Evo-Harness Paper Finds Verifiers, Not Reflection, Drive Agent Improvement
solyarisoftware · x · 2026-08-26
The paper proposes Evo-Harness, studying how frozen agents improve by updating a structured harness. Key findings indicate that while the model remains static, compiling execution context into skills boosts performance. Crucially, self-reflection degrades results, while using unit tests as verifiers significantly improves the agent.
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