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Demystifying Evaluations of AI Agents

Agent evaluations are more complex than traditional LLM tests because they involve multiple turns, tool usage, and state changes; the key is distinguishing between transcript (recorded interactions) and outcome (actual final state) to create meaningful assessments.

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Evaluating Deep Agents with LangSmith on AWS

AWS and LangChain present a new guide showing how developers can systematically evaluate and monitor AI agents, with LangSmith on AWS, Amazon Nova 2 Lite, and structured evaluation patterns significantly improving the reliability of complex multi-step agents from development through production.

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