Hey HN!Lathe is an experiment in using LLMs to teach me something new, instead of doing the work for me. It generates a hands-on, source-backed tutorial for any technical topic you want to learn. Then you work through it yourself by reading and typing the code by hand (gasp) in a local UI built for exactly that.
It's a Go CLI plus LLM agent skills (Claude Code / Cursor / Codex). You prompt something like "/lathe build a 3D slicer in Erlang", run `lathe serve` to spin up a local webapp, and read it in your browser. Every tutorial comes with the things that have made self-learning a pleasant experience for me in the past:
- table of contents that follows along as you scroll
- side-notes that nudge you to think
- exercises for the reader
- sources backing up the content that you can use to take you deeper
To help make up for the lack of human brainpower behind the tutorial, you can also ask questions about the content, have another LLM verify the tutorial actually compiles and runs, or extend it with another part (no more "Part 4 of 6" that hasn't seen an update since 2021).
I didn't build lathe to replace human-written tutorials. I built lathe because I _love_ human-written tutorials, but wanted to learn technical domains where no good human-written tutorial exists yet (building a 3D slicer from scratch, making embedded Zig approachable, etc). There's a longer story in the README about how I got started with programming through PSP homebrew tutorials, and why losing that to LLMs bugged me enough to build this.
I'm not here to sell you anything (there's nothing close to a VC-backed startup here :D). It's an LLM, and its output is usually good but not perfect by any means. So far, my experience is that because you're the one typing and actually engaged, you catch the weird stuff (and I'm finding that pushing back on it is its own kind of learning). And yes, it's vibecoded, because it's low scope, low risk, and scratching a personal itch. I run it on Claude Code + macOS personally, other setups should work but I haven't been able to verify them yet.
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, and I hope it serves as an example where LLMs can help us think better, rather than less.
Repo: https://github.com/devenjarvis/lathe
Would love your feedback if you decide to check it out!
▲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.
reply▲devenjarvis47 minutes ago
[-] I agree! I want to say I first saw this pattern in some work Simon Willison did (Rodney and Showboat). For certain workflows the pair of Skills + CLI give me a nice balance between the flexibility of LLMs and the consistency of a CLI.
reply▲threecheese27 minutes ago
[-] 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.
reply▲schmorptron2 hours ago
[-] 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... ) .
reply▲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.
reply▲devenjarvis2 hours ago
[-] Yea that’s definitely been a primary usecase for me! Easing the barrier to entry into a new project, and giving me the foundation to take it further on my own once I’m comfortable.
reply▲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.
reply▲I've been using it quite a bit and I like it a lot! You certainly could roll your own prompt for this. The value I'm seeing is in the reusable skill/prompt to structure tutorials in a way that help me think and learn a new concept (rather than Claude just giving me code to copy/paste), and the local UI that makes working through the tutorial much more pleasant than scrolling through Claude's markdown output. Plus tutorial series are persistent so I can easily come back around later with a `/lathe-extend` to explore an extension to a topic/tutorial I'm interested in.
That said, it's been a tool that's been helpful for me personally, but doesn't have to be for everyone! I've never used ChatGPT Study, I'll look into it more. Thanks for sharing!
reply▲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
reply▲Nice! I do this now locally with LLMS and ollama and my own havky prompts. I could not find if this also supports ollama?
reply▲devenjarvis53 minutes ago
[-] Thanks for checking it out! ollama wasn't top of my list for support, just because I don't have a machine powerful enough to run decent local LLMs (I wish I did!). I'll look into it though, nothing here should be locked in to any one LLM, as long as it has the concept of a skill/slash command/reusable prompt.
Someone else asked about Gemini, so I think broader LLM support will be my focus for v0.4.0
reply▲We have notebooklm at home? Is there any comparison between these two, looks nice
reply▲devenjarvis51 minutes ago
[-] Thanks for sharing NotebookLM, I hadn't seen that! I'll take a look and add a comparison to the README if it's compelling.
reply▲james_marks2 hours ago
[-] Love this idea, can’t wait to try it. Thank you for sharing!
reply▲great, i'll try this. something like this has on my list and i'm super curious :)
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