It's mentally gratifying to see all this well-organized, but I'm struggling to extract meaningful insights from this.
How do you synthetize all the knowledge in these databases? What useful meaning/insight/actionable items do you extract from them?
Can LLMs help here?
LLm could help bridge that gap a little more, but never 100%.
They have written two blog posts "Obsidian Note-Taking with ODIN: Intern's Perspective" [3] and "Building a Backend for ODIN and RUNE: How to Make a Knowledge Extraction Engine" [4] on this topic. The cover the reasoning why the did some things in the way that they did, and they do talk about LLMs. Also do take a look at "RUNE — Our Journey to Creating a GitHub LLM Analytics Tool: Intern’s Perspective".
[2] https://news.ycombinator.com/item?id=37597201
[3] https://memgraph.com/blog/addobsidian-note-taking-with-odin
[4] https://memgraph.com/blog/building-backend-odin-rune-knowled...
[5] https://memgraph.com/blog/rune-creating-github-llm-analytic-...
I now have a few simple text files with project ideas, book notes, and todos. It feels much better and I don't spend time managing it.