alt Hacker News> An LLM has never saved me time. It has always produced something that doesn't quite work, has the rough shape of what I want, but somehow always gets all the details wrong.
This reads like a skill issue on your end, in part at least in the prompting side.
It does take time to reach a point where you can prompt an LLM sufficiently well to get a correct answer in one shot, developing an intuitive understanding of what absolutely needs to be written out and what can be inferred by the model.
I’m curious about how you landed “git gud; prompt better” and not “maybe the domain I work in is a better fit for LLM code”. Or, to be a bit less generous, consider the possibility that the code you’re generating is boilerplate, marshaling, and/or API calls. A facade of perceived complexity over something that’s as complex as a filter-map or two.