Vibecoding
Vibecoding is building software by describing what you want to an AI and steering it to a working result. This pillar is the discipline behind it: how to plan, which tools to use, how to prompt the build, and — the part most guides skip — how to make what you ship secure and maintainable.
What vibecoding really is
Vibecoding is building software by describing what you want in plain language and letting an AI write the code, then steering it toward something that actually works. The name comes from the feeling of it — you follow the vibe, describe the next thing you want, and watch an app take shape without hand-writing every line. It has genuinely lowered the barrier to building: people who could never have shipped a working product a year ago now can.
But the version of vibecoding that ships something real is not vibes alone. It is a loop: describe a small piece, look at what the AI produced, verify it does what you meant, then describe the next piece. The people who get burned are the ones who accept a wall of generated code they never read, wire it to a real database and real users, and discover the problems in production. This pillar teaches the loop and the guardrails — planning, tooling, prompting, and above all security — so that what you vibe into existence is something you can actually trust.
Plan a little, then build in slices
The single biggest predictor of a vibecoding project that succeeds is a small amount of planning before the first prompt. You do not need a formal spec document, but you do need to be able to say, in a paragraph, what the app does, who uses it, and what the core screens or actions are. That paragraph becomes the brief you hand the AI and the yardstick you measure its output against — without it, every prompt drifts and the model happily builds something plausible that is not what you wanted.
From there, the reliable rhythm is to build in small, verifiable slices rather than asking for the whole app at once. Get one screen working and check it. Add one feature and check it. This keeps each change small enough to actually review, makes bugs easy to locate, and means you always have a working version to fall back to. Big-bang generation — 'build me a full SaaS with auth, payments, and a dashboard' — produces an impressive-looking pile you cannot debug when it breaks.
Pick the right tools — and a boring stack
The tool you build in matters. A chat window that hands you code to paste is the slowest, most error-prone way to vibecode; an AI-native environment — an editor like Cursor, an agent like Claude Code, or a build-an-app platform like Lovable, v0, Bolt, or Replit — keeps the AI connected to your actual files, a live preview, and your version history, so it can see what it is changing and you can undo when it goes wrong.
Just as important is the stack the AI builds on. Let it use a popular, well-documented, 'boring' stack — the frameworks and databases that appear millions of times in its training data — and the generated code is dramatically more likely to be correct, secure, and fixable. Steer it toward something obscure and you are on your own the moment something breaks. Choosing your tool and stack deliberately is the difference between a smooth build and a fight.
Security is the part you cannot skip
The uncomfortable truth of vibecoding is that AI will happily generate code that works in the demo and is wide open in production. It will put secret API keys in the frontend where anyone can read them, leave a database with no access rules so any visitor can read every user's data, skip input validation, and ship debug settings that leak internal detail. None of this shows up when you click around your own app — it shows up when a stranger does.
So the non-negotiable habits are: keep secrets on the server and never in client code, add real authentication and authorization before you have real users, lock down your database with access rules, and validate every input. You do not need to be a security engineer to do this — you need to know the handful of things that go wrong and ask the AI to do them right. The security cards in this pillar are the checklist. Treat them as required reading before anything you build touches the public internet.
What is vibe coding?
Vibe coding is building software by describing what you want to an AI in plain language and letting it write the code, then steering and verifying the result rather than typing every line yourself. Done well it is a loop — describe a small piece, check what the AI produced, then describe the next — which lets people build working apps with far less traditional coding experience. Done carelessly, by accepting code you never read, it produces software that looks fine but is fragile and insecure.
Can you really build a real app by vibe coding?
Yes — people ship real, working products this way. The projects that succeed share a pattern: a little planning up front, building in small verifiable slices instead of one big prompt, a mainstream tech stack the AI knows well, and — critically — attention to security before real users arrive. The projects that fail skip those, accept a wall of generated code, and discover the problems in production. Vibecoding lowers the barrier to building; it does not remove the need for judgement.
Is vibe coding safe? What about security?
The code itself is only as safe as you make it, and AI will readily generate insecure defaults — secret keys exposed in the frontend, databases with no access rules, missing input validation, debug modes left on. These do not appear when you test your own app; they appear when someone malicious does. The fix is a short checklist you can apply without being a security expert: keep secrets server-side, add authentication and authorization early, lock down your database, and validate all input. The security section of this pillar walks through each.
What tools do I need to start vibe coding?
You need an AI-native environment rather than a plain chat window — an AI code editor like Cursor, an agent such as Claude Code, or a build-an-app platform like Lovable, v0, Bolt, or Replit. These keep the AI connected to your files, a live preview, and your version history so it can see what it is changing and you can undo mistakes. Pair that with a popular, well-documented tech stack, and let the AI handle setup while you describe what to build.
Do I need to know how to code to vibe code?
No, but you need to know enough to steer and verify. You do not have to write the code by hand, but you get far better results if you can read what the AI produced well enough to tell whether it did what you asked, describe changes precisely, and recognise when something is wrong. The skill of vibecoding is less about syntax and more about clear description, checking output, and knowing the handful of things — especially in security — that must be done right.
Why does my vibe coded app break when I add features?
Usually because the app was generated in large chunks that were never reviewed, so each new feature sits on code nobody fully understands, and a change in one place quietly breaks another. The fix is to build in small, verifiable slices — add one thing, confirm it works, commit it — so every change is small enough to review and you always have a working version to return to. Giving the AI the exact error message and the surrounding code, rather than just saying 'it's broken', also dramatically improves its fixes.