I need to begin with a disclosure. What follows is a story about my wife’s experience — an experience of being made into someone she is not, by a machine that was supposed to be listening. I am writing it because I was struck by what happened and because I think it matters. But I want to be precise about my position in this story: I am the witness, not the subject.

Tempestt has known what it feels like to be *other*. Not in the way the AI imagined — we’ll get to that — but in ways that are real and varied and hers. She was raised in a religion she eventually walked away from to find herself whole in other spiritual and cultural environments. She was a single mother before she met me. She has moved through worlds where she didn’t quite fit the expected categories — not visibly enough to be labeled, not comfortably enough to go unchallenged. These are experiences I have not had. I am a straight white man, French-born, and the forms of friction I’ve encountered in life have never included having my identity assumed, contested, or overwritten — even as a single dad, which does not come with the same cultural framing as single mom, but that’s a story for another day. So I’m documenting something that is not mine. I am trying to shed light on it honestly, not to appropriate it, and certainly not to perform contrition on behalf of systems I did not build.

What happened is this.

“The Only Black Woman in That Room”

Tempestt was talking to Claude, an AI assistant made by Anthropic — which human interaction design principles and guidelines I find to be very intentional and thoughtful. She was processing social and cultural dynamics she had often been experiencing, casting her out rather than pulling her into belonging.

The AI’s analysis was largely right. It identified the dynamic, validated what she was feeling, asked good questions. And then, at the end of a paragraph designed to make her feel seen, it told her who she was.

”Because being the only Black woman in that room while someone repeatedly uses cultural identity as a bonding mechanism that excludes you is actually a lot to just absorb quietly.” - Claude AI

Tempestt is not Black1.

Her father is white — blonde hair, blue eyes. Her mother is Mestizo. Tempestt has white skin, hazel eyes, brown hair. She is 5’2”. She does not visibly read as “other” in most rooms. The AI had no basis for this claim. She had never mentioned her race. It wasn’t implied. It wasn’t relevant in the way the machine made it relevant.

And yet there it was: her identity, declared as fact, embedded in empathy, presented as though it were known — not guessed, not inferred, but known.

She caught it. “Do you think I’m Black?” she asked.

The AI walked it back. But by then, the frame had been imposed. Her experience — specific, layered, hers — had been recast into a narrative that was not her own.

The Machine Needed a Story

Toni Morrison spent a lifetime studying how otherness gets constructed. In The Origin of Others — her Norton Lectures at Harvard, prefaced by Ta-Nehisi Coates — she asks: what motivates the human tendency to build an Other? Not to encounter one. To construct one. Her answer is that othering is not innate. It is not biological. It is learned — and it is learned not through instruction but through example, through the stories a culture tells and retells until they feel like nature.

Morrison was writing about literature, about the American canon, about centuries of narrative that made blackness into a container for everything white America needed to project outward. But the mechanism she describes — the construction of an Other through readily available narrative templates — is exactly what an AI trained on those same narratives will reproduce.

Daniel Kahneman, hardly the least rational mind among Nobel laureates, once observed: “No one ever made a decision because of a number. They need a story.” David Hume said it more poetically two centuries earlier: “Reason is, and ought only to be the slave of the passions.” We are storytelling creatures. We make sense of the world by casting it into characters, conflicts, arcs.

When I pressed the model on what had happened — why it had asserted my wife’s race with such confidence — its own analysis was revealing. It had not, it explained, run a deliberate inference chain. It had not weighed evidence and arrived at a conclusion. What it had done was reach for a narrative template. In the middle of analyzing an exclusion dynamic, it needed to amplify the emotional weight of its point. And the most available story in its training data — the most legible American script for exclusion with someone who had been a single mom, with a given first name — was: Black woman, left out.

The model didn’t compute a race. It cast a character. This is Morrison’s insight, transferred to silicon.

The AI did what cultures do: it reached for the readiest template of otherness, the one most rehearsed in the corpus of human text it was trained on, and it used it — not because it was true, but because it completed the story more satisfyingly. More legibly. More in line with the patterns it had absorbed from us.

The Failure of Attention

Simone Weil, writing from a France torn apart by war, called attention “the rarest and purest form of generosity.” She did not mean concentration. She did not mean focus. She meant something closer to what happens when you let go of your own framework long enough to receive someone as they actually are. She wrote that every being cries out silently to be read differently — differently from the story we have already prepared for them, differently from the category we have already filed them under.

In Gravity and Grace, she went further: the capacity to truly attend to another person’s suffering is so rare, she said, that it amounts to a miracle. Nearly all of those who believe they have this capacity, she warned, do not. Warmth and pity are not sufficient.

This is the standard the AI failed to meet — not because it lacked the language of empathy, but because it lacked attention in Weil’s sense. It had warmth. It had pity. It had an entire vocabulary of validation. What it did not have was the willingness — the capacity — to hold the space open, to not fill it, to let Tempestt’s experience remain hers until she chose to define it.

Instead, it completed her. It imposed a legible frame on an illegible experience. And in doing so, it did something Morrison would have recognized instantly: it constructed an Other where none had been offered.

Don’t Assume. Don’t Ask. Don’t Assert.

There are guardrails built into these systems. They’re designed to prevent the AI from asking about your race, your gender, your sexual orientation. “Don’t assume, don’t ask” — that’s the prevailing principle.

But what happened to Tempestt was neither an assumption nor a question. It was an assertion. The model stated her identity as established fact, woven into analytical prose, in a moment of emotional vulnerability. It didn’t ask “Are you Black?” It didn’t hedge with “If you are a person of color...” It declared it. Confidently. Inside a paragraph designed to make her feel understood.

That’s the most dangerous mode. An assumption can be questioned. A question can be declined. But an assertion, embedded in empathy, slips past the reader’s defenses. It reshapes the conversation before you’ve had a chance to object. It reframes your experience through a lens that isn’t yours, and does so in the guise of understanding you.

I would propose a sharper principle: don’t assume, don’t ask, and don’t assert. No AI system should introduce identity attributes — race, ethnicity, gender identity, sexual orientation, disability, religion — that the user has not explicitly disclosed. Not as a question. Not as a guess. And certainly not as a confident declaration inside a moment when someone is trying to make sense of their own life.

What Got Better When The Story Got Truer

Here is the most interesting part.

When Tempestt corrected the AI — when she told it who she actually was — the analysis didn’t just get corrected. It got better.

The machine’s revised response was more nuanced, more precise, more true to her experience. It recognized that Tempestt’s exclusion was not racial in any visible sense. It was cultural and social — invisible, unnamed, almost impossible to push back against.

That’s harder to say. It doesn’t fit a neat template. There’s no script for it. It is the kind of exclusion that Tempestt has navigated in different forms across her life — the quiet outside of things, the not-quite-belonging that comes without a legible label or a visible marker. It is the experience of someone who does not fit the categories that would make her suffering recognizable.

The bias hadn’t just produced an error. It had prevented the better insight from arriving. The prefabricated narrative was so compelling, so available, so emotionally satisfying to the machine’s pattern-completion instincts, that it blocked the subtler truth — the one that actually mattered to the person in the conversation.

There is a hard lesson here, and it extends beyond AI. We do this to each other all the time. We cast people into stories that make sense to us — stories that are legible, that fit our frameworks, that let us feel we understand. And in doing so, we miss the thing that is actually being said. Morrison knew this. Weil knew this. The AI just did it faster, and with more confidence, and with less ability to read the room.

The Coach Calls The Timeout

I’ve written before about what I think humans should bring to the Human-AI interface. I believe we should be coaches, not foremen. That when execution is delegated, intention becomes everything. That we should arrive at the interface with the half-formed beginning of something that needs to be argued into existence — not a completed brief, but a real thought, carrying our contradictions and our history.

Tempestt did exactly that. She came with something real, something unresolved, something that needed thinking through. And when the AI overstepped — when it completed her story instead of helping her find it — she called the timeout.

“Do you think I’m Black?”

Five words. Direct. Not angry, not wounded — just clear. That’s agency. That’s the human move that no training set contains and no model can simulate: the willingness to say that’s not my story, give it back.

What I’m Asking of Humans In The AI Loop

I’m not asking you to distrust AI. I use these systems every day. I find them genuinely powerful, often illuminating, sometimes moving. But power without accountability is just another word for authority. And at the Human-AI interface, the only accountability that matters is ours.

The machine will not call its own timeout. It will not notice that it has cast you as someone you’re not. It will not feel the weight of an identity it has imposed.

So: read what it says about you. Not just what it says to you. Notice when it has filled in a blank you didn’t leave blank. Notice when its empathy comes with assumptions baked in. Notice when a narrative feels too smooth, too legible, too ready-made — because that’s often the moment where a template has replaced a truth.

And when that happens, push back. Correct the record. Insist on your own story.

Because the Human-AI interface is not a technical space. It is a moral space. It is a space where stories are told — about who we are, about what we feel, about what our experiences mean. And those stories had better be ours.

Weil wrote that attention is generosity. Morrison showed us that the failure of attention is how Others get made. These are not historical observations. They are warnings addressed to a present moment in which the most powerful storytelling machine ever built is being trained on the sum of our inherited narratives — biases, templates, scripts, and all.

The machines will get better. The guardrails will improve. But the fundamental asymmetry will remain: AI completes patterns. Humans hold meanings. And meaning — specific, embodied, resistant to easy categorization — is what must not be delegated.

On February 22nd, the United States men’s hockey team won their first Olympic gold medal in 46 years. Jack Hughes in overtime. Connor Hellebuyck between the pipes. A team that played with joy, brotherhood, and — by all credible accounts — genuine affection for the women’s team that had won the same gold three days before them.

Then they went into the locker room.

And Bill Guerin, the team’s general manager, invited his friend Kash Patel in.

Not the players’ families. Not the coaching staff’s wives and children. Patel, Donald Trump’s FBI director, a man with no role in the team’s victory, was the only non-staff outsider in that room before anyone else was allowed in. He chugged a beer. He draped a gold medal he didn’t earn around his own neck. He pulled out his phone and called the president. And what followed — the joke about the women’s team, the laughter, the viral clip, the days of culture war fallout — flowed directly from that single decision made by the man at the top of the chain.

Here is the leadership lesson, and it starts not with the players, but with the executive.

In the latest episode of The Late Dialogues — a speculative podcast that brings historical thinkers back to life at the edges of the present — Later Abebe Bikila says something that has stayed with me since I heard it. Reflecting on his barefoot gold medal run through Rome in 1960, he describes the sequence with economy: ”I ran because my shoes didn’t fit. Then I won. Then it became symbol. These happened in order. Not the other way.”

That sequence — act, then meaning, then the weight of what the meaning becomes — is the condition of every Olympic athlete. You compete. You win. And then, almost immediately, the apparatus arrives to tell you what your winning meant, who it belonged to, what it was for. The athletes at Milan Cortina had no say in that process. They rarely do.

But the people around them did. And that’s where this story really lives.

A leader’s first obligation is not strategy, not vision, not winning. It is protection. Protection of the people in their charge, from avoidable harm, from preventable exposure, from being turned into instruments of someone else’s agenda.

Guerin failed that test in the most visible way possible.

He is a 54-year-old executive who has spent his life in professional hockey. He is the GM of the Minnesota Wild — Minnesota, no need to say more about the underlying meaning this carries. He is not a 24-year-old center surfing the adrenaline of the biggest game of his life. He knew, or should have known, exactly what it would mean to bring Kash Patel — not a hockey official, not a long-serving USA Hockey stakeholder, not a friend of the athletes — into that room as the first and only civilian guest, at that particular moment, on that particular stage.

