I agree that it is easier than ever to start doing stuff, instead of reading. I don't think that means its easier to jump right to doing large projects. The problems to be solved there are often subtler, of a different class, and manifold, and a layman may not realise what has gone wrong until long afterwards or never (this also happened before, many people took on projects they weren't ready for and reinvented the wheel trying to solve issues they ran into)

it's oft debated, but I do fall on the side of "you should still know maths even in the age of the calculator/matlab/llms". I have found productive employment, and indeed tickets to speak to the big boys in their gilded palaces many times because graphs and charts are their favorite toys and knowing maths got me there. They have always been able to make things with excel, with matlab etc. Often they actually can make charts themselves, but they don't care to become experts in what data is important and what isn't.

The LLM isn't yet good enough to tell you what data matters. People act like LLMs are magical gods that do everything, but it is but another tool. It has limitations, just as it has strengths. It is not ultimately convincing, it is not infallible, and experts will keep finding edge cases all the damn time. Anyone working with them every day knows this, and you need to know it too.

On the flip side: it's trivial to search "how to fix that pipe" on YouTube, see a bunch of success videos, and trust them all.

I'm not sure I can trust any single AI, or even multiple AI models, to not hallucinate overconfidence in certain real world domains.

targeted, expertise, fast... pick 2