Vibe Code Janitor
Vibe Code Janitor | EARNST
Vibe coding ships fast -- but is it production ready? We make code from Cursor, Copilot, and Claude deployment-ready.
What this service does
Vibe Code Janitor transforms vibe coded prototypes into production-ready systems. Vibe coding with Cursor, GitHub Copilot, and Claude generates functional code fast, but that code often lacks proper error handling, security measures, tests, and documentation. It works as a demo but breaks in production. We audit the codebase, identify technical debt, fix critical issues, add tests, and document how everything works.
This is not about rewriting everything from scratch. It's surgical improvement: fixing security vulnerabilities, adding error handling, improving performance bottlenecks, writing tests for critical paths, and documenting architectural decisions. The goal is making vibe code maintainable, debuggable, and deployable with confidence.
Who needs this?
CTOs and development teams using AI coding assistants to build quickly but facing deployment anxiety. Common scenarios: you built a working prototype with Cursor but don't trust it in production, your AI-generated codebase has no tests, you're getting runtime errors you don't understand, or you need to hand off the project but there's no documentation explaining how it works.
Typical clients: startups with AI-built MVPs approaching launch, agencies who used AI to accelerate client projects, product teams who prototyped with Claude and now need to deploy, companies with junior developers using Copilot who need senior oversight. If you're asking "is this code safe to deploy?" the answer is probably not yet, and that's exactly what we fix.
How EARNST approaches it
We start with a comprehensive audit: running the application, reading the codebase, checking dependencies, looking for security issues, identifying architectural problems. We then create a prioritized list of issues categorized by severity: critical (security vulnerabilities, data loss risks), high (bugs that will cause production failures), medium (technical debt that will slow future development), and low (nice-to-have improvements).
The refactoring process is systematic: fix critical security issues first, add error handling and logging, write tests for essential functionality, improve performance where necessary, and document key decisions. We don't chase perfection. We aim for "good enough to deploy confidently and maintain efficiently." Every change is version controlled, tested, and explained.
Project scope
A typical Code Janitor engagement takes 2 to 4 weeks depending on codebase size and quality. This includes initial audit (1 to 2 days), critical fixes (security, major bugs), test coverage for core functionality, performance optimization if needed, and documentation. Very small projects (single page apps, simple scripts) can be reviewed in 3 to 5 days. Large, complex systems may require 6 to 8 weeks.
We deliver a detailed audit report highlighting what we found and what we fixed, a refactored codebase with version control history, automated tests, security hardening documentation, and deployment guide. Ongoing support is available on a monthly retainer basis for teams who want continued oversight of AI-generated code.
Typical Results
70%+
Test coverage after Code Janitor engagement
0
Critical security issues after audit
100%
Documented, maintainable code
What you get
Code Audit & Report
Comprehensive review of security issues, bugs, and architectural problems.
Refactoring Plan
Prioritized list of what needs fixing and why it matters.
Test Suite
Automated tests covering critical functionality and edge cases.
Security Check
Vulnerability scan, dependency audit, and security hardening.
Technical Documentation
Architecture overview, setup guide, and deployment documentation.
“You give him problems - he gives you a whole menu of solutions!”
Stefan Markov
Co Founder, ZeroBS Agency
Frequently Asked Questions
Which AI tools do you work with?
Cursor, GitHub Copilot, Claude (Code and Artifacts), ChatGPT, v0, Bolt. We know the typical patterns and problems each tool produces and what to watch out for.
How much does a code audit cost?
Code audit for small codebases (under 10k LOC): from 2,500 EUR. Larger projects 5,000 to 12,000 EUR. Refactoring and test implementation quoted separately. Fixed price after initial consultation.
Do you do the refactoring or just consulting?
Both. We can deliver the code audit as a report only (your team implements) or handle the complete refactoring. Often we fix the critical issues and your team works through the medium priorities.
How does ongoing code review work?
We review pull requests before they are merged, similar to a senior engineer on your team. Via GitHub/GitLab integration, with comments directly in the code. Monthly package or per PR.
Is AI-generated code really that bad?
Not bad, but unreliable. AI produces functional code but misses edge cases, security best practices, and long-term maintainability. Fine for prototypes, not for production with real users.
Ready to discuss?
Tell us about your project. We will get back to you within 24 hours.