How to Take a Vibe-Coded App From Prototype to Production

AI tools like Lovable, Bolt, v0, Replit and Cursor can build a working app in days, but a working demo is not the same as a production-ready product. Before real users, data and payments arrive, you need to check security, database access rules, secret keys, error handling, testing, hosting and backups. Most AI-built apps need focused fixes rather than a full rebuild. A short code audit tells you which.

Quick answer: move secret keys out of the front end, lock down database access on the server, add proper login and password reset, test payments and errors, set up monitoring and backups, then launch.

Why AI-built apps break in production

AI coding tools optimise for something that works on screen. They often skip the parts users never see, such as server-side permissions, input checks and error handling. Common problems include:

• API keys and secrets exposed in front-end code.
• Database tables readable or writable by anyone with the URL.
• Access rules that only hide buttons instead of blocking requests.
• No rate limits, so forms and APIs can be abused.
• Payments that succeed without updating the order or account.
• No tests, so every change risks breaking something.
• Hosting, environment variables and deployment that only one person understands.

Production readiness checklist

Security and access

• Store all secret keys on the server or in environment variables, never in the browser.
• Enforce permissions on the server or with database row-level security.
• Validate and sanitise every input.
• Add rate limiting to logins, forms and public APIs.
• Review third-party packages for known vulnerabilities.

Authentication

• Secure sign-up, login, email verification and password reset.
• Session handling and logout that work across devices.
• Roles and permissions that match how the business works.

Data and database

• Clear rules for who can read and change each record.
• Indexes on slow queries.
• Automatic backups and a tested restore process.
• A plan for migrating any data created during testing.

Payments and integrations

• Use payment webhooks to confirm payments before granting access.
• Handle failed payments, refunds and cancellations.
• Retry and log failures for email and third-party APIs.

Reliability and testing

• Automated tests for sign-up, login and payment flows.
• Clear error messages for users and error tracking for the team.
• Separate test and live environments.

Hosting and operations

• Reliable hosting with HTTPS and a custom domain.
• Uptime monitoring and alerts.
• A documented, repeatable deployment process.
• Legal pages: privacy policy, terms and cookie consent where required.

Fix or rebuild?

Situation	Usually best
Code is readable and the main features work	Fix and harden
Security issues are limited to keys and access rules	Fix and harden
Every change breaks something else	Rebuild key parts
Database design cannot support real use	Rebuild the data layer
The idea is still being tested with users	Keep prototyping, then harden

How much does it cost to make an AI-built app production-ready?

Our AI prototype to production service starts with a code audit for $199, delivered in 3 to 5 days with a prioritised fix list. Production hardening starts at $790 and usually takes 1 to 3 weeks. If parts need rebuilding, we quote after the audit, and the audit fee is credited. Larger products move into web application development from $3,490.

What the research says: Broken access control is the number one web application security risk in the OWASP Top 10:2025, and it is one of the most common gaps in AI-built prototypes, where hidden buttons are mistaken for real permissions. (Source: the OWASP Top 10:2025.)