Two Layers of Metrics
AI products need two layers of metrics: model metrics (accuracy, precision, recall, F1) and product metrics (user engagement, task completion, revenue impact). A model can be technically accurate but still fail as a product if users don't trust or use it.
Precision vs Recall
Precision measures how many of the positive predictions were correct. Recall measures how many of the actual positives were found. The trade-off depends on the cost of false positives vs false negatives in your specific product context.
Key Takeaway
Model accuracy alone doesn't make a successful AI product. Track both model performance and user-facing product metrics.