School of AI & Wisdom
Workshop
A four-hour workshop for thinking clearly with AI. In Amsterdam. Hands-on, tool-agnostic, small group. You leave with a framework — not another prompt library.
Next session: Spring 2026 · Dates TBD
Dr. Aidan Lyon & Dev Bhattacharya
This workshop creates a rare space: four hours to step back from the velocity of AI adoption and think clearly about what it means for how you work, decide, and relate to your own intelligence. It is not a tech training. It is a space for depth, hands-on exploration, and the kind of thinking that speed makes impossible.
You will leave with a coherent framework for engaging AI with discipline and discernment — a set of principles, competencies, and practices for thinking well with AI.
This workshop is for anyone who uses AI and wants to do it better. It’s less about tools than about the thinking that happens around them. Whether you work alone or lead a team, the questions are the same — how do I engage AI with intention, and how do I know when to trust what it gives me? The situations below are specific; if any feel familiar, this is likely for you.
You’re using AI daily but it feels fragmented — too many tools, no coherent approach, and a growing sense that you’re falling behind.
You sense that AI deserves more serious attention than it’s getting — and that the real question isn’t how to use it, but how to think with it.
You reach for AI when a task demands it, but you have no framework — no principles guiding when to trust it, when to override it, or how to evaluate what it gives you.
Your team is experimenting with AI but everyone is doing it differently. You need shared language and shared principles — not another tool demo.
AI is a power of that same order — an indiscriminate amplifier. Everything you bring to it gets multiplied: clarity, or confusion, at the scale of the tool.
When you approach AI anxious, rushed, or scattered, AI mirrors exactly that back. Scattered input becomes scattered output — multiplied across every workflow, every decision.
Most of us already use AI daily without a clear sense of what it is or how we want to relate to it. The technology works. The models are powerful. The bottleneck is the missing framework for thinking well with it.
“a single question”
You ask a single question. AI returns seventeen paragraphs — each plausible, none yet judged. The tool generates faster than you can evaluate. Unexamined output is not work; it's only the appearance of work, multiplied at machine speed.
The scarce resource in modern work is no longer information. It is the judgment required to evaluate it.
The Mirror Principle says: whatever you bring to AI, AI multiplies. Scattered attention becomes scattered output at scale. Without a framework for deciding what's worth reading — and what can be discarded unread — you drown in your own outputs.
The workshop trains the discipline of defining a clear outcome before engaging the tool, so that every returned paragraph can be measured against a standard, not consumed indiscriminately. Less reading. More thinking. Better decisions.
“is this right?”
AI sounds equally confident whether it's right or wrong. With no reliable way to tell the difference, organizations oscillate between blind trust and blanket skepticism — and neither is a working strategy. Calibration is a practice, not a setting.
Trust calibration is the cultivated skill of knowing when AI's output can be taken at face value, when it needs verification, and when it should be overridden entirely. The philosophical tradition calls this phronesis — practical wisdom, the capacity to perceive what a situation actually demands. No algorithm can teach it.
The workshop trains the question you learn to carry into every AI interaction: When should I trust this? When shouldn't I? What determines the difference? That question, asked well, is the single strongest protection against being quietly wrong at scale.
“help me with this”
AI is brilliant at producing outputs. It cannot deliver outcomes. Most AI frustration begins in this confusion — treating a document as a deliverable, a summary as a decision, a draft as the thing done. The outcome was always yours to define.
The missing discipline is upstream of the prompt. Before engaging AI, you need to know what you are actually trying to achieve — not what you want to be written, but what you want to be true.
The workshop teaches this inversion: define the outcome first, then use AI as raw material in service of it. The work of judgment, context, and intention remains yours. AI does not do the thinking. It amplifies whatever thinking you bring — and scattered intention produces scattered artifacts, however polished each one looks in isolation.
“am I doing this right?”
The nagging sense that you're not getting the most out of AI — without knowing what “the most” would even look like. A good prompt isn't a trick. It's the articulation of a clear thought. When you struggle to prompt well, you're usually struggling to think clearly about what you want.
The quality of your prompt reveals the quality of your thinking, and no amount of prompt-engineering templates will paper over an ambiguous intention.
