I do a variety of things, including iOS and web. Like you mentioned, LLM results between the two are very different. I can't trust LLM output to even compile, much less work. Just last night, it told me to use an API called `CMVideoFormatDescriptionGetCameraIntrinsicMatrix`. That API is very interesting because it doesn't exist. It also did a great job of digging some deep holes when dealing with some tricky Swift 6 concurrency stuff. Meanwhile it generated an entire nextjs app that worked great on the first shot. It's all about that training data baby
> `CMVideoFormatDescriptionGetCameraIntrinsicMatrix`. That API is very interesting because it doesn't exist.
same experience, and its been not great for juniors around me cause they have no idea why its not compiling or that the thing it wrote doesn't even exist... Honestly, with a lot of HN debating the merits of LLMs for generating code, I wish it were an unwritten rule that everyone states the stack they're using with it. It seems that the people who rave about it creating a whole product line in a weekend are asking it to write them a web iterface using [popular js framework] that connects to [ubiquitous database], and their app is a step or two away from being CRUD. Meanwhile, the people who say it's done nothing for them are writing against [proprietary in-house library from 2005].
The worst is the middleground of stacks that are popular enough to be known but not enough for an LLM to know them. I say worst because in these cases the facade that the LLM understands how to create your product will fall before you the software's lifecycle ends (at least, if you're vibe-coding).
For what it's worth, I've mostly been a hobbyist but I'm getting close to graduating with a CS degree. I've avoided using LLMs for classwork because I don't want to rob myself of an education, but I've occasionally used them for personal, weird projects (or tried to at least). I always give up with it because I tend to like trying out niche languages that the LLM will just start to assume work like python (ex: most LLMs struggle with zig in my experience).
> Meanwhile, the people who say it's done nothing for them are writing against [proprietary in-house library from 2005].
there's MCP servers now that should theoretically help with that, but that's its own can of worms.