Thesis

Coordination is becoming the bottleneck.

For most of history, execution was hard. You needed capital, labour, logistics, expertise. Ideas were cheap; making them real was expensive. Organisations existed primarily to execute—to assemble the people and resources needed to do things.

That's inverting. AI agents will increasingly handle execution. Code gets written, documents get produced, analysis gets done. The cost of making things is collapsing.

What remains scarce: knowing what to make, and with whom. Intention. Judgment. Trust. The combinatorial problem of matching people to people and people to purposes.

This is coordination, and it's where humans stay in the loop.

We're building infrastructure for coordination. The goal is to reduce the cost of finding the right people, at the right time, for the right purpose—then getting out of the way so they can act.

Why events

Events are our starting point because they solve several problems at once:

Embodiment. Events are irreducibly in-person. You can't automate showing up. In a world where more and more happens on screens, events are a forcing function for presence.

Fast feedback. At an event, you know quickly whether a connection worked. Did they meet? Did they talk? Did they exchange details? This tight loop lets us learn what good matching looks like.

Trust seeding. Shared physical context creates trust that's hard to manufacture otherwise. "We were both at X" is a foundation for "we should work on Y."

Natural expansion. A meeting at an event becomes a follow-up coffee. A coffee becomes a collaboration. A collaboration becomes a project. The platform grows with the relationship.

The long view

We start with events, but that's not where we end.

The same coordination logic that suggests "you should meet this person at this conference" can suggest "you three should work on this project together" and eventually "here's how these tasks should flow across this team."

As coordination demand grows—and it will, because good coordination creates new possibilities that themselves require coordination—the platform becomes a general-purpose layer for human agency. A canvas on which intentions become action.

We think this makes us, eventually, a new kind of institution. Not a company that does things, but infrastructure that enables others to do things. The coordination layer beneath an increasing share of how work and collaboration happen.

What we believe about humans

We don't think AI makes humans obsolete. We think it clarifies what humans are for.

Hannah Arendt distinguished between labour (necessary survival activity), work (making durable things), and action (initiating something new among others). Labour and work can be automated. Action cannot—it requires presence, plurality, the willingness to begin something whose consequences you can't control.

Our job is to create the conditions for action. Events are spaces of appearance. The platform is a way of ensuring that when you show up, it's to the right room, with the right people, around the right questions.

The goal is not to keep you on the platform. It's to get you off the computer and into the world, with higher-quality coordination than you could achieve alone.