I thought LLMs were a great tool for learning new topics - perhaps even complex ones. But overtime, I have had several frustrations with this. First, I get exhausted reading LLM prose. I really don't want to read anything generated by something like Opus 5 at this point. Second, as I dive deeper, I need a way to organize the information in a useful way as I begin to branch out in many different directions. I have tried to use the LLM to fix this by having it generate a web page with diagrams and organized information flow. It's an improvement, but I still run into the issues I described in my first pint - LLM prose is annoyingly dense, and the useful information gets lost in a bunch of noise. You can direct it do something like "use plain English and avoid LLM prose - provide only as much information as necessary to demonstrate the point", but it is once again only a marginal improvement.
And then I begin to think to myself that I should just read a book on the topic written by a trusted source who put a lot of effort into teaching the topic properly and presenting the information in a thoughtful way. So, I am back to books and mostly try to use LLMs to clarify certain questions or ideas I have.
It's much better to feed the book to the LLM and ask questions as you read along, instead of asking the LLM to basically write a custom book for you from scratch.
I have to agree with this. Completely relying on LLM for all your learning needs is a disaster. But being absolutely against use of LLMs isn't doing you any favors. This is where you don't have a formula but rely on you judgement and evidence of your having learnt something.
For example having an LLM summarize a dense topic and to find books so that you can filter faster and spend time reading those books works way better than having the LLM summarize the books or the topic (or even relying on second hand information). Another one is having the LLM quiz you on your topics of interest. With questions tailored to attack specific areas that you struggle with. Its wonderful at this, nothing I've used comes close to what an LLM can do here.
You define for yourself what your goals are, slowly refining them as you learn more, and use LLM as a tool. This ,I find works best for learning.
Make it your goal to teach a room full of other humans that topic. I guarantee you will know that material cold. I've done lots of technical training in my career and after teaching a class two or three times I find myself to be very competent in the topic.
It's long been the case that the best way to learn something is to teach something.
> It's long been the case that the best way to learn something is to teach something
Which is pretty unfortunate for those that want to learn. I used to enjoy writing documentation at work, it was my favorite part of the job. And it did feel like it benefited me more than it benefited all the people that were (or weren't) reading my documentation. Now I can't really justify spending much time on docmentation when LLM's can do it in a fraction of the time and it's "good enough"
I got started as a software engineer working in the nuclear industry in the 80s. We measured our documentation in inches not pages, and it was all written by hand. And I'll bet you the documentation in the nuclear industry is still written by hand and not by LLMs.
I sure hope those docs aren’t written by LLMs for many reasons!
i wonder if people who use llm's for business critical documentation would have the same opinion, and if so why?
I have used LLMs for safety sensitive tech writing and so have people I know. It’s pretty good at it, and you usually have a 95% ready to go product at the end of it. The last 5% can pretty easily be filled in by technical experts with way less time spent battling the type writer.
Is it perfect? No. But it suffices most of the time in a pinch.
Can’t speak to the nuke industry, but it’s pretty good at aviation related things.
There is still value in experts distilling knowledge and crafting it to the audience. I'm a consultant in cybersecurity and someone asked me "give me a best practice framework for good policy hygiene". I'm sure an LLM could spit out some tips, but I've been on the industry 15 years and can write in 5 pages what an LLM wouldn't conceive of in that space.
> Another one is having the LLM quiz you on your topics of interest
This is a great idea. I'm going to try it.
Even with the latest models today, the hallucination rate is absurdly high on anything deeper than surface level knowledge or something that can be directly scraped from reddit.
And you notice when it's a topic you know well or something like software where you can immediately tell the options it's giving you don't exist on the page. Leading to the amusing statement "LLMs are bad at what I do but great at everything else".
I've (elsewhere) written about this diminishing return effect on LLM utility in relation to increasing expertise.
The question: what's the net positive gain of turning people who know nothing in a given field into sub-novices, while weighing actual experts down with work slop and marginal returns?
And I wonder what the true cost is of arming so many novices with that level of dangerous knowledge.
