On May 17, 1994, a group of South Korean government scientists walked into the president’s office and presented a memo about dinosaurs. Not real ones. Steven Spielberg’s dinosaurs.

Their argument was simple: Jurassic Park had grossed $850 million worldwide, which was equivalent to the foreign sales of 1.5 million Hyundai automobiles. Korea, at the time, exported barely 700,000 vehicles per year.

A single Hollywood film was worth more than twice the country’s entire annual car export volume.

The president read the memo. The government created a Cultural Industry Bureau.

Four years later, in the middle of the worst financial crisis in the country’s history, South Korea’s new president made a bet that most economists thought was insane: he would spend his way out of the crisis by manufacturing pop culture.

Thirty years later, 9 of the 10 best-selling albums on the planet are Korean.

This is the story of how that happened.

The Memo

The memo wasn’t vague. It wasn’t a soft plea about “investing in the arts.” South Korea’s Presidential Advisory Council for Science and Technology titled it “Strategic Plan for the Growth of High-Tech Visual Arts,” and the arithmetic was blunt: Jurassic Park grossed $850 million on a $63 million budget.

That revenue equaled the foreign sales profit of 1.5 million Hyundai cars. Korea exported barely 700,000 vehicles that year.

A dinosaur movie, made in eighteen months, out-earned the entire country’s annual car export volume by more than two to one.

Scholars Vincenzo Cichelli and Sylvie Octobre later named this “the Jurassic Park syndrome”: the moment popular culture became viewed as a commodity with exchange value exceeding industrial goods.

The government created a Cultural Industry Bureau with an initial budget of 5.4 billion won ($4.1 million). Modest. Almost symbolic.

Then the 1997 Asian financial crisis hit.

South Korea took a $58 billion IMF bailout, the largest at the time. The economy cratered.

And incoming President Kim Dae-jung, inaugurated in 1998, made what looked to most economists like a reckless bet: spend your way out of a financial crisis by manufacturing pop culture.

The policy mechanics were aggressive, to say the least.

Government spending on culture jumped from $14 million in 1998 to $84 million by 2001. The music industry budget alone surged from 940 million won in 1997 to 14.5 billion won in 2000, a fifteen-fold increase in three years.

The 1999 Framework Act for the Promotion of Cultural Industries established the first comprehensive legal definition of cultural products and mandated tax incentives and export subsidies.

The Korea Creative Content Agency (KOCCA) received a mandate to subsidize record companies, fund overseas tours, and staff international music expos, eventually opening offices in the US, France, China, Japan, India, Indonesia, and Vietnam.

Government officials arranged ad sales for Asian TV stations so those stations would accept ready-to-play packages of Korean soap operas, already translated and subtitled, at no cost.

As journalist Euny Hong put it: “There was zero market for Korean popular culture. It had to be force-fed into foreign markets.”

The term “Korean Wave” (Hallyu) was coined by Chinese journalists in a 1999 Beijing Youth Daily article. They expected it to be a fad.

A country in the middle of the worst financial crisis in its history had looked at its balance sheet and decided the answer was boy bands and soap operas.

The Trust Layer

Why would anyone outside Korea care about Korean pop culture in the first place? The sequencing tells you everything. Korean industrial products established global credibility first. Cultural exports rode on that trust.

In the early 1990s, Samsung was known among expats as “Samsuck.” Hyundai’s Excel, launched in 1986 at $4,995 (the cheapest car available in America), was a recurring late-night punchline. Jay Leno made it a regular target. Consumer Reports relentlessly attacked its reliability.

Korea, in the Western imagination, meant cheap goods.

The transformation was very deliberate.

In 1993, Samsung’s chairman Lee Kun-hee gathered 200 executives in Frankfurt and told them to “change everything except your wife and children.”

The company scrapped $50 million in inventory, tripled R&D to $6.5 billion annually, and shifted from lifetime employment to merit-based promotions.

By 2005, Samsung surpassed Sony in global brand value. A Korean brand eclipsing Japan’s most iconic electronics company. By 2011, it overtook Nokia as the world’s largest smartphone maker, a position it held for 14 consecutive years.

In 1998, Hyundai introduced a 10-year, 100,000-mile powertrain warranty. The message: we now believe in our own cars. The brand went from punchline to J.D. Power’s Highest in Initial Quality award by 2019.

By the time Korean pop culture arrived in Western markets in the 2010s, “Korea” no longer connoted cheap goods. It connoted Samsung phones, Hyundai reliability, and LG appliances.

The top 10 Korean conglomerates account for roughly 60% of the country’s GDP.

I visited Seoul in 2024, and what struck me first was the grooming. Everyone was immaculately polished, in a way that went beyond fashion and into something closer to national discipline. I found myself dressing more carefully just to avoid feeling conspicuous.

That sensibility comes from the same coordination culture that turned Samsung from a punchline into the world’s largest smartphone maker: the instinct to engineer quality into every visible surface.

The pop music system just happens to be where that instinct became most legible to the outside world, second only to the dramas.

The Engineer

The government built the policy infrastructure: subsidies, legal frameworks, export support, and overseas offices.

But policy alone does not produce pop stars. Someone had to build the production system that could absorb those resources and convert them into exportable culture at scale.

That person was Lee Soo-man.

Lee was a modestly successful singer and TV emcee in 1970s Korea before leaving for California to study computer engineering at Cal State Northridge. While there, he witnessed Michael Jackson’s rise and the MTV revolution.

He came back with an inversion that reshaped an entire industry:

“Up until that time, the majority of people thought that it is only when you become a big and wealthy country that your culture gets to shine globally. Economy comes first and then culture will follow. But I started thinking in the opposite way, that culture should be first and then economy next.”

He established SM Studio in 1989 in the Apgujeong neighborhood of Gangnam, Seoul. His first signed artist, hip-hop singer Hyun Jin-young, was arrested for drug use, destroying the investment.

That failure was absolutely pivotal. Lee decided to build a system that ensured nothing was left to chance. The scandal inoculated SM against ever trusting talent development to organic processes again.

Modern K-pop, in its entirety, exists downstream of this moment. If you are a fan of BTS, aespa, or Blackpink, you have Mr. Jin-young’s behavior to thank for it.

Around 1997, he coined the term “Cultural Technology” (문화기술) and wrote a literal physical manual that SM employees were required to study.

His head of A&R, Chris Lee, explained to Billboard:

“Mr. Soo-man Lee has this mindset that when it comes down to technology or computer science, there’s always a manual. So he wanted to make sure that we have those manuals, specific manuals to follow to aim for perfection when creating creative content.”

His training as an engineer produced an entertainment system with the rigor of an engineering specification. SM receives approximately 300,000 applicants across nine countries every year. Roughly 100 receive training.

Of all trainees who enter the system, about 1% ever debut. The cost of developing a single idol was estimated at $3 million per member. Debuting an entire group costs $7.5 million or more.

Each group was designed for a specific strategic purpose.

H.O.T. (1996) was formed by polling high school students to determine what teenagers wanted.

BoA (2000) was deployed to conquer the Japanese market at age 13.

Later groups pushed the logic further: sub-units singing identical songs in Korean and Mandarin, city-based franchises designed with unlimited members.

This is what it looks like when government cultural investment meets an engineer’s instinct for systematization: not one artist hoping for a breakthrough, but a production system calibrated to generate them in sequence.

What happens inside that system has a texture that’s difficult to convey without gruesome specifics.

Former SM trainee “Euodias” described it in a 2020 BBC feature: each trainee was assigned a number, and instructors called them only by their numbers, read from stickers on their shirts.

“It felt weird, a bit like we were in some sort of science experiment.”

Trainees were divided into Team A and Team B, “largely based on visual potential and body weight, not skill.”

Weight surveillance is institutionalized. Companies weigh trainees publicly, announcing numbers out loud. Public shaming being insufficient, those over the company’s target are placed on water diets or denied food outright.

Companies cover all training costs as an advance loan; trainees who leave without debuting face penalties ranging from $86,200 to $129,000.

The system reformed somewhat after the TVXQ lawsuit of 2009, when three members of SM’s biggest boy group sued over their 13-year contract, claiming they worked with only four hours of sleep and received almost none of the profits.

The court ruled in their favor, and the Fair Trade Commission limited entertainment contracts to seven years.

The system reformed enough to survive. It didn’t soften.

What the System Produces

The girl group aespa, debuted in 2020, makes a useful case study because the group makes all of this infrastructure visible rather than hiding it.

One member, NingNing, moved from Harbin, China, to South Korea alone at age 14 and trained for five years. She was the only member of her trainee cohort to survive to debut. Every other trainee from her class was cut. Another member, Giselle, trained for approximately eleven months.

Same group. Same debut day.

Their concept pushes the engineering into the aesthetic itself. Each member has a digital AI avatar counterpart existing in a virtual dimension called KWANGYA. Even the members struggled with the lore. But member Karina captured the concept’s tension perfectly:

“æ-Karina doesn’t make mistakes. But I can make mistakes.”

By 2023-2024, SM quietly began retreating from the heavy KWANGYA narrative, shifting toward simpler aesthetics. Even the engineers recognized the concept had outrun its usefulness. But the instinct it expressed, making the construction visible rather than hiding it, remains the group’s defining characteristic.

The Unpaid Operations Department

The government built the policy infrastructure. Lee Soo-man built the production infrastructure. Neither fully explains how Korean music achieved the chart dominance it has today.

That required a third layer: the fans.

K-pop fandoms operate through what Korean fans call chonggong (총공, “collective attack”): coordinated mass action to break digital metrics. This is a decentralized operation performing the work traditionally done by marketing departments, except no one draws a salary.

The sophistication is operational, not just emotional. Streaming guides specify platform rules: on Spotify, play each song for 30+ seconds, switch between 3-4 playlists, include non-K-pop songs to avoid bot detection, pause every 20-30 minutes, mute the device rather than the app.

Fans in Indonesia and India wire money to US-based fans for bulk digital purchases to count toward Billboard charts. BTS ARMY achieved 101.1 million YouTube views in 24 hours for “Dynamite” through organized global shifts.

The Hyundai Research Institute estimated BTS’s annual economic contribution at $4.65 billion, equivalent to the output of nearly 500,000 average Korean workers, or roughly 0.3% of South Korea’s entire GDP.

The scale of fandom coordination has pushed beyond music entirely. BTS ARMY’s #MatchAMillion campaign raised $1,026,531 from 35,609 donors in roughly 24 hours. A single free BTS concert in Busan generated an estimated $500 million in economic value.

And then there’s the chart dominance, and the contradiction at its center.

On the 2024 IFPI Global Album Sales Chart, 9 of the top 10 and 19 of the top 20 best-selling albums worldwide were by K-pop artists. This dominance is partly driven by the fansign lottery system: fans purchase dozens to hundreds of copies of the same album for a chance to meet an idol in person, extract the collectible photocards, and discard the album shells.

Documented photos show boxes of hundreds of K-pop albums dumped on Seoul streets.

Nine of the ten best-selling albums in the world, and piles of them in the gutter.

The Frame

A system like that (numbered trainees, public weigh-ins, six-figure exit penalties) carries a predictable reputation in Western music criticism.

The framing is always the same: manufactured, artificial, factory-made.

But that reaction papers over a philosophical gap worth examining, because it explains why Western critics have such a hard time taking the music seriously, even as it dominates their charts.

Western pop is also extensively engineered. Swedish producer Max Martin has written or co-written over 25 Billboard #1 hits, surpassing the Beatles’ record of 20.

Berry Gordy Jr. explicitly modeled Motown Records on Ford’s assembly line:

“I worked in the Ford factory before the record business and I thought, why can’t we do that for the creative process.”

The machine exists. The cultural convention, inherited from Romanticism’s insistence that real art flows from individual genius, is to obscure it.

A Seoulbeats analysis identified a particularly telling example: New Yorker writer John Seabrook, in 2012, defended the Norwegian production duo Stargate’s role in creating Rihanna’s hits (”She embodies a song in the way an actor inhabits a role, and no one expects the actor to write the script”), then in the same year framed K-pop’s equivalent process as manufacturing in a chapter titled “Factory Girls.”

Same production model. Different framing, depending on who is doing it.

K-pop doesn’t hide its engineering. Instead, it treats visible effort as a selling point.

A 2025 academic paper in The Journal of Creative Behavior drew parallels between K-pop training and the Pansori concept of Gongryeok (功力): accumulated mastery through dedicated practice rooted in Confucian values.

In one framework, engineering is a mark against authenticity. In the other, it’s proof of seriousness.

What makes this tension productive (rather than merely academic) is how different Korean acts have navigated it.

BTS became the biggest act in the world partly by conforming to the Western authenticity frame: all seven members have had songwriting credits since debut, and RM told interviewers,

“We don’t want to change our identity or our genuineness to get the number one.”

They earned credibility within Western criticism by demonstrating personal authorship.

aespa did something closer to the opposite. The AI avatars, the metaverse, and the lore universe are all transparently constructed and even allude to the real-life SM Entertainment within the story.

The group made no bid for the Romantic ideal. They leaned into the engineering and made the engineering itself an artistic statement.

BTS proved Korean artists could meet the Western standard. aespa asked why they should have to.

Culture as Infrastructure

South Korea’s intellectual property exports (music, film, gaming) reached $9.85 billion in 2024, tripling from roughly $3 billion a decade earlier.

Of that total, gaming accounts for 73%; the music and television industries drive disproportionate attention and soft power relative to their direct revenue share.

Global Hallyu fans numbered 225 million in 2023, up from 46 million in 2012. South Korea climbed from 28th to 9th in the Brand Finance Global Soft Power Index for Culture and Heritage between 2020 and 2025, and ranked 1st globally for influential media.

The feedback loop between cultural and industrial exports is now self-reinforcing. K-pop drives interest in Korean cosmetics, fashion, food, tourism, and language study. Cultural exports are building a brand architecture on which everything else appreciates.

Thirty years ago, a government memo compared a Spielberg film to Hyundai sales to argue that culture could be as valuable as industry.

Today, a 14-year-old girl from Harbin moves to Seoul alone, trains for five years, survives a system that cuts everyone around her, and debuts as one quarter of a group whose AI counterparts live in a corporate metaverse at an address that matches the company’s actual building.

The memo’s math has inverted:

Korea no longer measures culture against car exports.

The culture is what makes the world want the cars.

In downtown Bangkok, a 49-story luxury tower stands completely empty. It has been empty for 27 years.

The Sathorn Unique was 80% complete when Thailand’s currency lost half its value in six months, GDP contracted 10.5% in a single year, and 56 of 91 finance companies were permanently shut down.

The developer’s son refused to declare bankruptcy. He wanted to repay every original buyer in full. That never happened. The tower survived the 2025 Myanmar earthquake that shook Bangkok. It became the set of a Thai horror film. It hosted a seminar on the 20th anniversary of the crisis that killed it.

It is, by any measure, the most haunting monument to a financial crisis anywhere in the world. The crisis ended decades ago. The psychology it installed never did.

The first time I went to Bangkok, in August 2023, I couldn’t square what I was seeing with what I thought I knew. The people were visibly sharp. The youth dressed like they’d walked off a Seoul street and spoke English with an ease I hadn’t expected.

One Bangkok, the $3.9 billion mixed-use district designed by the architects behind the Burj Khalifa, was rising in the center of the city. ICONSIAM, a $1.65 billion riverside mega-mall, housed an indoor floating market representing all 77 Thai provinces alongside Louis Vuitton and Chanel.

I’ve been going back regularly since then, and the feeling has only deepened. Thailand is full of people who should be living in a country that works better than it does.

The standard story about developing economies is that the bottleneck is human capital: the workforce is underskilled, the educational pipeline is broken, the culture doesn’t support innovation. Thailand inverts every one of those assumptions and still can’t break through. Between 2015 and 2024, Thailand averaged 1.9% GDP growth. Vietnam posted 7%. Indonesia managed 5%. Malaysia came in between 4 and 5%. Thailand fell from second to fifth among ASEAN economies for foreign direct investment between 2010 and 2022.

Over 3,500 factories shut between 2021 and 2024, with 51,500 workers losing their jobs in the twelve months through June 2024 alone (an 80% year-on-year increase). Subaru ceased all assembly at its Lat Krabang plant after production collapsed to 344 units in four months.

Suzuki announced closure of its Rayong factory by end of 2025. Samsung moved smartphone production to Vietnam years earlier, where its six factories now account for over 50% of the company’s global smartphone output and generate roughly 30% of Samsung’s total revenue. The consumer side is cracking alongside manufacturing: auto loan non-performing loans surged 32% year-on-year, car leasing NPLs hit 27.25% in Q4 2024, and commercial bank lending has contracted for four consecutive quarters, the longest contraction in over 20 years.

The numbers tell you what happened. They don’t tell you why. The answer is a structural trap with interlocking parts: a crisis that installed permanent caution, a concentration of wealth that was strengthened by that caution, and a demographic collapse driven by the resulting lack of opportunity. Each piece makes the others harder to fix, and the combined weight makes the trap politically unsurvivable: no leader lasts long enough to coordinate an escape.

The Psychology That Never Left

On July 2, 1997, the Thai baht was unpegged from the dollar after 14 years at a rate of 25:1. By January 1998, it had plunged to 56. Of the $38.7 billion in foreign reserves, only $2.85 billion remained. The IMF assembled a $17.2 billion rescue package. Over 300 high-rise projects were abandoned mid-construction across Bangkok. U.S. diplomat Marie Therese Huhtala recalled people pulling their kids out of school, executives losing everything, wealthy families selling furs and Mercedes at fire-sale prices.

