Getting Started with Vibe Coding
A practical introduction to building software with AI — what vibe coding is, how to think about it, and how to get your first project off the ground.
What Is Vibe Coding?
Vibe coding is a development approach where you describe what you want to build in natural language and let AI tools generate the code. Instead of writing every line yourself, you collaborate with AI — guiding it with prompts, reviewing its output, and iterating toward your goal.
The term was coined by Andrej Karpathy in early 2025:
"There's a new kind of coding I call 'vibe coding', where you fully give in to the vibes, embrace exponentials, and forget that the code even exists."
In practice, vibe coding ranges from fully AI-driven generation to a tight human-AI collaboration loop. Most successful projects fall somewhere in between.
The Vibe Coding Mindset
Think in outcomes, not implementation
Instead of thinking "I need to create a React component with useState and useEffect hooks," think "I need a search bar that filters results as the user types." Let the AI handle implementation details.
Iterate rapidly
Your first prompt won't produce perfect results. The workflow is: prompt → review → refine → repeat. Each iteration gets you closer.
Stay in control
Vibe coding doesn't mean blindly accepting AI output. You should:
- Review generated code before committing
- Understand the architecture even if you didn't write every line
- Test functionality at each step
- Keep your project organized
Choosing Your Tools
AI Coding Assistants
| Tool | Best For | How It Works |
|---|---|---|
| Claude Code | Full-stack development, complex reasoning | CLI-based agent that reads your codebase and makes edits |
| Cursor | IDE-integrated coding | VS Code fork with AI built into the editor |
| GitHub Copilot | Line-by-line code completion | Autocomplete suggestions as you type |
| v0 by Vercel | UI component generation | Chat-based UI that generates React components |
| Bolt | Full-stack app scaffolding | Browser-based AI that builds and deploys apps |
| Replit Agent | Quick prototypes | Cloud IDE with an AI agent that builds features |
| Lovable | Full-stack app generation | AI that generates and deploys complete apps |
Recommended Stack for Beginners
If you're starting your first vibe-coded project, this stack has the most AI tool support and community resources:
- Framework: Next.js (React)
- Styling: Tailwind CSS
- Database: Supabase (Postgres)
- Auth: Supabase Auth or Clerk
- Hosting: Vercel
- Payments: Stripe (when needed)
Your First Vibe-Coded Project
Step 1: Start with a clear idea
Write a one-paragraph description of what you want to build. Be specific about:
- Who it's for
- What problem it solves
- The core feature (just one to start)
Example: "A simple bookmark manager for developers. Users can save URLs with tags, search their bookmarks, and share collections. The core feature is saving and tagging bookmarks."
Step 2: Set up your environment
- Install Node.js (v18+)
- Choose your AI tool (Claude Code, Cursor, or v0 are good starting points)
- Create a new Next.js project:
npx create-next-app@latest my-app - Initialize a Git repository and make your first commit
Step 3: Build incrementally
Don't try to build everything at once. Work in this order:
- Landing page — Get something visual up first
- Core feature — The one thing your app does
- Authentication — Let users sign in
- Data persistence — Connect a database
- Polish — Improve the UI, add error handling
Step 4: Prompt effectively
When working with AI tools, provide context:
I'm building a bookmark manager with Next.js 14 (App Router),
Tailwind CSS, and Supabase.
I need a component that displays a grid of bookmark cards.
Each card should show:
- The page title
- The URL (truncated)
- Tags as colored pills
- A delete button
The bookmarks data comes from a Supabase table called "bookmarks"
with columns: id, title, url, tags (text array), user_id, created_at.
Step 5: Review and iterate
After each AI generation:
- Does it work? Run it and test
- Does it look right? Check the UI
- Is it organized? Check file structure
- Is it secure? Look for exposed keys, missing auth checks
Common Pitfalls to Avoid
-
Skipping version control — Commit frequently. AI can generate broken code, and you need to be able to roll back.
-
Prompting too vaguely — "Make it better" won't help. Be specific: "Add loading states to the bookmark cards and handle the empty state when no bookmarks exist."
-
Building too much at once — Ship a working MVP before adding features. You can always iterate.
-
Ignoring errors — When something breaks, paste the error message to your AI tool and ask it to fix the issue. Don't just skip it.
-
Not testing on mobile — Open your browser dev tools and test responsive layouts early. It's harder to fix later.
Next Steps
Once you're comfortable with the basics:
- Read the Choosing Your Tech Stack guide to understand your options
- Read Prompt Engineering for Code Generation to level up your prompting
- Read Deploying to Production when you're ready to ship