AI Code Not Working? I'll Fix It.

Expert refactoring for ChatGPT, Claude, and GitHub Copilot generated code

Common AI Code Problems I Solve Daily

  • "It worked in ChatGPT but not in production" - AI often ignores edge cases and real-world data
  • "I don't understand what this code does" - Overly complex solutions to simple problems
  • "The code runs but it's incredibly slow" - AI rarely considers performance implications
  • "Security scan flagged multiple vulnerabilities" - AI frequently generates insecure patterns
  • "Can't add new features without breaking everything" - Zero architecture, poor separation of concerns
  • "Tests are failing or don't actually test anything" - AI-generated tests that provide false confidence

How I Transform Your AI-Generated Code

1. Understand & Document

First, I figure out what your AI code actually does (vs. what you wanted it to do) and document it clearly.

2. Identify Critical Issues

Security vulnerabilities, performance bottlenecks, and maintainability problems get flagged immediately.

3. Refactor & Optimize

Restructure the code following best practices, remove redundancy, and implement proper patterns.

4. Test & Validate

Add real tests that actually verify functionality, not just AI-generated assertions that always pass.

5. Knowledge Transfer

I'll explain what went wrong and teach you how to get better results from AI tools in the future.

AI Platforms I Work With

I refactor and fix code generated by all major AI coding assistants:

  • ChatGPT (GPT-4/GPT-3.5) - Often generates outdated patterns and missing error handling
  • Claude (Anthropic) - Usually better but still needs production hardening
  • GitHub Copilot - Autocomplete that creates technical debt
  • Google Bard/Gemini - Inconsistent quality, needs heavy refactoring
  • Amazon CodeWhisperer - AWS-focused but often overengineered

Languages & Frameworks I Fix

Backend

  • Ruby on Rails
  • Python (Django/Flask)
  • Node.js/Express
  • RESTful APIs
  • GraphQL

Frontend

  • React/Next.js
  • Vue.js
  • JavaScript/TypeScript
  • Hotwire/Stimulus
  • HTML/CSS

Databases

  • PostgreSQL
  • MySQL
  • Redis
  • MongoDB
  • Query optimization

Real Examples of AI Code Issues I've Fixed

  • Rails N+1 Query Disaster: ChatGPT code making 10,000+ database queries - reduced to 3
  • React Memory Leak: Claude-generated useEffect causing browser crashes - properly cleaned up
  • SQL Injection Vulnerability: Copilot autocomplete creating security holes - parameterized queries
  • Python Performance: Bard code taking 5 minutes to process - optimized to 2 seconds
  • JavaScript Promise Hell: GPT-4 creating unmaintainable async code - refactored with async/await

Stop Fighting with AI-Generated Code

Get your AI code professionally refactored into production-ready, maintainable solutions.

Get Help With Your AI Code →