[theferret]

I feel like we've been here before, and there was a time when if you're going to be an engineer, you needed to know core equations, take a lot of derivatives, perform mathematical analysis on paper, get results in an understandable form, and come up with solutions. That process may be analogous to what we used to think of as beginning with core data structures and algorithms, design patterns, architecture and infrastructure patterns, and analyzing them all together to create something nice. Yet today, much of the lower-level mathematics that were previously required no longer are. And although people are trained in their availability and where they are used, they form the backbone of systems that automate the vast majority of the engineering process.

It might be as simple as creating awareness about how everything works underneath and creating graduates that understand how these things should work in a similar vein.

[Loic]

Exactly right now, I am helping a big oil and gas company have a process simulation software to correctly converge on a big simulation. Full access to the source code, need to improve the Newton method in use with the right line search, validate the derivatives, etc.

I do think that for most of the people, you are right, you do not need to know a lot, but my philosophy was to always understand how the tool you use work (one level deeper), but now the tool is creating a new tool. How do you understand the tool which has been created by your Agent/AI tool?

I find this problem interesting, this is new to me and I will happily look at how our society and the engineering community evolve with these new capacities.