For the better part of the last two years, I have been tracking what appeared to be a reasonably predictable pattern in AI development: a doubling of capability roughly every 3.5 months. That figure came from METR's time horizon benchmarks — measurements of how long an AI agent can work autonomously on a task before failing. Early 2024 through early 2026, the data held with uncomfortable consistency. If you plotted it, the curve bent upward with almost mechanical precision.

I say "appeared to be predictable" because that framing is now obsolete.

The variable that breaks every forecast model is Recursive Self-Improvement — the condition in which AI systems are no longer just tools that humans use to build AI, but active participants in building themselves. We crossed that threshold. The question of when is already behind us. The question now is what happens when a system that rewrites its own code, runs its own experiments, and optimizes its own training recipes starts doing so faster than any human team could direct it.

There is no clean answer. That is precisely the point.

What Has Actually Changed

Let me be specific, because vague gestures toward "exponential growth" have become their own form of intellectual laziness.

As of May 2026, Anthropic confirmed that more than 80 percent of the code merged into its own production systems was written by Claude — its own AI. Not assisted by Claude. Written by Claude. The company's own engineers have described the shift as moving from doing work to managing a system that does the work. One Anthropic engineer publicly stated that 100 percent of his personal code output was AI-generated, with 22 pull requests shipped in a single day.