The Uncomfortable Truth About AI-Assisted Development

AI-generated code contains 1.7 times more issues than human-written code, particularly in logic errors, security vulnerabilities, and performance problems. While AI coding assistants increase development velocity, they also lead to a significant increase in production incidents due to the code’s tendency to pass shallow tests but fail on edge cases. Effective mitigation requires grounding AI models in context, automating quality checks, and treating AI output as untrusted.