# The five-phase system for building real software with AI. > Context, Rules, Documentation, Verification, Feedback Loops — the five-phase system that turns AI from a slop machine into a tool that ships real software. The whole method, in plain terms. ## The five-phase system for building real software with AI. Not prompts. Not tricks. A method — five phases that turn AI from a slop machine into a tool that builds real software. Read this once. Then start. No prior code required. ## The skill isn't prompting. It's directing. Most people think building with AI is about finding the right prompt. It isn't. Prompts produce something that looks done and falls apart. AI builds real software only when you put a system around it — and stay in the driver's seat. That system is what you'll learn here. The AI is only as good as the person driving it. ## Five phases. In order. Every time. 01. **Context** — Before the AI builds anything, you give it the full picture — the goal, the user, the constraints, what already exists. Skip this and the AI guesses, and guessing is where most projects go wrong before they even start. 02. **Rules** — You set the standards the work has to follow — how things get built, named, structured, and kept safe. Without rules, the AI drifts: every session, it quietly does things a different way. 03. **Documentation** — You keep the project's memory — what was decided, why, and what's being worked on now. Without it, the AI forgets, and re-invents what you already solved. 04. **Verification** — You check the work the way a real user will — actually run it, actually test it, against a clear definition of “done.” Without verification, a demo that looks finished ships as a product that isn't. 05. **Feedback Loops** — You build the loops that catch problems early — so drift gets spotted, errors get traced, and every cycle makes the system better. Without them, the same bug ships twice. That's the method. Prompts are not enough. Systems are. ## You stop hoping. You start directing. With the method, building with AI stops being a gamble. You're not prompting and hoping — you're directing, the AI is building, and the work holds up because there's a system underneath it. You don't become an engineer. You become the person who can get the real thing built — software, a tool, an automation, whatever your work actually needs. That's the shift. ## Your path, start to finish. It starts free. - **Foundations** — the free course. Start from zero, understand the method, build your first small project. - **The Build Kit** — your free working starter, so your next project begins set up right. - **The Build Challenge** — your first real build: time-boxed, with a cohort. - **AI Code that Works Premium** — keep building, go deeper, with the people doing the same. You can go as far as you want. It starts free. Join the free course on Skool: https://www.skool.com/aicodethatworks/about ## The method, in plain terms. **What is the AI Code that Works method?** Five phases, in order, every time: Context, Rules, Documentation, Verification, Feedback Loops. Together they give the AI the structure to build real software instead of slop. **What are the five phases of building software with AI?** Context (give it the full picture), Rules (set the standards), Documentation (keep the memory), Verification (test like a real user), Feedback Loops (catch drift early). **Do I need to be a developer to use this method?** No. The method is designed for capable, non-technical people. It's about directing the AI well, not writing code yourself. **How is this different from just prompting?** Prompting produces output you can't reproduce or debug. The method puts a system around the AI so the work holds up in production — the place vibe coding always falls apart. **How long does it take to learn?** The free Foundations course walks the whole method in five short modules — and you build your first real thing in an afternoon. ## Next step Get the Build Kit — free: https://aicodethatworks.com/start --- Canonical: https://aicodethatworks.com/method This is the markdown view of the page. The full rendered version lives at the Canonical URL above.