Off topic, but just in case: is there a good reference on how people actually use LLMs on a daily basis ? All my attempts so far have been pretty underwhelming:

* when I use chatbots as search engines, I'm very quickly disappointed by obvious hallucinations

* I ended up disabling github copilot because it was just "auto-complete on steroids" at best, and "auto-complete on mushrooms" at worst

* I rarely have use cases where I have to "generate a plausible page of text that statistically looks like the internet" - usually, when I have to write about something, it's to put information that's in my head into other people head

* I'd love to have something that reads all my codebase and draws graphs, explain how things work, etc... But I tried aider/ollama, etc.. and nothing even starts making sense (is that an avenue to persevere in, though ?)

* At once, I tried to write in plain english a situation where a team has to do X tasks, in Y weeks, and I needed a table of who should be working on what for each week. I was impressed that LLMs were able to produce a table - the slight problem was that, of course, the table was completely wrong. Again, is it just bad prompting ?

It's an interesting problem when you don't know if you're just having a solution in search of a problem, or if you're missing something obvious about how to use a tool.

Also, all introductory texts about LLMs go into many details about how they're made (NNs and transformers and large corpuses and lots of electricity etc...) but "what you can do with it" looks like toy examples / simply not what I do."

So, what is the "start from here" about what it can really do ?