AI coding tools can write a function in seconds. The harder question is whether that function actually belongs in your codebase. Does it follow the existing architecture? Does it handle edge cases? Will the tests still pass? And when something breaks three files later, can the AI help find the real cause instead of generating another patch?
To answer those questions, I spent a month using Cursor, GitHub Copilot, and Claude Code as pair-programming tools while working through practical development tasks: writing code, debugging errors, refactoring functions, creating tests, and making changes across multiple files.
I wasn't testing which tool could produce the most code. I was testing which one could make real programming work faster without creating more work afterward.
The Short Answer
After using all three tools on real development tasks, I wouldn't call one tool the absolute winner.
