One of the more useful Substacks I read is from Greg Shove and Taylor Malmsheimer from SectionAI, the online school that has shaped so much of my way of thinking about AI, not as it’s applied to creativity, but how it’s applied to business. I completed my Mini-MBA in AI for Business with Section a while ago. In the most recent newsletter, Greg and Taylor point to two observations. They weren’t connected, rather part of a long list of observations.

I think they should be.

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The first: the work ratio has flipped. For most of modern professional history, work looked roughly like this — 10% deciding what to make, 80% making it, 10% checking whether it was any good. That middle 80% was the job. That’s where the hours went, where the craft lived, where you proved your value by volume of output.

Now it’s closer to 40/20/40.

Your numbers may look different right now. But start asking your team how they’re actually allocating their time on any given project, and watch what you find. The shift is already happening underneath the official version of how work gets done.

The making — the part machines have swallowed — is down to 20%. The bookends have doubled. Human time is now concentrated at the front, where you decide what matters and instruct the machine on how to pursue it, and at the back, where you judge what came out and refine it with something the machine doesn’t have.

We’ll get to what that something is.

The second observation: you feel like a bottleneck, yet more valuable at the same time. Machines work faster than you. You are simultaneously the most important part of the process and the thing slowing it down. That tension is uncomfortable.

It’s also correct.

Most people I talk to are experiencing this and don’t have language for it. They know something has shifted. They feel both more necessary and more exposed. They’re producing more, faster, and somehow feel less confident about what they’re contributing.

That’s not an accident. That’s the ratio doing its work on you.

Taste Is the Job Now

Here’s what’s actually happening at both bookends.

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The brief used to go to a photographer. Then to a stock library. Then to a prompt. If you’re still at the prompt stage and calling that an AI workflow, you’re already behind — you just haven’t felt it yet.

The moment you actually feel it is specific. It’s the first time you wire a text-to-image model to an LLM that’s writing its own prompts — and watch the system generate ten campaign variations from a single brand input, in parallel, without you touching it. And then, in a short time, you figure out how to use a Brand Book, a color system, a design aesthetic, not as PDFs to review, but as system-level inputs that guide the thinking of the LLMs as they begin to construct the outputs.

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Something shifts. Not in what AI can do. In what you now understand about how to use it. The chat box closes in your mind. The canvas opens. And you realize that prompting was never the destination. It was the first yellow bricks leading you to Oz.

Prompt engineering was the entry ticket. The ability to write a clear, structured, contextually intelligent instruction to a language model and get a high-quality output — that took real skill, and it separated those who understood what AI could do from those who were still dismissing it. But that window closed faster than anyone expected. What was a differentiator in 2024 is table stakes in 2026. And the new floor is significantly higher, technically more demanding, and far less forgiving of people who stopped learning when the first result impressed them.

Prompts and Orchestration

A prompt is a single conversation with a single mind. You write in, the model responds, you refine, it adjusts. Even a sophisticated prompt — one with role definition, context, constraints, output format — is still a one-to-one transaction. One human, one model, one output. It’s a remarkable thing. It’s also, structurally, not that different from asking a very good assistant a very well-phrased question.

The limitation isn’t the model. It’s the architecture. When everything runs through a single instruction in a single session, you are the only system. Your consistency, your brand knowledge, your quality control, your ability to scale — all of it depends on you being in the loop for every output. That’s not a workflow. That’s a bottleneck with better tools.

Node-based AI platforms — I’ve been working extensively in Figma Weave, though the category is expanding rapidly — make the architecture visible. Instead of a chat interface, you’re working on a canvas. Instead of one prompt, you’re building a network of nodes, each one a discrete function, each one governed by its own behavioral contract.

That last phrase is important.

In an orchestrated system, a system prompt doesn’t guide the node. It is the node — its role, its rules, its limits, encoded permanently. A node defined as a cinematic camera operator will always behave as a cinematic camera operator — assessing compositions, generating shot variations, maintaining visual logic — regardless of what’s flowing through the pipeline around it. Its role is fixed. Its judgment is encoded. You authored it once, and now it works.

What changes everything is what sits between those nodes. An orchestrator doesn’t produce the creative. It directs the system that produces the creative. In practice, this means an LLM interprets input, generates structured instructions, and routes them to the next node, which might be another LLM, a video model, an image model, or a logic gate that determines the workflow’s path.