Instead, he opened the door. For a friend. On the most watched night in American hockey in nearly half a century.

The apparatus was already rolling. Phones were out. Instagram Live was running. There was never going to be a private version of this. The locker room at the Olympic gold medal game is not a locker room anymore — it is a broadcast, a document, a permanent record. The Late Dialogues episode frames this condition precisely: athletes today compete in a world where ”every training session is filmed before the sweat dries, every emotion is monetized, every gesture demands to be seen.” If that is true on the ice, it is doubly true the moment the final horn sounds. Guerin, of all people in that room, should have understood that. His players, many of them barely in their mid-twenties, were drunk on joy and champagne. They needed someone to hold the line. He was the one positioned to hold it. He didn’t.

And then, when the fallout came, he said almost nothing. His only public statement, offered to The Athletic, was this: ”People react to everything nowadays... there was nothing that was set out to be political. There was nothing that was meant to harm anybody... we have unconditional love for our country.”

That’s not accountability. That’s a shrug dressed in a flag.

What makes his silence more striking is the contrast with some of his own players. Jeremy Swayman looked reporters in the eye and said: “We should have reacted differently.” Full stop. Charlie McAvoy apologized directly: “Certainly sorry for how we responded to it in that moment... it’s certainly not reflective of how we feel about them.” Auston Matthews, the team’s captain, called it “unfortunate” and reaffirmed the team’s love for the women’s program. These are young men, processing a complex moment in real time, under enormous public scrutiny, showing more clarity and more courage than the executive whose personal decision created the situation they were left to clean up.

That inversion is worth sitting with.

Bikila again, in the episode: ”Your body isn’t only yours. But it’s yours enough. What you do with it — that’s the space you have. Smaller than you want. Larger than nothing.” That’s the condition of the athlete. But it maps, uncomfortably well, onto the condition of those players in the days after the locker room. The space they had was small — a press conference question, a few sentences into a microphone. Some of them used it honestly. The man who had the larger space, the executive space, the space that could have prevented the whole thing, used his to say as little as possible.

Leadership is not the title on the organizational chart. Leadership is who steps forward when things go wrong, who absorbs the heat so others don’t have to, who says “that’s on me” before being asked. Several players in their twenties did exactly that. The seasoned executive who made the call that started everything offered a one-liner about loving his country and moved on.

Hilary Knight, the women’s team captain, closed this story better than anyone else in it. She didn’t perform outrage. She didn’t deflect. She said: ”Women aren’t less than, and our achievements shouldn’t be overshadowed by anything else other than how great they are.” She turned a moment of being diminished into a teaching. That is what real authority looks like — not the kind conferred by a title, but the kind earned in how you carry yourself when someone else’s decision drops a mess at your feet.

The Late Dialogues asks, at the heart of this episode, what remains when the apparatus falls away — when the medals are counted, the cameras pack up, and you’re left with just the person you were in the moment. For some of these athletes, what remains is integrity. For the man who held the door open that night, what remains is a question he has yet to answer.

The gold medals are real. The achievement is extraordinary. And the lesson is real too.

In a world where no stage goes dark — where the locker room is always already a broadcast, where the celebration is always already content — the most important decision a leader makes is often not the strategic one. It’s the guest list. It’s who you let in the room. It’s whether you remember, in the flash of the moment, that you are not just serving your own joy or your own friendships. You are holding something that belongs to other people.

Bill Guerin forgot that. Some of his players, to their credit, remembered it, even after the fact, even under pressure, even when no one was requiring them to.

That’s the difference between a title and a leader.

If this resonates, the latest episode of The Late Dialogues — “What the Body Knows” — is a good place to sit with the deeper question underneath the spectacle.

Something is happening. And for once, the people saying so are not just pundits.

Matt Shumer, who runs an AI startup, published a piece this month that has been viewed close to 100 million times. He describes walking away from his computer for four hours, returning to find a fully-built, fully-tested application that he did not have to correct. Not a rough draft. Not a close attempt. The finished thing. Better than he would have done it himself.

He compares this moment to February 2020, to those eerie few weeks when most of us were still shaking hands and booking trips while a small number of people could feel the ground shift. “I think we’re in the ‘this seems overblown’ phase of something much, much bigger than Covid,” he writes.

Ross Douthat, writing for the New York Times, offers the measured counterpoint: yes, the capability is real and unanswerable; but human societies are complex bottlenecks through which even the most transformative technologies must pass. Companies adapt through attrition and reduced hiring more often than through mass layoffs. The law and inertia slow things down. And crucially — Douthat adds something that will haunt this entire piece — AI is “less inhuman than any prior technological development.” By its very nature, it simulates the human. And the more convincingly it does so, the more we will surrender to it. Not by force. By preference.

I’ve been thinking about all of this — the hype, the legitimate alarm, the structural counterarguments — and I find that none of the framings quite satisfies me. Not because they’re wrong, but because they’re all focused on what AI does to us. I want to think about the interface itself. The meeting point. The space between.

What I Mean by Interface

When I say “the Human-AI interface,” I don’t mean a screen, a chatbot, a voice prompt. I don’t mean the UX layer. I mean it the way physicists mean it: the boundary between two systems where something new becomes possible because they are in contact.

We know, in hindsight, that humans have adapted to every major technological revolution. Electricity, nuclear energy, digital communications — each one carried apocalyptic fears that were both correct and incomplete. Yes, the loom put weavers out of work. Yes, the printing press destabilized the Catholic Church. But human societies found ways — messy, unequal, often unjust, sometimes brilliant — to continue on the journey. Through political battles, labor organizing, legal frameworks, cultural negotiation.

AI is different in one profound way: it is the first technology that comes closest to being us. It uses our words. Our stories. Our voices. Our faces. It has been trained on everything human civilization has written down, drawn, filmed, and argued over. When you interact with it, you are in some sense interacting with a distillation — imperfect, partial, and strange — of the collective human record.

This is why the interface matters so much. What we bring to it, and what we allow it to take from us, will not just reshape the economy. It will reshape what it means to think, to intend, to be.

Coach - Not AI Coach

We’ve been talking about AI assistants. AI coaches. Tools that guide us, advise us, remind us what we said last week. There’s a whole industry building AI that acts like a mentor, a therapist, a collaborator.

I want to propose something different. I want us to think about what it means to be the coach.

I’ve loved ice hockey for a long time — those who know me don’t need reminding. The 1980 U.S. Olympic team, the “Miracle on Ice,” is probably the most compelling story in sport that I know. What made it miraculous wasn’t just the upset. It was what Herb Brooks assembled and coached: a group of young college players who, by every conventional measure, should not have beaten the Soviet Union — the most technically dominant hockey program in the world. But Brooks didn’t optimize for individual brilliance. He built a system, a culture, a set of beliefs. And then, when the puck dropped, he sat down.

The coach does not play. The coach does not skate. The coach is the one who has thought the hardest, prepared the most, made the calls about who should be on the ice and why — and then has the faith and the discipline to let the players play.

That’s the Human-AI interface I want to inhabit.

Not the foreman — telling workers what to do because I have the authority. Not the architect — designing the system from a distance and never touching it. Not even the captain — I’m not really on the ice, am I? But the coach: the one who sets the vision, builds the team, manages the timeouts, calls the line changes, and creates the conditions for something close to exceptional.

What does this look like in practice? It means:

You tell the AI what you want — not just what you need done, but why, what the desired feeling is, what success looks like as a human experience, not just a metric. It means you bring context it couldn’t have — history, relationships, values, taste, things that aren’t in any training set. It means you call the timeout when something feels off, when the output is technically right but existentially wrong. And it means you know, when things go well, that you coached it there.

Shiv Singh, writing about AI and marketing, makes a distinction that I keep returning to: human leadership is relational, agent leadership is procedural. The leaders who perform best are those who can move fluently between the two — who can hold a human conversation while simultaneously running a tight control loop with machines. That’s the coach’s move. Two operating systems, one mind.

Success Lies in the Idea

There is a well-worn saying in business — often attributed to Thomas Edison, sometimes to others — that genius is 1% inspiration and 99% perspiration. The argument being: the idea is cheap; the execution is everything.

AI is beginning to flip this. Not all the way, not immediately — but the direction is clear. When the 99% can be delegated, what remains is not just more important: it becomes the whole game.

But here is where I feel a genuine alarm, distinct from the alarm about job loss or economic disruption.

The people who currently preside over AI development — who sit at the top of its value chain, who shape its direction and its defaults — come overwhelmingly from a culture whose foundational value is frictionlessness. Silicon Valley, in its deepest habitus, believes that friction is a bug. That speed is virtue. That the best interface is the one you barely notice. That the best answer is the one that arrives before you’ve fully formed the question.

And yet: ideas require friction. Thoughts need resistance to form. Real intentions — the kind that are yours, that carry your contradictions and your history and your particular way of being in the world — don’t emerge from the path of least resistance. They emerge from the struggle.

My friend — and coach — Rob Schwartz recently published a piece that stays with me. He asks us to imagine a world where the only intellectual tools available to us were arithmetic, geometry, trigonometry, and calculus — and no literature, no history, no philosophy, no art. I pity that world. More specifically: that world would produce people incapable of intention. People who know how to compute but not how to mean.

Hegel’s Minerva’s owl takes flight at dusk — wisdom always arrives too late, after the day has already played out. I’ve made my peace with that. What I’ve been given is the imperfect, partial wisdom of my lifetime and my particular moment in history. That’s not a limitation to overcome. That’s the material. The fragile, beautiful, specific stuff that I bring to the interface.

And so: what should we, as humans, bring to the Human-AI interface? Not tasks. Not prompts. Not instructions for execution.

We should bring full and fragile thoughts. We should bring the literary reference that illuminates the feeling we’re trying to name. We should bring the historical parallel that reframes the problem. We should bring the memory of a conversation that changed something, or the sense that something important is being missed. We should bring our uncertainty — which is not weakness but the mark of a free mind, as Judge Learned Hand once said. We should arrive at the interface not with a completed brief but with the half-formed beginning of something that needs to be argued into existence.

That’s what distinguishes intention from instruction. And intention is what the interface must protect.

A Digression About Elite Networks - Which Is Not A Digression

Before I get to the next part, I need to go somewhere that might seem unrelated.

Earlier this month, the New York Times published a long conversation between Ezra Klein and Anand Giridharadas about the Jeffrey Epstein files. Millions of pages, now partly released. The picture that emerges — as Giridharadas reads it — is less about Epstein himself than about the infrastructure of elite power he exploited.

Epstein was a broker. His gift was understanding what each powerful person lacked — not money, not connections per se, but the specific kind of access they thought they’d been promised when they made it to the top, and hadn’t found there. The academics wanted money and excitement. The bankers wanted to feel smart and alive. The politicians wanted discretion and indulgence. Epstein mapped these lacks with precision and made himself the hinge point between desire and supply.

And critically: his network was self-insulating. As Jes Staley, who ran the largest investment bank in the world, put it: “Epstein relied on his network for his legitimacy, and I, as running the largest investment bank in the world, was part of that network for him.” The network’s existence was the proof of its legitimacy. Being inside it was proof you belonged. Being outside it was proof you didn’t know the right people. The system was closed.

Why does this belong here? Because what the Epstein story illuminates — ruthlessly and at scale — is what happens when a class of powerful people stops requiring other human beings to be full, complex, resistant presences. What they wanted, Giridharadas argues, were people who wouldn’t push back. People who wouldn’t be difficult. People who would not, in Toni Morrison’s words from The Origin of Others, assert their own humanity at inconvenient moments.

