Checklist: 30 checks before publishing an app made with Lovable or AI

Published on 2026-10-27 by frfrand

30 steps to launch an application created with Lovable, Bolt, Cursor or ChatGPT: security, backups, payments, DNS and rollback.

Checklist: 30 checks before publishing an app made with Lovable or AI

How to know if your AI app is ready to receive customers?

Not because a demo loads quickly. You need to check what happens with two users, after a restart, if email fails, and if a payment arrives twice. This checklist is a control guide to use in every release. It does not replace a specific audit, but it reduces surprises.

The 30 checks

Code and architecture: 1) own repository; 2) lockfile; 3) runtime version; 4) reproducible build; 5) dependencies and licenses reviewed; 6) separate environments.

Security: 7) valid HTTPS; 8) secrets outside Git and frontend; 9) backend authorization; 10) multi-user testing; 11) upload validation; 12) updated dependencies.

Data: 13) schema migrations; 14) scheduled backup; 15) tested restoration; 16) constraints and integrity; 17) logs without credentials; 18) retention and deletion rules.

Operations: 19) persistent services; 20) health check; 21) accessible logs; 22) alerts; 23) resource limits; 24) documented rollback.

Business: 25) form with real submission; 26) transactional email; 27) payment validated in backend; 28) idempotent webhooks; 29) DNS, redirects, and sitemap; 30) full journey from a mobile with a new account.

Example: launching a booking SaaS

You have 200 slots and a list of interested clients. In staging you load test data, register two users with different permissions, simulate purchases and verify concurrent slots. You restore a copy of PostgreSQL and check that the result matches the expected one. You prepare a rollback commit. On cutover day, you monitor latency and errors and keep the previous version available until stability is confirmed.

How to prioritize the checklist

Not all projects need everything with the same depth: a static landing page does not process payments or sessions, but it should have a good domain, certificates, speed and SEO. A financial or healthcare app requires additional security, privacy and compliance reviews. The criterion is real risk, not collecting tools.

Frequently asked questions

### Does this work if it is still a private demo? Yes as guidance, but the level of control is adjusted to data and exposure. ### Can AI do the checklist automatically? It can help review, but results must be verified and approved. ### What are the three priorities? Secure permissions, recoverable data and a reliable way to roll back. ### Do I have to repeat it with every update? Repeat at least the tests affected by each release, and critical ones periodically.

Sources

OWASP Top 10 · GitHub Actions · Google SEO Guide.

What about ArduMaker?

This work fits the idea of a service that reviews AI-generated code, implements what is necessary, and takes it to operable infrastructure. The future page ardumaker.com/lovable will present this migration and deployment modality. The page does not exist yet, so it should not be announced as an automatic service already available. For products that exist today you can visit ardumaker.com. The actual scope is determined with an audit: permissions, data, integrations, and maintenance.

Editorial review: October 2026. Official references prevail over generic examples; make a backup and staging tests before any intervention in production.

What the photograph shows

Team celebrating the production launch of a project. 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.