Vibe Coding: What It Is and How to Build a Real App With AI

Vibe coding is building software by describing what you want in plain language and letting an AI tool write most of the code. You ask for a sign-up page with email login, the tool writes it, you run the result, and you steer with the next request. Your time goes into what the app should do rather than into syntax.

It works well for prototypes, internal tools and small products, and can take a solo maker from idea to a live app in days. It also fails in predictable ways when nobody checks the output. This guide covers the tools, a realistic workflow, quality and security, and how to get your first users.

What is vibe coding?

The term was coined by AI researcher Andrej Karpathy in early 2025. He described a way of working where you lean fully on the AI: accept its changes without reading every line, paste error messages back in, and see what happens. He presented it as fine for throwaway weekend projects. The phrase caught on fast and now covers any workflow where plain-language prompts drive most of the coding.

In practice there is a spectrum:

• Pure vibe coding. You never read the code. Good for experiments, demos and learning what is possible.
• AI-assisted engineering. You describe the change, the AI writes it, and you review, test and commit it like any other code. This is what you want for anything with real users or real data.

Most makers who ship end up in between: the AI does the typing, but they keep ownership of the structure, the data and the security decisions. This guide assumes that middle path.

Vibe coding tools: the main categories

Vibe coding tools fall into two broad groups. Both change quickly, so check current features and pricing on each product's site before you commit.

AI code editors and coding agents

These work with a real codebase on your machine or in a repository, so you keep full control of the code.

• Cursor is a code editor built around AI, with chat, inline edits and an agent mode that can change many files at once.
• Claude Code is Anthropic's coding agent. It works in the terminal and in code editors, reads your project, runs commands and tests, and makes multi-file changes.
• GitHub Copilot started as autocomplete inside popular editors and now includes chat and agent features that tie closely into GitHub.
• Windsurf is another AI-first editor with an agent that plans and applies changes across a project.

Pick this group if you want to own a normal codebase, use any framework and grow the project over months.

AI app builders

These run in the browser and go from a prompt to a working app, usually with hosting included. They are the fastest way to see something real.

• Lovable builds full-stack web apps from chat and connects to common backend services for data and sign-in.
• Bolt generates and runs web apps in the browser, so you can edit and preview without installing anything.
• Replit is an online development environment with an AI agent and built-in deployment.
• v0 by Vercel focuses on generating interfaces and web apps with modern front-end frameworks.

Pick this group for prototypes and simple tools, or if you have never set up a development environment. Most builders can export the code or sync it to GitHub; do that early so you are not locked in.

How to choose

A common path is to prototype in an app builder, then move the code into a repository and continue with an editor or agent once the idea proves itself.

How to vibe code an app: a step-by-step workflow

This workflow assumes a small web app, but the same steps apply to mobile apps and scripts.

1. Write a one-page brief. Who is it for, what problem does it solve, what is the single core action, and what is explicitly out of scope for version one. Keep it in a file the tool can read at the start of every session.
2. Pick a boring, popular stack. AI tools tend to write better code for widely used frameworks and databases, because far more examples of them exist.
3. Set up version control before the first feature. Create a Git repository, commit the empty project, and commit again after every working change. This is your undo button.
4. Build one thin vertical slice. Get the core action working end to end, from the screen to the database and back, before adding anything else. Ugly is fine at this stage.
5. Work in small, specific prompts. "Add a delete button to each item that asks for confirmation" beats "improve the item list". One change per prompt keeps diffs readable and makes it obvious which change broke something.
6. Run the app after every change. Click through the core flow yourself. When something breaks, give the AI the exact error, what you did and what you expected.
7. Add tests for the core logic. Ask the AI to write tests for the parts that must never break, such as pricing, permissions and data changes, and run them before each commit.
8. Use established services for the hard parts. Authentication, payments, email and file storage are solved problems. Use a well-known provider.
9. Deploy early. Put the app online in the first days, even if only you use it. Deployment problems are easier to fix while the app is small.
10. Keep a short notes file. Record decisions, conventions and known issues. Many agents read such a file automatically, which keeps new sessions consistent.

How to keep quality high when AI writes the code

Speed is the easy part. The habits below are what separate a demo from a product people can trust.

Version control and small commits

Commit every working state with a clear message. When the AI takes a wrong turn, roll back instead of asking it to fix the fix.

Review every diff

Before you commit, read what changed. You do not need to understand every line, but you should notice when a small request touched ten files, deleted a check, replaced real data with sample data or added a package you did not ask for. If a diff is too big to review, the prompt was too big.

Tests as a safety net

AI changes often fix one thing and quietly break another. A handful of automated tests on your critical paths catches that immediately. Be wary of tests that only confirm the code does what it currently does.