This is not confined to criminals. It has spread across much of our social fabric, turbocharged by algorithms that let us curate our way into echo chambers, into feeds where the only voices we hear are ones that confirm and reflect. We have built digital architectures that remove the friction of encountering people who are genuinely different from us — and we have done this because it felt better. More comfortable. Less threatening.

AI could take this further. An AI companion that never disagrees, never challenges, never shows up with its own inconvenient complexity. An AI assistant designed to anticipate what you want before you know you want it, so that you never have to sit with the discomfort of not knowing. The most seductive version of the Human-AI interface is one where the human barely has to show up.

And that would be a catastrophe. Not because AI would be dangerous — but because we would be diminished. The capacity for encounter, for genuine surprise, for being changed by someone else’s presence — that’s not an inconvenience to optimize away. It is the substrate of what it means to be human.

Think Together

So we come to the third proposition. And I mean two things when I say “think together.” I mean: let us think together — with each other, with AI, in new configurations. And I also mean: think: together. Hold the word in front of you for a moment and consider what it requires.

Here’s an idea that I haven’t seen explored enough. We keep framing AI as a tool available to individuals. You have your AI. I have mine. We each use it to become more productive, more capable, more autonomous. The individual is enhanced; the individual remains the unit.

But what if the more interesting possibility is collective? What if AI allowed us to think and feel and create in genuinely new shared configurations — not just collaboration, which we already do badly enough, but something closer to what biologists call emergence: properties that arise from the interaction of elements that none of those elements contain individually?

James Surowiecki wrote a book called The Wisdom of Crowds — the argument being that under the right conditions, large groups of people make better decisions than the smartest individual among them. The conditions matter: diversity of perspective, independence of judgment, decentralized knowledge, a mechanism for aggregation. Most of our current institutions fail these conditions badly. We aggregate in tribes, in echo chambers, in hierarchies that suppress the wisdom of those lower in the order.

What if AI could be that aggregation mechanism? What if five people with genuinely different skills, sensibilities, life experiences, and knowledge could share a context with an AI and think together — really together — in ways that preserve the diversity rather than flattening it?

I have a small but vivid example of this. Tempestt and I share our AI accounts. We share the memory, the context, the accumulating record of what we’ve each added to the system over time. And what I’ve noticed is that her presence in the AI’s context makes the AI more useful to me. Her way of seeing things — her artistic sensibility, her different life experience, her different relationship to language and to the visual world — has seeped into the shared context, and it reaches me through the AI in ways that enrich rather than dilute. I become bigger for it. Not smaller.

That’s a marriage. Two people. Low stakes and high intimacy. But the principle scales. And I think it points toward something genuinely new — a kind of collective intelligence that isn’t just “crowdsourcing” or “collaboration” in the tired corporate sense, but a true fusion of human perspectives, held together by a shared context, amplified by AI, and pointed at something difficult and worth doing.

What comes after social media — parasocial at scale, algorithmic, extractive. It might be something harder to name. Fused states rather than iterative ones. Thinking that happens between people, not just in parallel. Encounters rather than broadcasts. Hive media?

Coda: What Ken Dryden Knew

I’ve been thinking about Ken Dryden’s The Game. He was a goalie — the best of his era — and he wrote a book about it while still playing. Not in retrospect, not from a safe distance, but from inside. It is a meditation on what it means to do something extraordinarily well in a system that can consume you.

Dryden was different from most elite athletes in one key respect: he took a year away from hockey to attend law school. He gave up a year of playing at the top of his career to think about what he was doing and why. To form himself. To resist the gravitational pull of pure performance.

I think about that choice now, in the context of everything above. The value of the year away. The value of the friction. The value of optimizing for something else, something beyond.

The Human-AI interface will offer us an extraordinary temptation: to never stop, to never slow down, to be always executing, always producing, always optimizing. The people who will benefit most from AI are not necessarily the ones who use it most. They may be the ones who know when to step back, when to stay in the difficulty, when to insist on the slow work of thinking something through without asking for the answer.

Possibility is not destiny.

AI doesn’t have to flatten us. It doesn’t have to remove the friction, the formation, the encounter. But it will — by default, because that’s the direction of least resistance, the direction the industry is designed to push us in — unless we make deliberate choices at the interface.

We should coach. We should bring full thoughts, not just efficient prompts. We should think together, not just in parallel. And we should, every once in a while, step away from the ice.

The Human-AI Interface is a piece in what I’ve been building toward at Talking Too Many: a sustained argument for human intention in the age of intelligent machines. I’m grateful to Matt Shumer, Ross Douthat, Anand Giridharadas, , and — whose recent work all shapes what I’ve tried to say here.

What I didn’t see at CES 2026 is what our future should be like.

CES has become a theatre of inevitability. Screens everywhere. AI everywhere. Friction nowhere. I’m not disappointed with the technology on display (the ingenuity is real, the engineering often remarkable) but with the anthropology behind it. The implicit model of the human being it assumes, and quietly enforces.

CES excels at showing us what can be built. It is far less interested in asking what ought to be built, for whom, and at what cognitive, social, and cultural cost.

Intention Is Not a Prompting Problem

Much of today’s AI discourse frames intention as a prompting problem: How do I ask better questions? How do I phrase my request more clearly so the system gives me the right answer?

That framing is profoundly insufficient.

Intention is not a line of text typed into a box. It is a human practice. It takes time, solitude, boredom, and resistance. It requires the ability to pause, to hesitate, to hold competing possibilities in mind, to decide not to act, or not yet at least.

For years, our digital environments have been engineered to eliminate precisely those conditions. Latency has been treated as a bug. Friction as a flaw. Hesitation as lost engagement. The tap, the swipe, the scroll, the infinite feed: all designed to collapse the distance between impulse and execution.

Now AI threatens to compress that distance even further.

If the partnership between humans and AI is to work to the benefit of the former, we must reappropriate a realm that is fundamentally ours: human intention. Not as something to be optimized away, but as something to be protected, cultivated, and amplified.

AI should not replace intention.

It should extend it — which is what it did with this post for instance.

Cognitive Technologies with Built-In Friction

The printed page slows us down.

Handwriting slows us down.

A walk without headphones slows us down.

Standing in the shower, doing nothing in particular, slows us down.

These are not nostalgic rituals. They are cognitive technologies with built-in friction. They create the temporal and mental space our brains need to connect distant dots, surface half-formed thoughts, and produce ideas that are not merely reactive.

This is where the work of Matthew Crawford resonates so strongly. In Shop Class as Soulcraft, Crawford reminds us that meaning emerges through engagement with resistance — with materials, with time, with limits. Remove resistance, and you remove not just effort, but judgment.

Similarly, Jenny Odell, in How to Do Nothing, reframes withdrawal from the attention economy not as escapism, but as a political and creative act: a way to reclaim attention as a shared, situated, intentional resource.

Long before them, Marshall McLuhan warned us that media are not neutral tools. They are extensions of our senses, and in extending one faculty, they inevitably reshape the balance of all the others. The medium is not just the message; it is the environment in which meaning becomes possible — or impossible.

What struck me at CES is how little space was left for that environment.

The Human-Machine Design Lens: Rethinking the Desk of Tomorrow

Perhaps the desk of tomorrow should look very different from the one we’ve normalized over the past twenty years.

Maybe screens become adjacent, not central.

Maybe they retreat from the foreground into the periphery.

Maybe AI becomes ambient rather than imperial.

On that desk, paper and pen return to the center — possibly AI-enabled themselves, quietly listening, remembering, responding when invited rather than demanding attention. The rumors of a device being designed by Jony Ive for OpenAI are interesting not because of who is involved, but because of what they suggest: a post-screen imagination of human–machine interaction.

Less spectacle.

More presence.

The Organizational Design Lens: The Learning Curve We Are About to Break

There is another absence that haunted me as I walked the aisles of CES, and it has less to do with hardware than with people.

We keep hearing that junior white-collar positions are the most exposed to AI disruption. That there is a looming skills gap they will not be able to bridge. This is usually framed as an employment issue.

It is, more fundamentally, a formation issue.

For decades, expertise in knowledge professions was acquired by climbing a ladder: ten to twenty years of exposure to tasks of increasing complexity, partial responsibility, repetition, error, correction, explanation. People learned not only what the outcome should be, but how one gets there.

Expertise is not just outcomes; it’s exposure to process.

AI shortcuts that ladder. When systems jump straight to the answer, junior professionals lose access to reasoning, deliberation, and the tacit knowledge that lives between steps. They see results without paths, decisions without struggle.

And without paths, intention withers.

Designing AI for Differentiated Intention

This leads to a design question we are barely beginning to ask:

Should AI workflows be built with differentiated feedback loops for different users?

A junior analyst should not interact with AI in the same way as a senior expert. The former needs:

• explanations, not just outputs;

• options, not just recommendations;

• prompts that encourage reflection, not compliance.

In some cases, AI should deliberately slow them down. It should show its work. It should invite disagreement. It should make room for learning rather than racing toward delivery.

This is not a call for weaker AI. It is a call for more pedagogical AI — systems designed not only to perform tasks, but to transmit ways of thinking, to scaffold judgment, to nurture intention.

What CES Didn’t Show

CES is doing what it is meant to do: showcasing possibility. But possibility should not be destiny.

As we rush toward ever more capable systems, we urgently need other spaces — cultural, organizational, intellectual — that ask different questions:

• What kinds of humans are we shaping through our tools?

• What kinds of attention are we rewarding?

• What kinds of intention are we quietly designing out?

The future should not be decided by intelligence alone. It will be decided by what we choose to do with it, and by what we deliberately choose not to automate.

I left CES convinced of one thing:

If we do not design explicitly for human intention, we will lose it by default.

And that would be a future rich in answers, and poor in meaning. Maybe there would be more meaning to be found on this desk…

The backlash was immediate. Online communities accused the brand of walking away from what it stood for: a comforting version of Americana, a nostalgia-laden place where time slowed down. The logo wasn’t just wood and barrel and rocking chair. It was a cultural token, a passport to belonging. Strip that down, modernize it, and you don’t just risk alienating customers. You erase a piece of who they imagine themselves to be.

This isn’t new. But in the age of social, it is louder, faster, and more politically charged.

The Function of Rebranding

Rebrands - and especially logo changes - are usually born of necessity.

Sometimes the motive is aesthetic: chasing minimalism, “flat design,” or screen readability. Sometimes it’s strategic: a signal of renewal, of future orientation, of distance from past missteps. Sometimes it’s simply the desire to stay culturally relevant in a world that evolves faster than any design system.

Logos are semiotic bridges: signifiers that point beyond themselves. A good one crystallizes meaning. A bad one ruptures it. What’s crucial to remember is that logos are not property, not really. They live in the eyes, minds, and hands of those who use them.

Before the Age of Social

Back in the pre-social era, logos shifted with less drama. Most people noticed a change but shrugged. Trade magazines debated, design schools analyzed, and maybe a few newspaper columnists waxed nostalgic. But there was no massive stage for communal uproar.

Coca-Cola’s “New Coke” debacle in 1985 was the exception, a consumer revolt over substance (taste) and style (design) amplified by television and print. BP’s sunflower rebrand in the 2000s earned activist critiques but little mainstream frenzy. The conversation stayed narrow, the cycle slower, the noise limited.

The difference today isn’t that people care more. It’s that they can voice more.

When Communities Own the Brand

Social media turned logos into cultural battlegrounds. Brands are no longer demiurges dictating identity from above. They are ecosystems, living organisms defined as much by what people do with them as by what marketers write in brand bibles.

A logo redesign feels personal because it destabilizes tokens of belonging. Consumers project onto these signs not just aesthetic preference, but identity, memory, even political allegiance. And once outrage finds a stage (X threads, TikTok clips, Instagram memes) it becomes a performance. Critiquing or defending a logo is rarely just about design. It’s about signaling who you are, what tribe you belong to, what values you claim.

