Software solutions do not start with code
I can move from idea to code faster with AI, but the real work still starts before that: asking better questions, spotting constraints, and building the right mental model.
I can move from idea to code faster with AI, but the real work still starts before that: asking better questions, spotting constraints, and building the right mental model.
As AI takes over more of the mechanical work, engineers at every level need to learn how to direct, verify, and own what gets shipped. This article reflects on why that mindset should start early, not only at senior level.
Why AI makes engineering fundamentals more important, not less, and why I am starting a series on the principles that still shape real production decisions.
A reflection on turning one AI-generated Python prototype into reusable coding-agent guidance: clearer implementation boundaries, stronger quality expectations, and a shared quality bar before prototypes become real tools.
Running multiple coding agents in parallel feels like a speed win until the bottleneck becomes the person trying to supervise all of them.