The human is two levels up, authoring the director rather than the scene.

The screenshots embedded in this article show what this actually looks like in practice. Brand bible feeding brand elements feeding product iteration feeding ad generation — each node cross-referencing upstream data, maintaining consistency not through human checking but through structural design. Variables replacing single prompts, so that changing one input — character, location, time of day, camera type — recomputes the entire output without touching the logic. One composition fanning out simultaneously into ten camera angles, five format resizes, three video interpretations, all running in parallel. This is creative production at actual scale. Not faster one-at-a-time. Genuinely simultaneous.

The Creative Implication

The most significant shift isn’t speed or volume. It’s where creative judgment now lives.

In a prompting workflow, judgment happens at the output stage. You generate, you assess, you refine, you generate again. The loop is tight and human-intensive.

In an orchestrated system, judgment moves upstream — into the architecture itself. The decisions about how brand color should behave, what a photographer node is and isn’t allowed to do, what constitutes scene integrity, which variables are fixed and which are dynamic — those are creative decisions, made once, encoded into the system, and then enforced at every output automatically.

Brand stops being a PDF that someone consults inconsistently. It becomes a data structure that the system references structurally. Consistency ceases to be a discipline enforced by human review. It becomes a property of the architecture. The creative director’s judgment isn’t absent from the output — it’s present in everything because it’s built into the system that makes it all.

This is a different kind of creative leadership. Less about making the work. More about designing the machine that makes the work, and knowing exactly why every node is governed the way it is.

The tax, and why it matters

None of this is easy to learn. That’s not a caveat — that’s the point.

Orchestration requires understanding how to write behavioral contracts, not just instructions. How to design for parallel execution, not sequential refinement. How to think in data flow — what enters a node, what transforms inside it, what exits, and what the next node expects to receive. How to encode brand intelligence as structured variables rather than descriptive paragraphs. How to build constraints as architecture rather than relying on human oversight to catch drift.

This is a genuine technical tax. It takes time to pay, it requires deliberate study, and it separates those who are building serious AI-enabled creative systems from those who are still, in 2026, celebrating a well-written prompt.

I am one session away from completing the Lighthouse AI Academy Figma Weave Live Studio course precisely because I wanted to pay that tax in full, under instruction, with real deliverables. 7 session, 90+ minutes each, at 3am SGT.

I am earning my 10,000 hours the hard way. The only way.

Weave is my current platform of choice for orchestrated creative workflows — the node-based canvas makes system design visible, accelerating genuine understanding. But the thinking is not platform-specific. The same principles apply across every serious node-based environment emerging in this space.

What the course clarified for me wasn’t any single technique. It was the shift in professional identity that this type of work demands. You are no longer a creative who uses AI. You are a systems architect with creative intent. The outputs are still images, video, copy, and campaigns. But the work — the real work — is the pipeline.

Build the Craft. Break the System. Repeat.

Here is what nobody tells you about learning orchestration: you will build pipelines that fail elegantly, and pipelines that fail catastrophically, and for a while, you won’t always know the difference until you’re three nodes deep into the wrong answer.

That’s not a problem with your aptitude. That’s the curriculum. There is no shortcut through it, and the people building the most sophisticated systems in this space right now got there by breaking things methodically and paying attention to exactly what broke.

The mindset this work demands isn’t perfectionism. It’s scientific curiosity with a high tolerance for productive failure. You run the workflow. You read the output. You find the node where the logic drifted, the system prompt that was governing too loosely, and the variable that wasn’t constrained tightly enough. You fix it, run it again, and go one level further. Test-and-learn is not a methodology here. It’s the only way the knowledge actually enters you.

What I’d tell anyone serious about moving into this space: get on a node-based platform and stay there until the canvas stops feeling foreign. Figma Weave is where I do this work. New environments are emerging fast. The specific platform matters less than the commitment to working visually, spatially, systemically — understanding what enters a node, what transforms inside it, and what the next node needs to receive. That fluency is what you’re building. The tool is just where you build it.

And a word on the fundamentals, because this matters more than the industry currently acknowledges: do not abandon what you already know. Your eye is not obsolete. Your understanding of light, composition, pacing, brand voice, narrative structure — that is precisely what you are encoding into these systems.