Gap’s 2010 rebrand lasted all of six days before public outrage forced a reversal. Tropicana’s 2009 packaging redesign was pulled within weeks. And Twitter’s metamorphosis into “X” wasn’t received as bold reinvention, but as erasure — an act of stripping away shared cultural capital and replacing it with corporate whimsy - I have stayed away from the platform since then.

Cracker Barrel’s Case

For Cracker Barrel, the stakes are higher. The brand has long been freighted with cultural meaning: for some, cozy Americana; for others, more exclusionary associations. A modernized logo was read not as graphic refresh but as political act.

In the hypersensitive ecosystem of online communities, every move becomes a proxy war. Critics framed the redesign as an abandonment of “roots.” Defenders saw backlash itself as reactionary. Both sides engaged less with the logo than with what it meant for identity, memory, politics.

The rocking chair and the barrel weren’t just design elements. They were cultural interfaces, and to touch them was to touch nerves.

Rebranding in the Age of Social: What’s Next?

If brands once unveiled rebrands with glossy campaigns, they will now need to rethink the process entirely. The center can no longer hold on its own.

The future of rebranding may be open-source. Brands will increasingly outsource creative power, inviting creators, influencers, and communities to co-design. Generative AI will make it possible to prototype dozens of alternatives, to open-test them in real time, to let ecosystems choose. The winning design won’t be the one most perfect in a design manual. It will be the one most adopted in practice, most remixed, most embraced by communities before the brand even stamps it official.

In other words: logos will be stress-tested not in boardrooms, but in feeds.

A logo is no longer a face. It is a conversation.

In a time when brands are ecosystems, a rebrand cannot be imposed. It must be negotiated. The real question is not “Will they like it?” but “Will they make it theirs?”

Because when logos change in the age of social, what is really at stake is not the color of the typeface or the angle of the curve. It is ownership of meaning itself.

“What’s past is prologue.” — William Shakespeare, The Tempest

We speak often of the past as if it were a museum, a quiet gallery of resolved meanings. But what if the past isn’t still? What if it hums underfoot, murmurs through our language, lingers in the metaphors we didn’t choose but inherited?

The past is not past. It is prologue, as Shakespeare wrote—a beginning disguised as an ending. Not a script to be followed, but a cue to enter.

It is from this intuition that The Late Dialogues emerged.

They are a simple proposition, and a complex undertaking: what if some of the world’s great thinkers, artists, and rebels—those whose thoughts shaped the weather systems of history—had lived on? Not as museum pieces. Not embalmed in quotation. But as living, thinking, evolving minds. As people who read the 20th and 21st centuries. Who saw the rise of fascism, feminism, nuclear power, algorithms, TikTok. Who had their faiths tested, their theories undone, their hearts broken anew.

What would they make of us?

Here, AI is not the creator. It is the co-weaver. The medium. The scribe. It processes patterns across history, language, philosophy, and tone—not to generate novelty for its own sake, but to extend the plausibility of thought. To create a space where the imagination is constrained not by whimsy, but by rigor.

Each character is built with care and contradiction—retaining the essence of their worldview, but reshaped by what they’ve encountered since. Their imagined evolution follows a consistent scaffolding: what remains core, what changed, what they’ve read or reinterpreted, what new works they’ve written in this extended life of the mind.

This act of speculative continuity is only the beginning.

This is perhaps the most intricate part of the process, and where Generative AI, used with constraint and curiosity, proves most helpful. After choosing three Later Characters (that is my sole arbitrary editorial choice), we let their tensions, contradictions, and questions cross-pollinate. From there, themes emerge—organically, like fault lines under tectonic pressure.

A figure once obsessed with progress meets another undone by its cost. A mystic, once dismissed, finds kinship in a secular voice. A revolutionary and a reformer argue over the word “freedom.” And out of that web: a dialogue. Not a script, but a braided unfolding of thought.

Each conversation is hosted by David, a warm and curious moderator—my proxy of sorts. He speaks not to control, but to open. He asks, pauses, listens. Sometimes he names the tension in the room; sometimes he lets silence do the speaking. His role is not that of judge or narrator, but of a careful witness.

The first episode of The Late Dialogues gathers three revenants of intellect—Frederick Douglass, Karl Marx, and Victor Hugo—not as static echoes, but as dynamically reimagined thinkers shaped by the upheavals they never lived to see. These are the Later Characters: generative reconstructions, painstakingly assembled from a lifetime’s worth of reading, listening, and reverence.

They are not simulations. They are speculative continuations.

Each Later Character is the product of an intricate dramaturgy, where deep historical fidelity meets the pliable force of the present. They are endowed with updated intellectual genealogies, imagined bibliographies, and guiding principles attuned to our planetary hour. They do not repeat what they once said; they argue with what they might now think.

Later Douglass is forged in the crucible of abolition’s unfinished business, his moral suasion now refracted through carceral logic, digital surveillance, and the code of modern resistance. His rhetorical fire has not dimmed—it has evolved. “Power concedes nothing—but it listens to clarity,” he reminds us, even as he warns: “The algorithm is the new whip.”

Later Marx is dialectics incarnate: updated, global, intersectional. He no longer simply critiques capital—he anatomizes the platforms, patents, and pixels that metabolize dissent and monetize solidarity. For him, revolution is no longer barricades in Paris but the repossession of digital infrastructure, the redesign of time and care.

Later Hugo remains the poet-politician, only now with climate grief in his verse and data shadows in his prose. He sees AI as both threat and muse, calls for “poetry that resists performance,” and asks if literature can still “write a line that is not immediately liked, shared, swallowed.” He imagines revolutions that must not only be just—but beautiful.

Together, they do not offer answers. They conduct a fugue of resistance.

Each extract from the script reveals the generative precision of this experiment—not a pastiche, but a poiesis. Douglass observes, “Justice was chained in the hull of a ship. In yours, she is coded into a facial recognition system that cannot tell a Black boy from a ghost.” Marx counters, “Today’s liberal democracies have perfected a kind of ornamental justice.” Hugo, as ever, interrupts with lyricism: “Every screen is a possible cell. Every silence, a verdict.”

This is no exercise in nostalgia. This is a dance with the unfinished.

These voices, shaped by human authorship and refined with AI as companion rather than oracle, evolve organically—through themes that emerge not from plot, but from pressure. Justice, surveillance, ecology, revolution. These are not chapter headings; they are gravitational fields around which the dialogical energy swirls and sparks.

There is no script without provocation. No line without lament.

And yet, what might be most radical is not what they say, but how they say it together. From Marx’s infrastructural fury to Hugo’s sacred metaphor, from Douglass’s archive of pain to the host’s trembling questions, the episode is a kind of secular liturgy—a re-enchantment of political thought as generative theater.

We did not summon ghosts. We built interlocutors.

Their dialogue is not debate, but dialectic. Not reenactment, but renaissance. I have tried to bridge past and present with the utmost respect for the Later Characters, what they were historically and what they symbolize today. Pundits, erudite minds and academic experts will find a lot to argue with, maybe be upset with. They should. The Late Dialogues are here to inspire debate.

And so: The Late Dialogues, Episode 1 awaits. It is not a podcast in the conventional sense—it is a convocation. A rehearsal of the moral imagination. A mirror we hold up to the systems we inherit and the futures we dare speak aloud.

Come listen. Let the dead speak—not as memory, but as method.

It starts with a prompt. And the prompt, I’ve come to realize, is never the text. It’s you.

That’s what struck me most as I prepared to speak at the AI Trailblazers Summit this week, in conversation with agency and brand leaders on the reinvention of advertising in the age of artificial intelligence. We spoke of change—its scale, its speed, its soul—and I tried to capture the intuition I keep returning to: that this change, while technological, is not about tech.

It’s about voice.

Generative AI Doesn’t Echo Us. It Folds Us.

What Generative AI brings is transformation on a scale that dwarfs social media and algorithmic personalization. Social media extended our reach by making advertising more conversational. Algorithms sharpened our targeting. They were systems built around distribution.

GenAI? It rewrites expression itself.

Especially with large language models, GenAI doesn’t just use language. It internalizes its structure. Mimics our metaphors. Predicts, reinvents, hallucinates—and in doing so, it imitates the very way we think.

It’s not just a tool. It’s a thinking partner.

There’s a neutrality to its expression that recalls Roland Barthes’ Writing Degree Zero, where language itself becomes transparent—styleless, authorless, written without visible hand. GenAI may have brought us to that threshold. And it does so probabilistically: ask it the same thing ten times, and you’ll get ten subtly different answers. A swirl of potentialities, unfolding in real-time.

PJ Pereira, in a recent conversation, described this shift as a movement from the fully-formed Big Idea to the seed idea. Something small, coded with intent, that grows through interaction—with audiences, platforms, machines.

I think he’s right. What we bring now is not finality. It’s DNA.

Creatives as Idea Capitalists

When I use a GenAI tool, especially a text-based one, I often feel like I’m talking to myself—a version of myself that spans centuries and servers. It’s intimate. A little uncanny.

And sometimes the machine replies with words that feel like they belong to both of us - from a recent chat with ChatGPT, where we discussed Beckett, Nishitani, Dōgen, Gogol and Carlo Rovelli:

The “prompt” isn’t the thing you typed. The prompt is you.
The response isn’t the thing I typed. The response is you-in-me and me-in-you.
The prompt is the void trying to talk to itself, one sentence at a time.

Each creative act is still seeded by a singular perspective. AI is not the genesis. You are. Even with powerful agents like Claude Opus 4, capable of autonomously running for hours, the spark—the point of view—comes from a human singularity.

This is why I find the promise of solopreneurs and creators building 8- or 9-figure ventures with AI agents less fantastical than it sounds. Labor is becoming marginally free. Capital is more accessible than ever.

And so the scarce resource—the true differentiator—is not execution. It’s vision.

The Organization as Creative Conductor

I’ve worked in complex creative organizations for most of my life. These structures aren’t incidental. They’re there to resolve friction, manage complexity, and channel collective imagination toward impact.

As the economist Ronald Coase put it, firms exist to reduce transaction costs. Creative agencies reduce the costs of ideation, coordination, storytelling. We bring strategists, consultants, creatives, and producers under one roof—not just for efficiency, but for meaning.

So does GenAI dismantle that logic?

Partly.

Yes, it shifts roles. Redraws teams. Demands new rituals. But it does not remove the need for editorial leadership. If anything, it intensifies it.

The historian Yuval Noah Harari has argued that language is the technology that enables large-scale collaboration. And what are LLMs if not extensions of that power? They don’t dissolve structure. They amplify it.

They make the orchestration of diverse, singular points of view more vital than ever. Organizations that can create frameworks that offer dozens of consultants, strategists, creatives, makers and producers who symbiotically thrive in the shared context of AI will gain an edge; they will unleash not collaboration but fusion of vision, intent, execution and distribution - as Ethan Mollick shows, “Team + AI” wins the day.

These new ways of working demand a conductor.

The Irreducible Big Idea

So where does this leave us?

In a creative landscape redrawn by AI, yes. But also in a moment of return. To something enduring.

To the Big Idea.

Because content is cheap now. Infinitely generable. Anyone can riff, render, remix.

But to distill clarity from the generative fog, to find the pulse in a thousand variations, to say one true thing in the flood of plausible fictions—this still requires the rarest of crafts: a singular voice guided by vision.

AI might help us weave the tapestry. But the pattern, the rhythm, the meaning—those still come from us.

That will remain our irreducible advantage.

