Start Here: The AI Prototyping Workflow

The AI prototyping workflow is a structured, repeatable process for building working software prototypes using AI as your primary execution engine. Instead of learning to code or hiring developers, you follow a clear sequence of steps that takes you from raw idea to deployed prototype.

Each step produces a concrete output — a product brief, a design spec, a working codebase, a deployed URL. There's no hand-waving or "just figure it out" gaps. Every step tells you exactly what to do, what to feed the AI, and what to expect back.

This workflow is built for people who can describe what they want to build but don't have the technical skills — or the budget — to build it the traditional way. That includes founders validating ideas, product managers testing concepts, designers making their mockups real, and anyone tired of waiting for a dev team.

You don't need programming experience. You don't need to understand databases or deployment pipelines. The workflow abstracts those decisions into plain-language steps that you and the AI work through together.

The 12 guides cover the full lifecycle of prototype development: from defining your idea and structuring it for AI, through design and implementation, to testing with real users and deploying to the web. Each guide builds on the previous one.

By the end of the series, you'll have a working prototype deployed to a live URL — plus a repeatable process you can use for your next idea, and the one after that.

Start with Guide 1 and work through them in order. Each guide is designed to be completed in a single sitting (most take 30–60 minutes). Don't skip ahead — later guides depend on the outputs from earlier ones.

Have your AI tool of choice open alongside the guides. When a step says "prompt the AI with...", do it right then. The workflow is designed for active execution, not passive reading. You'll get the most value by building as you go.