Fast code, slow thinking. That’s the real trap.

This resonates deeply. I've seen this exact pattern while building automation systems for clients — the initial AI-generated code ships fast, but when you revisit it 3 months later for a feature extension, you spend more time deciphering than you saved. What helped me was enforcing an "architecture-first" rule: before any AI generates a single line, I write a clear system design doc with module boundaries and naming conventions. The AI then works within those constraints rather than inventing its own structure. Curious — do you think architecture decision records (ADRs) could be a practical guardrail here?

This hits a real issue.

Vibe coding works great until you move from isolated outputs to systems. That’s where missing structure starts compounding, unclear data flow, hidden dependencies, and inconsistent behavior across components.

AI makes it easy to build fast, but it also makes it easier to skip the thinking that keeps things stable later.