Ten vibe coding mistakes that appear when an app gets real customers

Published on 2026-10-27 by frfrand

The 10 most common mistakes when taking an AI-built application to production and how to detect them before losing data.

Ten vibe coding mistakes that appear when an app gets real customers

Why a beautiful app can fail on day one?

Vibe coding makes it possible to turn an idea into a functional interface very quickly. Speed is an advantage, not a flaw. Problems arise when the appearance of the demo is confused with reliability guarantees. The question is what happens when charging, saving information, restarting the server, or receiving multiple simultaneous requests.

The ten problems worth looking for

1. Simulated data: the dashboard shows figures in arrays; there is no persistence. 2. Public secrets: API keys in JavaScript. 3. Visual-only permissions: hiding buttons without protecting endpoints. 4. No restorable backups: saving data without a recovery path. 5. Manual deploy without history: overwriting files and not knowing how to go back. 6. API without limits: one user can saturate or consume resources. 7. Improvised sessions: insecure tokens or incorrect expiration. 8. Emails and webhooks without retries: silent loss of operations. 9. Lack of logs: no one understands the failures. 10. No operational owner: an outage goes unanswered.

Example: data from another company at one click

An AI-generated SaaS for reservations is nice. Company A's interface does not show Company B's customers; however, when requesting a resource via a legitimate URL with another identifier, the API returns someone else's record. The solution is not to change CSS: the API must validate the identity and ownership of the data. I wrote two tests, one authorized and one forbidden. If the second obtains private information, it is not published.

Review plan in one work week

1. Inventory real data, accounts, payments, and services. 2. Review access to resources, secrets, dependencies, and file uploads. 3. Remove business mocks and implement transactions. 4. Prepare backups, logs, and monitoring. 5. Automate build and deployment with staging. 6. Rehearse rollback before the first charge.

Frequently asked questions

### Is every AI project insecure? No. The result is evaluated with the same criteria as manually written software. ### Does a more powerful VPS fix it? No: power does not fix authorization or transactions. ### Do I have to rewrite everything? Not necessarily; prioritize failures according to impact and exposure. ### What is the most useful test? A complete business action and an access denied check with another user.

Sources

OWASP Top 10 · GitHub Actions.

Where ArduMaker Fits In

The VPS or ArduMaker services can be the destination for exported code if the architecture allows it, along with domain, HTTPS, and operational processes. But migrating the app does not automatically fix its bugs, permissions, or data design. At ardumaker.com/lovable (coming soon) the specialized service for migrating AI-generated code and converting it into a deployed application with technical review will be presented. The page has not been created yet: for current information, check ArduMaker.

Review: October 2026. Each platform and its export modalities change. Validate official sources and work on staging with test data.

What the photograph shows

Developer debugging an app before launch. Illustrative photograph generated for this article about taking code created with AI to a production application; it is not an official capture of the tool nor does it demonstrate a specific implementation.