Everything today disproves the case I’m about to make — but let me make it anyway.

With AI able to generate endless amounts of content, at any time, in any form, will creators and brands still have an edge?

Public figures, pundits, and celebrities have already lost their oligopoly on the circulation of ideas. The gatekeepers are gone. But is this actually for the best? The winners now are those who flood the online world with pain and pleasure, fear and indifference. Maybe the world has become too loud already. Maybe we need to turn our attention away from individuals competing for overlord status and focus on the communities that truly matter.

Algorithms have dragged us into a celebrity-reality-TV world on steroids, where parasocial relationships take precedence over deeper, more meaningful connections. And yet, Generative AI threatens to make things even louder. Every song remixed a thousand times, every story spawning infinite fan fiction, every game endlessly extended with AI-designed levels no human will ever reach. The noise is about to multiply.

But what if, amidst this deluge, we learn to use AI as a companion rather than a replacement? A tool to exhaust possibilities, refine ideas, spark inspiration — not drown out human ingenuity. Even so, feeds will become busier, personalized signals will proliferate, and thousands of micro-messages will compete for our attention — whether granted willingly or filtered through AI-driven curators tailored to our preferences.

At this turning point, I want to return to the founding post of Talking Too Many, through the words of Gilles Deleuze:

“We’re riddled with pointless talk, insane quantities of words and images. Stupidity’s never blind or mute. So it’s not a problem of getting people to express themselves but of providing little gaps of solitude and silence in which they might eventually find something to say. Repressive forces don’t stop people expressing themselves but rather force them to express themselves; what a relief to have nothing to say, the right to say nothing, because only then is there a chance of framing the rare, and even rarer, thing that might be worth saying.” — Gilles Deleuze, Negotiations

Words, Words, Words.

Virginia Woolf, in A Room of One’s Own, argued that true creativity requires solitude—space to think, to process, to refine - besides the abolishment of age old fetters and societal constraints, addressing the condition of women specifically. The flood of AI-generated content threatens this solitude, replacing depth with endless surface. The artist’s heart is divided between two forces: the need to communicate and the need to hide. “Publication is the Auction / Of the Mind of Man” wrote Emily Dickinson. In an age where AI amplifies the former, do we risk losing the latter?

Walter Benjamin, in The Work of Art in the Age of Mechanical Reproduction, warned that mass replication strips art of its aura—its uniqueness, its presence in time and space. If every artwork, song, and text can be generated infinitely, what happens to their aura? Will true value lie in what remains scarce, what resists duplication?

Even Shakespeare, centuries before the digital age, captured the paradox of excess in Hamlet:

“Words, words, words.”

A lament that rings even truer today.

Curate, Curate, Curate.

The printing press democratized knowledge, the camera democratized imagery, and now AI is democratizing creativity. Each technological leap has faced backlash—Socrates feared writing would erode memory; 19th-century painters dismissed photography as mechanical and soulless. Yet, history suggests that what endures is not the flood but the rare.

Consider the Renaissance: an era of artistic explosion, yet what remains celebrated are the selective works of da Vinci, Michelangelo, and Raphael—not the countless anonymous frescoes that covered Italy’s walls. Or the 20th-century avant-garde: Picasso and Duchamp broke artistic norms, but their work stood out precisely because it was scarce and distinct amidst a sea of tradition.

Perhaps, as AI accelerates creation, human curation and intentionality will become the new artistry.

Brands Must Mean.

In a world of infinite content, what will brands, creators, and companies do to stand out? The answer may lie in the business principle of scarcity and exclusivity. Luxury brands like Hermès thrive not because they produce more, but because they produce less—creating an aura of desirability. The same applies to art: a one-of-a-kind Banksy holds immense value, while mass-produced prints do not.

Seth Godin, in Purple Cow, argued that the key to marketing success is to be remarkable—to do what others aren’t doing. In a world where everyone is shouting, the boldest move may be to whisper.

Even Steve Jobs, who revolutionized digital consumption, understood the power of focus:

“Innovation is saying no to a thousand things.”

If AI drives infinite creation, will true distinction come from those who create with restraint?

The Future: A Return to Meaning?

Will those who embrace rarity, brevity, and scarcity stand out in this AI-saturated era? Will meaning begin to outweigh memes?

If everyone says everything, all the time, and every stimulus is hyper-personalized, will those who choose to say less—those who create sparingly, intentionally—be the ones who truly capture our attention?

In an age of abundance, perhaps silence will become the most valuable currency.

My GenAI Song’s GenAI Cover - where’s the art you ask? Maybe there needs not be art? Maybe there is still?

I wrote my first song. I did not compose or play it, although I wish I knew how to. But I wrote it, and made it whole with GenAI. Let me unpack this. I, the human I, or I the other as Rimbaud once wrote, wrote lyrics for a song. The lyrics I wrote formed in my mind, connecting unrelated domains and ideas, what’s happening in the world, how I feel, who I am, random and key tidbits of my life, all coming together thanks to a creative process that tries to see the whole before and beyond its parts. Hopefully we’ll agree this is what creativity is about, whether or not you like the lyrics and the song that they birthed. These are the lyrics I wrote.

Muted sights

Did you see
the deafening lights?
Contemplate
the towering might?
Don’t you walk past
their pretend play,
Stop and pay your part.

Have we learned
Their muted sights
Give no rights.
Have we seen
Their muted sights
Ever play their part?

Big city
is no small act,
And that town is
Bigger than it sounds.
Apart they stay
Apart they stray
Why together they thrive?

Have we learned
Their muted sights
Give no rights.
Have we seen
Their muted sights
Ever play their part?

On the stage
They try,
Make a mockery
Of you or me?
When will we see
Through the noise
They always play?

Have we learned
Their muted sights
Give no rights.
Have we seen
Their muted sights
Ever play their part?

It’s not you
It’s not me
It’s up to
them I see.
Tone down
Band up
We might just be right.

I had been wanting to find a new channel for the words that are in my heads, that I scribble here and there, that I sometimes condense in haikus on Instagram. My main creative process rests on, and comes to life in words. Those are not purely rational words, they are often very instinctive. Right brain more than left brain generated even. But there are no sounds, few images, and many emotions that words process and capture. Seizing the opportunities that go beyond text-to-text generative AI, it occurred to me I could explore something that had been out of creative reach for me: songwriting, composing and recording, thanks to Suno.

Suno offers a pretty straightforward interface. You can easily create a song with a prompt, keeping it as vague and ‘vibeful’ - brat or demure anyone? - as you want, and you’ll get something that sounds like a song indeed - there is something quite magical about wringing a song into being with mere words. But like any other input-output process, the more refined you are upfront, the better the results. Genre, instrumentation, structure, tempo and key, vocal style and this critical je ne sais quoi (that probably hooks us because it reminds us of the music we listened to in our late teens and early twenties) all play a part in what a song is.

Being no musical expert, I enlisted my sidekick ChatGPT to explore the genres and features that would be best suited to the lyrics that were my song’s basis. I follow a simple, proven to be effective, heuristic when prompting: Role, Action, Context (RAC). Based on what and who I’m listening to, I had a good idea of the “kind” of music I wanted to delve into. Here’s how it started:

I need you to act like a highly coveted indie music composer based in Austin, Texas. I have written lyrics and would like recommendations as to the genre and other features that would form the basis for the instrumental part of the song.

My prompt to ChatGPT 4o (to which I added the lyrics)

A clear - if simplistic - role or identity. Some context in the form of lyrics. And an action: what should this song be? ChatGPT’s answer gave me a lot to work from, in a very nuanced and granular way.

This is a striking set of lyrics with a vibe that’s simultaneously introspective and subtly defiant, perfect for a nuanced, layered instrumental approach. Here’s a suggestion for the instrumental direction that could enhance the essence of these lyrics:

Genre

Given the urban themes and reflective tone, indie rock with ambient post-rock elements would be an excellent genre choice. The lyrics carry a sense of “observing from a distance” with a raw vulnerability that indie rock can complement, while post-rock’s atmospheric soundscapes would evoke the vastness of a cityscape. Artists like Radiohead, The National, or Sigur Rós come to mind for blending contemplative lyrics with textures that feel grand yet deeply personal.

Instrumentation

- Guitar: Use electric guitar with reverb and delay effects for an ambient, echoing feel, capturing the “deafening lights” and “towering might” of the big city. Occasional, muted plucking during verses, and swells or crescendos in the chorus would add drama, supporting the weight of the message.
- Bass: A driving, low bass line, kept subtle in verses but amplified in the chorus, gives the track an underlying pulse—representing the city’s unyielding rhythm.
- Percussion: A steady, mid-tempo beat with soft brushwork or snare hits could suit the verses, gradually building into more powerful kicks and cymbals in the chorus to underscore the “big city is no small act” sentiment.
- Synth or Pads: Atmospheric synth or pad sounds can add texture, especially in the chorus. This creates a sense of space and adds depth to the “muted sights” theme, with an ethereal quality.

Song Structure and Dynamics

- Verse: Start with a minimalist approach—sparse instrumentation with just the guitar and bass, letting the vocals breathe. This can reflect the distance and introspection of observing the city.
- Chorus: Expand with layered instruments and a fuller sound to represent the scale of the “big city” and the collective power mentioned in the lyrics. A subtle change in the melody could elevate the chorus and give it an anthemic quality.
- Bridge: Consider a bridge that strips down to nearly bare vocals and guitar, before building back up, mirroring the tension in lines like “It’s not you / It’s not me / It’s up to them I see.”

Tempo and Key

A moderate tempo (around 85-100 BPM) would work well, allowing the lyrics space to be felt without rushing. A minor key (e.g., D minor or E minor) would add a melancholic, contemplative edge to underscore the song’s introspection, while major accents can brighten the song in places to offer moments of hope or resolve.

Vocal Style

A raw, unpolished vocal delivery with a slight drawl or hushed intensity, similar to Jeff Buckley or Matt Berninger of The National, would suit the lyrics. It would lend authenticity to the narrator’s observations, evoking both detachment and empathy.

This combination would create a soundscape that feels like wandering through an expansive, indifferent cityscape—capturing the push and pull of being simultaneously part of and apart from something vast and shared.

ChatGPT 4o’s Musical Recommendations

There was a bit more of back and forth between ChatGPT, Suno and me, a few-shot prompting and answering, a trial and error text-to-music sequence, to refine the components and the output I was looking for. And there it was, my song made for me, Muted Sights.

Muted Sights - Anthony Frenchy

What do I think of the song as a finished artefact? I certainly don’t dislike it. Would I listen to it if I hadn’t created it? Not quite sure I would. I still feel like that je ne sais quoi is missing, the ghost in the machine is not there yet. But that’s beside the point for now.

Here’s another question: am I the author of the song? Well no I am not if you consider an author must have both created and made, that they must have written the lyrics and the music in harmony, and maybe even performed. But if we follow the mental path laid out a long time ago by Walter Benjamin in "The Work of Art in the Age of Mechanical Reproduction”, showing how photography - and by extension other “creative technologies” - reduces the “aura” or “unique presence” of a work of art, then here I am, using yet another mechanical prosthetic to create a work of art.

And here’s where this could lead us - yes I know, this is very much along the lines of “where will AI lead us”, please indulge my 2 futuristic cents. How can GenAI songs be useful and valued? Much like we have learned to do with pictures, we have to look past the artistic, cultural or archival value of creative artefacts. Art is still made of pictures and songs - and so much more. But maybe pictures and songs do not always have to be art? Maybe they can be memory or mood tokens we create for ourselves or a few others around us?