Security basics you cannot skip

Most security problems in vibe-coded apps come from a few repeated mistakes. The OWASP Top Ten is a good general reference, and these are the essentials:

• Secrets. API keys and database credentials belong in environment variables on the server, never in front-end code or in the repository. Add your environment file to .gitignore. If a key ever lands in a commit or a public page, revoke it and create a new one.
• Authentication and authorization. Use a proven sign-in provider. Then check on the server, on every request, that the signed-in user is allowed to read or change that specific record. Hiding a button in the interface is not protection.
• Database access rules. If your front end talks to a hosted database directly, turn on and test its access rules, such as row-level security, so one user cannot read another user's data.
• Input validation. Validate every input on the server: type, length, format and allowed values. Use parameterized queries or an ORM, and escape user content before showing it on a page.
• Dependencies. Check that every package the AI adds is real, maintained and spelled correctly. AI tools sometimes suggest packages that do not exist, and attackers can register those names.
• Abuse limits. Add rate limits to sign-in, sign-up and any endpoint that sends email or calls a paid API, so one script cannot run up your bill.

It also helps to ask the AI for a security review of one specific area, then verify its findings yourself.

Common vibe coding failure modes

Knowing these ahead of time saves days.

• The fix loop. The AI fixes a bug, which breaks something else, which it fixes by breaking the first thing again. Stop, roll back to the last good commit and describe the problem differently, or ask it to explain the cause before it changes anything.
• Context drift. In long sessions the AI loses track of earlier decisions. Start fresh sessions for new tasks and point the tool to your notes.
• Invented APIs. The code calls functions that do not exist in your library version. Paste the relevant page of the official documentation into the chat.
• Silent fakes. To make an error go away, the AI may hard-code sample data, skip a check or catch and ignore an exception. Diff review catches this.
• Giant files. Everything ends up in one file that nobody, including the AI, can edit safely. Split it into smaller modules while the app is still small.
• Scope creep. Adding features is so easy that version one never ends. The out-of-scope list in your brief is there to stop this.
• No understanding when it breaks. If the app fails in production and you cannot read the code, you are stuck. Ask the AI to explain the architecture in plain language and keep that in your notes.

From working app to first users

An app that works on your laptop is not launched yet. These steps get it into real hands.

1. Put it on a real domain with HTTPS, a clear page title and one sentence that says what the app does and for whom.
2. Add a feedback channel, such as an email address or a simple form, plus basic error logging, so you learn about crashes before users give up.
3. Measure one thing that matters, such as how many people complete the core action.
4. Tell the people who have the problem. Share the app in the communities where your users already spend time, following each community's rules. Explain what you built and why, and ask for honest feedback rather than upvotes.
5. List it where makers and curious visitors browse. Directories and launch sites give a finished project a permanent home that people can find later. On One Dollar Planet, for example, a point for your project on a 3D planet costs $1 a year, and a logo with a catalog listing and a page of its own costs $19 and stays for good. You can add your project and see what other makers have built in the project catalog.
6. Talk to your first users one by one. Early on, a few conversations teach you more than any dashboard.
7. Keep shipping in small steps. The same vibe coding workflow now serves your users: small prompts, reviewed diffs, tests, then deploy.

Sharing progress and lessons as you build also gives people a reason to follow along before launch day. For more on launching small projects, browse the blog.

Key takeaways

• Vibe coding means describing what you want and letting AI write the code. For anything with real users, pair it with review and testing.
• Use AI editors and agents for code you will own long term, and app builders for fast prototypes.
• Commit often, keep prompts small and review every diff.
• Keep secrets on the server, check permissions on every request and validate all input.
• When the AI goes in circles, roll back instead of piling fixes on fixes.
• A working app still needs a launch: a real domain, a feedback channel and people who have the problem.

FAQ

What is vibe coding in simple terms?

Vibe coding is making software by telling an AI tool what you want in everyday language instead of writing the code yourself. The AI generates the code, you run it, and you guide the next step with more instructions. It is fastest for prototypes and small apps.

Do I need to know how to code to vibe code an app?

No, you can build a working prototype without coding experience, especially with browser-based app builders. To launch something that handles real users and data, you need the basics: how your app is structured, how to read a diff and how to keep secrets and permissions safe. The AI can teach you these as you go.

What are the best vibe coding tools?

It depends on the goal. App builders such as Lovable, Bolt, Replit and v0 are the quickest route to a running prototype. Editors and agents such as Cursor, Claude Code, GitHub Copilot and Windsurf suit longer projects with a codebase you own.

Is vibe-coded software safe to put in production?

It can be, if you treat the AI's output like code from a new teammate: review it, test it and check it for security issues before release. The most common problems are exposed API keys, missing server-side permission checks and unvalidated input. Code that nobody has reviewed or tested should not handle other people's data or money.

How long does it take to vibe code an app?

A simple prototype can take an afternoon, and a solid first version often takes days to a few weeks, depending on scope and experience. Most of the time goes into testing, edge cases and deployment, not the first draft. A tight scope is the biggest factor you control.