Comment by satvikpendem
3 days ago
> With this comes the consideration about the tradeoffs of "produce mediocre but large body of works" vs "produce high quality but small body of works".
Not really. The AI will output the same sort of code at a certain skill level regardless of speed, it's not a human so the above is a false dichotomy. Also, it's sort of strange that you're saying it's inventing work out of nothing, you've never heard of a backlog? In companies that can grow very long and the more usage means the more that can be tackled.
> You'd probably attack tasks/problems that you didn't consider actually spending time/energy solving.
Yes? But that's probably after the backlog is complete unless they are truly low hanging or high priority fruit. So not sure how that reasons with your point.
> The AI will output the same sort of code at a certain skill level regardless of speed, it's not a human so the above is a false dichotomy.
It'll output the same code given the same prompts yes, but you don't just accept whatever it puts out, it requires iterations before it's actually ready to be committed as none of the agents write perfect code on their first try. So, it's not a "false dichotomy", I'm just looking at larger things than "LLM does inference"
Ah, I see the confusion now. You are assuming one looks at the code at all and adjusts it to fit whatever style guide is needed. The parent you were initially talking to is talking about vibe coding, where whatever the agent spits out is accepted on the first try as long as it works for a given feature. Therefore the more usage one has the more features one can build.