Master the Art of Vibe Coding: A Step-by-Step Guide

You know the drill. You fire up Cursor, feeling inspired by yet another AI coding demo on Twitter. You type “build me a SaaS for influencer marketing courses” and hit enter. The AI starts generating code. Lots of code. Files everywhere. Half-working components. Broken imports. Nothing connects.

Three hours later, you’re staring at a pile of digital spaghetti that doesn’t even compile. You close the editor in frustration and tell yourself “AI coding isn’t ready yet.” But here’s the hard truth: the AI isn’t the problem. Your approach is.

But first here’s you (probably):

You open Cursor. Type “build me X.” It spirals. Nothing works. You start over.

That’s not development. That’s chaos.

LLMs Are Insanely Good Right Now

Let’s get one thing straight: modern LLMs are phenomenally capable at code generation. But here’s what most people miss: if you can’t get meaningful work done with current AI tools, you’re either prompting wrong or you didn’t give enough context.

The models aren’t the bottleneck. Your process is.

The Three-Step System That Actually Works

I have an incredibly simple system that works every single time as someone who has built multiple production-ready applications, with thousands of users, from just Cursor with minimum intervention:

Step 1: architecture.md

Open ChatGPT (4o, not o1/o3/o4) and say:

I'm building a [description of your product - the more detailed the better]. Use Next.js for frontend, Supabase for DB + auth.
Give me the full architecture:
- File + folder structure  
- What each part does
- Where state lives, how services connect
Format this entire document in markdown.

Save its output as architecture.md and throw it in an empty folder where your project will live.

Step 2: tasks.md

Now say:

Using that architecture, write a granular step-by-step plan to build the MVP.
Each task should:
- Be incredibly small + testable
- Have a clear start + end  
- Focus on one concern
I'll be passing this off to an engineering LLM that will be told to complete one task at a time, allowing me to test in between.

Save it as tasks.md. Again, throw it in the folder.

Step 3: In Cursor/Windsurf

You're an engineer building this codebase.
You've been given architecture.md and tasks.md.
- Read both carefully. There should be no ambiguity about what we're building.
- Follow tasks.md and complete one task at a time.
- After each task, stop. I'll test it. If it works, commit to GitHub and move to the next.

Include this as well — this is crucial:

### CODING PROTOCOL ###
- Write the absolute minimum code required
- No sweeping changes
- No unrelated edits - focus on just the task you're on
- Make code precise, modular, testable
- Don't break existing functionality
- If I need to do anything (e.g. Supabase/AWS config), tell me clearly

Why This System Eliminates the Spiral

This system fixes the biggest problem with vibe coding:

You’re not dumping everything into the IDE and praying. You’re giving it a roadmap. You’re keeping it on rails. You stay in control.

The traditional approach fails because you’re asking the AI to make hundreds of architectural decisions simultaneously while generating code. It’s like asking someone to build a house while you describe rooms one wall at a time.

Advanced Prompting That Actually Works

Context Is Everything

Modern LLMs have massive context windows — use them. Include relevant files, error messages, and background. The more context you provide, the better the output.

Be Stupidly Specific

Instead of “add authentication,” try “implement Supabase authentication with email/password signup, email verification, and protected routes that redirect to /login for unauthenticated users.”

Role-Based Prompting

Start with: “You are an expert React developer building a production application…” This primes the model for appropriate expertise.

Iterative Refinement

Don’t expect perfection first try. Use follow-ups like “refactor this to use custom hooks” or “add proper error handling.” AI excels at iterative improvement.

The Real Problem: You’re Flying Blind

Most developers treat AI like a magic wand. Type a wish, hope for the best. That’s not how you build software that works.

The structured approach prevents chaos by:

• Architecture.md handles all big decisions upfront

• Tasks.md creates testable milestones

• The coding protocol keeps AI focused on execution, not design

Stop Vibe Coding. Start Shipping.

This workflow lets you ship clean, testable AI-assisted code — without the spiral.

Your next production application is waiting to be built. The tools are ready. The question isn’t whether AI can help you build it — it’s whether you’ll use the right system to unlock its potential.

Ready to implement this system? Start with architecture.md for your next project and watch the chaos disappear.