The Bank of Thailand itself acknowledges the crisis left “remaining scars.” These manifest as institutional risk aversion of an intensity that is difficult to overstate. Foreign reserves were rebuilt from $2.85 billion to over $237 billion by 2018. Banking regulation became among the strictest in the region, with capital adequacy ratios at 17.8% and loan-loss reserves at 162% of required amounts. Corporate investment has been persistently weak since 1997.

Here is the frame that got installed: caution above all else. Safe export-oriented manufacturing. Tourism. Strategies that generate foreign exchange without the vulnerability of foreign borrowing. These were rational choices. They were also the choices of a country that would never again bet on itself the way it had in the late 1980s, when Thailand’s economy was growing at over 9% annually, the highest rate of any country on Earth.

The aspiration was set in that era. The caution was set by what came after. Both are still running simultaneously, and neither can overwrite the other. That tension defines modern Thailand more than any single policy failure.

And the caution didn’t just shape policy. It shaped who won.

Where the Money Sits, and Where It Doesn’t

If the 1997 crisis installed the psychology, the psychology installed the structure.

A banking system that will only lend to proven balance sheets lends to conglomerates. A regulatory system terrified of destabilizing the economy doesn’t challenge incumbents. An investment climate that only funds what’s already validated funds the people who already own everything.

Thailand didn’t develop extreme wealth concentration because a few families seized power. It developed extreme wealth concentration because the caution frame, applied consistently for 27 years, has a natural output: whoever was big enough to survive 1997 absorbed everything that came after.

Credit Suisse’s 2018 Global Wealth Databook ranked Thailand the most unequal country in the world among 40 nations surveyed. The richest 1% controlled 66.9% of all wealth. The bottom 50% held 1.7%. But the numbers matter less than the mechanism.

CP Group was forced to sell Lotus during the 1997 crisis. Then it bought everything back (Makro in 2013, Tesco Lotus for $10.6 billion in 2020) at moments when smaller competitors couldn’t finance operations. Today, CP Group controls 14,000 7-Eleven stores, Thailand’s largest telecom operator, and one of the world’s largest agribusiness operations.

TCC Group controls Thai Beverage, massive real estate holdings, and is the developer behind One Bangkok. Together with Boon Rawd Brewery, TCC controls over 90% of Thailand’s beer market. King Power holds a near-total monopoly on duty-free retail.

The combined wealth of Forbes Thailand’s top 50 reached $170.5 billion in 2025, roughly 33% of the country’s entire GDP.

Thailand’s 1999 Trade Competition Act yielded zero prosecutions in its first 17 years. When the True-DTAC telecom merger reduced the mobile market from three to two major players in 2023, the deal proceeded without resistance. This wasn’t corruption in the traditional sense; it was the caution frame working exactly as designed: don’t disrupt what’s functioning, don’t risk instability, don’t bet on an outcome you can’t guarantee.

Every subsequent downturn repeated the cycle. COVID was the most recent iteration: the big conglomerates were described as “among the few cashed-up Thai buyers” for distressed bank portfolios. The crisis that broke the middle class made the conglomerates stronger. Then the caution that followed the crisis made them permanent.

A Country Aging Without Getting Rich

The detail that reframes everything is the birth rate.

Thailand’s total fertility rate fell to 1.0 in 2024. Lower than Japan’s 1.2. Approaching South Korea’s record-breaking 0.72. But South Korea’s GDP per capita is five times higher, at $36,000 versus Thailand’s $7,300. Thailand is the only Southeast Asian country the UN classifies among nations with declining birth rates, a group that otherwise consists entirely of high-income, developed economies.

In 2024, Thailand recorded 462,240 births versus 571,646 deaths. The first time births fell below 500,000 since 1949. The fourth consecutive year deaths exceeded births. Thailand’s median age of 40.8 matches the United Kingdom’s. The ASEAN average is 29. By 2050, one in three Thais will be over 60, and the working-age population will shrink from 43.2 million to 36.5 million.

This demolishes the standard assumption that birth-rate collapse is purely about wealth. Thailand’s plunge below replacement fertility began in 1991, driven by an extraordinarily successful 1970s family planning program that cut population growth from 3.1% to 0.4%.

But the continued decline, a survey found only 35.8% of fertile Thai adults plan to have children, is driven by something harder to measure: the sense that the future doesn’t hold enough promise to invest in.

The conglomerate structure and the demographic decline reinforce each other: young people opt out because the economy offers them no path forward, and their departure further concentrates the domestic market in the hands of the incumbents who already dominate it.

The “Let’s Move Abroad” Facebook group, created in May 2021, attracted nearly 1.1 million members almost immediately. In a country of 72 million, that is a mass expression of generational despair.

Thailand produces 400,000 to 500,000 university graduates annually, fewer than half of whom find immediate formal employment. Starting salaries hover around 15,000 to 20,000 baht per month ($420 to $560).

A single BTS/MRT fare of 39.50 baht represents 11% of the daily minimum wage, the highest proportion in Asia. Bangkok earned UNESCO Creative City of Design designation in 2019. The 2024 film How to Make Millions Before Grandma Dies was an international breakout. The creative talent is unmistakable. The economic infrastructure to support it is not.

Breaking free would require coordinated industrial policy sustained over decades. An economy this rigid, a demographic clock this advanced, a debt burden this heavy: the structural conditions make that coordination almost impossible.

Thailand has had 11 prime ministers in 20 years, not because its politics are uniquely dysfunctional in isolation, but because the trap itself is politically unsurvivable. No leader holds power long enough to execute a strategy that takes a generation to pay off.

Why Others Pulled Away

Vietnam and Malaysia clarify what escape looks like.

Samsung’s Vietnamese supplier base grew from 25 enterprises in 2014 to 257 by 2022, a tenfold increase in local supply chain development. Vietnam secured a tariff deal with the United States. Intel committed $7 billion to expand advanced chip packaging in Penang, making it Intel’s largest global production base. Malaysia’s five economic corridors have collectively attracted $162 billion in cumulative investment. The Johor-Singapore Special Economic Zone is becoming a hyperscale data center hub.

What separates these countries from Thailand is policy continuity. Vietnam’s system provides consistent, decades-long investment-friendly policy. Malaysia operates on five-year development plans with dedicated statutory authorities for each economic corridor that function regardless of government changes, even through Malaysia’s own turbulence of three prime ministers between 2018 and 2022. These countries could make long-horizon bets and hold them.

Thailand, with its economic rigidity generating constant political churn, could not. The World Economic Forum found that business executives ranked leadership turnover as the single most problematic factor for doing business in Thailand. The signature digital wallet stimulus was indefinitely postponed in May 2025 with 157 billion baht reallocated after yet another transition in leadership.

Thailand has been middle-income for 37 years. World Bank simulations suggest it will likely remain so past 2050 under current trends. South Korea, starting from a similar GDP per capita in 1960, broke through in under three decades by investing heavily in domestic innovation, R&D, and education. Thailand chose the safe path and has been rewarded with safety and nothing more.

Every time I go back to Bangkok, I notice the same thing: the gap between the people and the system they inhabit. Thais are cosmopolitan, creative, industrious, and increasingly fluent in the language of the global economy.

They are also trapped in a structure that was built by a crisis nearly three decades old, maintained by conglomerates whose dominance predates that crisis, and reinforced by a collective memory that treats caution as the highest virtue.

The standard developing-country story is about building human capital. Thailand already has it. The standard demographic decline story is about rich countries running out of young people.

Thailand is running out of young people without ever having gotten rich. The standard stagnation story is about countries that can’t attract investment. Thailand attracts plenty of investment. It just flows exclusively into what’s already been validated a hundred times over: another mall, another resort, another 7-Eleven.

None of the usual frames quite fit. And that, more than any single statistic, is what makes Thailand’s situation a tragedy rather than a problem. Problems have known solutions. Tragedies are what happen when the ingredients for success are all present and the structure still won’t let them combine.

The Sathorn Unique still stands downtown. Eighty percent complete. Twenty-seven years empty. Nobody lacks the resources to finish it. They lack the conviction that finishing it is safe.

That’s the frame the crisis installed, and it applies to a lot more than one building.

When Sheikh Rashid discovered oil 15 miles offshore in 1966, he had a problem: nobody could see it. So he loaded crude onto a barge, towed it into the Creek, and pumped it into a sand embankment along the shore.

Oil appeared to flow from beneath the city itself. It was pure theater. Dubai never actually had much oil. Abu Dhabi holds 94% of the UAE’s proven reserves. Dubai’s were modest and started declining by the 1990s. Today, oil contributes less than 1% of Dubai’s GDP.

And yet for 30 years, the same Western analysts have kept predicting its collapse. The predictions use economic vocabulary, cite real conditional risks, and arrive at the same conclusion every time: unsustainable.

But strip away the models and what you find isn't economics. It's a story about how wealth is supposed to be earned, who deserves to have it, and what should happen to those who got it wrong.

Dubai keeps violating that story. The predictions keep coming anyway.

The First Thing the Predictions Have to Ignore

To sustain the story that Dubai is a petrostate waiting to implode, you have to skip past sixty-four years of commercial history that precedes the oil.

In 1902, Sheikh Maktoum bin Hasher abolished all customs duties on imports. No tariffs. No processing fees. An open door for anyone who wanted to trade through Dubai’s Creek. When Iran raised its own customs duties a year later, a wave of Iranian merchants relocated from Bandar Lengeh, bringing their families, their trading networks, and their architectural traditions. The coral-stone houses with wind towers that tourists photograph in old Dubai today were built by those Iranian settlers.

By 1949, the pearl industry had collapsed (Kokichi Mikimoto’s cultured pearls had killed the Gulf’s wild-catch market), and Dubai was in desperate shape. People were eating leaves, locusts, and a spiny desert lizard called dhub that tastes like chicken if you’re generous and like sand if you’re honest. The town had maybe 20,000 people and a creek so silted up that large dhows couldn’t enter.

Sheikh Rashid, who took power formally in 1958 but was running things well before, commissioned a British engineering firm to dredge the Creek. Their 1955 feasibility report contains a line of wonderful British understatement: “No records exist of any recent civil engineering works of any magnitude in Dubai and this, coupled with the isolated position of the country, make accurate estimation of costs difficult.” The price tag was £388,000, extraordinary for a town with no oil revenue. He scraped together £200,000 from a local bank and secured a £400,000 loan from Kuwait. When the dredging finished, ships of 500 tonnes could enter. Trade volume jumped immediately.

Edward Henderson, a British oil company representative, described a place where business worth millions was conducted with a wink and a nod, where an expanding town was operating under oil boom conditions fifteen years before any oil was actually discovered. Henderson wrote a line that reads differently in hindsight: “Goodness, what will he be like if he does find oil?”

The free trade zone in 1902. The infrastructure investment in 1959. The oil discovery in 1966. Dubai didn’t need oil to understand commerce. It needed oil to scale what it already knew.

What “Unearned” Actually Means

Why do the collapse predictions keep coming? Because Dubai violates a particular story about how wealth becomes legitimate.

The Western economic narrative is built on a template: labor, sacrifice, deferred gratification, productive struggle. This story has enormous power. It motivates. It organizes. It gives meaning to decades of effort. When a country satisfies the template (Japan’s postwar recovery, Singapore’s ascent from poverty, South Korea’s industrialization), Western analysts call it a miracle and admire it. When a country violates the template, they reach for words like “unsustainable” and “distortion.”

The Gulf violates that narrative. A commodity the world needs sits beneath their ground, and the world pays for it at scale. When wealth appears without the expected suffering, it triggers something that looks like analysis but functions like defense.

People predict collapse. They use economic vocabulary. They cite conditional mechanisms (Dutch Disease, resource curse, rentier effects) that describe real risks under specific conditions. But in ordinary conversation, the conditions drop away and the conclusion hardens: this wealth is unearned, therefore it is temporary.

That smuggles “deserved” into “durable.” It treats moral legitimacy and structural resilience as the same thing, when they are entirely separate questions.

This framing persists even when the data contradicts it. Dubai’s economy runs on wholesale and retail trade (26%), transport and logistics (12%), banking and finance (10%), manufacturing (9%), real estate (7%), construction (6%), and tourism (5%). No single sector dominates. By most measures, it is more diversified than many Western cities of comparable size. And still the analysis defaults to “petrostate.”

A Framework That Broke Inside the Academy

The intellectual scaffolding behind the predictions has a name: rentier state theory. In 1970, Hossein Mahdavy coined the concept to describe pre-revolutionary Iran, a state funded by resource rents from foreign buyers rather than by taxing its own citizens. Beblawi and Luciani formalized it in 1987, arguing that rentier wealth breaks from the “work-reward system” because it comes from “chance or situation” rather than productivity. That sounds like a neutral observation. It is also a value judgment embedded in an economic model. The “work-reward system” is treated as the baseline. Deviation from it becomes pathology.

The critics within the discipline have been saying this for years. Emilie Rutledge, publishing in the OPEC Energy Review in 2017, pointed out that the contemporary notion of rent as “essentially constituting unearned and thus unwarranted income” is divorced from the more accurate idea of ground rent as a legitimate charge for extracting depletable sovereign resources. Scholars treat oil revenue differently from coffee or cocoa revenue, and that difference has nothing to do with economics.

Ozyavuz and Schmid, writing for the French Institute of International Relations in 2015, named the problem directly: “This is where the hint of Orientalism that is sometimes evoked surfaces... analysis of rent in the Middle East appeared to support cultural prejudices.” They called classical rentier state theory “implicitly culturalist, betraying the energy-scarce West’s unease concerning the unequal distribution of energy resources.”

Even Luciani, one of the two scholars who formalized the original theory, eventually distanced himself: “It has never been my understanding that the rentier state paradigm should be either the sole or the overwhelming tool of interpretation.” Among Gulf specialists, by 2019, the original theory appeared “more often as a foil than as a bedrock theoretical perspective.” The framework’s own architects walked away from it.

Outside the academy, in Western media and popular commentary, the theory calcified into a genre. Martin Peretz, then editor-in-chief of The New Republic, wrote in 2008 that Dubai was “a Potemkin village, a house of cards, a mirage” and that it would collapse “soon.” The trigger changed over the decades. The conclusion never did.

The comparison that exposes this most clearly is Singapore. Singapore and Dubai share state-directed economic development, authoritarian governance structures, sovereign wealth funds, zero or low income taxes, a deliberate strategy of becoming a hub, deep dependence on migrant labor, and a founding autocrat whose personal vision drove the whole project.

When Singapore intervenes in markets, it’s called competence. When Gulf states do the same thing, it’s called distortion. Both are state-directed capital. The difference in how they’re discussed tells you more about the person doing the analysis than the country being analyzed.

The 2008 Test

The financial crisis gave the skeptics what looked like vindication.

Dubai had borrowed roughly $80 billion during a four-year construction boom. Property prices had quadrupled between 2002 and 2008. The Atlantis Hotel on Palm Jumeirah opened on November 24, 2008, with a $24 million launch party featuring a Kylie Minogue concert and fireworks visible from space. This was less than two months after Lehman Brothers collapsed.

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By early 2009, property prices in some areas had fallen 50-60%. On November 25, 2009, Dubai World announced it would seek a six-month standstill on $59 billion in debt repayments. European stocks dropped 3%. The Dow fell 155 points. Bank of America warned this could “escalate into a major sovereign default problem, which would then resonate across global emerging markets in the same way that Argentina did in the early 2000s or Russia in the late 1990s.”

For the collapse crowd, this was the ending they had been writing in their heads for years.

Abu Dhabi stepped in with approximately $25 billion in support. The Burj Khalifa opened in January 2010, renamed from “Burj Dubai” at the ceremony to honor Sheikh Khalifa bin Zayed of Abu Dhabi. Everyone understood what the name change meant. Ten months after opening, 825 of its 900 apartments sat empty. Coverage was gleeful. The world’s tallest building as monument to hubris.

Then something happened that the predictions couldn’t accommodate: Dubai recovered.

Dubai World restructured $23.5 billion in debt by May 2010. Nakheel repaid its restructured obligations ahead of schedule and posted AED 860 million in profit by year-end 2010. By October 2012, Burj Khalifa occupancy hit 80%. By 2024-25, it was running between 85 and 90 percent, with capital values reaching AED 3,930 per square foot (a 60% increase since 2021).

Dubai’s population doubled from 1.8 million in 2009 to 4 million by August 2025. Property transactions hit 205,100 residential sales worth $147 billion in 2025. The city attracted more greenfield FDI projects than any other city on earth for the fourth consecutive year.

Consider that the same pattern repeated in miniature with Emirates airline. In 1985, when Gulf Air cut service to Dubai, Sheikh Mohammed started a national airline from scratch: five months to launch, $10 million in seed funding, two planes wet-leased from Pakistan International Airlines. First year: 260,000 passengers and 10,000 tons of freight. Gulf Air’s profits dropped 56%. Analysts called it vanity.

By fiscal year 2024-25, the Emirates Group posted $34.9 billion in revenue and $6.2 billion in profit on a fleet of 260 aircraft. It is the most profitable airline in the world. Jebel Ali Port, dismissed as overkill for a small Gulf emirate, now handles 15.5 million TEUs annually, ahead of Rotterdam and Hong Kong. Capacity built ahead of demand reads as hubris to forecasters who assume demand is fixed. It reads as strategy to anyone who has watched Dubai for more than one cycle.

Mohammed Alabbar, chairman of Emaar Properties, said: “Crises come and go. And cities move on.”

