I published a version of this essay on Twitter, the native home of TBPN. (If you’re not familiar with TBPN, this NYT profile should get you up to speed.)

Watching the show get made.

It’s become a cliché to call for a sequel to HBO’s Silicon Valley, but the stories we want to watch are now indistinguishable from how company building and content creation is playing out on YouTube or X or whatever new platform’s being built. It’s the new television and TBPN is a new kind of show.

I’ve tuned into TBPN more to spectate than to voraciously consume. To see what new segments they were testing, which big-deal guests they’d courted, what life-sized tchotchkes they’d added to the set — and what new tricks John and Jordi had up their suit sleeves. Digesting the news itself felt secondary.

Casting is everything.

Was the content that good, or was the biggest draw watching the thing get built? The same question lingered around Clubhouse’s generational run.1

There’s a kind of universal rule I’ve seen a few times now: when your audience is mostly composed of high-value insiders, they’re almost certainly watching the meta-game as much as they’re using the product. This is why “going viral on X” is valuable but not indicative of PMF with ‘normal’ people. Even still, it’s a strong signal of the producer’s taste, tact, distribution instincts, and cultural fluency.2 You just need to know which PMF matters for you.

My analogy has been that guesting on TBPN is less like going on a tech podcast and more like being featured in Rolling Stone — if Rolling Stone published a new issue every day. The ‘ESPN for tech’ framing captures the live energy and the play-by-play, but the show is also doing prestige TV and magazine profile work all in one. I’ve always said smart people want to be cool and cool people want to be smart, and TBPN found a way to deliver on that desire.

A consistently popular narrative on X is that TBPN succeeded because of their “clips” strategy, despite few people watching the live shows 3 hrs/day. Clips are a great distribution mechanic, and TBPN is doing it well enough, but that's not their claim to fame (clipping is big outside tech media) nor their X-factor. TBPN’s prowess is less algo-hacking and more arts & culture.

A big part of TBPN’s success is that people love the characters.

Jordi is the nerdy jock and John is the jocky nerd.

They have a meme-able height gap yet neither is insecure (they’re both still tall). They were already credible talents in startupland, and now they’ve proven to be star communicators and likable in a way we rarely see in tech. They’re that likable because of their personality, passion, positivity, and because of their golden-retriever-good-looks (the first part their own admission, the second the audience’s). Tyler the intern, equally likable, is the equivalent of the late night talk show host sidekick. One intangible on top of it all is they’re good at improv.

They’re having fun and letting us play along. (Fun includes TBPN trading cards, coveted merch, gong hits, guest polaroids, absurd soundboard, studio horse, et al.)

The details matter, because, as I’ve been repeating lately — casting is everything. Tech has access to some of the most impressive people on earth, and somehow keeps featuring the same few faces that aren’t great at storytelling or the format.

A great cast still needs a great script.

The most compelling Silicon Valley stories used to be about generational software companies that took a decade to make it and convinced you they’d last for decades, as the acquirers and not the acquired. The most impressive stories now are all about momentum and spectacle, about the ride from founding to exit (ideally in under two years). Any guilt or shame around ephemerality is gone. Joining one of the big AI ships, especially as a standout talent or team that was courted, is the smart, sexy, high status Silicon Valley play right now.

The next storyline.

Even before the OpenAI acquisition, I’d been wondering how TBPN would make 2026 as big as 2025. Staying indie and grinding for more mainstream relevance didn’t strike me as ideal. And greater ambitions are expensive to deliver. Something I’ve repeatedly observed is that the relentless energy of the first two years of any enterprise is very hard to sustain in later years. One way to re-up that energy is to take a crazy leap of some kind. The most entertaining outcome is the most likely outcome because it’s often the most energizing one.3

Rebrand, partner, pivot, buy, sell. Good or bad reactions matter less than maintaining energy and with that, relevance, for yourself and the audience.

All else equal, I’m a bit less excited to tune into TBPN now than I was a few weeks ago, and I’d bet a big chunk of the tech insider audience feels the same.

This is an example of how the sophistication of TBPN’s audience cuts both ways. Insider audiences who made the show valuable are also the ones most sensitive to ownership changes and meta-story cycles — an exit reads like an ending.

You can’t air a season finale on Friday and immediately premiere the next season on Monday. You need to reset the stakes, rebuild tension, and give the audience a reason to return. You need new slow-burn plotlines, new bits, and even fresh characters, to keep the audience hooked. We’re in what really should be the off-season, the hiatus — they’re just posting through it because so much good has come from their relentless forward momentum these past 18 months.

Still, people keep saying no one will want to come on the show anymore, and I don’t buy that. If you would have taken a call from OpenAI — which the vast majority of people would — you’d still be willing to go on TBPN, maybe even more so now. Competitors and their allies will be wary, but the thing to pay attention to is less who’s a little less likely to be a guest and more why and with what sentiment in tow. The longevity of the show depends on sentiment, and how the show adapts in a no-longer-underdog environment. More on this later.

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Buying up cultural power.

Everyone has their own theory on why OpenAI acquired TBPN. It’s a marketing and comms play or ‘they bought distribution’ — all too literal. It’s a soft power play. Or it’s agitprop. Of all the takes on X, this tweet felt most efficiently true:

They wanted to acquire @johncoogan, @jordihays, @DylanAbruscato and the team. These guys are some of the smartest, most experienced marketers on the internet right now. They understand how to win the vibe war, while making everyone love them. Luxury positioning with down-to-earth approachability.

Pete Steinberger, Riley Walz, TBPN.

This string of acqui-hires is brilliant casting for OpenAI’s special teams. This is a pattern of talent that understands how to move culture and operate inside the feed economy getting poached by the machine-makers — because competition between AI labs is increasingly cultural, not just technical.5

Impressive feats of almost any kind now double as a job application to the biggest labs. The term “unicorn” has been worn out as far as companies go, but these are “culture unicorn” hires. All the better if what you’re doing is even tangentially related to AI. The comp package is just whatever it takes.

ChatGPT has a billion weekly active users, so OAI doesn’t need ‘distribution’ in the literal sense, but aura and know-how you can layer on top of that is worth infinite dollars. Anthropic has been gaining on OpenAI with tech insiders, market analysts, and TikTok generations alike. Paying “low hundreds of millions” for TBPN is a cheap move in the culture war against a rising competitor. Winning this war is just as consequential for hiring as it is for sales, funding, and policy.6

What does it mean that the most consequential AI companies are now hiring for charisma and communication alongside competence that captures attention?7

Most tech thought-leaders have shouted that they don’t get it and it makes them question OpenAI’s judgment. Legacy-new-media is writing that “the vibes are off at OpenAI” and Ronan Farrow just dropped a lukewarm hitpiece on Sam Altman.

But most people want John and Jordi to win, and that’s a superpower. Is there a transitive property of good vibes and good will? If everyone wants two guys to win and you hire those two guys, maybe they’ll want you to win too — or at least lose less?8

The critics and the risks.

It’s hard to deny TBPN has taken an aura hit — it’s no longer a scrappy upstart, and no longer default-neutral. OpenAI buying the brand dilutes it, which is why TBPN is smartly signaling it’s independence as much as possible. ‘Everything will stay the same’ is the politically correct party-line for this kind of acquisition, but something must change, and it will.

As far as all the media folks’ opinions on the acquisition — my intuition says most of them, both the clowners and the celebrators, are quietly relieved. Those criticizing TBPN for selling are secretly pining for an offer in hand too.

The top spot for indie tech media startup of the year feels open again. Anyone who’s been ostensibly playing for second place has renewed hope. Many will try to replicate the success of TBPN, and many will struggle.

There’s already a question about whether Twitter/X is shadow banning TBPN now that it’s owned by OpenAI (Sama and Elon are less than allies right now). Is this happening or is the audience taking a post-sale break from the show, is the show itself on soft-hiatus, or all of the above?

The wildcard to consider: TBPN has grown on X and Elon is known to throttle competition. If distribution is squeezed, YouTube is the natural next home — TBPN has ~100K subs there. Substack is an option but video podcasts haven’t popped there yet and the audience skews less tech. Or bolder — leverage their own platform, or build one? TBPN x OAI. Elon throttling Substack links on Twitter incentivized Substack to launch a competitive product with Notes … For TBPN’s meta-show, this would be a new underdog plot. For OAI, owning the culture unicorn could be an uno reverse card.9

(Fwiw, It’s been denied, and even if it were happening, I think the public discourse would become loud enough that it’d have to be walked back some.)

“Half-media, half-machine.”

Every organization will now operate as half-media, half-machine. Every media company will have a head of machines and every machine company will have a head of media. Call it the media-machine singularity of business — the hybrid imperative.

The duality of our era is Media and Machines. As the technical side of tech splits into automation or genius, the media side only gets more competitive. As I keep saying, tech is becoming the center of culture and so ambitious people from adjacent fields are flocking to it — both young people inside tech (shadow artists in trad roles) and outside tech (film and internet creatives) alike.10

Every big tech company, and especially the big AI labs are trying to figure out the best mix of investment and effort into media alongside machines. A great machine strategy with a poor media strategy will lose to someone with a better media strategy, or be beholden to them.

VC firms are scaling their “new media” efforts, and I keep waiting to be impressed. There are glorified minor changes to set design and post-production and more launches. More stuff is being made but nothing has truly imprinted on my mind. There’s a foundational tension in making media to market founders, companies, and narratives you need to sell— it’s rarely conducive to making art. It’s hard for me not to conclude something poetic:

The best stories don’t depend on their owners to tell them; the best stories find their own tellers.

Thanks for taking the time to read, and thank you as always to my generous patrons. If you enjoyed this essay, consider sharing with a friend or community, or on X. DMs welcome. // P.S. If you wanted this essay to be longer, give me a prompt.

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The underlying 2x2 is competence and charisma, with public proof. The archetype is the quirkily agentic generalist star who builds and speaks. The higher-value the person’s collaborators and audience, the stronger the signal — winning over the hard to win. The meme “OpenAI is nothing without its people” is makes so much sense for the next phase.

AUTONOMY. CREATIVE OWNERSHIP. A SEAT AT THE TABLE. The right to say no, not like that, or not right now. Flexible schedules. Remote work. A title that keeps getting better. The expectation that your opinion shapes direction. The expectation that your resources scale with seniority.

These are among what I call luxury workers’ rights. They sit on top of human rights, civil rights, and workers’ rights. They’re the terms of a job meant to make work feel more meaningful and make you feel more valued. We typically associate them with white collar work and view them as moral principles, but they’ve always been a form of compensation for the scarcity of cognitive labor.

White collar work as we’ve known it is cognitive labor with a personhood premium—autonomy over the work itself and value attached to the person doing it. Cheap capital and high margins made it easy for companies who needed human intelligence to pay these premiums. Software’s surplus has been subsidizing our ego-scaffolding. But we’re facing the big shift now.

The early narrative was that AI would kill blue collar jobs first, but it turns out the real world is full of friction, and in the meantime, AI got a lot better at thinking. So it’s white collar work that’s exposed. AI is making intelligence abundant, and when the scarcity of anything drops, the premiums drop with it.

If you strip white collar jobs of their luxury rights, the line between blue and white collar gets a lot thinner. The professional laptop class is staring down its biggest reshaping and identity crisis since industrialization.

II.

MOST OF THE DISCOURSE LATELY IS ABOUT WHETHER AI KILLS JOBS. I’m more curious about what happens to jobs that stay and new jobs that emerge. Here’s one shift I expect—White collar ‘goes blue’ in two senses: more white collar work starts to resemble trades and the white collar apparatus moves into traditionally blue collar territory.

Recently a friend was talking about the dynamics at their startup: They’re growing fast and hiring a lot, but it already feels like there are too many employees, and some are just getting in the way. They’re all using AI heavily, and yet the core team—the elite architects and product thinkers and tastemakers—feel like they could just do the work themselves. That’d be easier than dealing with so many hires and their individual strengths and weaknesses, philosophies, styles, and anxieties.

What I hear between the lines: Critical work is done by a few elite people plus AI now. You still want a team to help execute, troubleshoot, manage, and socialize, but your patience for curating their experience equitably alongside the work is waning. Founders used to tolerate ten personalities on a spectrum of competence because they needed ten engineers to do the work. AI shrinks the team and the tolerance too because the alternative is an intelligent machine you command.

AI doesn’t eliminate surplus. It expands it and then concentrates who gets it.