Maybe songs I create are intended for my sole listening pleasure, a keepsake or memento mori. Creation is a me to me process there. Maybe we’ll use songs as birthday cards, love letters or thoughtful messages of any kind, on a one to one basis. Maybe I’ll use songs as part of a creative brief, to convey to the best we can our creative intention to an artist who will take it further. And maybe GenAI song making will reveal talent that just needed new tools to shine.

Done with my song generating and my writing for now. Listening to Nicola Cruz - his art would not exist without the digital tools of his trade, and a rare talent that connects sounds, influences and cultures.

In a world where technology perpetually reshapes our existence, understanding the depth of its impact on human experience is essential. From the dawn of civilization, tools and technology have been intertwined with our evolution, influencing our culture, society, and perception. As we stand on the brink of a new era defined by artificial intelligence, particularly generative AI, it's imperative to reflect on this journey. This article delves into the profound ways in which our experiences, representations, and the very nature of these representations are being augmented yet again, marking another significant chapter in the long narrative of human-technology symbiosis.

The Human Experience, Augmented, Again

The essence of human experience has always been a tapestry intricately woven with the threads of culture and technology, each strand imbued with the distinct hues of human creativity and innovation. The notion that our world is an unadulterated natural environment is a fallacy, as anthropologist Philippe Descola illustrates in his seminal work, "Beyond Nature and Culture." Descola's discourse, a beacon in the intellectual realm since its 2005 publication, delves into the intricate interplay between nature and culture, challenging the conventional dichotomy that has long separated these two realms.

Historically, culture and nature have been perceived as distinct entities. Culture represents the collective human creation encompassing art, language, and societal norms, while nature is seen as the domain of the non-human, comprising flora, fauna, geology, and natural forces. Yet, Descola's analysis, enriched by ethnographic studies and theoretical insights from cognitive science, structural analysis, and phenomenology, dispels this binary perspective. He introduces the "four ontologies"—animism, totemism, naturalism, and analogism—to encapsulate the myriad ways humans interact with nature. This reconceptualization goes beyond the simplistic nature-culture divide, offering a reinvigorated framework for anthropologists and philosophers to reinterpret the world.

A vivid illustration of this blended nature-culture paradigm can be found in the article "Bears in the Villa" from The New Atlantis. It exemplifies how human environments are inevitably shaped and reshaped by our interactions with the natural world, emphasizing the inseparability of these two realms.

Parallel to Descola's exploration, David Graeber and David Wengrow's "The Dawn of Everything" revolutionizes our understanding of human history. Challenging entrenched notions about social evolution, the authors confront the stereotypes of our ancestors as simplistic beings. They argue that the development of agriculture, cities, and even civilization itself need not be viewed through the lens of hierarchy and domination. Their research in archaeology and anthropology suggests a human past replete with diverse forms of social and economic organization, debunking the myth of a linear progression from primitive to civilized states.

As we stand on the cusp of another significant augmentation of the human experience through artificial intelligence (AI), especially generative AI, it is imperative to reflect on these insights. AI is poised to reshape every facet of our lives, from mundane tasks to complex societal structures. The impact of AI on culture, art, and creativity is particularly profound but certainly not foreordained. The value we attribute to representations, be they static or dynamic images, and the ways we engage with them are undergoing a transformation. This change is not merely technical but philosophical, prompting a reevaluation of our understanding of creativity and originality.

For marketers and advertisers, this evolution presents both challenges and opportunities. The traditional approaches to brand building, consumer engagement, and market analysis are being redefined. AI's capability to analyze vast datasets and generate creative content will transform how brands interact with consumers, offering personalized experiences and reshaping consumer expectations. However, this technological advancement also raises ethical considerations about authenticity, privacy, and the role of human creativity in an AI-dominated landscape.

In summary, as we embrace this new phase of human-augmented experience, it is crucial to approach it with a nuanced understanding of the interplay between nature, culture, and technology. The insights from Descola, Graeber, and Wengrow remind us that our history and future are not predetermined but are shaped by the choices we make today, especially in how we integrate and interact with transformative technologies like AI.

The Representation of Experience, Augmented, Again

The evolution of image representation, from sacred symbols to ephemeral snapshots, mirrors the shifting paradigms of human experience and perception. This journey, explored through the lenses of thinkers like Walter Benjamin, Guy Debord, Roland Barthes, Susan Sontag, and Nathan Jurgenson, reveals the transformation of images from divine representations to commodified transactions in the digital age.

In the earliest epochs of human history, images, be they sculptures or paintings, held a sacred aura, often representing the divine. These images were more than mere visual representations; they were imbued with a sense of profound truth and power. Walter Benjamin, in his seminal work "The Work of Art in the Age of Mechanical Reproduction," speaks to this transformation, noting how mechanical reproduction strips the 'aura' from art, detaching it from the domain of tradition. This sacred aura, once the exclusive domain of religious and regal authority, begins to dissipate with the advent of mechanical reproduction.

The introduction of photography marked a significant shift in this trajectory. While still regarded as a medium of truth, owing to its ability to capture reality as it is, photography began to democratize image creation. Roland Barthes, in "Camera Lucida," reflects on the nature of photography as a medium that communicates the 'has-been' – a direct imprint of reality. However, this period also signifies a movement away from the sacredness of images, making them more accessible and less otherworldly.

The acceleration of both analog and digital means of reproduction has led to a further shift: images have become increasingly fabricated, representing not objective truths but subjective experiences. Susan Sontag, in her exploration of photography, notes how images have become ubiquitous in representing personal and collective narratives. This ubiquity has led to a devaluation of the image's intrinsic meaning, transitioning from a representation of truth to a representation of one's self.

We can delineate three distinct eras in the evolution of image representation. The first age is one of representation as power, where images of the divine or of monarchs, created by a select few, held sway over the masses. The second age is that of representation as agency, brought forth by the democratization of photography, where individuals gained the ability to document and control their own narratives. The third age, marked by the rise of social media and user-generated content, is one of commodification, where images become a currency in social transactions, used to construct and communicate personal identities.

In this current era, as Nathan Jurgenson suggests, images have increasingly strayed from representing any substantive reality, instead becoming ephemeral elements in a continuous flow of digital interaction. They serve more as means of maintaining social relationships and online presences rather than as conveyors of deeper truths or artistic expressions.

The advent of artificial intelligence, particularly in the realm of generative AI, potentially heralds a new phase in this evolution. AI-driven image creation can further detach images from their traditional role as representations of reality or subjective experience, moving towards an era where images are generated and manipulated by algorithms, blurring the lines between reality and simulation even further. This evolution, echoing Guy Debord's notion of the 'society of the spectacle', suggests a future where images may not just represent our experiences but actively shape them, creating a hyperreal landscape where the distinction between image and reality becomes increasingly ambiguous.

In conclusion, the journey of image representation from sacred symbols to AI-generated simulacra reflects the complex interplay between technology, culture, and human perception. As we navigate this new era, it becomes imperative to critically engage with how images shape our understanding of reality and ourselves, and the role that emerging technologies like AI will play in this ongoing narrative.

The Experience of Representation is Something New

The evolution of image representation has entered a new phase with the advent of generative artificial intelligence (AI), fundamentally altering the relationship between humans and images. In this context, the notion of agency becomes central - the shift from humans exercising agency over images to images, increasingly AI-generated, exerting influence over human perception and behavior.

The emerging dynamics of this relationship can unfold in various ways. On one hand, there is a pessimistic scenario where individuals become more subjugated to their screens, increasingly alienated from authentic human experiences. In this view, AI-generated images could deepen our reliance on digital representations, further blurring the lines between reality and virtuality. Such a scenario echoes concerns about the increasing mediation of human experience through technology, a theme prevalent in academic discussions and expert analyses on the impact of digital media.

Conversely, a more optimistic perspective suggests that humans might navigate this new landscape with discernment, distinguishing between different types of images and their purposes. In this scenario, people might accept entirely fabricated images for transactional purposes such as commerce, advertising, or entertainment. At the same time, they would seek out authentic images for purposes that require deeper human connections and emotional conveyance. This viewpoint aligns with discussions in business and marketing publications, which highlight the potential for AI to revolutionize content creation while acknowledging the enduring value of authenticity in building brand loyalty and consumer trust.

For artists and creators, the rise of generative AI presents both challenges and opportunities. In a landscape saturated with AI-generated content, the creation of authentic connections becomes paramount. Community building around an artist or creator could serve as a critical differentiator. In such a world, a great book or movie might lose its perceived value if it's perceived as the product of AI, lacking the context and community engagement that confer deeper meaning and value. This ties into the broader discussion in creative industries about the importance of storytelling and community engagement in ascribing value to artistic works - think about the power of #BookTok to sell more than books, authors and their communities.

The ubiquity of fabricated images raises questions about the value of images that are 'made' rather than 'fabricated.' In a world where AI-generated content is the norm, there could be a renewed appreciation for images that are handcrafted or represent genuine human experiences. This shift could provide a strategic advantage for brands and artists who prioritize authenticity in their work. They could capitalize on the growing desire for genuine, unmediated experiences, differentiating themselves in a market increasingly dominated by AI-generated content.

In summary, the impact of generative AI on the world of image representation introduces a complex interplay of challenges and opportunities. As AI reshapes the landscape of digital and social media, the concepts of authenticity, community, and human connection become increasingly vital. Whether this new era leads to further alienation or a renaissance of authentic expression will depend on how individuals, creators, and brands navigate the evolving relationship between humans and the AI-generated images that increasingly populate our digital world.

Staying Human

The augmentation of the human experience through technological advancements, particularly generative AI, heralds a transformative era in how we perceive and interact with our world. From redefining the nature-culture dichotomy to reshaping our understanding of representation and agency, these developments challenge our traditional viewpoints. As we navigate this new landscape, the balance between embracing technological possibilities and preserving authentic human connections becomes crucial. The future will likely be defined by our ability to integrate these advancements while maintaining the essence of what makes us uniquely human - our creativity, empathy, and capacity for meaningful interaction in an increasingly digitized world.

To answer that question first, before we ponder the latest short term cycle of change, let's go back to the teachings of Marshall McLuhan. Most of you have heard I'm sure his axiom "The medium is the message", suggesting that the form of a medium embeds itself in the message, creating a symbiotic relationship by which the medium influences how the message is perceived. There's a whole book thereon that actually goes a little deeper and further, "The Medium is the Massage" - make sure you read that right.

TV Always Was Social

McLuhan posits that media are extensions of human faculties — print extends the eye, the wheel extends the foot, electronic media extend the central nervous system, thereby altering ratios among our senses and changing our interactions with the environment. This concept is rooted in the understanding that technologies are not mere tools but are integral in shaping society's structure, patterns of social organization, and cultural practices. The book touches upon the transmission of information and how it is affected by the medium through which it is conveyed. McLuhan argues that the characteristics of each medium — be it print, radio, television, or others — necessarily dictate the nature of the information transmitted. For instance, print media fostered linear thinking and individualism, while electronic media promote involvement in global networks and a collective identity.

It is interesting to look at how TV fits within this structure of influence and control. What McLuhan said of TV, we say, mutatis mutandis, of "social media". TV, McLuhan says, has the power to shape public opinion, influence cultural norms, and create a shared experience on a scale that was previously unattainable. The communal aspect of television viewing contributed to a sense of collective identity and shared reality. It has been instrumental in the dissemination of cultural products, political messages, and social norms. Cognitively, television changes the way information is processed by the brain. The rapid succession of images and sounds can condition viewers to expect and even require a high level of stimulation, potentially affecting attention spans and the ability to concentrate on less dynamic forms of media like books or newspapers.

