Running a Vibe-Coded App in Production: Maintenance, Scaling and Security Risks

How do you maintain and scale a vibe-coded product once real users arrive?

Pause new features, put the code under version control with separate environments and working backups, then add monitoring and tests around sign-up, payments and data access. Fix the security basics next, and only then refactor and optimise, one area at a time, based on what monitoring tells you. Most vibe-coded apps don't need a rewrite; they need the missing engineering around them.

Why the first real users change everything

A prototype only has to work when you click through it. A production app has to work when a hundred people do unexpected things at once, when a payment fails, when someone pastes an emoji into a name field, and when you change one screen without breaking three others. Vibe-coded apps tend to look finished long before they are, because AI tools are good at producing the happy path and poor at telling you what they left out.

The good news is that the fixes are well understood. The order matters more than the techniques.

Phase 1: Stabilise (first one to two weeks)

1. Freeze features. Every new feature added to an unstable codebase makes the next fix harder. Tell users you are improving reliability; most will be glad.
2. Get everything into Git with a single main branch, and stop editing code directly on the server or in a hosted builder without committing it.
3. Separate environments. At minimum a development or preview environment and production, each with its own database and keys, so testing never touches real customer data.
4. Check backups now, not later. Find out exactly what your provider backs up. Supabase's documentation, for example, says Pro, Team and Enterprise projects get automatic daily backups (retained for 7, 14 and up to 30 days respectively) and recommends that free-plan projects regularly export their data themselves. Then do a test restore.
5. Move secrets out of the code into environment variables, and rotate any key that has ever been committed or pasted into a prompt.
6. Write down what exists. A one-page map of the main features, data tables, third-party services and who has admin access. AI tools can help draft this from the code, but check it by hand.

Phase 2: Make problems visible (weeks two to four)

• Error tracking on both the front end and the server, so you hear about crashes before users email you.
• Uptime checks on the home page, the login and one key API route.
• Structured logs for sign-in, payment and permission events, with no passwords or personal data in them.
• Tests around the money and the data. You don't need full coverage. Start with end-to-end tests for sign-up, login, the core action users pay for, and checkout, plus tests proving one user cannot read another user's data.
• Continuous integration that runs those tests and a type check on every change before it reaches production. Our guide to a modern web development workflow shows how this fits together.

Phase 3: Pay down technical debt deliberately

Vibe-coded apps often contain the same logic written three different ways, because each prompt produced a fresh solution. Refactor in small, tested steps: consolidate duplicated data-access code first, then shared validation, then UI components. Resist the urge to rewrite everything in a new framework; a rewrite throws away the bug fixes hidden in the current code and usually takes longer than expected.

Phase 4: Scale where the data says to

Most early apps hit database limits before anything else. Look at your slowest queries and add indexes for the columns you filter and join on. If you use Supabase row-level security, its documentation advises adding an index on every column your policies filter on, and wrapping helper calls such as auth.uid() in a select so Postgres evaluates them once per statement rather than once per row. Move slow work such as emails, imports and AI calls into background jobs, and cache pages that don't change per user. For the wider picture, see our guide to scalable web application architecture.

Using AI to maintain AI-written code

AI coding tools are useful in every phase, as long as a person stays responsible for the result. Anthropic's Claude Code documentation recommends giving the agent a check it can run, such as tests, a build or a screenshot comparison, and separating exploration and planning from implementation. In practice: ask the agent to explain a module before changing it, ask for a plan, review the plan, then have it make the change with tests and show you the test output. A second review in a fresh session catches more than the session that wrote the code.

When a rebuild really is the right call

Occasionally the honest answer is to rebuild: when the data model is fundamentally wrong for the product, when the app is locked inside a builder you cannot export from, or when every fix breaks something else and there are no tests to tell you what. Even then, keep the current app running and migrate in stages rather than switching over in one weekend.