Simon Willison — one of the most credible and consistent independent voices in AI infrastructure and tooling — published a piece on May 27, 2026, making a claim that would have sounded optimistic 18 months ago but now feels like describing observable reality: Anthropic and OpenAI have both definitively found product-market fit.

The post is worth reading carefully. Willison isn’t making a bullish prediction or a promotional argument. He’s doing what he does best: reasoning from data points he can actually observe, drawing careful inferences, and naming what’s happening.

The Evidence Willison Is Working From

Willison’s argument rests on several converging signals:

Anthropic’s financials: Anthropic is strongly rumored to be approaching its first profitable quarter. That’s a remarkable milestone for a company that was burning enormous capital on model training and infrastructure. Profitability — or near-profitability — at this stage means revenue is real, recurring, and growing faster than costs.

Enterprise budget shock: Stories are circulating of companies surprised at how expensive their LLM bills are becoming from usage by their staff. Willison cites reporting from The Information about Uber’s CTO discovering how much Claude Code usage was costing the company. Budget overruns from legitimate, valuable use of a product is a classic product-market fit signal — users are consuming more than they expected because the tool is genuinely useful.

The subscription math: Willison subscribes to both the Anthropic Max plan ($100/month) and the OpenAI Pro plan ($100/month). He ran the ccusage tool on his laptop to estimate what his actual usage would cost at API pricing — arriving at a figure around $2,180 per month. He’s getting roughly 10x value from his flat-rate subscription. When enterprise customers start doing that math at scale, they upgrade their plans and increase usage.

An inflection point around November 2025: Willison identifies something qualitative but important — that around late 2025, AI coding agents crossed a threshold from “interesting but unreliable” to “genuinely useful for real work.” That behavioral change in usage is what drives the revenue pattern he’s now observing.

What Product-Market Fit Actually Means Here

Willison’s framing is precise: this isn’t just about revenue growth. Product-market fit, as classically defined, is when a product so clearly addresses a real need that customers are upset when they can’t access it, usage grows organically, and retention is high. By that definition, the signals Willison is citing are telling.

Enterprise customers are now paying what would historically be API prices — a significant premium — for subscription access to coding agents. That’s not a trial behavior. That’s a “this tool is worth paying for at almost any reasonable price” behavior.

API revenue, notably, is becoming less important in the overall revenue mix for both companies. Direct subscription revenue from developers and enterprise teams is growing faster. That’s a structural shift — from “the labs make money when other companies build products” to “the labs make money when individuals and companies use their products directly.”

Why This Matters Beyond the Two Companies

Willison’s post isn’t really about Anthropic and OpenAI’s business health — it’s about what their business health implies for the rest of the ecosystem.

If the two leading AI labs have genuinely found product-market fit in 2026, several things follow:

  1. The agentic AI wave is real, not hype. Revenue from actual usage is the most honest signal available. Budget overruns caused by genuine utility are qualitatively different from adoption driven by curiosity or executive mandate.

  2. The infrastructure bet is validated. Every tool, platform, and framework being built to enable AI agents — MCP servers, agent runtimes, observability platforms, governance frameworks — is being built on top of demonstrated, paying demand.

  3. The competitive landscape will intensify. When a market is clearly real and growing, capital flows in. The managed runtime convergence we covered elsewhere this week is one expression of that; there will be more.

  4. Developer investment is rational. If you’re a developer or architect deciding whether to invest time in AI agent tooling, Willison’s argument provides a reasonable basis for confidence that the platform isn’t going away.

The Honest Uncertainty

Willison is careful not to overstate. He notes that “the AI failure stories around this are pretty thin” — meaning he’s not seeing the wave of high-profile enterprise failures that historically accompany oversold enterprise technology. But he also acknowledges that the labs are still spending enormous amounts, and that profitability depends on whether the trajectory continues.

Product-market fit doesn’t guarantee the companies will win long-term, doesn’t resolve competitive dynamics with each other, and doesn’t mean the technology will continue improving at the same rate. It means the demand is real and the business model is working. That’s a narrower — and more defensible — claim than many people make about AI.

Worth your time regardless of where you sit on the AI optimism spectrum. The post is grounded, honest about uncertainty, and based on actual data points rather than speculation.

Sources

  1. Simon Willison: “I think Anthropic and OpenAI have found product-market fit”
  2. TechCrunch: “Anthropic says it’s about to have its first profitable quarter”
  3. The Information: Uber CTO and Claude Code budget overruns
  4. Hacker News discussion: HN item #48296794

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