WeaveWithAI

WeaveWithAI turns an idea, written in plain words, into a working frontend whose code a team can keep. For now the generated apps are frontend only: their data lives in the browser behind a mock backend. AI app builders produce a demo fast, then leave days of cleanup: invented colors, hand-built components, code nobody wants to maintain. WeaveWithAI works like a product team. It plans first: user flows with every business rule, a design brief and a written spec for every screen, and a data contract whose operations map to the flow steps they serve. Each plan is a typed JSON artifact, checked by validators and reviewer agents over up to three rounds. Then Muse Code builds the app on a real design system. It looks up each component through a design-system MCP, and after every session the runner validates each file, checks every route in a real browser, and a UX reviewer reads a screenshot of every page. Findings are threads the coding agent can push back on. We ran three ideas end to end; each app, its brief and its full run data are at github.com/avcs06/WeaveWithAIExamples. Jaipur Studio Ceramics is a ceramics shop built from a 230-word brief in the owner's words, with a shop, cart, guest checkout and owner dashboard: 18 screens in 2 h 20 min for about $4.85. SoloStudio is a freelancer's workspace for clients, projects and bookings, with business rules such as slot availability: 14 screens in 1 h 40 min. DashForge, a personal dashboard builder, ran entirely on open-weight Muse Spark Open in 58 minutes. Across the three, checks and reviewers raised 219 issues and 175 were fixed and rechecked, and the final code has 0 design-system errors and 0 accessibility violations (axe, WCAG 2.2 AA). The apps use a mock backend in the browser for now. Built during the event: the whole agent. The design system's base components and its MCP existed before and were extended during it; the README lists what is what.