Building AI features people can understand and trust
A practical framework for deciding where AI belongs in a product and how to preserve user control.
AI is most valuable when it reduces effort without reducing agency. A user should know when a system is making an inference, what information shaped the result, and how to correct it.
Start with the user decision
Before choosing a model, define the decision the feature helps someone make. A narrow, well-explained suggestion is often more useful than a broad assistant with an unclear role.
Design for uncertainty
Model output is probabilistic. Previews, sources, editable drafts, and confirmation before consequential actions make that uncertainty manageable.
Keep a dependable path
When an AI service is slow or unavailable, the core product should remain useful. Graceful fallbacks are part of the product architecture, not an afterthought.