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- Hacker News
- > What you get is a beautiful animation that is 100% accurate and free of hallucinations
I can appreciate using all of the tools at your disposal to learn a new topic, and in no way want to discourage learning. I've used LLMs myself to question my own understandings and it can be helpful.
However, "... 100% accurate and free of hallucinations." isn't a statement someone who just learned the topic is capable of honestly stating.
by URMAJESTY68 - I only use LLMs for explaining things if the subject is one I’m deeply familiar with and can independently and easily verify the facts. Doing so with new knowledge areas is very risky for obvious reasons.
For example, “explain how the code in this file works,” I am familiar with the overall codebase, I know the purpose of the file, and I can read it or write tests to verify if I suspect what it’s telling me isn’t correct. Or, if it’s really important, I can overcome my introvertedness and ask the team member who wrote it…but that’s a last resort nowadays, which I am very thankful for. In 99% of cases since at least Claude 4.2 days, Claude and Codex have been very accurate. Gemini on the other hand messes up more frequently and sometimes does weird things like try to delete files it’s not familiar with, at least the 3.6 flash model I’ve been using lately does this. But, code explanations are still good for the most part.
by Revanche1367 - 100% agreed.by controlbird
- I once uploaded a 700 pages book and quizzed chatGPT strictly on its contents. It answered somewhere between 60-90% across 6 quizzes. This was 2 months ago. Those quizzes were fact checking statements, not even problem solving.
I'd be extremely cautious to ask it to have it explain any specialized concept even from a document.
by Thanemate - The title is not representing what the post is about. “Use LLM to learn complex topics” here actually means that the author asks an agent to describe the problem area, and then implement a simple web-based simulation game, and by playing that game, the author actually learns about the topic and its constraints. They use chip making as an example.
That's actually a fun way to learn processes!
by ventana - Thanks! The original title was "How I use LLMs to learn...", but somehow HN removed the "How" part. I even removed the initial post thinking it was a typo on my end and tried to post again, but I stumbled upon the same behavior.by laurentiurad
- Its fun but is it really effective ? I mean I checked the LLM one and I came out more confused about a topic I already know about, I find the best way to to learn using LLMs is to just generate an example try to somewhat get a mental model of how it works and then ground my understanding with traditional documentation and resources, its an iteration of a technique I used to do in college where I would read the textbook questions first to understand what is important and then read the chapter
- > In plan mode (using CC, or OpenCode) I ask a model to build the foundational knowledge for X topic.
Makes sense.
> I ask it to review the accuracy of the knowledge base it built in the previous step.
Ooookay that sounds good.
> I proceed asking it to build a simulation of that topic in a low-poly, Rollercoaster Tycoon-like animation.
wat.
by muh_gradle - It's such a surprising and delightful turn, I love it!by ch4s3
- Author likes this kind of animation. I have something similar like this, but without the animation step.
The main idea is you can do any style you want or like to learn.
by lfx - I’ve been using LLMs to create readable rewrites of RFCs and specs that interest me. It is not precise enough for implementation use, but it has increased my understanding of the underlying RFC.
Another useful approach has been asking Codex to implement complex things, like a Kademlia DHT or BitTorrent client in a literate style with the explicit purpose to increase understanding by reviewing the source code.
Examples: https://rickcarlino.com/notes/note-dump-and-ai-summaries/ind...
by rickcarlino - The biggest thing I've learned from doing stuff like this is that there are no shortcuts. At some point or another, to truly learn something deeply, you've got to dig in to the boring details and do things the hard way. LLMs can help with this...but I find it's usually tempting to try and just offload the boring stuff to them, which doesn't work.by royal__
- yes i've found that there are a few topics that i've really been able probably 10x my understanding of using LLMs, in particular in getting me over hoops that are hard to navigate when solo, BUT I have to be really careful for it to not just show me the answer all the time.by mhh__
- The LLMs are a way to get quick feedback and getting it promotes quicker learning (if the feedback is good). Learning is difficult, sometimes I get blocked on something and before llms that could prevent me from learning some material, nowadays I have another tool to help me unblock and learn faster.
I think that could be called a shortcut, not in learning per se, but in the process of getting to learn.
by mfalcon - Quite - you still have to do the work yourself. I think LLMs are best placed to act as an eager tutor that doesn't mind discussing a topic ad nauseam until you're certain you understand it.by ainch
- > The biggest thing I've learned from doing stuff like this is that there are no shortcuts. At some point or another, to truly learn something deeply, you've got to dig in to the boring details and do things the hard way.
