Few words have spread as fast in the AI world as "vibecoding". In less than a year it went from an offhand remark to one of the industry's most used terms. But what does it actually mean – and why is everyone talking about it?
Where the term came from
The expression was coined in early 2025 by Andrej Karpathy, one of the more influential voices in AI. He described a way of building software where you "give in to the vibes" – letting the AI write the code while you steer with words and intuition, rather than reading every line.
It captured something many already felt: that the bar for building something had shifted dramatically. Writing software used to mean knowing a language, a framework and the dozens of small conventions that hold a project together. Vibecoding moves that effort into the conversation. You say what you want, and the model handles the syntax.
What it actually means
In practice, vibecoding means you describe what you want in plain language, the AI generates the code, and you iterate by reacting to the result – "make the button bigger", "add login" – instead of writing it all yourself.
The loop is the point. You are not planning the whole thing up front and then building it. You are reacting to something real on the screen, noticing what is wrong or missing, and asking for the next change. The model keeps up, and the gap between an idea and a working version of it shrinks from weeks to an afternoon. That changes who gets to try things. When a rough version costs an afternoon instead of a sprint, far more ideas are worth testing, because the cost of being wrong is small.
The effect is that more people can build. Someone with an idea but no developer background can get further on their own than ever before. It's part of why the whole field around AI – and the role of AI consultant – is so new and growing so fast.
What it looks like in practice
Picture someone in operations who is tired of tracking supplier orders in a shared spreadsheet. They open a vibecoding tool and describe it in their own words: a simple page where the team can log an order, mark it as shipped or delayed, and see everything due this week. A minute later there is something on the screen.
It is not right yet, and that is fine. The dates are in the wrong format, so they say so, and it changes. The list is hard to scan, so they ask for the late orders to show in red. They want a note field, then a way to filter by supplier. Each request is a sentence, each result is visible at once, and the tool takes shape by reaction rather than by specification.
None of this required opening a code editor or reading a line of what was generated. The person who knew the problem best built the first version of the answer, and they did it in the time it would have taken to write a brief for someone else.
What it means for teams and companies
For non-developers, this is the real shift. The people closest to a problem – in sales, finance, support, operations – are often the ones who can describe the missing tool most precisely. Vibecoding lets them turn that description into something they can click on, without waiting in a queue for engineering time they were never going to get for a small internal need.
For companies, the bottleneck moves. It used to sit at the writing of code: ideas waited because there were only so many developers and only so many hours. When generating a first version becomes cheap and fast, the scarce skill is no longer typing the code. It is knowing what is worth building in the first place, and knowing what is safe to ship. Judgement becomes the constraint, not capacity.
That is a healthy shift, but it is not a free one. More people building means more things that work well enough to be tempting to rely on, and not all of them should be. The question quietly changes from "can we build this?" to "should this carry real weight, and what happens when it breaks?"
Where it fits – and where the line is
Vibecoding is hard to beat for exploring ideas, building prototypes and internal tools quickly. Where speed is everything and the margin for error is wide, it's enormously useful. A throwaway prototype that proves an idea is worth pursuing has done its whole job, even if the code underneath is rough. An internal tool used by five people who can shrug off the occasional glitch is a good fit too.
The line is drawn at what has to live in production – run every day, on real data, with real consequences. There the vibes aren't enough: it takes judgement about security, maintenance and what actually holds.
In production, the questions that vibecoding skips past become the whole job. How is customer data stored, and who can reach it? What happens under load, or when two people act at once, or when an input arrives that no one expected? When something breaks at two in the morning, can anyone understand the code well enough to fix it? Code that was never read by a person is hard to maintain, and "it worked when we tried it" is not the same as "it holds". Knowing which of these questions matter for a given tool, and which can wait, is exactly the judgement that does not come from the model. The technology makes the start faster; deciding what to harden, and how far, is still the work.
From prototype to something that holds
This is the part we enjoy. A promising prototype is a real asset: it proves the idea and shows what people actually want. Turning it into something that runs reliably, stays secure and keeps working as it grows is a different kind of effort, and it is the kind we do every day. If you have built something with vibecoding and want it to hold up in production, we'd be glad to talk it through with you.
