A working app in a few days, without a development team: that is the promise of vibe coding. You describe what you need in plain language, an AI tool such as Cursor or Lovable generates the code, and you steer it until it does what you meant. That promise mostly holds up. The question that actually matters to you is different: which kinds of projects is this a sound route for, and where does the risk start?
We can be honest about that, because we use these tools ourselves, every day, with software engineers who review every change before it goes live. We know both sides: what this way of working speeds up, and where it quietly breaks.
Where vibe coding proves its worth
Three situations come up again and again in practice. You want to test an idea before committing serious budget to it: a clickable prototype says more in a management meeting than twenty slides. You want to find out whether a small internal tool solves something, such as an overview that pulls three spreadsheets together, before anyone builds something lasting on top of it. Or the concept is settled, but you want to get a feel for how it works before anyone draws up an architecture.
These situations have something in common: the scope is small, the users are colleagues and the result is allowed to be unfinished: you build to learn, not to keep it running. Internal users know the context, forgive a rough interface and tell you within a day what needs fixing. That is exactly where speed is worth more than polish.
Where the line sits
The line sits where the consequences of a mistake outgrow the experiment. Does the application handle customer data or personal data? Does a business process depend on it? Will customers use it? Then vibe coding is not the right approach. AI-generated code looks convincing and runs flawlessly in a demo, but security, error handling and maintainability do not show on the surface. Without someone with the right expertise reviewing it, you do not know what is missing, and you only find out once it goes wrong.
That is not an argument against AI tools, but against skipping craftsmanship. You can read how the two relate to each other in the difference between vibe coding and traditional programming.
Five questions as a decision framework
Not sure about your own project? These five questions cut the choice down to its essentials.
- Is the scope small and clearly defined?
- Are the users internal colleagues who give feedback quickly?
- Is this a first version to learn from, not a final product?
- Does speed matter more than robustness at this stage?
- Is there room to invest in a solid technical foundation later?
If you answer yes to most of these, vibe coding is a fine starting point. But not every question carries the same weight. As soon as customer data or a business-critical process is involved, that one no outweighs four yeses.
When the prototype gets serious
A pattern we regularly see when reviewing vibe-coded tools: a tool built for one team turns out to be useful, spreads through the organisation and, over time, ends up holding data nobody thought about at the start. The requirements shift on their own: from working to secure, from demo to something your organisation leans on daily and someone else can build on. Those are engineering questions, and no prompt answers them.
Do you have a prototype like that outgrowing what it was meant for? You do not have to throw it away. Our engineers assess what is there, strengthen the foundation and turn it into software that can handle daily use. You can read how we approach that on our ongoing development and maintenance page.