I didn't mean it literally in the sense of "the machine can produce 1000 copies of the same program!" (which indeed would not need an LLM to accomplish...). I meant industrial-era automation in the wider sense of "a machine and a human operator can do in one week the work previously done by 10 people in two months".
To put it another way: a generalisation of OP's question is "is it worth spending a lot of effort learning to do X manually, when a machine can do a lower-quality version of X massively faster and cheaper than I can ever do?"
In the article, X = coding. I wanted to check if the arguments given for "yes, and" hold for different values of X and the first that came to my mind was rugs; probably unfortunate that I know nothing of that topic...
I don't think that the answers for one value of X always apply completely to other values of X (i.e. whatever happened to hand-woven rugs might well be very different than what happens with coding) but I found it an interesting thought experiment, because I can fully see a master artisan of any type of X giving a very close version of the article's arguments. Maybe finding when they were eventually right and when they were not for past scenarios can teach me something now. Maybe...
To put it another way: a generalisation of OP's question is "is it worth spending a lot of effort learning to do X manually, when a machine can do a lower-quality version of X massively faster and cheaper than I can ever do?" In the article, X = coding. I wanted to check if the arguments given for "yes, and" hold for different values of X and the first that came to my mind was rugs; probably unfortunate that I know nothing of that topic...
I don't think that the answers for one value of X always apply completely to other values of X (i.e. whatever happened to hand-woven rugs might well be very different than what happens with coding) but I found it an interesting thought experiment, because I can fully see a master artisan of any type of X giving a very close version of the article's arguments. Maybe finding when they were eventually right and when they were not for past scenarios can teach me something now. Maybe...