Most developers using AI start the same way: open a blank folder, paste their idea into a prompt, and let the AI go. Two weeks later, they’re untangling spaghetti code they barely understand. u/alfredowmm was one of them, until he reverse-engineered his own process and found a better way.
He’d just shipped steats.app, a food vendor app with two separate user flows, Stripe payment integration, and privacy and terms pages, all deployed to the web. Two weeks of work. Then he sat down and realized he could build the same thing in a single day.
The difference wasn’t a better model. It was a question asked before writing any code, and a folder structure that made everything after it faster.
The old way vs. the new way
Here’s how most AI-assisted builds go. You describe the full project in one shot. The AI fills in the gaps with assumptions. You discover the conflicts in week two, when they’re already baked into the codebase.
The problem isn’t the AI. It’s that nobody defines scope upfront. Nobody asks the hard clarifying questions before the first file gets created. A classic example: you build a checkout flow that assumes users are always logged in. Three days later you realize guests need to check out too, and half your state management has to be rebuilt from scratch. You build fast in the wrong direction, then you backtrack slowly.
The author’s new approach flips this entirely.
Step one: junior engineer mode
Before touching a single file, ask the AI to take the role of a junior engineer. Not a builder. An asker.
Its job at this stage is to grill you. What’s in scope? What’s explicitly out of scope? What does the MVP actually need to do on launch day?
This surfaces assumptions early, when they’re cheap to fix. The AI might ask something like: “Does the vendor dashboard need real-time order updates, or can it refresh on page load?” That’s the kind of question you would have answered in week two, with code already written around the wrong answer. Instead of discovering a missing user flow three days into development, you catch it in the first ten minutes. Once scope is locked, you build.
The Page-Component-Feature structure ⚙️
Here’s the folder structure the author builds with: every part of the project lives in a Page-Component-Feature hierarchy. One page at a time. Front end, back end, and cloud services all follow the same pattern.
Why does this matter? When something breaks, you know exactly where to look. Instead of asking the AI to read your entire codebase to find a bug, you tag the specific page or component and send just that. Say your payment confirmation page is misbehaving: you drop in the Payment folder and nothing else. Smaller context footprint. Less hallucination. Faster fixes.
The creator adds one more layer: a context.md file inside each folder. This file explains how that piece couples with the rest of the project. It makes you prompt like an engineer instead of a guesser.
The full workflow
Here’s what the process looks like in practice:
- 📂 Create your project folder and name it after your MVP.
- Start with junior engineer mode: before any code is written, ask the AI to ask YOU questions. Define what’s in scope and what stays out.
- Build vertically, one page at a time using the Page-Component-Feature structure throughout.
- Repeat for every layer: front end, back end, cloud services all follow the same folder pattern.
- 📄 Add a context.md to each folder explaining how this piece connects to the rest of the project.
The result: a codebase you can actually navigate. One you can debug without handing the AI the entire project and hoping for the best.
Why this is a prompting upgrade, not just an organizational one
When your folder structure is consistent, you’re not just keeping things neat. You’re building a coordination harness between you and the AI. The folder becomes the contract. It tells both of you what belongs where.
Context engineering is what separates developers who build fast from those who build a lot and ship rarely. The more precise your context, the more precise the output. A Page-Component-Feature structure makes that precision automatic, every time.
I’ve read a lot of “how I build with AI” posts. Most of them show the prompts. This one shows the scaffolding around the prompts. That’s the part most builders skip, and it’s the part that actually matters.
Try it on your next build
If your last MVP took longer than it should have, try this structure on the next one. Start with scope questions. Build vertically. Add the context files. See how many you can ship in 30 days!
The original discussion is live in r/PromptEngineering. Worth a read.
I built an mvp in 2 weeks, this is how I would build it in one day.
by u/alfredowmm in PromptEngineering