Practice — CI/CD for ML & Data Code (5 questions)

A data scientist opens a PR that changes a single constant in the training config: TRAINING_WINDOW_DAYS = 90 becomes TRAINING_WINDOW_DAYS = 180. The repo's CI runs linting and unit tests, both pass, and a reviewer approves the PR within a few minutes because "it's a one-line change." It merges and the nightly training job picks it up.

1. Explain why "it's a one-line change" is a misleading way to reason about the risk of this PR, using the "artifact is model + data + code" mental model.
2. Design the CI checks that should have run on this specific PR before merge, and explain what each one is trying to catch.
3. Suppose the model gate you designed shows the challenger's aggregate AUC is unchanged but the tenure < 30 days slice regresses by 3 points. Should this PR still merge? Justify your answer.