Module · Intermediate
Quality, evaluation and observability
How to test and evaluate agents, which metrics matter, how to log, trace and monitor in production, how to improve from real conversations, and how to A/B test prompts and models.
You cannot improve what you cannot measure. This module turns it seems to work into evidence.
- 1 Testing and evaluating agents (evals) Build repeatable tests that show whether an agent reaches the right outcome, follows its rules and keeps working after changes.
- 2 Metrics: accuracy, latency, cost, satisfaction Measure whether an agent solves the right problem at an acceptable speed and cost while giving people a useful experience.
- 3 Logs, traces and monitoring Follow an agent request from question to outcome, record useful evidence and investigate problems without collecting unnecessary private data.
- 4 Continuous improvement from real conversations Use real conversations to find root causes, make focused corrections and verify that each release improves the agent without breaking other work.
- 5 A/B testing prompts and models Compare two agent variants fairly, interpret uncertain results and roll out a change without mistaking chance or biased traffic for improvement.