Govern AI-Built Prototypes Before Adding Features

Henry Alfano pro California · 1H AGO

Let AI build your prototype, but don’t let your prototype own you. A working preview makes it tempting to keep asking for features. But the first screen tells you little about who controls the database, how the application is structured, or what the next prompt might change. I developed this workflow by putting my best-practices guides to work on a client project, then separating the reusable process from that project’s architecture. This workflow is for AI app-building platforms, often called vibe-coding platforms, where you describe an application and the platform generates and runs a working prototype. It focuses on keeping control of the code, repository, backend, and platform connections. It is not a general guide to coding agents or AI-assisted editors. Anyone who has watched a code generator slowly degrade a clean codebase knows why the starting conditions matter. Before asking for features, establish what you own, what the tool may change, and how you will check its work. Step-by-step: 1. Set ownership before the first build prompt. Decide what the application needs and who controls it. If it needs a new database or backend, provision it in an account you control before asking the builder to create the app. An existing API is another option, not a requirement; some prototypes need neither. Confirm the repository destination, integration permissions, and recovery access. Keep production behind a reviewed release process. 2. Give each tool readable rules. Establish one authoritative set of architecture, coding, and design standards. Identify which files each tool may change and which it may only read. Naming a rules file in a prompt does nothing if the tool cannot access it. Assign responsibility for data, authentication, application logic, deployment, and recovery. One person can hold several roles, but a UI task does not grant permission to redesign the backend. 3. Build the framework before the features. Use the opening prompt to establish the framework, runtime, routes, layout, and state ownership. Ask for empty page shells first. Check that navigation uses real routes and that shared elements have a defined home. Keep design values in one designated place. Any temporary authentication placeholder must be clearly labeled and isolated from protected data. Real users require real authentication and authorization. 4. Inspect and preserve the foundation. Read the generated files and inspect the running scaffold. Check for unrequested services, dependencies, and structural changes. A green build alone does not tell you whether the tool followed your instructions. Once accepted, protect the foundation files from routine UI prompts. Record the accepted commit and preserve a recovery copy beyond the integration’s ability to modify or delete. 5. Set up a prompt factory. A prompt factory is an assistant configured to turn a plain-language request into a bounded implementation prompt. Give it the project rules, file map, technical references, and current capabilities. It checks whether the requested behavior is supported before producing instructions. If something is missing, it prepares a prerequisite request for the responsible owner instead of inventing data or behavior to make the screen look finished. Each prompt names the tool, permitted files, protected files, applicable standards, relevant data and interfaces, exact change, what must be preserved, and observable checks. The factory prepares instructions; it does not approve architecture or release changes. 6. Build one governed feature. Where data is involved, establish correct data behavior first. Follow with a separate placement and styling task. Inspect the changes and test the affected behavior. Apply the One Fix Rule: one repair prompt, one attempt. If it fails, the generator is done with that file. Move the repair to manual maintenance rather than feeding another round of guesses into the codebase. After acceptance, save the next recovery point and update the working rules. Preserve the reason behind each rule so a later cleanup does not remove the safeguard. The point is to make the next feature less likely to undo the work you already accepted. Your database, where needed. Your code. Your standards. You control the tether. Part 2 will cover cutover: leaving the development platform with a controlled release, verification, and a recovery plan.