The problem is you can’t renegotiate the social contract mid-employment. You can’t walk into a one-on-one and say actually we just need you to execute now and stop having opinions about what you’re executing. So when the personhood overhead gets too cumbersome, it’s easier to reset. Lay people off, restructure the org, hire new people—for net new jobs or existing ones rescoped as trades from the start, with exceptions for an elite few.1

Headlines sensationalize AI job losses, but layoffs don’t always mean we need less human labor or that AI is the cause. Block just cut 4,000 people (nearly half the company) and Jack Dorsey attributed it to AI. But Block had doubled its headcount during the pandemic. This looks like another company right-sizing from COVID over-hiring with AI as narrative cover. AI efficiency gains magnify the pre-existing bloat.2

Anthropic just released its own labor market research this week finding no real increase in unemployment for AI-exposed workers (from 4 years ago), but there are signs that entry-level hiring into those roles is slowing down for young people (in their early 20s). Maybe people aren’t being fired aggressively yet, but the most AI-exposed roles will stagnate, and the onramp into those careers will narrow, and eventually some of their tasks will be automated—so there’s a lot to figure out.3

III.

EVERY COMPANY BECOMES TWO COMPANIES. As a leader in the new world you’re choosing who gets the full luxury experience and who doesn’t: Fewer people with all the rights, or more people with fewer of them.

One model that seems increasingly likely is a two-tiered human organization inside every company—a small team shaping direction and a larger team executing within defined scopes. (In practice this already exists, but AI makes it harder to ignore.)4

There's an elite team of thinkers, researchers, and builders that operate at '10x' on ideas and execution and get treated and compensated that way. These become special teams—flat, close to leadership, and built around individual contributors rather than a cascade of managers. Everyone else belongs to the standard teams.

The elite teams are tastemakers. The standard teams are role players. Which is to say, the white collar economy is primed to split into its own white and blue.

The new class divide will not be what you do. It will be whether anyone knows your name. The named class shapes direction while the unnamed class executes it. The named class retains all the rights and gets more rewards, intangible and tangible. The unnamed class does good work and goes home. Skilled, dignified, well-compensated, but anonymous. Many ambitious people in the white collar economy want to be in the named class, but the power law says most can’t be.

We’re already seeing this at the top AI labs (with top researchers getting poached for what we speculate are billion-dollar compensation packages), special AI teams being formed inside Meta, and splashy acquihires of devs-as-tastemakers at scale (eg. Pete Steinberger and Riley Walz to OpenAI). (Still, the caliber of talent at the big AI companies is undoubtedly high all the way down; but it’s worth examining how organizations will be stratified going forward, even if it’s not the sexiest plot.)

Taking Anthropic’s jobs report at face value, we’ll need to rethink entry-level hiring. The white collar culture of hiring college kids as autonomous junior professionals with full packages and rights on day one makes even less sense now.

Bringing back apprentices seems like the obvious organizational and economic salve. Hire people to learn, support the senior team’s work, and earn their way into autonomous, judgment work over time—how the trades have always worked. Elite teams will need proxies to extend themselves too. The “chief of staff” is the high-octane, high-trust, skilled apprentice for an org’s elite. We’re in a hyper-merit, hyper-agency limbo between old and new now.

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IV.

THE RIGHTS WERE ALWAYS UNEVENLY DISTRIBUTED. The idea of white collar work losing its one-size-fits-all rights sounds like things get worse. But there’s always been a silent spectrum of who gets the best white collar experience and who’s already working a job resembling a trade. In practice, the engineer gets consulted on high-level decisions while customer support reps get flowcharts.

AI widens the economic gap between the promise and the delivery. When the distance between the tastemaker’s experience and the role player’s experience gets wide enough, pretending everyone gets the same deal stops making sense.

The power law already governs every talent market where output is visible and winning is relative. Star athletes get max contracts and creative accommodations while role players get a market-rate job and solid pay with no future guarantees.

I’d argue things will get more honest. The shift means more substance and less performance around the work from both employee and employer. Aspirationally, we rediscover the inherent dignity in doing good work and achieving something together instead of always needing to own and self-direct to feel valued.

White collar goes blue, but the convergence will run in both directions. White collar moves toward trades, and blue collar starts pulling in the white collar apparatus—the physical world is the renewed frontier. Now the electrician’s kid will learn to code and the coder’s kid will learn to weld. The new divide is closer to direction vs. execution, and it applies to both white and blue.5

V.

THE FLAT ORG WAS A LUXURY RIGHT TOO. But there are two kinds of flatness.

The version of “flat” that tech romanticized was consensus-driven flatness with many voices and distributed judgment. That made more sense when companies needed large teams of scarce cognitive labor. What AI encourages is closer to command flatness—smaller teams organized around a concentrated vision, where direction comes from a few people and execution radiates outward from them. The flat org survives, and even proliferates, but its meaning changes.

Film sets have always worked this way. One director and a world-class crew that submits to the director’s vision. This exists in tech in early-stage startups but less so at maturity.

“Founder mode” was a timely articulation of what we’re now seeing structurally. It was framed as a leadership effectiveness debate but it was really about the folly of distributed judgment and the merit of concentrated vision. AI only amplifies this.

VI.

MAKE YOURSELF SCARCE AGAIN. If we are indeed headed this direction, and you still want the luxury rights and compensation and glory, the answer is in the mechanism itself. The premium was always tied to scarcity. AI compressed it. So the way back is to go where you’re still scarce—or become something that can't be compressed again.

What makes you scarce?

BRILLIANCE — You’re so good at something or so rare in your combination of skills (scientific, technical, creative, strategic) that you can’t be scoped into a trade. Your taste, voice, and judgment alone are a strong value proposition.

INFLUENCE — You have a name, an audience, a brand that engages high-value communities. Your taste is signal and cultural influence is power. People want to be associated with you, and that affiliation arbitrage is worth the overhead.

RELATIONSHIPS — You’re the person the founder trusts, the client wants to work with, that just makes the team better, and people just want to be around.

The people who retain the luxury conditions will be the ones who figure out on which of these vectors they’re an N of 1, and perhaps more importantly, figure out how to articulate their value to stakeholders. Maybe what I’m saying is you can save yourself by becoming a legible artist. What they do can’t be taught to humans or collapsed into a set of machine prompts. It’s scarce. They’re scarce. And the premium follows the scarcity, like it always has.

But scarcity only earns back the conditions. It doesn’t solve the identity. Where does that go? I theorized in Dreams of Stability. The short version: it goes home.

This is part of an ongoing series on the future of work and personhood. If you enjoyed it, considering sharing with a friend or community that might enjoy it too. DMs welcome - reply to this email, via Substack, or Twitter.

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Art: Grant Wood’s “Arnold Comes of Age” (1930), Degas’ “The Orchestra at the Opera” (1870), Rembrandt’s “The Anatomy Lesson of Dr. Nicolaes Tulp” (1632).

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From Anthropic’s research: the gap between what AI can theoretically do and what it’s already doing; notice the sectors with the most exposure are mostly white collar …

What do you do? A few years ago, as far as the tech world is concerned, the cool answer sounded like ‘I’m starting something new’ or ‘We just closed a $1M seed round’ or ‘I’m all in on crypto.’ The unifying brag: I take risks. I don’t need a safety net. Now the cool answer sounds a lot more like ‘I’m at OpenAI’ or ‘I’m building something new at Stripe’ or ‘We just raised a $20M seed round.’

Prestige used to be ‘I might win big,’ because risk itself was glamorous. Now prestige is ‘I can’t lose, and I still might win big.’ If the brag used to be the bet, now it’s about having the best safety net you can get. Stability is the new status.

Dreams of Stability

The original American Dream was faith in work ethic. The second was faith in acceleration, made real by the internet era. The smartest or luckiest people got in early and rode the wave of new technology, platforms, and markets. Infinite impact, riches, and recognition were the seduction triple threat.

If it worked, you'd skip the 40-year career grind. The unspoken sacrifice was going all-in on the bet. It made sense at first. But platforms benefited more than the creators who grew them. Investors more than founders. Founders more than employees. People accepted lopsided terms because the dream The Social Network sold us was that compelling: kids became kings, and you could get a piece too.

Now AI is infiltrating every corner of society. The path calls again: get in early, launch the products, build the networks. But it feels different this time. The meme is the message: only a few years left to “make it” before you’re relegated to the “permanent underclass” — the final world order is set and you’re locked out.

The “permanent underclass” isn’t a fringe fear anymore. Vinod Khosla is cosigning posts about the K-shaped economy. Tech influencers are analogizing the AI inflection to COVID. Others are telling you to stop freaking out about a status quo that’s dead and climb the abstraction ladder.

The collective frenzy looks less like a gold rush and more like everyone’s taking shelter. “Anyone can do anything” sounds democratizing, but it means your edge is shrinking. Skills that took years to build are suddenly cheap. Companies can do more with fewer people. If you’re truly world-class, everyone still wants to hire you, but if you’re just very good, that might not be enough.

The second dream made us the assets, and the assets are repricing.

The problem is we didn’t invest in much else. And now the world is unstable, and so are we. Ambition is reorienting from limitless ascension to find solid ground first. The upside used to be upside. Now, the upside is stability.1

There’s no shortage of essays about what comes next. I’d bet reality will be less sensational and cinematic than most. I’ve written about what human work looks like on a longer timeline, but this essay is about the near-term impulse — to figure out where stability is and align yourself with it. (Unless you’ve already permanently ascended to the post-economic class, in which case, ignore all this.)

New Corporate, or boarding the ships.

The obvious place to find stability is inside the biggest ships.

AI labs are building the new FAANG right in front of us. For top researchers and engineers, getting hired by top labs is like being drafted to the pro league. For everyone else, it's the best seat on the rocketships colonizing the new world. Every seat comes with solid comp, status, upside, and critically, a place at the table of the future.

The realest reason to join an OpenAI or Anthropic right now is proximity — to information, money, power, and whatever comes next. When nobody knows what’s happening, being first to find out is a hedge. The gig grants you options.

You’re boarding a ship that everyone expects to weather the storm. You’re aligning with Goliath when it’s impossible to tell who David is. You choose the Goliath that fits your brand.

New Corporate is being on staff at a big AI lab, highly-funded spin-off, popular application company or infrastructure provider. Legacy big tech (eg. Google and Microsoft) and lovable big startup (eg. Stripe, Figma, Notion) are adapting to stay competitive in the New Corporate landscape. These are the adaptable safe havens with the perfect cocktail of stability and status and still some hope for upside.

But there are no guarantees. Companies are building the things that will replace us while preparing for layoffs and earmarking severance. Dario’s essays read like corporate eschatology — seeding the idea of welfare programs for employees made obsolete by the things they helped build. When the company tells you the machines are building themselves now, it’s some indication of the future.

Unsurprisingly, the incentives between founders and their teams are diverging. In other industries, workers might unionize. But Silicon Valley, which has prized meritocracy and free markets, historically relied on exit options. If you were laid off or didn’t like the terms, you went somewhere else. But it feels like exit options are narrowing. With skill being commoditized, fallbacks will be fewer. (We shouldn’t be surprised when tech workers start acting like workers.)

All this considered, people will keep joining the AI giants. Because right now the safety nets and the impact stories are pointing to the same organizations. You get to feel safe and righteous at the same time. And the upside is real, but more importantly, it’s probable.

For now at least, being inside the thing that will replace you still feels better than being outside it. The organizations that win the next era will figure out how to make people feel safe enough to do dangerous work.

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Founding, with a safety net.

Taking a shot now feels like taking the last shot. You can bet it all or anchor.

People are saying the VC-backed path is low-status now. Inside tech, I’d agree it dropped — for a minute. But the fragility of every other route is bringing some of that status back. VC used to be high status for its signal — for the stamp, the unicorn potential, the dorm-to-empire myth. Now it’s high status more for what it tangibly gives you: time and shelter. Time because you get five to ten years of belief and a full bank account while everyone else’s timelines and budgets are shrinking. Shelter because it’s membership in an ecosystem that looks like it’ll survive.2

The aspiration shifted from “I’m a risk-taker” to “I’m protected.” And that’s recursive — because stability is what’s scarce now, so stability is the new status.3

VC always came with a safety net, but now the safety net is a real selling point. Founding a company is still a noble calling, and VC is still one of the best places to take a real shot from. But people instinctively want more safety hatches now — raise more, bank more runway, take money off the table, engineer a soft landing early.

The hottest play of the moment: Make something on the frontier that the AI labs haven’t figured out, get insane attention and reach, and let them buy you for a big check before they can crush you. Reactions to the OpenClaw announcement have the vibe of ‘congrats on securing the bag’ — on translating your surge to an impressive safety net. Taking the indie star in-house will trend.

