I get your point and this certainly applies to most modern computing where each new layer of abstraction becomes so solid and reliable that devs can usually afford to just build on top of it without worrying about how it works. I don’t believe this applies to modern AI/ML however. Knowing the chain rule, gradient descent and basic statistics IMO is not the same level of solid as other abstractions in computing. We can’t afford to not know these things. (At least not yet!)