From Model Tests to Product Decisions

The Trap

Teams often run a large set of model experiments but still cannot answer one question: should this ship?

My Evaluation Frame

For each experiment, I record:

1. Input conditions.
2. Parameter changes.
3. Output quality metrics.
4. Failure examples that matter to users.

Decision Rule

I only promote a model change when it improves target quality and does not increase important failure modes.

Result

This keeps iteration speed high while avoiding "metric-only wins" that hurt real user outcomes.