Define useful before building AI.

Collect representative examples of the task you want to improve. Include ambiguous cases and situations where the system should ask for help.

Define the outcomes your team will accept, then evaluate changes against those examples. Keep human review where errors carry meaningful consequences.

Treat the first version as a learning tool. The aim is a useful feature with known limits and a way to measure whether it improves.