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Edjere Evelyn Oghenetejiri
Edjere Evelyn Oghenetejiri

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How I Use AI to Build Full-Stack Apps (The Pipeline Nobody Talks About)

#webdev #nextjs #ai #programming

Everyone's talking about AI coding assistants. But here's what most people get wrong:

They don't have a system.

They just throw random prompts at ChatGPT and hope for the best.

I've been building full-stack applications with AI for months now, and I've developed a repeatable pipeline that actually works. Think of it like an ML pipeline — structured, predictable, and efficient.

Here's the exact workflow I follow. 👇

The 6-Step Pipeline 

PLAN → BACKEND → FRONTEND → CONNECT → PUSH TO GITHUB → DEPLOY
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Simple? Yes. But the magic is in HOW you execute each step.

Step 1: Plan Before You Prompt

Before writing a single line of code, I have a conversation with the AI about architecture.

What I ask:

  • "I want to build X with Y tech stack. What's the folder structure?"
  • "What endpoints will I need?"
  • "Create an implementation plan"

This gives you a blueprint. No more building blind.

Step 2: Backend First (Always)

I build the backend before touching the frontend. It's like preparing your data before training a model — the foundation matters.

The sequence:

Step What to Do
1. Models Define your data structures
2. Routes Create your API endpoints
3. Logic Add authentication, validation
4. Test Verify everything works

💡 Pro tip: Be specific with your prompts. Instead of "make the backend work", say "Create a POST endpoint at /api/users that takes name and email".

Step 3: Frontend with Next.js + Tailwind

For the frontend, I recommend Next.js + Tailwind CSS.

Why this stack?

Next.js Tailwind CSS
File-based routing No custom CSS needed
Built-in SSR Rapid prototyping
Easy Vercel deployment Responsive out of the box

The sequence: 

# 1. Setup
npx create-next-app@latest my-app --tailwind --typescript --app

# 2. Run dev server
cd my-app && npm run dev
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Then:

  1. Components — Build reusable UI pieces
  2. Pages — Create your routes
  3. Polish — Make it look amazing

Step 4: Connect Everything (The Critical Part)

This is where 90% of developers get stuck. Linking frontend to backend.

My checklist:

  • [x] Add CORS to your backend
  • [x] Create an API service in your frontend
  • [x] Set up environment variables for the API URL
  • [x] Handle authentication/tokens
  • [x] Implement error handling

Example API Service 

// lib/api.ts
const API_URL = process.env.NEXT_PUBLIC_API_URL || 'http://localhost:8000';

export async function fetchData(endpoint: string, token?: string) {
  const response = await fetch(`${API_URL}${endpoint}`, {
    headers: {
      'Authorization': token ? `Bearer ${token}` : '',
      'Content-Type': 'application/json',
    },
  });

  if (!response.ok) throw new Error('API request failed');
  return response.json();
}
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When something breaks (and it will), share the exact error message with the AI. Not just "it's broken."

Step 5: Push to GitHub (Always!)

This is non-negotiable. Before deploying, always push your code.

Why it matters:

  • Version control saves you when things break
  • You can rollback to previous versions
  • It's your backup AND your portfolio
  • Deployment platforms can auto-deploy from your repo

My habit:

# After every working feature
git add .
git commit -m "feat: add user authentication"
git push origin main
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⚠️ Never deploy code that isn't in your repo.

Step 6: Deploy

What Where
Frontend Vercel (free tier, takes 2 minutes)
Backend Render or Railway (also free tier friendly)

Both can auto-deploy from your GitHub repo — that's why Step 5 matters!

The Golden Rules

✅ Do this:

  • Be specific with prompts
  • Share error messages + relevant code
  • Build one feature at a time
  • Ask for explanations when confused

❌ Avoid this:

  • Vague prompts like "make it work"
  • Building everything at once
  • Copy-pasting without understanding

The Bottom Line

AI won't replace developers. But developers who know how to work WITH AI will replace those who don't.

Having a structured pipeline turns AI from a random tool into a reliable co-pilot.

Start with the plan. 
Build the backend. 
Create the frontend. 
Connect them. 
Push to GitHub.
Deploy.

Rinse and repeat.
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What's your workflow for using AI in development? I'd love to hear different approaches in the comments. 👇

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