Using Multiple AI Agents to Review UI Fidelity to Custom Designs

📝 Originally published (in Japanese) at forge.workstyle.tech . 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. Reproduction of Oversights — If you missed a specific element in the mockup during implementation, you are likely to miss it again during review for the same reasons. Fixed Perspectives — Being alone can lead to cognitive bias; for example, you might focus too much on "are the colors correct?" while overlooking the "hierarchical structure of the layout." Even if you ask a single AI agent to "compare the mockup and the implementation," you will encounter similar issues, albeit to a lesser degree. A single response tends to lean toward one perspective; if you ask it to look at too many things at once, each individual check becomes shallow. The solution is to split the perspectives and assign them to multiple agents . Instead of asking one agent to look at everything, assign each agent a specialized role and have them run independently. Workflow: Paral