You cannot write a behavioral contract for a photographer node if you don’t understand how photographers see. You cannot build a brand architecture pipeline if you don’t have a genuine command of what brand consistency actually requires. The craft doesn’t disappear inside an orchestrated workflow. It moves upstream, becomes structural, and governs everything downstream. But it has to be there first.

The system is only as intelligent as the thinking you build into it.

This is why the creative leaders who will matter most in the next 12 months aren’t the ones who abandoned traditional craft for AI, or the ones who dismissed AI to protect traditional craft. They’re the ones who understood that the relationship between human judgment and machine execution just got more intimate, not less — and went to work on learning the new language of that relationship.

The stakes have changed. The minimum buy-in has increased. Most people are still counting their chips.

The question worth asking yourself — honestly — is whether you’re building systems or still writing prompts and calling it AI fluency. Both have value. Only one of them has a future at the serious end of this industry.

If you’re leading a creative agency, a production company, or a brand team and you’re trying to understand where your operation actually sits in this new landscape — I work with leaders on exactly that. Strategic assessment of AI readiness, workflow architecture, and team capability.

If you’re building something serious and need someone who has done the technical work, not just theorized about it, let’s talk. And if you want your teams to develop this fluency from the inside — the systems thinking, the orchestration mindset, the hands-on craft — that’s a conversation I’m equally ready to have.

In Part I of this series, I wrote about AI as rehearsal space — the cognitive interval that prepares us for the conversations, relationships, and moments that actually matter. This is where that argument lands.

We are experiencing the synthetic expansion of our world, and with it, the rediscovery of presence. The Presence Economy is the growing premium placed on lived, embodied, and shared human experience in an increasingly synthetic world. I’ve spent enough time in and around live events to know exactly what’s missing from them.

What follows is what that means for every brand, agency, and organization trying to figure out where trust gets built next.

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The Practitioner’s Paradox

I am an AI practitioner. I have been building with these tools since before most agencies had a policy about them. I believe in what AI can do at the ideation stage, the production stage, the distribution stage. I use it every day.

And I am telling you: the most important thing a brand can do right now is get people into a physical space.

That is not a contradiction. That is the whole argument.

If Part One was about what AI is doing to individuals, this is about what a world saturated with AI is doing to the value of physical presence — and what that means for every brand trying to build something real.

The Great Flood of 2025

In 2025, AI-generated content flooded the internet. Not trickled. Flooded. Video, copy, images, campaigns — all of it faster, cheaper, more scalable than anything human hands could produce at volume. The platforms filled up. The feeds became indistinguishable. And somewhere in the noise, something quietly broke.

Consumer preference for AI-generated content has collapsed — from 60% to 26% in three years. More than half of all consumers now disengage the moment they sense a machine made what they’re looking at. McDonald’s Netherlands pulled an AI Christmas ad mid-season after audiences called it, with surgical precision, “soulless.” Coca-Cola’s holiday experiment generated more backlash than brand love. Industrial Light and Magic — the company that literally invented modern movie magic, the people who put the Millennium Falcon in hyperspace — got condemned at their own AI presentation.

This is not a niche reaction. This is not the cultural equivalent of people who still buy vinyl. This is a market signal.

People are not just tired of bad AI content. They are increasingly unable to trust any content at all. Nearly 60% of consumers now doubt the authenticity of what they encounter online. And doubt, once seeded, does not discriminate. It spreads to everything in the feed — the real and the manufactured alike.

The algorithm cannot save you from this. You cannot prompt your way out of a trust collapse.

And here is the part nobody in a content strategy meeting wants to say out loud: the audience learned this from us. We taught them to be suspicious. We flooded their attention with generated sameness until their instincts recalibrated. Now those instincts are working exactly as designed — against us.

Which means the next move is not more content. The next move is the one thing that cannot be generated.

You Can’t Produce the Feeling

Bono said this to David Letterman. Not in an interview about music. In a conversation about Ireland — a country rediscovering itself through the collision of tradition, dissent, and community. About what happens when people stop consuming a culture and start inhabiting one together.

He wasn’t talking about concerts. He was talking about the irreducible thing that happens when human beings share physical space at a moment that matters. The emotion is the event. Everything else — the stage, the sound, the production — is just the architecture that creates the conditions for it.

