“Forget that the code even exists.”
With that phrase, Andrej Karpathy – leading AI researcher and co-founder of OpenAI – introduced a new way of writing software. One where you don’t control every line, but instead, flow with the AI. And so, Vibe Coding was born.
What is Vibe Coding?
Vibe coding isn’t a methodology. It’s a state of mind. It happens when:
- You put on your headphones, open your editor, and let ideas unfold
- You treat AI like a creative partner, not just a tool
- You build prototypes or explore ideas without worrying about perfection
Karpathy popularized the term in February 2025, and it quickly went viral across dev communities, hacker forums, and startup culture. Soon after came articles, tutorials—and yes, hundreds of “Vibe Coding” playlists on Spotify.
How AI Supercharges the Flow
With LLMs like ChatGPT, GitHub Copilot, or Cursor AI, the vibe becomes exponential:
- Prompt-based programming: Describe what you want. The AI codes it.
- Real-time refactoring: “Make this cleaner, faster, more Pythonic.”
- Creative branching: Test multiple approaches without reinventing the wheel.
- No friction: No syntax errors. No config files. Just… ideas into motion.
It turns coding into something closer to design than engineering.
What Comes After: Agentic Coding
But vibe coding was just the beginning.
As AI evolves from assistant to autonomous collaborator, we enter the next phase: Agentic Coding.
💡 What is Agentic Coding?
Unlike vibe coding where humans still guide the process, agentic coding relies on AI agents to manage entire software lifecycles:
- Design, implementation, testing, and deployment
- Self-debugging and optimization
- The human becomes an overseer, not a co-pilot
In practice, the AI doesn’t just respond—it acts. It solves problems before you even articulate them.
Vibe Coding vs Agentic Coding
| Aspect | Vibe Coding | Agentic Coding |
|---|---|---|
| Human Role | Creative driver / prompt engineer | Overseer / orchestrator |
| Collaboration Style | Prompt-response | Autonomous, agent-led cycles |
| Typical Use Cases | MVPs, creative exploration | Production systems, enterprise workflows |
| Dev Experience | Flow state, expressive, iterative | Supervision, validation, coordination |
Risks & Considerations
The rise of vibe/agentic coding also brings real challenges:
- Quality & security: AI-generated code isn’t always safe. Some startups already faced security breaches from auto-written code.
- Skill atrophy: If you never write or read code deeply, can you still understand what your systems are doing?
- Accountability: Who owns the bug? The developer? The model? The platform?
What’s Next?
Vibe coding is still relevant. Agentic coding is rising. And beyond them?
- Self-improving agents that optimize their own code
- Multimodal prompts – voice, sketches, gestures
- Autonomous feature delivery – AI that builds, deploys, and A/B tests without human involvement
The future developer won’t just “write code”—they’ll direct and supervise entire AI ecosystems.
Final Thoughts
Vibe coding reminded us that software creation can feel like music. A flow. A rhythm.
Agentic coding shows us that AI can now take initiative, not just follow directions.
What’s the common thread? The developer is evolving—from code monkey to creative director, from problem-solver to system orchestrator.
The challenge ahead isn’t learning another framework. It’s learning how to think, communicate, and create in a world where machines speak back.
