Show HN: Lathe – Use LLMs to learn a new domain, not skip past it

A related idea is to have the LLM quiz you, Socratic-style about a topic of interest. It persists in asking questions at deeper levels until you arrive at the answer yourself. This forces you to think hard about a problem, and this effort helps with understanding, learning and retention. Of course I made a Socratic-quiz skill for this, to use with any coding agent or similar:

https://pchalasani.github.io/claude-code-tools/plugins-detai...

For example I’ve used this to better understand counter-intuitive things about diabetes/insulin, dopamine and motivation, Claude’s implementations, etc (to combat so-called cognitive debt).

Strong LLMs are surprisingly good at this type of quizzing, they display a semblance of “theory of mind”.

I think there's going to be the exact and precise range of people there has always been: some people are curious, and want/need to understand what they're doing, some people are not and just want to do. That want/need is a fundamental personality trait what makes an expert.

LLM are a dream come true for these curious types. They'll only be accelerated by them. I don't think there's any real "loss" out there, just a bunch of people that don't care boing things easier. Good for them, good for the curious people. Net win.

I’ve been using this general pattern - a custom cli app for deterministic tasks, skills for the agent harness, run the skills in the agent and it produces artifacts for you by using the cli and its own agentic reasoning - a lot lately for work. Things like “give me an executive brief of the activity in these teams backlogs over the last month” and in 5-10 minutes I have a few page doc I can read that is cited with the tickets it analyzed and I don’t have to go bug people or ask them to do yet another task for me, just make sure your backlog is updated and detailed like normal practice. It’s awesome and really fits a useful spot between pure agent usage (which is hard to get consistent results from on repeat tasks) and not having to build/buy a full blown app for every random thing.

Hey this is neat!

I was telling my friend the other day. The way you learn programming is by typing code out by hand. And I suggested using LLMs to generate minimal educational examples aligned with his interests and needs.

I've tried the Zed Shaw method to learning programming (just typing out code examples by hand -- doing "studies", the same way you would with music or art). I tested it on a programming language I had been learning for a while and was struggling with. After just a few hours of typing my fluency had skyrocketed.

I realized that in several hours of typing I had written more code than in weeks of study. Because when you don't know a language yet, producing code is extremely slow and error prone. But typing out correct code is relatively straightforward.

So due to changing my approach to "just blindly typing", I got more practice (at least as far as reading and muscle memory goes) in a few hours than the previous few weeks.

Now of course understanding is important too, but it's a separate dimension, and largely comes after memory and fluency in my experience. (Understanding something theoretically and being able to use it are two very different things!)

The general principle here is Stephen Krashen's Input Hypothesis of language acquisition (https://en.wikipedia.org/wiki/Input_hypothesis) which says a baby learns language by just hearing stuff -- just being exposed to inputs -- and that adults can learn the same way too.

And I heard it on the excellent website (now defunct?) All Japanese All The Time, where the author tested the hypothesis on himself by mostly listening to a lot of Japanese and gained fluency in a year.

https://web.archive.org/web/20080705194055/http://www.alljap...

I have updated the popular /grill-me skill for this exact purpose! I had a very insightful grilling session yesterday on what exactly happens when you try to load an extremely large dataset in pandas, covering everything down to the last detail !

This is a very cool idea, feels like a sane way to use LLMs in this crazy time! Could be a very good way to break the ice when starting a new project and everything is friction.

Cool project! I'll be trying it out. I've been a big fan of throwing whatever sources I have on a new topic i'm trying to get into into a llm "project" and then asking it to teach me, grounded on the actual content to speed things up.

But at the same time, I'm afraid getting everything laid out for you in exactly the way you want will erode some of the understanding you build by going through a primary source directly and figuring things out the hard way. So this having more focus on actually doing stuff by yourself seems right up my alley (while still tending to the LLM induced intellecutal laziness... ) .

I think you're tackling an interesting area. I was thinking of something similar for system design prep. I experimented with a couple of series of blog posts - one for designing Twitter, another for WhatsApp: https://prepcommons.com/.

Still, it took a lot more effort than just delivering the initial request. AI makes everyone produce something average but you still need taste to produce something good - I guess this applies to courses too.

I like the focus on learning rather than replacing learning. One risk with AI tools is that people can become very productive without actually understanding the underlying domain. Tools that help users learn while using AI feel much more sustainable long term.

This looks really nice ill check this out

I have been using a similar skill (built over a few iterations) that builds whatever I ask, through a series of milestones, and then creates a full tutorial to follow in markdown and uses zola to turn it into a full static site.

90% of my Claude usage is getting it to write me guides, that I can then spend most of my time following to build the end results.

