This is different.
Understanding assembly/machine code is optional but helpful. The programming language semantics are enough to reason about what the program is doing. Other tools also help, but are optional for learning how to program.
Using an AI, there is no semantic model that can be used to reason through. You're left without any mental model of the proglblem at all.
LLMs these days seem to have no problem using language semantics to conceptualize what’s happening in a program. This is my favorite use of an LLM, “why is this library doing x” and then it digs through the library itself in my venv to find an answer.
I've been arguing for years that is isn't optional and treating it like it is is how we ended up with Electron and 400MB JavaScript websites.
When you have no mental model of the machine running your code or what the physical implications of code mean, you fundamentally lack the ability to reason or care about performance. "Works on my machine" is the original vibecoding.