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LangChain Rubrics Make Agent Evals Part of the Runtime
LangChain's rubrics for Deep Agents point at a practical agent pattern: self-correction works only when rubrics are versioned, executable, and sampled against human review.
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Salesforce's StateAct paper argues that long-horizon computer-use agents should inspect files, DOM, and saved outputs directly instead of treating screenshots as the whole world.

LangChain's rubrics for Deep Agents point at a practical agent pattern: self-correction works only when rubrics are versioned, executable, and sampled against human review.
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