Why Good Models Fail After Deployment

Six months ago, your recommendation model looked perfect. It hit 95% accuracy on the test set, passed cross-validation with strong scores, and the A/B test showed a 3% lift in engagement. The team celebrated and deployed with confidence. Today, that model is failing. Click-through rates have declined steadily. Users are complaining. The monitoring dashboards show no errors or crashes, but something has broken. The model that performed so well during development is struggling in production, and the decline was unexpected.