[vishnumenon]

My current hypothesis here is that the way to make coding assistants as reliable as possible is to shift the balance towards making their output rely on context provided in-prompt rather than information stored in LLM weights. As all the major providers shift towards larger context-windows, it seems increasingly viable to give the LLM the necessary docs for whatever libraries are being used in the current file. I've been working on an experiment in this space[0], and while it's obviously bottle-necked by the size of the documentation index, even a couple-hundred documentation sources seems to help a ton when working with less-used languages/libraries.

[0]: https://indexical.dev/

[mr_toad]

I like that your solution is basically telling the LLM to RTFM.

[vishnumenon]

Yeah I've been using it with prompts that ask it to cite sources as well, honestly I think the best results are when I'm still interacting w/ the docs directly in addition to having the LLM look at em - still can't quite replace needing to RTFM!

[spadufed]

This is the way forward imo. Particularly as we've started to flesh out the relationship between model size and true context reliability. We've found that raw context-window size is not representative of what the model can actually consistently recall, but we've also found the recall is consistently reliable out to a point. I suspect more robust theoretical models around superposition will move us a long way towards understanding the limits of context reliability rather than what would currently be an experimental approach.