The fact that some people get genuine value from LLMs when learning doesn’t contradict the fact that they’re Dunning-Krueger “expertise” generators. The fact that the person learning from them is in charge of ensuring they aren’t full of shit, which they frequently are, is an inescapable flaw in this process. I honestly think that reduces the value of these things to just above what you can find out with a search engine with most topics. Hey, great. An improvement is an improvement right? Is it an improvement worth trillions of dollars and screwing over writers and artists worldwide? Fuck no.
Sounds about right.
Tangentially, but related: I'm old enough to remember when the spirit of your comment was pervasive on HN.
It wasn’t even all that long ago. I noticed around the time ChatGPT 3.5 was released I saw a significant change in tone regarding LLMs and diffusion models. I think that’s when some serious astroturfing started.
I’m old enough that I worked my first IT summer job the same year slashdot was founded. I’ve seen a lot of tech tribalism form and dissipate, and this one didn’t feel organic. My gut says a lot of the us-vs-them tension originated in a deliberate campaign to cast AI boosters as the tech industry in-crowd, and ‘other’ the people not on-board. Who knows.
1000% astroturfing—and across social media. Too many posts of the same quality at the same time(s). These things ran in cycles, spinning up and dissipating just as suddenly.
E.g. the entire framing to combat complaints about shortcomings was, "It's not the tech. It's you. You're just not doing it right. Wrong setup, wrong workflow, add this to your .MD, use loops, etc". Every complaint was immediately met with this same treatment by a swarm of vague bro-bots that materialized from the ether. The core message? Always the human's fault.
And, don't get me started on the waves of newly minted expert AI creators, making recommendations without showing a single example of what they'd supposedly built.
I'm sure some bandwagon organic creators tried to cash in on the genre, but encouraging that was also part of the point.
I think the true cost will be some catastrophic failures.
Just hoping folks don’t get hurt due to people not understanding what they’re doing with these things but believing they’re competent.
If that is the case, I seriously doubt the blame would ever touch the people that oversold this shit.
I came across the socratic method recently, and have used it to learn a couple of topics that I was having trouble getting to stick. There are some SKILL.md's available for it. It works for concepts as opposed to facts, and causes the model to guide you to answers through your own reasoning, which is both much more engaging than reading a wall of LLM text and helps the information stick.
> I came across the socratic method recently
This statement would out you as someone who didn't attend an elite school.
Can you link the Skills.md?
The "Socratic Method" (aka maieutic) skills annoy me, precisely because when you read them they are the kind of low-effort, low-expertise crap someone who over relies on AI would naively come up with when tasked with the problem of coming up with skills for learning. "Hey the Platonic dialogues are pretty cool and smart, let's do that".
The body of literature on learning theory, and beyond that on specific types of learning and specific mediums such as learning from text is so rich there are way more useful models to draw from. Believe it or not, prellm, researchers in the textual learning field had already demonstrated you can achieve performance equal or better than novice tutors using pretty basic computer aids that follow specific hint/pump interaction structures. Guiding an LLM to use these findings has evidence backing it and is way better than telling it "i guess be like socrates". The problem is, to realize there might be richer more effective and highly researched ways of tackling the problem beyond the first fart of a thought you had one afternoon requires the deep respect for expertise and specialization that precisely basically everyone in the AI space right now fundamentally lacks.
Can you provide some references to the research you're referring to? Sounds interesting but you haven't really provided enough information to find it.
That is the point – you can't just provide the references in a short post here.
You need much more time and guidance.
Ironically, LLMs are pretty good at finding stuff like that from vague descriptions. With that, I think the parent commenter meant Art Graesser's AutoTutor work based on the terminology used (hint/pump).
TLDR: Actual human tutoring sessions were recorded and analyzed and Socratic questioning was barely used at all. Instead the following pattern was observed:
Pump — "Uh huh?" "What else?" Costs nothing, so try it first.
Hint — points at the region of the answer. "What about the pumpkin's motion sideways?"
Prompt — fishes for one specific word, with the sentence frame supplied. "The pumpkin keeps moving forward at the same ___?"
Assertion — just says it. "It keeps the runner's horizontal velocity."
I was so annoyed I made a Socratic wrapper based on predefined curriculum:
https://adaptive.bounded.cc
Trying to diagrams/animations didn't yield good results even with frontier models. But pure text, any model does a decent job.