The Story That Doesn’t Update

Sheikh Rashid reportedly told an advisor: “My grandfather rode a camel, my father rode a camel, I drive a Mercedes, my son drives a Land Rover, his son will drive a Land Rover, but his son will ride a camel.” He saw the timeline. The urgency that built Dubai came from that awareness, not from Western op-eds. The response to that urgency was to convert the windfall, relentlessly, into infrastructure, connectivity, and institutional capacity that would outlast the resource.

The real risks exist: concentrated decision-making in a single ruling family, dependence on Abu Dhabi as a financial backstop (as 2008 proved), and a structural reliance on migrant labor with limited political voice. A properly calibrated framework would interrogate those vulnerabilities. Instead, the predictions keep defaulting to “oil will run out” for a city that already ran past oil and kept growing.

The crisis was real. The recovery wasn’t supposed to be. The predictions have been wrong for thirty years because they were never really about economics. They were about sustaining a story of how wealth is supposed to work. And stories, unlike economic models, don’t update when the data comes in.

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49 tweets between 3 and 4 a.m. One every 80 seconds. That was Elon Musk on February 2, 2025, while he was ostensibly leading the federal government’s efficiency initiative.

His friends have begged him to stop. “Get an ice cream cone. Just don’t use Twitter,” pleaded one investor. Grimes, the mother of three of his children, publicly wrote: “I love you but please turn off ur phone.”

His own response: “I think I should not tweet after 3 a.m.”

He kept tweeting after 3 a.m.

I wanted to understand why. Not the pop psychology version, but the structural version.

The Hotel Safe at 3 a.m.

In 2019, Tesla board member Antonio Gracias locked Musk’s phone in a hotel safe. Gracias entered the code himself so Musk couldn’t retrieve it. A well-meaning intervention, the kind of thing friends do when the habit has gotten bad enough that other people can see the damage.

Musk woke at 3 a.m. and called hotel security to crack the safe open. Walter Isaacson, who spent two years shadowing Musk, leads with this anecdote when discussing his relationship to Twitter. Most people hear it and think “addiction.” I did too, at first. Then I looked at the numbers.

In 2018, the Wall Street Journal analyzed 4,925 of his tweets and found it was common for him to post more than 30 times in a single day. By mid-2024, independent analysts measured 67.8 tweets per day over a seven-week span.

Then the 2024 election arrived. Le Monde counted 101 tweets daily between October 5 and November 5. The Washington Post documented 3,870 posts in 26 days (roughly 130 per day), generating over 33 billion views.

During his first 15 days heading DOGE, Irish broadcaster RTÉ counted 1,494 posts, peaking at 178 on a single day. The content shifted as dramatically as the volume: the Washington Post found political tweets rose from 2% of his feed in 2021 to 17% in 2024.

A 2025 academic paper in SAGE Open, analyzing 2,391 tweets through personality modeling, documented the transformation from “neutral and technology-centric discourse” to “politically engaged and emotionally charged presence.”

An independent analyst cross-referenced his posting times with Jack Sweeney’s private jet tracker to estimate time spent on the platform. The conservative number was 3.2 hours a day.

The richest person on earth spends more time posting than most people spend commuting. And the curve is still going up.

The natural response is that he’s wasting his time. That it’s ego, or compulsion, or both. But there’s a problem with that explanation, which is that the returns are enormous and measurable.

And there’s a problem with calling it pure strategy, too: no strategist calls hotel security at 3 a.m. to crack a safe for his phone. The compulsion and the payoff are wired into the same system. Tracing how that system works starts with the money.

The $0 Marketing Department

Tesla, through 2022, spent effectively $0 on traditional advertising. Zero. GM spent $5 billion annually. Ford spent $4.3 billion. Tesla spent nothing. Musk’s personal account (more followers than Ford, Chevrolet, and Chrysler combined) was the marketing department.

The company reached a trillion-dollar market cap on the back of earned media, and Musk’s timeline was the engine producing it. Tesla topped the Wall Street Journal’s list of brands with cultural traction, beating Apple and Nike.

Each individual tweet carried financial weight that entire corporate communications departments couldn’t match. His August 7, 2018, “funding secured” tweet drove Tesla stock up 11% intraday before a halt; expert testimony in the subsequent class-action case estimated $12 billion in aggregate investor harm.

On the upside, a single 2025 tweet detailing Tesla’s AI chip roadmap added approximately $90 billion in market cap in one session. An academic event study analyzing 47 crypto-related Musk tweets found individual posts moved Bitcoin by up to 16.9% in either direction.

No other individual on earth can move this much capital with a sentence typed on a phone. The people closest to him knew it, and they tried to stop it. Tesla investor Joseph Fath compared Musk’s tweeting to Lindsay Lohan’s erratic public behavior and emailed him: “Remember the golden rule. Delete. Don’t Tweet.”

Less than three weeks later, Musk sent the “funding secured” tweet that led to $40 million in SEC fines. The SEC settlement required his resignation as chairman and a consent decree mandating pre-approval of tweets containing material business information, a mechanism people around him called the “Twitter sitter.”

Musk repeatedly violated it. When he tried to terminate the consent decree in 2022, Judge Lewis Liman denied the motion, calling his arguments “meritless.” The Second Circuit upheld the settlement in May 2023. He kept posting.

The hotel safe, the SEC consent decree, the pleas from investors, the judge calling his legal arguments meritless: these are all attempts to build a wall between this man and his phone. Every single one failed. And when you see the returns those tweets generate, you start to understand why.

But advertising replacement and market-moving are the obvious parts. The less obvious part is what happened after he bought the platform.

The Man Who Owns the Acoustics

In February 2023, Musk’s Super Bowl tweet about the Philadelphia Eagles received roughly 9 million impressions. President Joe Biden’s Super Bowl tweet got 29 million. For a man who had just paid $44 billion for the platform, this was apparently intolerable.

Musk flew his private jet to Twitter headquarters that Sunday night. His cousin James Musk sent a Slack message to engineers at 2:36 a.m. flagging a “high urgency” issue. Approximately 80 engineers were pulled in.

By Monday afternoon, the recommendation algorithm included what internal documents called a “power user multiplier” that boosted Musk’s tweets by a factor of 1,000.

When Twitter open-sourced its recommendation algorithm two months later, the code revealed “author_is_elon” as its own category, sitting alongside “Democrat,” “Republican,” and “Power User.”

A literal hardcoded privilege in the system. Internal estimates found over 90% of Musk’s followers now see his tweets in their “For You” feed. Platformer broke the story. Bloomberg confirmed it.

Rather than just owning a megaphone, he owned the acoustics of the room.

The effects were … measurable. Queensland University of Technology researchers found a statistically anomalous engagement boost starting July 13, 2024 (the day of his political endorsement): view counts up 138%, retweets up 238%, likes up 186%, far outpacing comparable political accounts. The AP found his interactions with a German politician boosted her daily audience from 230,000 to 2.2 million.

During the four months around the 2024 election, his posts received 133 billion views: 15 times the audience of any individual elected official, more than 16 times the combined reach of all incoming members of Congress.

But reach is a broadcasting metric. What the algorithm actually gives him is something closer to cognitive infrastructure: 133 billion moments where his framing of an event arrives before anyone else's. When a story breaks on X, Musk's interpretation is often the first one users encounter, and the first frame installed tends to be the one everything else gets measured against. He owns the order in which people receive their thinking.

Political strategists spend millions finding the right word for a policy; “death tax” polls differently than “estate tax.” Musk skips the word choice entirely. He controls the infrastructure through which the words travel, determining which stories get oxygen and which suffocate.

Paddy Leerssen, a researcher at Stanford’s Center for Internet and Society, published a paper in 2025 naming what Musk was doing: “economic instrumentalism,” which he defined as leveraging platform control over public discourse to protect a portfolio heavily dependent on government contracts. Musk’s companies have received $38 billion in cumulative government contracts, loans, subsidies, and tax credits. The posting and the portfolio are connected, and the connection runs through the algorithm.

The Ledger

So there are two sides to this, and the tension between them is what makes Musk so hard to categorize.

On one side: a trillion-dollar company built on $0 in advertising, 220 million followers, 133 billion views in four months, a government appointment, and $38 billion in contracts across his companies.

On the other: a Yale and NBER study (the first rigorous academic analysis of CEO partisan activity’s impact on sales) found his polarizing behavior since October 2022 cost Tesla between 1 million and 1.26 million U.S. vehicle sales. Monthly sales by Q1 2025 would have been approximately 150% higher without the partisan activity. Competitors’ EV sales increased 17 to 22% as customers substituted away. Tesla’s brand value collapsed from $58.3 billion to $27.6 billion, a 53% decline in two years, per Brand Finance.

Then there’s the advertiser exodus. In November 2023, Apple, Disney, IBM, Comcast, Warner Bros., and Paramount all pulled their ad spending from X. Internal documents tracked over 200 ad units from companies pausing or considering pausing. At the DealBook Summit shortly after, Musk told departing advertisers to “go f*ck yourself,” specifically calling out Disney CEO Bob Iger. Then acknowledged the boycott could “kill the company.” U.S. advertising revenue during a five-week span in spring 2023 had already plunged 59% year-over-year.

A million lost car sales and a 53% brand value collapse on one side. A $38 billion government contract portfolio and 133 billion views on the other. Both columns are growing simultaneously, which is exactly what makes the standard explanations fall apart.

Most analysis tries to resolve this tension by picking a side. Either he’s a genius playing 4D chess, or he’s someone who can’t stop posting. I think the more honest read is that both are true simultaneously, and that the inability to separate them is the whole point.

At CNBC, Musk offered his own version: “I’ll say what I want to say, and if the consequence of doing that is losing money, so be it.”

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The Ford Parallel

When people reach for historical comparisons, they usually mention Hearst, Murdoch, or Berlusconi. But the parallel with real structural teeth is Henry Ford.

After losing a Senate race in 1918, Ford bought a newspaper and used it to shape public discourse by owning the outlet directly. The paper reached circulation of 700,000 to 900,000, partly because Ford required every dealership to distribute it.

Every Ford showroom in America became a node in a media distribution network. If you walked in to look at a Model T, you walked out with Ford’s newspaper. A forced-distribution system structurally identical to Musk’s algorithmic self-amplification: you don’t just write the content, you also control the delivery infrastructure that puts it in front of people whether they asked for it or not.

Ford’s “Mr. Ford’s Page” column, where the industrialist spoke directly to a captive audience and bypassed editors entirely, is a direct ancestor of the Musk timeline.

Both men built a manufacturing empire first, then acquired a media channel to protect and extend it. Both understood that owning production wasn’t enough; you had to own the narrative around the production. And both discovered that once you control the distribution infrastructure, there is no external check on what travels through it.

But Ford’s system had limits Musk’s does not. Ford owned factories and a newspaper, but he couldn’t measure in real time which articles resonated, couldn’t adjust distribution speed by the hour, couldn’t suppress a competitor’s message while amplifying his own. He never held a government appointment.

Musk owns the platform, the algorithm, the content, and the audience simultaneously. He can post, boost the post, suppress competitors, and measure the results in real time, all within one system.

Hearst owned newspapers but not factories. Berlusconi held office and broadcast licenses but didn’t manufacture anything. Nobody before Musk has fused media ownership, industrial production, government authority, and personal celebrity into a single integrated operation.

The Engine

Former Tesla employee Christian Marcus described on LinkedIn how this integration actually worked day to day:

“When Elon Musk was informed that we were about to implement a new solution, he would respond in his Twitter feed and let our customers know... This created a powerful communication strategy that made it seem like we were able to react to customer needs and implement changes at lightning speed.”

The company looked impossibly responsive because the CEO’s timeline was synchronized with the engineering team’s deployment schedule. The tweets were coordinated announcements disguised as spontaneity.

That coordination extends across the entire portfolio. Tesla’s vehicle fleet generates physical-world data. X generates human discourse data. xAI’s Grok was designed to leverage X’s live information stream. Together they create a proprietary advantage no competitor can replicate, because no competitor owns both the cars and the conversation.

And the platform keeps getting harder to leave. Government agencies now use X as their primary communication channel, embedding it in public infrastructure. A 2022 paper in Celebrity Studies found that Musk represents “a hyper-celebrified mode of management that has yet to be reproduced by any other executive,” one grounded in “constant conflict” rather than the usual corporate optimism.

A 2025 study in Public Relations Review found that controversy from celebrity CEOs leads to immediate stock declines, but those declines are “partially buffered by high message visibility.”

The more visible you are, the more the market forgives you for being erratic. And Musk is the most visible CEO who has ever lived.

All of it feeds a single loop. More posting drives more followers (his count has more than doubled since acquiring X, reaching 220 million, with no other top account achieving comparable continuous growth). More followers generate outsized influence. That influence converts to political access. Political access protects $38 billion in government contracts across SpaceX, Tesla, and his other companies. And those business resources sustain control of the platform where the posting happens.

As Harvard political scientist Steven Levitsky put it: “This is a combination of economic, media, and political power that I believe has never been seen before in any democracy on Earth.”

Isaacson posed what I think is the right question: “Would a restrained Musk accomplish as much as a Musk unbound?”

The answer is probably “no.”

The same compulsive energy that wakes him at 3 a.m. to break into a hotel safe for his phone is the energy that built a trillion-dollar company on zero advertising dollars.

The same impulsivity that cost a million car sales also produced 133 billion views in four months. The strategic and the pathological are fused, and that fusion is the engine.

The people around Musk have tried everything to separate them. Hotel safes, SEC consent decrees, judicial rulings, public pleas from the mother of his children. None of it worked, and none of it was going to, because the system he’s built doesn’t distinguish between the compulsion and the strategy.

They run on the same circuit, through the same phone, at the same hour of the night.

“I’ll say what I want to say, and if the consequence of doing that is losing money, so be it.”

The phone is where the trillion dollars lives.

In 1989, Alexey Pajitnov had created the most addictive video game on the planet. Tetris was generating millions of dollars across three continents.

His compensation from the Soviet Academy of Sciences: one IBM PC/AT, already obsolete by Western standards.

Pajitnov wasn’t robbed. That framing assumes a thief, a victim, and a shared understanding of what “ownership” means. The category “game designer who owns his creation” didn’t exist. Not suppressed. Not forbidden. Just absent, the way a color you’ve never seen is absent.

The Soviet system had no slot for Pajitnov, and the Western system had no way to explain why.

This is a story about what happens when two worlds collide and discover they aren’t even disagreeing.

The Crowded Desk and the Missing Category

Pajitnov woke between 7:30 and 8 AM, “maybe later, because I worked until midnight every day.” Breakfast was sausage, eggs, and cottage cheese.

He arrived at the Computer Center of the Soviet Academy of Sciences around 10 AM, where his workspace was, in his own words, “extremely crowded, a room built for four or five people seated at desks. On most days it had to accommodate 15 researchers.” He shared his desk with three other people.

The real work happened late, after the desk cleared out.

The Computer Center was busy solving differential equations for outer space and nuclear war. “Nobody gave a shit about this stuff, you know, a small, little game,” Pajitnov said. “Games were something absolutely alien for them.” He built the first Tetris prototype in two weeks on an Elektronika 60 with only 8 kilobytes of RAM, programming in Pascal.

Meanwhile, the KGB was interested in his other work: automatic speech recognition. They wanted to build an audio surveillance system that would start recording automatically when certain “dangerous” keywords were uttered. Pajitnov and his colleagues “tried to avoid, obviously.”

That detail has stayed with me. The KGB showed up at Pajitnov’s crowded desk for the speech recognition work. Nobody showed up for Tetris. The system’s priorities were internally consistent.

The only tangible reward the system ever gave him for creating the most popular video game in history was that single obsolete computer.

He had signed over the rights to the Computer Center for ten years: “It was easier and wiser for me to allow this arrangement than to try to fight for certain personal rights that were almost non-existent during that time.”

And then, remarkably: “You can’t imagine how much internal laws and instruction I overstepped during this time. It’s unbelievable. So if somebody would really look at me, I would be definitely in jail.”

No bitterness. His public stance has been consistently philosophical: “I didn’t make much money at first.” He said he was “happy that so many people were enjoying his creation.”

Pajitnov inhabited a world where the concept of individual ownership of creative software simply did not exist. You can’t feel robbed of something your entire reality has no container for.

A Gray World With No Advertisements

In February 1989, a Hawaiian game designer named Henk Rogers flew to Moscow on a tourist visa, which meant even discussing business was technically illegal. His overwhelming impression was captured in a single word: gray. Gray skies, gray streets, gray and unsmiling people.

The television in his Intourist Hotel room showed only static. The radio played only noise. What disturbed the born marketer most was the complete absence of advertisements: “Nobody was trying to sell you anything!” His brother, who accompanied him on a later trip, “likened it to being in a prison. No colour anywhere.”

Rogers had catastrophic reasons for being there. He’d already convinced Nintendo of America president Minoru Arakawa to bundle Tetris with every Game Boy. Two million dollars’ worth of Game Boy units were already being manufactured, and his in-laws’ property in Hawaii was pledged as collateral.

“I was in deep ‘kimchi,’” Rogers told SpyScape, “because I had 200,000 game cartridges at $10 apiece being manufactured in Japan, and I’d put up all of my in-laws’ property as collateral.” Failure would have destroyed not just his company but his extended family’s financial security.

He couldn’t even find ELORG, the Soviet agency that controlled the Tetris rights. The hotel information desk had no listing. He hired an interpreter from a booth in the hotel lobby who he was certain was KGB but who knew exactly where to go.

Then Rogers did something no Soviet bureaucrat would have anticipated. He simply walked up unannounced and knocked on the front door.

“It was like walking into an ant’s nest because people don’t walk in off the street. Everyone has an appointment and I was supposed to go to a window and present my credentials and I didn’t. I just talked to a random person and said, ‘I’d like to speak to somebody about Tetris,’ and I showed him my little NES version of the game.”

