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Comments (22)

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  c3z_
  I've learned that for both humans and models: system > willpower. The key is entirely in designing the environment.For me personally, that means setting up 'attention getters' for the important things in life - 'totems' that force a context switch. For AI agents, it means well-designed CLI tools that help the agent orient itself in a task and pull exactly the 'context-for-the-job' it needs right then.This is exactly what makes building modern GenAI decision-support systems so difficult. It's no longer just about finding the right software abstractions. You now have to account for the unknown cognitive construct of a completely different intelligence.
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  james_ross
  This rings very true to me, and it's why I've been mildly obsessed for a decade plus with how to share mental models between people, and now LLMs, of any domain, be it technical, commercial, scientific or anything else. My inspiration was a book called Learning How To Learn by Novak, which TBH is so dry I'm not sure anyone I've recommended it to has actually finished it :) So then I point them to a talk here: https://www.infoq.com/presentations/concept-map/ and an app to help render the shared mental model in plain text accessible to the LLM while providing visual interactivity to the humans here: https://thinkingtools.software/concepticon/
• rrook
  I've been working like, almost this exact idea! https://github.com/hale-lang/papers/tree/main . The same capacity allocation bound algorithm appears naturally not only in human and llm/agent congnition, but in many natural systems as well.
• drooby
  All I want to say is that I absolutely love this essay. Thank you.
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  zby
  It is interesting to compare this to LLMs - they also have the bounded context that you can see as the analogue to our working memory. It can contain enormously more bits of information than the 4 things the article says is the capacity of our working memory - but the 4 things can probably be much more complex internally - they are more like 4 pointers probably.But at some level context engineering is very similar to what this article talks about.
• anon
  undefined
• actionfromafar
  "When you take all that away, the honest figure for how many separate things a person can hold in mind at once, with no help at all, is about four."That's funny, isn't it the same for dogs?
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  chrisjj
  > You've probably heard that the mind can hold seven things at once.What I've heard is human short-term memory can hold seven things at once. Fortunately the mind is much more.
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  dcre
  This reads to me as fully written by LLMs. Pangram agrees. Note the (alleged) author misHQ’s comments on this thread are getting downvoted as obvious slop.https://news.ycombinator.com/item?id=48706307Even if it were written by hand, it’s a very poor and frankly stupid essay about an interesting topic. “The model's attention is a fixed quantity, and it has to add up to one, so the more things you make it look at, the less of that attention any single earlier thing can keep.” This is borderline gibberish and it outright rejects the interesting question about LLMs and attention, namely that they have very different capacities from us. LLMs can read an entire OpenAPI schema in seconds and immediately construct valid requests from it. The article first points this out, and then switches to arguing that LLMs have similar limits to us. It’s completely incoherent.
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  ares623
  Reminds me of Rich Hickey's "Simple Made Easy" talk
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  metalman
  That is a good read, but as someone who tests in the first percentile for reading/listening, comprehension and retention, helps explain why many people who try to have discussions with me, shift there premise mid argument to fit there "evidence" and then cant remember where they started from, when reminded, and of course become agitated when challenged. Right now I am puzzling over how to deal with a part time employee, who is addicted to this sort of disconected "style" of discourse, and am useing a disturb and observe approach,and as it seems to go unoticed, is informative in it's own right.
• kumiko_studio
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• tatsuya-tamaya
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• kevinten10
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