[deleted]
Claude Skills
101–110 of 443 posts
Re: Claude Skills
#102I feel like a danger with this sort of thing is that the capability of the system to use the right skill is limited by the little blurb you give about what the skill is for. Contrast with the way a human learns skills - as we gain experience with a skill, we get better at understanding when it's the right tool for the job. But Claude is always starting from ground zero and skimming your descriptions.
> Contrast with the way a human learns skills - as we gain experience with a skill, we get better at understanding when it's the right tool for the job. Which is precisely why Richard Sutton doesn't think LLMs will evolve to AGI[0]. LLMs are based on mimicry, not experience, so it's more likely (according to Sutton) that AGI will be based on some form of RL (reinforcement learning) and not neural networks (LLMs). Mor…
For humans, it’s not uncommon to have a clever realization by way of serendipity. How do you skill AI to have serendipity.
Re: Claude Skills
#103getting hard to keep up with skills, plugins, marketplaces, connectors, add-ons, yada yada
IMHO, don't, don't keep up. Just like "best practices in prompt engineering", these are just temporary workaround for current limitations, and they're bound to disappear quickly. Unless you really need the extra performance right now, just wait until models get you this performance out of the box instead of investing into learning something that'll be obsolete in months.
I agree with this take. Models and the tooling around them are both in flux. I d rather not spend time learning something in detail for these companies to then pull the plug chasing next-big-thing.
Re: Claude Skills
#104Earlier quoted context omitted.
The industry has been doing RL on many kinds of neural networks, including LLMs, for quite some time. Is this person saying we RL on some kind of non neural network design? Why is that more likely to bring AGI than an LLM?. > More specifically, LLMs don't have goals and consequences of actions, which is the foundation for intelligence. Citation?
Why are you asking them to cite something for that statement? Are you questioning whether it's the foundation for intelligence or whether LLMS understand goals and consequences?
Yes, I'm questioning if that's the foundation of intelligence. Says who?
Re: Claude Skills
#105Does anyone know how skills relate to subagents? Seems that subagents have more capabilities (e.g. can access the internet) but seems that there's a lot of overlap.
I've asked Claude and this it answered this:
Skills = Instructions + resources for the current Claude instance (shared context)
Subagents = Separate AI instances with isolated contexts that can work in parallel (different context windows)
Skills make Claude better at specific tasks. Subagents are like having multiple specialized Claudes working simultaneously on different aspects of a problem.
Re: Claude Skills
#106getting hard to keep up with skills, plugins, marketplaces, connectors, add-ons, yada yada
IMHO, don't, don't keep up. Just like "best practices in prompt engineering", these are just temporary workaround for current limitations, and they're bound to disappear quickly. Unless you really need the extra performance right now, just wait until models get you this performance out of the box instead of investing into learning something that'll be obsolete in months.
I agree with your conclusion not to sweat all these features too much, but only because they're not hard at all to understand on demand once you realize that they all boil down to a small handful of ways to manipulate model context.
But context engineering very much not going anywhere as a discipline. Bigger and better models will by no means make it obsolete. In fact, raw model capability is pretty clearly leveling off into the top of an S-curve, and most real-world performance gains over the last year have been precisely because of innovations on how to better leverage context.
Re: Claude Skills
#107getting hard to keep up with skills, plugins, marketplaces, connectors, add-ons, yada yada
All of it is ultimately managing the context for a model. Just different methods
Re: Claude Skills
#108I feel like a danger with this sort of thing is that the capability of the system to use the right skill is limited by the little blurb you give about what the skill is for. Contrast with the way a human learns skills - as we gain experience with a skill, we get better at understanding when it's the right tool for the job. But Claude is always starting from ground zero and skimming your descriptions.
This is the crux of knowledge/tool enrichment in LLMs. The idea that we can have knowledge bases and LLMs will know WHEN to use them is a bit of a pipe dream right now.
Re: Claude Skills
#109Earlier quoted context omitted.
> Contrast with the way a human learns skills - as we gain experience with a skill, we get better at understanding when it's the right tool for the job. Which is precisely why Richard Sutton doesn't think LLMs will evolve to AGI[0]. LLMs are based on mimicry, not experience, so it's more likely (according to Sutton) that AGI will be based on some form of RL (reinforcement learning) and not neural networks (LLMs). Mor…
The industry has been doing RL on many kinds of neural networks, including LLMs, for quite some time. Is this person saying we RL on some kind of non neural network design? Why is that more likely to bring AGI than an LLM?. > More specifically, LLMs don't have goals and consequences of actions, which is the foundation for intelligence. Citation?
Looks like they added the link. But I think it’s doing RL in realtime vs pre-trained as an LLM is.
And I associate that part to AGI being able to do cutting edge research and explore new ideas like humans can. Where, when that seems to “happen” with LLMs it’s been more debatable. (e.g. there was an existing paper that the LLM was able to tap into)
I guess another example would be to get an AGI doing RL in realtime to get really good at a video game with completely different mechanics in the same way a human could. Today, that wouldn’t really happen unless it was able to pre-train on something similar.
Re: Claude Skills
#110Does anyone know how skills relate to subagents? Seems that subagents have more capabilities (e.g. can access the internet) but seems that there's a lot of overlap. I've asked Claude and this it answered this: Skills = Instructions + resources for the current Claude instance (shared context) Subagents = Separate AI instances with isolated contexts that can work in parallel (different context windows) Skills make Clau…
How this reads to me is that a skill is "just" a bundle of prompts, scripts, and files that can be read into context as a unit.
Having a sub-agent "execute" a skill makes a lot of sense from a context management, perspective, but I think the way to think about it is that a sub-agent is an "execution-level" construct, whereas a skill is a "data-level" construct.