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- 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.
by mobiuscog - 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.
by ramon156 - 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!
by devenjarvis - 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.
by mmarian - 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.by te_chris
- 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... ) .
by schmorptron - 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.
by zuzululu - 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.by tatjam
- 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.by devenjarvis
- 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 !by rdksu
- Do you have that version published anywhere?by smallerize
- 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...
by andai - 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.by dchuk
- Can you give some examples of the deterministic tasks? So in your example, was the deterministic task “fetch this team’s backlog”? And then the LLM parts are “process each backlog” and “combine a summary”?by edot
- 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.by devenjarvis
- This approach works well, I agree. But I keep wishing that I could invert it. The architecture I feel like I keep yearning for, is a traditional CLI program that encodes most workflow knowledge/decisions as real code; but which does "just a little bit of coding agent invocation" during one specific workflow step.
Not sure how to accomplish this. Anyone have any suggestions? Are there libraries for this yet? (And how would they even work? It feels like, to do this right, there would have to be some background service that CLI software could expect to interact with via a well-known local IPC socket — similar to how e.g. the docker daemon works. But I'm unaware of any coding agent software/frameworks that expose such an IPC capability...)
by derefr - 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.
by nomel - The issue is that there are now different expectations surrounding velocity and apparent productivity. Previously an individual new to web development might have genuinely needed to develop an understanding of web protocols, HTML and other stuff in that domain in addition to actually wanting to wrap their head around it. Nowadays spending the time required to understand how a website works carries a heavy opportunity cost, at least in the short term.by dtj1123
- Some people will probably be curious regardless of their environment but I think there are others who could be swayed into developing curiosity (or not) by life experiences. And an ever-present "just gimme the answer now" button could be a powerful force pulling them toward the "incurious" side.
- I guess I'm both people, depends on what it is and what other things I'm doing. Sometimes it's fun and interesting to delve deeply (oh no he didn't) into something for long periods of time, just for the sake of exploring and understanding. Sometimes I'm not curious about why something specifically doesn't work, I just need it to work so I'll hack around it any way possible so I can move on with what I really wanted to do.
I find that LLMs are useful for both cases in the end.
- 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”.
by d4rkp4ttern - if your power is LLM, what are you without it ???by tonyhart7
- This is really good! Thank you for this skill, it seems like this method of learning is working really well for me, it is much more engaging, and I have just learned new things about my team's project by using it.
I'll definitely check out your other skills.
by hootz - How do you deal with context length degradation here?
The harder questions will only arrive when the context is getting full.
- I think this might be useful if you are supplementing your learning from actual sources. Like you casually said you understood counter-intuitive things about diabetes/insulin, dopamin and motivation etc but these are very complex topics and require a lot of study to fully "understand". Its okay if you just see it as curiosity-driven learning but I dont see this as a way to learn anything that is actually important or serious.
Traditional method of looking up stuff, going through guided lessons etc are just more streamlined and faster than this method.
by altmanaltman