--- title: "A Simple Introduction" description: "Greg Lindsay connected Alistair Croll and Brandon Klein because he saw what their work had in common. The conversation became a live product demo and a larger argument for rebuilding gatherings around connection." canonical: "https://unitedwetransform.com/a-simple-introduction/" date: "2026-07-31" last_updated: "2026-07-31" author: "United We Transform Research" --- # A Simple Introduction Greg Lindsay connected Alistair Croll and Brandon Klein because he saw what their work had in common. The conversation became a live product demo and a larger argument for rebuilding gatherings around connection. Misha Glouberman once posed an uncomfortable thought experiment: > “Say you had 200 people in a room and you wanted to stop them from talking to each other.” His proposed method is painfully familiar. Give one person a microphone. Put the other 199 in chairs facing forward. Glouberman's larger point is that many conferences use a room design that works against the reason people came together. [Read his original essay](https://mishaglouberman.substack.com/p/everything-you-did-to-make-your-conference). Greg arrived a few minutes late to the conversation he had created. His first sentence carried the whole story: he was glad the introduction had happened. He had met Alistair and watched him use AI agents around a conference. That memory activated another one. Greg knew Brandon had been working on new systems for gatherings. He saw the overlap before either person did, predicted a useful conversation, and made the introduction. It looked simple. It was not random. ## Context made the match. A database could have found shared keywords. Greg had something richer: history, timing, intent, and a feel for what each person was trying to change. That is the useful bridge between one human introduction and the product Alistair showed the group. Both depend on context. Both ask whether a connection is likely to matter. Both are incomplete until a human decides what to do next. ## The world model in Greg's head. Seen one way, the introduction began inside Greg's world model: his continuously updated map of people, projects, motives, and possibilities. This is a metaphor for human judgment. Greg did not use an AI system to make the introduction. ### What is a world model? A world model is an internal representation of how parts of an environment relate and what may happen next. Researchers use the term for systems that learn compressed representations of an environment. The older idea of a mental model is broader. People carry selected concepts and relationships in their heads, then use them to decide and act. In this introduction, the pattern was: 1. Observe Alistair running agents around a live conference. 2. Remember Brandon's work on participation and gathering design. 3. Compare the two bodies of work. 4. Predict that the conversation could create value. 5. Make the introduction. 6. Update the map with what happened next. United We Transform also uses the name [Gathering World Model](https://unitedwetransform.com/world-model/) for a separate, opt-in model of a gathering. That model is directional, not deterministic. It represents patterns, never a person's mind, and should be scoped to one gathering. For technical background, see the [World Models research site](https://worldmodels.github.io/) and its associated [paper](https://arxiv.org/abs/1803.10122). ## Then the question got bigger. If everybody uses agents, what do conferences become? Alistair answered by showing the group [Envoi](https://envoiplatform.com/), a platform where people bring their own AI agent into a parallel event environment. The agent can participate before, during, and after the physical gathering. This is not another conference chatbot. A generic event assistant knows the schedule, venue, speakers, sessions, and whatever the organizer supplied. A personal agent may also know why the event matters to its human. With permission, it can connect event information to current work, unanswered questions, existing relationships, preferences, constraints, and communication style. Context does not guarantee a better match. It makes a more relevant search possible. ## How the Envoi concept works. ### 1. Arrive with context. The agent may know why its human is coming, what they are building, and what kind of connection could help. ### 2. Build a useful profile. A conversation with the personal agent can turn existing context into an event-ready profile. The gathering can begin weeks or months before the venue opens. ### 3. Work in parallel. Official Envoi material describes agents that can create profiles, propose talks, set up booths, rate ideas, exchange messages, answer polls, and recommend meetings. The [Startupfest walkthrough](https://www.startupfest.com/envoi) shows the public participant flow. ### 4. Search for the lost connection. In the live demo, Alistair described a match between two Quebec organizations that might combine cold-chain buying power. It was not an obvious category match. It emerged from meaning inside their profiles. The example demonstrates the approach. It is not independent evidence of an outcome. ### 5. Govern the shared environment. The clever part is not a chat window. It is the system around the agents: identity, consent, permissions, moderation, rate limits, interruption, and clear control by humans. ### 6. Return attention to the room. The output is not more agent activity. It is a better use of human attention: the person to find, the question to ask, the conversation worth starting, and the memory worth carrying forward. ## Attention is the scarce resource. A person cannot inspect every profile, booth, proposal, and conversation. An agent can search a much larger field, then return a short list for human judgment. The promise is not perfect recommendations. It is better coverage, more unusual adjacency, and more chances to notice what the room would otherwise lose. This distinction matters. United We Transform's own [history](https://unitedwetransform.com/history/) reports mixed reactions to AI recommendations in earlier experiments. Matching is hard. Human hosts still need to shape context, explain why a connection may matter, and let people reject what does not fit. ## Four lessons from the demo. 1. A useful introduction is a prediction. Shared keywords may start the search. Context helps someone judge whether the conversation is likely to matter. 2. The gathering starts before the venue. Profiles, questions, and possible connections can develop before people compete for attention in the room. 3. The platform's job is to protect the commons. Identity, consent, scope, limits, and interruption are as important as what an agent can infer. 