The events industry forgot this. Somewhere between the LED walls and the production riders and the keynote run-of-show, the category confused the container with the content. Brands spent decades building bigger rooms and more impressive reveals — optimizing for what the audience could see rather than what the audience could feel.

AI just made that mistake unforgivable. Because AI can now produce technically flawless spectacle. Visuals. Sound. Narrative architecture. It can generate the stage. What it cannot generate is the collective holding of breath. The person in row seven who doesn’t know why they’re crying. The moment a room full of strangers becomes, briefly, a single organism responding to the same thing at the same time.

That is what brands are actually buying when they invest in live. Not the production. The conditions for emotion. The engineering of the moment where something real happens to someone who will remember it.

You cannot produce the feeling. You can only produce the conditions for it. And that requires people in the same place at the same time.

Consider what women’s football became in the space of three years. Not incrementally more popular. Culturally detonated. The 2023 Women’s World Cup final drew 400 million viewers. The NWSL went from afterthought to sold-out stadiums and Nike signature deals. The Lionesses became household names in a country that had largely ignored them for decades. None of it was manufactured by a content strategy. All of it was witnessed — in stadiums, in pubs, in living rooms full of people watching people play in front of people. The physicality of the validation was the point. You could feel the realness of it from the outside because you could see the realness happening live.

Brands noticed. More importantly, the PR organizations that know how to focus cultural attention on a thing that deserves to be seen noticed. The lesson women’s football taught the industry is not about sport. It is about what happens when you put something genuinely compelling in a room and then build the right machinery to surface its importance to the people who weren’t there. The content followed the moment. The moment came first.

The global event market hit $1.6 trillion in 2026. Experiential marketing sits at $55.5 billion and climbing. 74% of Fortune 1000 marketers are increasing experiential budgets at the exact moment overall B2B marketing spend is declining by 3%. That contrast is not noise. That is a directional bet, made by the largest organizations in the world, with the largest stakes.

The dominant research finding across the experiential industry right now is a shift from events designed to impress to events designed to create belonging. And here is the counterintuitive data point that should end every debate about scale: companies investing in micro-events — 50 to 75 people, intentionally contained — are 15% more likely to hit year-over-year growth above 20%.

Live is the next channel. Presence is the product.

The Irony

The backlash against AI-generated content is real and it is growing. But the answer is not to abandon AI. The answer is to understand where AI belongs — and where it does not.

AI does not belong in the thing that is supposed to feel human. It belongs in the architecture behind the thing that feels human. In the intelligence gathering before a single concept is pitched. In the imagination explosion that happens before a dollar is spent on fabrication. In the reactive environments that make a built space feel alive and specific. In the content harvest that extends a physical moment into every digital channel — for weeks, in clips, in coverage, in conversation.

The brands that figure this out will not look like AI brands. They will look like the most creatively alive, most culturally present, most emotionally resonant brands in the room. Because they will be in the room. And they will have used every intelligent tool available to earn the right to be there.

That is the irony. And it is also the strategy.

AI killed content trust online. AI, used correctly, builds better live expressions so people feel something real. And then the right people — the ones who know how to focus attention on a thing that deserves to be seen — make that real moment matter beyond the room it happened in. In an era where audiences have learned to distrust what was made for them, something witnessed carries a different weight entirely. PR’s oldest instinct — surface the importance of a real thing rather than fabricate the importance of a fake one — is suddenly the most sophisticated move in the playbook.

Four Places AI Earns Its Place in a Live Event

There are four distinct areas where AI is changing what live experiences can be — and what brands should start demanding from the agencies they are about to spend significantly more money with.

Most practitioners are working one or two zones. The opportunity is in holding all four simultaneously, from brief to build.

Intelligence. Before a single concept is pitched, AI can distill what audiences actually want from an experience. Behavioral data, cultural signals, desire mapping, competitive scans — assembled and synthesized at a speed and depth that no research team can match manually. The strategic question that precedes every great experience still requires a human who knows how to ask it. But the intelligence that informs it no longer has to take weeks to surface. This is the difference between going into a brief with a hypothesis and going in with an argument.

