Have you ever been hit by a wave of anxiety after implementing a UI based on a mockup? You might think, "I tried to build it as faithfully as possible, but is it really matching the design?" As the person doing the implementation, it is easy to overlook small compromises made during coding or details missed in the mockup. This is the inherent limitation of self-reviewing your own code.
When humans work together, having multiple people involved increases the number of perspectives. My approach—which I introduce in this article—is to replicate this by running multiple AI agents. By having several independent review agents evaluate how faithfully your implementation matches the mockup (in terms of layout structure, positioning, and component mapping), you can reinforce the single review with multi-angled verification.
Why "One" is Not Enough
Self-reviewing by the original implementer has structural weaknesses:
Confirmation Bias — Since you already have the memory of "how you built it," you tend to view the mockup in a way that justifies your own implementation.
