Shipping features with Claude Code or Cursor is fast now. Getting that code to hold up in production is a separate problem entirely. AI reduces implementation time. It does not produce production engineering.

I went through 8 AI-generated production apps. They all had roughly the same issues:

Supabase RLS misconfigured

secrets sitting in the codebase

no rate limiting, no caching

bad data structures

components re-rendering constantly

AI features open to prompt injection and RAG attacks

basically no tests around anything important

Most of them worked. Hardly any were production ready.

A year ago, writing code was the bottleneck. Now it's reviewing and hardening what got generated. That's a different skill, and most teams aren't there yet.

The reason this keeps happening: AI is excellent at extending local patterns. It's much worse at understanding long-term system boundaries, scaling behavior, and operational risk.…