Everyone is talking about how AI is helping junior developers write code they couldn't write before. That's true. But there's a less-told story: what happens when a senior developer picks up these tools. The leverage is completely different — and I didn't fully understand that until I was six months deep into it.
Here's how my working relationship with AI actually evolved, from tentative experiments to the workflow I rely on today.
Stage 1: Testing the Water with Copilot
I started where most developers start: GitHub Copilot inside VSCode, some time in 2025. I wasn't asking it to build features. I was using it for the mundane layer of senior work that nobody talks about — summary reports, technical emails that needed the right tone, quick estimations for sprint planning.
It was useful enough that I got curious. I started intentionally switching models to understand the differences: GPT-4, Claude Sonnet, Gemini X Pro, Kimi2.5, Minimax. Each had a different character. Some were better at structured reasoning, some at generating clean code, some at explaining tradeoffs. I started to develop a mental model of which tool for which job — not because any article told me to, but because I was running informal experiments every day.