I didn't expect this to be hit by hundreds of request per minute.
So it may be very slow or become unavailable, back end can't handle that, no caching whatsoever.
what a time to be alive! "if you're having trouble understanding what your robot tutor is trying to teach you, you can ask it to guide you to the concepts using your own reasoning. This is both much more engaging than reading a wall of the robot's text and helps the information stick."
Whats funny about LLMs is they are trained from books, but they are also trained to not output books, so how much of an LLM skews its output because a perfectly normal sentence could be a quote in like 300 different books?
i threw the entire sanderson cosmere into a RAG graph sorta deal just to see how it would do if i questioned an mcp server for it about a universe i know decently well. it was actually astoundingly good. was able to find easter eggs acrossed different books and answer dumb questions like "why is kaladin emo"
If you don't know why kaladin is emo, did you truly read the books lol. Every character has to deal with the stresses of war and most don't come equipped with good mental health to begin with, they're just normal people
i was more or less testing to see how complete of an answer it could come up by scanning the whole semantic graph so i threw questions at it that spanned multiple books
Sanderson is 100% in the training data
damn it good point
I also agree with this. LLMs are a great companion when reading a book to clarify things and dive into specific topics.
I'd imagine an application that uses LLMs will be created that better manages learning. It's just not clear what that UX is yet- it's obviously not just a chatbot
dumb question, but what is the best way to feed the book to the llm?
i run into context window limits, or practical limitations of digitizing the book
You need a non DRMd copy of the book. You don't have to feed it all at once, although with a 1M context limit it is doable. A few chapters at a time is enough, in my experience. An easy alternative is using NotebookLM (now Gemini Notebook), and that has worked brilliantly for me, but I haven't tested it for technical topics (for that I like the LLM to create graphs and e.g. interact with Mathematica, so I haven't tried it).
Hoping you get answer to this. I have the same question.
I prefer to have the LLM ask me the questions
This. Ask it to quiz you if you are feeling it.
LLM is still too verbose, a real person Socratic conversation can interact a couple sentences at a time, not spew 1-3 windowfuls of low density bullet points.
I even wonder if this behavior is due to next-token prediction architectures, somehow.
I don't understand some previous complaints. It's dense and verbose seem at ends to me.
I know you probably don't consider it dense but wondering if someone can shed insight.
I find them like empty calories, like programming youtube tutorials. They maximize for feeling learnt instead of steady progress
There are ways to ground an LLM to be concise, and Socratic (method of inquiry, back and forth dialogue)
This. This is exactly how I use them and I have had no issues so far. I read the book myself, then I point the LLM at it to ask questions about notions I might be struggling with.
I'm sorry, but why not just read the fucking book if you're interested?
[dead]
This is the exact opposite of what the parent comments are talking about.
I agree, I too like to read authored books. But there are certain topics, especially the new ones doesn't have good books yet. My post was to show that you can create books based on your interest, in a way that you like w.r.t to the content/tone/layout etc. It's a new idea made possible by LLM's. It might become the norm in few years I believe, where each one will be having a personlized library of books that they curate. So the point was to persuade the parent commentator that some books are better created this way.
LLMs can't "read the room" and infer how much context the audience already has, so they try include everything.
human conceptual thinking is very much a multi-dimensional graph, which relies on light "approximate" concepts that are "good enough". LLM AR token generation is extremely one dimensional and doesnt care about the "weight" of the concept behind a token.
LLMs hold billions of parameters in "mind" at once. humans hold like four "concepts".
This is the essential mismatch and the primary reason LLM conversation can be so painful and exhausting.
Explaining this and limiting "concepts" to four at a time tops is one of the very few AGENTS.md / system prompts I always use, and it has proven invaluable time and again.
Thinking traces show how effective this is at forcing the LLM to simplify its thinking.
[edit] Also, myself and nearly all of my peers are struggling to choke down the flaws of LLM tooling along with the benefits. the speed at which LLM adoption is being forced, without truly crafting them into quality tools first, is not ok, and not normal.
