Depending on a corporation to do your programming (and burning half the planet in the process, pardon the hyperbole) is the very opposite end of the "hacker" ethos where Lisp stands. Very surprising to see this sort of comment on HN, of all places.
@brailsafe has accurately captured where I am coming from.
I want more blogs/discussion from the community about the existing tools.
In 3/6 months, how many skills have you written? How many times have you used each skill? Did you have edit skills later due to unseen corner cases, or did they generalize? Are skills being used predominantly at the individual level, or are entire teams/orgs able to use a skill as is? What are the usecases where skills are not good at? What are the shortcomings?
(You being the metaphorical HN reader here of course.)
HN has always been a place of greater technical depth than other internet sites and I would like to see more of this sort of thing on the front page along with day one calls.
Please do open-source your skill and blog about it. Also, would like to hear from your experience after a few months of use. Like - how many times did you use the skill, did you run into some problems later (due to some unexpected thing in the markdown), did the skill generalize - or do you have to make tweaks for particular inputs.
I looked at superpowers, but it felt way too generic. Thanks for sharing unwind. More discussion/blogs about these kind of skills is what I am looking for. I would encourage you to write a blog on unwind, explaining in detail how it has helped you. Even better if you do it after 3 months of use, explaining the journey/evolution of the skill.
I thought skills were supposed to be sharable, but (a) ones that are being shared openly are too generic and not useful, (b) people are writing super specific skills and not sharing them.
Would strongly encourage you to open-source/write blog posts on some concrete examples from your experience to bridge this gap.
I looked that the official repo of skills, but I found those very generic and artificial.
I would encourage you to write up a blog post of your experience and share a version of the skill you have built. And then follow up with a blog post after 3 months with analysis like how well the skill generalized for your daily use, whether you had to make some changes, what didn't work etc. This is the sort of content we need more of here.
First thing I did here is a grep for "Skills" and no hits. Simon's posts are well upvoted here and Anthropic/Claude is a bit of HN darling, but I think they are playing the hype game a bit too well here.
3 months ago, Anthropic and Simon claimed that Skills were the next big thing and going to completely change the game. So far, from my exploration, I don't see any good examples out there, nor is a there a big growing/active community of users.
Today, we are talking about Cowork. My prediction is that 3 months from now, there will be yet another new Anthropic positioning, followed up with a detailed blog from Simon, followed by HN discussing possibilities. Rinse and Repeat.
This is something I have experienced first hand participating in the Vim/Emacs/Ricing communities. The newbie spends hours installing and tuning workflows with the mental justification of long-term savings, only to throw it all away in a few weeks when they see a new, shinier thing. I have been there and done that. For many, many years.
The mature user configures and installs 1 or 2 shiny new things, possibly spending several hours even. Then he goes back to work. 6 months later, he reviews his workflow and decides what has worked well, what hasn't and looks for the new shiny things in the market. Because, you need to use your tools in anger, in the ups and downs, to truly evaluate them in various real scenarios. Scenarios that won't show up until serious use.
My point is that Anthropic is incentivized in continuously moving goalposts. Simon is incentivized in writing new blogs every other day. But none of that is healthy for you and me.
Is there an Anthropic document that says this? I mean about the "training" portion. The docs I am seeing talks about Claude Code or Desktop being able to use skills - that's a totally different matter.
Shameless plug: I built [1] and use a small magit like interface on top of org-mode.
I love org for all its bells and whistles and use them in various ways. But most of the time I need a small subset of org in a form-factor that allows ease of use.
I created my own X11 window manager [1] at the start of this year in around 800 lines of C.
I had been using dwm (4000 lines of C) for many years and wished to write my own for a long time, but what made me take the leap was really steveWM [2] and TinyWM [3] which are both super small.
I think all this discussion around Open-source AI is a total distraction from the elephants in the room. Let's list what you need to run/play around with something like Llama:
1. Software: this is all Pytorch/HF, so completely open-source. This is total parity between what corporates have and what the public has.
2. Model weights: Meta and a few other orgs release open models - as opposed to OpenAI's closed models. So, ok, we have something to work with.
3. Data: to actually do anything useful you need tons of data. This is beyond the reach of the ordinary man, setting aside the legality issues.
4. Hardware: GPUs, which are extremely expensive. Not just that, even if you have the top dollars, you have to go stand in a queue and wait for O(months), since mega-corporates have gotten there before you.
For Inference, you need 1,2 and 4. For training (or fine-tuning), you need all of these. With newer and larger models like the latest Llama, 4 is truly beyond the reach of ordinary entities.
This is NOTHING like open-source, where a random guy can edit/recompile/deploy software on a commodity computer. Wrt LLMs, Data/Hardware are in the equation, the playing field is complete stacked. This thread has a bunch of people discussing nuances of 1 and 2, but this bike-shedding only hides the basic point: Control of LLMs are for mega-corps, not for individuals.
Thank you for this comment - you have succinctly captured something that I have been feeling but unable to express in words.
Stories/memes/narratives are the most easy/potent form of mental ingestion - so much so that I think humans cannot ingest facts or ideas at all, only stories. And this puts a collective responsibility on all of us to be very careful about the stories we create.
I strongly recommend everyone read Luhmann's original paper [1] on Zettelkasten.
What I got from it is that, the process is less about storing/retrieving information, but more about building a system that can surprise you - the way ideas emerge when you brainstorm with others. These others being people with the same level of knowledge as you - so, not the kind of information flow that happens between an expert and a beginner, but between peers who have access to the same kind of information, but simply look at things differently.
For some reason, every Zettelkasten system out there focuses on the mechanics, and in my opinion, not enabling the original intent of the approach. Not that I have a solution to the problem.
Shameless plug. For those who use Orgmode, but think that Agenda is a bit too heavyweight to manage Todos, I created a Magit like interface to manage Todos (in an orgmode file): https://github.com/ChanderG/toodoo.el