He was promptly interrogated for two hours. Seven people were in the room, “some of them KGB types, being given the third degree.” Rogers’s way of charming police during speeding tickets, he noted, “wasn’t going to work in Moscow. I felt I could end up in a gulag.”

Rogers held up a Nintendo cartridge containing Tetris. To him, it was a commercial product with licensing rights attached to a chain of creators and distributors, and he needed to secure those rights or lose everything.

To the seven officials staring at him, it was something else entirely: unauthorized reproduction of state intellectual property, created by a state employee at a state institution, the rights to which belonged to a state agency.

Same plastic cartridge, two incompatible realities. Thomas Kuhn noticed this same structure in the history of science: where a Newtonian sees a pendulum, an Aristotelian saw constrained free fall.

Same swinging weight, different ontologies. The men in that room weren’t disagreeing about who owned Tetris. They were looking at the same object and seeing different realities.

Foxes, Bodyguards, and a Pidgin for Power

Rogers wasn’t operating inside anyone’s paradigm. He was improvising at a boundary between worlds that had no common language for what was happening. So how did the deal get done?

The answer involves a Soviet bureaucrat named Nikolai Belikov, and it reveals how coordination happens even when mutual understanding doesn’t. Belikov replaced Alexander Alexinko in handling the Tetris negotiations in October 1988, and he was no ordinary apparatchik.

He had built a reputation as “the consummate bureaucratic in-fighter, a master of the art of the well-timed back stab whom you trifled with at your peril. He was the sort of man who was put on the job to do an agency’s dirty work.”

When Rogers walked in unannounced, Belikov didn’t turn him away. He realized “a third party to play against the other two could be a very good thing to have.” Robert Stein, the Hungarian-born middleman who had first brought Tetris to the West, was a “pugnacious” operator whose fatal habit was selling rights before securing them.

He’d sold Tetris PC rights to Mirrorsoft for £3,000 plus royalties before he had any signed agreement from Moscow, maintaining a “Chinese wall” between his Western partners and the Russians, keeping each side ignorant of what the other knew.

Belikov dismantled him by adding a clause to Stein’s contract specifically excluding console rights while distracting him with other changes. “Stein, so focused on just getting the rights, neglected to see the new clause.”

The physicist Peter Galison studied this kind of problem in twentieth-century physics, where theorists, experimentalists, and instrument-makers from entirely distinct communities somehow managed to do productive work together.

His concept was the “trading zone”: a space where two groups can agree on rules of exchange even if they ascribe utterly different significance to the objects being exchanged. Contact languages develop in stages, Galison observed. Jargons become pidgins, pidgins become full-scale creoles.

Belikov was building a trading zone. He didn’t need Rogers, Nintendo, or Stein to share his understanding of what Soviet state property meant. He just needed them to converge on specific terms for specific rights in a specific room. And he found an unlikely counterpart in Nintendo’s Howard Lincoln.

The two were described as “two sly old foxes with far more in common than the gulf of culture, language, and politics that lay between them might suggest.” They “sniffed one another out.”

The signing ceremony on March 22, 1989, had the weight of deliberate theater. Lincoln and Arakawa had traveled to Moscow in secret, telling only two confidants where they were going and using a cover story about visiting Nintendo’s parent office in Japan.

Two heavyweight Soviet bureaucrats attended as witnesses. Nintendo guaranteed ELORG would make at least $5 million. Previous negotiations had dealt in nickels and dimes, “$50,000 here, $100,000 there.” Nintendo’s offer “elevated the discussion to another financial plane entirely.”

But Belikov faced real consequences for building his trading zone. Several influential Soviet officials were displeased. He was questioned by prosecutors. There were rumors of bugs in telephones and men in trench coats trailing people through the streets.

Belikov hired a pair of personal bodyguards. His defense was elegant: Gorbachev said producers needed economic freedom. He was “just doing perestroika.”

Meanwhile, Mirrorsoft’s position had already been torpedoed by Kevin Maxwell, son of media baron Robert Maxwell. When Belikov showed Kevin a Tetris cartridge for the Nintendo Famicom during a meeting, Maxwell had no idea what it was, despite the fact that his own company supposedly held the console rights.

Instead of asserting Mirrorsoft’s claim, he told Belikov he would “entertain a deal” for the console rights, inadvertently confirming that Mirrorsoft’s position was hollow.

When Kevin told his father, Robert Maxwell “went apeshit” and contacted Gorbachev directly. Gorbachev, dealing with a country on the verge of collapse, told Maxwell: “You should no longer worry about the Japanese company.” By then, the contract was signed.

Stein, the man who first brought Tetris to the West, reportedly walked away with only $150,000 to $200,000 total. He “never really got over losing Tetris since he believes it turned friends into enemies.” He died in 2018.

But trading zones don’t always get built successfully. On February 6, 1840, at Waitangi in New Zealand, Captain William Hobson signed a treaty with Māori chiefs. The English text stated that Māori ceded “all the rights and powers of sovereignty.”

But the missionary translating overnight rendered “sovereignty” as “kawanatanga,” a neologism with no prior existence in Māori, while the Māori text guaranteed chiefs “tino rangatiratanga” (full chieftainship).

A bystander known as “Trader Jack” interrupted the proceedings: “Begging your pardon, Sir, but it’s that Mr Williams. He’s not translating a good half of what the Māori say.” In 2014, the Waitangi Tribunal concluded that “the rangatira who signed te Tiriti did not cede their sovereignty.”

No shared object. No pidgin. Just two complete worldviews, each internally coherent, generating a wound that 185 years have not closed.

Belikov’s achievement was building the narrow table at which incommensurable parties could sit. Whether what happened there constituted understanding or merely coordination is a question the participants themselves might not have been able to answer.

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The Pidgin That Worked

Amid all the foxes and bodyguards and collapsing empires, the friendship between Rogers and Pajitnov is the thread that makes this story more than a business case.

When they met during the ELORG negotiations, Pajitnov saw something different from the parade of suited businessmen: “Finally out of all this dressed-in-suit business world, I saw a guy who really liked and understood the game. And somehow we liked each other, almost immediately.”

Rogers recalled: “He was the friend I was looking for in Russia. We got together that night, started talking about game design, immediately jumped into Tetris II. We had stuff to talk about.”

That first night, they drank vodka inside the Pajitnov family’s humble apartment, communicating despite Pajitnov’s broken English and Rogers’s nonexistent Russian. The recognition was professional. “Alexey figured out right away that I was not just some con artist, I was a game designer.”

Rogers noted the decisive difference between himself and Robert Stein: Pajitnov “offered me nothing and asked for nothing.”

Two game designers, from incommensurable worlds, who could not agree on what ownership meant, what a government was for, or what an individual creator was owed. But they could recognize each other across the gap. They could talk about game design. That narrow band of shared understanding became the pidgin through which everything else was eventually negotiated.

For Rogers and Pajitnov, the shared object was the game itself. Trading zones don’t require mutual comprehension. They require something both sides can point to, even if they describe it in different languages. Belikov built his zone out of contract clauses and hard currency. Rogers and Pajitnov built theirs out of falling blocks and vodka.

The long arc confirms it. Pajitnov immigrated to the United States in 1991, settling in Bellevue near Seattle. His work visa was sponsored by Rogers’s company. Six months later, his wife Nina and their sons Peter and Dmitri joined him.

Rogers sold a 15-year license to Tetris to Jamdat (later EA) in 2005 for $137 million, cleverly retaining ownership: “I get the rights back in five years so I can sell them again.” He became one of the wealthiest people in Hawaii.

Belikov, savvy as ever, turned ELORG into a private company after the USSR dissolved and sold his Tetris stake in 2005 for $15 million, with the deal signed in Panama, “in an episode that had much the same spy-movie flavor as the original negotiations.”

The Color You’ve Never Seen

Pajitnov got his computer, then got his freedom, then got his royalties. Rogers risked his family’s home and won a fortune. Stein brought Tetris to the world and died having never recovered from losing it. Belikov became a capitalist. Maxwell lost out.

Kuhn articulated something scholars call “Kuhn Loss”: when one paradigm gives way to another, “problems whose solution was vitally important to the older tradition may temporarily disappear, become obsolete or even unscientific.”

They don’t get answered. They become unthinkable. When the Soviet system dissolved, certain questions (who does creative output belong to collectively? how should a state allocate intellectual work?) didn’t get resolved; they simply evaporated.

At the end of The Structure of Scientific Revolutions, Kuhn asserted that science does not evolve toward anything but only away from something. There is no destination. There is only departure.

The Tetris story works the same way. We didn’t arrive at a resolution where everyone finally agreed on what intellectual property means, who creative output belongs to, or what a game designer deserves. We just departed from one configuration and entered another.

And what stays with me is not who won. It’s the moment before the collision, when each side’s categories were complete and internally coherent and absolutely invisible to the other.

The Soviet system wasn’t evil for failing to compensate Pajitnov. It was something more unsettling than that: it was whole. It had its own logic, its own categories, its own coherent way of making sense of creative work. The slot for “game designer who owns his creation” was absent, the way a color you’ve never seen is absent.

And no amount of arguing, negotiating, or even winning can make you see a color that isn’t in your spectrum.

Only a shared game could do that. And even then, only between two people at a kitchen table, not between two worlds.

On November 17, 2023, Sam Altman clicked a Google Meet link in a Las Vegas hotel room and learned he had five minutes before a blog post would announce his firing as CEO of an $86 billion company.

Microsoft, the company’s largest investor at $13 billion, got sixty seconds of warning.

The board’s entire justification fit into six words: “not consistently candid in his communications.”

What followed was the most unhinged five days in Silicon Valley history: a 52-page secret dossier sent via disappearing emails, a wooden effigy burned in a forest, 97% of employees threatening to quit, and a smoke machine setting off fire alarms at the victory party.

But the real story is what happens when the legal structure of a company and the lived reality of that company become two completely different things. Four people with zero equity tried to blow up a $90 billion enterprise over a weekend.

This crisis exposed a dynamic with implications far beyond tech: structural drift. It’s what happens when an organization’s formal governance framework stays fixed while the lived reality of the organization changes underneath it.

The charter stays the same. The bylaws stay the same. But the organization quietly becomes something else, and nobody updates the paperwork, because everyone implicitly agrees on what the organization actually is.

The formal structure becomes decorative. Then one day, someone tries to use it for its intended purpose, and the whole thing detonates.

That’s exactly what happened at OpenAI. The board tried to exercise the authority the charter gave them. They had the legal right. They had documented evidence. They may have been right on some of the merits. And they discovered that the authority existed only on paper, because the organization described in the charter and the organization experienced by 770 employees, $13 billion in Microsoft capital, and a hundred million users had become two entirely different things.

The question that matters is how the gap between charter and reality grew so wide that nobody noticed until it was too late.

The Structure That Made It Possible

OpenAI was incorporated in December 2015 as a 501(c)(3) tax-exempt nonprofit in Delaware. Its founding donors, including Altman, Elon Musk, Reid Hoffman, and Peter Thiel, pledged $1 billion, though only about $130 million was actually collected.

The charter declared a fiduciary duty not to shareholders but “to humanity.” The mission: ensure artificial general intelligence benefits all of humanity.

By 2019, it became clear that donations couldn’t fund the billions needed to train frontier AI models. So the board created something baroque: a “capped-profit” subsidiary called OpenAI Global LLC, managed by the nonprofit through a shell entity. Investors and employees could earn returns, but those returns were capped at 100x for the first round, with anything beyond the cap flowing back to the nonprofit.

The operating agreement contained a sentence that still makes my jaw drop every time I read it: investors should view their money “in the spirit of a donation, with the understanding that it may be difficult to know what role money will play in a post-AGI world.”

The nonprofit’s six-person board was the supreme governing authority over everything. Microsoft held a roughly 49% profits interest but zero governance rights.

No investor had a board seat, a veto, or any protective provision. The board’s fiduciary duty ran to the charitable mission, not to profit generation.

This structure made perfect sense in 2019. It made progressively less sense every month after ChatGPT launched in November 2022 and reached a hundred million users in two months.

By late 2023, the structural drift had become a chasm. The board governed a nonprofit with a safety mission that happened to run a commercial subsidiary.

The employees, the investors, and Microsoft worked at an $86 billion technology company that happened to have a nonprofit parent. Both versions were internally coherent. Both were defensible on their own terms. They just couldn’t coexist in the same boardroom.

And the board that governed one of the fastest-growing companies in history? It included Adam D’Angelo, the Quora CEO whose AI platform Poe directly competed with OpenAI’s GPT Store, a conflict no one addressed. It included Helen Toner, a Georgetown academic who joined the board through effective altruist networks. It included Tasha McCauley, who co-founded Fellow Robots and taught robotics at Singularity University.

None of them had experience governing a company at this scale.

And it included Ilya Sutskever, OpenAI’s chief scientist. Sutskever had co-invented AlexNet under Geoffrey Hinton at the University of Toronto and catalyzed the deep learning revolution. He was OpenAI’s intellectual core.

He was also the person who, at a September 2022 leadership offsite at Tenaya Lodge in the Sierra Nevada, commissioned a wooden effigy from a local artist. It represented a “good and aligned AI” that turned out to be “lying and deceitful.”

Researchers in bathrobes formed a semicircle beneath ancient redwoods. Sutskever doused the effigy in lighter fluid and set it ablaze. They watched in silence. At the 2022 holiday party, he led employees chanting “Feel the AGI!”, a moment so memorable that staff created a custom Slack reaction emoji. Three employees told reporters he had started “acting like some sort of spiritual leader.”

These four people had the legal authority to fire Sam Altman with zero notice. That authority was about to collide with reality.

A Year of Waiting and a 52-Page Bomb

The coup did not happen overnight. In his sworn October 2025 deposition in the Musk v. Altman lawsuit, Sutskever revealed he had been contemplating Altman’s removal for at least a year before it happened.

The problem was board composition. With Reid Hoffman, Shivon Zilis, and Will Hurd on the board (all considered Altman-friendly), the votes weren’t there. But across 2023, all three departed: Hoffman over conflicts with his own AI investments, Zilis quietly, and Hurd for a quixotic presidential campaign. Their seats were never filled because the remaining directors couldn’t agree on replacements.

“I was waiting for a moment when the board dynamics would allow for Altman to be replaced,” Sutskever testified. “That the majority of the board is not obviously friendly with Sam.” The chief scientist of one of the most consequential organizations in the world spent a year watching board seats empty, waiting for the arithmetic to tip. This was patient.

In October 2023, the catalyst arrived. Sutskever and CTO Mira Murati approached the independent board members with what Toner described as “really serious” conversations.

They used the phrase “psychological abuse.” They said Altman cultivated “a toxic culture of lying.” Murati reportedly told the board: “Altman had a simple playbook: first, say whatever he needed to say to get you to do what he wanted, and second, if that didn’t work, undermine you or destroy your credibility.”

Sutskever added: “I don’t think Sam is the guy who should have the finger on the button for AGI.”

Sutskever compiled his evidence into a 52-page memo. Its opening line: “Sam exhibits a consistent pattern of lying, undermining his execs, and pitting his execs against one another.” He sent it only to the three independent directors using Gmail’s disappearing-message feature.

When asked in his deposition why he used self-destructing emails: “Because I was worried that those memos will somehow leak.”

When asked why he didn’t send it to Altman: “Because I felt that, had he become aware of these discussions, he would just find a way to make them disappear.”

Toner, in a May 2024 TED AI Show interview, laid out the specific instances behind the board’s six-word justification. Two stand out for their concreteness.

When ChatGPT launched in November 2022, the most consequential product launch in AI history (maybe in history, period), the board was not informed in advance: “We learned about ChatGPT on Twitter.”

And when OpenAI’s restrictive agreements threatening to claw back departing employees’ vested equity became public, Altman said he had not been aware of the specific provisions. Vox later obtained incorporation documents from April 2023, bearing his signature, that explicitly authorized them. Whether that reflected genuine unawareness of boilerplate language or something else, it became another data point in the board’s case.

Toner cited additional instances involving the OpenAI Startup Fund and internal safety processes. “We just couldn’t believe things that Sam was telling us,” she said. “And that’s a completely unworkable place to be in as a board.”

Here is the detail that keeps nagging at me. Much of the memo’s content came from a single source: Mira Murati. Sutskever admitted under oath that he never independently verified several key claims, including allegations that Altman had been “pushed out from Y Combinator for similar behaviors.”

When asked why he didn’t verify with Brockman directly: “It didn’t occur to me.” In hindsight, he conceded, “secondhand knowledge is an invitation for further investigation.”

This is where process collapsed.

Whatever the merits of the underlying concerns, a 52-page document built partly on unverified secondhand claims, distributed via disappearing messages, used to justify the termination of a CEO running an $86 billion company with no advance notice to investors, is not a process. It’s a conspiracy. And I don’t mean that pejoratively.

The board members genuinely believed they were protecting humanity. They were operating entirely within the version of OpenAI described in the charter: a nonprofit whose board had unchecked authority and a fiduciary duty to all of mankind.

Within that version, their actions were logical.

The problem was that almost nobody else inhabited that version anymore.

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When De Jure Met De Facto

Thursday, November 16. The four dissenting board members held a furtive video call and voted to fire Altman. That evening, Murati was informed she would become interim CEO.

Friday, November 17, noon. Altman clicked the Google Meet link. Sutskever read a prepared statement. Altman recalled: “It was very strange. I couldn’t get any questions answered. I really did in that first moment think I was having some crazy vivid dream.” Nineteen minutes later, Brockman was told he was removed from the board but “vital to the company.” By 12:30 PM, the blog post was live. Altman’s email and computer access were immediately deactivated.

