Common symptoms
- - Code works in dev but fails under realistic production traffic
- - No clear ownership boundaries between generated modules
- - Security controls are inconsistent across routes and services
- - Refactors keep breaking existing behavior
Pre-release quality control
AI Code Review Checklist Before Production
A practical checklist to detect hidden issues in AI-generated code before they become outages, incidents, or expensive rework.
Business risks
- - Urgent bug-fixing cycles that slow down roadmap delivery
- - Higher incident probability during launches or traffic peaks
- - Rising cloud and engineering costs from patch-based fixes
- - Team confidence drops as code quality becomes unpredictable
How AI2H handles it
- - Map critical user journeys and rank failure impact
- - Audit auth, data access, API boundaries, and dependency risks
- - Refactor high-risk modules for readability and ownership
- - Harden deployment path with production guardrails
Expected outcomes
- - Clear go / no-go view before production release
- - Reduced regression risk during updates
- - Faster onboarding for developers maintaining the codebase
Need a fast diagnosis on your codebase?
AI2H helps teams convert fragile AI-generated code into secure, scalable, maintainable production systems.