Something interesting is happening in software development.

Developers are shipping features in hours instead of days. Non-technical founders are building MVPs without hiring engineers. People with ideas are turning them into working products faster than ever before.

They’re not doing it by learning to code in the traditional sense. They’re doing it by learning to collaborate with AI effectively. This approach has a name: vibe coding.

What Is Vibe Coding?

Vibe coding is building software through natural language conversation with AI assistants. Instead of writing code line by line, you describe what you want, review what the AI produces, iterate through conversation, and ship.

The term was coined somewhat tongue-in-cheek (Andrej Karpathy mentioned it in a tweet), but the practice is serious. It’s how a growing number of developers actually work.

Traditional coding:

  1. Understand the requirement
  2. Plan the implementation
  3. Write the code
  4. Debug the code
  5. Repeat until it works

Vibe coding:

  1. Understand the requirement
  2. Describe it to an AI assistant
  3. Review the generated code
  4. Request changes through conversation
  5. Repeat until it works

The core skill shifts from writing code to specifying what you want and evaluating whether you got it.

Why Vibe Coding Works

AI coding assistants have reached a threshold where they can produce production-quality code for a wide range of tasks. Not perfect code. Not code you should ship blindly. But code that’s good enough to be useful, good enough to iterate on, good enough to ship after review.

This changes the bottleneck.

In traditional development, the bottleneck is often writing the code—translating requirements into working implementation. With AI assistance, that translation happens in seconds. The new bottleneck is specifying requirements clearly and evaluating whether the output is correct.

If you can describe what you want precisely and verify that you got it, AI can handle much of the mechanical translation.

The Three Core Skills of Vibe Coding

1. Specification Engineering

This is the ability to describe what you want in enough detail that AI produces useful output. It’s not “prompt engineering” in the sense of tricks and templates. It’s the skill of precise communication.

Good specification includes:

  • Technical constraints (tech stack, libraries, patterns)
  • Behavioral requirements (what it should do)
  • Acceptance criteria (how you’ll know it works)
  • Context (existing code, conventions, limitations)

Example of weak specification:

make a todo app

Example of strong specification:

Create a todo list component with:

Tech: React 18, TypeScript, Tailwind CSS, Zustand

Features:
- Add todo via text input (Enter key submits)
- Toggle completion (checkbox, strikethrough when done)
- Delete with confirmation
- Filter: All / Active / Completed
- Persist to localStorage

UI:
- Clean minimal design
- Smooth transitions for add/remove
- Empty state message
- Mobile responsive

Provide component, store, and types as separate files.

The second specification is more work upfront but produces usable output on the first try.

2. Quality Evaluation (Without Reading Every Line)

You can’t review AI-generated code the same way you’d review human-written code. There’s too much of it, and it comes too fast. You need strategies for verifying quality without reading every line.

Verification approaches:

  • Test-first prompting: Write tests first, then ask AI to implement code that passes them
  • Incremental building: Small pieces that you can verify individually
  • AI-assisted review: Ask the AI to explain its own code and identify issues
  • Output testing: Run the code and verify behavior matches requirements
  • Spot checking: Review critical sections (auth, data handling, business logic)

The goal isn’t to read everything. It’s to build confidence that the code is correct through targeted verification.

3. Debugging Through Re-prompting

When AI-generated code doesn’t work, the fix is usually another prompt, not manual debugging.

Traditional debugging:

  1. Read error message
  2. Find the bug in code
  3. Understand why it’s wrong
  4. Fix it manually

Vibe coding debugging:

  1. Read error message
  2. Describe the problem to AI
  3. Let AI suggest or implement fix
  4. Verify the fix works

This doesn’t mean you never read code. Sometimes you need to understand what’s happening. But often the fastest path from bug to fix is through conversation.

"When I click submit, I get 'Cannot read property 'id' of undefined'. 
Here's the component: [paste code]. Here's the error trace: [paste trace]. 
What's wrong and how do I fix it?"

The AI can often identify and fix issues faster than you can trace through the code yourself.

Tools for Vibe Coding

Conversational AI (Claude, ChatGPT)

Best for:

  • Generating complete features
  • Explaining code
  • Architectural decisions
  • Debugging complex issues
  • Learning new technologies

Workflow: Copy code into conversation, describe what you want, copy output back into your editor.

AI-Integrated Editors (Cursor, GitHub Copilot)

Best for:

  • Inline code generation
  • Small edits and refactors
  • Context-aware completions
  • Multi-file changes

Workflow: Work in your editor, invoke AI for specific changes, accept or modify suggestions.

AI Coding Agents (Claude Code, Aider, etc.)

Best for:

  • Multi-file changes
  • Larger refactors
  • Tasks that span the codebase

Workflow: Describe the task, let the agent explore the codebase and make changes, review the results.

Most vibe coders use a combination. Conversational AI for complex tasks, integrated editors for inline work, agents for larger changes.

What Vibe Coding Is Not

It’s not “no code.” You need to understand code well enough to evaluate it, debug it, and specify it. You just don’t type every line.

It’s not copy-paste without thinking. Blindly accepting AI output is how you ship bugs and security vulnerabilities. Review is required.

It’s not a replacement for learning fundamentals. You need to understand programming concepts to specify them clearly and evaluate whether AI got them right.

It’s not magic. It’s a skill that takes practice. Some people are much better at it than others.

Who Is Vibe Coding For?

Experienced developers use it to ship faster. The code you’d spend 30 minutes writing, AI generates in seconds. You spend your time on architecture, specification, and review.

New developers use it to build real things while learning. You can create working software while gradually understanding what the AI is producing.

Non-technical founders use it to build MVPs without hiring engineers. If you can describe what you want precisely, you can ship a product.

Career changers use it to enter software development from other fields. The barrier to building useful things has dropped significantly.

How to Get Good at Vibe Coding

1. Practice Specification

The core skill is describing what you want precisely. Practice by:

  • Taking a working piece of software and trying to specify it fully
  • Reviewing your old prompts and identifying vague areas
  • Getting feedback on prompt quality (more on this below)

2. Learn to Read Code (Enough)

You don’t need to be able to write every line, but you need to understand:

  • Basic programming concepts (variables, functions, loops, conditions)
  • The tech stack you’re working with
  • Common patterns and anti-patterns
  • Security basics (auth, data validation, SQL injection, etc.)

3. Build Things

The fastest way to improve is by building real projects. The feedback loop of prompting → reviewing → debugging teaches you what works.

4. Get Feedback on Your Prompts

Unlike code, prompts don’t have tests or linters. It’s hard to know if a prompt is good until you see the output. Tools that evaluate prompt quality can accelerate your learning.

5. Learn From Others

See how other people approach the same problems. What do their prompts include that yours don’t? What patterns do they follow?

The Future of Development

Vibe coding isn’t replacing traditional coding. It’s adding a layer. The developers who thrive will be those who can work at multiple levels:

  • Write code by hand when precision matters
  • Direct AI effectively for acceleration
  • Know when to use which approach

The percentage of code written by AI will keep increasing. The question isn’t whether to embrace this but how to get good at it.

Start Building Your Vibe Coding Skills

VibeQ offers two paths to improve:

For practice: Daily coding challenges where you solve problems by prompting. Get scored on how efficiently you specify requirements.

Try Today’s Challenge →

For learning: Structured training that takes you from basics to production-ready vibe coding in 4 weeks.

Explore the Training →

Or start by evaluating a prompt you’ve used recently:

Free Prompt Evaluator →