"It is well that we are so foolish, or what little freedom we have would be wasted on us. It is for this that Book of Cold Rain says one must never take the shortest path between two points."

https://croissanthology.com/earring

Compilers are deterministic and, luckily, not agentic.

But yes, it's not obvious (or perhaps even likely) that it just happens that current high-level languages are the "correct" optimal level of abstraction at which you can ignore the sausage-making details at the lower levels. Ultimately, of course, it depends on the use case. Something like Python is so far removed from machine instructions that knowing assembly hardly gives the programmer any additional value.

(Also, obligatory reminder that assembly and even numeric machine code are also abstractions, an "API" provided by the CPU. Instructions get split or fused into micro-ops, named registers are a backwards-compatible abstraction over a much larger register file, instructions get reordered and executed in parallel depending on their data dependencies, a large fraction of the total transistor budget is spent on multi-level caches and cache logic to maintain the illusion of fast access to a single, uniform memory space...)

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.

Developers can change their minds.

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If it's a one off and needs no or minimal maintenance work afterwords, sure.

If it's intended to be actively maintained, then you probably should understand how things work, unless you want to wipe everything and start from scratch when the LLM creates such a mess that it can't be sorted out.

If you look into large fully-vibecoded projects getting styling changes to work is a nightmare. The problem with agents is using them on large projects without manual review for consistency, guidelines and taste. Doesn't really matter the type of project.

Agents can't look at a large system holistically, guidelines on .md files only go so far.

This line of thinking is like suggesting people who would like to become structural engineers should learn to Google plans and copy them since in the future, all plans will be out there more or less, or something that insane.

CSS keeps improving and models still train on legacy. So yes, knowing what’s possible and how is very much needed if you want to do something scalable and maintainable. Random blog or landing page, not so much.

Sometimes it's kind of cool to just ask a well phrased question and watch it spit back out a result that would've taken you hours, like cross referencing industrial widgets that have their critical information available but spread out all over.

That said, I don't usually ask it tightly bounded clerical questions and not thing that imply sub-tasks like "scan the dark web".

Post reads as English as a second language.