Vibe Coding: What It Is and Why Developers Love It

Vibe coding sounds like a meme. It is not. It is a real workflow shift that has quietly changed how thousands of developers write software. The term, coined by Andrej Karpathy in early 2025, describes a development style where you work with AI by describing what you want in natural language, reviewing the output, and iterating through conversation rather than typing every line yourself.

It is not about replacing coding skills. It is about spending your expertise differently.

## What vibe coding actually looks like

Imagine you are building a settings screen for a mobile app. In traditional development, you open your editor, import components, lay out the UI, wire up state management, handle user interactions, add error states, and write tests. That is 200-400 lines of code and 45 minutes of focused work.

In vibe coding, you describe the screen: "Settings screen with toggles for notifications, dark mode, and biometric lock. Include a section for account info (name, email) with edit capability. Logout button at the bottom with a confirmation dialog." The AI generates the full implementation. You review it, ask for adjustments ("make the logout button red and move it inside a danger zone section"), and iterate until it matches what you need.

The key difference is not speed, although it is faster. The key difference is where you spend your cognitive energy. Instead of thinking about syntax, import paths, and boilerplate, you think about product decisions. What should this screen do? What should it look like? How should it behave?

## Why experienced developers love it

You might expect experienced developers to resist vibe coding. The opposite happened. Senior engineers were among the first to adopt it, and they are its biggest advocates. Why?

Because senior developers have already solved most problems before. They know what a settings screen should look like. They know the patterns for form handling, state management, and API calls. Writing those patterns by hand for the hundredth time is not rewarding work. It is repetitive. Vibe coding lets them skip the repetition and focus on the parts that require genuine thought: architecture decisions, edge cases, and user experience details.

Junior developers get a different benefit. They can build things beyond their current skill level, then study the generated code to learn patterns they would not have discovered on their own. Vibe coding becomes a teaching tool. You describe what you want, see how the AI implements it, and absorb the patterns.

## The workflow in practice

A productive vibe coding session follows a pattern:

**Start with architecture.** Before generating any code, describe the overall structure. "I am building a React Native app with tab navigation, Supabase auth, and four main screens." The AI sets up the foundation.

**Build screen by screen.** Describe each screen's purpose and layout. Review the generated code. Make adjustments. Move on. Do not try to generate the entire app in one prompt. Screen-by-screen gives you checkpoints.

**Handle edge cases explicitly.** The AI will produce the happy path by default. You need to ask about error states, loading states, empty states, and offline behavior. "What happens when the API call fails? Add error handling with a retry button."

**Review everything.** This is not optional. AI-generated code works 80-90% of the time. The remaining 10-20% contains subtle bugs, security issues, or performance problems. You need to read and understand every file. Vibe coding means you direct the work. It does not mean you stop thinking.

## Where vibe coding fits in the builder ecosystem

Vibe coding tools like [Cursor and Copilot](/compare) occupy one segment of the AI building spectrum. They are powerful for developers who want to stay hands-on but move faster.

At the other end of the spectrum, [full-lifecycle builders](/features/building) take the concept further. Instead of vibing with an AI about one screen at a time, you describe the entire app and let an automated pipeline handle architecture, code generation, testing, and deployment. Think of it as industrial-scale vibe coding, where the system handles the prompting and iteration for you.

Both approaches have their place. Vibe coding gives you control. Full-lifecycle building gives you speed. Some builders use both: they generate an app with a full-lifecycle tool, then vibe-code their customizations on top.

## Common mistakes

**Generating too much at once.** Asking the AI to build your entire app in one prompt produces mediocre results. Break it into components. One screen, one module, one function at a time.

**Not reading the output.** If you accept AI-generated code without reading it, you are building on a foundation you do not understand. When something breaks (and it will), you will not know where to look.

**Ignoring types and tests.** Vibe coding works best with typed languages (TypeScript, not JavaScript) and a test suite that catches regressions. Ask the AI to generate tests alongside the implementation. It takes 30 seconds and saves hours of debugging later.

**Over-describing implementation details.** "Use useState with a Record<string, boolean> for the toggle state" is fighting the AI. "Add toggles for each setting that persist when the user leaves the screen" lets the AI pick the right pattern. Describe behavior, not implementation.

## Getting started

You do not need to change your entire workflow at once. Start with one task you find tedious. Maybe it is writing tests for existing code, or building form validation, or setting up a new screen layout. Let the AI handle that one thing while you continue coding everything else manually.

As you build confidence, expand the scope. Let the AI generate more. Keep reviewing everything. Over time, you will develop an intuition for which tasks are best handed to the AI and which need your direct attention.

Vibe coding is not a replacement for knowing how to code. It is a force multiplier for people who already know what they want to build. And for the tasks where the result matters more than the process, it is the fastest way to ship.

Explore [Goodspeed's approach](/how-it-works) to see how we apply this concept across the entire app building pipeline, from idea scoring to app store submission.