Test Complex Interactions Earlier with AI Prototyping

Megan Chan of Nielsen Norman Group shows designers using AI tools to test complex interfaces with users before engineers build them, and warns that a polished prototype is not finished.

Interfaces such as filters, dashboards and chat assistants have many possible states, so designers used to test only a few expected paths before engineers built the real product. Megan Chan of Nielsen Norman Group, a user-experience research firm, describes AI tools that now let designers build a working prototype in a day and test it with users. Her examples come from designers at Ramp, whose product manages company expenses, and from researchers at Purdue University.

• At Ramp, senior product designer Pavan Garidipuri used the AI coding tool Cursor to prototype an expense-policy editor that users change through chat. Test participants used the prototype with their own anonymised data and found that its display of edits was confusing.
• Researchers at Purdue University tested static wireframes of a filter tool for traffic engineers, then an interactive version built with AI tools. Participants gave more specific feedback on the interactive version, though the study was not a controlled experiment.
• Chan says the designer must still make the design decisions, including layout and error states, and write them into the prompt. Where the designer leaves gaps, the tool fills them without attention to detail.
• A polished prototype prompts people to ask whether it can ship as it is. Chan recommends that someone with strong design knowledge reviews it before it goes to production.

A team that shows a realistic prototype outside the design group can state at the same time what the prototype has not yet been checked for. This is an inference and is not the author's claim.

Derived by Working Surface from the article. Source line: This looks great, can we just ship this?

16 September 2026: when AI helps produce work, a person still checks it before others rely on it.