This is the only path to mastery, or understanding if one prefers. There are no shortcuts to a person achieving deep understanding (a.k.a. "Aha!" moments).
Can a tool such as GenAI be beneficial to someone who already has done the work to understand? Absolutely. But it cannot infuse mastery into a person simply by its use.
Only the time and effort a person devotes can do that.
by AdieuToLogic - I’ve found that if I’m not struggling I’m not learning. If stuff is coming fast and easy that’s a sign that what I’m doing is not stretching existing skills enough.
It’s true of most things. Running, dieting, weightlifting being uncomfortable is a sign of progress.
by yoyohello13 - Having an initial higher level understanding across the domain is extremely useful to contextualize the deeper stuff. I think boring details is a very leaky characterization, but I'll continue with it.
In my experience it's infinitely easier and faster to learn deep, "boring" things when you understand how they relate to your shallow and wide understanding of all of the related components.
The LLM is merely a tool. And you can use it for domain discovery that enables efficient deep learning at an unprecedented rate or you can develop a cursory understanding of a topic and think yourself an expert.
by hahahacorn - What’s everyone’s opinion on learning new tech things in this day and age? My opinion swings between positive and depressing vision of the future.
I still learn new stuff, but I’m afraid it won’t have any value in a year or so.
For example, I’m pretty good at optimizing low level stuff, but right now you can just ask LLMs to do so and they are pretty good at it. They will profile the code and suggest reasonable options like 90% of the time.
by f311a - I have staff ranging from 10 years of IR experience to right out of college.
I can tell you that there is an enormous gap in ability between them despite them both using LLMs for daily IR work.
The reasons aren’t complicated. The senior responders have tacit knowledge of how breaches evolve and what to look for which gives them a much better framework for where to employ the LLM.
The juniors will normally start from “here are some logs, look for weird” which is fine but leads to tunnel vision and a lack of confidence in their reporting.
I don’t mandate that anyone do work with or without an LLM. I hire seniors based on experience and juniors based on interest. But my experience has so far been that our best up and comers focusing more on learning the technologies instead of leaving those details to the LLM are developing their intuition and understanding faster and in a more robust manner.
by ofjcihen - There’s still an immense value in training the brain to learn and be able to approach new problems with the sort of procedural thinking that LLMs enable. We can explore topics that we are curious about and develop that sort of “muscle” to continue asking questions when we have them. I have no fear that when those bigger (and existential) problems arise we’ll be well equipped to keep asking questions and figuring out ways to solve them.by shannadige
- There's a big gap between being able to ask questions about something and understanding something.
The more things you understand, the higher the chance you'll spot a situation to use them in the future.
I think the best innovations come from times when someone is uniquely able to combine two of their previous experiences together. The more experiences you have in your back pocket the more combinations you have access to and the more likely you'll have a unique combination when the right problem comes along.
by simonw - I sometimes get vague ideas for solving maths/science problems. They never pan out but i can talk in detail on group theory and advanced maths and science topics due to investigating such vague ideas over the years. These days the LLM shoots the ideas down instantly and honestly correctly, i know enough to know "yeah that's right, oh well" and move on. Which actually takes away a huge avenue of learning. I'm pretty torn on the outcome of this honestly.
I'm not 'wasting time' but I'm also not really learning.
- > I still learn new stuff, but I’m afraid it won’t have any value in a year or so.
I have stuff to do now, the value of the knowledge in a year or two isn't important if it solves the issues I have today.
by SkyeCA - I can only speak for myself, so I hope this resonates with you.
I wasn’t even really concerned with optimizing low level code before LLMs and that wasn’t why I was hired either.
However following that low level thread: We can look at the reasonable options and immediately know if they’re reasonable or nonsense. Why? We know the code. Now zoom a level out, where I think our expertise really lies.
Building a complex system isn’t easy. There are customers with requirements, there are budgets, SLAs etc. Sometimes one customer needs X and one needs Y. Our expertise is taking all of this in, and producing something that balances all the different variables. It’s knowing that we’ll expect X events a second so we’ll need Y to ensure we can tolerate failure.
