On paper, vibe coding and traditional programming seem to compete for the same job. The first route produces something that works in an afternoon; the second costs a development team weeks. Anyone who decides on software and puts the two side by side arrives at an obvious question: what are you still paying for with the second route?
The answer lies in what each approach actually is. With vibe coding, you describe what you want in plain language and AI generates the code, without anyone with the right expertise checking it line by line. With traditional programming, a developer writes and reviews the code themselves, making deliberate choices about architecture, security and maintainability. That sounds like a technical difference. It is mainly a difference in responsibility.
Working code is not the same as good software
An AI tool optimises for a result that works and looks plausible. That is not the same as software that fits your organisation. Whether login details are stored securely, whether the application holds up with ten times as many users, whether another developer will still understand the code in two years: none of that shows up in the demo.
That is where the real difference lies. A professional developer can explain every choice in the code to an auditor, a security specialist or a successor. With pure vibe coding, nobody can: the code exists, but the understanding behind it does not. That catches up with you the moment something breaks, data is exposed or a change is needed.
At its strongest when nothing depends on it
None of this makes vibe coding worthless; it defines where it belongs. For exploration, speed is a real advantage: testing an idea before you commit budget to it, a demo for a board meeting, a throwaway tool for a one-off job. If the prototype can be discarded afterwards, it has done exactly what it was for. Anyone who works with it directly soon notices that it demands more knowledge than the term suggests; we wrote earlier about why vibe coding doesn’t mean you don’t need to learn anything.
The line is drawn at customer data and processes people rely on
The decision framework we use ourselves is short. Choose professional development as soon as one of these situations applies:
- The application processes personal data or other sensitive information
- A business process starts to depend on it, such as invoicing, planning or order processing
- The software needs to last for years and be extendable by others
- You need to be able to account for it to a client, auditor or regulator
Hold a vibe-coded prototype up against these four points. If it touches none of them, you can keep experimenting with it without worry. If it touches just one, the prototype is the start of a project, not the end product.
How we work with it ourselves
We are not AI sceptics; our own engineers develop AI-assisted. When we explore an idea for an internal tool, we let AI generate a first working version in an afternoon. But the moment such a tool touches customer data or becomes part of our own workflow, it goes through the same process as everything we have delivered since 2001: architecture decisions made by an engineer, line-by-line review, tests and monitoring. AI speeds up the work. The craft around it decides whether the result is software you can rely on.
Has your vibe-coded project turned into something serious in the meantime? It doesn’t have to end up in the bin. We assess what is there, make it secure and maintainable, and then develop it further into fully fledged software. You can see what that step looks like on our ongoing development and maintenance page; with a specific question, you’re also welcome to come to us directly.