pawel.world
Paweł Sysiak
Karma: 31
a) I love Spaced Repetition systems mainly bc it feels empowering that you actually have a choice on what you will remember b) I cannot wait until there will be a fully AI driven one. I just want to chat via voice about concepts, and the agent attacks the question from different perspectives as opposed to asking in a statically formatted question-answer format c) I want that bc it will be nicer to just talk and bc the biggest problem with the system rn is that you memorize the static question–answer pair, association that is often tied to the context of your deck, and it’s often hard to use the knowledge in the real world. e.g.: I remember having in my deck a card that uses these words, asks in this specific way about something and I remember correctly that the answer is X. I think the only way I know out of this dynamic is to do more than one card per concept and to do reverse cards, but this is a lot of maintenance and in practice I rarely do it. If you have any pointers on how to deal with this please let me know!
I meant this bit on https://digtext.github.io (see image)
hover don’t work on mobile so its not a viable solution IMO
how would do u feel about the solution from the image?
I didn’t fully thought :::dig syntax through but I imagined adding a script on top of the site and inside dig tags all bulleted lists would render as dig text. Am I missing something in this solution?
I like the idea of footnotes on footnotes. I can see an interesting exploration in this space where footnotes (and footnotes of footnotes) appear as a bottom bar/appearing over the text. Sidebars don’t work IMO as on smaller screens there is not enough horizontal space, and mobile is where a lot of text is read.
thank you for the feedback, noted
Thanks for your patience, I am back from my time off.
You listed a lot of bugs, visual problems that I want to fix. Thank you.
I agree that just text color for pluses may be a better choice here.
I agree that the best use is when digs don’t hold a small amount of text, but this is up to the writer
“Pressing Enter should move focus somewhere sensible, rather than eating the focus. Probably to the ending parenthesis for expansion, and to the original + icon for collapsion”. I think this is very interesting. I have been thinking how to approach this. I think there are tradeoffs here, mostly simplicity. There is a way, actually, to have preview text (see dig example and text in parenthesis). I will think if there is a sensible way to bake it in more universally into the dig format eg.: • {{preview text}} or similar.
I’m trying to find the best user experience for progressively expanded reading. Footnotes, for example, are only one indentation level and honestly most of them online are a pretty terrible experience to click on.
Paweł Sysiak’s Shortform
I just created Dig Text, a new writing standard, which allows you to read the shortest version first, and dig deeper only where it interests you. I thought about dig about ten years ago, lol, and now, with the help of Claude Code, I spent two weeks thinking it through and coding it. It’s still in BETA, so I’m gathering feedback, but I would love if you try it and let me know what works and what doesn’t. https://digtext.github.io
Expert Trap: why expertise breeds error—and how to course-correct
One way to go after mnestics: If you’re running a spaced-repetition system, add flashcards with the structure Title | Content for each mnestic. Then create a “master card” with the question: “What are your mnestics?” Whenever you come up with a new mnestic, update the master card and maybe reset its review interval a bit.
*I read this a while ago and the concept of mnestics stayed with me. great read!
I also gather the “Coordination and epistemic tools” resources https://www.pawel.world/Coordination-and-epistemic-tools-6508c74fbeaf4fbd8405c729993db3eb?pvs=4
What specifically does the author mean by lack of numeracy skills?
Expert trap – Ways out (Part 3 of 3)
Expert trap: Why is it happening? (Part 2 of 3) – how hindsight, hierarchy, and confirmation biases break conductivity and accuracy of knowledge
Expert trap: What is it? (Part 1 of 3) – how hindsight, hierarchy, and confirmation biases break conductivity and accuracy of knowledge
To-do waves
Elephant in the Brain influenced extensively ways I perceive social motivations. It is talking exactly about the same subject and mechanisms of why we don’t discern it in ourselves. If you didn’t read it you should check it out. It rewrote my views to the extent that I feel afraid to read “The status game” because it feels so easy to fall into confirmation bias here. This seems to me so active that I would love to read something opposite. Are there any good critiques of this view? Once I was listening to Frans de Waal’s lecture when he expressed this confusion that in primatology almost everything is explained through the hierarchy in the group. But when we listen to social scientists almost none of it is. Elephant in the brain. I think this is such an important topic.
I asked Opus 4.8 to see what are solutions to this in the two texts i liked about Anki https://www.lesswrong.com/posts/7Q7DPSk4iGFJd8DRk/an-opinionated-guide-to-using-anki-correctly and https://augmentingcognition.com/ltm.html
The two additional solutions are:
– make cards very atomic (compare a more complex one-card-anki to four-cards-anki with the same knowledge, but a lot more atomic—atomic wins bc this type of knowledge is quicker to retrieve and more adaptable to the real life context, e.g.: in real life context you may need only 2 of 4 atomic bits, and you need to retrieve cards really quickly, and perhaps reassemble with different knowledge bits)
– to formulate cards from an angle of the real-world trigger you will most likely have.
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Claude Opus 4.8 (full-answer)
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Both texts address your exact problem (recall getting welded to the deck’s phrasing and context). Here is everything they offer, grouped by solution.
From “Guide on using Anki correctly”
Name the card for its real-world prompt, not its content. The core fix for “I only recall it when asked in that specific way.” Ask what real-life trigger should surface this knowledge, then build the card around that trigger. Their example: don’t name a card “length of whale intestine,” name it “animal fun facts,” because the real moment of retrieval is wanting an animal fun fact, not being quizzed on whale anatomy. If the natural real-life prompt genuinely needs a longer card, make the longer card.
Put the meaning in the answer, not just the bare token. The “24%” example: instead of “In 1950 Germany, what % of workforce was in agriculture? / 24%,” write “historical size of agriculture sector / 1950 Germany: 24% of workforce.” You are more likely to reach for “what do I know about the history of agriculture” than the narrow framing. Memorizing the isolated number without what it means is useless for real use.
Anchor to semantics, not visual shape. Their diagnosis of why cloze deletions fail is your exact problem: excessive context makes you learn “visual shape of the card leads to answer” instead of “semantic meaning leads to answer.” The problem is context volume, so strip context down until the recall path runs through meaning.
Redundancy as a deliberate feature. This generalizes your reverse-card instinct. Multiple cards with slightly varied prompts (small “epsilon” changes to wording and angle) train you to recognize the whole solution space rather than one frozen pairing. Cards should reinforce the pattern “circumstances lead to solution,” which is what makes knowledge fire in the real world.
Brevity forces transfer. Max ~9 words for most cards, at the absolute most 3 bullets / 18 words. If you cannot compress it, you do not understand it well enough to break it down. Short cards recall faster and resist context-anchoring.
From “Augmenting long-term memory” (Michael Nielsen)
Atomic questions you reassemble in unexpected ways. Break each idea into its smallest pieces. His soft-link example splits one routinely-missed card (“create a soft link”) into “what’s the basic command” and “what order do the arguments go.” The payoff he names directly: you later “assemble the atomic questions in an unexpected way.” Atomicity is what lets knowledge recombine in novel real situations instead of firing only as one block.
Never orphan questions, and add several per concept. This is the stronger version of your “more than one card per concept” instinct. He makes it a rule to never add just one question, always at least two, preferably three or more, so the fact becomes “the nucleus of a bit of useful knowledge.” Lonely orphan cards get missed constantly and are a waste. A tightly interconnected web of facts retains and transfers far better than isolated ones.
Multiple passes, 5 to 20 questions per source. Re-read hard material several times, adding questions after each pass. This layers the concept from different angles, which is a manual version of the “attack from different perspectives” agent you want.
No yes/no questions (from his work-in-progress notes). They let you pass on recognition without real recall.