Google Research has published a coding guide for RRSI, or Regularized Recursive Self-Improvement, a technique for building AI agents that can refine their own behavior. The guide is aimed at developers who want to implement self-improving systems without letting them drift into unsafe or inefficient territory.
The method relies on three main mechanisms. Noise bands add controlled randomness to exploration, cost rules constrain how much resources an agent can spend on improvement, and leakage screens filter out changes that would let internal logic or data escape unintended boundaries. Together, these are meant to keep recursive self-improvement both practical and safe.
Because the source is a single guide, there are no contrasting viewpoints to report. The article positions RRSI as a structured alternative to open-ended self-improvement, where agents are given explicit guardrails rather than unlimited freedom to rewrite themselves.