Anthropic's Historic IPO Has Arrived | S1 Breakdown

00:12:07 · S1Play from here

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00:14:20 · S1Play from here

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00:14:48 · CJ GustafsonPlay from here

[00:14:48] S0: How are they making money? They're making a lot of this money. There are four model classes. They get the mythos, mythos, mythos, including fable, opus, sonnet, and haiku. Each one sits at a different point on what they call... I love I love this. The capability cost speed curve. Customers use the smart expensive ones for coding and agents and route these simple shit to the cheap fast ones. I forgot my password. I forgot my login. They charge two ways. The first is pay for intelligence. Customers pay for usage metered in tokens and price by model. This was 80% of revenue in the first half of twenty twenty six. And subscriptions, Clouds apps on a monthly or annual plan for enterprise and prosumers like myself with terms of twelve months or less, this was the other 20%. The two models feed each other because when a subscriber runs out of the usage in their tier, they can move up a tier or buy more intelligence directly, which turns that subscription revenue into usage revenue. And that's why the usage revenue is far outpacing the subscription revenue. A growing number of enterprises also sign non cancelable annual or multi year contracts with minimum spend commitments in exchange for a committed price list. So like to lock in with certainty what you're gonna pay. These mostly show up as usage revenue too. So they sell it through what they call surfaces. Claude platform, the building blocks or developers put Claude inside their own products. Claude code, the coding agent, Claude co work, the knowledge work agent, which they started merging with Claude dot ai in September. Let's talk about distribution, which they called the fusion. Much of the diffusion of Claude has been organic because prosumers use it in their own personal life and then eventually they bring it to their company life. By the time the sales team from Claude is there, they're already using it in some way, shape, or form. They're looking to get better pricing. The biggest benefit to the go to market is that it's available through all three major cloud providers. So a customer can buy inside the AWS, Google Cloud, or Azure relationship they already have. And Anthropic keeps the contract with the customer and pays each cloud a fee, a vig, a rake. And then there's the old fashioned channel model via consultants, the Accenture's, the Deloitte's, the KPMG's, and PWC's of the world.

00:17:05 · CJ GustafsonPlay from here

They all have these cloud practices. They will make a ton of money in this boom just implementing it. And then Salesforce and Snowflake embedded into their platforms as well. So a lot of ways to buy. They also see the private equity angle. PE's eating everything, baby. The problem is how you get it into mid sized companies who aren't that tech forward. So they launched Ode with Anthropic, that's o d e, an AI services company built with PE firms to deploy Claude across their portfolio. So sales, marketing, and partnerships came to 19% of that massive revenue in the first half, and most of that was fees to channel partners. They don't call it ARR. So a few weeks ago, I wrote, there are no new crimes, just new ways to calculate revenue. Ain't that true? Well, after Higgs Field CEO was on twenty minute VC, and he said that they calculated annualized revenue, quote, the same way OpenAI and Anthropic do by taking the last twenty eight days of revenue and multiplying by 13. Anthropic doesn't call it ARR. They call it run rate revenue. Quote, the sum of one, our consumption based fees during the trailing twenty eight period ended on the measurement date multiplied by 13. So I think that's like 364. They give you one day back. How generous. And two, our aggregate monthly subscription fees as of the measurement date multiplied by 12. Like I said, last twenty eight days times 13 plus monthly subscription times 12. But this is the kicker. They don't give you a number. They just define it. That is a first for me to have this definition and then not give us a number. However, they've been telling everybody and their mother for months. So Dario said on stage in April that they'd hit a 30,000,000,000 run rate, then the series h announcement in May said 47,000,000,000, and Bloomberg reported 65,000,000,000 at the end of July, up from about 9,000,000,000 at the end of twenty twenty five. When the 30,000,000,000 number came out, OpenAI argued, hey, hey, hey, the same, overstated by about 8,000,000,000, and the filing shows why they might say that and be right, because Anthropic books cloud marketplace sales at the gross larger amount before the cloud providers take their cut. As for year end, the Financial Times reported investors expect run rate to land somewhere between 100,000,000,000 and 120,000,000,000 at the end of the year.

