Learning to Code in the Age of AI Code Generation

Learning to code was never about learning syntax. It was about: – how systems think – how state changes over time – how abstractions leak – how small decisions compound – how to understand errors and fix When you write code yourself, you are forced to be precise. AI is great at producing code. But it doesn’t automatically give you the mental model of why it works, where it breaks, or how it fits into a larger system. Without that model, you can’t reliably steer, debug, or extend what AI produces. In practice, learning to code matters even more now. You are no longer just writing instructions, you are supervising a probabilistic system that writes them for you. The future developer writes less code by hand, but understands more of it.