Anthropic’s product-market fit
Anthropic raised another round, collecting $65bn at a $965bn valuation, and reported that earlier this month it passed $47bn ‘run-rate annualised revenue’ (i.e. previous 28 days multiplied by 13), up from $30bn in April and $9bn at the end of last year. OpenAI hasn’t given a public number recently (which speaks for itself) - apparently it recently passed $30bn, but note that Anthropic is giving these numbers gross, before payments to its inference partners, whereas OpenAI gives them net. A few people are still trying to persuade themselves that this revenue is all made-up, but that would be securities fraud, and we’ll get the audited GAAP numbers in the IPO filings soon enough.
A few observations - first, agentic coding really works and really has product-market fit: companies are willing to pay hundreds of thousands of dollars per programmer for this, and collectively tech companies are paying Anthropic 3-4bn a month. And this is only the first generalised big use-case (though even at the end of last year, before agentic coding started working, OpenAI and Anthropic were at a combined $30bn run-rate). Second, the revenue model, pricing, and margin structure for this is very far from being worked out yet. However, it is clear that inference itself has positive gross margins.
Also... $965bn is more than the total market cap at issue of every single venture-backed IPO in the USA from 1995 to 2000. LINK
Tokenmania
The other side of the agentic coding revenue surge is a lot of bill-shock, as CFOs everywhere get a nasty surprise in their latest Claude Code bill. Last month, Uber said it had already spent its entire 2026 budget (unsurprising given that would have been set in late 2025, before this worked), and now that’s a trend: Amazon pulled an internal leaderboard that drove more use, and the WSJ points to a lot of other companies cracking down. On the other hand, Salesforce increased its budget buy 10x. LINK, AMAZON
Back at Uber, the COO said on a podcast that while the spend is high, it’s not always as easy to point to specific gains, which speaks to a broader challenge in early deployment: it’s easier to say you’re using this a lot and love it that prove how many more features you’re shipping. LINK
More capex
Softbank announced a plan to spend ‘up to’ €75bn ($87bn) to build 5GW of AI data centres in France, leveraging ‘data sovereignty’ on one hand and France’s nuclear-generated electricity on the other. Of course, given that Softbank also announced ‘Project Stargate’ to build $500bn of infra with OpenAI at the beginning of last year and almost none of that seems to have happened, we should regard this with caution. LINK
Meanwhile, and perhaps more consequentially, Bloomberg reports that Bytedance is considering increasing its capex from $25bn last year to as much as $70bn in 2026 to invest in AI. Up until now, Chinese tech giants have been notable in their absence from the AI capex boom, partly because they can’t get enough Nvidia chips anyway, and hence the second penny to drop is that Bloomberg also says Bytedance is doing a server chip deal with Qualcomm. But, would that be covered by the same sanctions as Nvidia? LINK
Spending flow-throughs
Dell shares jumped 40% after it said its server revenue is booming: quarterly revenue for the segment was $16.1bn, up from $1.9bn a year ago, and it expects to sell $60bn of AI servers in the full year, up from a previous estimate of $50bn. LINK
Meanwhile, the SaaS apocalypse is getting some nuance. Earlier this year, the entire software market was radically re-rated, not because anyone seriously (or anyone serious) believes people will vibe-code their own Stripe or SAP, but because it’s obvious that AI will lead to a lot more competition, competition in new forms, new pricing and margin environments, and a lot of general swirl as everything recalibrates, and there’s no real way to be sure which companies will suffer. The other side of this, though, is that some companies will get a lot of new business from the change, and this week Snowflake’s stock went up by 36% (and it’s a $50bn company) on good numbers and a thesis that companies migrating to AI will use Snowflake to get there. LINK
Meta does enterprise?
Last quarter, Meta raised its CY2026 capex outlook from $115-135bn to $125-$145bn, which is well over 50% of expected revenue, and it’s the only one of the big four hyperscalers that doesn’t have any kind of cloud or enterprise business to load onto that (let alone the coding tools that are working so well at Anthropic). That might change: apparently now it’s setting up an Enterprise Solutions group. Easier said than done (just ask GCP, which has been in a distant third place in cloud despite pretty much inventing cloud) - enterprise infra is a very different business. LINK
Meanwhile, at the AGM this week Mark Zuckerberg said that if Meta finds it’s overspent and has excess capacity, it would be willing to resell in competition with AWS, Azure, and GCP. Yes, xAI is doing that now with Anthropic, but that’s because it screwed up its models: if, on the other hand, it turns out that AI in general doesn’t need this much capacity, then everyone else will be dumping their capacity onto the market too. LINK
Nvidia AI PCs
Axios says that Microsoft will have a second try at ‘AI PCs’ this week with ARM devices using an Nvidia chip. There’s a whole platform development story here (and recall that Microsoft first tried ARM over a decade ago with the original Surface), but the end-game is that if you can run a good-enough small model on the user’s compute, it doesn’t have marginal cost. We should expect Apple to spend a lot of time talking about this at WWDC on 8 June. LINK
Blue Origin blows up on the pad
Congratulations to Jeff Bezos on one of the coolest explosions ever. Every FX lab in the world has this as a reference. (Seriously - bad luck, but no-one was hurt, and this is how we build stuff.) LINK, ANALYSIS
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