How can developers evaluate whether an AI-generated design matches the product requirements?

How can developers evaluate whether an AI-generated design matches the product requirements?

Developers can evaluate an AI-generated design by tracing the approved user journeys through it and checking whether every required action and state is represented. Visual appeal is one consideration; the design also needs to support the product's behavior.

Compare the design with the release scope

Start with the PRD and list the actions each user role must complete. For a wedding organizer, this might include creating an event, assigning a task, and viewing invitation responses.

Locate each action in the design and inspect what happens next. Flag required actions that are missing and controls that imply unsupported features. A “Pay vendor” button creates an expectation even if it was added only for visual completeness.

Exercise realistic states and content

Review empty data, long labels, loading, validation errors, and failed saves. Check whether the user can recover without losing entered information. Inspect narrow and wide layouts rather than assuming a desktop mockup automatically works on a phone.

Consider role differences as well. A guest-facing screen should not expose organizer-only data. The design can communicate restrictions, while server code remains responsible for enforcing actual access.

Turn findings into specific changes

Write feedback as a requirement, an observed issue, and the expected improvement. For example: “The V1 task flow includes assignees, but task cards omit them. Add a readable assignee label to each card.”

Ask AI to help compare the brief with screenshots or inspect a running implementation when appropriate tools are available. Verify its findings yourself and review important flows with representative users. Keep a short record of accepted design changes so engineering, design, and future AI sessions all work from the same decisions.