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Understood. Thanks for clarifying.

Yeah, I've been in the game for "a while" myself. The example you gave with garbage collection reminds me of stories I've heard about Assembly language programmers back in the day, declaring that devs who use high level languages (like C) don't really know how to write good code.

There's probably something to that, but it does beg the question "what's the right tradeoff?" Not only do we not have to deal with memory management, but also data structures and common algorithms, etc. I do think understanding those things made me a better coder, but perhaps progressively less meaningfully so, as time marched on and the lower level stuff was abstracted away by more and more layers on our move up stack to solve harder problems.

So, the emphasis on writing code from scratch lessened over the years, and development became more about integrating other people's code (frameworks, libraries, API's, etc). So, I think that kind of teed up this AI approach to writing code, in that it's just more code to integrate that you didn't write.

But, it is qualitatively different from the "natural progression", in that they're not writing code at all. In that way it feels like the last stop on the coding continuum. I suppose that makes sense, since we're told that we soon won't need human coders at all.



I'm reminded of Buckminster Fuller's concept of ephemeralization: as technology improves, you can do more and more with less and less, until eventually you reach the point where you can do everything with nothing.

https://www.umsl.edu/~sauterv/analysis/Fall2013Papers/Purcel...




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