Evaluating written artifacts is broken in education because the end goal of education is not the production of written artifacts - it is the production of knowledge in someone’s mind and the artifacts were only intended to see if that knowledge transfer had occurred. Now they no longer provide evidence of that. A ChatGPT written essay about the causes of the civil war is not of any value to a history professor, since he does not actually need to learn about the civil war.
But software development is about producing written artifacts. We actually need the result. We care a lot less about whether or not the developer has a particular understanding of the world. A cursor-written implementation of a login form is of use to a senior engineer because she actually wants a login form.
I think it's both actually, and you're hitting on something I was thinking of while writing that post. I'm reading "The Perfectionists," which is about the invention of precision engineering. It had what I would consider three aspects, all of which we should care about:
1. The invention of THE CONCEPT BEHIND THE MACHINE. In our context, this is "Programming as Theory Building." Our programs represent some conception of the world that is NOT identical to the source code, much the way early precision tools embodied philosophies like interchangeability.
2. The building of the machine itself, which has to function correctly. To your point, this is one of the major things we care about, but I don't agree it's the only thing. In the code world this IS the code, to your point. When this is all we think about, though, I think you get spaghetti code bases and poorly trained developers.
3. Training apprentices in both the ideas and the craft of producing machines.
You can argue we should only care about #2, many businesses certainly incentivize thinking in that direction, but I think all 3 are important. Part of what makes coding and talking about coding tricky is that written artifacts, even the same written artifacts, express all 3 of these things and so matters get very easily confused.
This is a key difference, but I think it plays less of a role than it initially appears because growing knowledge of employees helps building better artifacts faster (and fixing them when things go wrong). Short term, the login form is desired. But long term, someone with enough knowledge to support the login form, for when the AI doesn't quite get it all right, is desired.
But software development is about producing written artifacts. We actually need the result. We care a lot less about whether or not the developer has a particular understanding of the world. A cursor-written implementation of a login form is of use to a senior engineer because she actually wants a login form.