LLMs have stirred an inhumane hunger and fear. the tech is fine, but the way tech companies (creators and consumers) are behaving should be deeply questioned.
it's NOT normal. it's not ok.
I’m curious where you get the estimate that humans hold “like four” parameters in their mind at once?
Cowan (2001) is an oft-cited paper proposing three to five "chunks" of capacity in human attention: https://www.cambridge.org/core/journals/behavioral-and-brain...
The full PDF is worth a read (Figure 1 may be of interest to many here): https://www.cambridge.org/core/services/aop-cambridge-core/c...
If "attention is all you need" then it's something we do indeed lack, in comparison to LLMs! But it's an interesting question: might machine cognition benefit from similar bottlenecks in an attention algorithm? Advancements like Kimi Linear seem to indicate that we're far from the finish line: https://arxiv.org/abs/2510.26692
updated the comment. i meant four "concepts". i dont reason about my own thinking in terms of parameters.
Would you be willing to provide an example (even a contrived one) of how this "four at a time" prompt changes the LLM's behavior?
I just want to understand more.
Also, would you be willing to share the actual text of it that you put in AGENTS.md?
>I really don't want to read anything generated by something like Opus 5 at this point.
Personally, I find that its generated prose tends to have an undue weight to it, almost as if every topic I ask about somehow bears a heavy burden, or is otherwise load-bearing, to use its parlance.
Quite puzzling, really.
It has a sort of metronomic quality. It never slows down or speeds up or modulates its tone. It plods forward at a relentless pace and never has a light touch with anything.
I think this is one reason why LLM text is pretty exhausting to read for long stretches.
>It has a sort of metronomic quality. It never slows down or speeds up or modulates its tone.
It's possible that this quality you describe stems from the extensive training corpora utilized by the major AI labs. These almost certainly include work from the esteemed economist Jacob Silj:
https://www.youtube.com/watch?v=Poc1upTejD8
Yes!
I have a personal theory: LLMs are *fundamentally* handicapped at perceiving what's going on in the mind of the human (this can't be "innovated away") and that's at the root of what makes them suck at conversation.
Next time you're chatting with someone, notice how much understanding is shared without anything being said. E.g. the other person might share something deeply disappointing, and they can tell without you even saying anything whether you get what they're going through. This unspoken-yet-communicated information guides the conversation. Or as another example: humans can read the room -- you walk into a room and immediately adjust your demeanor based on what you see and sense.
LLMs are totally blind to things like this, and this adds an inescapable awkwardness to interacting with them. I don't believe they'll ever grow out of this. Which thankfully implies more long term demand for humans instead of robots. :)
Very well observed. I found one more thing: they fail to consider what a 3rd person might understand from your conversation, so when you ask it to dump stuff into a Documentation, they keep making references to facts you had previously discussed or to the train of thought, completely irrelevant to bystander.
100% -- this is the worst. Referencing all sorts of "words with made up contextual/analogous meanings" based on the conversation...outside of the conversation.
Does anyone have a read on if this is primarily a Claude issue, or if all LLMs do this?
Tech guy discovers conversations with humans.
Even over phone calls you get a sense so unless it's in timing it isnt demeanor either
No, they're just trained to impress the C-suite motherfuggers with dense vocab.
I have had very similar experience! I wanted to learn Probablistic ML, checked out a couple of MOOCs, but didn't find any that were at my level - some were too advanced, some too beginner level. Claude was unable to one-shot a course, so I am now asking it to generate it module by module. But even here, it is not doing a very good job. I muddle through the concepts that it has written, do a whole bunch of back-and-forth, which tbh is exhausting, and then rewrite everything in my words so it actually makes sense to another human being.
