How I Use AI for Development and Why Context Matters

When it comes to AI, I do not really think about magic. I think more about another colleague helping me out. Sometimes that means architecture. Sometimes implementation. Sometimes testing, review, CI/CD, or deployment. But this only works with trust, and trust needs communication. If I do not know something, I ask. If code looks strange, I ask. If tests fail, I ask. The less I need to ask, the more likely it is because I already gave enough context up front: architecture, documentation, constraints, examples, and what I actually want. Even then I still review the result. That is why using AI well is a skill you build over time. My first larger projects with AI were much less smooth than newer ones. Over time I learned that better context, better tooling, and better guardrails lead to much better results. AI can speed things up a lot, but it does not remove engineering judgement. My workflow changed over the last year Last year I was mostly just using ChatGPT directly, before tools…