AI usage generates a fragile codebase

A former Meta engineer argues that heavy reliance on AI for coding generates fragile, low-quality codebases that create long-term technical debt. While AI excels at solving isolated problems within its context window, it fails to consider broader architectural implications, writing shallow tests, overly complex code, and missing scalability issues critical for large-scale SaaS applications.