That evening, as he prepared to fly from Las Vegas back to San Francisco, Oliver Mulherin put his hands on Sam’s shoulders at the foot of the airplane stairs: “Sam, I’m with you 100 percent no matter what, but what the f*ck did you do?” Altman: “Gosh, no!” Oliver: “Okay, I’m good.” They boarded the plane.

Saturday, November 18. Altman had a call with two board members who floated his return. His first reaction: “Absolutely not.” His second: “I will come back if all of you resign right now.” He later called this “not a constructive thing” and said a more diplomatic response might have ended the crisis that morning.

That evening, Altman tweeted “i love the openai [sic] team so much,” and employees began quote-tweeting it with heart emojis en masse, a coordinated signal of loyalty, a headcount of who would follow him out the door. It was most of the company. The first tremor of de facto power making itself felt.

Sunday, November 19. Negotiations, mediated remotely by Satya Nadella, continued all day. The board agreed in principle to resign, then reversed course and installed Emmett Shear as interim CEO.

Shear, the former Twitch co-founder, was on paternity leave with a nine-month-old son. He estimated his personal probability of AI-caused human extinction at between 5% and 50%. He was reportedly a character in a Harry Potter fanfiction popular within the effective altruism community. He accepted after reflecting “for just a few hours.”

Meanwhile, the board had already been rejected by GitHub CEO Nat Friedman and Scale AI CEO Alex Wang. They contacted Anthropic CEO Dario Amodei about replacing Altman and proposed merging the two companies entirely. Toner was “the most supportive” of the Anthropic merger. Sutskever was “very unhappy about it.” Amodei declined both proposals.

Then Nadella made the single most decisive move of the entire crisis. He publicly announced that Altman and Brockman would lead a new Microsoft AI research team, with positions available for every OpenAI employee at matched compensation. Microsoft calculated the cost of absorbing the entire team at approximately $25 billion.

Nadella later called it “in a world of bad choices... definitely not my preferred thing,” but “the worst outcome would have been all these people leave and they go to our competition.”

The announcement gave Altman leverage, gave employees a credible exit, and applied existential pressure on the board. Microsoft stock rose 2% to near all-time highs. The board, which had de jure authority, suddenly had no moves left against the de facto coalition assembling against it.

Monday, November 20. Altman was shaken awake by Oliver, still groggy from a sleeping pill he’d taken at 3 AM. “You need to check your phone.” Sutskever had posted his regret. The emotional turning point had come the day before.

According to the Wall Street Journal, Anna Brockman (Greg’s wife, whose wedding Sutskever had officiated in 2019 at the OpenAI offices, with a robotic hand serving as ring bearer) went to the offices and cried and pleaded with Sutskever to change his mind. The man who had married the couple had tried to destroy the company the groom co-founded. The weight of that broke something.

The structural drift had been invisible for years. One exchange during the crisis negotiations made it impossible to miss.

When OpenAI executives warned that Altman’s absence would destroy the company, and that this contradicted the board’s mission, Toner responded that destruction “could be consistent with the mission.” Even Sutskever testified he disagreed: “At that point in time, the answer was definitely ‘No’ for me.”

That single exchange captures the philosophical chasm at the heart of everything. To Toner, the mission was the load-bearing element. If the company had to be destroyed to protect it, so be it. To the 770 employees who built ChatGPT, the company was the mission.

Both positions were internally consistent. Both were, within their own framing, rational. They were just operating inside different versions of the same organization, and when those versions collided in that room, everyone present could finally see the gap that had been widening for years.

By Monday evening, 745 of approximately 770 employees (97%) had signed a letter threatening mass resignation. The signatories included Murati, COO Brad Lightcap, and, astonishingly, Sutskever himself.

Tuesday, November 21. Shear told the board he would resign, too, if a resolution wasn’t reached. By 10 PM, Altman was back as CEO with a new board chaired by Bret Taylor, alongside Larry Summers and Adam D’Angelo. Three of the four directors who had fired him were gone. At the offices, someone brought a smoke machine to the victory celebration. It triggered the fire alarm and dispatched two fire trucks.

I couldn’t make this up if I tried.

What the Collision Destroyed

The new board hired WilmerHale to investigate. The law firm reviewed 30,000 documents and conducted dozens of interviews. Its March 2024 conclusions threaded a diplomatic needle: the prior board “acted within its broad discretion” to fire Altman, but his “conduct did not mandate removal.”

The firing arose from “a breakdown in the relationship and loss of trust,” not from “concerns regarding product safety or security, the pace of development, OpenAI’s finances, or its statements to investors.”

Larry Summers reportedly told people privately that the investigation found “many instances of Altman saying different things to different people” but to a degree the new board decided “didn’t preclude him from continuing to run the company.”

The full report was never released. The dueling narratives hardened. Toner and McCauley, in a 2024 Economist op-ed, criticized the secrecy.

The aftermath reshaped OpenAI completely. By October 2025, the nonprofit had become the OpenAI Foundation, the for-profit had become a Public Benefit Corporation, and the 100x profit cap was eliminated entirely. Microsoft held a 27% equity stake. Altman, who had held zero equity during the crisis, was reportedly in discussions for a 7% stake. The valuation soared from $86 billion to $500 billion.

No employees actually left for Microsoft. Not one. The threat of 97% of the company walking out had been the ultimate negotiating lever. It worked without a single person following through.

The human cost ran in a different direction. Sutskever departed in May 2024 and founded Safe Superintelligence Inc., which raised $3 billion at a $32 billion valuation largely on the strength of his reputation.

Jan Leike, who co-led the Superalignment team, left for Anthropic, writing that “We finally reached a breaking point” Murati departed in September 2024 and founded Thinking Machines Lab, which reached a $12 billion valuation within months. Nearly half of all AGI safety researchers had left by August 2024.

The Superalignment team, Sutskever’s signature initiative that had been promised 20% of OpenAI’s compute, was dissolved entirely.

The four board members had the legal authority to fire Altman. They had documented evidence of what they genuinely believed was systematic dishonesty. They may have been right on the merits.

But they underestimated something fundamental: that de facto power in an organization doesn’t live in the charter. It lives in the 770 people who show up every day, the $13 billion in capital, and the hundred million users who depend on the product.

The nonprofit board had de jure authority over an $86 billion enterprise. The de facto power belonged to the employees, the investors, and Microsoft. It always had.

The Safety Mechanism That Ate Itself

Exercising the safety mechanism destroyed the safety mechanism.

The board members who cared most about keeping OpenAI accountable to its mission were removed. The Superalignment team was dissolved. The profit cap was eliminated. The nonprofit became a foundation with an equity stake. Every structural guardrail that the original charter had put in place to prevent exactly this outcome was dismantled in the aftermath of the one serious attempt to use them.

Toner and McCauley warned in their Economist op-ed that “self-governance cannot reliably withstand the pressure of profit incentives.” They were right, though the pressure didn’t come from investors or shareholders.

It came from 745 people who chose their CEO over their board, a partner willing to absorb the whole team for $25 billion, and a structure that was only as durable as the shared belief that sustained it.

That’s structural drift in its terminal phase. The charter described one organization. Reality had built another. When the charter tried to assert itself, reality won, and then reality rewrote the charter to make sure it could never happen again.

Governance documents describe an organization. But the organization people actually experience is built from accumulated practice, shared investment, and the interpretive frames that 770 people carry to work every morning. When those two versions diverge far enough, the document becomes decorative. The lived version becomes the real charter.

Every organization carries formal structures designed for a version of itself that may no longer exist.

Most of the time, the gap is invisible.

It becomes visible only when someone leans on the wall and discovers it’s no longer load-bearing.

In August 1939, Albert Einstein sat down on Long Island and wrote a two-page letter. By the time its consequences finished unfolding, the United States had spent $2.2 billion (about $46 billion today), employed 130,000 people, and built a weapon that ended one war while starting an entirely new kind of fear.

Two pages. That’s it.

No detailed budget. No technical specifications. No multi-year roadmap. Just a few hundred words that converted a chaotic pile of uncertain physics into something a President could act on without looking reckless.

I used to assume history turned on speeches, on grand moments of oratory. Then you start noticing how often it actually turns on paperwork.

A war starts because of a telegram. A company pivots because of a memo. A scientific field reorganizes itself because of a short preprint. The big machinery only moves after someone produces a small artifact that makes movement permissible.

If you care about how power actually moves in the real world, Einstein’s letter to Roosevelt is the ultimate case study.

The Mechanics of the Letter

I spent a lot of time with this document. The original sits in the FDR Presidential Library archives, dated August 2, 1939, written from Old Grove Road in Peconic on Long Island. You can read every word. And what strikes me isn’t the physics. It’s the structure.

The letter opens with a move that’s easy to miss: Einstein immediately attributes the underlying work to others. “Some recent work by E. Fermi and L. Szilard,” he writes, “leads me to expect…”

Enrico Fermi was already famous among physicists. Leo Szilard was less famous to the public, but he mattered here more than almost anyone. Szilard was a Hungarian-born physicist who had been thinking about chain reactions for years and who had the political urgency of an immigrant watching Europe (once again) slide into catastrophe.

Einstein was the amplifier. Szilard was the engine.

Then comes something else that’s easy to miss: the letter mixes scientific possibility with operational guidance. Einstein tells Roosevelt that a nuclear chain reaction in uranium may be possible “in the immediate future,” and that this would lead to power and “the construction of bombs.”

He’s careful about uncertainty. He notes that it is “conceivable” that “extremely powerful bombs of a new type” could be built, but also that such bombs might be too heavy for delivery by air.

That last detail is one of my favorites. In the same paragraph where he helps usher in the nuclear age, Einstein still imagines the bomb as something “carried by boat and exploded in a port.” The future arrives wrapped in the constraints of the present.

On the second page, the letter pivots into supply chains. The U.S. has “only very poor ores of uranium in moderate quantities,” he says, and points to Canada, Czechoslovakia, and the Belgian Congo as important sources.

This is one of the tells that the letter was written by people who were thinking concretely. The letter goes beyond “science might do X” to specify exactly where the operation would choke if X turned out to be real.

The Routing Problem

If you want to understand the letter’s force, you have to understand that it was not inevitable that Einstein would be the signer.

The Franklin D. Roosevelt Presidential Library has a short post about the letter that includes this sentence: because Einstein had a prior personal relationship with the Roosevelts and was internationally well-known, a letter was drafted for his signature.

That is blunt, almost to the point of being uncomfortable. Einstein would get read. That was the entire calculation.

This is a thing smart technical people learn late: in large systems, the constraint is often not truth. It is routing. You can have the right idea and still fail if you cannot get the idea to the person who can authorize motion, in a form that survives the trip.

I think about Barry Marshall, the Australian doctor who in the 1980s couldn’t convince the medical establishment that ulcers were caused by bacteria rather than stress.

He had the evidence. He published peer-reviewed papers. Nothing moved. The field had seen the data, but ordinary proof simply couldn’t reorganize an economy of attention and belief that had calcified around stress as the cause.

So Marshall drank a suspension of Helicobacter pylori, gave himself gastritis, and cured it with antibiotics. He needed something dramatic enough to force a recategorization.

Einstein’s letter solved a similar problem through different means. His name was a form of preloaded legitimacy, a credibility escrow account. You could spend it to buy attention from the highest level of government.

And there’s another routing detail that gets smoothed over: the letter was not immediately delivered.

The National Archives notes that Alexander Sachs, a Wall Street economist and Roosevelt adviser, personally delivered it on October 11, 1939, after the outbreak of World War II delayed the initial attempt.

Einstein and Szilard didn’t just “write to the White House.” They found a person who could walk it into the room. The DOE’s Manhattan Project history describes Sachs meeting Roosevelt, initially struggling to persuade him, then succeeding at a second meeting over breakfast.

The Roosevelt Library’s post adds the most quoted line: after learning the contents, Roosevelt told his military adviser, General Edwin “Pa” Watson, “This requires action.”

That phrase is the hinge. The moment a possibility becomes an administrative obligation.

Category Creation

Why did those three words matter so much? Because until Roosevelt said them, the atomic bomb didn’t exist as a category of legitimate government concern.

This is the part that took me the longest to understand. The “problem” with nuclear weapons in 1939 wasn’t that nobody understood fission. Physicists had been publishing about chain reactions. The problem was that no government had installed “atomic bomb” as a real category of risk yet.

Before the category exists, action looks paranoid. After the category exists, action looks responsible.

Einstein’s letter created the category.

Once “atomic bomb” existed as a legitimate object inside the administrative imagination of the U.S. government, it could be staffed, funded, argued about, and escalated.

The letter didn’t contain the Manhattan Project. It contained the seed of a decision tree. It created an official pathway for nuclear work, which then intersected with other inputs (British conclusions, wartime pressures, organizational restructuring) that changed the slope.

The first action was almost comically modest. The uranium committee met on October 21, 1939, recommended acquiring graphite and uranium oxide, and in February 1940 allocated $6,000 to support chain reaction research at Columbia University.

Six thousand dollars is a rounding error in federal budgets, even back then. It is also exactly what early-stage commitment looks like when a system is still deciding whether a new reality is real. You don’t get the blank check. You get the pilot.

But that pilot existed because the category existed. And categories compound.

In June 1940, the uranium committee was subsumed under the National Defense Research Committee, created at the urging of Vannevar Bush. In July 1941, Bush received the British MAUD Committee report estimating a critical mass of uranium-235 around ten kilograms, enough for an enormous explosion, buildable in approximately two years.

By August 1942, the Manhattan Engineer District was officially created. At its peak: 130,000 workers, $2.2 billion spent, over $30 billion in 2023 dollars.

The letter didn’t cause all of that directly. But it made all of that administratively possible.

Writing as a Control Surface

So what was the letter, functionally?

The more I sit with it, the more I think the answer is: a control surface. Writing, in environments where resources are concentrated, reaches into the future and rearranges what becomes possible.

Einstein asks Roosevelt for one thing: a channel. Someone Roosevelt trusts to coordinate across departments, secure uranium ore supply, and speed experimental work. Big projects rarely start with fully funded programs. They start with a person who can carry the problem across the internal borders of a large system.

Einstein also includes a specific claim meant to make the risk feel immediate: Germany has stopped the sale of uranium from mines in Czechoslovakia that it has taken over. He adds a detail about the Kaiser Wilhelm Institute in Berlin and the son of German Under-Secretary of State von Weizsäcker being attached there.

Even if you don’t know how accurate each micro-claim was at the time, you can see what it’s doing structurally. It turns “Germany might” into “Germany is already acting.” A warning becomes a race.

The letter offered Roosevelt a frame where action was prudence and inaction was the real risk. The memos that move resources are rarely the memos that ask for everything. They’re the memos that make the first step unavoidable, and trust that the rest will compound.

When people ask what “narrative power” means, they often expect messaging tricks, clever framing, and persuasion tactics.

Narrative power operates at a deeper level. It is the ability to make a certain course of action feel inevitable, or at least defensible, under uncertainty. It is the ability to install categories that redirect budgets, careers, and national priorities. It operates through small artifacts that cross institutional borders and make movement permissible.

Einstein’s two-page letter is one of the cleanest examples in modern history.

It is short. It is concrete. It is written in the receiver’s language. It comes with preloaded legitimacy. It asks for one thing: a channel. It grounds the physics in supply chains and bottlenecks. And it creates a category where none existed before.

That combination is rare. When it happens, two pages can make $2 billion feel like the responsible next step.

There’s one more detail worth holding. Einstein became a U.S. citizen in 1940, but the Army denied him a security clearance. He was never part of the Manhattan Project, never set foot in Los Alamos.

The system used his legitimacy to justify action while keeping him far from the execution. Once you set a system in motion, the system becomes its own actor. You can start the chain. You cannot steer every link.

I keep asking myself which decisions are sitting in the “looks paranoid” bucket right now that will, five years from now, sit in the “obviously necessary” bucket.

Somewhere, someone is writing the two-page document that will make the difference.

If you’re working on something that needs to cross an institutional border, I’d genuinely like to hear about it. Hit reply.

The question isn’t why Barry Marshall drank a petri dish of bacteria in 1984. The question is why he had to.

He’d already published papers showing Helicobacter pylori in the stomachs of ulcer patients. He’d already demonstrated the association.

The medical establishment looked at his data and shrugged.

“Interesting,” they said. “Not decisive.” Meanwhile, surgeons kept cutting vagus nerves, and pharmaceutical companies kept printing money on acid blockers.

Rather than fighting ignorance, Marshall was fighting an economy. Ulcers were less a disease, and more a business model, a career path, and a definition of what “good medicine” looked like.

Being right wouldn’t be enough.

To win, he had to make being wrong more expensive than changing one's mind.

The Shape of Ordinary Proof

In early July 1984, Marshall underwent an endoscopy to confirm he was negative for H. pylori, the bacterium he believed caused ulcers.

Three weeks later, he drank a suspension of the bacteria.

Five days after that, he felt bloating and fullness, his appetite dropped, and testing confirmed he had colonized his stomach and developed gastritis, the same infection believed to drive most peptic ulcers.

If you tell this as “one brave doctor proved a point,” it becomes medical folklore. If you tell it as an institutional story, the pattern generalizes: the system was structured so that ordinary proof could not land.

That is why he had to turn himself into a walking exhibit.

Marshall’s self-experiment was an assault on deniability. Peer-reviewed data fails in paradigm conflict because it leaves room for the incumbent frame to declare the anomaly irrelevant. “Contamination.” “Selection bias.” “Association, not causation.” “Commensal colonization.”

