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Co-Steward With Us

The most powerful way to partner with the Applied AI Society is to co-maintain the truth.

The Model​

The Applied AI Society maintains an open source knowledge base of playbooks, concepts, frameworks, and workshop formats for applied AI education. This is not a static textbook. It is a living, version-controlled commons that evolves every week based on what practitioners and educators are learning in the field.

We do not need every organization to become an AAS chapter. We need organizations to co-steward the shared truth about what works.

The metaphor: Google, Amazon, and Microsoft compete fiercely. But they all contribute to the Linux Foundation because every data center runs Linux. The shared infrastructure benefits everyone. Applied AI education is the same. The playbooks for how to teach people to thrive in the applied AI economy are public goods. They should be maintained like public goods: openly, collaboratively, and with real accountability to quality.

What Co-Stewardship Looks Like​

Share Your Playbooks​

If your organization runs AI workshops, hackathons, mentor networks, skill trees, or any structured learning program, your playbooks belong in the commons. Not locked in a Google Drive. Published, version-controlled, and available for anyone to fork, adapt, and improve.

What we are looking for:

  • Workshop formats. How do you run your events? What works? What did you try that failed? The MVJ Workshop playbook is an example: continuously updated based on real sessions, honest about what went wrong, and immediately usable by anyone who wants to run one.
  • Curriculum and skill trees. How do you take someone from zero to building with AI agents? What is the progression? What are the prerequisites?
  • Expansion playbooks. How did you scale from one location to five? What did the second chapter need that the first one did not?
  • Concepts and frameworks. Have you coined a term or developed a mental model that helps people understand applied AI? Contribute it. Name it. Let the community build on it.

Co-Maintain What Exists​

Contributing a playbook once is valuable. Co-maintaining it over time is where the real leverage appears.

Applied AI moves fast. A workshop format that worked in January may need updates by March because the tools changed. A concept page that was accurate last month may need a new section because the landscape shifted. Compounding docs only compound if they stay current.

Co-stewardship means:

  • Filing issues when something is outdated or wrong
  • Submitting updates based on your own experience running the playbook
  • Adding lessons learned from your community to the shared knowledge base
  • Keeping the signal high and the noise low (signalmaxxing applies to docs, not just feeds)

Run the Playbooks in Your Community​

The best way to improve a playbook is to run it. Take the MVJ Workshop format, run it with your community, and report back what worked and what did not. Take the event formats, adapt them to your audience, and share what you learned.

Every community is different. What works for business owners in Austin may need adjustments for engineering students in Milwaukee or artists in Los Angeles. Those adjustments are the contribution. They make the playbooks more universal and more useful for the next community that picks them up.

Who This Is For​

  • University AI clubs that have built learning programs and want to share them with a broader network
  • Community organizations running applied AI events in their city
  • Corporate training teams that have developed internal AI education and are willing to open source parts of it
  • Individual practitioners who have developed workshop formats, frameworks, or curricula worth sharing
  • Anyone who believes applied AI literacy is a public good and wants to help maintain it

What You Get​

This is not a one-way contribution. Co-stewards get:

  • Access to the full commons. Every playbook, concept, framework, and workshop format that every co-steward has contributed. Your organization benefits from the collective experience of every community in the network.
  • Visibility. Your organization and contributors are credited in the docs. When someone runs your playbook in another city, they know where it came from.
  • Network. Connection to a growing network of educators, practitioners, and community builders who are all working on the same problem from different angles.
  • Feedback loops. When other communities run your playbook and improve it, those improvements flow back to you.

How to Start​

  1. Look at what exists. Browse the playbooks, concepts, and event formats. See what is already documented and where the gaps are.
  2. Share what you have. Email your playbooks, skill trees, workshop formats, or curriculum to us. We will work with you to integrate them into the commons in a way that is useful to everyone.
  3. Run what exists. Pick a playbook and run it in your community. Report back with what worked and what needs updating.
  4. File issues. Found something outdated or wrong? Open an issue. That is a contribution.

Reach out via the contact page or join the Discord to get started.

Current Co-Stewards​

  • OpenTeams and Open Technology Incubator: Founding sponsors. Building the infrastructure layer for applied AI and open source.
  • Milwaukee AI Club: 500+ member student-led AI organization across 5 Midwest universities. NVIDIA expansion partner. Contributing mentor network playbooks and skill trees.
  • Applied AI Institute for Europe: European applied AI research and education institute. Bridging applied AI literacy across the Atlantic.

This list grows as more organizations contribute to the commons.

Further Reading​