Same here. I like tinkering with my Home Assistant setup and small web server running miscellaneous projects on my Raspberry Pi, but I hate having to debug it from my phone when it all falls over while I'm not near my computer.

Being able to chat with somebody that has a working understanding of a Unix environment and can execute tasks like "figure out why Caddy is crash looping and propose solutions" for a few dollars per month is a dream come true.

I'm not actually using OpenClaw for that just yet, though; something about exposing my full Unix environment to OpenAI or Anthropic just seems wrong, both in terms of privacy and dependency. The former could probably be solved with some redacting and permission-enforcing filter between the agent and the OS, but the latter needs powerful local models. (I'll only allow my Unix devops skills to start getting rusty once I can run an Opus 4.5 equivalent agent on sub-$5000 hardware :)

What if you don't want to tinker? You just want something that works. Is it still transformative?

Yes, they already said that.

> because it’s a threat to their business model.

Quantized, heavily, and offloading everything possible to sysram. You can run it this way, just barely reachable with consumer hardware with 16 to 24gb vram and 256gb sysram. Before the spike in prices you could just about build such a system for $2500, but the ram along probably adds another $2k onto that now. Nvidia dgx boxes and similar setups with 256gb unified ram can probably manage it more slowly ~1-2 tokens per second. Unsloth has the quantized models. I’ve test Kimi though don’t have quite the headroom at home for it, and I don’t yet see a significant enough difference between it and the Qwen 3 models that can run in more modest setups: I get a highly usable 50 tokens per second out of the A3B instruct that fits into 16gb VRAM with enough left over not to choke Netflix and other browser tasks, it performs on par with what I ask out of Haiku in Claude Code, and better as my own tweaking improves with the also ever better tooling that comes out near weekly.

I have an AMD Epyc machine with 512GB of RAM and a humble NVIDIA 3090. You will have to run a quantized version but you can get a couple tokens per second out of it since these models are optimized to split across the GPU/RAM and it's about as good as Claude was 12 months ago.

Full disclosure, I use OpenRouter and pay for models most of the time since it's more practical than 5-10 tokens per second, but the option to run it "If I had to, worst case" is good enough for me. We're also in a rapidly developing technology space and the models are getting smaller and better by the day, ever year the smaller models get better

Good News! The Models are done, and you can download them for free. Even if they stopped being worked on this moment, those are finished and usable right now, and won't get any worse over time.

P2P training is a possibility. With so much compute running the block chain I can see this utilized for AI.

Big tech is bought and paid for by consumers. We can do the same for oss trained models.

What privacy? If you're using ChatGPT or Claude, your chats are still logged.

It's the other way around. At least for most people, it grants access to your personal data to an LLM (and by extension its inference provider) in the cloud.