> This is a great insight. For software engineers coding is the way to fully grasp the business context.

> By programming, they learn how the system fits together, where the limits are, and what is possible. From there they can discover new possibilities, but also assess whether new ideas are feasible.

Maybe I have a different understanding of "business context", but I would argue the opposite. AI tools allow me to spend much more time on the business impact of features, think of edge cases, talk with stakeholders, talk with the project/product owners. Often there are features that stakeholders dismiss that seemed complex and difficult in the past, but are much easier now with faster coding.

Code was almost never the limiting factor before. It's the business that is the limit.

It’s perplexing; like the majority of people who insist using AI coding assistance is guaranteed going to rob you of application understanding and business context aren’t considering that not every prompt has to be an instruction to write code. You can, like, ask the agent questions. “What auth stack is in use? Where does the event bus live? Does the project follow SoC or are we dealing with pasta here? Can you trace these call chains and let me know where they’re initiated?”

If anything, I know more about the code I work on than ever before, and at a fraction of the effort, lol.

I think that for the average developer this might be true. I think that for excellent developers, they spend a lot of time thinking about the edge cases and ensuring that the system/code is supportable. i.e. it explains what the problems are so that issue can be resolved quickly; the code is written in a style that provides protection from other parts of the system failing; and so on. This isn't done on average code and I don't see AI doing this at all.