Most knowledge work is ephemeral–we write documents, emails, code and then it’s done. The ways in which we work don’t tend to compound or accumulate over time. This makes knowledge work lossy. A good example of this is note taking–we tend to never look at notes once they are written.
Ideally, all work we do builds on and increases our capacity for new ideas. Systems we put in place should allow us to add to and extrapolate from our knowledge.
See also:
- Andy Matuschak’s note where this idea came from (actually I heard it at talk he gave)
- Zettelkasten is a note taking system which attempts to build up a ‘conversation partner’ by accumulating notes with a dense set of connections thus accreting knowledge systematically.
Links to this note
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Knowledge work processes should be accretive (rather than ephemeral or ad-hoc). For note-taking, adding new notes should make other notes more useful and the accumulated knowledge should lead to new connections and thereby new ideas.
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Tools that enable connections between ideas and memories help to improve the growth of accumulated knowledge. These tools build a ‘knowledge graph’ that mirror the way the human brain functions and offer the possibility to query it in ways that we typically access knowledge and memories, by context and association.
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The other day I noticed a tweet from Justin Duke which outlined a plan to get his company’s codebase ready for Devin—a programming focused generative AI product. While many are skeptical about AI taking over coding tasks, progress happening quickly and it seems likely that these tools will help software engineers, though maybe not replace the job outright).
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Product Work Is a Pursuit of Facts About the User, Market, and Their Problems
When building products you are always learning new things about the user, the market, and their problems. Sometimes this happens intentionally (e.g. doing user research) and sometimes it happens unintentionally (e.g. adding a feature that suddenly takes off in usage). Ideally these facts are made explicit and is accretive over time so that new facts leads to better understanding over time which leads to more successful products. This also requires flexibility and updating ones model as new information is uncovered.
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A fictional device from the essay As We May Think, written in 1945 by Vannevar Bush, which both stores knowledge (books, notes, annotations, conversations) and connections between them allowing someone to follow trails of associated knowledge. A memex is an example of a tools for networked thought that builds on top of existing knowledge.
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Knowledge Work Productivity Can Be Measured by the Number of Notes Added Per Day
A single number to measure the productivity of a knowledge worker could be the number of new notes added per day. This idea comes from Andy Matuschak based on a foundation that knowledge work should be accretive and each note being an atomic idea that contributes to the overall pool of knowledge one can access.
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Knowledge Capture Loops Make for Good Systems
Real world systems for operating a complicated process don’t start out perfectly designed complete systems. New information reveals itself only after you’ve done it a few times. Failure modes you weren’t aware of become apparent only after the system breaks.
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Here’s how to write permanent notes based on How to Take Smart Notes.