Self-improving harnesses are one of the most discussed ideas in AI right now.

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This work proposes a new harness, RuHarness, that beats the strongest harness-evolution baseline by 4.5 points on held-out tasks with Qwen3.5-35B-A3B, and by 5.3 points with GLM-4.7-Flash.

The work targets a gap in current methods. They evolve the harness but keep the criteria that guide each edit fixed, so the criteria stop matching the agent's weaknesses after a few rounds.

RuHarness evolves the rubric along with the harness. Each round, it finds behavioral criteria in the trajectories, re-scores them, and directs harness edits at the most relevant unresolved weakness. Criteria that stop firing go dormant and return if the weakness reappears.

If your harness evolution stops improving after a few rounds, update the critic too.

https://arxiv.org/abs/2610.36826

Chat with Paper: https://academy.dair.ai/papers/when-the-critic-falls-behind-co-evolving-rubrics-and-harnesses-for-continual-age-2610.36826