Personal notes, a team wiki and a knowledge base for AI differ in who reads them: your future self, your colleagues, a model. All three have to answer what to keep, how to organize it, how it gets found and who maintains it. Research on personal collections finds that most 'finding' is re-finding things you have already seen; research on enterprise wikis finds that once the person who tidied or wrote the content leaves, it starts to decay.
Before choosing a note tool, ask five things: can other programs open its files, do links survive renaming, can you search and filter, does it sync across devices, and does it work offline. Obsidian's notes are just Markdown files in a folder on your computer, but syntax such as block references can't be followed outside Obsidian, and on iPhone only two sync methods are officially recommended. Notion's databases are powerful, but an export takes only one view, callouts become HTML, and an export can't simply be uploaded back to restore your workspace. Before switching tools, export once and open the result in another program.
Schedule a 30-minute weekly review: empty the inbox, deal with finished projects, and pick one question from an MOC to think further about. Summarizing needs no schedule; add a layer only when you touch a note anyway. An LLM can find duplicates, suggest possibly related notes and flesh out key points you've written first; the sentence in your own words, deciding what matters and whether to delete are yours. In one 30-person study comparing three kinds of AI help, the group given complete AI notes learned the least and edited the least.
To decide whether to keep something, ask three questions in order: can I name a concrete use for it, can I find it again later, can I write one sentence of my own about it. No use, don't keep it; if the original is findable again keep only a link, otherwise save a copy; only items with that sentence go into the knowledge base, the rest go on a to-read list. Empty the inbox every week. The reason behind it: every keep-or-skip decision risks two errors, keeping too much buries what matters and keeping too little means searching again, and loosening or tightening your threshold only trades one error for the other.
After this post you'll be able to rewrite a reading summary as two or three notes that link to each other, and build a map note (MOC) once your notes pile up. The method comes down to four principles: one concept per note, organize by concept rather than by book, write in your own words, and state why you make each link. It goes back to Luhmann's slip box; research supports the idea that generating something yourself beats just reading it, but I found no credible controlled experiment on the Zettelkasten itself.
Once studying went fully digital, paper still holds three places with real evidence: reading (paper over screens at g ≈ −0.21 across 171,055 participants, widening to 0.35–0.48 when scrolling is required), writing while you answer (on screen, harder questions draw less scratch work, not more), and drawing (45% recall against 20% for writing). The one claim most people lean on, that handwritten notes stick better, spans −0.008 to +0.248 across four meta-analyses with no consensus.