8 min readvibe-coding · ai-workflow · building

Vibe coding — what it is and when it makes sense

Vibe coding is coding with AI where you don't read every line carefully. When it's a brilliant move, when it's a bad idea — and how to use it safely.

The term "vibe coding" was coined by Andrej Karpathy in early 2025. He described how he codes with Claude Code and Cursor without actually reading a single line: describe what you want, accept what appears, if it works keep going. Vibe.

Opinions split. Senior devs grimaced: "Irresponsible, scrambles the codebase, creates supply chain issues, doesn't survive production." Junior devs and founders cheered: "Finally I can build things that used to require a team."

Both are right. Vibe coding is fantastic in certain situations and destructive in others. The question is when which.

What vibe coding actually is

Let's get specific. Vibe coding is NOT just "AI helps me code." Classic AI-assisted coding is:

Dev writes a function. AI suggests lines. Dev reads, accepts, edits. Dev understands every line.

Vibe coding is:

Dev describes the outcome. AI builds. Dev runs it, sees if it works. If it works, continues. Dev doesn't read every line and might not understand the details.

The core of vibe coding is a leap of faith: you trust the AI without verifying. This is new — and that's why reception is divided.

When vibe coding works

Vibe coding makes sense in these situations:

1. Prototypes and demos

If you're building something to show a customer, an investor, or yourself to see what the idea looks like — vibe rocks. You don't need production-grade code, you need an impressive mockup. 80%-correct AI code is enough.

2. Internal tools

A small script that processes a CSV. A webhook handler that reformats data. A cron job that posts to Slack. These don't touch customers, cost little, and if they break you fix them next week.

3. Familiar territory where you're just lazy about typing

You've written a hundred React components before this one. You know what good looks like. AI produces the skeleton, you skim and spot anything weird. This is efficient, because you understand the domain — you just delegate the typing.

4. One-off bugfixes you don't want to dig deep into

The log shows a strange error. You want a quick fix. AI says "this is typically X, try Y." You try. If it works — bonus. If not — you dive in for real.

When vibe coding is a disaster

The risks are especially big in these situations:

1. Payment processing, authentication, encryption

No code that involves money or access rights should be vibe-coded. AI makes delicious bugs in these areas — like skipping input validation, leaving open redirects, mishandling SQL injection.

The last time I saw AI-built payment logic: it worked exactly right but skipped payment verification because "it's pointless in tests." The damage in production would have been a few thousand euros.

2. Security boundaries

Public-facing API endpoints. User input validation. File uploads. This is OWASP top 10 territory, and AI may write code that looks safe but is trivially exploitable.

3. Performance-critical code

Vibe code can do N+1 queries, leave caches empty, load entire tables into memory. At low volume this works fine. At a thousand users, the system crawls.

4. Code no one will read in six months

You forget. Someone joins the team. If the code lacks a comment explaining why something was done, the AI's "looked good at the time" code becomes a mystery. Vibe coding's worst outcome: a codebase no one dares change.

Practical rules for safe vibe coding

If you vibe-code — and you probably should sometimes, because it's fast — keep these in mind:

1. Don't ship vibe code to production without tests. Ask the AI to write tests, and READ them. Tests tell you what the AI thinks the code does. If the tests check something different from what you need, you know right away the AI is off.

2. Don't vibe-code security-critical areas. Payments, auth, user permissions, data sharing — read line by line. I'll say that again: line by line.

3. Do a regular "reading exercise." Every day, pick one file the AI changed today and read it properly. Don't skim — understand. This keeps you connected to the codebase, and you catch early when the AI starts writing in a strange style.

4. Use git history. Commit often, small commits. When something breaks, you can revert to a specific point. Vibe coding + git bisect = friends.

5. Don't fix the AI's mistake with another AI prompt forever. If the AI can't fix a bug in three tries, you fix it by reading the code. The endless "didn't get it this time, try again" loop produces more complex and less stable code each round.

6. Draw a clear line between "vibe areas" and "line-by-line areas." E.g., UI components = vibe ok. API routes = vibe ok if no money/permissions. Payment logic = never vibe. Auth = never vibe.

What Innovaidor does around vibe coding

Innovaidor isn't a coding tool — it's a concept sharpening tool. But the output is documents that travel to Lovable, Claude Code, or Codex. The very tools where you vibe-code.

In practice:

  1. In Innovaidor you define what you're building and why (BMC, Design Sprint, sparring)
  2. You get a handoff document: product description, MVP plan, user stories
  3. You take the handoff to Lovable or Claude Code
  4. During building you already know which areas are vibe-safe and which aren't, because you thought them through in the design phase

This is Innovaidor's whole point: if you vibe-code without a clear concept, you build the wrong thing extremely fast. Concept first, vibe later.

Closing

Vibe coding is a real superpower. It's also a real risk. The old "when will AI take a developer's job?" is still too abstract — the right question is when does AI-generated code cost you more than it saved.

The answer: when you use it in areas you didn't define ahead of time, didn't verify afterwards, and hope it works in production.

Don't hope. Think, then vibe — only when you can revert without regret.