Emergent note taking: what ants can teach us about notes

Emergent note-taking treats a personal knowledge base like a living system: notes start as loosely connected “whatever I’m interested in right now,” then later recombine into patterns and new ideas that none of the individual notes were designed to produce. The core claim is that clusters don’t have to be planned top-down; they can be surfaced bottom-up by (1) writing notes in ways that make them easy to retrieve and relate, and (2) regularly running discovery routines that reveal what’s already latent in the vault.

The method begins with a practical definition of “emergence,” borrowed from Steven Johnson’s book *Emergence*: complex behavior can arise from many simple parts without any single part “intending” the final outcome. Ant colonies and natural selection serve as analogies—no one ant or organism is coordinating the whole system, yet coordination and adaptation appear. Applied to notes, the goal becomes building conditions where useful connections can arise unexpectedly when notes are found, linked, and reviewed.

To make notes findable and cluster-able, the workflow emphasizes writing notes you’ll later be able to locate and recombine. A key example uses the LATCH system—Location, Alphabet, Time, Category, Hierarchy—implemented through an Obsidian setup with the Templater plugin. Templates are applied automatically based on folder rules, so new notes inherit consistent structure. “Location” is handled less as geography and more as adjacency inside the vault: the note is placed relative to existing notes using links (e.g., a “clean code” note positioned next to a “software development” note). “Alphabet” becomes a title plus aliases to hedge against future search terms (e.g., “clean code” vs “clean coding”). “Time” links each note to the daily note via a templated date link, turning daily chronology into a navigable trail of what was being worked on. “Category” and “Hierarchy” add metadata that signals both topical grouping (e.g., “best practices”) and relationships to other concepts (e.g., “test-driven development” as an adjacent topic, or “applies best practices” as a relational label).

The second half of the emergence strategy is routine review—actively searching for patterns rather than waiting for them to appear. Keyword discovery starts with tools like a quick switcher (file-name search) and a broader search pane (body text search), with tactics to narrow results using quotes and exclusions (e.g., avoiding the TTRPGs folder). When no topic is known, the approach shifts to “lightning rods of thought,” using multiple Dataview queries to identify candidates for new writing: notes with many outgoing links (often already central ideas), notes with many incoming links (topics that may be underdeveloped), lines containing specific keyword combinations (e.g., “observability” and “tracing” together), and “orphans” (notes not linked anywhere, which are effectively invisible).

To explore relationships visually, the workflow also uses ExcaliBrain, which builds a relationship map from the note metadata and can even surface links to concepts that don’t yet have their own pages. Finally, it rounds out discovery with traditional navigation (folders), semi-structured navigation (bookmarks), tags, and even controlled randomness (a random note resurfacing items tagged “inbox”). The closing message frames the whole practice as “subversive”: it rejects the need to know in advance what will be learned, betting instead on sustained curiosity, iterative linking, and—optionally—learning in public to increase the odds that new connections will be stumbled upon by others.