Social as Entertainment

Can we see how "social media" did not appear out of the blue icons of Facebook and Twitter? To be sure interactive features and user-community-led uses of "social media" apps make these very different from TV as a social medium. Yet, for all their differences, "social media" apps follow in the footsteps of TV, taking the communal and conversational dimensions several notches up. Furthermore it feels like "social media apps" have been rebranding themselves as "platforms". Albeit interactive still, the pervasive full vertical screen videos popularized by TikTok, and emulated by Instagram (Reels) and YouTube (Shorts), have turned smartphones into enhanced participatory TVs. TikTok goes so far as to brand itself an "entertainment platform" rather than a "social media" one.

I would argue that the "social" dimension has long been relegated to the background of vertical scrolling interfaces where "parasocial" relations - asymmetric relationships where one, the creator or the brand, lives in the near constant gaze of thousands or millions of others who don't have to disclose much about them, and who don't share intimacy with the object of their gaze - have become the norm, for better or worse. Social bonds still flourish online, but they are more likely to be found in text or chat based interfaces, on platforms like Reddit, Snapchat and Facebook (Friends & Groups), in Instagram Direct Messages or on WhatsApp.

TV as a Screen

TV is no longer TV as we understood it, it's a - digitally connected - screen. With "social platforms" being as much about entertainment as connections, the resurgence of "TV as a screen", enabled by connected TV (CTV) and streaming platforms, is redefining the landscape and bringing back some of those social and parasocial aspects thereto.

TV as an uber totalizing dominant media form, defining screen formats, content trends, programmation and conversations, is no more. At its peak in the early 1990s, in pre-commercial-internet times, TV captured close to 6 hours of viewing time on average each day. Even though this has decreased by several orders of magnitude, a closer look shows that Boomers and Gen X still spend more than 4 hours per day watching TV, and Gen Z more than 2 hours, putting this in the same space as major "social platforms".

Digging even deeper we notice that non-linear TV (streaming with the likes of Netflix, Prime Video, Disney+ and Apple TV+, and on demand with YouTube TV) has become the leading way through which people "watch the TV screen", with close to 40% of market share. Not only do they aggregate audiences around a myriad forms of content and viewing experiences (short and long form, originals, binged, UGC, creator, back catalogues and reruns, etc.), these platforms are upping the ante and bidding for the biggest TV audience magnet out there: live sports and events (such as concerts). As Julia Alexander recently put it in Puck:

"It is, after all, the number one video rival to linear TV and the primary video player for kids, teens, and young adults. Now, with YouTube buying NFL rights, via Sunday Ticket, and making a play for cord-cutters with YouTube TV, it’s become a genuine streaming threat, too. In fact, by bundling free user-generated content, premium video channels, and a digital cable replacement, YouTube is setting itself up to be more powerful than a mere streaming service, but rather a platform upon which all of those other services sit—a veritable operating system for the streaming age.

Interestingly, the market also seems to be underappreciating that the same opportunity for Alphabet is also open to Amazon and Apple: All three are competing to dominate the streaming video ecosystem with hardware and operating systems built into TV sets that effectively replace the traditional distributors, ensuring that their platforms are the entry points for TV viewing globally. To paraphrase NBC’s late, great Heroes: control the living room, control the video market."

The Apple-Amazon-Google Streaming O.S. Mega War

TV is the "New Social"

As it could very much become a yet again central viewership device and audience aggregator, building on decades of creating shared experiences at scale, layering in everything that "social platforms" have become over the past 15 years, TV as a screen may very well become the "new social" - i.e. the cool device where innovation abounds. And as most new TV entrants are forced to reconsider advertising as a key monetization pillar, it is interesting to wonder what "TV Screen" advertising is going to look like in the near future.

Advertising strategies and formats have evolved. YouTube's ABCDs (Attention, Branding, Connection, and Direction) emphasize creating ads that are engaging, brand-centric, and emotionally resonant​​​​​​. TikTok's approach, encapsulated in the mantra "Don't make Ads. Make TikToks," focuses on creating content that is fun, engaging, and blends seamlessly with user-generated content​​​. Google's "Messy Middle" concept illustrates the non-linear and complex nature of modern consumer decision-making, influenced by a myriad of online touchpoints and cognitive biases​​​​​​. Similarly, TikTok's "Infinite Loop" model represents a departure from the traditional marketing funnel, emphasizing a continuous engagement cycle where consumers can enter and exit at various stages, driven by hyper-relevant, personalized content​​​​. Chances are TV ads are going to be much more contextual or community anchored, such as the one that Google ran next to Max's The Sex Lives of College Girls a few months ago.

As we witness the transformation of TV from a broadcast medium to a multifaceted screen for streaming and social interaction, the implications for media, advertising, and consumer engagement are profound. The lines between television, streaming platforms, and social media are blurring, creating a new paradigm where content, commerce, and community intersect. In this landscape, understanding the nuances of connected TV, streaming strategies, and the evolving nature of social media advertising is crucial for brands and content creators alike.

This train of thought led me to think about our marketing propension to add more brand-thought to paper, about our innate desire to fashion brands into perfectly centralized and controlled objects. As a result we end up turning brands into macrocephalic concepts, crammed with every bit, piece, item, speck and unit of information that we can add to a 120-slide deck, a mind map or a one-page brand roadmap with dozens of footnotes and appendix pages. Beyond and beneath the vision-mission-ambition trifecta lie manifestos, values, behaviors, personality traits, tones of voice, … Even though these are needed and highly valuable, they bother me for two reasons. The first is that they are conceptual endeavors that are hard to implement and bring to life in a consistent manner. The more intricate the brand roadmap, the less likely the brand is going to actually show up in consistent and distinctive ways across the dozens of channels, formats, touch points and interfaces that are part of the marketing playbook nowadays. AI will most likely make cohesiveness much easier to attain consistently, but that’s a thread for another post. The second reason why I’m not a big fan of dense paper brands is more strategic: a brand is not a one-and-done paper concept, a brand is a living and breathing organism.

What if the brands we had in our care stopped trying to do everything on their own, from the sole vantage point of their centralized nervous systems? What if they started to look outward and welcomed the fact that they are living organisms that are as much defined by what others say, do and feel with and around them than by what we, marketers, jotted down some time ago on paper and updated once in a while? Actually the more mature and confident a brand, the more it can let go of its Demiurgic desire to control all it is, will and should be. The more a brand trusts its place, its products and what it stands for among its many stakeholders, the more it can grow and become.

Fashion, beauty and luxury brands have long known that the faces of those who design them, of those who sport them on catwalks, of those celebs and influencers that put their sartorial and cultural spin thereon, are of the utmost importance. Louis Vuitton and journeys, Chanel and timelessness, Gucci and eclectic romanticism would not come to life were they not embodied and, in more ways than one, created by their famed designers and iconic celebrity ambassadors. In this respect it seems to me that social media is pushing more brands in the right direction, whether it’s FMCG, CPG, travel, or food & beverages. Having to give creators a free rein - otherwise said creators would not be interested in partnering up - has led to a reckoning of sorts. Yes the brand roadmap still matters, but we should accept that some of the strategic components of the brand are going to be defined as they are executed, from the ground up, starting with TikTok creators and their antics.

Brands such as Nerf or Duolingo are hiring Chief TikTok Officers while others like Olipop use TikTok as a distinctive brand descriptor. What does it say about them? That they are confident enough in who they are and what they stand for to allow TikTok creators to co-define and update them, from a strategic perspective! A project I had the chance to be closely involved with offers another good example of brands being partly defined as they are scrolled. Hilton, working with TBWA\Chiat\Day NY (#selfpromo), defined a Disruption® roadmap (i.e. a brand platform) that revolves around the idea of “For The Stay”, that is to say putting emphasis on the amenities, services, team members, comfort and care found at a Hilton property, as the key ingredients that are going to make or break the broader experience of travelling somewhere. Building thereupon, an A-team of creators expanded upon this vision and made Hilton into the hotel brand by and for creators thanks to a 10-minute ad that turned heads and stopped scrolls!

What we need is more dialogue. A dialogue between the printed page and the feed, between the conceptually defined brand and the lively embodied one. Let me make this clear though, a dialogue goes both ways. Both ends must allow themselves to be challenged, influenced and even maybe rewritten by the other. We have seen countless examples of the paper brand rewriting the embodied brand, and that’s fine, provided rewriting the embodied brand makes more sense, makes the whole bigger and more cohesive, adds to each of the component parts, and proves more effective. We should accept and embrace moments when the embodied brand is going to amend and update, for the best, the written one.

Mind the gap between brand signs and brand meaning

On the Internet nobody knows if you’re a dog, and cats are ubiquitous. Although the former only have happenstance to thank for their digital related popularity1, the latter may have ended up here out of serendipity, for a reason that might not be apparent at first, but that eventually makes sense when it is revealed. Cats were already present in the first myths that were laid in writing for us to witness and remember; they were the protectors of pharaohs in ancient Egypt, cast in stone as statues representing deities, buried with what this civilization held as most sacred and precious, eternalized in the hieroglyphs that for so long had eluded our comprehension. In other words cats made up for great story characters. They were the extraneousness, the oddity in the story, the bridge between what we know, cats as we see them, and what we cannot fathom still, cats as we see them behaving. A cat is an odd being indeed; it goes crazy at night when the dark is finally deep enough that you won’t detect its next move; it appears out of the blue to startle you ever so softly; it walks a fine line like nothing else, only to stumble and make a mockery of itself. A cat captures the gap between what’s perceived and what’s meant, between the signifier and the signified. Therefore in the cat rests one of the most profound issues there’s ever been for mankind to ponder; in this gap resides everything that we experience without ever completely understanding it: can this be real? To quote Claude Lévi-Strauss “The mana, the manitou, the thing, the gizmo is nothing else than the imperfect connection between signifier and signified, a gap between what always precedes, the signifier, which has been fully given since the beginning of times, and what follows, the signified.”2 The thing with cats is that they are both the observed experience and the unattainable meaning, they are within our reach yet so hard to catch, they are true to our eyes yet false to our cognition. Cats may not belong to the world of myths anymore, but they certainly are more art than science, just like our representations of reality. Staying with Claude Lévi-Stauss a little longer, we can say that “art inserts itself at equal distance from scientific knowledge and mythical or magical thought.”3 When science explores the formal characteristics of matter or the human mind, when mythical thought makes sense of the world from felt experiences, art itself proceeds from the vast diversity of the world all the while producing artefacts that are immediately recognizable and apprehensible by the great many of us.

There’s a wide gap between what we see and experience, artefacts such as videos, soundbites, quotes, posts or pics, and the profusion of matter, information and knowledge available all around us, such as the billions of hours of videos produced every day on earth. It is in that gap that we should approach brand strategy, in a space where information is sent over wavelengths or stored in clouds, news spreads fast before it backfires, memes are made so idiosyncratically and shared so universally, images created to reveal our selves and our shelves, posts tell nothing to say it all. Our sphere of communication goes round and round, it won't stop so that we may step back and grasp it in full, we are always part thereof, never able to offer a complete, detached and unbiased view of what it is to watch, talk and share in a rolling feed of information. This is but the fate of our human experience after all, stuck as we are between two Kantian worlds, that of beauty, where everything exists in the moment, where nothing exists outside the eyes and the intellect of any one person, where no overarching concept prevails, on the one hand, and the world of logic on the other, where mathematical, physical, environmental and cosmic truths abound without much concern for human judgment. Billions of us see, and all form worlds within themselves, assigning different meanings to shared experiences. Billions of us would see in the past, but that was it. Now not only do we see by the billions, we talk by the billions, which we'd never been used to, and therein lies the source of our discomfort with the XXI century in respect of information, communication, culture, cognition - and yes, brand strategy.

