What Vibe Coding Really Is – and What It Isn't

The term appeared everywhere in a short space of time, and as usual with such terms, everybody now means something different by it. To some, vibe coding proves that software development has become trivial. To others it is a slur for prototypes nobody can maintain. Both camps are a little bit right and miss the same thing.

I work this way, so here is what I understand by it.

The simple definition

Vibe coding means: you describe what should come into being, and the implementation follows from that. You no longer primarily read code, you judge results. The place where the work happens shifts from syntax to intent.

That sounds like a detail and is not. It inverts the division of labour. The specification used to be the tedious prelude and the implementation the real work. Today the specification is the real work, and the implementation is what happens afterwards.

What it is not

It is not "knowing nothing about software". That is the biggest misunderstanding. Someone who cannot judge whether a data structure holds up, whether an interface is cut sensibly, or whether error handling actually handles the error, still gets something that runs. They just find out later that it is the wrong thing. Vibe coding lowers the cost of building, not the demands on judgement.

It is not "describe it once and you're done". It is a dialogue. Describe, look, correct, sharpen. Stopping at the first result means you did not run the process, you aborted it.

It is not a substitute for architecture. Quite the opposite: because so much comes into being so fast, structure decides a project's fate earlier than it used to. Poor data modelling now produces in two days the damage that used to take two months.

It is not a prototyping tool. It can be used for prototypes, but using it only for that gives away the larger part. The difference between a prototype and a product does not lie in how the code came about, but in whether somebody stands behind operations, security and maintenance.

What it really is

From my practice: vibe coding is above all a shift of the bottleneck.

Before, the bottleneck was implementation capacity. You knew fairly precisely what you wanted, and the question was when somebody would have time to build it. Prioritisation was therefore always a discussion about effort.

Today the bottleneck is clarity. The question is no longer when something can be built, but whether what should be built has been described precisely enough. And that is a more uncomfortable question, because it goes back to the client rather than to the development team.

You notice it immediately in projects. As soon as a question about the business is open – what happens in this edge case, which rule really applies here – the work stops. Not because the technology is missing, but because the decision is.

What this looks like day to day

A typical cycle for us has four steps, and three of them have nothing to do with code.

Understand. What should the thing do, for whom, under which conditions. What are the edge cases that only surface at the third round of questions.

Describe. Not in prose, but precisely enough to be unambiguous. Data structures, rules, expected behaviour at the edges.

Generate. The fast part. This is where the implementation comes into being.

Review. Does it run – and is it factually right? Two completely different questions. A test answers the first. Somebody who understands the subject matter answers the second.

Run this cycle as a whole and you get software in days that used to take months. Do only the third step and you quickly get something that looks like software.

Why I still like the term

It is imprecise, but it captures something true: that the mode of working has changed. You no longer think in implementation steps but in intentions and results. It genuinely feels different – more fluid, less mechanical.

What the term does not convey is the responsibility that remains. That is why I prefer telling clients how we work rather than what it is called: first we understand the business, then we build, then we put it into operation and stay responsible for it.

The next article is about the level above this: why most AI initiatives at SMEs fail not on the technology, but on the fact that nobody has an overall concept.