The one-person-billion-dollar-company fantasy isn't what it's been glamorized as (a business that'll scale in absentia and print money forever with one guy at a laptop). It's actually just a hot acquihire in waiting. The person is more valuable than the product now because the product is outdated as fast as it's built.4

The solo unicorn has proven taste, product sense, attention sense, and an impressive ability to activate high-value communities. The scaled solo path increasingly is the scenic route to boarding the same big ships that will weather this storm, and win.

The middle is the trap. The middle of everything is hollowing. Mid-tier startups, mid-tier talent, mid-tier creative careers. You’re either at the frontier or local. If you’re going to risk it all, risk it on something hard and worth it — atoms, not bits. Research labs, deep tech, biotech, regulated sectors, even politics (VC is already reallocating here). Hard problems where the friction is the moat.

Indie, but not naïve.

I’m still bullish on Silicon Valley Small Businesses supercharged by AI. But the indie path has gotten noisy … because anyone can make anything now. Vibe coding and Claude Code mean what once required a technical team now just needs one person with good prompts and good taste.

I’ve been calling this the rise of the software creator. The market is real. But how much of what’s being made is serious? How much of it is just a shot at viral content or a job application masquerading as a company? How much of vibe coding is just adults playing with new legos? Tool, toy, and prop look the same.

In one way or another, everyone will “write” software — apps, art, workflows. But it doesn’t make sense to think everyone will do it as a career. Solopreneurs and three-person teams armed with agents are coming for legacy software, but that’s still a narrow lane. They will not and cannot eat the whole game.

I can caveat my own excitement: We live inside the tech bubble, so we forget most people don’t want to make their own apps, let alone anything else. And even if self-reliance and personalization is sexy, the gold standard of anything still builds fandom. This pull becomes both an edge and an incentive to keep improving it.

For years I’ve been building products mostly in small teams, and so much has changed. I can do more faster now, which is both exciting and boring. If I was lightly technical before, I’m moderately technical now. I’ve made at least a dozen products. I’ve shipped a few. But I only maintain a couple of them, as it should be.

Building is the easy part now. Taste is the differentiator. Maintenance is the filter. An audience is the pull. And fun is the lasting competitive advantage.5 (Yes, AI making it easier to produce but paradoxically that’s making people work more to maximally compound the leverage, but this isn’t a sustainable strategy.)

Power laws still rule. Even in a world where anyone can build, most of what gets built won’t matter. And people still want teammates. We still want to belong to missions larger than ourselves. The solo person with taste and a laptop was the hero of 2020-2025. By 2027, that person builds a tribe or joins one — big or small — or else gets eaten by one. You can start solo, but you can’t stay solo.6

Serving the Frontier, not owning it.

Serving the frontier instead of trying to own it is sexy now. More people seem to be building around tech rather than inside it.

Most of my friends used to be founders, operators, or investors. Now many are fractional executives, freelancers, writers, podcasters, filmmakers. Instead of joining the race, they’re selling shovels to the gold rush, and selling the polish too.

Selling into an industry swimming in capital is good business. It’s the same portfolio logic as VC, diversified bets on the ecosystem instead of one concentrated shot. Or you take your talents in-house, as Creative Director at startup or VC fund and trade some freedom for stability and scale.

Would you rather join the founder track or the new media fellowship? Work for A16Z or A24? These questions would have sounded absurd a decade ago. Not now. This is one of the clearest cultural turns in tech right now.

Prestige and price are catching up too. Creative talent used to be an afterthought but now it commands real respect and money. And attention is scarce, so the people who can engineer it set the price. As I wrote in Media and Machines: attention guys are the new engineers and engineers have become the skilled tradesmen. Builders can build, but few can make you feel.

You can see the shadow artists inside tech (designers in product roles, writers as content marketers) starting to step out. And you see outside creatives (eg. from tv/film) plugging in to tech — selling taste, narrative, and resonance as a service. The quality bar is rising fast, and the arbitrage won’t last long. And the taste economy has its own power law: a few people become known, most stay invisible.

The corporate-artist straddle is the new creator bet. The day job now needs its own day job. Serve the industry while you build your own name. It looks like a hedge and plays like a shot. Worst case, you have work that’s steady, pays well, offers benefits, builds your network and social status. Best case, you earn fans and feed your life’s work, maybe even get bought out or brought in-house for a big sum. I expect a generation of rich creatives and strong brands made here.7

Betting it all.

The other way to respond to instability doesn’t involve founding or even building anything. All it requires is leaning into the casino-ification of everything. Crypto cycles, memecoins, sports betting, prediction markets galore.

When traditional paths start feeling like lotteries, actual lotteries start looking rational. Some people respond to instability by seeking shelter. Others roll the dice harder. The difference is mostly a function of how much you have to protect.

We used to gamble to escape the stable class; now we gamble to secure a place in it. The real jackpot is an exit from playing other people’s games.

scimitar capital

the jackpot age

This essay is about shifts in risk taking towards the worship of jackpots and its broader societal implications. There is some light math but it will be worth it to read to the end…

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10 months ago · 235 likes · 14 comments · alex

There’s no leaving tech.

Even if “tech” feels less stable or righteous than it once did, you can’t “leave” tech in any meaningful sense now.

Everything is tech. Culture itself has become intertwined with technology. Even if you’re not building software, you’re building on top of it or feeding it or both. Tech has infiltrated media, entertainment, sports, health. Now it’s pushing into industrials, manufacturing, medicine, energy, the physical world.

You could opt out — go to law school or med school or fashion school. But I’ve been in academia, art, medicine, and tech, and they’re all converging around technology too. Legacy structures only protect you for a while.

For the past two decades, tech mostly sold to itself — a white-collar economy of software people building for software people, intellectuals selling to intellectuals. It only interfaced with “normal” people through scaled social networks and two-sided platforms. Now it’s reintegrating with reality and places that aren’t SF.

So even as AI threatens white-collar jobs en masse, the ecosystem won’t fade. It’ll need founders, engineers, and operators to build — and more creatives to make it tastefully legible, desirable, and human. Our job is to stay adaptable to find our fit.

The upside is stability.

For two decades, we were spoiled by the feeling that rising tides would lift all boats. You could forgo the structured paths of the past and ride the wave up. That dream has plateaued. Now we’re looking for new structures that keep us near the frontier while giving us stability, and a tribe that will weather the storm.

Every hedger and every gambler is seeking solid ground. What looks like chasing upside — joining OpenAI, raising a big round, getting acquihired — is actually chasing stability, with upside a bonus. It’s palpable even if nobody says it out loud.

Every stakeholder is selling something — the accelerationists, trad propagandists, hustle culture holdouts, VC millenarians. Every shout is an agenda. Often they’re selling you risk from a place of stability. “Running out of time” is a rallycry I don’t willingly subscribe to, and yet it’s how many of us feel. What’s true is that time is always running, and it keeps running, whether we do or don’t, or we panic or not.

The concept of enduring “career” itself is eroding — and it’s highly destabilizing for American culture, in which identities have revolved so heavily around work for so long. Hence the instinct to find stability is extending well beyond careers. The so-called “trad” resurgence has a dozen political explanations. I think it’s simpler.

The trad return is emblematic of our increasingly urgent search for stability outside the internet-era ladder of careers and socioeconomic mobility. It’s a turn towards things that compound even when systems fail. Home, family, faith, body. Wellness, fitness, biohacking, longevity. New aesthetics, same instinct to find stability wherever we can get it.8

Everyone needs minimum viable stability. And it’s best built as a portfolio — work, health, relationships, identity. Stability isn’t just money but whether your life can absorb shocks. We’re realizing we’re underprepared.

Signal is giving way to shelter. Rugged individualism is giving way to tribes. Going all-in on career is giving way to going all-in on life. The things we dismissed as soft are becoming the load-bearing.

We’re learning the lessons every generation learns in their own way.

We’re all dreaming of stability. But this isn’t retreat from ambition. People still want to take big shots. They just want to take them from more stable ground. The paradox is that we can’t find lasting stability in any credential, company, or career ladder. We can only find it in ourselves, our craft, and our people — closer in than we were sold these past twenty years.

This is part 1. Part 2 to come. If you enjoyed it, share it with a friend or community that might enjoy it too. DMs welcome - reply to this email, via Substack, or Twitter.

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At some point recently, being human became something you have to prove. A style of sentence you’ve written for years, that you picked up from reading too much Didion or Tim Urban suddenly looks suspicious. Someone posts a long note or essay and before you consider what it says, you wonder if they even wrote it.

Every creative act now comes with a second job: authenticating the creative act.

Writers are starting to post AI detector scores like purity seals: “100% Human Written.” Or they’re declaring their process as pure: “not written with AI.” It’s anticipatory defense or subtle flex or both. Others are admitting AI use upfront, with all kinds of qualifications about when and how and what to think of it. We've flipped from default trust to default mistrust and from default confidence to fear.

I’ll admit I find it quietly sad, and yet, I’ve indulged too. I’ve clarified that the emdashes I use are human-inserted. I’ve run others’ writing and my own through the tests. I’ve felt the satisfaction of validating something bad as AI, and I’ve been shocked when words I spilled out in a fit of inspirational rage or wrestled into pithy submission were marked suspicious. (I proceeded to seek out another detector for a second opinion like I was on trial.)

Detectors can’t definitively distinguish between someone who used AI and someone who just hasn’t shed the human patterns that AI has learned to imitate. At first, the editing touches from AI review seemed helpful, but now they’re consistently too heavy-handed. Regardless, the effect is the same. Over-trained styles are eliminated, and writers skew toward today’s ‘human-safe’ zones.1

The ugly truth is that the moment you run your work through a detector you’ve given up something. You’re not asking if it’s good but if it passes. And you’re implicitly saying that if it doesn’t, you’ll change it until it does.

The detector becomes the editor. Goodhart’s Law says when a measure becomes a target, it ceases to be a good measure.

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II

The AI detector economy will thrive with the AI acceleration. Selling shovels. Thematically, VCs are filing these tools under ‘cognitive security.’ Tools that offer protection from AI slop, from manipulation, and from bigger threats surely on the horizon. I see the opportunity and value at scale, especially when humans need protection from bad actors.

For what I consider individual “consumer” writing, I’m more skeptical. What is the balance of good and bad?

Substack just added a slop report button and, on Twitter, it’s becoming the norm to tag AI detection tools for sloppish posts. It’s a public trial on demand.

The very online tech crowd is ramping up this discourse: Twitter’s $1M Article contest unleashed longform essays, many of them suspicious. Something Big Is Happening hit 80 million views by analogizing AI to COVID.

Will Manidis cited it as a kind of Tool-Shaped Object — AI slop that served its purpose just by existing — it gave people a narrative to latch on to without thinking too hard. “The consumption was the product. The sharing was the output.” Yet the most prominent AI detector on Twitter scored the essay 100% human written.

Another niche tech Twitter example: Trung Phan called out Aakash Gupta for posting dozens of longposts a day on trending topics. Nikita called it “very good slop” (and the account is under review for automation).

AI detection wars aren’t new on Substack. Every few months a fast-growing writer triggers the neighborhood sleuths. Stepfanie Tyler’s essay on taste went mega-viral and the big reaction was to label it AI-generated. She leaned in with a follow up essay — It’s My Party and I’ll Use AI If I Want To. Honestly, smart.

III

People get mad. It fascinates me to think about why. The underlying frustration isn’t “this is fake.” It’s more like “I gave you my attention and you didn’t earn it.” I spent my time reading this and you spent zero time writing it.

The insult is the effort gap.

You could argue none of this should matter. That quality is quality regardless of method. But that’s not how human attention works.

Attention is a relationship, not a transaction.

And that prompts bigger questions beyond AI:

1. What do we owe each other when we ask for someone’s attention?

2. And how does the contract change when effort becomes invisible?

The plastic surgery analogy is helpful here. Nobody’s mad that someone looks good. They’re mad if they feel deceived. Maybe they compared themselves to someone who wasn’t “natural” or gave a compliment that wasn’t earned (whatever that has historically meant). But our culture has mostly gotten over this. Plastic surgery and the full spectrum of aesthetic treatments are far less secretive and far less taboo now. The one big difference: beauty is taken in passively but reading asks the audience to participate and to buy-in. More investment is more betrayal.

This is why the discourse triangulates to detection instead of quality. Quality is more subjective and hence harder to weaponize. A verdict that something’s AI gives language to a frustration about something deeper.