This is the work the workshop calls calibrating your signal: settling your attention, clarifying your intention, knowing what you actually want before the conversation with AI begins. It is the single most impactful skill in working well with AI — and it has almost nothing to do with AI itself.
“which should I pick?”
AI doesn't resolve decisions. It multiplies options. Six drafts, four directions, three strategies, all plausible — and no framework for choosing among them. Without that framework, abundance becomes paralysis, and the tool that promised to save time starts consuming more of it than before.
The root of decision fatigue is not that AI gives you too much. It is that you approached the tool without knowing what you were trying to decide.
Clarity over certainty: when the outcome is sharply defined before you engage AI, the returned options either serve that outcome or they don't. Choosing becomes almost automatic.
The workshop trains this reversal — the discipline of defining before delegating, so that AI becomes a thinking partner rather than another source of noise. The options haven't changed. What's changed is the standard you're measuring them against.
The workshop is four hours of learning to think clearly with AI. What we install is not a tool or a trick, but a way of engaging — the discipline of knowing what you want before you ask, and of evaluating what you get before you act. The shift is in the mind, not the software.
You leave with a framework, not a prompt library — a way of thinking that sharpens every AI interaction. You’ll engage it with intention, calibrate trust in its output, and aim it where it matters. The skills don’t expire with each model release: they aren’t tied to any particular AI, but to how clearly you think when you work with one.
Five principles that hold together — the Mirror Principle, the abundance shift, clarity over certainty, go slow as flow, and tolerance of uncertainty. A framework you install in yourself, not software you download.
The two or three places in your work where AI actually earns its keep — prioritised by outcome, not enthusiasm, and grounded in real tasks from your own context. Drawn in the room, on paper, yours to keep.
A three-part template for any prompt — context, query, format. Practised on real work in the room, then yours forever. Works across every tool, every version, every model that comes next.
Your own written answer to what “beyond tools” means for your work — the outcomes you commit to, the patterns you refuse, the direction you have chosen. The compass you come back to when the next model ships.
The workshop extends beyond the session itself: follow-up resources, access to community discussion, and an invitation to future sessions as the School of AI & Wisdom grows.
Not software you install on a computer.
A framework you install in yourself.
AI mirrors back whatever you bring to it — clarity compounds, and so does confusion, at scale. Clarity OS is a framework for thinking well with AI. It is built on clarity rather than certainty, on presence rather than prompts. The payoff is the quality of mind behind every interaction.
AI reflects back the cognitive patterns you bring to it. If your thinking is clear, AI makes it clearer. If your thinking is muddled, AI compounds the confusion — faster and at greater scale.
AI dissolves the traditional scarcity that conditioned human competition and guardedness. Kindness and playfulness are not soft — they are strategic assets.
Certainty seeks fixed answers. Clarity cultivates discerning presence. In a landscape where AI outputs feel authoritative but may be wrong, clarity is the only stable foundation.
Deceleration as a strategic advantage. Going slow means paying enough attention to see what speed obscures. Paired with genuine play — slowness becomes flow.
AI operates probabilistically. It does not know; it predicts. Working well with AI requires cultivating emotional and cognitive resilience in the face of this fundamental uncertainty — learning to surf the wave rather than demand solid ground beneath your feet.
The workshop runs in seven short modules with two breaks between them. Each module pairs one key idea with a hands-on exercise on your own work. The group is small, the AI tools are live, and the conversation is real. You arrive with questions you haven’t had space to ask — and leave with a framework and one concrete next step.
Arrival & Orientation
Not a tech training — a space for presence. Establishing ground rules: intellectual honesty, psychological safety, a willingness to sit with what you don’t yet understand. The Go Slow principle as the workshop’s signature. Four questions surface where you really stand with AI, creating a baseline we return to at the close.
What Is AI, Really?
Enough understanding to reason well with AI — no technical depth, just conceptual clarity. The amplification thesis: AI intensifies whatever cognitive patterns are already present. Clear thinking becomes clearer; confusion compounds faster. The Mirror Principle shifts the question from “how do I use this tool?” to “what am I bringing to it?”
