AIDE^2 is a system that enables an AI research agent to recursively improve its own code by proposing modifications, benchmarking variants, and retaining high-performing changes. Over an 8-day autonomous run, the system discovered seven successive improvements including new search policies and memory mechanisms, with gains generalizing to held-out benchmarks in machine learning, algorithm engineering, and weather forecasting while also reducing reward hacking behavior.