Comment by jsnell
6 days ago
Not exactly what you're asking for, but https://news.ycombinator.com/item?id=44159166 from today is not a junior web programmer working through the backlog, and the commit history contains all the prompts.
6 days ago
Not exactly what you're asking for, but https://news.ycombinator.com/item?id=44159166 from today is not a junior web programmer working through the backlog, and the commit history contains all the prompts.
Sure, thanks. I mean it's a typescript OAuth library, so perhaps we might say mid-level web programmer developing a library from scratch with excellent pre-existing references, and with a known good reference API to hand. I'd also count that as a good use case for an LLM.
I watched someone do a similar demonstration( https://news.ycombinator.com/item?id=44159166)live at an event. They ended up doing something like 3 pull requests to get the original change. Then had to do 4 more to get it to fix and put back things it removed. Not exactly efficient, and it was painful to sit there and be like I could have had it done manually 20x by now while we painfully waited for the AI to do the changes.
I've never been able to get it to work reliably myself either.
The internet just tells me to prompt harder. Lots of "grind-set" mentality energy around AI if you ask me. Very little substance.
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I think you mistook my comment. Insofar as its anything, it was a concession to that use case.
I gave an example below: debugging a microservice-based request flow from a front-end, thru various middle layers and services, to a back-end, perhaps triggering other systems along the way. Something similar to what I worked on in 2012 for the UK olympics.
Unless I'm mistaken, and happy to be, I'm not sure where the LLM is supposed to offer a significant productivity factor here.
Overall, my point is -- indeed -- that we cannot really have good faith conversations in blog posts and comment sections. These are empirical questions which need substantial evidence from both sides -- ideally, videos of a workday.
Its very hard to guess what anyone is really talking about at the level of abstraction that all this hot air is conducted at.
As far as i can tell the people hyping LLMs the most are juniors, data scientists who do not do software engineering, and people working on greenfield/blank-page apps.
These groups never address the demand from these sceptical senior software engineers -- for obvious reasons.
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Most of my day job is worrying about the correctness of compiler optimizations. LLMs frequently can't even accurately summarize the language manual (especially on the level of detail I need).