Ship AI Features Like Software, Not Magic

Model capability is rising fast, but product quality still fails for ordinary engineering reasons: vague inputs, silent failures, no baseline, no rollback story.

I frame AI features with the same checklist as API endpoints: what is the input contract, what does success look like, what happens on timeout, and how do we know it got worse last week?

That means logs for prompts and retrieval paths (with privacy in mind), simple eval sets, and UI states for partial or low-confidence results.

Full-stack ownership matters here. The model is only one piece — schema design, caching, streaming UX, and clear error copy decide whether the feature feels reliable.

Magic is great for demos. Contracts and feedback loops are what survive production.