The regression safety net — evaluation in CI/CD

Lesson 2.4 is the final lesson of Week 2. This week has been about building instrumentation: learning what data to capture so an AI system can be evaluated. The what-to-log and where-the-checkpoints-are questions are answered. Now the question becomes: what to actually DO with all that data. This lesson closes the loop. The instrumentation exists. Now it gets used to catch regressions before they hit production. Not after. Before. The concept is a regression safety net. It consists of three things. A living collection of test cases that represent known failure modes. Threshold-based gates that distinguish real breakage from random noise. And a CI workflow that blocks deployment automatically when something breaks. That last part is the key. Not "alerts the team." Not "sends a Slack message." Blocks the deploy. Automatically. No human in the loop at the gate. By the end of this lesson, a 20-case regression suite that actually stops bad deploys (not just logs them) will be in place.