I've also wondered this - including if we might see a breed of 'higher level' languages (i.e. much higher level than Python) which can then be 'AI compiled' into highly efficient low level code.
i.e. the advantages of an even-higher-level python that's almost like pseudo-code with assembly-level speed and rust-level safety, where some complexity can be abstracted out to the LLM.
I disagree. Chatgpt is helpful here because f# is a paradigm shift for this otherwise experienced programmer. The programmer probably knows juuussstt enough f# to guide the llm.
I mean why is f# the goal, and could we write a better f# with the use of AI.
As an example, why not write in f# and let an 'AI-compiler' optimise the code...
The AI-compiler could then make sure all the code is type safe, add in manual memory management to avoid the pitfalls of garbage collection, add memory safety etc - all the hard bits.
And then if we gave the AI-compiler those sort of responsibilities, then we can think about how this would impact language design in the longer term.
None of this is with current generation LLM's, but might be where we end up.
In current generation language there is definitely a trade-off between language productivity (i.e. speed of writing) and features such as speed and memory-safety.
So far we haven't been able to close this gap fully with current compilers and interpreters (i.e. python still runs slower than C).
It seems like that gap could be closed through, for example, automated refactoring into a rust-like language during compilation, or directly into more-efficient byte-code/ASM that behaves identically.
And surely if that is a possibility, that would affect language design (e.g. if you can abstract away some complexity around things like memory management).
i.e. the advantages of an even-higher-level python that's almost like pseudo-code with assembly-level speed and rust-level safety, where some complexity can be abstracted out to the LLM.