[londons_explore]

As an employer, I want AI to be fully allowed for assignments, and the assignments to be made trickier to compensate.

Let's train people to use all the tools available to solve the hardest problems, rather than solving toy problems with a slide rule.

[dogleash]

As an employer, I want education to be robust from the ground up, not turn uni into an attempt to bootcamp whatever is hot today.

I don't think a 4 year postsecondary education is enough time to make a developer that can hit the ground running. Not if it's 100% of class time on CS theory. Nor if it were 4 years of vocational training and labwork that leaned heavy into AI. Nor some mix. We train on the job heavily, it's just not possible to fit everything into the sausage grinder.

So why not throw in some mandatory non-major electives? Take the time to do stuff that frustrates people who want uni to be a certificate mill. I don't care if green employees are experts at the exact narrow set of tools I use. I want them to be good at learning, and to have gotten most of the standard CS topics out of the way.

[recursivecaveat]

I don't think you will achieve much that way. Suppose you pair me with a plumber, an area I know almost nothing about. The plumber is not able to finish anything 'trickier' because they have an ignoramus looking over their shoulder. Maybe I can learn some things by watching, having things explained to me as they work. On the other hand if I just walk away there's no way to tell from the final product. You gotta learn the fundamentals to at least a comparable level to be able to contribute. Same reason you couldn't just google everything on your phone in calculus.

[dontlikeyoueith]

> As an employer, I want AI to be fully allowed for assignments, and the assignments to be made trickier to compensate.

This is like saying first graders should learn to use calculators, not how to do arithmetic.

Some skills are foundational, and must be learned first in order to be able to solve harder problems. Skipping those skills because software can do them is moronic.

[jimbokun]

You have to balance that with teaching the skills needed to understand the domain sufficiently to take over when the model gets things wrong.

[unglaublich]

What a ridiculous take. Just because solutions exist in the llm training data, doesn't make these problems 'toy' or 'easy'. The human 'engineering hardness' scale doesn't align with what an llm can and can't do.