AI can't write maintainable code, and people who rely on it won't learn either

Alexandru Nedelcu argues that vibe-coded projects inevitably decay into unmaintainable messes because maintainability has no instant reward signal for RL training—bad architecture takes months or years to surface. He notes that even SOTA models fail at extracting clarifying, reusable functions, and that most training data reflects the mediocre code found in the wild. The deeper risk is that developers who outsource both writing and reading to AI stop making choices, owning mistakes, and building the intuition that separates experts from advanced beginners. His prediction: more companies will start advertising a “NO-AI” policy as a competitive edge.