[HN Gopher] Reading across books with Claude Code
___________________________________________________________________
Reading across books with Claude Code
Author : gmays
Score : 133 points
Date : 2026-01-16 18:49 UTC (1 days ago)
(HTM) web link (pieterma.es)
(TXT) w3m dump (pieterma.es)
| jszymborski wrote:
| This is all interesting, however I find myself most interested in
| how the topic tree is created. It seems super useful for lots of
| things. Anyone can point me to something similar with details?
|
| EDIT: Whoops, I found more details at the very end of the
| article.
| alansaber wrote:
| He asks g2.5 flash to assign a topic. I am also interested in
| the best way to develop a general schema- there is a good deal
| of literature on this but nothing stands out, I think the
| standard approach is open ended classification generation using
| a single model then binning. Actually the novelty in his
| approach is first asking if a chunk is useful (ie adding a
| filter for non-semantic information) which I would normally do
| at the dataset creation stage.
| duck wrote:
| Discussed earlier this week:
| https://news.ycombinator.com/item?id=46567400
| kylehotchkiss wrote:
| In several years, IMO the most interesting people are going to be
| the ones still actually reading paper books and not trying to
| shove everything into a LLM
| hungryhobbit wrote:
| I don't think the Venn diagram of those people and everyone
| else is as separate as you imagine.
|
| I'm a Literature major and avid reader, but projects like this
| are still incredibly exciting to me. I salivate at the thought
| of new kinds of literary analysis that AI is going to open up.
| imdsm wrote:
| the people most likely to analyse books like this are those
| of us who are more likely to read them as well
| pradmatic wrote:
| Sure but those people don't have to be mutually exclusive. At
| the very least, a tool like this can help me decide what to
| read next.
| alansaber wrote:
| I can't wait to have the LLM autopilot my neuralink whilst i'm
| in VR mario kart.
| fatherwavelet wrote:
| I still read a lot of books and I use LLMs all the time. I have
| even got a bunch of book recommendations from LLMs. Imagine
| that. You actually have agency over these tools. I know it is
| hard to believe for some.
| gulugawa wrote:
| [flagged]
| gjm11 wrote:
| I agree that we should be reading books with our eyes and that
| feeding a book into an LLM doesn't constitute reading it and
| confers few of the same benefits.
|
| But this thing isn't (so far as I can tell) even slightly
| proposing that we feed books into an LLM instead of reading
| them. It looks to me more like a _discovery_ mechanism: you run
| this thing, it shows you some possible links between books, and
| maybe you think "hmm, that little snippet seems well written"
| or "well, I enjoyed book X, let's give book Y a try" or
| whatever.
|
| I don't think it would work particularly well for me; I'd want
| longer excerpts to get a sense of whether a book is
| interesting, and "contains a fragment that has some semantic
| connection with a fragment of a book I liked" doesn't feel like
| enough recommendation. Maybe it is indeed a huge waste of time.
| But if it is, it isn't _because it 's encouraging people to
| substitute LLM use for reading_.
| imdsm wrote:
| commenter above probably didn't read the post, ironically
| ryan_n wrote:
| Guess we need "reading across hacker news articles with
| Claude code."
| mikkupikku wrote:
| I zgrep my epubs, is that a problem too?
| stavros wrote:
| I need a name for people who dismiss an entirely new and
| revolutionary class of technology without even trying it, so
| much so that they'll not even read about any new ideas that
| involve it.
| imdsm wrote:
| we call them luddites
| lsaferite wrote:
| I'm not entirely sure that's a fair association. The
| Luddites weren't against technology in general, they were
| fighting for their livelihoods. There very well could be a
| fresh luddite movement centered around the use of AI tools,
| but I don't think "luddite" is the right term in this
| specific case.
| ironbound wrote:
| No that was a labor issue, abusive factory owners got
| targeted.
| dang wrote:
| The HN guidelines include the term "curmudgeonly", which IMO
| is fair.
| smakt wrote:
| And I need a name for shills that handwave the whole magic
| thinking in a blog post and conclude with "oh my claude code
| pointed out correlations between atlas shrugged and steve
| jobs" I'm so much smarter and ready for the future that's
| coming.
|
| You are damn right I didn't try it out. I try things
| published in journals, vetted by peers, with clear
| explanations and instructions. On the other hand, when the
| tone is "It's All Magic Sprinkle(TM)" my pseudoscience alarm
| goes off.
| stavros wrote:
| Why are you reading this comment section? Nothing here has
| been peer reviewed. In fact, all my comments here are
| written by an LLM, because I can't be bothered arguing with
| closed-minded people.
| dang wrote:
| " _Please don 't post shallow dismissals, especially of other
| people's work. A good critical comment teaches us something._"
|
| " _Don 't be curmudgeonly. Thoughtful criticism is fine, but
| please don't be rigidly or generically negative._"
|
| https://news.ycombinator.com/newsguidelines.html
| voidhorse wrote:
| This was posted before and there were many good criticisms raised
| in the comments thread.
|
| I'd just reiterate two general points of critique:
|
| 1. The point of establishing connections between texts is
| _semantic_ and terms can have vastly different semantic meanings
| dependent on the sphere of discourse in which they occur. Because
| of the way LLMs work, the really _novel_ connections probably won
| 't be found by an LLM since the way they function is quite
| literally to uncover what _isn 't novel_.
