Practice. Passion. Purpose.

I am a facilitator, operator, and experience designer who uses AI to help groups think better together.

My practice is facilitation powered by AI.

I am good at reading the room. I know when people are confused, when they are performing agreement, when the loudest voice is taking over, when the quiet person has the real insight, and when a group needs structure before it can make progress.

That skill did not come from a facilitation textbook.

It came from years of bringing very different people together under pressure: customers, operators, founders, executives, technical teams, governance participants, community members, and people with competing incentives who still needed to make high-impact decisions.

That is why AI is so useful in my sessions.

Used well, AI gives the group something to react to. It creates drafts, maps tensions, compares perspectives, generates possibilities, and helps synthesize what the room is saying. It can make abstract conversations concrete. It can help people see their own thinking from the outside.

The entry point is often AI adoption, because that is the urgent question many teams are asking right now:

• How should we actually use this?
• Where is it safe?
• Where is it useful?
• How do we build confidence without creating chaos?
• How do we help people activate without forcing them?

A strong AI activation session can answer those questions while giving the team a shared experience of what better AI-assisted thinking feels like.

My approach to this is the AI Activation Playbook: a structured facilitation method that moves groups from uneven AI curiosity to practical, shared momentum. The method is designed for the room you actually have, not a room where everyone arrives at the same starting point.

Beginners, enthusiasts, and skeptics in the same room is not a problem to manage before the session starts. That uneven readiness is the material the session works with. Your team can be anywhere on the AI readiness spectrum and the session still works.

From there, the work can expand.

Once a team sees that AI can help them think together, the same practice can support opportunity discovery, strategy exploration, decision-making, customer insight, internal alignment, service design, and countless other core business problems.

AI adoption is the doorway. The deeper practice is helping groups think, decide, and move better together.

My passion is designing interactive AI experiences for groups.

I care about the live moment: the room, the energy, the reveal, the surprise, the useful artifact people leave with, and the conversation that happens because people experienced something together.

That might be a team session. It might be a conference booth. It might be an internal meeting. It might be a chamber talk. It might be an event partner looking for something more engaging than another panel or slide deck.

The question I keep returning to is:

Sometimes that means a simple exercise where everyone gives AI the same input and compares what comes back.

Sometimes it means using agents to organize different perspectives.

Sometimes it means turning audience responses into a live synthesis.

Sometimes it means designing a custom experience where participants leave with a personal artifact, a team-level insight, or a new way to talk about what is possible.

I am interested in the frontier of AI not because every group needs the newest tool, but because the frontier keeps expanding what a live experience can be.

AI can make events more participatory. It can make meetings more revealing. It can make group thinking more visible. It can help people move from passive attention to active discovery.

That is the part I love. AI as a medium for better shared experiences.

Before a decade in startups, governance systems, and AI workflows, I learned how to read a room.

I DJed. I bartended. I worked in retail sales. I sold cars. I founded and ran an events company.

That background matters more than it might seem.

It taught me how energy moves through a group. It taught me when people are engaged and when they are just being polite. It taught me how to create momentum, how to recover when something feels awkward, and how to make an experience feel alive instead of forced.

Then I spent the next decade in startups, consulting, product strategy, operations, decentralized governance, machine learning-adjacent work, and systems design.

I have worked around messy real-world constraints: teams, incentives, budgets, trust, politics, execution gaps, and technology that does not behave as cleanly as the demo promised.

That mix is the point.

I am comfortable with people who are excited about AI, people who are skeptical of it, and people who are quietly worried they are already behind. I can talk with non-technical operators in plain language, and I can also think deeply about agent systems, governance design, workflow architecture, and collective decision-making.

I use AI and agent systems in my own work every day. I have built notation experiments, open-source projects, and personal operating systems because I prefer to learn from practice rather than theory alone.

But the tooling is not the center of the story. The center of the story is that I know how to design a room where people can try something new without feeling stupid, where useful tension can surface without derailing the session, and where the group leaves with more clarity than it came in with.

I am serious about the work, but I do not think the work needs to feel stiff. The best sessions have structure, momentum, humor, usefulness, and a little bit of surprise.

The deeper thread running through my work is collective decision-making.

Collective decision-making is the intellectual root of this work. The facilitation method grows out of it, and it is the reason the AI adoption moment holds my attention as a genuine question worth working on, not just a business to run.

I care about how groups make choices, how communities coordinate, how institutions earn legitimacy, and how technology can help people cooperate at larger scales. That interest has shaped everything: how I think about room design, what questions I ask before a session, and how I read what a team actually needs.

Elinor Ostrom showed that communities can govern shared resources through practical, context-sensitive systems rather than relying only on top-down control or pure market logic. That framing is present every time I design a session that asks the group to figure something out rather than receive a decision made elsewhere.

RadicalxChange was another major influence. After reading Radical Markets by Glen Weyl and Eric Posner and attending the first RadicalxChange conference in Detroit, I started the first RadicalxChange meetup in Chicago. It helped connect a lot of threads: markets, democracy, public goods, identity, governance, incentives, and the possibility of better systems for cooperation.

The long arc of this runs past any single session. I want to help build technology that makes group coordination work better: open systems where useful contributions are recognized, shared decisions get easier to make, and more people can take part in building things of shared value. Helping teams adopt AI well is the near-term, practical edge of that longer effort.

The AI activation work grows directly from it. A team that learns to think together with AI is practicing, at small scale, the same thing I care about at large scale: groups making better decisions together, with better shared information, and without losing the people who hold the real knowledge.

I have always been interested in the moment when a group becomes more than a collection of individuals.

• A dance floor finds its energy.
• A team sees the real problem.
• A room full of skeptics gets curious.
• A messy conversation turns into a decision.
• A new technology stops feeling abstract and becomes something people can use.

That is the work I want to do.

AI gives us a new medium for it.

My job is to design the experience that helps people feel what is possible, think more clearly together, and leave activated.