A churn model looks excellent in the notebook and mediocre in production. The model isn’t broken. The training table computed orders_7d with a rolling window over the full history, so some rows counted orders placed after the label date. The serving code, written later in another language, counts a calendar week instead of seven days. One feature, two definitions, and a quiet look into the future. Those are the two bugs a feature store exists to prevent: training-serving skew and label leakage.