In a mature field, those words are tools for keeping the map intact. But if a healthy investigator demonstrates baseline negativity, then self-inoculates, then develops symptoms and shows colonization and inflammation on follow-up, the easy objections collapse.

In his Nobel lecture, Marshall explicitly positions the self-experiment as a response to a field that wasn’t treating his claim as a credible causal model.

Even that didn’t instantly flip the establishment.

The Economy of Ulcers

To see why Marshall’s evidence couldn’t land through normal channels, you have to understand what ulcers were before H. pylori.

Not the disease. The economy.

For much of the 20th century, peptic ulcer disease was treated as a chronic acid problem. Sometimes a stress problem. Often, a surgical problem. Vagotomy was a standard procedure. Surgery was serious medicine, and ulcers were a serious surgical domain.

Then the drug era arrived and strengthened the acid paradigm rather than weakening it. Cimetidine hit the market in the mid-1970s and became foundational therapy. It worked. Patients felt better. The mechanism was elegant. The money was extraordinary.

Once a frame has a clean mechanism and a blockbuster treatment, it stops feeling like a hypothesis. It starts feeling like reality itself.

Against that backdrop, Warren and Marshall’s claim that ulcers were tied to a bacterial infection sounded like a category error.

The stomach was supposed to be a hostile, acidic environment where bacteria couldn’t meaningfully persist. The bacteria model implied that a large fraction of ulcer care had been organized around the wrong kind of problem entirely.

They published early signals anyway. In 1983, they reported unidentified curved bacilli on gastric epithelium in active chronic gastritis. In 1984, they reported that such bacteria were present in most patients with active chronic gastritis, duodenal ulcer, or gastric ulcer, suggesting an etiologic role.

Those papers were asking colleagues to reclassify the disease. That’s very expensive.

A worldview employs people. It funds departments. It creates “serious” specialties. It produces prestige.

When ulcers are treated as an acid disorder, a certain kind of competence is rewarded: careful titration, elegant pharmacology, sophisticated surgery for refractory cases.

When ulcers are treated as an infection, the center of gravity moves. The old work doesn’t become worthless, but much of it becomes less central, less heroic, and in some cases less necessary.

This is why early rejection tends to be framed as epistemic but driven by incentives and identity.

People don’t experience it as “I am defending my status.” They experience it as “this is not how reality works,” because their professional self is built inside that particular description of reality.

Why They Can’t Switch Sides

A paradigm is a massive machine for manufacturing what you might call symbolic capital: the accumulated expectation that listening to certain people will save time, reduce risk, and prevent embarrassment.

It makes the words of skeptics sound half-believed. Without it, even correct claims must be over-proven and over-proven again.

A significant portion of gastroenterology’s symbolic capital had been accumulated under the acid and stress worldview. If the bacterial story wins, the old “good judgment” gets repriced. People who were cautious within the old map become wrong within the new map. That feels like theft, because their status was earned under the prior rules.

This explains a fact that looks paradoxical until you see the structure: even people who privately suspect you are right may still oppose you publicly. Public adoption requires them to defect from the coalition that grants them legitimacy before the new coalition is stable enough to protect them.

A paradigm is a coordination device. It tells people which facts matter, which risks are tolerable, and what counts as a responsible response. Organizations select for plausibility before accuracy, because plausibility allows coordinated action without embarrassment.

When you threaten the paradigm, you’re threatening the coordination mechanism, not merely a set of beliefs.

The Semmelweis Lesson

In the 1840s, at Vienna General Hospital, Ignaz Semmelweis observed that maternal mortality was far higher in the doctors’ clinic than in the midwives’ clinic.

He traced the difference to doctors moving from autopsies to deliveries without washing their hands.

When he instituted mandatory handwashing with chlorinated lime solution, mortality dropped from mid-teens percentages to below 2% within months.

If you read this through a modern germ-theory lens, the refusal to adopt his method looks insane. If you read it through the institutional lens of the time, it looks grim but coherent.

Semmelweis could show an intervention worked. He could not supply a mechanism the establishment recognized as real. Germ theory wasn’t installed yet. “Cadaverous particles” sounded like mysticism.

Most importantly, his conclusion implicated his colleagues. The new practice didn’t merely say “we can do better.” It said “your ordinary work has been killing mothers.”

Semmelweis was asking colleagues to accept that the defining ritual of their profession was a vector of death. Far beyond a technical correction, that’s a demand for public self-indictment.

Semmelweis is less a story about arrogance and more a story about how paradigms defend their moral order.

The old frame preserved innocence. The new frame distributed guilt.

What Marshall Understood

Marshall did something most “right early” people refuse to do. He paid the cost personally to change the cost structure for everyone else.

He didn’t just submit more papers. He constructed a demonstration that moved the argument from “interpret this dataset” to “watch this happen.” That shift matters because it changes what kind of courage is required of the adopter.

His self-experiment was a piece of borrowed cognition: a pre-assembled sequence that others could deploy without having to fight the full battle themselves. Baseline negativity, ingestion, symptoms, colonization, cure. It condensed an abstract causal argument into a narrative that was easy to repeat.

Narrative functions as uncertainty-reduction technology. Frames spread when they provide repeatable justification. Marshall’s demonstration gave the field something they could use.

Semmelweis couldn’t do that.

He lived before the mechanism that would let others narrate his results without the stigma of superstition or accusation. He could mandate practice locally. He couldn’t furnish a grammar that let physicians adopt it without feeling accused or irrational.

By February 1994, the NIH Consensus Development Conference recommended antimicrobial therapy to eradicate H. pylori.

That’s a full decade after Marshall’s self-experiment. The new model had to become official before it became normal.

Once the consensus statement existed, adoption no longer required personal heresy and became professional compliance.

Marshall and Robin Warren received the Nobel Prize in 2005. The Nobel framing treats their work as transforming ulcer disease from chronic recurrence to a condition that can be cured.

More than a scientific conclusion, it became a reallocation of what counts as legitimate medicine in that domain.

The Cost of Being Right Early

Being right early means you’re fighting a disease model and a prestige model at the same time. You’re asking for admissions that can feel morally catastrophic. You’re threatening the coordination mechanism that tells everyone what “responsible” action looks like.

Cynics will cite the obstacle as ignorance or corruption, but it (usually) isn’t. The obstacle is that your audience doesn’t yet have a script that makes adopting your model feel safe. They can’t use your evidence without a grammar that lets them speak it.

If you’re sitting on evidence that your institution isn’t ready to hear, the question isn’t whether you’re right. The question is whether you can make your map easier to adopt than their map is to defend.

Don’t fight for correctness. Fight to make being wrong more expensive than changing their minds.

Most tech CEOs are misunderstood in ordinary ways. People over-attribute success to charisma, or luck, or a single product decision.

Alex Karp is misunderstood in a stranger way: people misclassify what kind of company he runs, so they reach for the wrong interpretive template entirely.

They evaluate him like a consumer-tech founder. He is not one.

They evaluate Palantir like a data company. It is not one.

The result is that Karp gets filed under “eccentric,” “controversial,” or “ideological,” when the more accurate file is “institutional operator selling cognition at scale.”

The Commitment Signal

Read Palantir’s S-1 filing and you’ll find language that would make any normal tech PR team faint. “We have chosen sides,” the company declares, framing its software as a duty to “keep soldiers safe” and explicitly tying its product to “our most vital institutions.”

In a market where CEOs are trained to sound values-neutral and customer-agnostic, Karp narrows the moral and geopolitical frame, polarizes the audience, and keeps going.

If you interpret that as a personality quirk, you miss what it’s actually doing:

This is a commitment signal. It constrains optionality on purpose.

It tells institutional customers (often the state or state-adjacent organizations) that Palantir won’t treat them as an embarrassing phase to grow out of. It tells prospective employees this company won’t rebrand the moment the cultural climate shifts.

In markets where credibility means surviving consequences, Karp is making himself legible to the people who buy consequences.

Two Kinds of Software

To see why this works, you need to understand two kinds of software and why Palantir is playing a different game entirely.

Call it Type A versus Type B.

Type A software is built for clean environments. It wins by being simple, self-serve, and scalable. The customer adapts to the product.

Type B software is built for hostile environments. It wins by being adaptable, secure, and embedded. The product adapts to the customer.

“Hostile” here doesn’t mean violent. It means high stakes, high friction, and high constraint: legacy systems, compliance, coalition politics, adversarial threats, operational urgency.

Palantir is Type B. According to their 2024 annual report (the most recent annual report available at the time of this writing in early 2026), 55% of revenue came from government customers and 45% from commercial.

That alone should push you away from the default Silicon Valley mental model. This is not a company monetizing attention or convenience. Its center of gravity is institutional adoption, procurement, compliance, and long-duration missions.

Once you build for that world, you start to look strange to the rest of tech, because you stop optimizing for what the rest of tech optimizes for.

If you think Palantir is a dashboard company, the pricing looks insane. If you think it’s a data broker, the customer relationships look wrong. If you think it’s an AI lab, the deployment style looks too operational.

Palantir is closer to an operating system for institutional reality, which is not a category most people are used to naming.

This is why Palantir pioneered the “forward deployed engineer” model: sending strong engineers into the field to make software work inside the customer’s messy reality, then iterating based on what breaks.

Karp made this bet early and refused to abandon it, even as the rest of the industry chased product-led growth and self-serve scale.

This is the opposite of the modern SaaS fantasy where products sell themselves and customers are interchangeable. It’s expensive, slow, and deeply sticky. Which is exactly why it fits institutions that treat failure as catastrophic and adoption as political.

In July 2025, the U.S. Army announced an enterprise service agreement allowing the Army and other DoD agencies to purchase Palantir products over up to ten years, with a spending cap of $10 billion.

A cap isn’t a guarantee, but the form matters. This is the Army treating Palantir less like a vendor and more like enterprise infrastructure you want easy to pull off the shelf.

The Legitimacy Engine

Once you accept all this, Karp’s communication style snaps into focus.

Silicon Valley culture treats likability as a proxy for legitimacy. That works when your market is consumers and your distribution is persuasion. In institutional markets, legitimacy is closer to permission.

Permission means the institution can defend the purchase to oversight committees, auditors, and its own sense of identity. The buyer has to be able to explain itself after it buys you.

Karp’s real job, then, looks less like “run a software company” and more like “run a legitimacy engine that lets a certain class of institutions adopt certain capabilities without losing face.”

That is a very different CEO job than “build an app people love.” It requires different language, different recruiting, different tolerance for controversy, and different time horizons.

The irony: the very traits that make Karp hard to market to mainstream tech culture are the traits that increase trust with institutions.

Institutions are allergic to vibes.

They want continuity and commitment.

Karp’s refusal to sand down his worldview is part of how he sells that commitment.

Why It Works

Rather than just the Palantir story, it’s a template for any company (or their founders) trying to sell capabilities, not conveniences, to institutions.

Consumer-tech founders optimize for broad appeal. Institutional operators optimize for trust among buyers who face real consequences. The playbook is different: commitment signals instead of PR polish, embedded deployment instead of self-serve scale, controversy tolerance instead of universal likability.

The companies that win the next decade in institutional markets may look “wrong” through the consumer-tech lens. Too serious. Too opinionated. Too tied to specific customers. Too willing to alienate broad audiences.

But that is not a bug. That’s the strategy.

Most CEOs are misunderstood because people misjudge their skill or luck.

Karp is misunderstood because people misjudge his market.

When Palantir takes heat for controversial contracts, that doesn’t hurt them with the customers who matter. It helps.

It proves to defense buyers and intelligence agencies that this company won’t buckle under activist pressure. It proves the commitment signal is real.

The controversy, the polarization, the refusal to soften his worldview: these aren’t liabilities in his market.

They’re the product.

Sam Altman is unusually good at attracting suspicion.

Depending on who you ask, he’s a visionary trying to steer an unstable technology, or a power-maximizer using “AI safety” as cover. Every news cycle produces a new round of cynical takes: too polished, too political, too eager to sit at the center of the system.

What almost none of those takes do is treat him as a deliberate strategist over a 15-year arc.

Because there is a concrete, traceable story here: how a twenty-something with a decent-but-not-spectacular exit moved laterally, again and again, into roles that controlled distribution, capital, and eventually an entire AI super-cycle.

Whether your feelings are admiration or not, you don’t have to approve of the outcome to learn from the method. And you should.

Altman has, helpfully, left a paper trail. In 2020, in an essay titled The Strength of Being Misunderstood, he argued that the question isn’t “How do I stop caring what people think?” It’s “Whose opinions should I care about and on what timescale?”

Most people, he wrote, figure out the first but neglect the second.

He says the most impressive people he knows care deeply about what others think, but on a very long horizon. They’re willing to let “the newspapers get it wrong” so long as “the history books get it right.”

That frame explains quite a lot about the career that followed.

Why Combinator?

In March 2019, Altman faced a very binary choice.

For a little over three years, he’d been running two organizations at once:

1. Y-Combinator, where he’d become president in 2014, gave him access to over a hundred startups per batch and hundreds per year.

2. OpenAI, which he’d co-founded in 2015, was still mostly a research lab, even as it became more than an academic exercise.

YC’s leadership told him he had to pick one: commit full-time to YC or commit full-time to OpenAI.

He chose OpenAI.

To most people in tech, this looked insane. “President of YC” was the most powerful position in startup land. Direct access to hundreds of companies per year, the ability to shape an entire generation of founders, and a platform that had minted some of the most valuable companies of the decade.

He walked away from it for an odd hybrid: a nonprofit-controlled, “capped-profit” AI lab that still looked more like a research shop than a product company.

Even if it managed to raise serious capital, it was still fundamentally competing with DeepMind, Google Brain, and FAIR on research.

The conventional wisdom was clear: you don’t give up the top of the mountain to bet everything on a weird research lab.

Altman bet on it anyway.

Choosing Platforms Over Exits

The standard path to influence in Silicon Valley is simple enough: get into a rocketship early, ride it to a huge exit, and let the combination of wealth and “I was there” carry you into every important room.

Altman’s path diverged from that script early.

He co-founded Loopt in 2005, went through YC himself, and spent years grinding on a location-based social app that never quite hit escape velocity. In 2011, while still running Loopt, he joined Y Combinator as a part-time partner.

Loopt was sold in an acqui-hire for about $43.4 million in March 2012. With dilution, terms, and the like, his take-home was likely around $4-6 million. Life-changing money, but not “you now own a large fraction of the internet” money.

At that point, the obvious move would have been: do it again. Start another company, knowing more and having more.

He didn’t do that. He used part of the Loopt proceeds to launch Hydrazine Capital, an early-stage fund focused heavily on YC companies. He bought himself a position slightly up the stack, allocating capital across many bets instead of concentrating everything on one.

Then in February 2014, at 28, Paul Graham asked him to become president of YC.

This wasn’t a difficult decision. This was Paul Graham handing him the most powerful platform in startup land. Of course you say yes. Direct access to hundreds of founders per year, the ability to shape how an entire generation thinks about building companies, and a reputation-compounding machine that had already minted Airbnb, Dropbox, and Stripe.

What was unconventional wasn’t taking the role. It was how he used it.

Most people would have treated YC as a job. A prestigious job, but still: show up, run the batches, give advice, post on Twitter, collect the salary and carry. Altman treated it as infrastructure for something else.

You can already see the pattern forming:

• Trade operator role in one company for a platform role across many companies

• Trade clean ownership for messy, leveraged influence

• Trade near-term clarity for long-term optionality

That pattern repeats.

The Multiplier

Altman’s core ethos is simple:

Influence compounds differently than capital.

Capital compounds through returns on financial assets. Influence compounds through network effects.

With money, you can put dollars into deals and hope to get more dollars out. With access and a platform, every interaction is a potential edge: introductions, information flow.

YC was a perfect laboratory for this.

Every batch, Altman met dozens of founders at the most malleable stage of their careers. He saw everything: the raw deck, the dysfunctional founding teams, the early flashes of product-market fit. He had leverage over what they built, who they met, and how they thought about ambition and risk.

A lot of those companies disappeared. But some became Instacart, DoorDash, and Coinbase. Their founders were the ones who remembered who took them seriously when they were pitching half-finished slides to a conference room on Pioneer Way.

Notice the selectivity. Altman didn’t help everyone. He helped people who were ambitious, building something, playing a long game. People who might be important later.

This created a particular kind of reputation. People don’t say, “Sam helped me because he calculated I’d be useful to him later.” They say, “Sam helped me when no one else would.” Both things are true. The calculation doesn’t diminish the value of the help.

From the outside, this looks like “being generous with your time,” as Bay Area figures often are.

From the inside, it’s a very specific kind of leverage:

• Each founder you help is a future allocator of equity, attention, and introductions

• Each company that works becomes a node in your personal distribution network

• Each batch increases both the number of nodes and the density of edges between them

Most people treat “networking” as a set of social obligations. Altman treated YC as a compounding system.

Strategic Opacity

How comfortable Altman is being misread in the short term matters as much as any specific bet he’s made.

In The Strength of Being Misunderstood, Altman argues you should be very selective about whose opinions you weight and on which topics, and that you should care about those opinions on a very long timescale. You should be willing to trade “short-term low status” for “long-term high status,” which means being patient about looking foolish or wrong.

Once you read that, his public behavior looks less enigmatic.

Altman will talk at length about AGI timelines, universal basic income, or the need for more energy. He’ll lay out his views on what a healthy tech ecosystem looks like. But when it comes to concrete maneuvers (why he backed a particular structure, what exactly he promised which investor, what line he’s walking with regulators), the record gets much thinner.