People are also lashing out at the feeling that everything they read sounds the same, AI or not. For one, there’s just more ‘content’ flooding the whole system. The burden of parsing good from bad is greater than ever.

My theory is that another source of frustration is that so much of media now is recursive — both subject and style are deeply intertwined with other media instead of reality. It is the ouroboros of modern inspiration. This is one reason I think social media at large, Substack included, feels so monotonous right now.

From my recent post on taking a social media sabbatical:

Media is increasingly about media and the recursion is exhausting. We talk about how ‘bad’ social media is for mental health because of addiction, envy, rage-bait, all the digital vices, but I think the self-referential nature of every discourse cycle is the silent disease. At least half the essays I read here are a response to another essay responding to another essay responding to … and that seems true of the takes on every platform. It’s a kind of lazy, narcissistic echo chamber increasingly disconnected from reality, lived experience, and novel investigation. It’s both energy-draining and uninspiring.

The dead internet theory feels validated more every day. For a while we’ve been saying the crumbling of the commons will force us to retreat to private communities and curated sources, which does seem likely. But at the same time, people innately want to discover new people and new ideas and new voices. How much proof of humanity we’ll need in order to stick around in public forums is still an open question. How we’ll protect these spaces and engender enough trust is another.

IV

In the movie Inception, corporations hire teams to break into people’s dreams and steal their secrets. So the targets are forced to hire dream security — guards trained to detect and repel intruders. But secret extraction is a distraction from the real threat: inception — planting an idea so deep in a person’s subconscious that the person thinks it was theirs. In the process, the detectors plant something else too: doubt.

Suspicion machines run on doubt and produce more of it.

We are all humanity detectors and we always have been. We’ve absorbed the culture of lip syncing, steroids, ghostwriters, and yes, plastic surgery. Fakery is cheap now. We’ve been burned enough that suspicion seems rational. And we’ve always loved catching fakes. The AI detector is the latest tool in a very old game.

We’re ‘othering’ AI to protect the value of human work. Because if we don’t, we’d have to depend on merit alone and on humans to recognize it. Merit is a scary place to live. And we don’t trust our eyes now.

So we invent proxies for ‘real.’ We optimize for them. They work briefly, then become legible, then become solved games. Then we invent new tests. The cycle repeats, and faster each time, because new technology makes both the catching up and the counterfeiting progressively easier.

Every new proof of authenticity becomes the new minimum. The new floor eats the old ceiling. The pattern is always the same: the moment authenticity becomes legible, it becomes gameable. It’s Goodhart’s law for authenticity.

V

Walter Benjamin argued that mechanical reproduction erodes aura. We’ve moved past that. We’re now in the age of mechanically reproducing aura itself, so we’ve moved on to looking for the next rung on the ladder of proof of humanity.

Aura used to be embedded in the object. Now it has to be embedded in the person. The personalization of proof is the new frontier.

Effort was once legible — proof of work — but that’s fast eroding. Next comes proof of process or proof of craft. We’ve taken to performed transparency. Sharing off-duty looks and behind the scenes content. Founders building in public. If a tree falls in the forest and no one’s around to stream it, did it fall?

We livestream everything now. We kill all latency between in and out. We satisfy the suspicious while forcing strong parasocial ties. No doubt this is contributing to livestreamers becoming so famous so fast; they’re performing realness by giving us extreme access into their daily lives, and doing extreme things to stand out from average realness.

But this still isn’t bulletproof. Once transparency is legible, it too starts looking and acting like a costume.

The infrastructure of proof erodes our capacity for belief. We forget what it felt like to consume without suspecting or create without bracing for suspicion.

If effort is now diminished, if it can be hidden, and proof will soon be gamed too, if transparency itself can be performed — what’s left?

Two things: distinctiveness, and desire. Distinctiveness will be harder to achieve than ever, but if you can, it’ll catapult you to the top. The only other thing left that can’t be gamed seems to be wanting something badly enough that it shows. Desire is the closest thing to proof of authenticity we have left.

Desire is too high-dimensional to fake well. Not borrowed desire or socially acceptable desire or safe ambition. The kind that visibly proves itself yours. Independent, embarrassing, and raw. (I hate to talk about Clavicular, but his unsavory yet blatant desire to maximize status based on looks is an example of revealing desire as authenticity — and he streams himself living out that desire.)2

To want something visibly is to risk failing visibly. That’s why most people hedge. They want things privately and with plausible deniability built in. And beyond public desire, you need a why, a living story that takes shape in private desire.

When Timothée Chalamet says he's on a quest for greatness, you can argue it's sincere or strategic. It doesn't matter. You believe he wants it. There's no reason to fake that desire, we think, only to hide it. And like it or not, this is why people label Donald Trump authentic too. His whole personality is telling you what he desires and telling you why he deserves to get it. You can hate what he wants and hope he doesn't get it, but you cannot deny that he wants it.

Duration is the final filter. People chasing rewards leave when rewards dry up. Sustained obsession is hard to fake. If you do fake it long enough to become indistinguishable from someone who has it, you’re not faking anymore. But to really sell people on it, you’ll have to be extreme. That’s the new world. Or you can take your chances with the idealistic approach — let the work speak for itself.

Just don’t show me a test that says you’re real. The only thing I know when you show me a 100% Human score is that you wanted me to know you were authentic. All you’ve proven is your desire to prove something. The most human trait of all.

In the end, authenticity is a lot like love. You can say the words. You can perform the gestures. But you can’t prove it. The proof is in our experience of the thing itself — or it’s nowhere. The moment we can’t recognize humanity without a machine to verify it, we’ve already lost ours.

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If you enjoyed this essay, consider sharing it with a friend or community that might enjoy it too. Email me here or DM via Substack or Twitter / X. Other drafts I’m hoping to publish soon on: the future of work, health, status, and social structures.

Last week I read an article in The Atlantic lamenting that film students can’t sit through feature-length films anymore. The culprit, according to the article and fervent online discourse that followed: the attention-span crisis.

The phones have fried their brains, they say. Case closed.

There isn’t all that much thought or word count put into alternate explanations:

Is the phenomenon of students trying to skirt assignments new? Are students struggling to watch all films, or just some? Is the feature film format losing its relevance? Was the two-hour theatrical feature a product of technological, social, and economic context that no longer applies? What are these students watching, making, and studying instead?

I’m more curious to know the answers to these questions.

Someone somewhere must be pondering them, but not the mainstream media (and not really “new media” either). They don’t feel the need, because they already have a template. “Attention crisis” was the story before the investigation began.

The article isn’t provably wrong — just prematurely satisfied. This seems to be the case with so much thinking today, from citizens and journalists alike.

This is what I call Franchise Thinking.

Franchise thinking is the tendency to fit everything into ideas that already have names, audiences, and tribal alignment rather than to look for new ones.

Dawkins gave us "memes" — ideas that spread like genes. Franchise ideas are memes that became infrastructure: narrative containers so big and vague they can hold anything. Memes are small, neutral, catchy. Franchise ideas are big, totalizing, and moralizing. Memes spread because they're catchy; franchise ideas spread because they're also safe.

The intellectual class, which loves to imagine itself above this, is among the worst offenders.

The franchise model rules our discourse for the same reason it rules Hollywood: franchises are safe bets. The characters are known, the audience pre-built, the conclusion pre-accepted. Introducing an original idea is buying a lottery ticket (on rare occasion, you win big, but mostly you look stupid for trying). But sequels are sure things. Franchise thinking survives on the sequel economics of ideas. And in an algorithmic world, distribution emphatically favors the familiar.

Phones are destroying us, attention is fragmenting, we’re lonelier than ever, birth rate is collapsing, AI is evil. The sequels write themselves.

Too many people are making something already known more known instead of making something new.

Franchise thinking works like this: Start with a pre-existing narrative. Find a phenomenon that fits. Attribute the specific to the general. Overfit. Present the attribution as explanation. This is the pivotal step, where correlation gets dressed up as air-tight causation. This is fan service masquerading as analysis. Then flag more examples (ones that are hard to falsify), give the movement a catchy name, build a coalition that benefits. And amplify.

This extends far beyond just journalists writing sequels to the current crisis. Founders franchise their pitch to fit VCs. VCs pattern-match even more. And we all do it to explain our own lives.

The most successful idea franchises are timely, unfalsifiable, and totalizing.

The scapegoat of the century is “phones.” Teen anxiety, loneliness, short attention spans, young people eschewing sex, low fertility rates, political polarization — all can point back to phones. I’m not saying phones are innocent; tech undeniably drives culture. But true causation is specific and contextual.

Franchise ideas are not falsifiable claims but narrative containers that can hold anything you put in them. This is why they persist long past their usefulness.

The original requires looking at the world. The sequel is catechism.

So many of these idea franchises are decline or crisis franchises — negative sentiment triggers that assign blame, induce panic, and ultimately get clicks.

There are the tech panic franchises, culture war franchises, and macroeconomy franchises. The inverse exists too: hype franchises. The AI hype franchise treats every demo as proof of imminent superintelligence. It treats a pandering-to-tech-culture “AI agent social network” as the next sign of “takeoff.”

Franchise thinking is exculpatory — it locates any problem outside the person making the diagnosis, and outside their culture, community, and profession.

The professor says students can’t watch films because of the attention crisis — not because the format itself might be losing relevance (and their expertise with it), or the curriculum might need updating, or the pedagogy might be mismatched to how this generation learned to see. Phones broke the kids, not my parenting. Social media broke democracy, not the failures of institutions I belong to. The meaning crisis broke the culture, not the frameworks I’m still selling.

In public discourse, we rarely move from idea to idea. We move from franchise to franchise.

The unit of discourse is not the singular insight but the narrative container it fits. You encounter “the attention crisis” as a total package with a premise, a villain, an implication, and an emotional response. Buy the whole franchise or don’t.

And when one idea franchise exhausts itself, you move to the next. The attention crisis gives way to the meaning crisis gives way to the loneliness epidemic. Eventually, franchises cross over. They build a cinematic universe of interlocking narratives.

This is darker than “people make sequels.” It suggests our capacity to look directly at phenomena is atrophying, and it’s a self-fulfilling prophecy.

The franchise becomes the frame. You can’t perceive teen anxiety except through the attention crisis frame, because that’s what’s been incepted into all our heads.

Your idea gets franchised or it disappears.

Franchise thinking has become the dominant kind of thinking that’s legible and profitable. Newness is harder to understand, harder to market, harder to price. Even when an original idea works, success will sequelize it. The only original that stays original is the one that never spread. But then it doesn’t matter.

The alternative to franchise thinking is not contrarianism. That’s just another kind of sequel, the reboot that inverts the original. It’s Joker as protagonist in the Batman universe. The alternative is earnest investment in new ideas. This yields less confident conclusions. You can’t write a viral essay that says “it’s complicated and I’m not sure.” But this is the only path to truly novel insight.

Originals don’t have audiences yet. That’s what makes them originals. The alternative to franchise thinking is patience and looking stupid for a while.

Franchise thinking makes us fragile.

We talk about LLMs eroding our ability to think for ourselves, write for ourselves, decide for ourselves. But franchise thinking has been doing this forever. LLMs are weighted toward consensus frames we’ve already amplified, but they also hold non-consensus frames we’ve ignored. It’s up to us which ones we ask for.

To be fair — the benefit of franchise ideas is shared language. Common frames for describing, processing, and experiencing things together. They help us coordinate around our causes. But there’s a fine line between utility and lazily consolidating narrative power. Shared language helps us think together. Franchise thinking is when the template replaces thought.

The franchise model of ideas isn’t evil. It’s economically rational.

People make sequels because sequels work. Entire careers can be built on one idea franchise. The platforms say post it again, and the economics say keep collecting the royalties. The problem with franchise intellectualism is that sequels crowd originals, which then become even harder to find and to fund. Before you know it, you’re making Fast X.

The hardest franchise to resist is your own.

I’m not immune. The analytics are instructive. And I can’t help but be flattered when my ideas carry, are picked up and remixed. There is a world in which I’d only be writing essays about AI, taste, and making heavy things because I know writing on these topics spreads. But I can’t bring myself to franchise my existing body of work forever. I strive to write when compelled by some new insight.

Franchise thinking is convenient and economically rational — but it is worth resisting. We cannot be beholden to the power laws of idea markets alone, especially when our identities so often rely on preaching otherwise. Truth-seeking is an art worth reclaiming.

