I'm completely equally lost the other way. I've went through multiple phases of LLM usage for development. GPT3.5 era: wow this is amazing, oh. everything is hallucinated. not actually as useful as I first thought GPT4 era: very helpful as stackoverflow on steroids. Claude 3.5 Sonnet: have it open pretty much all the time, constantly asking questions and getting it to generate simple code (in the web UI) when it goes…
I'm convinced the vast difference in outcome with LLM use is a product of the vast difference in jobs. For front end work it's just amazing. Spits out boilerplate and makes alterations without any need of help. For domain specific backend, for example robotics, it's bad. Tries to puke bespoke a-star, or invents libraries and functions. I'm way better off hand coding these things. The problem is this is classic Gell M…
It's good at stuff that most competent engineers can get right while also having the sort of knowledge breadth an average engineer would lack. You really need to be a domain expert to accurately judge its output in specific areas.