That isn’t an accident. It’s a division of labor:

• Worldview: broadcast widely; invite allies; build consensus over decades

• Tactics: keep quiet; let results, not blog posts, explain the moves

This creates something valuable: interpretive room. When Altman makes a move, different people can read different motives into it.

When the OpenAI board ousted him in November 2023, he didn’t immediately go public with a detailed counter-narrative. He let employees, Microsoft, and other stakeholders make the case.

This allowed multiple versions of the story to coexist, each one serving his interests with different audiences.

His public statements on AI safety follow the same pattern. He expresses enough concern to be taken seriously by safety-focused researchers, but remains optimistic enough to keep building aggressively. Both AI accelerationists and AI safety advocates can find something in his public position to work with.

Compare this to someone like Elon Musk, who over-explains as a rule. Musk will tell you exactly what he thinks about everything, in real-time, often emotionally. This creates clarity but eliminates optionality.

You always know where Musk stands, which means you can predict him, oppose him, or potentially box him in. Altman doesn’t give you that opening.

Lesson: Be open about your worldview and frameworks. Be silent about your tactics and specific calculations. Maximum influence, maximum flexibility.

Public Vision, Private Tactics

A big part of why Altman gets read as “calculating” is that he does something most powerful people avoid: he writes down his worldview.

Starting around 2014, his essays began to cluster around a few consistent themes:

• Intelligence as the master lever on the future (the 2015 “machine intelligence” posts)

• The need for a social backstop like basic income in a highly automated economy (2016 YC basic income project)

• Cheap, abundant energy as a foundation for growth (2015 “Energy”)

• A belief that we can and should drive the cost of many essentials down over time (”Moore’s Law for Everything”)

By the time he co-founded OpenAI in December 2015, he had already spent reputational capital on the argument that machine intelligence would be both enormously valuable and potentially dangerous.

This matters for two reasons.

First, it makes his later moves legible to long-term observers. When he pivots from running YC to running OpenAI, it doesn’t look like a random lurch; it looks like the obvious next move for someone who has been talking about AGI and social risk for years.

Second, it increases the surface area of his influence. Every essay is an invitation to a different set of people (researchers, regulators, founders, policy thinkers) to plug into his frame for what matters. The result is a much thicker web of people whose default assumption is “Sam is basically serious about this.”

Critics argue about how sincerely any of this is held. But the mechanism is straightforward: public worldview, private tactics. The former earns him trust and attention; the latter preserves flexibility.

The OpenAI Coup

The OpenAI pivot in 2019 is a textbook application of the method.

In December 2015, while still president of YC, Altman co-founded OpenAI with Elon Musk and others as a nonprofit lab. He was operationally involved from day one: fundraising, strategy, recruiting. For a little over three years, he effectively ran both YC and OpenAI.

Then, in March 2019, he made the high-variance move.

OpenAI created OpenAI LP, a nonprofit-controlled “capped-profit” entity designed to raise serious capital while nominally preserving its charter. Altman became CEO of this new structure. A few months later, in July 2019, OpenAI announced a $1 billion partnership with Microsoft and committed to using Azure as its exclusive cloud platform.

What Altman saw that others didn’t:

• He saw that AI was going to be genuinely transformative, not in a vague futurist sense but in a three-to-five-year sense.

• He saw that the path to influence in AI wasn’t through gradual academic research but through building something people could touch.

• He saw that being early to this transition would matter more than being right about any particular technical bet.

The transformation of OpenAI from pure research lab to product company (ChatGPT in November 2022, GPT-4 in March 2023, the expanded Microsoft partnership in January 2023) were Altman moves. They were pragmatic, commercial, and slightly norm-violating. They made OpenAI matter in a way that pure research never could.

The November 2023 board fight (brief ouster, rapid return) revealed how strong the network around him had become.

Hundreds of employees threatened to walk. Microsoft made it clear that the partnership was with Altman as much as with the corporate shell. The board surrendered quickly.

The network he’d built was strong enough that the company couldn’t function without him.

The Method, Distilled

If you just want to understand the mechanics, the Altman method looks roughly like this:

Choose leverage over ownership. Repeatedly trade clean founder equity for platform roles that sit on top of many companies (YC) or entire technology layers (OpenAI).

Design for network effects. Put yourself where flows converge (deal flow, talent, research, distribution) rather than where one product lives or dies.

Invest in selective generosity. Spend time and capital on people who are clearly ambitious and long-term oriented. Think of every introduction, every early check, as a possible future edge in the graph.

Broadcast worldview; hide tactics. Use essays and public talks to explain what you’re trying to do in broad strokes. Say very little about how you’re actually going to do it.

Accept being misunderstood on a long horizon. Be willing to look opportunistic, over-optimistic, or even hypocritical in the short run if you believe the long-run bet is sound. Trade “short-term low status” for “long-term high status.”

Compound patiently. Don’t expect the payoff in a year or even five. Altman co-founded OpenAI in 2015 and didn’t go all-in until 2019. The real returns (ChatGPT, GPT-4, the board fight) didn’t show up until the early 2020s.

None of these moves is spectacular on its own. Being a part-time YC partner, starting a small fund, co-founding a research nonprofit, stepping into a strange “capped-profit” structure: each step is legible but not obviously world-historical.

What makes the story interesting is the consistency. Over fifteen years, Altman has repeatedly optimized for position over immediate payout, for platform over product, for history books over newspapers.

Most people in tech, when they have a modest win, try to roll it into a bigger version of the same game. Altman switched games. He chose to play for influence first and money second.

He ended up with both.

Note for newsletter recipients: I changed my newsletter’s name from LinkedUp to Sam’s Newsletter to give me room for broader topical coverage in line with how my positioning is evolving (more on that here).

It’s interesting how quickly things change. Three years ago (can you believe it!), when ChatGPT launched, the consensus was obvious: writers were doomed. AI could already write better than most people, and it was only going to get better. If you made your living producing text, you were in trouble.

Last week, Anthropic posted a job listing for a writer. The salary range: $255,000 to $320,000.

This isn’t Anthropic being quirky. In September, OpenAI posted a content strategist role at $310,000 to $393,000. Same month, PayPal posted a “Head of CEO Content” position with a range cited between $170,000 and $292,000. Just last week, Andreessen Horowitz announced an entire fellowship program for what they called “highly functional people who are also very online.”

I tweeted about the Anthropic JD without thinking much: “Basically all bad/okay writers are near worthless now. Now extremely good writers with great taste trade at a huge premium and own the future of content.”

It got 32,100 views. Which tells you something: people felt this even if they couldn’t articulate it.

Why? Why would Anthropic (the company that makes Claude, probably the best creative writing AI in the world) pay someone $320,000 to write? The obvious answer is they need economics expertise. But The Economist doesn’t pay anywhere near this much. Something else is happening.

Shaping Questions, Not Answering Them

I pulled both of Anthropic’s editorial job postings to see what they actually wanted, and the language is revealing in a way I (mostly) didn’t expect.

The Economics & Policy Lead says:

“Anthropic is at the center of critical conversations about AI’s economic and societal implications.”

Interesting. Continuing:

“[The role will] engage with policymakers, think tanks, academic institutions, and media to advance productive conversations about AI policy and economics.”

Not report on conversations. Advance them.

They want someone with “strong instincts for identifying which policy and economic questions will matter most as AI develops” who can “represent Anthropic’s perspective effectively while engaging constructively with diverse viewpoints.”

Read that first part again. Instead of hiring someone to explain what happened, they’re hiring someone to shape what questions get asked in the first place.

Notice something else: Anthropic posted two editorial roles. The other is for AI and Science, at $200,000 to $255,000. Still substantial, but the policy role pays $65,000 more at the top end. That spread tells you what they think is strategically important.

Algorithmic Negotiation

What these companies are paying for is what I’d call “algorithmic negotiation” at institutional scale. Here’s what I mean by that:

Modern discourse operates on two opposing forces. On one side: the specific knowledge that makes someone worth listening to. On the other side: legibility to the right audiences. Understanding how ideas move through institutions, how frames shift, how to make concepts matter.

Most people can do one or the other. Academics produce rigorous but often unreadable work. PR people produce polished but often empty messaging. The valuable skill is negotiating between these forces without capitulating fully to either.

This requires being embedded in discourse. Not watching it, but living in it. Understanding moves and counter-moves. Knowing which frames are played out and which are fresh. Having what Anthropic’s posting calls “strong instincts for identifying which policy and economic questions will matter most.”

More than simple writing ability, that’s predictive judgment about which conversations determine everything else.

AI can produce clean text explaining any position. But it can’t tell you which position to take, or which question to elevate, or how to shift what the institutions that matter think is important.

What used to be a personal skill is now being systematized.

From Skill to Infrastructure

The a16z fellowship makes this systematization explicit, and it’s where the large strategy becomes clear.

How a16z describes what they’re building: “Forward deployed New Media, where team members embed themselves in portfolio companies for critical periods, and execute a launch together.”

In other words, embed and execute - using the term “forward deployed,” a term popularized by Palantir to describe the concept of sending their engineers into literal warzones to deploy their software for government clients.

The eight-week fellowship has a founding cohort that includes James Reina, Chief of Staff to Mr. Beast. Mr. Beast has 450 million subscribers and routinely gets over 100 million views per video. Reina was inside that operation, understanding how it works.

What is a16z doing here exactly? Extracting operational knowledge about how to build massive audiences, then deploying it strategically.

The speaker lineup includes Marc Andreessen and Katherine Boyle (who both spend lots of time online, specifically on X), Lulu Cheng Meservey (who is famous inside the Bay for flipping the script on PR, guiding clients like Sam Altman and Palmer Luckey out of tricky situations), and Dylan Patel from SemiAnalysis (who turned semiconductor analysis into one of tech’s most influential newsletters).

The fellowship page is explicit about placement: “Potential forward deployment to drive impact at an a16z portco.” They’re embedding them directly into portfolio companies to 10x their influence.

A16z calls this “timeline takeover” - they explicitly offer to “win the internet for a day” as a service.

Their goal, in their own words, is building “the best turnkey media operation in venture” to help founders “win the narrative battle online.” The old agency timeline of three to six months to plan a launch is “archaic,” they write; you now must execute “in a shockingly short period of time.”

What a16z is creating is, ultimately, a pipeline that turns narrative understanding into a competitive advantage for their entire portfolio. They describe themselves as “the F1 Pit Crew of Venture” - systematic infrastructure designed for speed and precision.

Cultural Upstream

This explains something that otherwise seems strange: why do mega-successful entrepreneurs who should be far too busy to post spend hours online?

Elon Musk runs multiple companies. Marc Andreessen runs a major VC firm. Both spend enormous amounts of time posting on X. That looks like distraction until you understand what they’re actually doing:

Building infrastructure to control cultural upstream.

Every industry now has a cultural upstream, and it lives on platforms. In tech, it’s largely Twitter/X. In beauty, it’s TikTok and Instagram. In gaming, Twitch and Discord. The specific platform varies, but the principle is constant.

This creates a recursive loop. The platforms don’t just reflect what’s important. They determine what becomes important. Control the upstream and you control what flows downstream.

From Chaos to System

This shift from individual skill to systematic infrastructure isn’t limited to business. In fact, you see it more clearly in politics.

The 2016 election was the first fully social-media-driven U.S. presidential cycle. The outsider candidate won partly because he understood platform mechanics better than his opponent. But it was still somewhat chaotic; his advantage was partly accidental. Wired wrote at the time about how Facebook and Twitter propelled his campaign in ways that hadn’t been systematically planned.

By 2024, everything had changed. Both campaigns were running sophisticated narrative operations. Politico covered how one campaign joined TikTok despite previously trying to ban it - recognizing the platform had become essential to owning the narrative. The Washington Post documented the rapid-response content operations running in real time. GMF called it “the TikTok era” for presidential campaigns. The professionalization was complete at the national level.

This capability is now cascading to local races. What presidential campaigns had in 2016, city candidates have in 2025 (looking at New York City’s mayoral election earlier this month).

Where Power Flows Now

Big picture, I think we’re watching a major reallocation of power.

For most of history, cultural production was controlled by institutions with distribution: newspapers, publishers, TV networks. The internet disrupted that, but for a while, the new equilibrium wasn’t clear.

Now it’s becoming clear. Cultural production happens on platforms, but control requires systematic infrastructure. And not just using the platforms, but building organizational capacity around them.

That’s why Anthropic is paying $320,000 for someone who can be “at the center of critical conversations.” Why a16z is recruiting from Mr. Beast’s operation and forward-deploying fellows into portfolio companies. Why OpenAI is paying nearly $400,000. Why billionaires who should be too busy are spending hours crafting posts for their growing audiences.

They’re building infrastructure for a new kind of power: the power to shape which questions get asked, which frames become standard, what people think matters.

You might find this uncomfortable. We’re watching influence centralize around systematic infrastructure in a way that feels different from what the early internet promised.

Elite institutions are building machinery to occupy the highest levels of cultural upstream, and they’re doing it by hiring the best people at algorithmic negotiation and embedding them (shameless plug: people like me).

But uncomfortable or not, it’s happening. a16z has the language right there on their site: “embed themselves in portfolio companies” for the purpose of pushing their narrative effectively. Anthropic is explicit that they want to be “at the center of critical conversations.”

The bad writers are finished. The okay writers are finished. The content mills are definitely finished.

The people who can identify which questions will matter before they’re obvious, who can engage with institutions while maintaining strategic clarity, who can negotiate with algorithms while maintaining substantive knowledge?

They’re going to own discourse.

And in a world where narrative increasingly shapes reality (where questions determine policies, regulations, and who gets to build) owning discourse means owning outcomes.

The $300,000 salary isn’t for writing.

It’s for power.

And institutions are paying accordingly.

If you’re creating LinkedIn content without a proper strategy, you’re making it 100 times harder to succeed than necessary. Seriously.

And while everyone tells you to “plan out your content” on LinkedIn, nobody ever tells you how to actually do it.

If they do, they’re giving basic advice that’s (most likely) not technically wrong, but not actionable enough to be valuable in any meaningful sense.

And that’s a gap I’m very excited to fill today: I’m sharing my strategy for maximum impact on LinkedIn—in any vertical, niche, or positioning.

This doesn’t just result from my 2.5+ years of constant posting to build 230,000+ followers—it results from building content strategies for 40+ B2B leaders, including venture-backed CEOs, agency owners, influencers with millions of followers, and more.

So, let’s dive in—step-by-step:

1. Laying Out The Facts

Before deciding what content to create, you need to consider the foundational facts of your business, which will define your content strategy as a whole.

High level, we’re talking about things like:

• The details of your business/offer

• Your professional persona and voice

• Your goals/most desired outcomes on LinkedIn

Without clarity on those elements, your content will inevitably lack focus and fail to resonate with the right people. At best, you’ll accidentally hook in someone here and there, but never with any real consistency.

Those facts are your content compass—they'll guide every piece you create.

Open up a blank document and make subheadings for the following sections:

• Offer description

• Ideal customer profile (ICP)

• Key competitive differentiators

• Key target market pain points

I’ll teach you what exactly to define for each next:

Offer Description

Write a clear, concise description of what you sell and how it helps your target market.

You need to include:

• Your core product/service

• Primary benefits and outcomes

• Pricing structure

• Delivery method

• Time commitment required

• Any unique aspects of your offer

This isn't just for your reference—it's crucial because every piece of content you create should relate to your offer in some way, directly or indirectly.

Here’s an example I created for a cold email agency focused on B2B SaaS:

Ideal Customer Profile (ICP)

Define exactly who you're trying to reach with your content. This should cover:

• Job titles/roles they hold

• Company size and type

• Industry verticals

• Annual revenue range

• Key challenges they face

• Decision-making authority

• Professional goals and aspirations

• Budget for solutions like yours

This sort of information shapes your content's tone, topics, and examples—that’s why the more specific you are, the better off you’ll be.

When you know precisely who you're speaking to, your content naturally becomes more relevant and engaging to your target audience.

Your ICP details will also help you:

• Filter out unqualified leads early

• Speak directly to decision-makers' needs

• Create content that resonates emotionally

• Focus on problems you're best equipped to solve

• Identify which case studies to highlight

• Target specific industries effectively

…all cool stuff you don’t want to miss out on.

Let’s go back to our B2B SaaS cold email agency:

Key Competitive Differentiators

What makes your solution unique in the market? Or, to put it bluntly, “Why should I, your target customer, choose you over everyone else?”

Remember that you’re competing on LinkedIn—not just with your industry competitors (though that will certainly be the case), but with everyone posting on the platform for impressions in general.

It’s a zero-sum game; ~10% of the creators on LinkedIn will get 90% of the leads.

Why? Because they offer a unique appeal to their target audience that they haven’t found anywhere else—on LinkedIn or elsewhere.

PS: note that I say “90% of the leads,” not "90% of the impressions.” Viral-bait posters listing out the Top 10 TED Talks and a motivational quotes they found on Google may get more likes and comments than you, but it’s all ephemeral—they’re not building long-term credibility with a valuable audience like you are.

So, to find your “unique appeal,” outline:

• Your unique methodology or approach

• Proprietary technology or processes

• Special expertise or credentials

• Results and success metrics

• Customer service philosophy

• Speed of delivery or implementation

• Industry-specific knowledge

• Team composition and expertise

• Pricing model advantages

• Quality assurance standards

• Unique partnerships or affiliations

• Geographic advantages or reach

• Specialized tools or resources

• Client support systems

…these differentiators should be woven into your content naturally—not as direct promotional points (at least most of the time), but as underlying themes that demonstrate your expertise and unique value proposition.

Going back to our example:

Undeniable advantages like these are worth repeatedly emphasizing in your content.

But at the same time, the goal isn't to explicitly state these differences in every post, but to let them inform your content's perspective and insights holistically.