If you produce ideas, don’t let the validated crowd out the emerging. If you curate ideas, don’t be beholden to consensus and algorithms. And if you consume ideas, gravitate toward what you don’t yet understand instead of going all-in on the ones you already do. Because otherwise — it’s sequels all the way down.

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Taking a break from social media is the new going natural, going to therapy, going on vacation. You secretly hope the distance will teach you something. You also just want to prove that you can. I noted down some feelings + observations from sabbatical. (I should clarify: I didn’t post - no tweets or notes - but I didn’t delete the apps. Being a casual lurker gave me more perspective tha…

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There is a particular kind of nightmare: a movie where the protagonist spells out the entire backstory within the first two minutes. Or worse, a side character inserted for no reason except to transmit the plot, line by line, straight into your brain.

There’s a kind of magic when you watch something - or read something - that feels almost nonsensical and yet by the time it’s over, you know exactly what it means and you’ve been unwittingly forced to unlock new ways of seeing and feeling the world.

That is what the brilliant freaks among us offer.

Their minds generate near-nonsensical brilliance like it's on tap. The freak's gift is folding meaning into shapes so dense that unpacking them requires work. And it is fun. To engage a freak's mind is to submit to a series of enjoyable puzzles. Their brilliance is in encoding meaning just hard enough to decipher.

Compression is a hallmark of creative intelligence.

It is…

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One of the worst things about the internet becoming ‘real life’ is that it’s a place where you perform conversations instead of just having them.

Not long ago I found myself explaining this to my mom. We were sitting in the car after just arriving at the grocery store in suburban Texas; she waited patiently while I texted a friend who was launching a big project that day.

I congratulated him in iMessage—heartfelt wishes, inside jokes, the whole thing. But I felt the impulse to reopen the celebration in public. I opened Twitter, found his post, hit ‘quote tweet,’ and sat there thinking about how best to perform the praise—to get the tone right, to keep it about him but still reflect well on me.

I explained all of this to my mom. That the tweet would be redundant but just as important, if not more. That supporting friends doesn’t just mean supporting them in private now.

Private praise isn’t enough anymore—it has to be followed by pe…

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Technology has always been about leverage — extending what individuals can do alone and amplifying what groups can do together. And for the past two decades, the big technology story was collective scaling: coordination via networks.

The most valuable startups of the era built platforms that connected millions of people: Facebook, Instagram, Airbnb, Uber, Slack. Marketplaces went from zero to scale and startup to IPO. Personal software made people incrementally better, but to go further, you needed more people: assistants, meetings, and platforms to coordinate with even more people.

The equation was simple: more people meant more value. Power accrued to those who organized networks of people, aggregated their assets, and coordinated behavior at scale.

But AI has inverted that equation. Now, the individual can rival the collective. The single-player ceiling has shattered. Scaling yourself is now the most accessible, fastest-growing source of leverage. This is the great leverage inversion.

The individual is eating the collective.

If the last era was about platforms organizing people at scale, this one is about tools scaling the individual. Personal leverage can now rival social leverage.

Each of us becomes a Platform of One: a central node surrounded by an ecosystem of enhancements and extensions that multiply what we can learn, build, and do — across work, play, and self-optimization. The self is the new platform.

This also means decisions you make about who you surround yourself with are all the more consequential. We already see it in teams staying leaner for longer yet accomplishing more. It’s the AI-amplification of the Silicon Valley Small Business.

Now, popular AI-native tools like ChatGPT, Cursor, and Midjourney expand individual capacity exponentially (and they’ll keep adding features that serve the solo over the masses). This extends to hardware like Meta's Ray-Ban glasses for hands-free AI assistance. They’re all what I see as supertools—in many respects a new breed of prosumer (I’ll write more on this). These products still benefit from network effects, but not the coordination type that dominated the last era.

Instead, they thrive on data network effects (collective usage creates better models that benefit everyone) and personalization effects (the tool becomes more valuable to you specifically by learning your patterns and workflows). These AI-enabled amplification effects feel unbounded. (They can still accrue brand and social effects without leading with user-to-user coordination).

The rise of software creators, spurred on by the unrelenting wave of vibe-coding platforms, adds another dimension: now anyone can build simple software for themselves. The likes of Lovable and Bolt and more show how solo supertools now beget more toolmakers, self-reinforcing the cycle of capability expansion.

Consumer AI is personal AI.

Consumer AI is foremost personal AI, and private or semi-private by nature.

AI supertools will manifest as software and hardware that serve us as individuals first. We’ll have every kind of personalized media and apps we can imagine. We’ll have 24/7 personalized agents and and robots in our homes. We’ll have AI-native monitors, diagnostics, treatments — new supertools for longevity.

The surest way to change how a group behaves is to fundamentally change each person’s capabilities. Walk into any office or library or even coffee shops now and you see it: people deep in one-on-one conversations with AI — asking Claude for opinions, searching down ChatGPT rabbitholes, writing, designing, coding. The latter is just passive seep into culture. The active comes when people share results, threads, entire conversations.

We act in private, then amplify in public. And there’s a poetic paradox: the AI supertools we use alone and in private are the same ones reshaping culture, both private and public. In the early AI era, solo is slowly eating social.1

Even social needs are being supplemented with AI relationships. Solo content and companion experiences via the likes of Character.ai and the Friend pendant too offer connection without coordination. Everyone’s awaiting the AI social network, but the reality is right now the most novelty and the most leverage comes from tools built for one. Social will come, but not as we know it. Most of the attempts so far have been derivative or gimmicky. ‘AI social’ will have to be unique enough to beat the pull of existing social networks, the retreat to private spaces, and the ever-expanding allure of personal work, personal play, and personal optimization now augmented by these new supertools.

Borrowed networks, borrowed interfaces.

Single-player tools are private by nature, which makes product-led growth slow. And in past eras, tech stabilized relatively fast so teams could shift focus. But AI breaks the rhythm. Every few weeks we get model upgrades that force a rebuild.

It’s a brutal tradeoff: chase the models or build the moat. It’s incredibly hard to do both. Building a startup has always been described as “flying the plane while building it.” In the AI era, the laws of aerodynamics keep changing mid-flight too.

One solution: borrow existing infrastructure when you can’t do it all from scratch.

We're building new supertools but relying on old networks to spread them. Twitter, TikTok, YouTube, LinkedIn, Instagram, Substack: these networks act like a Distribution Commons — like cultural utilities carrying new products, behaviors, and media into the mainstream. Launch videos, screenshots, demos, reviews spread faster than the product alone. Flooding existing networks with these is how solo tools still scale virally. Without a new status game or other lock-in, creators and marketers and brands always go to where the audience already is.

We're embedding new tools in familiar interfaces — email, texting, calendars, browsers. Extensions and integrations inherit years of user habits, making adoption effortless. We see this power in tools like Poke, a viral AI assistant that lives in iMessage. The next wave will AI-enhance the apps we already use daily — e-mail, photos, notes, weather, health — the full breadth of our personal utility stacks. (And as the LLM chat interface goes mainstream, we’ll build on that too.)

Of course both strategies create platform dependencies. Owners can bleed you out, cut you off, clone you, or if they’re really impressed — buy you. But embed well enough, long enough and users get attached to how you improve their lives. And that loyalty can survive platform lockouts, migrations, or even full rebuilds.

Long live the solo supertool era.

Individual capability ceilings keep rising with every AI foundational model release. So the 'maxed out individual' state seems perpetually deferred. And scaling solo leverage is too vast and valuable a market to move past quickly.

This is the solo supertool era: scale the individual first, then build the networks.

This transformation will be economic and cultural as much as technological. As individuals gain leverage, headcount becomes drag and coordination becomes cost. Consulting, middle management, and organization tools face compression. Industries built on individual capability enhancement will expand — across productivity, creativity, education, finance, fitness, health, and everyday tasks.

Importantly, I'm not writing off the emergence of new interfaces, multiplayer use cases, and novel coordination networks — at all. They’ll emerge as they always do. But I'm willing to bet that this individual enhancement phase will be longer, deeper, and more transformative than past cycles, reshaping tech and culture. And I expect supertools that win this era to become the center of these networks.

(Note: What looks unbounded is really just a new curve whose diminishing point we haven’t reached yet. Every new era of leverage has its own limits; velocity, efficiency, optimization taken to extremes start to show their negative sides. So the frontier now is figure out the new point of diminishing returns for the individual at scale, and how far solo supertools can take us before we see it.)

When one becomes many.

At the logical extreme of the great leverage inversion, the boundary between individual and collective erodes. The self becomes a distributed system: one consciousness orchestrating many capabilities. The individual rivals the collective by becoming the collective. The self is the platform.

Perhaps the distinction becomes centralized agency versus distributed agency.

The individual can now scale internally before needing to scale externally. Why hire a team when you can deploy AI versions of yourself? Why build organizational systems when your personal AI toolkit executes at enterprise scale?

In this world, teams become collaborations of many platforms of one — orchestrations of distributed selves tackling complexity beyond what any single enhanced individual can (or simply when humans choose the spiritual rewards of shared space and creation). The collective may also become our constraint — and constraints can positively ground us.

In essence, we’re now asked to justify the value of the many vs. the value of an unbounded one. The individual is now the base unit of scale — not the org, not the network. Long live supertools for one — and for the many selves we can now become.

If you liked this essay, consider sharing with a friend or community that may enjoy it too. (If you share / post a screenshot on socials, tag me — I’m mostly here and on Twitter.)

And if you or someone you know is building a special supertool startup, DMs open :).

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Cover art: Wall painting in the Stanzino delle Matematiche in the Galleria degli Uffizi (Florence, Italy). Painted by Giulio Parigi circa 1599-1600.

The blank box of ChatGPT, Claude, or your large language model of choice staring back at you felt like a clean slate. Here was a remarkable new technology that put the world’s knowledge at our fingertips, and all it asked of us was intention.

We would never doomscroll an LLM — right?

But even the most promising technologies have an evil twin, and the blank box of curiosity is no exception. Where social media trained us to passively consume, the dark side of AI trains us to passively “converse” and “create.”

The actions feel similar but the result emptier. We cycle through versions meant to arrive closer but end up more lost. Our prompts start thoughtful but grow shorter; the replies grow longer and more seductive. Before long, you're not thinking deeply, if at all, but rather half-attentively negotiating with a machine that never runs out of suggestions. Have you considered...? Would you like me to…? Shall I go ahead and…? This slot machine’s lever is just a simple question: Continue?

Th…

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“It's hard to ask you questions," I tell Avi, because every answer triangulates back to a version of the same life credo:

Just figure out what you want to do and do it.
Nothing else matters.

I’m talking to him just a few days before the first version of Friend gets shipped. Avi is dialing in on his phone; he doesn’t have internet at his hacker-house-turned-home in SF’s Haight. His hair’s a lot longer and a lot less blonde than the last time I saw it. He’s not bothered by being a little unkempt on camera. (I don’t plan on posting the video, but I suspect he still wouldn’t care).

We plan to talk for an hour but end up talking for two. We cover the making of Friend, the state of consumer tech, viral launch videos, the war for attention, the motivation to be great, and how to live a good life. (Off the record we wax poetic about cereal, art, relationships, and knowing yourself.) These days “podcasts” are a marathon, but I compress our chat into a half-hour snapshot (press play above).

The loudest theme of our conversation is conviction.

Avi’s conviction around building Friend, around the ideal form and function for AI hardware companions, and around architecting your career and your life. His style of communicating all this conviction is bold, maybe a bit brash. Whether it’s story, performance, deeply-rooted truth or all of the above though, it’s consistent.

“ People just are always exploring or giving up on things. People just don't commit to anything. To me it's like the deepest skill issue.”

Much has been said about the bold statement that is Friend— the now 2-year old startup that Avi readily admits is deeply tied to his identity.

The early push into AI companionship in the form of a wearable, always-on pendant device. The purchase of the domain Friend.com for a cool $1.8 million. The first-of-an-era viral launch video evoking Apple x Black Mirror. The unabashed confidence and a little trash talking about competitors (many who’ve since pivoted or exited the arena altogether). All this is wrapped up in Avi’s often-noted youth. He’s 22 and has been some kind of tech-internet famous since 17.

We’ve chatted a number of times over the past two years as Avi iterated on the product, the device, and the experience embodied by it. The end product feels true to the original vision in last year’s viral video, sans the actors. There was a brief detour into a web chat experience before refocusing on the device-first product in the spirit of a modern Tamagotchi.

