AI-Assisted Coding 101

AI coding assistants — tools that read and write code alongside you inside an editor or terminal — have changed what it means to build software, but not in the way early hype suggested. They rarely replace the need to understand code; instead, they change the ratio of time spent typing versus time spent reviewing, directing, and deciding.

What these tools are actually good at

• Writing boilerplate and repetitive code quickly, based on a clear description.
• Explaining unfamiliar code, error messages, or concepts in plain language.
• Suggesting fixes for bugs once you've described the symptom.
• Refactoring code into a cleaner shape while preserving behavior.

Where they still need supervision

AI coding tools can confidently produce code that looks correct but has subtle bugs, especially in edge cases or unfamiliar libraries. They also don't inherently know your project's conventions or constraints unless you tell them. Treat generated code the way you'd treat code from a fast but junior collaborator: useful, often good, but always worth reviewing before it ships.

The skill that matters most isn't typing code faster — it's describing intent clearly and reviewing output critically.

Getting started well

If you're new to AI-assisted coding, start on a project you already understand — your own small script or a personal project — rather than an unfamiliar, high-stakes codebase. Practice giving specific instructions: what the function should do, what inputs it receives, and what edge cases matter. Vague requests produce vague, often wrong, code. Precise requests produce precise, usable code.