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. It generates code that looks right in isolation and breaks under real conditions.…