How we build evals for Deep Agents

The article discusses the process of building effective evaluations for Deep Agents, which involves directly measuring agent behavior that matters, sourcing relevant data, creating meaningful metrics, and conducting targeted experiments. By doing so, evaluations can shape agent behavior, making them more accurate and reliable over time.

⚡ Key Takeaways

• Effective agent evaluations should directly measure behavior that is relevant to the task or goal.
• Sourcing diverse and relevant data is crucial for creating meaningful metrics and experiments.
• Well-scoped and targeted experiments can help refine agent behavior and improve accuracy and reliability.

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