Keeps the brain healthy and also provides bespoke learning, rather than a generic course off the internet. Definitely a great use of AI.

What I'm more looking at is your own experience with a vibed tool. I cannot really tell from this introduction whether you actually use and like it (you mentioned you use it and sometimes push back, which is a learning strategy of its own?)

Also, I wouldn't say "have another model test the tutorial compiles" a feature, but also I do not expect a fool-proof tutorial from a one-shot, I guess.

Not sure why I would try this over a hand-written promot. Also wondering why ChatGPT Study mode failed, it seemed interesting.

It's very cool, and I can really see myself use that, but not in that form of deliverable.

See the best place I learn and read through materials is when I'm commuting. Far away from a console.

Could you envision a way to deliver this as a web app linked to e.g. an OpenRouter/Anthropic/OpenAI API key?

I just use https://blog.google/products-and-platforms/products/educatio... and similar features of other AIs.

Oh my, this sounds like an idea I have been toying with. I really want a tutor to explain how random repos I find work.

Do you think Lathe could be adapted to use a codebase as the source material?

For a somewhat hybrid approach here, have a look at https://github.com/DrCatHicks/learning-opportunities — the idea is to be used during “productive work” (so it’s not purely learning-oriented as with your repo here), and to interject as you work to ensure that you learn related concepts as you go.

I've had claude write my rust tools for a year without learning any rust. gonna try this to finally learn it for real.

Did you write the skill.md files yourself? I often wonder this; there’s so much text in most skills, and I can’t imagine it’s human generated.

I don’t write my own - I can’t optimize for the models understanding, and so I just give the skill-creator skill an outline and then have it refine until the output is what I want.

I just use md files to plan questions, track my answers, and implement rehearsals for concepts that need more repetition from claude code. And I start from a good book or documentation as source material, first the agent reads the learning material and structures it for learning.

> If you can find resources to learn something that was written by a human, read that first. But Lathe is here to fill in the gaps when that isn't the case

Well, but it will still serve you content from humans, but without any attribution.

I like the idea and I know you explicitly address this but wonder if still it could search for human made works for you to learn from first

If it does find some, maybe it could supplement them instead of just from scratch

Do you have any evaluations/ comparisons between small open source LLM and frontier LLM in the Lathe?

Love this idea, can’t wait to try it. Thank you for sharing!

Can I use this to learn about a complex private repo or how it does things?

There is of course a degree of true usefulness to this. However I’ve been a technical educator for years and I’ve tried to do lots with LLMs.

Even now, LLMs are terrible educators. They do not make coherent progressive curriculums. They hallucinate details which the student will not have the knowledge to challenge.

If you use an LLM to make a tutorial you will get some benefit for sure, especially if you use it for Socratic sessions based on a corpus of data you provide (like a blog post or documentation).

Don’t expect it to teach you reliably though. It feels good to ask the LLM whatever you want, but if you’re learning a topic you don’t have the instinct to realize when it’s giving you a poorly chosen progression of information or teaching you something flat out untrue.

Nice! I do this now locally with LLMS and ollama and my own havky prompts. I could not find if this also supports ollama?

I think this is quite a refreshing idea

LLM's big point is that it is an excellent learning tool

Lot of people want to generate stuff from it

but perhaps overlooked is the knowledge you can gain from it

it is the best tutor you will ever have!

btw it sucks that you have to disclose if you are trying to make a buck from a project or not.

Making money shouldn't be vilified or frowned upon.

Maybe add voice to it so that it reads the tutorial out loud and listen to it lessons on the move?

great, i'll try this. something like this has on my list and i'm super curious :)

We have notebooklm at home? Is there any comparison between these two, looks nice

Nice. I've got Claude code teaching me maths at the moment. Some skills, file system learning log, oss text books and a full curriculum based on Math Academy (which I was doing before but got bored of) and UK high school and university. Teaching me concept-first though. So we start with something complex and go up and down until I get it all. It's not necessarily thorough for everything, but the depth of my intuition is much better and each time I use it I find myself unlocking another sector of the map. I love LLMs for this.

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I like this framing a lot: using LLMs to stay in contact with the material, not to skip past it.

In coding-agent work I see a similar pattern. The best outcomes usually happen when the agent is forced to study concrete source material first: real repos, real docs, real examples, and the constraints behind them. The worse outcomes happen when it generates a plausible path from a vague prompt and never has to reconcile that with existing practice.

For learning, I imagine the same thing matters: the LLM should help structure the path and explain the friction, but the learner still needs to touch the code and compare against sources.

The source-backed part feels more important than the generated tutorial part.