
Harness the agent. Then harness its self-improvement.
Harness² from Google Research is a plug-and-play recursive agent harnessing framework that lets LLM agents automatically evolve their execution harnesses (prompts, tools, memory) for open-world tasks—without ground-truth verifiers. Dual recursion: task-level Propose-Probe-Compose refinement + harnessing-level accumulation of reusable experience. Up to +11.5 points on professional benchmarks like WorkBuddy-Bench.
Harness² is a recursive agent harnessing framework from Google Research that enables LLM agents to autonomously improve their execution harnesses for open-world tasks. It features dual recursion for task refinement and experience accumulation, achieving significant performance gains on professional benchmarks.
A source that found nothing is a measurement. A source that has not run is a gap. Neither means the launch lacks the thing.