What Is Vibe Coding? Where It Works, Where It Breaks

"Vibe coding" went from a joke on X to a mainstream search term in about a year. At Lasting Dynamics we build software for demanding clients and train developers in our academy, so we see the phenomenon from both sides: in the exciting prototypes candidates show us, and in the wreckage we're occasionally asked to repair. Here's an honest guide to the term — what it means, where it genuinely works, and where it breaks.

What vibe coding actually means

Andrej Karpathy popularized the term in early 2025: coding by "giving in to the vibes" — you describe what you want, accept what the AI produces without really reading it, paste errors back when something breaks, and repeat. Code stops being something you write and understand; it becomes something you summon.

The honest definition has two inseparable halves:

1. You describe outcomes instead of writing instructions — this half is the future, and it's here to stay.
2. You don't read what comes back — this half is the problem, and it's the literal definition of the term.

Many people now use "vibe coding" loosely for any AI-assisted development. That's worth correcting upfront: using agentic tools with discipline isn't vibe coding — it's modern engineering. Vibe coding is specifically the variant where understanding is optional.

Where it genuinely works

Let's say this without snobbery, because critics skip it:

• Prototypes and proofs of concept. Validating an idea in an afternoon instead of two weeks changes business decisions. It works.
• Throwaway personal tools. The one-off script, the dashboard only you will use — if it breaks, nothing breaks.
• Learning by exploring. Watching an AI build something is a legitimate way to discover patterns and libraries — if you then go back and understand what it did.
• The first 80% of non-critical work. Layouts, boilerplate, standard integrations: AI does these fast and well.

Anyone dismissing all of this has missed the shift: the barrier to building something has collapsed, and that's good.

Where it breaks

Then the prototype works, someone says "let's ship it", real users arrive — and the bill comes due. The failure modes repeat with remarkable consistency:

1. The understanding wall. While every request is additive ("add a button"), things flow. The day you need to change something structural in a codebase nobody has ever read, you discover you don't know where to put your hands — and neither does the AI, because the structure is sediment from unreviewed accidental choices.

2. Security doesn't emerge from vibes. Input validation, session handling, permissions, secrets in the wrong files: AI generates plausible code, and plausible security code is precisely the kind that gets broken. Nobody who isn't reading the code will notice before attackers do.

3. Data is unforgiving. A database schema that grew by accretion holds up while data is small and paths are happy. Migrating real data out of a wrong schema is among the most expensive work in software — and no prompt makes it painless.

4. Review debt compounds. Every line accepted without understanding is a small loan. Over a thousand lines, manageable; over fifty thousand, the codebase is technically yours and practically no one's.

5. Without tests, the AI guesses confidently. An agent that can run a trustworthy test suite converges toward correct. One pointed at an untested codebase — vibe coding's typical product — produces changes that look right. Production is where you find out.

The discipline that replaces the vibes

The answer to vibe coding isn't going back to writing everything by hand — that's answering car crashes with horses. It's the discipline that makes the speed sustainable:

• Precise briefs instead of vague prompts: context, constraints, definition of done.
• Review of every line that lands: if you don't understand it, ask the AI to explain it — it's excellent at that — until you do.
• Tests as the agent's leash, written before or alongside the code.
• Small verifiable increments, each one a commit, instead of avalanches of change.
• Architecture decided by you: the AI fills the structure; the structure is your job.

Engineers who master this discipline get vibe-coding speed plus a system that holds. It's literally what we teach: in the Lasting Dynamics Academy curriculum, hands-on agentic AI work sits next to software architecture, design patterns, testing and relational models — because a multiplier without fundamentals multiplies zero. For ten years we've trained the engineers we then hire exactly this way: free, fully remote, selective, with a weekly mentor review and a job offer for everyone who completes.

If you've vibe-coded something you're proud of and want to become the kind of developer who can also maintain it, the discipline lives in our agentic coding program — applications for the next cohort are open.

FAQ

Are vibe coding and AI-assisted development the same thing? No. AI-assisted development with review, tests and judgement is modern professional practice. Vibe coding is the variant where you accept output without understanding it. The difference isn't the tool — it's the discipline.

Is vibe coding a good way to learn to code? As a spark of curiosity, yes. As a method, no: you learn to obtain code, not to understand it, and the wall arrives fast. The path that works is using AI while insisting on understanding every line — twice the effort at the start, ten times the return later.

Can a vibe-coded product go to production? Some have, and a few survived long enough to be rewritten by engineers. The real question: who answers the first security hole, the first data bug, the first migration? If the answer is "nobody knows how", production will let you know.

Which tools do people vibe code with? The same ones serious engineering uses: Claude Code, Cursor, Copilot and friends. We wrote a complete Claude Code guide — which is, in effect, the manual for using these tools without surrendering to the vibes.