The Data Flywheel

1. INTIntroduction: You Have the Data. You Don't Have a Loop.9
2. 01Collecting Data Is Not the Same as Building a Loop15
3. 02Event Design: What to Capture, and Why Most Teams Capture the Wrong Thing21
4. 03Review Queues: Who Actually Reads What the Model Got Wrong28
5. 04Labeling Rules and the Problem of Two Reviewers Who Disagree35
6. 05Signal From Noise: The Vanity-Metrics Trap41
7. 06Privacy Constraints: What You're Allowed to Keep, and For How Long47
8. 07Retraining Triggers vs. Prompt and Retrieval Updates53
9. 08Improvement Per Reviewed Interaction: The Only Metric That Matters59
10. 09Which Interactions Deserve Permanent Memory66
11. 10The Cold-Start Problem: Building a Loop Before You Have Data72
12. 11The Flywheel as a Habit, Not a Project78
13. ENDConclusion: The Loop Is a Discipline, Not a Dashboard84

The full chapters, illustrations, and reference material are included in the downloadable PDF.