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If you start from scratch trying to build an ideal system to program computers, you always converge on the time tested tooling that we have now. Code, compilers, interpreters, versioning, etc.

People think "this is hard, I'll re-invent it in an easier way" and end up with a half-assed version of the tooling we've honed over the decades.




> People think "this is hard, I'll re-invent it in an easier way" and end up with a half-assed version of the tooling we've honed over the decades.

This is a win in the long run because the occassional and successful thought people labor over sometimes is a better way.


Agreed. We wouldn't have distributed version control, container environments, profilers, etc without people trying to to make programming better. But those are all based on improving single aspects (better versioning, repeatability, debug, etc).

When the goal is "re-invent programming to make it easier" all you get is a hodgepodge of half-ass solutions like GP said. Enhancing traditional focused workflows seems a lot more interesting to me than "coding assistant".

Hopefully AI tooling will continue to evolve. I don't see how you get around the reliability issues with this iteration of AI (GPT+RLHF+RAG, etc). Transfer learning is still abysmal.




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