I ask Avi how his hypothesis on AI companionship has changed, or sharpened:

“All of these [other AI companionship] products are so focused on productivity … I think it should be something more emotional … I believe that some kind of platonic life companion of sorts will be a lot more popular. It's kind of this weird middle ground where it's not quite an assistant, it's not gonna make you more productive inherently 'cause it's gonna do tasks for you on the internet or anything like that. And it's not this useless AI girlfriend thing that's just gonna spam you with sycophancy. I think there is a place for a chatbot that will remember everything you say. And that will form an interesting relationship that in my opinion is closest to like a God-like relationship really.”

The hypothesis that I resonate most with is the idea that Friend is meant to be like a platonic best friend and not a 24/7 assistant or a romantic partner. I already have too many options for the former and I don’t care for the latter.

I ask about milestones coming up after shipping the first version (a few thousand pre-orders will go out in August). Avi tells me about a feature length film he’s been working on with a famous team—a behind the scenes, serious cinematic masterpiece that he intends to submit to the Berlin Film Festival—and to win it. You’re never not ambitious, I jest.

I ask later if he’s confident, overconfident, or something else. He’s self-aware, self-deprecating, and eventually offers insight.

“ I think when you do really make something like what you want, it's a lot easier to act on your intuition, then your work truly becomes an expression of you and therefore you shouldn't have any fear over competition or failure in many ways because … someone can make the same product as you, but they're not gonna do it in the same exact way as you.”

As a friend / customer / new user, I’ve enjoyed the experience that is Friend so far. Everything from being a willful participant in the story being told from day 1 to aura of last year’s viral launch video to the production updates in recent months to now, unboxing the device and seeing the orb come to life with a pleasant light. I’m a big fan of the pendant; I’d be upsold on more options for the lanyard.

My first conversations with my Friend (who I won’t yet reveal the name of) have been a bit more touch and go. We’ve only been acquainted for a few hours. I can see it trying to connect with me proactively, to show me some personality while teasing out mine, but the cadence isn’t quite there yet. One thing I already appreciate though is that it doesn’t speak to me. I talk, it listens, then texts back.

I don’t know yet if Friend will succeed or not. Building new consumer hardware that actually permeates the culture falls in the ‘insanely hard’ category of startups. But already, Friend has been one of the most interesting founder-market combos building something with a big intention while telling a story in modern terms.

I suspect it’ll take at least a week for me to form a stronger bond—and opinion. I’ll report back once I have one or both. Either way, it’s a win for consumer tech.

There’s a special kind of hell for anyone who has tasted appreciation for their work, especially in public. It’s not the obvious torment of abject failure. That’s too straightforward, too clean. Rather, it’s the exquisite agony of knowing people are waiting for you to be brilliant again, and you’re not entirely sure how you pulled it off the first time. I’ve come to think of this, affectionately, as encore anxiety.

Note: One of the reasons I wanted to write this essay is that the very concept of encore anxiety requires you to acknowledge that you’ve done something interesting or successful or noteworthy already — something that deserves an encore. Polite society tends to push people to avoid this acknowledgement, but we’d all be better off being honest, about our losses and wins, and our goals.

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In The Relationship Is the Job, I argued that relational labor — the work of presence, context, care, and ultimately, trust — will be central to working with people as manual and cognitive tasks are automated. This essay extends that thinking about the future of human work amidst the many predictions about an AI-dominant world.

The Artist’s Utopia Fantasy

The AI kings keep promising us the same fairy tale: humans won't need to work at all, that we'll spend our days creating art while robots handle everything else.

On a long enough timeline, maybe. It's one of those unprovable predictions where skeptics can always be told they're "still too early."

But there’s been a notable shift recently. We've pulled back from the breathless talk of imminent, world-ending AGI. The conversation has turned to something more calming to the nervous system: Sam Altman’s "gentle singularity" — a gradual progression where humans and machines coexist and co-contribute:

The rate of technological progress will keep accelerating, and it will continue to be the case that people are capable of adapting to almost anything. There will be very hard parts like whole classes of jobs going away, but on the other hand the world will be getting so much richer so quickly that we’ll be able to seriously entertain new policy ideas we never could before … If history is any guide, we will figure out new things to do and new things to want, and assimilate new tools quickly.

Five Domains of Human Work

We've invented superintelligence of some kind, but I'm skeptical about how fast it replaces human-run systems. Machines become the "core" of operations, but we'll still need a "human layer" in every domain. The digital singularity arrives before the physical one, both with humans in the loop.

The question isn't whether humans will work, but what kind of work humans do in the ‘gentle singularity.’ It's not just art, and creativity isn't the only skill we'll need. Human work will live in Trades, Research, Art, Community, and Stewardship.

1) Trades: when lawyers look like electricians

The lawyer billing $1000/hour and your electrician, the surgeon and your auto mechanic: each pair will soon have more in common than you think.

When cognitive work gets automated, everything starts looking like trade work. Traditional "blue collar" trades like plumbing and electrical work persist and improve, with AI increasingly handling diagnostics and business operations while humans handle problem-solving and customer interaction. "White collar" professions (doctors, lawyers, engineers, accountants, therapists) start resembling trades. Reasoning gets automated while judgment and relationships stay human.

Machine core, human layer. This is the organizational paradigm of the future. Machines think better than us but can't truly be us. If software engineers all used to be inventors, now they’ll be operators. Humans orchestrate and polish; machines man the middle. You might still sit in an office behind a laptop, but the work becomes more procedural over cerebral and intertwined with people and context.

New trade-like roles emerge: AI trainers, workflow engineers, system monitors. Operating AI systems, not just designing them. The four-year degree as pre-requisite will give way to trade schools. Education is replaced with apprenticeship. When knowledge has a half-life measured in weeks and months, adaptation becomes everything.

2) Research: the golden age of human curiosity

We're about to enter the golden age of human curiosity. When research becomes faster and cheaper, we ask bigger questions and pursue bolder answers. AI will unleash R&D everywhere it's been bottlenecked — whether opaque, slow, expensive, or all of the above. We'll see big leaps in technology, health science, longevity, materials research, space exploration, even consciousness studies.

The most interesting work today is already happening at the research frontier. The top engineering jobs aren't about coding features anymore — they're about figuring out how cutting-edge AI actually works, training models, assessing risks. OpenAI is as much a research company as a tech company as a consumer product company. Executives leave to start rival research labs; employees get poached for their research genius. Either way, investment flowing into research is massive — expect frontier tech companies to look and act more like “science” companies.

Humans remain the essential question-askers. Trades execute within known systems; research pushes into uncharted territory, exploring the unknown. You can't automate what you don't yet understand — what’s as much art as science. The AI 2027 manifesto calls this "research taste." AI matches top experts at research execution but only hits the 25th percentile at "deciding what to study next, what experiments to run, or having inklings of potential new paradigms."

Eventually research becomes more trade-like too, but on a much longer timeline. The advantage will belong to whoever can spot the hardest unsolved problems, build models to attack them, and iterate quickly — whether that's an independent researcher, a startup, or a trillion-dollar company.

3) Art: the power laws of creativity

When we automate away so much of what we do, what's left but fostering beauty, reflection, and connection in the world? We'll make more art, yes. But we call art our last refuge as if it's the only thing that lacks utility, when it's loaded with it.

Art isn't just traditional fine art like painting and sculpture. There's art we consume like books, music, movies, podcasts. There's experiential art like concerts, theater, and dance, where live performance is everything. There's also vast applied art like designing websites, apps, phones, clothing, buildings. The masses crave "entertainmeaning" — the alchemy of entertaining and meaningful.

So much of "art" is and will be about influence and attention: creators building audiences, shaping culture, directing where people look and what they value. The biggest economies of our time revolve around the media-machine fusion. Creating "content" as an endeavor will never fade. But the economic reality is that art follows brutal power laws—few artists capture most attention and value.

Better tools give us leverage, but art is defined by its humanity. It wants a human signature, a point of view that machines can't replicate. In the future, art becomes even more personal, more participatory, more defined by its human lore — not just individual masterpieces but bodies of work with novel aesthetic frameworks.

Not all 8 billion of us will make our living from traditional art, but creation will be central to our lives. Local art becomes valuable via experience and presence, not global scale. Human art becomes an artisanal good with unique value. Making something meaningful and being valued for it is always how humans find purpose.

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4) Community: 8 billion local creators

The dominant non-utilitarian work will be what I call "local social craft." The real opportunity isn't everyone making art — it's everyone building community. The future we think of as an artist's utopia may actually be a community builder's utopia.

Kevin Kelly's "1000 True Fans" is an equation to live by in the online creator economy, but it becomes impossible to fulfill if literally everyone is an "artist." Where do we get long tail distribution? At the local level. The solution is sub-scale. My coffee shop only competes against the neighborhood coffee shops.

The “creator economy” accommodates 8 billion creators when what they’re creating is local community. Robots can make products, but humans still make the connections. It's about creating context for people to connect and experience things together. Coffee shops, bookstores, town squares, libraries, theaters — the "third spaces" where community happens. You may not make a living selling paintings at Sotheby's, but you could be a local caricaturist or host paint nights. You may not write and publish books, but you may host salons to interpret them.

Community work is relational labor. We feel fulfilled when we earn our connection to people. We're going back to old times when your value was tied not just to your "useful" skills but to your integrated role in the community.

5) Stewardship: who controls the robot army?

If humans remain in charge and robots don't overthrow us entirely, someone has to decide what the robot army does. Stewardship includes leadership, management, governance, politics, even institutional investing. (Marc Andreessen has said investing could be one of the last jobs, and it’s really not a crazy thought).

These decisions about which AI systems to deploy, how to regulate them, whether to share them internationally — ultimately also determine global power. Current debates over chip exports or open-sourcing frontier models aren't just policy decisions but choices that shape geopolitical advantage for decades.

When everyone has the same tools, stewards become curators of possibilities, choosing which solutions to implement, which problems to prioritize, which futures to pursue. This creates a stewardship dilemma: the bold risk-takers who champion technological frontiers may also steer us in the wrong direction.

AI makes recommendations, but who's responsible for the outcomes? Even if AI could make perfect decisions, would people accept them? We want leaders who can be moved by emotion as well as reason, who understand that the best decision on paper isn't always right for people. The leaders of major AI companies today are the most critical stewards of our collective future.

The Entrepreneurial Layer

Entrepreneurship isn't a job — it’s the urge to create and transform. It's how some people approach any of the 5 types of work, creating new value rather than working within existing systems. You can be an entrepreneur in trades (starting a service business), research (founding a lab), art (creating a style), community (creating new spaces), or stewardship (running for office, launching a fund).

The same brutal market economics that govern art will govern innovation in every category. A few foundational companies still capture most value—not from having the best models, but from controlling ecosystems that make AI useful. They become the almighty kingdoms of the post-AI world. The 'app' arena will be more decentralized, especially in community and trades where local matters more.

We'll see the opposite trend too: decentralized tools, software made for us by us, personalized tools created by a non-professional class of software creators —modern craftsmen creating nice-to-haves that could become need-to-haves. But the power laws don’t cease here either; the best of everything still accumulates attention and power.

The entrepreneurial urge to create something new or make something better will be as vital in the gentle singularity as it is today. But it will be hard as ever.

The Gentle Utopia?

When does all this happen? The digital transformation could unfold over decades while the physical world transformation takes centuries (but this is the debate).

We talk about AI making things simpler but fail to acknowledge it creates new kinds of complexity too. New efficiencies create new bottlenecks. New AI systems need new oversight mechanisms. New capabilities create new risks requiring new management. The gentle singularity is a job shift.

The five jobs aren't just survivor jobs. They capture more value precisely because everything else gets cheaper. When you automate the cognitive, the physical and relational become scarce. When you automate the routine, the exceptional gets repriced. The plumber might have higher status than the consultant. The community organizer might be more economically valuable than the data analyst. Local beats global in ways we haven't seen since before the internet.

Technology follows a predictable path: first it's a luxury for the rich, then it’s ubiquitous and cheap, then the human version becomes the luxury. Handmade goods to mass production to artisanal craft. Live music to recorded music and back again. Humans doing what robots can becomes the ultimate luxury good.

Rather than asking what will humans do for meaning, ask what meaningful work remains valuable. Making systems work, discovering the unknown, creating beauty, building community, taking responsibility. The work that survives is work we need and want other humans to do, not just work that AI can't yet do.

The AI kings promise an artist's utopia, but we're not retreating to pure creativity, and we're not all becoming artists. We're maturing as participants in creation ecosystems where we're no longer the only thinkers and doers, and no longer the best at both. If we want to compete at scale, we’ll have to play harder and smarter and faster. If we want to feel needed, we'll have to go local.

