This is all true. The best way to treat LLM's as they are now is one step above the abstraction offered by compiled languages over assembly. You can describe something in plain english, note its explicit requirements, inputs and outputs, and an LLM can effectively write the code as a translation of the logic you are specifying. Using LLM's, you are best served minimizing the entropy they have to deal with. The transformer is essentially a translation engine, so use it as a translator, not as a generator.

That being said, every few months a new model comes out that is a little less encumbered by the typical flaws of LLM's, a little more "intuitively" smart and less needing of hand-holding, a little more reliable. I feel that this is simply a natural course of evolution, as more money is put into LLM's they get better because they're essentially a giant association machine, and those associations give rise to larger abstractions, more robust conceptions of how to wield the tools of understanding the world, etc. Over time it seems inevitable that providing an LLM any task it will be able to perform that task better than any human programmer given it, and the same will go for the rest of what humans do.

This is a false analogy. LLMs do not "compile" natural language to high level code in the same way that a compiler or interpreter implements a high-level programming language in terms of machine instructions (or, for that matter, how a CPU implements machine instructions in hardware).

Programming and machine languages aim for a precise and unambiguous semantics, such that it's meaningful to talk about things like whether the semantics are actually precise or whether the compiler has a bug in failing to implement the spec.

Natural language is not just a higher level of abstraction on our existing stack. If a new model comes out, or you even run an existing model with a new seed, you can get different code out that behaves differently. This is not how compilers work.

No, LLMs are not an "abstraction" like a compiler is. This is bullshit. LLMs are stochastic token generators. I have NEVER met someone in real life that has produced something I wouldn't throw in the trash using LLMs, and I have had the displeasure of eating cookies baked from an LLM recipe.

No, LLMs will not get better. The singularity bullshit has been active since 2010s. LLMs have consumed the entire fucking Internet and are still useless. Where the fuck is the rest of the data going to come from? All these emails from people wanting high quality data from PhDs only for them to be scammy. People only want to train these things on easily stolen garbage, not quality input, because quality is expensive. Go figure!

This optimistic horeshit hype is embarrassing.