Harness² Explained: Self-Improving Agents Without Training

Harness² is a research framework from Google Cloud AI Research and Northwestern University that lets an AI agent rewrite its own harness (its prompts, skills, scripts, subagents and control-loop hooks) for every new task, without retraining the model. In this video I explain how it improves a harness with no answer key (Propose, Probe, Compose), why it has two levels of recursion with an experience library, what the results show against Claude Code and Codex, and where the approach breaks. Paper: https://arxiv.org/abs/2610.14224 Code: https://github.com/google-research/harness2 Project page: h