Imagination. AI as previsualization engine. Before fabrication. Before a vendor is briefed. Before a floor plan is drawn. AI can build the experience and let you walk through it. The tunnel that takes you from now into the brand’s vision of tomorrow, fully rendered in generative video before a single wall is built. The room that shouldn’t exist yet, pressure-tested before the budget conversation. This is where ideas that would never survive a PowerPoint actually get argued — and where the ideas that seem impossible suddenly become fundable. It moves the creative conversation from description to demonstration.

In-Experience AI. The built environment that responds to the people inside it. Reactive surfaces. Generative visuals personalized to each visitor’s inputs. Spaces that are not the same on Friday as they were on Tuesday — because the audience on Friday is not the same audience as Tuesday. This is not technology as spectacle. This is the oldest storytelling instinct — make the audience feel like the story is about them — executed at a scale and specificity that was not previously possible. The experience stops being an installation and starts being a conversation.

Content Harvest. 72% of attendees capture content during live events. The question is whether that capture is accidental or engineered. In the clip economy, every experience needs to be architected with its afterlife in mind — the clips that carry the story, to which audiences, at which moment, through which channels. The live event is not just an event. It is a content production environment with a live audience inside it. AI processes, sequences, and optimizes the harvest. Human intelligence decides what the story is and why it matters. PR determines which version of that story travels furthest — and to whom.

The harvest is not what happens after the event. It is what the event was always also for.

The Missing Role That Changes Everything

Most experiential agencies have producers, creatives, and technology vendors. Three separate conversations, happening sequentially, each one handing off to the next with some information lost in every transition. The intelligence brief doesn’t fully survive into the imagination phase. The imagination phase doesn’t fully translate into the built experience. The built experience generates content that nobody planned for properly.

What’s missing is not another vendor. What’s missing is a single point of creative intelligence that can hold all four zones simultaneously — someone who understands what the data is saying, can explode it into something imaginative and unbuildable-looking, translate that into a reactive physical environment, and design the content harvest before the first guest arrives.

That is not a producer. It is not a creative director in the traditional sense. It is not a technology consultant.

It is a new role. And right now, almost nobody is doing it.

The brands that find those people — or build those capabilities — will not just produce better events. They will produce the experiences that become the proof of record for what their brand actually stands for. In a world where generated content has devalued the claim, the live experience becomes the evidence.

Where This Goes

Part Three of this series will go deep into the mechanics — how each zone works in production, what the technology enables, what the creative direction requires, and what a brand brief for an AI-augmented live experience should include.

The digital feed is full. The trust is gone. The next beachhead for any brand serious about building something real with its audience is not a campaign. It is not a content series. It is not a platform strategy.

It is a place. Designed with intelligence. Built with imagination. Alive with technology. And harvested — deliberately, precisely, with full knowledge of where each clip needs to land — long after the lights go down.

The most powerful signal a brand can send in 2026 is the one that requires someone to show up.

Build something worth being there for.

Work With Me

Most briefs for live experiences arrive too late and ask too little. If you want to change that — and build something that earns its place in the Presence Economy — let’s talk before the brief is written.

RockPaperScissors was built on a simple belief: that AI and human creativity are not opposing forces. That the best experiences — live or otherwise — happen when intelligence works invisibly behind the thing that feels human. That is what we do.

My name card says AI consultant. My CV says strategist, creative, filmmaker. But if I’m honest about what connects thirty years of work across all of those disciplines, it’s this: I am a cultural anthropologist without the degree. No fieldwork grants. No peer review. No institutional affiliation lending weight to the observation. Just four decades of walking into rooms, asking questions, and paying very close attention to the distance between what people say and what they mean.

Which is why, over the past several months, I’ve been spending a lot of time with a generation that most people my age are content to theorize about from a distance. Not in focus groups. Not through data. In rooms. Actual conversations. The kind where you put the framework down and just listen.

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I have been talking to a lot of young designers lately — in their twenties and early thirties, all of them Gen Z — to try to understand how AI is impacting their lives, for good or bad. The conversations always tend to follow a very specific route. Not to productivity. Not to prompts. Not to which tool was fastest, cheapest, or most likely to take their jobs.

They describe how AI makes them feel.

One called it a sounding board. Another said it was the first place she went when she had a question she didn’t want to ask out loud. A third described it, without a trace of embarrassment, as a colleague. Not a human colleague. Something different. Something that was always there, always available, and more importantly, something that was there that never made her feel stupid for asking.

