What is vibe coding? How it works, and the risks most guides skip
Vibe coding is building software by describing what you want in plain language and letting an AI model write the code. You run what it made, tell it what to change, and go again. In the strict sense of the term, you never read the code. You only check whether the app behaves.
That is the whole idea, and it is why the phrase spread so fast. This guide covers where the name came from, how the work has changed, which tools are worth your time, and the part most cheerful articles skip: where it goes wrong.
Where the term vibe coding came from
Andrej Karpathy, an AI researcher who helped start OpenAI and later led AI at Tesla, named it in a post on February 2, 2025. He described a new way of working where you "fully give in to the vibes, embrace exponentials, and forget that the code even exists".
He was talking about throwaway weekend projects. He accepted every change the AI suggested, pasted error messages back in without comment, and let the code grow past what he would normally understand.
The phrase stuck anyway. Collins Dictionary chose it as Word of the Year for 2025, and by 2026 it is used for almost any kind of AI-written software, which is where the confusion starts.
Vibe coding vs AI-assisted development
People use "vibe coding" for two different things. The difference matters more than the name.
| Vibe coding | AI-assisted development | |
|---|---|---|
| Who writes the code | The AI | The AI, with a developer |
| Who reads the code | Nobody | The developer, every change |
| How you judge it | Does the app seem to work? | Tests, review, understanding |
| Good for | Prototypes, personal tools, demos | Software that real users depend on |
| Main risk | Problems nobody has seen yet | Slower than it feels |
Programmer Simon Willison drew this line early, in a March 2025 essay. His point: if an AI wrote every line but you reviewed, tested and understood it all, that is not vibe coding. That is using an AI as a typing assistant.
So the same tool can be used both ways. What changes is whether a person checks the result.
How it moves past frameworks to intent
Traditional web development starts with a framework. You pick React or Vue, learn its rules, and translate your idea into its terms. Most of the early effort goes into setup, not into the product.
Prompt-based development turns that around. You begin with the outcome and the tool picks the parts.
Interface design shows it best. In place of a component list, you write something like this:
The AI chooses the layout, spacing and behaviour on a phone. You then react to what is on screen: "make the header smaller", "this feels too corporate", "the button should stand out more". Those are design notes, and current tools act on them.
The frameworks are still there. The AI still writes React, Tailwind and SQL underneath. You just do not need to know the syntax to get a first version in front of you.
Full-stack prompt engineering
Early AI tools gave you snippets. Today's tools build the whole application: screens, database, sign-in and hosting. Describing all of that clearly has become a skill of its own, often called full-stack prompt engineering.
Prompts that work well tend to do four things:
- Name the user and the goal, not only the feature. "A tutor tracks which students have paid" beats "make a payments table".
- Say what data is stored and who is allowed to see it.
- Set limits: the tech stack, the style, and what must not be touched.
- Go one step at a time, and test each change before asking for the next.
It reads less like code and more like a careful product brief.
Vibe coding tools worth knowing in 2026
There are dozens of AI co-pilots in 2026. These three show the range, from the browser to the professional code editor.
Vercel v0
v0 began as a generator for single interface components. Vercel renamed it from v0.dev to v0.app in August 2025 as it grew into a full app builder. You describe an app, watch a live preview appear, and refine it in chat. It writes Next.js and React code and publishes to Vercel's hosting.
Best for: good-looking front ends, landing pages and quick product prototypes.
GitHub Copilot
Copilot is how most developers first met AI help. It started as autocomplete. In agent mode it now plans a task, edits several files, runs commands and corrects its own mistakes. Its coding agent can pick up a GitHub issue and come back with a pull request for a person to review.
Best for: working developers inside an existing codebase. Because the result arrives as a pull request, review is built into the process.
Google AI Studio
AI Studio used to be a place to test Gemini models. Its Build mode now turns a prompt into a running app. Since March 2026 it connects to Firebase: the agent notices when your app needs saved data or user accounts and offers to set up a Firestore database and sign-in.
One detail in Google's own announcement is worth noticing. It tells you to review the database security rules the agent writes before you go live.
