The slot is 45 minutes, first thing on the Friday, with a VC panel on AI as a competitive edge straight after. The job is to level-set the room. The audience splits three ways: investors who are not close to what is really happening in agentic AI, founders building at the forefront, and VCs financing all of it while running their own firms on none of it.

The talk starts from the gulf between the popular mental model of AI, a ChatGPT prompt for 20 euros a month, and what founders and engineers actually mean when they say agents: systems that decide what to do, do it, and iterate until the goal is met. From there it moves through how my own working week changed, what a shared context vault looks like in practice, and what enterprise rollout really involves. It is an adaptation of the INSEAD executive primer I gave in June, sharpened for an investor room: where in the VC value chain agents can be deployed today, and what that implies for the companies they back.

I will publish the deck and notes here after the event.

The format is deliberate. Four days, a beautiful remote chalet in the Alps near Geneva, and a group small enough that everyone is in every conversation. Mornings are for the mountains: hiking, cold water, silence. The rest is structured work in two strands. Alexander and Caitlin provide the coaching side to take on the founder as a person: fear, limiting beliefs, what leadership actually costs. I take the operator side: mentoring circles where each founder puts a real problem on the table and gets worked answers from people who have been through it, on products, fundraising, hiring, enterprise sales, and AI engineering itself.

The session participants consistently rate highest is the one we now call The Board You Cannot Afford: a closing circle where the group acts as each founder's board for an hour. The feedback across cohorts says the same thing in different words: the compound of peer mentoring plus proper coaching plus altitude does something a conference cannot.

Participants have come from across Europe and the US, from seed-stage founders to people building inside the frontier labs. Cohorts are invitation-first and kept deliberately mixed by stage.

If you are an AI founder and this sounds like your kind of thing, get in touch or register interest on our site here.

I designed and built a new website for them in Claude Design to enable hobbyists and researchers to access the full corpus of evidence and relate it to the chronology of the Shakespeare canon.

It is a fun project, but it is a clean example of a pattern I keep seeing at every scale, from heritage societies to enterprises: the AI layer is the last 10% of the work, and it is only as good as the corpus underneath it.

My html slides are here: https://insead.sambourton.ai/

The premise: most executives are treating agentic AI as an infrastructure decision and delegating it to IT. That is a mistake. Every choice in AI carries trade-offs in strategy, operations, organisational design and talent, so the strategic question is not "are we using AI" but where on the spectrum from prompting to goal-seeking agents your organisation actually sits.

Four parts, in twenty minutes, over lunch. From prompting to agents: why the architecture shift changes what AI can do inside an enterprise. Under the hood: a live demo of the actual development environment used to build agents today, including my own second brain, a knowledge graph of 1,700-plus linked notes with agents working across it, no slideware. From roles to workflows: why AI automates tasks rather than jobs, and what it means to lead when you orchestrate agents alongside people. And the right questions: the ones that separate executives who get value from those who do not, for your teams, your vendors, and yourself.

The room was senior, non-technical, and sceptical in the useful way. The talk was twenty minutes; the discussion ran seventy-five with really great questions.

The interesting part is what works on top of it. A set of personal AI agents share the vault as their common context. Scheduled agents produce the daily layer: a morning brief, meeting prep, email triage, an AI news digest, all landing as notes before I sit down. Meeting transcripts flow in automatically and get routed to the right project with the right people linked. A conversational agent on Telegram gives me the whole thing by voice from anywhere - both in English and a French agent which also acts as my personal French tutor. And when I work, in Cowork or Claude Code, the agents read and write the same files I do, so context never has to be re-explained.

The guardrails matter as much as the capability. Agents draft, I decide: nothing is sent, published or deleted by an agent, ever. No one will ever get an email or message purporting to be from me but written by AI. New artifacts land in staging folders for review and distillation. Every session logs what it changed to a shared journal, so each agent, and I, can see what the others did.

The compounding effect is the real product. Every meeting makes the next brief better; every decision logged makes the next agent run smarter. It is also a working demo of what I think organisations will build: I showed it live at the INSEAD executive session in June, and a codified blueprint of the whole setup, with a replication checklist, is how I help others build their own. I plan to open source the blueprint soon.

The argument drew on the QuantumBlack years: the distance between an AI system that demos well and one that a hospital, an examiner, or an international organisation can depend on is not a model problem, it is an engineering and organisational one. Scaling is where most of the difficulty and most of the value lives, and the organisations with society-critical missions are exactly the ones that cannot afford to get it wrong.

The conference is also where several threads of my Geneva work started: conversations that turned into advisory relationships, and a first-hand read on how the city's international organisations are thinking about AI.