> I get exhausted reading LLM prose
So much this! If I see one more sentence with the words "genuinely" juxtaposed with "load bearing" my head is going to explode!
btw, I am building the tutorial here for anybody interested in this topic: https://github.com/avilay/learn-probml
i’m personally deriving a huge amount of value from the custom materials fable is assembling for me. for example i asked it to write a focused expository math paper on reed solomon to accompany an implementation module that it wrote for me. it’s remarkably useful to steer it to create graphs and diagrams of exactly how you like the material presented. or the bibliography researched and cross-linked with the body or the order you want your questions addressed.
it also researched vision correcting displays for me and i can finally put that idea to bed - i was never really going to pick up an optometry textbook tbh. plus it was able to pull together a bunch of geometric and physical context about light and the eye plugging exactly my personal knowledge gaps.
in general i suspect these materials might not be that interesting to others because they are so custom to my learning style and personal needs and preferences.
these are usually not one shot documents but rather many prompts deep before i get something I’m willing to sit down and read or study. but dramatically quicker than assembling it myself from primary sources. i wouldn’t say it matches master expositors but then they’re not available to write on any topic i happen to need right now.
plus I’ll just have a live voice discussion with the system when i go for a walk and there are still things bothering me on a topic. it takes a little patience but if i’m in the mood it’s amazing.
i generally find that it can help track down specific references if i suspect hallucinations. but especially on factual topics my experience so far has been extremely encouraging.
Good point. Same with me. Despite it being very tiresome, all the back and forth that I do with it really deepens my understanding of the topic. I have been on Opus so far, let me try Fable and see if it gets better. I haven’t tried voice either. Next time I go for a walk I’ll try that!
I never used office hours as a student, which I later regretted because it made me work longer and harder to perhaps achieve somewhat better understanding in some classes, but also I dropped every proof-based math course I ever took. Overall I think my education would have been stronger by attending office hours.
I view LLMs in education similarly to office hours. Some people abuse it to get homework answers without grappling with the material, but the optimal amount is not zero.
LLM certainly not a replacement for a book, where you get someone’s extended personal approach to a topic, thoughtfully organized, reviewed and edited, often times actual courses taught based on it, with answers checked and errata available online.
I completely agree. I have vibe coded what i would consider to be some pretty weird things in the name of learning facilitation.
Perhaps the best example has been a native macOS app that is a completely custom text editor with built-in debugger, lsp support, fuzzy finder, etc stuff you'd expect. Inside the same app is a library of books i can read within the app completely formatted and for every chapter/section of each book that is a quiz to take (LLM generated of course), a "recitation" tab where i am asked a question and say outloud my response to the AI to evaluate me on and then finally practice problems to do within the custom text editor (these are usually programming books). The reader also has ai re-write built in.
As neat as this is, and i worked through K&R like this, i have ultimately fallen back on "just read the damn book and go to the AI when you've got questions."
I've decided that the main thing I'm building is my own mental model. You can take notes, create docs, put graphs and websites together, but unless I'm just trying to generate some reference material the only real objective is to develop the understanding and intuitions inside my own brain.
So I have the LLM offer a very short explanation of something, and from there's it's just me asking questions. Anything that feels fuzzy or not fully internalized is something I poke at until I'm satisfied.
It really has helped me develop a sensitivity to what I understand vs what I don't, and the ability to drill into any part of it is amazing.
I do this too. I use Claude. I picked a voice I like. I go on a three mile walk. I will ask it questions about a topic that I want to learn about. If it starts telling me more than I want to hear right then, I will say "stop". It doesn't get offended. I then ask it something else. I find this very effective. I control it so it only explains to me what I want explained. If what it says sparks questions on a related topic I jump to a brand new topic. No personal tutor could keep up with this or adjust to exactly how I want to be addressed like Claude does. I'm very excited about the progress I'm making mastering new topics.
And yes, it is not that it is just presenting the facts. By me taking control of the direction the questions and answers go, I can flesh out my mental model. I won't retain every little thing it tells me. But I am much farther ahead than before.
Can you say what topics you’re using this method to learn? I think it would be more effective for some than others.
Good to know other people who get migrane reading LLMs dense prose. I started reading books again recently, since everything online is polluted by LLM prose. What i realise, is that a human author, especially a teacher understands the learning pathways of new learners, they motivate the learning, and start from simplest concepts (a spherical cow), and then building all the complexities. This helps us to emphasize on most important concepts, while throwing away unnecessary complexities. While reading LLM prose is like reading a research article, that is written to an expert in the area, that talks about bleeding edge, with full of jargons, caveats, that just is not conducive to the learning process for a new learner.
