Future Makers

The Value of Intimate Gatherings

Meaningful connections and serendipitous interactions are more likely to occur at smaller-scale events compared to massive, highly-produced conferences.

“I'm talking about the weirdest stuff. The stuff that happens around the edges, around the periphery, around the fringes of the festival”

The Value of In-Person Connection

In an era dominated by digital loneliness, AI-generated content, and remote work, physical gatherings provide essential, high-value human connection that cannot be replicated by digital tools.

“with all the kind of, you know, AI slop and algorithms and Microsoft Teams calls... I think it's even more special and valuable to be in a room together”

The pursuit of human enhancement prioritizes future utility over immediate biological health.

While the rhetoric of design often centers on the baby, the underlying objective is the cultivation of a specific type of adult. We are less concerned with the infant's immediate state than with engineering future capabilities and intelligence.

The Value of In-Person Connection

In an era dominated by digital loneliness and synthetic media, physical gatherings provide a unique and essential space for genuine human interaction that cannot be replicated by virtual platforms.

“real conversations matter. Being in the room matters. Yeah? The conversations between the conversations matter.”

Individual-first tools create friction in shared spaces.

Personal AI privatises what used to be collective and visible — the fridge to-do list moves inside one person's glasses — and strips conversation of its natural ephemerality. ("Space is not faces.")

“So the to do list that is currently on the fridge where everyone can see it is going to become something that only I can see inside my glasses.”

Multiplayer AI is a Trojan horse for old, unsolved relational problems.

Adding people to a conversation is easy; the layer underneath — permissions, turn-taking, accountability, and what a shared AI should remember and for whom — is genuinely unsolved.

“What a shared AI should remember and for whom That's still very much unsolved.”

How do you sell this kind of new, unfamiliar work to clients who've never seen anything like it?

"Not very well. [But] because we have this confidence — and a network of collaborators with this creative confidence — what we're selling a lot of now is, no one knows what the hell they're doing, no one can see three or six months out. So the trick is to go: we don't know what you need either. Let's talk about it, then go make a bunch of things. Because right now we're telling you stuff, and you don't know how that feels." The follow-on point that lands it: briefs now tend to evaporate after the first meeting — "we tried to write a brief, but we don't really know what we're asking for" — because the old RFP loop was always fiction anyway.

Good AI makes work harder and more valuable — not just cheaper

The dividing line isn't AI vs. no AI; it's intent. Bad AI chases efficiency and cost-cutting and replaces human creativity. Good AI creates new value and lets people attempt things that were previously impossible — and teaches you as you build, giving the confidence to make things you couldn't have six months ago.

“But at the same time, if we don't do it, if good people don't do it, then what gets left is a bunch of assholes shaping the technology into something terrible.”

Memory and data are inherently social, yet our systems are database-first.

Today's memory serves the company more than the user. A social lens means modeling relationships and shared understanding, not just logging individual data points.

“At the moment, the way that we experience memory in our systems today is you are sort of expected to go somewhere in the settings and find individual data points that are more useful really to the company than to you.”

AI works best as a coordinator, not a participant.

AI-generated content isn't "load-bearing" because it represents no one in the room. The winning pattern is managing group memory and connecting people to the right human expertise — and native models still lack the social intuition to know when to speak or defer.

“I'm more intrigued about Bose. What does an AI look like when it belongs to a group together... It helps coordinate. It provides some memory. It can refer backwards, but it doesn't actually participate like a person does.”

The real barrier in big companies isn't ideas or budget — it's the permission bottleneck

In large, matrixed organizations the constraint is rarely ideas or resources — it's permission. Progress comes from engendering belief through proof points and micro-experiments, not from technology.

“The biggest challenge isn't the lack of ideas… They've got the resources and everything. It's permission. It's really not a technology problem, but a legitimacy opportunity.”

Is innovation ideation, or execution?

Innovation only becomes real when an organisation solves an actual problem and ships something; an idea on its own doesn't count.

“Innovation doesn't happen. It doesn't become real until an organization actually does something… You've got a problem that you're solving, you have an idea that gets after that in a way that's not been done before, and you are executing on it.”

Trust is bound to the human behind the content — and identity tools carry social risk.

Decoupling a contribution from its author destroys its credibility. Verification tools must be designed for the "unhappy paths," where the other party isn't who they claim to be.

“It feels like trying to decouple the person who is contributing from their contribution... leads to failure.”

AI can scale serendipity while protecting creative weirdness.

Freed from the consensus bottleneck, small teams get weirder and more personal, and prototyping hard, human-acceptable tools exposes what big labs still can't do. The bigger prize: acting as a "virtual yenta" that restores and scales the serendipitous connection physical hubs once provided, reaching talent outside London or San Francisco.

“It's people socializing together and serendipity. ... If only there can be some kind of serendipity that brings people together. ... And it's a place where automation could really help.”

Life isn't single-player — but AI is built as if it were.

AI today assumes individual accounts, private chats, and personal devices, yet real decisions and daily life are collaborative. "Multiplayer AI" spans people sharing a room, collaborating remotely, and agents acting for groups — and the right approach starts from the human and trust, not from scaling single-player tech.

“Those sorts of relational design moments are still really tricky to design for. We often don't get them right.”