I'm starting a newsletter :). Why now? Because I needed a place to document what I'm working through. AI is changing the workshops I design and facilitate. I'm having to rethink methods I've used for years — what still works, what needs adapting, what needs replacing entirely. And at some point I thought: if I'm doing this work anyway, why not share it? Hey, maybe even get some feedback on it :). That's what AI + Facilitation is. A bi-weekly Substack where I document what I'm learning as I adapt my practice. Facilitation techniques remapped for AI contexts. Moves I'm actually testing. A clear point of view on what's shifting. You're the first community I'm sharing this with — because if anyone gets why this work matters, it's you. First issue is live. https://open.substack.com/pub/danavetan/p/the-ai-facilitator-isnt-a-new-role?r=1w2obo&utm_campaign=post&utm_medium=web

I've been writing a series on AI Facilitation for the DSA blog — and this latest piece is the one I'm most curious to get your take on. It's called "What no one tells you when you start facilitating AI workshops." The core argument: you are not facilitating a team. You are facilitating a group of strangers who don't speak the same language. Is transitioning into AI facilitation something you're actively exploring? I ask because I keep seeing two kinds of facilitators right now. Those who feel pulled toward it ... because clients are asking, the work is there, and it feels like a natural next step. And those who aren't sure - because the AI part feels like a stretch, and they don't want to start something from scratch. But I'm more curious about where you are. Is this a transition you're moving toward — or does it feel like a different world from where you currently work?

Hey Design Sprint Masters, As facilitators, we all feel the pressure: workshops only matter if teams act on them. That led me to a basic rethink: what does a facilitator do in an AI-heavy organization? Over the past few months we’ve been shaping what we call the AI Facilitator—along with the tools and methods to help teams make AI decisions with a clear process. In Berlin this month, we’re sharing what came out of that work. It’s the biggest change we’ve made to the Design Sprint format. We’re not calling it a Design Sprint anymore. We call it the AI Workflow Sprint. Why? Because most organizations exploring AI aren’t trying to design new apps. They’re trying to redesign how work gets done: - Where AI should help or take over - Which use cases are worth building So the sprint starts with a real workflow, not a product idea. During the sprint, teams: 1. Map the current workflow 2. Spot where AI could change the process in a meaningful way 3. Redesign the workflow with people + AI together 4. Prototype the new experience 5. Test it with users We kept the core rhythm—diverge, then converge. But the thing you’re designing is the workflow, not just an interface. We’ll teach this for the first time in our AI Facilitator Training in Berlin this month. You should join: https://learn.designsprint.academy/AI-facilitator-training Unfortunately the early bird discount of €500 expires tonight. Until then you can still use code EARLYAI at checkout for €2,000 instead of €2,500.

Sometimes the best customer insights are hidden behind workarounds, hacks, substitute solutions. That’s why we created P.A.L.T. at Design Sprint Academy. It helps teams see the unseen — the less obvious problems — and explore territory where competitors aren’t. Proof: Claude Cowork Anthropic didn’t build Cowork because users requested it. They built it because they watched users hack Claude Code (a developer tool) to handle everyday tasks they couldn’t quite describe yet—like organizing files or planning trips. That’s a Painful + Latent sign. What P.A.L.T. stands for: P (Painful): → A problem that hurts, costs time, money, or trust. A (Aspirational): → A desire or wish that would feel good to achieve, but not critical. L (Latent): → A hidden issue or desire the user hasn’t yet recognized or can’t clearly express. T (Top of Mind): → Something the user is already aware of and actively thinking about (or actively looking for solutions). We use P.A.L.T. inside our AI Problem Framing workshop as a filter before teams commit to solutions. It helps them ignore, for a moment, the Top-of-Mind problems (where competitors also focus) and spend time where they can make a unique difference: Painful + Latent. I wrote a deeper breakdown of how Claude Cowork maps to P.A.L.T. (and how to replicate their way of thinking). https://www.designsprint.academy/blog/p-a-l-t---the-framework-anthropic-accidentally-proved-with-cowork Hope you'll find it helpful.

We have officially opened the agenda for next year's AI Facilitator Bootcamps. If you are ready to move to bridge the gap between AI ambition and execution—this is where it happens. We are keeping the cohorts small and the work hands-on. Join us in Berlin or New York: 👉 https://learn.designsprint.academy/AI-facilitator-training