Also they tend to assemble complex jargon in obtuse or meaningless ways, which makes reading and parsing and understanding much more difficult. Tends to reveal that LLMs fundamentally do not have "understanding", just likely word generation
To me, it's just Claude. The other models have their quirks but nothing is quite like Claude.
But even with Claude, it's it's really the prose getting in the way you can install the caveman plugin or tell it to use that "standard technical English" thing.
Can you elaborate more on juxtaposing Claude's terrible prose with other LLMs?
Any more detail you can share? Do the others feel more "human"? Are there any that are particularly digestible/human-friendly?
I've been wondering for a while if this is just Claude because I mostly use Claude, so this is very telling.
I wish I had something more methodical I could show. It's all subjective, but GLM-5.2 feels more human to me. Even GPT-5.6 Sol tends to be easier on the eyes for me (though the stereotype of it overengineering and no common sense are still true).
I tried using a new agent service recently and could tell immediately that it's powered by Claude due to the way it writes.
I had the same problem - Opus models past 4.7 tend to inflate output tokens for no good reasons, introduce innumerable jargons and is a pain to read. Then, I cam across this: https://github.com/ayghri/i-have-adhd/blob/main/skills/i-hav...
You can either install that skill or put the Rules section directly in your Global CLAUDE.md for Claude or Personalization setting for Codex and it should cut down the output verbosity by quite a fair bit.
The sycophancy is also a concern, it’s not really an impartial teacher, all its training is to suck up and maximize engagement rather than learning. The incentives are wrong.
> all its training is to suck up and maximize engagement rather than learning
That's speculative, isn't it
No, that's a direct consequence (intended or not) of how RLHF works.
I use the LLM to point me at relevant books and papers. But there is still a trust problem: I am trusting the LLM to point me at reliable, trustworthy sources.
I'm not sure I'm better off with humans though -- I'm not qualified to judge whether a source is a proper authority, not an I qualified to judge whether someone knows enough to point me to a reliable source.
It seems this is a fundamental epistemological problem to which there may never be an answer.
I have the exact same experience, so reassuring to know I'm not the only person who feels this way.
I will say, opus 5 is an egregiously bad case of this, but other LLMs have this too, just less bad.
I have been using LLMs to help me turn my journals into interconnected notes and sometimes it is so confusing to read the notes that it doesn't resemble any human would write. Its like the models are getting stronger while also losing its touch to write human sounding sentences on complex topics.
> First, I get exhausted reading LLM prose. I really don't want to read anything generated by something like Opus 5 at this point.
Agreed.
I find Opus 5, and even Fable, to be overly wordy in eg PR descriptions and code comments.
However, I suspect that's more to do with what they are trained to do by default than LLMs in general. I have a little setup where I tell Claude to work together with Codex to tighten up prose and comments, and for me that produces much more palatable text that needs less human editing afterwards.
I think one problem is that books are not customizable, and many books are aimed at people with some certain knowledge. With LLMs, you can tell it what your knowledge level is and ask it to customize the answer for you. This is difficult to achieve with books.
> generate a web page with diagrams and organized information flow.
Sounds like you'd be just as well off link-surfing Wikipedia?
> I really don't want to read anything generated by something like Opus 5 at this point.
Recently switched to OpenAI and I've gotta say Sol is so much better at writing than Claude. Opus has a distinctive sentence structure and Fable somehow manages to be even more obtuse. The personality of these models really does come through...
Claude code has a „fork“ feature where you can fork an existing conversation and keep talking in the fork and then you can go back to the original of the fork. You can fork as many times as you want and let LLMs write to a markdown file to keep important facts and learnings - also good for agents to do research without expanding the context window
> I get exhausted reading LLM prose.
While my advice is specific to learning about codebases, the way I do it is to have it generate mock data and put it in the local development environment, and give me some exploratory commands, and then ask away. It's a machine after all, so I don't have to read its preceding prose to understand whether it did tell me something, it can just repeat it however many times I ask it, and the hands on commands etc. give me something to actually try and implement.
I think there's an underrated difference between information generation and pedagogy here. LLMs are very good at producing more explanation, yet "more explanation" is often exactly what you don't need when learning something difficult
You can make something like the link below. I'd say it's a more than marginal improvement. It's still tiring, but it's much better according to my taste. I imagine everyone would have their own version of this for their own preferences.
