs yet in any meaningful way because ARR didn't really start to accelerate till the beginning of the year. We think of other cases like cyber, where that can be similar to coding, where these are 8 figure plus contracts with leading enterprises that can scale very quickly due to all the cybersecurity incidents we're seeing. And then I think you get to other verticals like bio, and then to get to a trillion, I think we do have to move some of that white collar work and where it's more of AI's augmentation to labor saving or replacement in some areas. And I think you look at things like Microsoft's offerings to employees as you know, maybe down the line at some point, but you know, there's no wealth of other verticals that they can get into and really start to move the needle.
00:06:11 · Nilay Patel
[00:06:11] S2: This to me is the single biggest question I have, not just about the S1 but the entire industry. I would understand that if there are one or two leading labs, right? There's two big companies, they've got a technology that can automate a whole bunch of things. We will see how well that automation goes sector by sector. But there's not just two leading labs. There's quite a few of them. There's open weight models. I've heard from a lot of CEOs who are very nervous about giving all their data to an open air Anthropic and they would like to run some things on prem. There's like law firms running on prem AI now, is the funniest turn in in maybe all of history. How do you see that playing out? Because so much the pressure on this S1 was the numbers inside themselves which I want to talk about, but then there's the external pressure of well you've got to grow and it growth is not as short. So how do you see all of that playing out?