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“I can build my app myself with AI, it won’t cost me anything.” That is the objection I hear most often. And it is partly true: with Lovable, Bolt, v0 or Cursor, you can get an app that works on screen in a weekend. For testing an idea, that is great, and I recommend it.
So the real question is not “can it be done?” but “what happens the day this app becomes important to your business?”
What AI does very well
- Screens: forms, lists, dashboards, in a few minutes.
- Prototypes: showing an idea to your team or your clients before investing.
- Simple internal tools: a small tool for one or two people, with no sensitive data.
- Speed: within a few hours, you know whether the idea holds up.
What it does badly without supervision
Screens are the visible part of an app. The rest is invisible, and that is where AI-generated apps run into trouble:
- Data access: who can read, edit or delete what? One badly set rule, and a user sees someone else’s data.
- Security: API keys exposed in the browser, checks done only on screen and not on the server.
- Edge cases: the client with no email address, the zero-value invoice, two people editing at the same time.
- Payments and compliance: refunds, compliant invoices, GDPR.
- Longevity: as requests pile up, the AI does not keep the whole history of the project in mind. Every fix can break an existing feature.
- Search visibility: an app rendered in the browser can look almost empty to Google.
My experience: my own website
My previous website was an app generated with Lovable. It looked good, was quick to build, and had every feature I wanted. It also had an invisible flaw: to Google, every page was an empty loading screen, with the same title and the same canonical URL everywhere. Months of content, almost impossible to find.
I rebuilt it as a static website, page by page. I have nothing against these tools, I use them, but I now know exactly where they stop.
The real cost of “free”
| Item | Doing it yourself with AI | Getting professional support |
|---|---|---|
| Tools | Subscriptions and credits, which rise with usage | Included in the service |
| Your time | Often dozens of hours of prompts and testing | A few hours of workshops and approvals |
| Security and data | Up to you to check | Designed and checked from the start |
| When it breaks | You, on a Monday morning | A professional who knows the code |
| Improvements | Risk of regressions with every request | Development in tested batches |
The biggest item is your time. Forty hours spent talking to an AI, valued at your hourly cost as a business owner, often add up to the price of a supported project, without any guarantee of the result.
Three possible paths
- On your own with AI: ideal for a prototype, a personal tool or a market test. Keep it away from sensitive data and payments.
- On your own, but supported: you build with AI, a developer sets up the architecture, reviews security and gets you unstuck. You keep most of the work and the budget.
- I take it from here: you have validated the idea with your prototype; it serves as the requirements document for building a solid, secure and maintainable version. Because the need is already clear, the project moves faster and costs less.
The checklist: is your AI app ready for production?
Tick each item honestly. Below 8 out of 10, your app is not ready for real clients or sensitive data.
My advice: use AI to test your idea, it is the fastest and cheapest way. As soon as the app touches your clients, your data or your revenue, have it reviewed, or have it rebuilt properly. And rest assured: I use AI to develop too, that is what allows me to offer the prices I display.