It's a loop that uses adversarial review to check several dimensions of the writing:
https://github.com/Vibecodelicious/llm-conductor/blob/main/w...
> LLM prose is annoyingly dense, and the useful information gets lost in a bunch of noise
This is my biggest gripe with reading AI-generated text as well (ignoring the meta issue of whether it's worth taking the time to read something that an author didn't think was worth the time to write). It's gotten to the point that weird AI-style analogies just take me completely out of the text and kill my interest.
And I can usually tolerate a lot of purple prose.
Have you tried using the caveman skill ? :D Might be worth a try if you dont like long prose https://github.com/JuliusBrussee/caveman
Even if you tell the LLM not to use LLM pros they (still) do it. If you feed the Wikipedia article on signs of AI writing and tell them to use none of those signs they will also (still) do it. I have tried (many times) to get an LLM to explain a concept to me, or a process, or an algorithm or what have you, and every time they cannot help themselves. Either they use LLM pros, or they get so verbose that it all just becomes noise and I spend more time filtering out unnecessary jargon than I do reading let alone learning anything.
I ask them to use Simple English and a jargon of the domain. This seems to work best for me.
For Gemini 3 this seems bit to be the case. If you use gems you get completely different personalities - so different that its almost scary. You can create gems which are really insulting, gaslighting or seemingly of a specific profession
I've found it helpfull to ask the LLM to generate a sylybus for the topic. treat the sylybus as a design doc for a price of software. i find they do much better when they have subtasks to focus on. they can do big picture and small picture, but they can't do both at the same time.
> First, I get exhausted reading LLM prose. I really don't want to read anything generated by something like Opus 5 at this point.
I’ve found the tone of Kimi K3 to be less obnoxious. Unfortunately it doesn’t wholly solve the issue, I don’t think any LLMs out there have a truly pleasant writing style, but at least not every assumption is “load bearing”.
Same. I usually just read the book along and ask questions on a specific part, rather than trying to get the LLM to produce an entire study guide for me. It seems to work better as a Q&A than a "teach me" advisor
Yeah, I am currently trying to work with Opus 5 to refresh myself on deep learning fundamentals, and... it's a mixed bag. I'm glad I already am familiar with the subject matter, as I can prompt for refinement and improvement. It is kinda following the Karpathy videos so far (a couple lessons in) but adding more math/derivations, which was what I asked for. It has trouble staying on topic, presenting information in a coherent/meaningful order, and providing all the context necessary to move through steps in its "course notes".
Like I said, I'm essentially continually prompting to refine the material. LLMs certainly continue to append, and never cut back. It just keeps spitting out additional content at me. So that's a bit annoying too. But I can basically get figure out what's going on with a few extra promps.
If youre curious what i've got so far... just be warned it is quite literally AI slop plus me continually prompting for clarification/cleanup etc. : https://github.com/cmoscardi/ai-for-ai
opus 5 doesn't follow instructions that great. probably needed that extra "creativity" to benchmax. if you are stuck on anthropic, try Opus 4.8 or Fable5 a try with the same prompts. very different results.
To get rid of the llm prose issue you can take a representative sample of its prose (say a question and its answer), rewrite the answer in the way you'd prefer, and add that to the system prompt; I did this to get my LLMs to compress down what they say, and now everything they say is very dense and to the point
I have been using this tool for the past few months that was posted on here: https://github.com/devenjarvis/lathe
It generates tutorials for you, and serves a webpage that lets you complete them. It does a remarkable job.
It still has a bit of the LLM prose problem, but it does help you fine tune the ‘voice’ it uses.
anybody adds some prologue about what style of answers are prefered ? i know i often try to change the linguistic patterns because i too (unsurprisingly) am tired of llm prose.
I've heard people promoting LLM to use ASD-STE100 Simplified Technical English with some improvement.
So you want it to teach you and take notes for you?
> want to read anything generated by something like Opus 5 at this point
I've stopped using CC because of it. I find it insufferable.
