Tag: Pi

PrismML released Bonsai 2 27B this week. It is built on Qwen3.8 27B, but compressed to ternary weights: each weight is +1, 0, or -1 instead of 16 bits. That drops the size from about 56 GB to 5.9 GB. On PrismML’s benchmark suite, it keeps about 98% of the original model’s score. It runs on a Mac (Metal), on Linux or Windows (CUDA, Vulkan, ROCm), or on CPU alone.

I tested it on my M4 Mac with 24 GB of RAM. I wired it to my Pi coding agent and gave it a code review task. It is pretty cool.

Bonsai 2 followed my codereview.md rules. It checked the change against the other files in the repo, the way I asked it to.

The full task took 30 minutes. Token speed on my M4 was about 10 tokens per second. Other reports show 40+ tokens per second on an M5.

Agent skills let humans organize, distribute, discover, and compose an agent’s capabilities. A skill is typically a markdown file, with optional scripts, references, and evals bundled alongside it.

Think of an agent skill as programming in natural language, written in markdown. It can hold knowledge, workflow logic, guardrails, required tools — basically anything.

Some outstanding skills:

• autoresearch instructs an agent to tirelessly tune models. It defines a workflow — really a loop — and states plainly what the agent can edit and what it can’t.
• img2threejs turns an image into a 3D model. It defines a workflow with heavy guardrails at every stage.
• superpowers defines a software development lifecycle. It has an opinionated, mandatory way to deliver software.

You probably already do some of this by hand. Just write it down, name the file SKILL.md, and let the agent pick it up. It’s that simple.

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