Continuous Feedback and Improvement › Continuous Feedback and Improvement

In the previous chapters, you learned how to set success criteria and test your agent with examples. But here's the truth: evaluation isn't something you do once and forget. The best AI agents get better over time because their developers treat evaluation as an ongoing conversation, not a final exam.

Think about how you improve at anything. You try something, see what works and what doesn't, adjust your approach, and try again. Your agent deserves the same treatment. In this chapter, we'll explore how to create a feedback loop that continuously improves your assistant based on real-world use.