Show HN: An AI zettelkasten that extracts ideas from articles, videos, and PDFs
github.comHey HN! Over the weekend (leaning heavily on Opus 4.5) I wrote Jargon - an AI-managed zettelkasten that reads articles, papers, and YouTube videos, extracts the key ideas, and automatically links related concepts together.
Demo video: https://youtu.be/W7ejMqZ6EUQ
Repo: https://github.com/schoblaska/jargon
You can paste an article, PDF link, or YouTube video to parse, or ask questions directly and it'll find its own content. Sources get summarized, broken into insight cards, and embedded for semantic search. Similar ideas automatically cluster together. Each insight can spawn research threads - questions that trigger web searches to pull in related content, which flows through the same pipeline.
You can explore the graph of linked ideas directly, or ask questions and it'll RAG over your whole library plus fresh web results.
Jargon uses Rails + Hotwire with Falcon for async processing, pgvector for embeddings, Exa for neural web search, crawl4ai as a fallback scraper, and pdftotext for academic papers.
This is neat, but it's not zettelkasten - it's building a browse-able knowledge DB from content.
Zettelkasten is about about writing down your ideas in response to content, with a link to that content, and then linking to other ideas that your already logged. It's not an extraction of ideas from that content. This is a common mis-understanding of zettelkasten.
I’ve thought about something like this, but I feel like the core part of the Zettelkasten method is the act of making connections and extracting ideas from the sources you interact with.
It removes the most important part of Zettelkasten: You