Is it possible LLMs will be able to do all of that too? Maybe. But then why would our customers need the enterprises they pay for?
by cautiouscat - Generally speaking, the pattern is that people are overestimating how much "work replacement" will happen, and underestimating how much "work shifting" will happen.
What is fascinating is how you can witness it at so many levels of organization. One example: Employer executive get enamored with moving from labor to capital. They believe that by using LLMs, they can replace a lot of workers. At my place of employment, we have people that are surprised they can't file a Jira ticket describing a product ask, and have it kick off an implementation. You can build the skill to attempt that, but invariably you'll get back questions like "what do you mean by <x>" and "what do you want to do in this case, a, b, or c?"; questions that a product person or an exec are not well suited to answer.
In the past, programmers did that kind of interpretation and judgment call. So then you're in a quandary; who should do that work? Work that previously, you never imagined was an inherent part of what the replaceable code monkeys do at your beck and call?
And then, how do you hire for that? How do you find the training for the people that are experienced enough with... something... to know what a cohesive error response is, or what kind of telemetry strategy is best for that particular product and organization, what collection of product asks are incredibly complicated for what they're asking and can deliver 95% of the benefits at 5% of the work if we just do this instead, and whether you want to aim more towards thick or thin clients?
Who are those people? Wait, those are programmers? Wait, there's this whole collection of inherently human skills that we devalued, by not appreciating they were always quietly doing that for us in the past?
That's just one example. There's a repeating pattern of discovering where the work truly is, work that was embedded in manual patterns we might not have to involve ourselves with anymore, but is yet still essential. So the nature of our jobs changes massively, but the overall level of employment does not.
At least, not in the medium to long term. There is a lot of painful churn we have to suffer through first.
by tunesmith - They're amazing at it, provided you keep asking the right questions.
Trust me when I say that in the hands of someone who doesn't have your experience, the LLMs would not be getting the results you get.
You might think what you're doing is trivial, it may be sessions that flow roughly, "Instrument this, okay this part is slow, profile this part, OK read the profile output and suggest a better approach".
But your experience will be steering it in the right direction, and you're probably unaware of just how much your experience is doing that guiding, as the LLM shoots off at 100mph, you feel like it's taking you with it, but you will be guiding it a lot more than you realise, and that's where learning and experience comes in, even if you're no longer operating at the lowest depth, your knowledge of that layer will be helping.
If nothing else, the experience to know when something is actually slow is a skill in itself. If a function takes 200ms, sometimes that's as quick as it can realistically go, and sometimes that's literally a million times slower than it could be, and there's actual skill and experience wrapped up in knowing what "slow" looks like.
by eterm - I've had success using the socratic method. I give Claude some topic (say, how the intricacies of the bond market works, the content from which are screenshots of pages from a textbook), and then I go on a walk chatting with it in voice mode. Claude is the expert, I am the student. Claude asks me questions, leading me to an answer logically. I come back with questions, and we back and forth. LLMs arent like they were in '23-'25. I'm almost always skeptical its going to lie, and almost always wrong.
In particular:
- I limit it/encourage it to give me single sentence questions
- I sometimes will ask it to tell me a motivating, human-grounded story, when we're starting a new concept: claude responds "Maya is a bond portfolio manager, and her boss has asked her to quickly price in what happened if yields go down. She knows her bond's average duration, a measure in time, but she doesn't have a percentage, which is what her manager wants. How can she give him a percentage number with just a duration figure and the proposed new yield?"
- I'll often ask claude to let me work through it, to derive the thing myself, often resulting in a string of thoughts with "yes/no" trailers, to get the LLM to reply yes or no only, and avoid derailing my train of thought. If yes, my train of thought keeps going. If no, I've got something wrong.
- I'll sometimes stop and have it craft an artifact. I typically say "build me a Brilliant.org-style interactive demo of the topic", especially when we get into the realm of looking at the actual maths of a thing (for which prose and dialog is not optimal by itself AFAICT)
- I'll do this while I'm traveling, while I'm walking, while I'm doing chores.
It's so much fun.
by gnarlouse - can you share ane example of one of your prompts? I have tried to convert some text into the socratic method and haven't succeeded yet.by pumanoir
- > What you get is a beautiful animation that is 100% accurate and free of hallucinations.
I'm not sure I follow how this is actually guaranteed? The fact-checking process mentioned just seems to involve asking AI to review its own work.
by wxw