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Vibe coding: where it helps and where it breaks
Patrick Corn · 2026-05-03 · via DEV Community

Patrick Cornelißen

Vibe coding is one of those terms that sounds unserious until you notice how many people are actually doing it.

The basic idea is simple: describe what you want, let an AI coding tool generate the implementation, run it, adjust the prompt, and keep going.

It can feel magical. It can also go wrong very quickly.

What vibe coding is good at

Vibe coding works best when the problem is visible and forgiving:

  • small prototypes
  • internal tools
  • UI experiments
  • scripts
  • throwaway demos
  • first drafts of a feature

In those cases, speed matters more than perfect architecture. You can see whether the result works, and mistakes are usually cheap.

Where it breaks

The approach becomes risky when the code has to survive contact with real users.

Typical failure modes:

  • hidden edge cases
  • inconsistent state management
  • weak error handling
  • missing tests
  • security issues
  • duplicated logic
  • code that "works" but nobody understands

The danger is not that the AI writes bad code every time. The danger is that it often writes plausible code. Plausible code is harder to distrust.

The human job changes

With vibe coding, the developer's role shifts. You spend less time typing boilerplate and more time judging direction.

You still need to decide:

  • what should be built
  • which constraints matter
  • whether the implementation fits the architecture
  • which tests are missing
  • whether the code is maintainable

If you skip that judgment, the speed advantage turns into technical debt.

A better workflow

Vibe coding becomes more useful when it is paired with review loops:

1. Ask the AI to implement a small slice.
2. Run the tests.
3. Ask the AI to explain the changes.
4. Review the diff yourself.
5. Ask for tests and edge cases.
6. Refactor before moving on.

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The point is to keep each step small enough that you can still understand the result.

The real skill

The real skill is not prompting the model into writing more code. It is knowing when to stop and inspect.

Good questions:

  • What assumptions did the model make?
  • What happens when input is empty or invalid?
  • Which part of this code would be hard to change later?
  • Is there a simpler design?
  • Would I be comfortable reviewing this in a pull request?

If the answer is no, the workflow is moving too fast.

Bottom line

Vibe coding is useful as a creative and exploratory mode. It is not a replacement for engineering discipline.

Use it to get moving. Do not use it as an excuse to stop reading the code.


This article is based on the German original on KIberblick:
https://kiberblick.de/artikel/grundlagen/vibe-coding/