Vibe coding cleanup services: audit, fix and stabilise your AI-built app

AI app builders are very good at the first 80%. The trouble starts later: a feature that worked last week stops working, every new prompt breaks something else, the app works in preview but not on your domain, or someone tells you your database can be read by anyone. If you have typed "my AI app not working" into a search bar late at night, the work so far is usually not wasted.

This service is for when the code exists but you no longer trust it, and you want someone to say honestly what is wrong and fix it in an order that protects your users first. If your app works and you mainly need it launched properly, with payments, a custom domain and email, that is my Lovable and Bolt app to production service. If you have only an idea and want to plan before building, see app idea to product.

AI tools write code that runs in a demo. They are weaker at what a demo never tests: a second user, a malicious user, a retry, a large table. These are the AI generated code problems I look for, roughly in order of damage:

• Exposed API keys. Secret keys for OpenAI, Stripe or a database admin account placed in the browser code, where anyone can read them. Some keys are designed to be public; an admin or service key never is.
• Database rules left open. Tables with no row-level access rules, or with rules that let every logged-in user read every row. Database rules still in test mode. Storage folders set to public with customer documents inside.
• Auth only in the frontend. Pages hidden behind a login screen, but their data returned to anyone who calls the API directly.
• No server-side validation. Prices, quantities and discount codes checked in the browser only, so a user can edit the request and pay what they like.
• AI features called from the browser. A chat box or summary feature that calls the OpenAI API straight from the page, with the key visible and no limit per user. I move these calls to the server, as in my OpenAI and ChatGPT integration work.
• Duplicated logic. The same rule written three times, slightly differently, because each prompt solved it from scratch.
• No error handling. Failures swallowed silently, or raw database errors shown to users. Nobody is told when a payment webhook fails.
• N+1 queries. One database query per row on a list page: fine with ten test records, painfully slow with two thousand.
• No tests and prompts that loop. Nothing checks that login still works after a change, so the AI fixes one bug, breaks another, then reverts its own fix.

A messy codebase costs you time. An open database costs you customers, and in some countries it creates a legal duty to report a breach. So the report separates AI generated code security issues from everything else and marks each finding as critical, important or tidy-up. Critical items, such as a readable customer table or a live payment key in the browser, are fixed or switched off first.

I check how the app behaves, not just how the code reads. That means logging in as two different test users and trying to read each other's data, calling the API without a login, changing a price in the request, and uploading the wrong kind of file. Most broken access control is invisible in the code until you try it. If you want to run a first pass yourself, my vibe coding security checklist has thirty checks you can do without writing code.

Most AI-built apps do not need a rebuild. The screens are usually fine, and the problems sit in a few places: rules, auth, payments and error handling. Fixing those is far cheaper than starting again.

A rebuild of the backend makes sense in a few cases: the data model cannot represent your business without constant workarounds, money or stock moves through logic that cannot be made reliable where it lives, or the app needs integrations, scheduled jobs and reporting beyond what the current setup handles well. Then I rebuild the backend properly in Laravel and MySQL, my daily work, using the same transactions and locking as my export operations ERP, with a documented API for the screens to call. The screens themselves stay with your AI tool or a frontend developer. The report states which route I recommend and why, and you decide.

Be careful with anyone who calls themselves a vibe code fixer and promises a perfectly secure app in a weekend. No honest audit can prove an app has no flaws. It can find and close the common, serious ones, and add checks so new ones are noticed.

I should also be clear about what I bring. I am a backend engineer: PHP 8, Laravel and MySQL are my core tools, and I work with REST APIs, webhooks, application security, the OpenAI API and Linux deployments in production. I use AI coding assistants in my own work. I am not a frontend developer. I follow the generated screens only to see what they send to the server and what they trust, and I fix the server side. If your main problem is visual design or complex screen behaviour, a frontend developer is the better hire, and I will say so. As a vibe coding cleanup specialist, my value is in the parts that hurt when they fail: data, access, money and deployment.

You will probably keep building with AI after I finish, and the handover is designed for it. Your code lives in your own GitHub repository, so every AI change can be reviewed and undone. A short rules file your AI tool reads with every prompt lists what must not change: access rules, the payment flow, where secrets live. Tests on the critical paths catch a prompt that breaks login before your users do.

Vibe code repair is rarely a one-off. A few monthly hours for reviewing changes before they go live costs far less than a second cleanup. Ongoing work can run on the same terms as my maintenance and support plans.

I do not publish prices, because two apps that look alike can differ several times in effort. The audit is quoted on its own first. The main cost drivers are:

• The number of screens, tables, user roles and connected services
• How many critical findings there are, and whether data has already been exposed
• Payments, file uploads, AI features or third-party API integrations
• Fix in place or rebuild the backend, which the audit decides