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Because any precise description of what the computer is supposed to do is already code as we know it. AI can fill in the gaps between natural language and programming by guessing and because you don't always care about the "how" only about the "what". The more you care about the "how" you have to become more precise in your language to reduce the guess work of the AI to the point that your input to the AI is already code.

The question is: how much do we really care about the "how", even when we think we care about it? Modern programming language don't do guessing work, but they already abstract away quite a lot of the "how".

I believe that's the original argument in favor of coding in assembler and that it will stay relevant.

Following this argument, what AI is really missing is determinism to a far extend. I can't just save my input I have given to an AI and can be sure that it will produce the exact same output in a year from now on.


alightsoul
With vibe coding, I am under the impression that the only thing that matters for vibe coders is whether the output is good enough in the moment to fullfill a desire. For companies going AI first that's how it seems to be done. I see people in other places and those people have lost interest in the "how"
birn559 OP
Which is fine in general. It has been a selling point for SQL or C, for example. What I wanted to say is that for AI output becoming a replacement for code, a necessary requirement is that the output becomes deterministic. While LLMs provide that technically, I am not sure the "culture" that has evolved the technology will lead to product that provide determinism.

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