Banger paper from Google DeepMind on co-evolving an agent's harness and its weights. (bookmark it) If you already log your harness changes and results, those logs can become training data for the model running inside the harness. This is a nice paper from Google showing how to do this co-evolution. Specifically, they propose Evo2, a framework for weight-harness co-evolution. How it works: One policy plays two roles. As a Proposer, it writes edits to its own harness, and as a Reflector, it…