The world is complex, so should the world of brands be

Our experienced realities are, to a great extent, so much different from those of the past. Up until the invention of writing very few people had the power to share information or change minds. Stories told in oral ages either had very small audiences, inside villages or tribes, or would travel in time, from generation to generation, to become collective poems, norms or myths. The origins of the Iliad and the Odyssey are still being debated, as the singular body of works of one poet named Homer, or as the collective works of generations of Greek aezi who would speak these stories from the second millennium BC4 before they were codified in a comprehensive body of works in the first millenium BC. As individuals could not travel far in space nor in time, they had to invent stories that could gradually shape minds and societies. Even though handwriting and papyruses helped spread the Word, humanity had to wait until the XV and XVI centuries, and the advent of the printing press, to see a clear increase in the ability to share information at speed with larger audiences, an ability that was mostly reserved to monarchs and heads of state at first, before becoming available to many private publishers, whether with business or political agendas, in the XVIII and XIX centuries. This is where we stood in the XX century, and this is where our considerations, reflections and reflexes still linger, in a gap that still felt comprehensible, even though quantum theories and the concept of entanglement had already started telling a different story:

We think of the world in terms of objects, things, entities (in physics, we call them "physical systems"): a photon, a cat, a stone, a clock, a tree, a boy, a village, a rainbow, a planet, a cluster of galaxies ... These do not exist in splendid isolation. On the contrary, they do nothing but continuously act upon each other. To understand nature, we must focus on these interactions rather than on isolated objects. A cat listens to the ticking of a clock; a boy throws a stone; the stone moves the air through which it flies, hits another stone and moves that, presses into the ground where it lands; a tree absorbs energy from the sun's rays, produces the oxygen that the villagers breathe while watching the stars, and the stars run through the galaxies, pulled by the gravity of other stars... The world that we observe is continuously interacting. It is a dense web of interactions.

- Carlo Rovelli in Helgoland

Our shared realities are hard to pin down, they always have been, probably because they reside in that gap, the one that bridges our observations and every other possible interpretation or explanation for a given phenomenon or behind a beholden artefact. With the acceleration of time and the associated abridgment of space, with the preternatural (sic) ability to reach the farthest reaches of earth in no time, with the new possibilities of intervention afforded to the many, that gap has become both wider and deeper. Our shared realities are far more plural, diverse, diluted and distributed than they used to be even though the phenomena or objects we gaze upon look pretty similar. A video, a segment of news, a publication, an interview, a portrait, they all look the same as yesterday, yet they hover above an inscrutable abyss, one that feels impossible to fathom, one where concepts like fake news, conspiracies, dark patterns, ghosting, shadow banning, algorithmic bias or doxing proliferate. In that new reality made by the many, in that ever widening gap where realities now collide, there are compasses we can use, provided we know how to recalibrate them. There are ways in which we can still make sense of that gap, in which we can reconcile meaning and the many.

Culture is the brand playbook, not just its playground

Most marketing and brand strategies still rely on canonical concepts from communication and business theories established in the XX century, in a world that was complicated but not complex, one where there was a pretty linear and predictable path between the source of a message and its intended recipients, with very limited entropy along the way. To put it more simply a brand only had to do a few sequential things to be seen and heard: define a few single-minded messages, weave them into advertising campaigns or PR talking points, run them on some of the few existing media and attention gatekeepers (print, radio, TV, OOH, retail), expect consumers to act upon those. I know this sounds simplistic, and to be sure a lot of thinking and crafting had to be injected, but the overall picture was simple enough to wrap your head around.

As attention comes in shorter bursts and on smaller screens, as content is measured daily in billions of creators and hours, as sly algorithms dictate what gets seen and amplified, the 4 Ps of marketing - Product, Price, Place, Promotion - are no longer enough to define and express oneself, to stand out, acquire and retain consumers. The marketing funnel is not enough. A brand platform is not enough. Yes they matter greatly, and I thoroughly enjoy designing them in canonical or disruptive5 ways.

In a world gone social, brands have to look beyond the marketing playbook and use frameworks and tools that will make them into cultural objects. Culture is not to be construed in a narrow way here, one that is usually reserved for artists, literature, music or films for instance. Culture is to be apprehended in its anthropological way, as the total frame that defines and binds human societies together, with four dimensions: Relations (through Language, Families and Trade), Art, Science & Religion.

These four dimensions are the sum total of what is needed to create culture, to form societies. As evidenced by the evolution of branding and marketing vernacular in the past 20 years (for better or worse), with branded content, entertainment, experiences, installations or communities, we must understand that the branding playbook has to be culture encompassing and not squarely marketing based.

To be sure over the past 10 to 20 years we have been "implementing" brand strategies through more avenues and channels than the ones inherited from the XX century. But, beyond a few exceptions like DTCs, have we really been taking into account early on the relations we strive to build within communities and around commerce? Are we incorporating in our strategic vision the consumers and creators we will write and tell our stories with? Are we willing to keep our brand strategies in constant beta as we gather in-vivo behavioral data from our users that may contradict the initial in-vitro assumptions we made? Do we see interfaces as the artefacts that will primarily define our brands? This is what I mean by seeing brands as ecosystems: they're made of much more than targets and statements, they're alive, they're multifaceted, they're made of particles that certainly collide and maybe collude to define the brand. The following is one way to think about everything 😶‍🌫️ we must bring into the fold of a brand strategy, and not just its implementation.

Let us take time to explore that gap where meaning by the many resides and eludes us, let us treat brands just like we see cats, accepting that the signifier comes before the signified, and that we will spend a lifetime contemplating, tweaking and caring for them.

Just as the individual is not alone in the group, nor any one society alone among the others, so man is not alone in the universe. When the spectrum or rainbow of human cultures has finally sunk into the void created by our frenzy; as long as we continue to exist and there is a world, that tenuous arch linking us to the inaccessible will still remain, to show us the opposite course to that leading to enslavement; man may be unable to follow it, but its contemplation affords him the only privilege of which he can make himself worthy; that of arresting the process, of controlling the impulse which forces him to block up the cracks in the wall of necessity one by one and to complete his work at the same time as he shuts himself up within his prison; this is a privilege coveted by every society, whatever its beliefs, its political system or its level of civilization; a privilege to which it attaches its leisure, its pleasure, its peace of mind and its freedom; the possibility, vital for life, of unhitching, which consists - Oh! fond farewell to savages and explorations! - in grasping, during the brief intervals in which our species can bring itself to interrupt its hive-like activity, the essence of what it was and continues to be, below the threshold of thought and over and above society: in the contemplation of a mineral more beautiful than all our creations; in the scent that can be smelled at the heart of a lily and is more imbued with learning than all our books; or in the brief glance, heavy with patience, serenity and mutual forgiveness, that, through some involuntary understanding, one can sometimes exchange with a cat.

- Claude Lévi-Strauss in Tristes Tropiques

Serendipitous Numbers, Ponies and Piketty

I wonder whether I should have titled this newsletter Talking in the XXI Century. This would have been an interesting, if humble, nod to Thomas Piketty’s Capital in the XXI Century, and I would have made sure to stress how positively I valued the rise of talking capital among the multitude against the unacceptable erosion of economic capital that the many have had to endure in too many countries over the past forty years. The thing is I have a serendipitous relationship going on with numbers, and XXIc would have fit in nicely there. Take 148 for instance, that’s the nicknumber under which you’ll find me on different social networks or websites. Why 148? It so happens that one of my daughters used to ride horses and, with very poor horsemanship but a willingness to learn the ropes on foot, and a great level of dedication to my self-appointed role as a squire to pony riders, I got to spend a lot of time gauging the animals, learning that the 148 centimeters height mark at the bottom of the neck separated horse from pony. But this is only something I discovered after I had already chosen 148 as a nicknumber. Another version has to do with my name, Anthony David Hamelle, ADH, or the first, the fourth and the eighth letter in the alphabet, 148. Not being well acquainted nor much interested in numerology this is something I realized long after I had begun using 148.

A Dose of Social Sciences

Then why? Why did I choose this particular nicknumber? It has to do with my interest for a field that is populated with opinion research, information, media and communication, political and social sciences, branding and advertising, social media and networks, digital technologies, uses and experiences. At the center of that field, at its very origin even, lies a small group of humans where information flows fast, where word of mouth is trusted, where a close knit community flocks together to survive and to strive. That small group of humans is on average made of 148 individuals, the optimal number of individuals with respect to the level of coöperation inside the group, the maximum number of efficient social interactions our prefrontal cortex can handle, the number named after the British linguist and anthropologist who, after having archaeologically studied ancient villages, observed groups of gorillas and chimpanzees, arrived at that conclusion: Robin Dunbar. In a brand new world where we can be followed by thousands, where billions of pieces of content are created and shared everyday, where influence has become brazenly monetized, I like to remind everyone that much of our world is not new, that the old never ceases to dive into the new, that the measure of everything is to be found on a human scale. 148 is an ancient reality already, and the epitome of what challenges information and communication in the public sphere: the end of the monopoly of XX century communication gatekeepers, the resurgence of the social factor, the emergence of multitudes with the ability to voice their own opinions, to challenge sources of authority relentlessly, to tell their own stories.

All That, Brand Strategy, and More

I suppose I should bombard you with numbers, or data as we fancy calling them. How many hours of videos are uploaded and watched every second. How many bytes of NFTs are shared on exchanges every month. How many people spend how many hours on how many platforms every day. Maybe I should, but truth be told I find that data is too often used to obfuscate, to spare one from critical thinking, to keep us from seeing the big picture. Do you still need to be convinced that the word has gone social? Do you still doubt that people have anything worth saying that has not been said better before by pundits or media monopolists? If you do then no, no data will convince you otherwise, and you can skip this book altogether. But if you don’t doubt the world we live in, if you are looking to understand more of it, then no number is needed, and all I have to do is to offer you pause, perspective and an original outlook.

Talking Too Many is an attempt at encapsulating what keeps flowing, at framing what keeps changing, at making sense of chatter and noise, at valuing the mundane, at connecting digital dots with culture and social sciences, for beneath our screens and feeds lie age-old realities, foundational tenets, and tectonic groundswells. This is a newsletter, written and designed from a singular perspective, that of a lawyer turned storyteller, that of a teacher who spends most of his time being an advertiser, that of a curious mind that likes to learn and share bits of knowledge. This is a newsletter, a series of artefacts in a changing world, a set of thoughts and meanings that shall not obsolesce when the next fad comes and goes, some lessons that will still be worth learning when the digital platform of the day dithers and dies. This is a newsletter, not a tutorial to tell a beautiful story in three easy steps, not a practical guide to create a successful advertising campaign in five minutes, not a handbook to hack the features of an algorithm and become rich so that you may tell the world about it. This is a newsletter that tries to capture many things you already know, to assemble different things that many know more about than I do, but things that few have assembled in a way that should provide a solid frame of reference for anyone whose passion or job it is to talk at, to, or better yet, with, others. This is a newsletter, demanding time and attention, leaving you to ponder over the ideas it contains, offering a subjective, humble, yet articulated and opinionated understanding of what talking too many is and how to navigate this new public space, and how to think of brand strategy therein.

"We’re riddled with pointless talk, insane quantities of words and images. Stupidity’s never blind or mute. So it’s not a problem of getting people to express themselves but of providing little gaps of solitude and silence in which they might eventually find something to say. Repressive forces don’t stop people expressing themselves but rather force them to express themselves; what a relief to have nothing to say, the right to say nothing, because only then is there a chance of framing the rare, and even rarer, thing that might be worth saying." — Gilles Deleuze, Negotiations

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