Stanford ACE team unveils Sentry: failure tips in context hurt LLM agents, +39% gains
StanfordAILab · x · 2026-10-06
The Stanford ACE (Agentic Context Engineering) team found that keeping failure-recovery tips permanently in an LLM agent's context degrades performance even when nothing goes wrong. Their fix is Sentry, a test-time framework that stores failure knowledge outside the agent and only steps in when a failure actually occurs. Averages: +39% over their own ACE and +37% over the best runtime-intervention baseline. Paper and code are available.
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