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Vibe Code Cleaning for AI-Generated Apps

You built it with Lovable, Bolt, Replit, Cursor, or ChatGPT. It works. Now make it secure, maintainable, and production-ready without a full rewrite.

Sound familiar?

This is what happens when you build fast with AI tools. The app works. The code underneath isn't ready for the real world. That's what I fix.

What I Do

I take your vibe-coded app - built with Lovable, Bolt, Replit, Cursor, or plain ChatGPT - and turn it into something production-ready. Structured code, proper error handling, security basics covered, tests in place, and documentation your next developer can actually work with.

Starting at

$2k

Typical range: $2k–$6k

Get my code audit

What's Included

  • Code audit - full review of what was generated, what's broken, what's risky
  • Security pass - secrets moved to env vars, auth logic reviewed, input validation added
  • Refactoring - duplicated logic consolidated, modules structured consistently, dead code removed
  • Error handling - try/catch coverage, proper error logging, user-facing error messages
  • Test coverage - critical paths covered so you can deploy without holding your breath
  • Documentation - README, architecture notes, and inline comments so future developers can work on it

Signs your app needs cleaning

API keys or secrets visible in the codebase
No tests - you can't change anything without fear
Developers you hire refuse to touch it
Errors crash the app instead of being handled gracefully
No logging - you don't know when things break
The same logic is copy-pasted in five different places

Process

1

Audit

I review the full codebase and deliver a written report: what's risky, what's broken, what can stay, what needs to change.

2

Refactor

I fix the issues in priority order - security first, then structure, then tests, then docs. You see progress in stages.

3

Handoff

You get clean code, a documented architecture, and a developer-ready codebase. I walk you through what changed and why.

Deliverables & timeline

  • Within 2 business days: audit report with prioritized risk list and fix plan
  • Week 1: security fixes, secret handling, auth and validation hardening
  • Week 2+: refactor critical modules, add tests for high-risk flows, improve logging
  • Handoff: PRs, architecture notes, runbook, and walkthrough call

Typical engagement: 1-3 weeks depending on codebase size and risk level.

Case Study

Lovable + manual ChatGPT SaaS, 3-person founding team

Booking platform - 9k lines of AI-generated code, first paying customers incoming

A founder team had built a service booking platform using Lovable and ChatGPT over 3 months. It was live, had 40 beta users, and was about to launch publicly. But their first developer hire looked at the codebase and quit on day one. They came to me two weeks before launch.

What I found:

  • Stripe secret key hardcoded in a frontend component, visible to users
  • Auth middleware generated by Lovable had a logic flaw - any user could access any booking
  • No error handling - a failed payment just showed a blank screen
  • The same booking validation logic existed in 6 different files with slight variations
  • Zero test coverage, no logging, no way to know when something broke in production

What I delivered:

  • All secrets moved to environment variables, Stripe key rotated before launch
  • Auth logic rewritten and tested - booking access properly scoped per user
  • Payment flow with proper error handling and user-facing messages
  • Validation logic consolidated to a single shared module
  • 70% test coverage on critical paths, error logging with Sentry
  • Architecture doc and README so the next developer could onboard in a day

Outcome:

  • Critical security and auth risks fixed before public launch
  • Cleanup completed in 5 days for launch deadline
  • Codebase stabilized for developer handoff and ongoing feature work

Related services and resources

Get Started with Vibe Code Cleaning