|
| 2. Part of the point in making these connections is the _process_
| that acts on the human being making the connections. Handing it
| all off to an LLM is no better than blindly trusting authority
| figures. If you want to use LLMs as generators of possible
| starting points or things to look at and verify and research
| yourself, that seems totally fine.
| smakt wrote:
| One has to be the special kind of stupid that is blinded by
| efficiency promises from the LLM Church to think the article is
| any worth.
|
| It's the usual jargon soup. Publish a vetted paper with
| repeatable steps instead of a hyped-up, garbage, supposed 100x
| productivity bomb.
|
| And his best result is mechanical findings from where the LLM
| got the highest correlations between its vectors: Bravo;
| there's always going to be a top item in any ordered list, but
| it doesn't make it automatically interesting. Reading
| literature is about witnessing the journey the characters take.
| Reading technical material is about memorizing enough of it. In
| both cases the material has to go through a brain. I find it
| idiotic to assign any value to outputs like "Oh King Lear's X
| is highly correlated to Antigone's Y"
| skeptrune wrote:
| I really like the idea of the topic tree. That intuitively
| resonates.
| ebiester wrote:
| I did a similar thing with productivity books early last year,
| but never released it because it wasn't high enough quality. I
| keep meaning to get back to that project but it had a much more
| rigid hypothesis in mind - trying to get the kind of
| classification from this is pretty difficult and even more so to
| get high value from it.
| doytch wrote:
| The mental model I had of this was actually on the paragraph or
| page level, rather than words like the post demos. I think it'd
| be really interesting if you're reading a take on a concept in
| one book and you can immediately fan-out and either read
| different ways of presenting the same information/argument, or
| counters to it.
| Ronsenshi wrote:
| For me this looks like a great way to build connections between
| books in order to create a recommendation engine - something
| better than what Goodreads & Co provides. Something actually
| useful.
|
| The cost of indexing using third party API is extremely high,
| however. This might work out well with an open source model and a
| cluster of raspberry pi for large library indexing?
| padolsey wrote:
| The incumbants Goodreads and their owner Amazon have indeed
| done such a poor job at this. Seven years ago I tried creating
| a basic graph using collaborative-filtering (effectively using
| our actual reading patterns as the embeddings space instead of
| semantics [human X likes book Y so likers of Y might like other
| things that human X has enjoyed]). It works well to this day
| (ablf.io) but the codebase is so ugly I've not had the bravery
| to update its data in a couple of years.
| alansaber wrote:
| Yes imo this is very useful but there's not a clear industry
| standard on how to do so yet, which I imagine will change?
| Tell me if i'm missing something
| nubskr wrote:
| I've been using Claude Code for my research notes and had the
| same realization, it's less about perfecting prompts and more
| about building tools so it can surprise you. The moment I stopped
| treating it like a function and started treating it like a
| coworker who reads at 1000 wpm, everything clicked
| lloydatkinson wrote:
| How can anyone even trust crap like this? It was only a few days
| ago Claude and ChatGPT hallucinated a bunch of stuff from actual
| docs I sent them links to. When asked about it, they just
| apologised.
| mpalmer wrote:
| Synthesizing 500 words at a time into digestible topics is
| significantly less prone to error. You're giving it a lot of
| info and asking for an organized subset. It's good at following
| such direction.
|
| In your example, you're doing the inverse (give me a lot of
| text based on a little), and that's where LLMs have no problem
| hallucinating the new information.
| alansaber wrote:
| Exactly the more tightly scoped the problem the less
| stochastic noise. Even better if you can add more signals
| based on deterministic algorithms like keyword presence etc.
| It gets very domain-specific very fast
| zkmon wrote:
| I used AI for accelerating my reading a book recently. This is a
| interesting usecase. But it same as racing for the destination
| instead enjoying the journey.
|
| It kills the tone, pace and the expressions of the author. It is
| pretty much same as an assistant summarizing the whole book for
| you, if that's what you want. It misses the entire experience
| delivered by the author.
| alansaber wrote:
| Yes AI subsumes edge cases to produce a very uniform _optimal_
| writing (what we call AI slop). I am assuming this is a book
| you were reading for knowledge work, not for fun? Not heard
| about people recreationally using AI for consumer content that
| 's a bridge too far for me lol.
| CuriouslyC wrote:
| It's not optimal. It's overwritten, repetitive, cliche and
| increasingly incoherent over longer generations. I say this
| as someone who likes AI and uses it to create rough drafts
| and structural revisions of my ideas.
| alansaber wrote:
| Exactly stochastic but statistically optimal based on a
| bunch of very broad range of text which often is not
| actually good writing
| rbbydotdev wrote:
| I had a similar toy project. Attempting to make custom day trips
| from guide books. I immediately ran into limitations naively
| chunking paragraphs into a RAG. My next attempt I'm going to try
| using a llm model to extract "entities" like
| holidays/places/history and store them in a graph db coupled with
| vectors and original source text or index references(page +
| column)
|
| Still experimental and way outside my expertise, would love to
| hear anyone with ideas or experience with this kind of problem
___________________________________________________________________
(page generated 2026-01-17 23:01 UTC)