There’s a good chance someone in your organisation is already using vibe coding tools. A marketer putting together a campaign tool with Lovable, an analyst getting ChatGPT to write code for a report, a developer working in Cursor without anyone ever deciding it was allowed. The question is no longer which tool is best. The question is on what grounds you approve one.
That distinction matters. Which tool leads the pack changes every quarter; the criteria you judge them by hold up for years. So instead of a ranking, here is an assessment framework that still works when the tool landscape looks different next year.
Four types of tools, four risk profiles
The term vibe coding covers quite different tools. AI editors and assistants such as Cursor and GitHub Copilot support a developer who still sees and reviews the code themselves. Generation platforms such as Lovable and Bolt turn a plain-language description into a complete web application. Replit combines generating, testing and hosting in the browser. And chat tools such as Claude and ChatGPT produce individual pieces of code that someone then deploys somewhere else.
As the decision-maker, what matters most is who is checking the work and where the result ends up. An AI editor in the hands of an experienced developer stays within your existing quality control. A platform that lets a colleague without a technical background generate an application and put it live straight away bypasses that same control entirely. Same label, a completely different risk.
Code ownership comes first
The main difference with classic no-code platforms is that vibe coding tools produce actual source code. That advantage only holds if you can take that code with you. Check whether you can export the code, host it elsewhere and have another party continue developing it. A tool that locks the code inside its own environment is functionally a no-code platform, with the same vendor lock-in: you’re tied to the supplier, its pricing and its continued existence.
Security is about data flows, not just code
Two questions determine the security picture. Where do your prompts, code and data go, and does the supplier train its models on them? Anyone who pastes a customer file into a prompt is sharing personal data with an external party; GDPR applies in full. And how good is what comes back? Generated code is optimised to work, not to be secure. Authentication, authorisation and the handling of user input deserve review by someone who knows what to look for. You can read which mistakes come up most often in our article on the pitfalls that catch out even advanced users.
An approval framework in five questions
If you want to allow these tools in a controlled way rather than quietly tolerating them, hold every candidate up against the same yardstick:
- Who owns the generated code, and can we export it and host it elsewhere?
- Where are our prompts and our data stored, and are they used to train models?
- What data is allowed in? Customer data and business-critical information don’t belong in a prototype.
- Who reviews the code before anything runs with real users or their data?
- What happens to our applications if the tool shuts down, gets acquired or becomes significantly more expensive?
You reject a tool with no satisfactory answer to these not because AI is unreliable, but because it fails to meet the requirements you set for any supplier.
A tool, not a finished product
That’s how we see it too. Our engineers develop AI-assisted: the tools speed up the work, craftsmanship decides what makes it into production. For a prototype, a demo or a throwaway internal build, vibe coding is an excellent tool. For software that processes customer data or carries a business-critical process, it isn’t. That needs someone who can read, test and improve the generated code.
If a vibe-coded prototype starts to matter in your organisation, it doesn’t have to go back to the drawing board. We turn it into robust software: we review the code, close the gaps and put it on a foundation that can handle growth and maintenance. You can read what that step looks like at ongoing development and maintenance.