Self-Harness automates agent harness tuning, but evaluation gates the gains
Shanghai Artificial Intelligence Laboratory researchers introduced Self-Harness, a framework that lets LLM-based agents rewrite their own operating rules by mining execution traces for failure patterns and proposing targeted harness edits. On Terminal-Bench-2.0, three model configurations improved 33 to 60 percent relative to baseline, with the