Design the moment when AI needs help

The main AI interaction is often easy to imagine: a user asks, the system responds, and the task moves forward. A useful product also has to handle the moments when that path breaks. The model may lack enough information, a service may be unavailable, or the result may need a specialist's judgment.

Identify these states while mapping the first user journey. Separate an empty response from an unsupported request and a temporary system failure. Each state needs a message that helps the user understand what happened and what they can do next.

Offer a recovery step that fits the cause. Missing context may call for one focused follow-up question. A service failure may allow a retry while preserving the user's work locally where appropriate. A request outside the product's scope should lead to a clear explanation and an alternative path.

When a person reviews an output, show the evidence needed for the review. A button labelled approve adds little value if the person cannot inspect the relevant sources or understand what will happen next. Make the consequences of approval visible before the action occurs.

Design for correction as well as acceptance. A user should be able to edit a draft, replace an incorrect extracted value, or flag an unsupported statement. Treat the correction as a product signal without collecting more sensitive information than the review process requires.

Test recovery with complete tasks. Ask someone to work through a missing document, a long response time, and an incorrect suggestion. Observe whether they know what to do and whether their work is preserved. Those observations often reveal gaps that a successful demo never exposes.

A product earns trust through predictable behavior when conditions are imperfect. Clear limits and useful recovery steps should be part of the initial scope.