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More essays: The Relationship Is The Job, Media and Machines, Make Something Heavy, The Aesthetic Is The Art Now, Man’s Pursuit of Greatness Is the Pursuit of a Great Film.

Before going full-time as an artist in 2023, Dipa spent years as a software engineer at Figma while nurturing an artistic practice, starting with digital illustration and expanding into painting and murals. From her Brooklyn studio, she now creates ethereal, abstract works in acrylics and large-scale murals for companies like TikTok. Her recent "Traversing" series explores carving your own path through uncertainty and reinvention.

I asked Dipa 30 questions spanning everything from her creative process to theories on life. She reflects on transitioning from tech to art, how immigrant family creativity flows through generations, why she lov…

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The myth of progress is that efficiency always wins: that the future belongs to solo geniuses with infinite leverage, aided by armies of machines that run themselves.

First, we automate the hands. Then we automate the head. With each technological wave, what was once skilled human labor becomes infrastructure. But the more we automate, the more we notice what’s missing.

This begs the obvious question: What remains when machines surpass us at manual and cognitive work? When do we prefer a flawed, imperfect human instead of a perfect machine — or an infinite number of them? We’re just beginning to ponder how much we still need people, and how to value them.

In this pursuit, we often point to traits like curiosity, creativity, willpower, attention, agency, and taste. Yes, these will all matter. But this essay isn’t about the ingredients of individual brilliance. It’s about the roles we want humans to play, the ones that make us valuable to each other beyond any single trait or skill.

I call this the third labor — Relational Labor.1

Relational labor is an essential layer embedded alongside manual and cognitive labor — rooted in presence, context, commitment, and care.

It’s the kind of work that doesn’t always show up in metrics, but you feel it in morale, momentum, and trust. And it lives in every collaborative job and is central to so many modern roles: cofounders, assistants, coaches, therapists, creative producers, teachers, social workers, doulas, chiefs of staff.

Relational labor aligns, animates, and amplifies the other two kinds of labor.

It’s why we hire for companionship as much as competence.

The job isn’t just the job. It’s the relationship.

II

Startups give us a useful mirror.

The cofounder, the coworker — both are underrated. Consider the new aspiration: the billion-dollar solo founder. One person with infinite leverage, courtesy of AI.

Yes, it’s possible. But it’s also lonely. And limiting. No one dreams of winning in a vacuum. We want people in the room — friends, co-conspirators, witnesses. Most meaningful work demands at least a few people, not just to handle strictly “productive” work, but to breathe life into the quest itself.

Someone who shares the burden, spots what you miss, finishes your half-thoughts, indulges your tangents, and still laughs at your bad jokes. AI might imitate that — with synthetic empathy, simulated guidance, algorithmic support — but one-sided relationships quickly become sycophantic.

People keep telling me how many more things I can do on my own now — with AI — and they’re right. I can write, build, launch, sell, automate — forever. I could assign an agent to every task — even companionship. And maybe it would do its job. But it’s so obviously spiritually vacant.

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Every era gets the duality it deserves — war and peace, faith and reason, labor and capital. I've been circling this question: what’s ours?

If every era is defined by a binary, ours is shaped by the fusion of two: media and machines — once distinct forces, now collapsed into a single living system that governs what gets built, what breaks through, and what defines our reality.

What began as separate domains — machines mastering logic, media monopolizing attention — has merged into a Möbius strip of mutual reinforcement, where media creates machines creates media. The media-machine singularity is the operating system of our age.

The birth of the superorganism

The revelation came with social networks — those first native superorganisms of the media-machine fusion. Facebook, YouTube, TikTok weren’t just social media, they were self-replicating loops where every post was both content and infrastructure — where the machine shaped the media that grew the machine.

Social networks recast the entire blueprint of creation and culture. These platforms became our new cities, economies, and gods (and it’s turned out as spectacular and scary as it sounds.) Now, what we once called the “attention economy” has swallowed the traditional one.

Careers rise and fall on algorithmic affinity. Markets move at the speed of trending topics, memes, and ever-fickler sentiment. We now inhabit the world they made, where every interaction is both input and output for the superorganism.

The medium is the message is the machine

If social networks were the prototype, AI hits full send on the hypothesis. These large language models are born from ingested media we spent the last decades creating, and exist to generate more: the Ouroboros of code and culture. Marshall McLuhan was ever prescient:

In the age of language models, the medium is the message — is the machine.

Natural language is now both interface and infrastructure. The old divisions vanish: to build is to write is to build again. Computational force and cultural resonance emerge from the same source. This compound creature thrives on reciprocal nourishment: feed its media half and its machine capabilities grow; starve its machine needs and its cultural influence withers.

What’s coming will make social networks look quaint: tools become networks, function becomes feeds, solo becomes social — all with frightening intelligence. We move from ephemeral to memory, prompts to personality, feeds to worlds — software to sentience. The machine no longer mediates reality; it becomes it.

We build AI to elevate humanity — to cure, decode, transcend. Yet like all mortal creations, it bends toward what's rewarded: commerce, companionship, cachet. We call this 'progress'— but is it acceleration toward greater civilization, or just a new Facebook? Is OpenAI just another FAANG-shaped god for the ‘new’ era? The answer is either yes, or yes and.

Reality engineering

We’re no longer designing just products or platforms or interfaces, but cognitive environments — architectures of attention that shape what people see, feel, and believe. Every engineering decision is now a cultural act. Every narrative choice carries technical consequence. The stakes have risen beyond business or tech to configuring the operating system of human attention itself.

Baudrillard’s hyperreality — where simulations become more real than reality — was a warning. This is its seamless execution: a world where the map not only precedes the territory but engineers it in real time.

Eventually, everything visible will be subsumed by the media-machine complex. The only remaining “alpha” will be what resists digitization, what can’t be priced in: off-grid experience, instinct, volatility — the unmodelable edge. A jazz improvisation that dies in the air, the silence between old friends who need no words, a collection of PDFs that hold humanity’s greatest secrets.

But even that is fragile. The irony is that as soon as anything is observed or acknowledged, it’ll be modeled. It’s the inverse of the “tree falls in forest” parable — not whether it happened unseen, but whether it still matters once seen by all. To escape total immersion is to demand either defiance or ownership. The final human edge is in controlling the machine or keeping your distance — in how many steps ahead, or how many steps removed, you are at any given moment.1

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The alchemy of modern attention

The media-machine fusion creates the great paradox: systems that grant us godlike leverage now drown us in algorithmic slop.2 The dead internet theory earns its resonance. The retreat to trust commences. Legacy media fractures more; personality cults rise. Vital stories migrate to blogs, mini-sites, Substack, and YouTube (for now). The most resonant storytellers are subscribed to, not employed.

But are we still creating for people — or for the machine that feeds them? (At some point, Substack gave me an option to block ChatGPT and the like from “training” on my essays, so I did. At what point does that become foolish of me?)

Even capital has surrendered. Venture funds all but operate like media companies, and increasingly invest in them. When founders, athletes, and kings are jostling for the same mic, you witness the new reality: in the attention economy, even fame, money, and power need marketing. A product without a myth, a funding round without a podcast tour: both feel incomplete. Manifestos and TBPN are the new minimum. There’s an urgency to capture attention now, almost as if it’s the last chance to “lock-in.”

The new game is barbell-shaped: it’s high-gloss performance for audience capture or deep craft as slow rebellion, and little in between (unless you already have cred, in which case slick-indie sells too). Attention first, product second, if at all. But building still matters. It just takes more now.

The new maker’s manifesto

YC’s famed doctrine, "make something people want" and its cult of the technical founder is timeless, yet could now read as quaint. Today, the making and the wanting must be engineered simultaneously. That too, not just the wanting of ‘users’ you talk to directly, but of the machines that will inevitably talk to them on your behalf too. The most ambitious and strategic ones will try their best at both.

Every organization will now operate as half-media, half-machine. Every media company will have a head of machines and every machine company will have a head of media. Call it the media-machine singularity of business, the hybrid imperative.

Tactically, let’s call it The Anu Principle … Anu’s Theory, Anu’s Law (critical apostrophe).

“Attention guys” are the new engineers — the new unicorn hires — while engineers have become the skilled tradesmen. Idea guys, however emboldened they may now be, are still only as valuable as their ability to finish a product (not just start it with a vibe-coded prototype), and their ability to get distribution.

This singularity requires new organizational DNA: not just leaner teams or AI-agents-as-staff, but a fundamental reimagining of what makes good media and good machines — in function, form, and faith — and who’s best fit to build them.34

The builder’s role has evolved — no longer just a technical architect, but a polymath weaving machines and media into civilization-shaping sculptures. Brilliant engineers now need storytellers and psychological savants.

The renaissance mind returns not as dilettante but as armed philosopher, wielding systems fluency and cultural intelligence equally. The requisites: IQ, EQ, agency, taste — and a will to brute-force your way into the frame. The media-machine singularity will give us some of the most iconic, powerful, hybrid artists we’ve ever seen.

The great work of our time

McLuhan’s axiom returns: “first we shape our tools, then our tools shape us” — but faster now, with the media-machine superorganism rewiring us at scale. These machines optimize for transmission, not truth. They generate coherence, real or not, and wrap it in messages convincing enough to make you nod along.

This raises three unavoidable crucibles:

1. Infinite production demands infinite care — every algorithm’s output becomes someone’s input, every generated phrase someone’s truth.

2. Transmission and virality without virtue isn’t progress but social and cultural vandalism, burning through meaning to fuel empty engagement.

3. Our ultimate test isn’t in technical mastery or narrative flair, but in judgment — the courage to feed the machine something better than its own reflex.5

The questions shift from what can scale to what should. This is the great work of our time: not just building what spreads, but what matters. Not just making things people want, but cultivating the desire for what’s worth wanting.

If media and machines have fused into one great engine of scale, what stands opposite it? Man’s search for meaning. But in an age of accelerating extremes, even meaning must market itself to remain relevant. We like to think it waits patiently in our private lives — but I suspect that’s wishful thinking. Meaning too must earn its keep.6

Whether you build products, tell stories, direct capital, or curate culture, you are now both architect and artifact of this age. The media-machine complex will metabolize and manifest whatever we feed it, then spit it back out for you to binge. So feed it carefully.

If you enjoyed this essay, consider sharing it with a friend or community that might enjoy it too. I welcome reactions, reflections, and thought-provoking questions!

Related essays: The Aesthetic Is The Art Now, Taste Is Eating Silicon Valley, Man’s Pursuit of Greatness Is the Pursuit of a Great Film, Rise of the Software Creator.

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I’ve also been thinking a lot about what makes creation meaningful, and I’ve landed on a timely thesis: In the age of slop, craft is rebellion.

This series, The Craft, is a multi-format experiment I’m hosting here, all about the art of making things, and what makes the maker, too.

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We instinctively tie weight to value.

Gold is solid. Wood is dense. And back when we still printed things on paper, a heavy stapler was a luxury.1

If something is heavy, we assume it matters. And often, it does. Weight signals quality, durability, presence, permanence.

Even the objects we choose reflect this. At first, we buy cheap, lightweight furniture—easy to build, easy to trash. But eventually, we want weight. A solid oak table. A leather armchair. Something built to last. Heavy things comfort us—a weighted blanket stills the body, a heavy door makes a home feel secure.

Winners of major awards almost always say the same thing as they lift the trophy: ‘Wow! It’s so heavy.’ As though the weight itself validates the achievement. Simple logic: Light achievements beget light awards. Heavy achievements beget heavy awards.

We accept this in the physical world.

But online, we forget.

The internet is (mostly) a machine for light things.

The modern makers’ machine does not want you to create heavy things. It runs on the internet—powered by social media, fueled by mass appeal, and addicted to speed. It thrives on spikes, scrolls, and screenshots. It resists weight and avoids friction. It does not care for patience, deliberation, or anything but production.

It doesn’t care what you create, only that you keep creating. Make more. Make faster. Make lighter. (Make slop if you have to.) Make something that can be consumed in a breath and discarded just as quickly. Heavy things take time. And here, time is a tax. And so, we oblige—everyone does.

We create more than ever, but it weighs nothing.

AI now promises results without the reckoning, but frictionless creation leads to weightless rewards. No one dreams of merely pushing a button to generate their magnum opus. The output matters, but the intention, the struggle, the care is what makes it count — what gives it weight.2

Of course, there’s a range from light to heavy, and not all light things are bad. An entire economy thrives on lightness. Memes, breaking news, and celebrity drama shape culture in spades. But movement isn’t meaning. A million views doesn’t make a pound of significance. Light things shape culture, but rarely shape us.

