Building a Personal AI Agent with Markdown-Based Skills and Local Models
By
Tomasz Tunguz
Pure flour-power. Hearty enough to carry you through lunch.
Summary
The article describes a personal AI agent built on Pi that manages the author's inbox, calendar, deal pipeline, blog publishing, and research. The system uses two layers: a local markdown knowledge base (QMD) with ~80 workflow files for procedural guidance, and atomic SKILL.md files that each describe a single job. The approach allows frontier models to teach smaller, local models to perform real work without retraining, functioning more like a small operating system than a chatbot.
Key quotes
· 5 pulledI've been using state-of-the-art models to teach small models running on my computer how I work.
My personal agent, based on Pi, runs my inbox, my deal pipeline, my blog publishing, my calendar, & my research.
It looks less like a chatbot & more like a small operating system.
The first layer is QMD, a local markdown knowledge base of about eighty workflow files in ~/memories.
The second layer is Skills, atomic SKILL.md files that describe one job each.
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