00:19:19 · CJ GustafsonPlay from here

So keep that in mind for the valuation portion. If I'm being honest, I like the old school version of run rate revenue better where you take your last quarter and multiply it by four because you have three months in there to smooth any sort of seasonality out. So if you do that with q two, you get around 46,000,000,000, which is right in line with that 47,000,000,000 they announced in May, and the roughly 16,700,000,000 in q three. I can back into that. I'll show you in a minute how I do the wizardry, do the math in here. And if you multiply that out, you get the 67,000,000,000 or close to the 65,000,000,000 at Bloomberg reported in July. Net net, I think gap revenue is a much more honest view of what they can actually do than this run rate kabuki. Usage revenue moves around a lot. For example, during the two weeks ended January 2, they said total customer spend dropped about 20% compared to the two weeks before because developer commits slow down during holidays and all the retail companies do code freezes. Quote, run rate revenue is not a substitute for revenue prepared in accordance with GAAP or a forecast of revenue. I feel like they listened to me. Did I influence them? They also say recent run rate growth was driven in part by rapid initial customer adoption and expansion often characteristic of an early adoption period, and that they expect the growth rate to decline possibly significantly and more rapidly than we anticipate. I still bet dollars to donuts that we start hearing a lot more about ninety day averages when that starts to slow down. You can go back and forth on revenue growth expectations, but you can't argue with the revenue efficiency. These are the highest efficiency numbers I have ever seen for a company. Net revenue retention is about 900%, meaning customers who were spending a year ago are now spending about nine times as much. Snowflake was at 158% when it filed, and GitLab was at 152. People thought that those numbers were crazy. This is this is multiples more. Some of this is admittedly a feature. It's not a bug because of their pricing model. So AI is pretty much synonymous with usage based pricing at this point, and 80% of Anthropic's revenue is consumption. So revenue go up as long as customers use more. Well, I don't think this figure will stay at 900% forever even if it is cut to 300% that would be s tier.

00:21:35 · CJ GustafsonPlay from here

Also, it's crazy how they can both have 900% ndr and like also be a commodity product with little to no switching costs. How how can both of those things be true? Oh, and revenue per employee, 6,800,000. I would love to have that in my company, up from 1,400,000 a year ago. My rule of thumb for a public company is 450 k to 500 k is the median. TTM revenue here grew about 1200% over the past year, while headcount growth grew about a 170% from roughly 940 to the 5,300 today. I know I just said that everyone was talking about revenue too much, you can kinda back into the revenue as of September, which they don't disclose using the revenue per employee in the employee count. They say TTM revenue per employee was over 6,600,000 as of September 30. It was approximately 5,300 people working there, which puts trailing twelve month revenue at roughly 35,000,000,000. So if you subtract the three quarters, we do have q four twenty five through q two twenty six, about 18,300,000,000 comes out, and q three twenty six comes out to roughly 16,700,000,000 up from 11,600,000,000 in q two. I love math. I wanna take you through four drivers because they interestingly have four different time horizons. Okay. So the filing lays out the company's financial model. It's important to outline these four. So one, adoption of Claude. Each new model version brings in new customers and pushes existing ones into new workflows and revenue growth. Two, compute efficiency. More intelligence and more revenue out of every dollar of compute. Three, operating efficiency, talent density and efficient go to market in their own teams using cloud, which shows up in operating margin and revenue per employee. Fourth, compute investments, the big checks. So the first three have all been moving up very, very fast. But the fourth one that I mentioned, the compute investment that lags. So they say compute is procured and committed in advance and the expense is incurred as it is brought online and added to our fungible pool, often in large discrete steps. They typically commit to compute twelve to eighteen ish months before it's available. And once it comes online, the expense hits the p and l whether or not the revenue it's meant to support has shown up yet. So every time a big tranche lands, margins will take a step down and they tell us that directly.