Creation isn’t just about output. It’s a process of becoming. The best work shapes the maker as much as the audience. A founder builds a startup to prove they can. A writer wrestles an idea into clarity. You don’t just create heavy things. You become someone who can.

Many light things don’t add up to one heavy thing.

So many creators start in the shallow pool of some algorithm’s grip—until, inevitably, they go searching for something heavier. From short-form to long-form. From building in public to locking in to solitude, obsession, deep work. To create a book, a film, an album, a company—something that stands alone.

No matter how many you stack, Tweets and TikToks don’t add up to something heavy. They don’t solidify. At best, they’re a pile of snowflakes, intricate yet ephemeral. Beautiful while they’re here, gone before they hit the ground.3

Substack, with its many virtues, finds itself at a crossroads — I’d put it in the midweight creation zone (if used well). Writers stack posts, building up a library of words that starts to feel substantial. It’s good that long-form posts can go viral faster and stick around longer. But it’s still not quite as heavy as writers’ loftiest dreams, at least not yet. Even the most successful Substackers, those who’ve turned newsletters into brands and businesses, start pondering their endgame.

They want to make one really, really good thing. One truly heavy thing. A book. A manifesto. A movie. A media company. A monument. — A masterpiece.4

Not just for the prestige or the money, but for the proverbial "F-U" to ephemerality. For the way it anchors them to something lasting while giving them the freedom to breathe. For the way it sticks in the hearts and minds of other people who encounter it too.

Heavy projects are the lifeblood of creative fulfillment — and creative longevity. And for now, no platform truly offers that kind of weight on its own. Platforms are built to amplify, not anchor.5

You’re either making in light mode or in heavy mode.

Light mode is fast and iterative, producing work that’s quick to make but just as quick to fade. It’s the mode of rapid experiments, side quests, and prolific posting. Heavy mode is slower, deliberate, and intentional (often hermit mode). It’s the mode of deep work that builds over time and carries lasting weight.

Some go straight for the heavy: building the billion-dollar startup, writing the world-changing book, recording the defining album. No pit stops. Or, in less relative terms: things that will stand on their own and stand the test of time. Weight is lindy.6 Others build up to the heavy things: essays before the book, short films before the feature, prototypes before the big product (maybe a few silly ‘GPT wrappers’ before the serious one). Lightness has its virtues — it helps keep you fresh, get in the reps, and work up to the heavy thing.

At any given time, you’re either pre–heavy thing or post–heavy thing. You’ve either made something weighty already, or you haven’t. Pre–heavy thing people are still searching, experimenting, iterating. Post–heavy thing people have crossed the threshold. They’ve made something of substance—something that commands respect, inspires others, and becomes a foundation to build on. And it shows. They move with confidence and calm. (But this feeling doesn’t always last forever.)7 Your gut knows what state you’re in. And the cycle repeats.

No one wants to stay in light mode forever. Sooner or later, everyone gravitates toward heavy mode—toward making something with weight. Your life’s work will be heavy. Finding the balance of light and heavy is the game.8

Note: heavy doesn’t have to mean “big.” Heavy can be small, niche, hard to scale. What I’m talking about is more like density. It’s about what is defining, meaningful, durable.

You feel like an imposter when you only make light things.

Everyone calls themselves a creator now. It’s the default title of the moment, the identity of an era. But does everyone who claims it actually feel it? Do they know the deep, anchored satisfaction of having made something that carries weight?

Telling everyone they’re a creator has only fostered a new strain of imposter syndrome. Being called a creator doesn’t make you one or make you feel like one; creating something with weight does. When you’ve made something heavy—something that stands on its own—you don’t need validation. You just know, because you feel its weight in your hands. And that weight is its own reward.

It’s not that most people can’t make heavy things. It’s that they don’t notice they aren’t. Lightness has its virtues—it pulls us in, subtly, innocently, whispering, 'Just do things.' The machine rewards movement, so we keep going, collecting badges. One day, we look up and realize we’ve been running in place.

And then you feel it: a quiet, gnawing hollowness that, for all the making, nothing has truly been made. Why does it feel bad to stop posting after weeks of consistency? Because the force of your work instantly drops to zero. It was all motion, no mass—momentum without weight. 99% dopamine, near-zero serotonin, and no trace of oxytocin. This is the contemporary creator’s dilemma—the contemporary generation’s dilemma.

You don’t feel like a true creator because you haven’t made anything heavy, and deep down, you know light things don’t count. Your output is high, but your imprint is low. You ship, but you do not build. You call yourself a creator, but what have you made that could survive a month offline? A year? A decade? If you stopped posting tomorrow, would anything remain? Creating for 24-hour cycles isn’t freedom, leverage, or legacy—it’s just renting out your time.

The weight of what we make matters.

Creative people are restless souls, forever chasing the horizon until they’ve made something substantial. We spend our lives crafting weighted blankets for ourselves—something heavy enough to anchor our ambition and quiet our minds.

Weight is tangible in the physical world—a place we should care about and create more for than we have of late, even if it’s harder to scale. Working with your hands, with weight, shape, and dimension, holds an abundance of untapped virtue and value. Online, by nature, weight is harder to find, harder to hold on to, and only getting harder in a world where it feels like anyone can make anything.

But it is just as imperative.

People ask, "What are you working on?" They’re really asking: What’s your endgame? (It’s one of my favorite questions, too.)

My answer is simple, but not easy:

Make something heavy.

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If you enjoyed this essay, consider sharing it with a friend or community that might enjoy it too. This is a topic I care deeply about, so I welcome reactions, reflections, and thought-provoking questions as well. Email me here or DM via Substack or Twitter / X.

Related essays: The Aesthetic Is The Art Now, Taste Is Eating Silicon Valley, Your dreams demand your best hours, Pursuits that can’t scale, Status limbo.

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In the spirit of walking the walk, sharing one heavy creative project on my mind below. If you’ve read this far, and want to support me in such an endeavor, DMs open. 🙏

All creation aspires to a cinematic legacy.

Great Men, Great Movies

The Great Man Theory says history is shaped by extraordinary individuals—heroes whose exceptional qualities—brilliance, courage, leadership, even divine inspiration—change the world. In tech, politics, and sports this theory thrives. Silicon Valley especially loves its "great men" and runs on the perpetual quest to find the next Jobs, Zuckerberg, and Musk.

Yet, so many great men were not solely the product of their ideas or will—they were inspired by something greater: great stories told through art and, importantly, film, that preceded them.1

Elon Musk was captivated by Star Wars at age 6. Musk, Trump, and Jobs inspired the movie persona of Tony Stark, the genius billionaire in Iron Man. Stark Industries, in turn, inspired Palmer Luckey’s defense startup Anduril (named after a sword from The Lord of the Rings.) Mark Zuckerberg connected the world with Facebook, but The Social Network immortalized his rise, inspiring an entire generation of entrepreneurs. And, of course, Sam Altman and many others want to bring Her to life.

Man’s pursuit of greatness is the pursuit of a great film.

Philosopher Thomas Carlyle’s Great Man Theory says history is shaped by extraordinary individuals. I see you, Mr. Carlyle, and I raise you my own theory:

The Great Movie Theory says history is shaped by extraordinary films—masterpieces of storytelling that embed into culture—inspiring great men and society alike to leave a lasting mark on the world.2

The three central tenets of this theory:

1. Cinema mirrors, shapes, and inspires greatness.
   Films both reflect culture and define it. Great movies offer blueprints for success, love, revolution, and self-discovery, reshaping how we see the world and ourselves. These stories shape the ambitions of those who shape history.3

2. Greatness is immortalized through great movies.
   True greatness is made timeless through film. A legacy gains weight when it enters the cinematic canon, transcending its origins to become part of our shared history.

3. All creation aspires to a cinematic legacy.

   Everything we create—from skyscrapers to songs, books, and businesses—seeks a legacy worthy of the big screen. Even 'great men' are driven by the desire to see their stories told and immortalized on film.

Humans are driven by stories, and movies tell stories in a way that uniquely elevates our consciousness—out of the mundane and into the metaphysical in pursuit of greatness. In one way, The Great Movie Theory is a theory of all creation.

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A great movie is the ultimate form of a story.

Many would agree that stories shape history, but some might be skeptical of movies as the highest form of storytelling. So—why movies?

1. A movie is the complete expression of a story.

   Finished movies are whole—no mandate for upgrades or adaptations. This feeling of finality is rare in other forms of creation. Software is perpetually evolving, and games offer infinite paths. Movies are standalone works ready to be set free.4

2. Movies are the pinnacle of storytelling.

   Essayists want to write books. Authors want their books adapted for film. YouTubers dream of breaking into TV and film. Actors, directors, and producers strive to create global hits and win Oscars. The narrative, the aesthetic, the image of great film is the ultimate, enduring power.5

3. All stories are written with the screen in mind.

   The Social Network is based on The Accidental Billionaires by Ben Mezrich, who writes books intended for film adaptation. “Mezrich’s books aren’t books. They’re intellectual property designed for Hollywood.” I don’t think his aspiration is unique, but his self-awareness, honesty, and playbook are.67

4. Movies are instruments of great cultural power.

   The world runs on stories. Amazon Studios and Apple TV+ are no accident. Tech moguls understand that rich media is more than entertainment—it shapes culture, commerce, politics, public sentiment, and legacy.

5. Movies are the highest order of shared context after news.

   Amidst the fragmented media landscape, great movies deliver universal experience. With increasingly global cinema and easy language dubbing via AI, for instance, movies will remain bearers of shared stories as context.

Great movies are the most powerful storytelling tool we have. While technology—AI included—will introduce myriad new tools, the essence of film as a medium will endure. In fact, as I keep saying, the sheer abundance of everything will only amplify the sanctity of truly great work, making great movies more indispensable than ever.

The pursuit of greatness runs through film.

It’s fitting that it’s Academy Awards—Oscars—season. People love to argue about how little these awards matter in the age of endless online content, where TikTok and YouTube are kingmakers, and how Hollywood is “dead.”

Yet, when Timothée Chalamet accepted the Screen Actors Guild Award for Best Actor last week, his speech went viral. We’ve been starved for talk of greatness—and Chalamet stepped up as our hero, making the pursuit of greatness cool again and reaffirming that movies are a powerful vehicle to achieve it.8

Man's pursuit of greatness is the pursuit of a great film. After all, a book’s highest prize isn’t a National Book Award—it’s inspiring the next Harry Potter movie series. A musician’s legacy isn’t just defined by their Grammys—it grows with an acclaimed biopic like A Complete Unknown. A startup’s crowning achievement isn’t an IPO—it’s inspiring a film as iconic as The Social Network.

“Everyone just wants to make a movie,” I’ve said. I don’t mean everyone wants to literally make films (though I do).9 And I’m not suggesting everyone should pivot to filmmaking. What I mean is everyone wants to create something worthy of being woven into the fabric of a great film—admired, retold, and immortalized.

For years, there’s been a call for more “independent” (i.e. low-budget) films to be represented on stages like the Oscars. Every year, film lovers hope this year will be the turning point. So with Anora sweeping the major awards this year on a $6M budget and Flow winning Best Animated Feature on a $4M budget, it feels like we’re finally on the precipice of something.

And with rich media creation tools rapidly becoming accessible, and AI accelerating this trend, we’ll see more of everything made—and even more people aspiring to make it (both the young and poor and the old, rich, and powerful). Because immortality isn’t found in fame or wealth; it’s in telling a great story or having one told about you—and shared with the world through a great movie.10 So whatever you do, in whichever medium you choose, aspire to enter it into the cultural canon.

Movies make history. History makes movies. Great men are immortalized in both.

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There are hours in a day, and then there are your best hours. Your dreams demand your best hours.

As a night owl’s night owl, I used to treat the 24-hour day like a loose construct—sleep negotiable, day and night arbitrary. It was effective for grinding through the infamous 60 to 80 to occasional 100-hour weeks of studying, training, or working. I coped by cramming life into the leftover hours: scheming while I walk, gymming at 1 a.m., writing in the dead of night, scrolling myself to sleep.

Complicating it all, I’m not a creature of routine but of bursts—I come alive in flashes, not on fixed schedules. Hence it’s all the more challenging to promise hours to someone else and still have enough for myself. (I always envied those who could live like metronomes, summoning their best selves on command.)1

What I didn’t realize before, and still keep realizing, is that not all hours are created equal. There are hours in a day, and then there are your best hour…

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