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This is a practical account of using AI coding agents to generate a working app from user stories and APIs, then refining it through designer review. The useful lessons are about limits: AI output can run end to end yet still miss visual consistency, usability, and polish, and round-tripping designs through tools like Figma MCP can lose interactions and animations. Teams evaluating AI-assisted front-end workflows should weigh those handoff costs against the speed gains.
Design-to-Code: Reimagine Handoff Workflow with AI – Rebuilding PubHub Part 3
How the PubHub team replaced the Figma handoff with an AI-built, designer-refined HTML prototype, and what worked and didn't along the way, so other teams can adapt it.
For a long time, our UI/UX workflow followed a familiar pattern: designers created screens in Figma, then developers translated those designs into code. Design and implementation happened in separate tools, with a handoff workflow in between. That process worked well when we had time to design and build each experience carefully. On the latest revamp of PubHub (a DevNet internal publication tool), we didn’t. We needed to move quickly, so we tried a different approach: asking AI to build the interface directly from our user stories and backend APIs. What followed was a series of experiments that changed not only our tools, but how designers and engineers worked together. This blog covers what we tried, what didn’t work, and the workflow we landed on, so other teams can adapt it. The…
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