5 questions to ask before building an AI feature

These days almost everyone wants to add "something with AI" to their product. In my experience building data-driven products, the most successful features start with a simple question: what problem are we solving?

1. What exactly is the user's problem?

If you can't describe the problem without the word "AI", you haven't found it yet.

2. Do we have enough of the right data?

A model is only as good as its data. Check quality, volume and ownership early.

3. What does "good enough" mean?

There is no 100% accuracy. Agree on a measurable bar with your team and stakeholders.

4. What happens when the model is wrong?

Designing the experience for errors matters as much as the model itself.

5. How will we learn and improve?

Build a feedback loop so the product keeps getting better after launch.