Recursive self-improvement in 2026: how far has AI building AI actually gone?
A lengthy Chinese feature surveys the state of recursive self-improvement (RSI) in 2026: Anthropic says Claude "leads" 26% of its R&D work and wrote over 80% of merged code, OpenAI says its "intern-level" AI research assistant arrived on schedule with roughly 3.1 "agent workdays" per human researcher day, and Zhipu and MiniMax describe self-improvement loops around inference infrastructure and scaffolds. It also offers counter-evidence: a Princeton "shadow evaluation" in which Claude failed to produce a publishable paper, and Weco AI's AIDE², which claims level-1 "net positive" RSI but did not pass its own level-2 "ignition" test. The piece cites Mikhail Burtsev's R_AI "recursive reproduction number" to argue the signal to watch is whether each research-capability gain makes the next gain easier.
If the AI-improves-AI loop closes, frontier progress would stop being limited by human researcher capacity — which is why labs are now publishing internal automation metrics even as calls to pace the frontier grow louder.