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LLM agents can improve their decision-making by learning from their own diagnosed failures, with first-proposal corrections boosting success rates by over 30 percentage points.
Translating learned strategic principles into an external runtime harness yields a 12-point performance boost over directly feeding those same principles into an agent's context window.