As I listened, I found myself paying less attention to what they were saying and more attention to how they were saying it. Because they weren’t describing a tool. They were describing a relationship.

I’ve spent thirty years in rooms like that one, listening for what people mean rather than what they say. And what I kept turning over afterward wasn’t what they were using AI for. It was what they were using it instead of.

For many observers, this is where alarm bells start ringing. The narrative is familiar. Young people are lonely. Technology is replacing human connection. AI will make things worse.

But I wonder if we’re misunderstanding what is actually happening. Because what I heard wasn’t a generation trying to replace people. What I heard was a generation creating space.

The Thing Between Things

The easiest way to explain this is through architecture. In design, we often talk about the importance of objects. A colour system, a typeface, how a thing feels in your hands, how a thing might sound, or behave. But what often matters just as much is the attention to what we call the negative space. The pause. The breathing room. The silence that allows everything else to exist.

There is a Japanese concept called ma. It doesn’t translate cleanly into English, which is part of why it matters. It is not emptiness. It is not an absence. It is a meaningful interval — the pause between musical notes that gives the melody its shape, the silence between words that tells you something important just happened, the negative space in a room that allows the furniture to exist without crowding each other into irrelevance.

I think AI, at least the way this generation is using it, is functioning as a form of ma inside the architecture of human relationships. Not a replacement for those relationships. Not a shortcut around them. Something that sits in the interval. Something that creates the conditions in which the relationship can be better. Not replacing relationships. Creating cognitive space around them. A place to test an idea before bringing it to a colleague. A place to rehearse a difficult conversation before having it with a spouse. A place to ask a question without fear of judgment. A place to think out loud.

That is a meaningfully different claim than the one most people are making about AI right now.

The Rehearsal Room

Before AI, people had other ways of doing this. Journals. Long showers. Drives alone with the radio off. Mentors who had enough patience to hear a half-formed idea without immediately trying to fix it. Therapists who charge by the hour to hold the space while you work out what you actually think.

Some people had access to all of those things. Many people had access to almost none of them.

What this generation has discovered, not through research or intention but through instinct and iteration, is that AI can serve as a cognitive rehearsal space. A place to test the argument before you make it in the meeting. A place to draft the difficult conversation before you have it with the person you love. A place to ask the question you’re not ready to be seen asking yet.

The young designer who told me she goes to AI when she has a question she doesn’t want to ask another person — she wasn’t describing avoidance. She was describing preparation. There is a difference. One is retreat. The other is how you get ready to advance.

This is what distinguishes AI from every previous tool in that list. A journal doesn’t respond. A mentor has opinions, an ego, and limited availability. Google returns 10 links and trusts you to synthesize them. Reddit responds, but with judgment attached, which rather defeats the purpose.

AI responds immediately, retains context, doesn’t tire of half-formed thoughts, and imposes no social consequences on the exploration. For the first time in history, you can think out loud to something that thinks back, and the only person who has to know is you.

That is not a small thing. That may be one of the most quietly significant cultural shifts of this decade.

What Remains

What if AI doesn’t diminish the value of human relationships? What if it increases it?

At first glance, that sounds backward. Much of the public conversation assumes that every interaction delegated to AI is an interaction lost. That every question asked of a machine is a question no longer asked of another person.

But that assumes all interactions are equal. They aren’t. Some interactions are transactional. Some are exploratory. Some are rehearsals. And some are presence.

The conversations I was having with these young designers made me wonder whether AI is quietly absorbing a category of interaction that has traditionally happened in public. The half-formed idea. The embarrassing question. The rough draft of a difficult conversation. The uncertainty we are not yet ready to expose to another person.

In that sense, AI is not replacing the relationship. It is preparing us for it. The meeting still matters. The friendship still matters. The mentor still matters. The person on the other side of the table still matters. Perhaps even more than before. Because once the rehearsal moves elsewhere, what remains becomes increasingly valuable. The performance. The conversation. The moment of genuine human connection.

The Presence Economy

I have started thinking about this as the emergence of what I call the Presence Economy. For most of modern history, information was scarce and access was valuable. Today, information is increasingly abundant, and conversational intelligence is becoming ubiquitous.

