I guess you can argue that these are two independent processes so you can combine them to get something more reliable than both - this might be a viable path. But from what I heard writing formal specifications is just really hard - I haven't seen anything practical in this area.

Especially all bookkeeping logic should move into the symbolic layer: https://zby.github.io/commonplace/notes/scheduler-llm-separa...

    Formal specification layers that agents execute against, not just prompts

It is probably easier to just write that program.

I can see a similar problem with this article - the author notices that LLMs produce a lot of errors - then concludes that they are useless and produce only simulacrum of work. The author has an interesting observation about how llms disrupt the way we judge knowledge work. But when he concludes that llms do only simulacrum of work - this is where his arguments fail.

Maybe you can use the instructions from my repo - which are here: https://github.com/zby/commonplace/blob/main/kb/agent-memory... and run them on your code directory? Then send me the result.

But the reviews are written automatically - here are the instructions: https://github.com/zby/commonplace/blob/main/kb/agent-memory...

Overall the knowledgebase is a mixture of these. I have this disclaimer on the first page:

This KB is itself agent-operated: a human directs the inquiry, AI agents draft, connect, and maintain the notes. The framework for building knowledge bases is documented using that framework.

I hope it is enough - I've seen many people get angry with publishing LLM generated work.

Together with the other hundred llm memory systems: https://zby.github.io/commonplace/agent-memory-systems/

I have also written a wishlist for these systems: https://zby.github.io/commonplace/notes/designing-agent-memo...

It is a third llm wiki on front page in 24 hours! Obviously it is a hot topic. I have my own horse in that race - so I might not be objective - but I've compiled a wishlist for these system: https://zby.github.io/commonplace/notes/designing-agent-memo...

I wish there was a chance for collaboration - everybody coding their own system seems like a lot of effort duplication.

The reviews are done automatically - here are the instructions: https://github.com/zby/commonplace/blob/main/kb/agent-memory...

I am open to changing these instructions - it cannot be about just making your system look better - but I'll try to incorporate genuine ideas how to improve these reviews.

It is the second llm wiki on frontpage today!

I wish the scene was more collaborative - instead of everyone writing their own. But I guess this is the llm curse - too easy to start. I am afraid it will all go in the LangChain direction with VC funding designs that are not yet ready solidifying choices that would normally be superseded.

By the way - here is the prompt for these reviews: https://github.com/zby/commonplace/blob/main/kb/agent-memory...