I am also pursuing something similar (complementary?) to this (recently started writing a Rust-based "distributed OS" that manages ML resources in a network of heterogenous systems: varied cores, system RAM, GPU VRAM, I/O). So my focus is not so much distributed agents, but more distributed inference (and fine tuning) that would benefit agents, distributed or not. I may blog about my work soon.
Thanks, softwarewright; would love to hear more about your work. I've been implementing small-model inference in Zug inside WunderOS, but it's not done yet, so nothing public just yet.
I'm in a research/prototyping phase with no truly verified results yet, but I have all the hardware I need to do actual testing. I have an OS that boots in a VM, it just isn't verified to have practical value yet. It could be an AI coding agent's fever dream until I use it anger. So far Apple Silicon only, but most of my systems run Linux and most of my GPUs are NVIDIA, so moving development from Mac to Linux soon. It does have tests, demos, docs. Iterating on it daily.
Good stuff here, much of which resonates with me. FWIW, my notion of an OS for agents isn't as close to the metal yet, ie, my view of agent lifecycle is that they look a lot like WhatsApp or Discord traffic. So, based on that DEEP analysis, I decided to build on BEAM/OTP for the control plane: basically, Elixir for the UX and Gleam for everything else. And the data plane is pure Zig: data sidecar into BEAM/OTP via NIF.
So that gives me a certain freedom for deploy: bare metal, containers, VMs, even K8S. And since there are some tools for pickling all that into a single binary, and running BEAM/OTP on u-kernel sorts of things, I can get all the way to the metal in the way that you are. Whether or when that happens remains to be seen, etc.
I think this article points out a bunch of ways in which a persistent agent orchestrator does directly analogous things to an OS.
I'm building a kind of orchestrator and I haven't thought of the OS analogy in a serious way other than the interface, but indeed I do already have scheduling, isolation, observability and identity, and I'm currently building a filesystem (versioned project-wide agentic artifacts).
Maybe I really do ought to call my project an "agentic desktop OS" and it isn't a misnomer after all.
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[ 0.27 ms ] story [ 17.2 ms ] threadYour posted link is helpful, thanks.
https://github.com/sw-ml-study/sw-os-ml
I also have been implementing small model inference:
https://github.com/sw-ml-study/moe-microscope
So that gives me a certain freedom for deploy: bare metal, containers, VMs, even K8S. And since there are some tools for pickling all that into a single binary, and running BEAM/OTP on u-kernel sorts of things, I can get all the way to the metal in the way that you are. Whether or when that happens remains to be seen, etc.
Thanks for sharing! See https://pentad.ai/PLRN for more about what I'm up to.
I'm building a kind of orchestrator and I haven't thought of the OS analogy in a serious way other than the interface, but indeed I do already have scheduling, isolation, observability and identity, and I'm currently building a filesystem (versioned project-wide agentic artifacts).
Maybe I really do ought to call my project an "agentic desktop OS" and it isn't a misnomer after all.