It’s international, but there are a lot of Europeans: archlinux.org/people/developers/

CachyOS has its roots in the Polish Arch community if I recall correctly. It’s much less daunting, and I’d highly recommend it.

Check out Garuda. It’s a really stable, well maintained version of Arch. I’ve been running the same install of it for over 9 months with only one screw up that garuda’s own health tool fixed for me.

It’s been a great way for me to learn Linux and Arch, and it rivals Bazzite in my own gaming benchmarks.

I man, I guess I could see it as a sort of training wheels to get going, if one comes in to this cold… There are certain commands that just have very complicated arguments, and particularly if only very occasionally needed, an LLM I could see as helping folks get whatever specific bit they want out of a very verbose usage output or man page.

But it so famously messes up that they have to go lookup any suggestions to understand what it will do better than it would.

If one has no interest in actually learning the command line as a long teem goal though… Just don’t bother. Their usage scenario is almost certainly within the scope of the gui experience. They might be slower on some tasks and unable to scale out their skills to mass operations or create convenient automation, but not everyone has that need.

After evaluation of local models, Claude, gemini 3, chatgpt… It’s certainly interesting but it really messes up a lot and if it has access even in their to anything “real”, it’s supremely dangerous to use if you are not qualified to review the results.

Yeah, that is a great application because you can eyeball your bash script and verify its functionality. It’s perfectly checkable. This is a very important distinction.

It also doesn’t require “creativity” or speculation, so (I assume) you can use a very low temperature.

Contrast that with Red Hat’s examples.

They’re feeding it a massive dump of context (basically all the system logs), and asking the LLM to reach into its own knowledge pool for an interpretation.

Its assessment is long, and not easily verifiable; see how the blog writer even confessed “I’ll check if it works later.” It requires more “world knowledge.” And long context is hard for low active parameters LLMs.

Hence, you really want a model with more active parameters for that… Or, honestly, just reaching out to a free LLM API.

Thing is, that Red Hat’s blogger could probably run GLM Air on his laptop and get a correct answer spit out, but it would be extremely finicky and time consuming.

Yeah, I suppose so. I find plenty to hate about the way companies and too many individual apps talk about LLMs. I really hate that it’s one of the metrics my employer looks at. I always hate how wasteful speculative bubbles like this are.

But maybe this isn’t the place for me since I see some good use cases and appreciate the few times someone does it right.

• I hate how companies like Google and Microsoft are putting LLMs everywhere, making things worse for everyone, forcing everyone to deal with it
• I find it strange that there’s an LLM in my car but it Carrie’s a decent conversation and it can’t actually do anything
• I like this approach of building the mcp server. Keeping it read only, keeping it optional, and leaving the actual LLM open. I also like Apples approach where they seem to care about privacy, about executing on device, and about taking their time to put it in useful places