Agent Evaluation Readiness Checklist

📰 LangChain Blog

A practical checklist for agent evaluation, covering error analysis, dataset construction, and production readiness

intermediate Published 27 Mar 2026
Action Steps
  1. Manually review 20-50 real agent traces before building eval infrastructure
  2. Define unambiguous success criteria for a single task
  3. Separate capability evals from regression evals
  4. Assign eval ownership to a single domain expert
  5. Rule out infrastructure and data pipeline issues before blaming the agent
Who Needs to Know This

This checklist is beneficial for AI engineers, data scientists, and product managers working on agent development, as it provides a step-by-step guide for building, running, and shipping agent evaluations

Key Insight

💡 Start with simple evaluations that give signal and add complexity only when necessary

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