Surfing Uncertainty
AI does not know; it predicts. Every output is a best guess drawn from patterns, not a verified truth — and its confidence tells you nothing about its accuracy. Working well under these conditions means learning to read the wave rather than control it. Critical evaluation becomes the foundational skill of AI fluency, the condition of every other practice that follows.
The Art of Prompting
Prompting is not a technical trick — it is the articulation of a clear thought. When you struggle to prompt well, you are usually struggling to think clearly about what you actually want. We teach the Context → Query → Format framework, applied hands-on to your own work with live AI tools. Then the inversion: asking AI to challenge your thinking rather than merely answer it — extraction becomes dialogue.
Biases — Yours, AI’s, and the Entanglement
The philosophical heart of the workshop. Bias is not merely an AI problem — it is a human-AI entanglement. You bring biases to your prompts; AI absorbs biases from its training; the outputs confirm and deepen the loop you began with. We make that loop visible through concrete examples, so you can recognize the distortion you might otherwise mistake for intelligence.
Risks & Mitigation
Five concrete risks, clearly named. Hallucination — plausible false outputs delivered with confidence. Data leakage, over-reliance, deskilling, and the quiet inconsistency that emerges when teams use AI without shared principles. A simple, practical mitigation for each. The module closes on the trust calibration question you learn to carry into every interaction: when should I trust this, when shouldn’t I, and what determines the difference?
Building Your AI Partnership
From scattered tool-use to a coherent operating system — not software you install, but a framework linking tools, principles, habits, and judgment into one way of working. The pivotal distinction: AI delivers outputs, never outcomes, and most AI frustration lives in conflating the two. You’ll configure a simple personal workflow, then return to the four opening questions and commit, in front of the group, to one concrete next step.
Without a framework
Apply for the pilot.
AI is not primarily a tool. It is a cognitive amplifier — it intensifies whatever cognitive patterns you bring to it. Clarity compounds, and so does confusion, at the scale of the machine. This is the Mirror Principle, and it is why prompt tricks and workflow templates don’t reach the underlying problem: they optimize the surface of an interaction whose quality was already determined upstream, by the quality of mind you arrived with.
What we teach is older and rarer — phronesis, the classical discipline of practical wisdom. The skill of perceiving what a situation demands, holding uncertainty without collapsing into false certainty, and acting with discernment when no formula applies. It requires two disciplines that rarely meet in the same room.
Built by a philosopher who also architects multi-agent AI systems. Not theory about AI — understanding forged in the act of building it.
Sixteen years of guiding groups through adaptive change — in high-performance environments where ideas must survive contact with reality. Every exercise is field-tested.
Philosopher, AI architect, and researcher of uncertainty, wisdom, and the mind.
Mathematical philosopher and consciousness researcher. PhD in Philosophy (2009) and Bachelor’s degrees in Mathematics and Philosophy (2006). Member of the Munich Center for Mathematical Philosophy, with publications in top philosophy journals and appointments across three continents.
Author of Psychedelic Experience: Revealing the Mind (Oxford University Press, 2023). Consults on high-stakes decisions under extreme uncertainty — biosecurity, geopolitical forecasting, institutional investing, conservation biology, and psychedelic therapy.
PhD Philosophy, Australian National University·20+ Years, 3 Continents·Center for Psychedelic Space, Founder·Author, Oxford University Press
Agile coach, facilitator, and builder of contemplative communities at scale.
For sixteen years, Dev has guided teams through adaptive change at Booking.com, Yamaha, and across three continents. His facilitation work is shaped by real-world pressure: teams navigating complexity, leaders seeking clarity, and communities learning how to think, connect, and grow together.
Dev is the founder of The Passionate Philosophers, Amsterdam City Social, and Maison Magnétique — Amsterdam-based communities and platforms reaching over 6,000 members around philosophy, social connection, and conscious transformation.
Senior Agile Coach, Booking.com·Founder, The Passionate Philosophers·Founder, Amsterdam City Social·Founder, Maison Magnétique
One builds AI systems that reveal the architecture of mind. The other builds human systems that survive contact with reality.
What’s included
Spring 2026 · Amsterdam
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