Best for: apps built around AI features, and for experimenting at no cost.
Others people compare
Lovable, Bolt and Replit are browser-based builders close to v0. Cursor and Windsurf are AI code editors nearer to Copilot. Most have a free tier, so the practical advice is to give the same prompt to two of them and compare.
| If you want | Start with |
|---|---|
| A polished web app from a description | v0, Lovable or Bolt |
| Help inside code you already have | GitHub Copilot or Cursor |
| An app with AI features and a database | Google AI Studio |
Where vibe coding goes wrong
The demos are real. So are the problems, and they tend to appear after launch.
- Security. Veracode tested more than 100 AI models on 80 coding tasks in its 2025 GenAI Code Security Report. In 45% of the tests, the model introduced a well-known type of security flaw. The code worked. It was not safe.
- Exposed data. In May 2025, a security review reported by Semafor found that 170 of 1,645 apps built with one popular vibe coding platform had a flaw that could expose their users' data.
- Speed that is partly a feeling. A controlled study by METR in July 2025 gave experienced open-source developers 246 real tasks. With AI tools they took 19% longer, although they had expected to be 24% faster.
- Debugging code nobody read. When the app breaks and the AI cannot fix it, you are left with a codebase you have never looked at.
None of this makes the approach useless. It tells you where to use it. A habit tracker for yourself is a fine thing to build on vibes. A shop that stores card details is not.
A short checklist before you share a vibe-coded app
- Search the code for API keys and passwords. They should never sit in files a browser can load.
- Open the app while signed out, and as a second user. Check that you cannot see the first user's data.
- Read the database rules, or ask a developer to. "Anyone can read and write" is a common default.
- Run the whole sign-up flow yourself: the confirmation email, the password reset, the wrong-password message.
For that last step, register with a throwaway inbox so your own address does not fill with test accounts. A temporary email address works for manual checks. If you want the test to run automatically, the Mailfornet API for developers lets a script create an inbox and read the verification email back.
Will vibe coding replace developers?
It replaces tasks. It has not replaced judgment.
Boilerplate, first drafts of screens, tests, documentation and moving code between languages are now mostly handed to an AI. That work used to fill a large part of a developer's week.
What remains is the harder part: deciding what to build, how it should hold together a year from now, whether it is safe, and who answers when it fails. The job is moving from writing code to directing and reviewing it.
For beginners, the door has never been wider. You can build something real in an afternoon. The people who also learn the basics, such as how data is stored and how a login works, are the ones who can keep going when the AI gets stuck.
Common questions
What is vibe coding in simple terms?
Vibe coding is building software by describing what you want in plain language and letting an AI model write the code. You run the result, say what to change, and repeat. In its original meaning you do not read the code at all. You judge it only by whether the app does what you asked.
Why is it called vibe coding?
The name comes from a post by AI researcher Andrej Karpathy on February 2, 2025. He described a way of working where you "fully give in to the vibes, embrace exponentials, and forget that the code even exists". Collins Dictionary made it Word of the Year for 2025.
Is vibe coding bad?
Not for the right job. It is a good way to make prototypes, personal tools and weekend projects. It becomes a problem when unread code handles logins, payments or other people's data. Veracode's 2025 study found that AI models introduced a known security flaw in 45% of its test tasks.
Is vibe coding the same as using an AI co-pilot?
No. A developer who uses an AI co-pilot but reads, tests and understands every change is doing AI-assisted development. Vibe coding means accepting the code without reviewing it. The tools are often the same. The difference is whether a person checks the result.
Can I vibe code without knowing how to program?
Yes, for simple apps. Tools such as v0, Lovable, Bolt and Google AI Studio turn a description into a working web app with no code typed by you. You will get further, and get stuck less, if you learn the basics of how web apps store data and handle logins.
Will vibe coding replace software developers?
It replaces a lot of typing, and it has not replaced the judgment. Someone still has to decide what to build, check that it is secure, and fix it when it breaks. The work is moving from writing code towards directing and reviewing it.
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