What Is Vibe Coding? Building Software with AI Assistants

The phrase "vibe coding" was popularised in early 2025 to describe a way of building software where you steer an AI assistant in natural language and let it write most of the code. Instead of typing every line, you describe the outcome you want, review what the model produces, run it, and iterate. This article explains what vibe coding actually is, where it works well, and the habits that keep it from going off the rails.

How it differs from traditional coding

In traditional development, the programmer holds the full mental model and writes the code directly. In vibe coding, the AI holds much of the implementation detail while the human holds intent, judgement, and review. The developer becomes an editor and director more than a typist.

This shift is powered by capable coding models and agentic tools that can read a codebase, make multi-file edits, run tests, and respond to errors. The workflow is conversational: describe, generate, run, correct, repeat.

Where vibe coding shines

It is fastest for greenfield prototypes, small scripts, boilerplate, and well-trodden problems where the model has seen thousands of examples. Building a landing page, wiring up an API, scaffolding a CRUD app, or writing a one-off data script are all tasks where an assistant can save hours.

It also lowers the barrier to entry: people who know what they want but not the exact syntax can now ship working software, and experienced developers can move faster on the parts they find tedious.

Where it still needs a human

Vibe coding struggles with novel architecture, subtle security decisions, performance-critical code, and anything requiring deep knowledge of a specific system. Models can produce code that looks right but hides bugs, leaks secrets, or ignores edge cases. Without review, small errors compound across a session.

The developers who get the most from it treat AI output as a draft: they read every change, keep commits small, write or ask for tests, and never ship code they do not understand. The "vibe" gets you a draft; engineering discipline gets you production.

Getting started well

Start with a clear, written description of what you are building. Work in small steps and verify each one. Keep the codebase under version control so you can undo freely. And pair the assistant with real tests — they are the fastest way to catch the confident-but-wrong output that AI tools sometimes produce.