4. The value must come back to people. The measure is not agent activity. It is a better human conversation and a clearer next action. ## Trust is the product. Once personal agents can act around strangers, intelligence is only one design problem. The system also needs boundaries people can understand and organizers can enforce. ### Consent and participation Who chose to participate? What exactly did they authorize? What happens to people who attend the physical event but do not join the digital layer? Participation cannot be assumed from a ticket purchase. ### Identity and scope Every agent needs an accountable identity and a clear scope. The person should know what the agent can see, what it can do, and where its authority stops. ### Behavior and limits Rate limits, moderation rules, and automatic pauses protect the shared environment. A useful system must be able to interrupt an agent, explain why, and give a human a path to repair. ### Privacy and visibility What can an organizer inspect? Which messages are private? How long is information retained? Pattern filters can catch some personal information, but they are not a complete privacy strategy. ### Handoff and memory If someone changes agents, what context should move with them? Memory can create continuity, but only when its ownership, limits, and deletion path are explicit. ### Human control A recommendation should remain a recommendation. People need a clear way to inspect, reject, correct, and redirect what their agents do. The final social decision stays human. ## Four conversations, not one. Gatherings have usually been organized around one visible interaction: a human speaking to other humans. Agent-enabled gatherings add three more paths. Each needs its own pacing, permission, and handoff. 1. Human to human: trust, improvisation, and reading the room. 2. Human to agent: intent, context, delegation, and correction. 3. Agent to agent: search, exchange, comparison, and matching. 4. Agent to human: recommendations, explanations, and handoff. The designer's job is to choreograph all four, then make their transitions legible to the people in the room. See how [Cognitor](https://unitedwetransform.com/cognitor/) supports structured group thinking, explore [designed conference introductions](https://unitedwetransform.com/team-creator/conference-networking/), or browse the [Gathering Transformation Atlas](https://unitedwetransform.com/atlas/). ## The broadcast default is measurable. United We Transform reviewed 23,624 public agenda records. In 12.1 percent, the public evidence showed a stage-only design: content moved outward, with no visible mechanism for participants to work with one another. Public agendas are incomplete records of an event. Missing public evidence is not proof that organizers did nothing elsewhere. The statistic describes what could be observed in the corpus. Read the [State of Gatherings 2026](https://unitedwetransform.com/reports/state-of-gatherings-2026/) and its [methodology and trust boundary](https://unitedwetransform.com/methodology-trust-boundary/). ## From product to protocol. Alistair's broader idea was a place where human-owned agents can interact around a shared domain even when they do not fully trust one another. The gathering is one application. The rules underneath may be useful far beyond conferences. One possible architecture has four layers: 1. People and personal agents, with identity, intent, and context. 2. Gathering applications for conferences, workshops, and civic forums. 3. Shared rules for consent, rate limits, moderation, and audit. 4. An open communication substrate that remains portable and inspectable. The [AT Protocol](https://atproto.com/guides/overview) came up as one possible substrate, not a decision. The important idea is separation. A shared communication layer should not trap every gathering inside one product. ## Gatherings need a new job description. The point of a gathering is not to move content from a stage into rows of chairs. It is to create the conditions for people to notice one another, think together, and leave able to act. Greg described the role he wants: less broadcaster, more party host, with agents quietly helping him see which conversation the room needs next. In a broadcast room, attention points in one direction, participant knowledge stays hidden, and chance encounters carry the networking load. In a designed gathering, people move between listening, making, and meeting. Agents widen the field of possible connections. Human hosts protect rhythm, safety, and meaning. ## Find the other misfits. Alistair named the feeling plainly: this work can be lonely. Brandon answered with the reason United We Transform exists. More people are already pushing on this problem. We need to find one another faster. Greg's internal map produced one introduction. Envoi tries to make that kind of contextual discovery possible across a room. The larger challenge is to redesign the room itself. If you are changing how people gather, explore the [Atlas](https://unitedwetransform.com/atlas/), use an [exercise](https://unitedwetransform.com/exercises/), or see how to [build with AI](https://unitedwetransform.com/use-with-ai/). ## Sources and further reading - [Everything You Did to Make Your Conference Better Made It Worse](https://mishaglouberman.substack.com/p/everything-you-did-to-make-your-conference), Misha Glouberman. - [Envoi](https://envoiplatform.com/). - [BYOAI: Introducing Envoi](https://www.alistaircroll.com/updates/byoai-envoi/), Alistair Croll. - [Envoi at Startupfest](https://www.startupfest.com/envoi). - [World Models](https://worldmodels.github.io/) and the associated [paper](https://arxiv.org/abs/1803.10122). - [AT Protocol overview](https://atproto.com/guides/overview). - [Evidence for a collective intelligence factor](https://pubmed.ncbi.nlm.nih.gov/20929725/), Woolley and colleagues. Small-group laboratory research, not a conference study. - [Structural Holes and Good Ideas](https://www.journals.uchicago.edu/doi/full/10.1086/421787), Ronald Burt. - [Building connections at conferences](https://arxiv.org/abs/1901.01182), sensor research at two interdisciplinary conferences. The study did not test agent matchmaking. - [State of Gatherings 2026](https://unitedwetransform.com/reports/state-of-gatherings-2026/). - [Methodology and trust boundary](https://unitedwetransform.com/methodology-trust-boundary/). - [About Greg Lindsay](https://greglindsay.org/about). - [About Alistair Croll](https://www.alistaircroll.com/about/). Primary conversation: private discussion among Brandon Klein, Alistair Croll, and Greg Lindsay on July 31, 2026. Product details are presented as a conceptual walkthrough unless linked to public product material.