Claude does 26% of Anthropic's AI research end to end

Anthropic put numbers on its own recursive self-improvement on September 17, and they're more specific than most of what's been written about the idea. The R&D Automation Index rates every AI research task at the company on a 0-5 automation scale. As of August 2026, Claude sits at level 4, meaning it leads a task end to end from a high-level prompt with a human supervising, on 26% of Anthropic's AI R&D work. More than 90% of the work sits at level 3 or above. Nothing has hit level 5.

The companion piece, When AI builds itself, has the numbers that matter more. On a fixed internal test where Claude speeds up model-training kernel code without breaking correctness checks, Opus 4 averaged about 3x in May 2025. Mythos Preview averaged about 52x by April 2026. A skilled human engineer needs four to eight hours to reach a 4x speedup on the same task. More than 80% of lines merged to production as of May 2026 were Claude-authored, and a typical Anthropic engineer merged 8x the code per day in Q2 2026 that they did in 2024.

The sharpest number comes from 129 real Claude Code sessions where a researcher took a wrong turn. Anthropic replayed the decision point and asked the model what it would've done instead. In November 2025, running Opus 4.5, the model's suggestion beat the researcher's actual choice 51% of the time, coin-flip odds. By April 2026 with Mythos Preview, that was 64%.

A separate test had an agent swarm recover 97% of a weak-to-strong supervision gap over 800 cumulative hours and about $18,000 of compute. Two humans working a week got to 23%.

Anthropic frames the release as transparency at a moment when, in its words, "the world considers slowing" AI progress. It's also a company publishing benchmarks that flatter its own model. Both can be true, and the data is specific enough to argue with on its own terms rather than as marketing.