The author of that article admits that the sample size is not large enough to draw meaningful conclusions.
Hey, you brought it up - I just pulled the thread. Not my fault it cuts against your argument.
But besides that, I believe LLM code generators can be a useful tool, provided you are willing to go over their output with a fine-tooth comb and assume it is broken until you have proven otherwise,
So, exactly like a junior dev?
going to completely solve it, and are willing to overlook the myriad ethical issues with all major LLMs in existence today.
That's a different claim than the one you opened with though. Most of those objections have documented counter-arguments, btw:
https://blog.andymasley.com/p/a-cheat-sheet-for-conversations-about
https://aicentral.substack.com/p/why-anthropic-burned-the-books
Data centres were polluting long before LLMs arrived. Crypto, cloud storage, Netflix, YouTube, AWS - AI isn't all data centre load. Blaming the latter for the former is like blaming sunscreen for melanoma.