Code Review
Architecture, data models, dependencies, duplicated logic, unfinished paths, tests, and security-sensitive areas.
AI Code Review
Find out whether AI-generated code is usable, risky, or quietly unfinished.
AI-generated code can look complete while hiding architecture gaps, security problems, brittle logic, weak tests, missing platform behavior, and deployment failures. HerbDev reviews both the code and the operational system around it.
Request an AI Code ReviewCommon AI Code Risks
The problem is often not one bad file. It is missing engineering discipline.
Compile without being maintainable
Contain duplicated logic
Hide security problems
Use inappropriate dependencies
Lack error handling
Invent APIs or methods
Mix architecture patterns
Omit required platform behavior
Produce weak tests
Leave unfinished placeholder code
Create inconsistent data models
Expose secrets
Fail during production deployment
Operational Review
Environment configuration, deployment assumptions, secrets handling, logs, build steps, database setup, and rollback risk.
Plain-English Findings
A prioritized explanation of what is safe, what is fragile, what should be repaired, and what may need to be rebuilt.