Checklist before you scale AI features
Before you spend more on AI, make sure you can tell whether it is working—and stop it quickly if it is not.
- Test cases you keep — a fixed set of questions and the answers you expect, rerun after every change.
- Logs you can read — record what the AI did, how long it took, and what data it used.
- Human spot-checks — someone reviews a sample of real outputs every week.
- Cost limits — budgets per customer or feature so bills do not surprise you.
- A way to turn it off — switches to roll back to a previous version without redeploying everything.
We build these steps into AI projects from the start—not as a cleanup task at the end.
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