AI app builders are most useful when the prompt looks less like a wish and more like a lightweight spec. I have been testing NxCode with that mindset: use natural language, but keep engineering discipline. NxCode's documentation describes a Conductor + Virtuoso workflow. Conductor turns requirements into scoped tasks with acceptance criteria. Virtuoso executes the plan in a real environment, installs dependencies, runs builds, and iterates. That matters because a prototype is only useful when someone can actually click it and review the flow. The prompt structure I use Build a [type of app] for [user]. Core workflow: 1. User does [action]. 2. System stores [data]. 3. User sees [result]. Screens: - Dashboard: [must show] - Detail page: [must show] - Settings: [if needed] Acceptance criteria: - A user can complete [core action]. - Empty/loading/error states are visible. - Data persists after refresh. - UI should feel [style].…