[placebo]

This got me thinking: I am not about to fight windmills and the future will unfold as it will, but I think the idea of "LLM as a compiler of ideas to high-level languages" can turn out to be quite dangerous. It is one thing to rely on and not to be able to understand the assembly output of a deterministic compiler of a C++ program. It is quite another to rely on but not fully understand (whether due to lazyness or complexity) what is in the C++ code that a giant nondeterministic intractable neural network generated. what is guaranteed is that the future will be interesting...

[bobjordan]

The way I'm keeping up with it (or deluding myself into believing I am keeping up with it) is by maintaining rigorous testing and test standards. I have used LLMs to assist me building C firmware for some hardware projects. But the scale of that has been such that it can also be well tested. Anyway, part of the reason I was so much slower with python is I'm an expert at all the tech I used, spending literal years of my life in the docs and reading books, etc., and I've read everything the LLM wrote to double check it. I'm not so literate with go but its not very complex, and given the static nature, I just trusted the LLM more than I did with python. The react stack I am learning as I go, but the tooling is so good, and I understand the testing aspects, same issue, I trusted the LLM more and have been more productive. Anwyay, times are changing fast!