A wireframe may look like a simple picture, but it hides dozens of decisions about behavior, validation, data, APIs, error states, and user expectations. Asking AI to “build this screen” skips those decisions and usually produces a convincing interface with an incomplete specification underneath it.

In this fast-paced session, I’ll start with only a wireframe image and use GitHub Copilot to uncover the specification hidden inside it. We’ll turn visual elements into user stories, generate testable acceptance criteria, identify assumptions, and surface unanswered questions before writing code.

Next, we’ll map each control to domain logic and typed API contracts, then scaffold the feature as a set of focused Blazor components. Copilot will help generate the implementation and tests, but we’ll review every decision, resolve ambiguity, and preserve existing business rules where the wireframe represents a modernized legacy workflow.

Finally, we’ll validate the finished feature against the original wireframe and acceptance criteria. You’ll see a repeatable path from an ambiguous visual artifact to working, reviewable, and testable software.

Takeaways
- Turn wireframes into testable requirements.
- Map UI controls to domain logic and APIs.
- Validate the feature against the original design.