The Human in the Loop
Feb 25 2026AI can write code — that's no longer the interesting question. The interesting question is what happens to us when it does. This piece explores the tension between generation and understanding in AI-assisted development: the tools let you prototype five approaches in an afternoon, which is a genuine superpower, but they also create a seductive dopamine loop where effortless output bypasses the struggle that builds real competence. The core problem is trust calibration — AI-generated code passes structural smell tests while subtly failing semantic ones, and catching that gap requires exactly the kind of embodied intuition you only develop by wrestling with problems yourself. The highest-leverage meta-skill turns out to be decomposition: breaking complex problems into pieces you can reason about, which can't be delegated because it is the understanding. The practical sweet spot isn't avoiding AI or surrendering to it — it's using it for breadth (exploring patterns, drafting alternatives, generating boilerplate) while reserving depth for yourself, especially in the genuinely hard parts where judgment, taste, and debugging intuition matter most. What remains irreducibly human isn't the code — it's the walk that builds the navigator.