Sign inYou describe the app. AI writes the code. You don't even read it. Welcome to vibe coding — the controversial new paradigm where developers become directors.
There's a new kind of developer in the wild. They don't trace through stack traces. They don't memorize syntax. They describe what they want in plain English and let an AI figure out the implementation details. They call it vibe coding — and it's either the democratization of software development or the beginning of a quality apocalypse, depending on who you ask.
The term was coined by Andrej Karpathy in early 2025, describing his experience building software by talking to Claude and Cursor. "I just see things, say things, run things, and copy-paste things," he wrote. "It's not really coding. I just see stuff, say stuff, run stuff, and it mostly works."
The typical vibe coding session looks something like this: you open an AI-powered IDE, describe a feature you want, accept the generated code, run it, see if it works, and iterate from there. The key insight is that you're operating at the intent level rather than the implementation level. You say "add a dark mode toggle that persists in localStorage" rather than writing the CSS variables and event listeners yourself.
Tools like Cursor, Windsurf, and Replit Agent have made this workflow seamless. They understand project context, can read your file tree, and generate code that actually integrates with your existing architecture rather than producing isolated snippets.
Vibe coding is absurdly fast for prototyping. Ideas that would take a weekend to build can be functional in an hour. Non-programmers can build tools they actually need — custom dashboards, data scrapers, automation scripts. The barrier to entry for creating software has essentially collapsed.
For experienced developers, it eliminates the tedious parts. Boilerplate code, API integrations, CSS layouts — the tasks that eat time without requiring creativity. Vibe coding lets senior engineers operate at the architecture level while AI handles the implementation grunt work.
The code AI generates works, but "works" and "works well" are different things. Vibe-coded projects accumulate technical debt at an alarming rate. Security vulnerabilities slip through because nobody reads the generated code carefully. Performance issues hide behind functional facades. Dependencies multiply unchecked.
The real danger isn't bad code — it's the illusion of competence. A vibe-coded prototype that "works" can create false confidence. Teams ship it. Users depend on it. Then the edge cases arrive, and nobody understands the system well enough to fix them.
Vibe coding is phenomenal for personal tools, prototypes, and learning. It's risky for production systems that handle money, health data, or critical infrastructure. The smartest developers aren't choosing between traditional coding and vibe coding — they're using both, applying each where it makes sense.
The future isn't vibes or rigor. It's knowing which one the moment demands.
