AI writes code fast. But who checks the architecture?

We're in the age of AI-assisted coding. Claude Code, Cursor, Codex — these tools can build entire projects in hours. And they're getting better every month. But there's a problem nobody's talking about enough: AI coding tools don't think about architecture. They generate code that works. It passes tests. It compiles. But over weeks and months, your codebase quietly accumulates architectural debt that humans don't notice, and even AI code reviews miss — circular dependencies between services, data layer code calling the API layer directly, god modules with 50 exports, dead code that's no longer used. I started noticing this in my own projects. AI agents were writing code for my projects faster than ever, but when I started reviewing the generated code more closely, it was a mess. Services that should never talk to each other were tightly coupled. Layers that should be separate were bleeding into each other. But no one was watching the system as a whole. Not me, not the AI writing the co