Testing the Agent with Examples › What You've Built

You now have a practical framework for testing your AI agent. You can create test cases that cover all your agent's capabilities, run those tests systematically, and track performance over time. More importantly, you understand what makes a good test and how to interpret the results.

Testing finds bugs and reveals your agent's strengths and weaknesses, helping you decide where to improve. Every test run gives you data to work with, and that data guides your development.

In the next section, we'll look at how to create a feedback loop that uses these test results to continuously improve your agent. Testing measures performance. The feedback loop turns those measurements into action.