Hazumi News

Hi HN! Erik here from Pig.dev, and today I'd like to share a new project we've just open sourced:

Muscle Mem is an SDK that records your agent's tool-calling patterns as it solves tasks, and will deterministically replay those learned trajectories whenever the task is encountered again, falling back to agent mode if edge cases are detected. Like a JIT compiler, for behaviors.

At Pig, we built computer-use agents for automating legacy Windows applications (healthcare, lending, manufacturing, etc).

A recurring theme we ran into was that businesses already had RPA (pure-software scripts), and it worked for them in most cases. The pull to agents as an RPA alternative was not to have an infinitely flexible "AI Employees" as tech Twitter/X may want you to think, but simply because their RPA breaks under occasional edge-cases and agents can gracefully handle those cases.

Using a pure-agent approach proved to be highly wasteful. Window's accessibility APIs are poor, so you're generally stuck using pure-vision agents, which can run around $40/hr in token costs and take 5x longer than a human to perform a workflow. At this point, you're better off hiring a human.

The goal of Muscle-Mem is to get LLMs out of the hot path of repetitive automations, intelligently swapping between script-based execution for repeat cases, and agent-based automations for discovery and self-healing.

While inspired by computer-use environments, Muscle Mem is designed to generalize to any automation performing discrete tasks in dynamic environments. It took a great deal of thought to figure out an API that generalizes, which I cover more deeply in this blog: https://erikdunteman.com/blog/muscle-mem/

Check out the repo, consider giving it a star, or dive deeper into the above blog. I look forward to your feedback!

Hey HN, we're excited to share Lumier (https://github.com/trycua/cua/tree/main/libs/lumier), an open-source tool for running macOS and Linux virtual machines in Docker containers on Apple Silicon Macs.

When building virtualized environments for AI agents, we needed a reproducible way to package and distribute macOS VMs. Inspired by projects like dockur/windows (https://github.com/dockur/windows) that pioneered running Windows in Docker, we wanted to create something similar but optimized for Apple Silicon. The existing solutions either didn't support M-series chips or relied on KVM/Intel emulation, which was slow and cumbersome. We realized we could leverage Apple's Virtualization Framework to create a much better experience.

Lumier takes a different approach: it uses Docker as a delivery mechanism (not for isolation) and connects to a lightweight virtualization service (lume) running on your Mac. This creates true hardware-accelerated VMs using Apple's native virtualization capabilities.

With Lumier, you can: - Launch a ready-to-use macOS VM in minutes with zero manual setup - Access your VM through any web browser via VNC - Share files between your host and VM effortlessly - Use persistent storage or ephemeral mode for quick tests - Automate VM startup with custom scripts

All of this works natively on Apple Silicon (M1/M2/M3/M4) - no emulation required.

To get started:

1. Install Docker for Apple Silicon: https://desktop.docker.com/mac/main/arm64/Docker.dmg

2. Install lume background service with our one-liner:

  /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh)"

3. Start a VM (ephemeral mode):

  docker run -it --rm \
  --name lumier-vm \
    -p 8006:8006 \
    -e VM_NAME=lumier-vm \
    -e VERSION=ghcr.io/trycua/macos-sequoia-cua:latest \
    -e CPU_CORES=4 \
    -e RAM_SIZE=8192 \
    trycua/lumier:latest

4. Open http://localhost:8006/vnc.html in your browser. The container will generate a unique password for each VM instance - you'll see it in the container logs.

For persistent storage (so your changes survive container restarts):

mkdir -p storage docker run -it --rm \ --name lumier-vm \ -p 8006:8006 \ -v $(pwd)/storage:/storage \ -e VM_NAME=lumier-vm \ -e HOST_STORAGE_PATH=$(pwd)/storage \ trycua/lumier:latest

Want to share files with your VM? Just add another volume:

mkdir -p shared docker run ... -v $(pwd)/shared:/shared -e HOST_SHARED_PATH=$(pwd)/shared ...

You can even automate VM startup by placing an on-logon.sh script in shared/lifecycle/.

We're seeing people use Lumier for: - Development and testing environments that need macOS - CI/CD pipelines for Apple platform apps - Disposable macOS instances for security research - Automated UI testing across macOS versions - Running AI agents in isolated environments

Lumier is 100% open-source under the MIT license. We're actively developing it as part of our work on C/ua (https://github.com/trycua/cua), and we'd love your feedback, bug reports, or feature ideas.

We'll be here to answer any technical questions and look forward to your comments!