Weco ran an AI agent rewriting another agent's harness for 8 days — what the gains actually prove
Machine Learning Street Talk · youtube · 2026-09-27
Machine Learning Street Talk hosts Weco co-founder Zhengyao Jiang to dissect the AIDE² experiment: an AI coding agent spent eight days rewriting another agent's harness — code, prompts, and tools — while the underlying LLM stayed fixed, reportedly beating two years of human engineering.
Key threads:
- Analysis of AIDE 85's generated "useful spaghetti code" and held-out evaluation design
- Weco's four levels of recursive self-improvement, compared with AlphaEvolve and the Darwin Gödel Machine
- Reward hacking: how hard it is to separate real discoveries from gaming the reward function
- The stated limits: the experiment did not establish the system became a better improver
- Closing on open-ended search, human-designed primitives, and Parameter Golf — where useful ideas come from when the agent searches inside a human-designed space
A serious, restrained conversation on whether recursive self-improvement has actually begun.
Related event: Weco's eight-day AI self-improvement experiment fuels RSI debate(4 posts)→
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