As abundance grows, something else becomes scarce. Not information. Not intelligence. Not access. What becomes scarce are the things abundance struggles to reproduce: attention, trust, connection, and presence. The ability to sit with another human being and feel genuinely seen, understood, challenged, supported, or inspired.

The irony may be that AI helps us rediscover the value of precisely those things. Not because it can replace them. Because it can’t.

What fascinates me is that this observation seems to lead directly into another trend that, on the surface, appears completely contradictory.

If AI is becoming more deeply embedded in our lives—if we are increasingly comfortable using it as a sounding board, a collaborator, a rehearsal space, and in some cases a companion of sorts—then logic would suggest that human-to-human interaction should become less important over time. That has been the dominant narrative for years. Every new technology arrives accompanied by the same warning: people will become more isolated, more disconnected, more removed from one another.

And yet that is not entirely what I am seeing.

At precisely the same moment that AI is becoming more conversational, more capable, and more integrated into daily life, there is a growing hunger for experiences that are unmistakably human. Live music is thriving. Festivals continue to attract enormous audiences. Retreats, workshops, communities, running clubs, creator gatherings, supper clubs, and countless other forms of in-person participation seem to be growing rather than shrinking. In a world where almost anything can be consumed digitally, people continue to seek out experiences that require physical presence.

These trends appear to be moving in different directions. One seems to pull us inward, toward reflection and preparation. The other outward, toward experience and connection.

But I am beginning to wonder if they are actually part of the same story. Because abundance has a curious habit of changing what we value. When a thing becomes scarce, we value access to it. When it becomes abundant, we begin to value the qualities that abundance cannot reproduce.

The industrialization of food did not eliminate our desire for authentic food. If anything, it amplified it. The more standardized food became, the more fascinated we became with provenance, craftsmanship, local ingredients, and the story behind what was on the plate. The rise of mass production created a parallel demand for authenticity.

But the more I sit with that thought, the more I find myself returning to a different word. Not authenticity. Authentication.

Authenticity is a quality. Authentication is a process. One describes what something is. The other describes how we come to believe it.

Authentication

Perhaps something similar is happening with intelligence, creativity, and communication.

For most of human history, creating content required effort. Producing an image required skill. Writing required time. Research required access. The friction involved in creation gave the output value.

AI changes that equation dramatically.

We are moving toward a world of near-infinite generation. Infinite images. Infinite videos. Infinite articles. Infinite opinions. Infinite versions of the same idea expressed in slightly different ways.

That abundance is extraordinary. It is also changing the nature of scarcity. Because while content may become effectively infinite, trust does not. Presence does not. Shared experience does not. Meaning does not.

No matter how sophisticated our systems become, there remains a category of human experience that cannot be generated. It has to be lived.

A concert is not valuable because of the music alone. We can already stream the music. A gathering is not valuable because information is exchanged. Information is abundant. A conversation with someone you trust is not meaningful because words were spoken. Words are everywhere.

These experiences matter because they authenticate something. They transform information into understanding. They transform connection into trust. They transform participation into belonging. That distinction feels increasingly important.

As synthetic experiences become more abundant, authentic experiences become more valuable. As generated content becomes easier to produce, lived experience becomes more difficult to imitate. As intelligence becomes increasingly available on demand, the moments that allow us to feel genuinely connected to another human being become more precious.

Seen through that lens, AI and the Presence Economy are not opposing forces. They may be accelerating one another.

AI is where we prepare. Life remains the place where we authenticate.

The machine helps us organize our thoughts, challenge our assumptions, explore possibilities, and rehearse difficult conversations. But the conversation itself still matters. The relationship still matters. The moment of trust still matters.

Perhaps more than ever.

One Day, the Technology Will Disappear

Every transformative technology eventually disappears into the background. Not because it failed, but because it succeeded. The printing press did not remain a novelty. Electricity did not remain a conversation topic. They became infrastructure — invisible, assumed, load-bearing. AI will follow the same trajectory. One day we will stop talking about it the way we stopped talking about electricity. It will simply be part of how thinking happens.

And when that day comes, our attention will move — as it always does — toward what the technology cannot replace.

The moments of trust. The moments of genuine connection. The experiences that can only be authenticated by being inside them. The conversations that require two people to be present, undistracted, willing to be changed by what the other one says.

The great irony of artificial intelligence may be that it helps us rediscover the value of what was never artificial in the first place.

