The code that LLM outputs, has worked well enough to learn from since the initial launch of ChatGPT. This even though back then you might have to repeatedly say "continue" because it would stop in the middle of writing a function.
Necessarily, LLM output that works isn't gibberish.
Also, it's actually fun watching LLMs debug. Since they're reasonably similar to devs while investigating, but they have a data bank the size of the internet so they can pull hints that sometimes surprise even experienced devs.
I think hard earned knowledge coming from actual coding is still useful to stay sharp but it might turn out the balance is something like 25% handmade - 75% LLM made.
they have a data bank the size of the internet so they can
pull hints that sometimes surprise even experienced devs.
it might turn out the balance is something like 25% handmade - 75% LLM made.