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Robinson AI Lab is a community-led AI research initiative with a public-interest mission. We bring together people who are curious about AI and committed to studying it, building with it, and sharing what they learn.
We explore AI-enabled management, organizational learning, and human–AI collaboration through concepts, practical experiments, and open-source tools. Our flagship initiative is FridayOS: an evolving Agent OS designed to make AI collaboration more approachable in everyday work.
Explore FridayOS 1.0 · Getting started · Share a question or idea
The name draws on the association between Robinson and Friday. For us, it evokes a partnership: exploring unfamiliar ground, learning through experience, and building something useful together.
Robinson is our space for research and collaboration. FridayOS is where we turn that idea into tools. We want people to feel supported by AI while retaining agency, clear choices, and responsibility for important decisions.
| Research area | Questions we explore | What we aim to share |
|---|---|---|
| AI and management | How does AI change work, organizational learning, and the division of responsibility? | Concepts, research notes, and methods |
| AI in practice | How can AI support real workflows? Under what conditions does it help or fail? | Reproducible experiments, anonymized cases, and evaluation methods |
| Human-centered Agent OS | How can people understand, delegate to, and work alongside agents? | FridayOS, interaction studies, and collaboration tools |
| Open learning | How can people from different backgrounds participate in AI research? | Guides, examples, reusable resources, and constructive discussion |
By Agent OS, we mean a collaboration environment connecting AI agents, knowledge, tools, and tasks. Our research includes ways to make this environment approachable through familiar spaces, roles, and playful interaction, while keeping progress and human control understandable.
Current public starting point: FridayOS 1.0, formerly FridayOS-Lite. It provides a practical route into AI-assisted personal knowledge management using local Markdown files, Obsidian, and AI tools such as Claudian. Blueprints, setup guides, and fictional examples help people learn by doing.
Broader agent coordination, task execution, and interactive workspaces remain areas of ongoing development and validation. Each repository documents the capabilities of its own version.
- Start with a concrete problem. Describe the context and intended outcome before choosing a tool.
- Design around people. Reduce unnecessary complexity and keep meaningful human judgment in the loop.
- Show the evidence. Distinguish proposals, prototypes, observations, and validated results; document limitations and failures.
- Make learning reusable. Share clear methods, documentation, examples, and reproducible steps.
- Build openly and responsibly. Respect privacy, attribution, and project licenses when sharing research and tools.
Co-founder · Management practitioner and AI product builder
Owen brings experience in human resources, organizational learning, and product development to the intersection of AI, management, and gamification. He explores how knowledge and experience can become practical support for everyday work, and helps shape FridayOS's product direction, human-centered experience, and front-end exploration.
Full introduction in English · 中文介绍 · @Owen-Teng
Co-founder and collaborator — building and learning together at Robinson AI Lab.
You do not need to be an AI expert. A real question, a carefully documented experiment, or a clearer explanation can be a valuable contribution.
- Try it: explore FridayOS 1.0 and tell us where the experience is clear or confusing.
- Ask and discuss: describe your use case or research question in Issues.
- Contribute: improve a guide, translate a page, share an anonymized example, or propose a focused code change.
- Learn together: help make concepts and tools accessible across disciplines and languages.
Read our contribution guide, community standards, and security guidance.
Together, we learn, build, and share.