Which brought me to a place I did not expect to arrive when I sat down with those young designers. Because if AI is genuinely preparing us for presence — if it is, as I’ve come to believe, the rehearsal space before the performance — then something significant follows for how brands, agencies, and the organizations that serve them need to think about where trust gets built next.

That is not a philosophical argument. It is a strategic one. And it is what I will write about next.

It starts here, though. With a generation that taught me something I hadn’t thought to ask.

Last week, Thom Yorke walked to a podium at Grosvenor House in London to accept the Fellowship of the Ivors Academy — the highest honor British music gives to its songwriters — and proceeded to do what he has always done. He said the uncomfortable thing, clearly, in front of the people most uncomfortable hearing it.

Watch Thom Yorke’s full acceptance spe…

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A note of thanks. I was invited to speak at Campaign360 on the main stage, in front of an audience of some of the region’s most senior creative and marketing minds. That invitation meant something. Not just as a professional recognition, but as a signal that the questions I’ve been asking, quietly, sometimes inconveniently, belong in the larger conversa…

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You finish the render. You play it back. The image is exactly right — the light, the motion, the texture. All of it. You’ve been staring at this thing for days, and it finally looks the way you had intended, or at least hoped for.

And yet, there is a hollowness to it, a lack of depth, an anchor to hold it in place. It’s missing… presence, atmosphere. Ano…

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This is my first long read in a while, not because I had nothing to say, but because I was too busy learning to say it properly.

That’s the thing about writing honestly about AI and creative practice — you can’t fake the reps. You either know what you’re talking about from the inside, or you’re just repackaging someone else’s observations with better voc…

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I’ve been carrying a bias. Time to put it on the table.

Every time someone asked me about AI and the creative industry, I’d circle back to the same concern. The entry-level job is disappearing. The tasks that young creatives used to cut their teeth on — the resize, the copy variation, the spec ad, the deck draft — AI is eating those for breakfast. And if…

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Today, it seems that every article, post, and carousel needs a hook to get people to read it.

Ok, so here is the hook...

“I’ve had impostor syndrome my entire professional life. And the first thing I’ll tell you is — stop calling it that.”

The label you put on a feeling determines the ceiling you put on yourself. And “impostor syndrome” is one of the most …

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Most brand storytelling still works the same way it did twenty years ago. Big ideas. Big budgets. Long production cycles. But generative tools are quietly changing something more fundamental than production speed.

They are changing the role of experimentation in storytelling.

Instead of asking whether an idea is worth producing, we can now explore ideas q…

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After forty years in the creative industries, you recognize patterns. The industry has never lacked ideas. It has never wanted for talent or imagination. And yet something was missing.

Ideas arrive in flashes, campaigns come and go, and technologies rise and fall. Agencies reorganize themselves every few years in response to the latest shift — social, mo…

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The sentence arrives casually now, almost as a reflex.

It shows up in pitch meetings, brand reviews, procurement calls, and late-stage budget negotiations. Someone leans back in their chair, glances at the production estimate, and says it with a kind of satisfied clarity:

“If we shot this properly, it would cost two hundred thousand. But with AI… it’s bas…

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Generative AI is not just changing how films are made. It is changing how stories are written—and for scriptwriters, that shift may be the most consequential creative development since the script itself became the industry’s dominant unit of meaning.

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There is no doubt in my mind that this is the most important piece I’ve written so far.

History rarely announces itself. It arrives quietly, disguised as efficiency and ease. Artificial intelligence is doing exactly that—slipping into our thinking, our decisions, and our creative work faster than we are pausing to notice.

This essay is an attempt to slow…

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Every technology that survives long enough eventually undergoes the same transformation. It stops being discussed as an object—something new, something impressive, something external—and instead becomes embedded in language as an action.

It turns into a verb.

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There is a sentence I keep hearing lately, delivered with an odd mix of amazement and alarm, usually by people who want you to know they are paying attention to the moment we’re in. “It’s getting really human now.” Sometimes they lean in when they say it. Sometimes they lower their voice. As if they’re sharing a secret. As if the machine might be listen…

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RockPaperScissors completed it’s second year of operations a couple of days ago. I’ll write more about my thoughts on this later, but I wanted to first say thank you to everyone involved in this growth, and my own journey - my clients, partners, and confidants. I am truly grateful.

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