Vibe Coding

Vibe coding is a development approach where you describe your intent in natural language and let AI handle the implementation details. Instead of writing code manually, you collaborate with AI assistants to generate working software while focusing on creative direction rather than syntax.

Origin

Coined by Andrej Karpathy, former Tesla AI director, in early 2025. He described it as "fully giving in to the vibes" and letting AI take the wheel on implementation while you focus on what you want to build.

Example

Instead of manually writing a React component with proper TypeScript types, hooks, and styling, you describe: "Create a user profile card that shows avatar, name, and bio with a follow button" and let the AI generate the implementation.

Vibe coding represents a fundamental shift in how software gets built. Rather than fighting with syntax, debugging cryptic errors, and searching Stack Overflow for the hundredth time, developers describe what they want and collaborate with AI to bring it to life.

The Core Idea

Traditional coding requires translating your mental model into precise syntax that machines understand. Vibe coding flips this — you express intent naturally, and AI handles the translation to working code.

This doesn't mean developers become obsolete. Understanding code helps you guide AI better, catch errors faster, and make architectural decisions that require human judgment. Vibe coding amplifies your abilities rather than replacing them.

Why It Matters

The gap between imagination and execution has always been the biggest friction in software development. Vibe coding dramatically reduces this friction, enabling:

  • Faster iteration — Test ideas in minutes instead of hours
  • Lower barriers — Non-developers can build functional software
  • Better focus — Spend energy on interesting problems, not boilerplate
  • Continuous learning — Watch AI solve problems and learn new patterns

The Mindset Shift

Vibe coding is as much about mindset as it is about tools:

  1. Describe outcomes, not implementations — Focus on what the code should accomplish
  2. Embrace iteration — Your first prompt won't be perfect, and that's fine
  3. Stay in control — You make the final decisions, AI is your collaborator
  4. Learn continuously — Every AI interaction teaches you something new

Further Reading