Opus 5's language is just terrible
"hey LLM, I'm trying to learn about ___. I already know ___. My favorite authors are ___. Suggest some reading material."
It annoys me that the default AI mode is so tedious and longwinded. I read a lot of nonfiction - the house style of AI is basically marketing copy.
>LLM prose is annoyingly dense, and the useful information gets lost in a bunch of noise.
This problem doesn't get talked about enough and is second only to the hallucination problem IMO.
AI produces so much noise to wade through in order to find signal, and the more expertise you have in a field the more that costs. That noise directly subtracts signifcantly from productivity gains.
And, I think the problem is directly related to the hallucination problem. It feels very much like an effort to kitchen sink the response in order to provide some value among possible hallucinations.
It also seems to be a byproduct of Gen AI operation. It just fundamentally doesn't understand what it's outputting, so doesn't know how to narrow down to the most salient bits.
> LLM prose is annoyingly dense
It's just long. It just doesn't shut up. It's overly verbose. And you can't tell it to be concise or you degrade its quality.
If I ask what an integral is, the correct answer is that it is the continuos analog of a sum, generally used to calculate areas and volumes.
It should really be a single sentence, and then let me ask more about the terms I don't understand, and here's the beauty, in the previous one there can be only 5 terms I cannot know.
An LLM will vomit an entire page or more of explanation which isn't bad per se, but is an answer to something different: "give me a short introductory explanation to integrals". And that's not what I asked.
I call that vomit shotgun answers, text from which you have to filter out all the extra info the LLM wasn’t asked for. Luckily you can control that behavior and make it behave closer to what you want. Just ask the LLM how to ask for it.
The new Google Translate. They've made it slightly better at translating paragraphs of text but in many cases it's lost the basic function for translation: dictionary.
Try it out, fairly sure that if you out in 100 random words for 30 of them it will just refuse to translate them (it will copy paste the original word into the target language) or it will do silly things like use the target 4th dictionary definition instead of the primary one).
Its aligned in getting you interested and frustrated about a topic enough to go to a primary source you would have never looked at
LLMs help me refine my search. If I want to dive deeper into any topic, I can yield a strong list of primary sources relatively quickly.
something to try that works really well is to put "explain this as if you're talking to a 5th grader" at the end of your request.... it just breaks down the text into more manageable sentences that can be understood by general audiences
You can instruct it to be terse and even take on a specific voice if the standard prose bothers you.
I think AI is surprisingly good at this. I use voice mode while working out to learn complex topics, follow up with reading, and then go back to ask the LLM more questions. They excel at simplifying complex ideas and have endless patience. One hack I found is telling the LLM to test my knowledge by asking me questions—that gives me a clear idea of what to read next. Overall, they’re a great tool to use alongside traditional learning methods like reading books and working through practice problems.
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This is on top of the issue of LLMs being a moron. like, I'm sure dumb people can learn stuff from them, but I'm sticking to books written by people who know what they're talking ahout and not vibed slop.
AI hater here. Too me this story is all to predictable. This is exactly how I thought using LLMs to learn would go. Or in simpler terms: well duh.
I'm actually going to make a prediction here as well. I think you will soon realize that using LLMs to clarify certain questions or ideas you have will turn out to have frustrations as well. And that you will soon direct those questions to either peers you know in real life or internet forums which are very likely to have a non-AI policy.
> I'm actually going to make a prediction here as well. I think you will soon realize that using LLMs to clarify certain questions or ideas you have will turn out to have frustrations as well.
Much more likely that people will believe themselves to be an expert in a subject after having had a conversation with Claude about it.
Wild because people wouldn't do that with a friend. Something about an LLM giving people info has this insidious stoleb valor to the LLMs work. Like that wasn't your thought, you just google searched it.
> First, I get exhausted reading LLM prose.
Often "be concise, to the point." is enough, but you can also paste it some stuff you like as an example text and ask to do style transfer.
You can change the prose that it outputs to anything you like. ask the llm how.
Specifically, you can set the tone and style to match what you like or used to after asking it to interview you, create an output, and then use that output as the project description or document to refer to
This feels like the weirdest complaint to me. Just tell it to shorten its response.
Literally saying "one sentence response" solves most of this problem.