For example, if one of your key differentiators is your deep expertise in a specific industry vertical, your content should naturally demonstrate that expertise through industry-specific examples, relevant terminology (avoiding too much jargon), and nuanced insights that only someone with your background could know.

That sort of authenticity is way more powerful than simply claiming expertise.

It shows rather than tells, building credibility organically through your content rather than through explicit statements about your qualifications.

PS: Some telling is okay—you should be repeatedly emphasizing the results your work creates for the sake of crediblity, but all things in balance. Sometimes it should be implicit, sometimes it should be explicit.

Key Target Market Pain Points

Understanding your market's challenges—as specifically as possible—is non-negotiable for creating content that converts with any sort of meaningful consistency.

List out your target market's primary pain points, like:

• Lack of clarity on ROI measurement

• Difficulty scaling operations efficiently

• Limited access to reliable market data

• High customer acquisition costs

• Inefficient internal processes

• Challenges with team coordination

• Resource allocation issues

• Technology integration problems

• Compliance and regulatory concerns

• Time management struggles

These pain points should form the core themes of your content strategy since they represent the key problems your audience is actively seeking solutions for.

Again, going back to our B2B SaaS cold email agency example:

If you can effectively address pain points like these in your content, you'll naturally attract the right audience and position yourself as a solution provider.

Because, ideally, each piece of content should either:

• Directly address one of these challenges

• Offer practical solutions or frameworks

• Share relevant case studies

• Provide actionable insight/knowledge, or

• Demonstrate your understanding of the problem

And while there will be some exceptions (personal posts, for example), the key is to ensure that most of your content directly addresses these fundamental pain points.

Through maintaining this focus, you'll build a content library that consistently resonates with your target audience and demonstrates an increasingly-deep understanding of their challenges.

That gives you infinitely more leverage in your industry—not just through the benefits of LinkedIn directly (though there will be plenty of that), but through being a recognized thought leader in general.

Your prospects will Google you, and having them land on your high-value LinkedIn profile consistently sharing genuinely actionable information is one of the best credibility-builders you can possibly have.

For example…

2. Defining Your Persona

It’s extremely crucial to be intentional with how you present yourself to your audience.

While many might just say, “Be yourself,” that's not always the best approach for business content.

Your professional persona should be carefully crafted to resonate with your target audience while remaining authentic to who you are.

The balance is key—you want to be relatable and genuine while maintaining the level of expertise and professionalism your audience expects. Think of your persona as the bridge between your authentic self and your professional brand.

You don’t need to be overly specific with rules, but you should have clear guidelines for how you'll present yourself.

Think about things like:

• Your communication style (formal vs. casual)

• The type of language you'll use

• How much personal information you'll share

• Your stance on controversial topics

• The balance between educational and entertaining content

• Your visual branding elements

• Formatting rules (e.g. no emojis, line breaks every 2-3 sentences, etc)

For example, if you were a wealth manager at Merrill Lynch, your persona might be more formal and conservative. You would focus on professionalism and expertise, avoid controversial topics, and keep personal sharing minimal.

In contrast, if you're a tech startup founder, you might adopt a more casual, transparent approach. You might share behind-the-scenes glimpses and personal experiences while maintaining professional credibility.

The key is consistency—whatever persona you choose should feel natural and be sustainable long-term. At the fulcrum of that, of course, is authenticity.

Your persona must be genuine enough that you can maintain it consistently across all your content without feeling forced or artificial.

This means choosing characteristics and communication styles that align naturally with your personality while still serving your professional goals.

3. Defining Your Goals for LinkedIn

Clear goals are essential for any content strategy, and LinkedIn is no exception.

Each post you publish should explicitly exist to accomplish one (or more) of the objectives that got you on LinkedIn in the first place.

Some of the most common LinkedIn content goals might include:

• Building thought leadership in your industry

• Attracting potential clients or partners

• Growing your professional network

• Establishing credibility in your field

• Driving traffic to your website

• Generating leads for your business

• Increasing brand awareness

• Recruiting talent for your organization

• Sharing company culture and values

• Engaging with industry peers

Your goals probably fall within one of those, more or less. And even if they’re a bit more nuanced, the core principles remain the same.

For instance, if lead generation is your primary goal, your content strategy might emphasize demonstrating expertise and providing value-added insights that naturally lead to business conversations.

Of course, you’ll also want to be sharing lots of case studies and client results—not just as a vehicle for booking calls (though that will certainly be effective for compelling case studies) but also for demonstrating your track record of success and building credibility with your audience (which could be a secondary goal).

So, outline 3-5 of your main goals in your content strategy document and prioritize them in order of importance. This will help guide your content creation process and ensure that every post serves a strategic purpose.

Here are some example goals from our hypothetical SaaS agency:

Remember that your goals may evolve over time as your business grows and market conditions change—it’s perfectly fine to come back and tweak this (encouraged, actually)

For each goal, establish specific metrics to track progress. These could include:

• Engagements from your target market

• Inbound connection requests from industry peers

• Profile views from decision-makers

• Direct messages from potential clients

• Website traffic from LinkedIn

• Conversion rates on calls-to-action

• Growth in follower count (controlled for targeted content)

Each of these metrics should be monitored regularly and analyzed against your goals. This data-driven approach will help you refine your content strategy over time, allowing you to focus more on what works and less on what doesn't.

If you don’t have clear metrics to track, you'll struggle to optimize your content strategy effectively. Make sure to set up a simple tracking system—even a basic spreadsheet will do—to monitor your key performance indicators (KPIs) monthly.

Data is by far one of LinkedIn’s most valuable assets for publishers on the platform. It offers a level of granularity wholly unrivaled by any other platform—enabling you to measure your goals with remarkable precision.

You can track engagement metrics and audience demographics, including industry, seniority level, and company size.

Test specific topics, see who they resonate with (demographic data) and by how much (engagement data), and double down on what seems to be working.

For example, here’s the engagement and demographic data of a post that did exceptionally well in creating visibility from my target market:

This data tells me I’ve found an angle I need to double down on and continue to optimize.

That’s a perfect example of how this sort of in-depth information helps you understand exactly who's engaging with your content and adjust your strategy accordingly.

Not using that means giving up one of your biggest competitive advantages.

PS: If you want to get ultra-granular in tracking your data (which I recommend you do), I recommend using either Shield or Aware, which are leading LinkedIn analytics tools that honor LinkedIn’s ToS (unlike many other LI tools out there).

4. Outlining Your Content Pillars

Content pillars are the core themes or topics that form the foundation of your LinkedIn content strategy.

Without them, your content can (and will) feel scattered and unfocused. Most successful LinkedIn creators stick to 3-to-5 main content pillars that align with both their expertise and their audience's interests.

Your pillars might include:

• Industry insights and trends

• Professional development tips for your industry

• Behind-the-scenes looks at your work (building in public)

• Case studies and client success stories

Those are broader examples, however—you should narrow down your pillars to be more specific to your niche.

For instance, if you work in SEO, your pillars might include technical SEO strategies, content optimization techniques, link-building methods, and Google algorithm updates.

Whatever your industry, each pillar should represent an area of deep expertise in which you can provide valuable insights based specifically on your direct experience (that’s where credibility comes from).

So, in your content strategy doc, outline your 3-5 main content pillars. Under each pillar, list 5-10 specific topics you can write about. This creates a content bank you can draw from when planning your posts.

To show you what I mean, I created pillars for our B2B SaaS agency example referenced above:

But no matter your niche, remember that your pillars should:

• Reflect your expertise

• Address audience pain points

• Be distinct from each other

• Allow for regular content creation

• Support your broader goals

Overall, they should feel natural and sustainable. This will allow you to consistently create valuable content without running out of ideas or deviating from your core message.

Furthermore, when developing your pillars, also think about how they intersect and complement each other. You wouldn’t want them to be completely isolated topics.

The most engaging content often emerges from the overlap between different pillars, creating unique perspectives nobody else has combined before.

For example, if you were following someone in the venture capital space, you wouldn’t want them to suddenly switch to posting recipes or travel tips.

Instead, their pillars might include startup analysis, investment strategies, market trends, and founder stories—all interconnected topics that serve their audience's interests and expertise.

When your pillars align naturally, you can create content that flows seamlessly between topics while maintaining relevance and authority.

This intentional, strategic coherence builds a strong personal brand and keeps a high-quality audience engaged over time—the opposite of someone going from topic to topic based on whatever they feel will get the most engagement.

Implementing Your Strategy & Following the Data

Once you've established your content strategy, the key is consistent implementation while remaining flexible enough to adjust based on performance data.

Start by creating a content calendar that maps out your posts for at least two to three weeks in advance.

Any longer could defeat the purpose of being flexible—you don’t want to plan out two months’ worth of content only to realize in week two that you’re going in the wrong direction (once you’re good an idea of what hits, sure, but not starting out).

Your content calendar should include a mix of post types across your defined pillars, with specific topics, posting times, and formats planned out.

Monitor engagement metrics closely during these first few weeks to identify patterns in what resonates with your audience.

Pay attention to:

• Which topics drive the most meaningful engagement

• Which content formats perform best

• Which posts generate quality comments and discussions

• Which posts create the most leads

Use this data to refine your approach, doubling down on what works while phasing out underperforming content types (performance defined by ICP visibility).

The goal is and will never be to accumulate vanity metrics but to build genuine connections and drive real business results.

Stay consistent, track your results, and adjust as needed.

Closing Notes

My entire approach to content strategy centers around my undying belief that success on LinkedIn isn't about creating “viral” posts. Instead, it’s about building a sustainable, long-term presence that establishes you as a trusted voice in your industry.

Focus on delivering consistent value through well-crafted content that speaks directly to your target audience's needs and interests. We’re running a marathon, not a sprint.

As you analyze your metrics and refine your strategy, you'll develop a deeper understanding of what resonates with your actual target market.

This will lead to more meaningful engagement, yes, but it’ll also lead to a deeper understanding of what sort of messaging resonates with your target market as a whole.

That kind of insight is, obviously, incredibly valuable. If you knew exactly which positioning creates the most interest from your target market, you’d promote it through every channel you could for maximum impact.

This is a key aspect of my pitch to B2B leaders when discussing creating LinkedIn content on their behalf—you won’t only get results from LinkedIn itself, but the data you gather will also enable you to perform better on every other channel.

So, if you’re a business owner who’d like to leverage my experience growing my own profile past 230,000 engaged followers and creating results for 40+ B2B leaders, book a call with me here, and let’s chat about how I can help you.

With that said, if you’re not a business owner and still want my help, book a coaching call with me here—I’d love to do whatever I can to level up your LinkedIn content strategy.

And no matter what, make sure you’re subscribed to LinkedUp for more insight like this in your inbox:

Subscribe now

See you next time.

LinkedIn is currently the highest-leverage content marketing channel on the face of the earth. And I mean that in every sense of the word.

It’s scalable, undersaturated (seriously, you’re early), creates results quickly, is easily repurposable, and has an incredibly high presence of B2B decision-makers. And it’s super easy to contact them, too—just send a connection request and/or a DM.

If you have a LinkedIn account — no matter where you are — you are staring at an absolute gold mine of potential, more than any other platform can offer you.

Almost nobody realizes this yet (again, you’re early). And even if you do realize, there’s a good chance you don’t know where to start.

This newsletter will solve that.

In this post, I’ll teach you how to add $25,000 in revenue to your personal income/company pipeline using the highest-leverage platform in the world (LinkedIn!).

Selling Something People Actually Want

If you’re going to make money with LinkedIn, you have to sell something.

This “something” has to be something people actually want because a scarily large number of people do not understand that there’s no amount of marketing that can sell something nobody wants.

I repeat: if your offer (the thing you’re trying to sell) sucks, nobody is going to buy it, no matter how much credibility you have or how good your copywriting is.

Imagine I offered you these two cars for $20,000:

Offering the first car for that price—a junker—would be insulting. You would accuse me of being a con artist, and be offended that I’d think you’d be stupid enough to pay $20k for something that’s worth, at most, $500.

I could assemble the greatest sales team on the planet in one room, give them enterprise subscriptions to Sales Navigator, Smartlead, and Apollo, offer them a $10,000 commission,* and 0% of them would be able to sell the car.

*No, offering the prospect part of their commission to buy the car wouldn’t count.

But the second car—a Ferrari LaFerrari?

You’d jump through flaming rings of fire for the opportunity to buy it for $20,000. Even if the salesperson showed up drunk, in their pajamas, and insulted your mother, you’d do whatever it took to get your name on the dotted line.

Why? Because the value is immediately clear to you.

Even if you didn’t know the exact value (somewhere between $3M and $5M for those who are curious), you’d understand the immense potential in the deal. Even if you had no interest in the actual car, you’d know you could sell it for a minimum 150x return.

And that’s fundamentally the exact same reason people will buy things from you: they expect to get more money out of it than they paid for it. It’s literally that simple.

If your offer sucks—specifically, if people don’t see a way in which the thing they’re paying you for is going to create a minimum 5x ROI—your life is going to be so much harder than it has to be.

Bad offer, hard life. Great offer, easy life. Great offers create lots of leads, and it is really hard to be poor when you have a lot of leads.

What Should You Sell?

This newsletter isn’t about sales as a whole, so I’m not going to pretend otherwise and try to include every piece of sales knowledge I have.

However, to get you started, you’re probably best off building an offer around your prior experience. The reasons why are simple:

1. You’re experienced. You wouldn’t be building your systems from scratch.

2. You have credibility. Your prospects know you have experience in the thing that you’re doing.

For example, if you’re a Head of Content at a venture-backed B2B SaaS, you’re likely only 4-6 months away from $10,000/month (and beyond) as an independent entity delivering fundamentally the same service.

You could pitch developing content strategies and fulfilling them (using a team of freelancers) to the exact same market you currently serve.

Since you’d deliver said services as an agency, you could pitch them reduced costs (your retainer would cost less than a full-time employee, most likely) at the same (or higher) level of quality.

Since you already have experience to point to, it would be a no-brainer for the prospect.

And, of course, there are many more ways to add value beyond simple cost savings.

Side-Note: Total Addressable Market (TAM)

By the way, it’s really important that there exist at least 1,000,000 people/businesses on earth who are capable of purchasing your service. In marketing, this is called TAM, and it completely defines the way you market your services.

Marketing a service with a large TAM is relatively straightforward because, at its core, it’s a numbers game. Assuming you have a good offer, the only barrier between you and more revenue is the number of decision-makers who are aware your offer exists and the benefits it provides.

But if you have a small TAM, it’s only a numbers game to the extent that numbers are available.

Take, for example, Steinway Tower in New York City.

This is an apartment building, with its “cheapest” entry available at $15,000,000 and topping out at around $50,000,000.

The most generous TAM possible for these units is 295,450 people (the approximate number of people with a net worth of $50M+ in the world).

You’d then have to filter the number of people who are interested in property in NYC and further filter it for those willing to invest in a newer building that’s yet to stand the test of time (when they could invest the same money in proven real estate).

This is probably less than 10,000 people globally. Maybe less than 1,000.

Due specifically to the small TAM, this unit requires a highly intensive marketing process to sell—including highly personalized outreach, countless private tours, extensive awareness campaigns, months of negotiation, and much, much more.

Even then, there’s no guarantee. Many of Steinway Tower’s units remain vacant.

The developer most likely realized this would happen and is betting on Steinway becoming an iconic building over the years that UHNW individuals feel comfortable investing in. This is obviously not a viable strategy for the vast majority of people.

In contrast, consider a townhouse in a desirable part of Washington D.C. or San Francisco hovering around $1,500,000.

Units like these are much, much easier to sell since they not only have a large target market but also offer clear value to the client.

The takeaway here is that, assuming your offer is fundamentally worthwhile, TAM completely defines your ability to market and sell your service.

This is why you should not niche down too much. Be a B2B SaaS marketer, not a B2B newsletter marketer for health tech brands that are training to raise a Series B.

Proving Your Credibility

I’m probably going to have to reiterate this in many newsletters, but before you think about using LinkedIn to draw attention to yourself, you have to be ready to receive it.

Let’s start with your profile.

Your LinkedIn profile is your digital first impression, and it needs to prove your credibility to the amount maximum extent possible.

When people talk about “optimizing your profile,” what they actually mean (or should mean) is “making your credibility flagrantly clear and directing the resulting high-quality attention to a high-converting landing page.”

Here is Justin Welsh’s profile:

It’s very, very credible.

Not just because he has a lot of followers (that definitely helps), but because it looks professional and showcases prominent media features he’s received (Forbes, Insider, Vice, etc.).

After viewing this, you’ll then be directed to his landing page, which further showcases his credibility (a 4.98/5 rating from 25,000+ students).

While you won’t be selling courses*, you’ll still follow the same fundamental formula: offer something enticing, multiply the appeal of said enticement with your credibility, and transition the now-intrigued prospect to a channel in which they can convert.

*Why shouldn’t I sell courses?

Selling courses is an unproductive pursuit for the vast, vast majority of people. The reason is that “it’s not a real business” (quote from Daniel Fazio, an entrepreneur producing over $600,000 per month, with his income streams including a portfolio of educational products).

Courses only have one sales channel: your social media profile. No serious business can depend on a single sales channel because the lack of diversification massively exposes it to catastrophic income variation if (and when) the status quo stops working in its favor (even if temporarily).

That is not a real business; it’s a glorified lemonade stand, capturing and converting attention from passing cars in the neighborhood (yes, some people make tons of money this way, but 99.99% of people do not!).

Maybe if you become a gargantuan influencer who can afford to potentially lose money (I’m talking tens of thousands) on ads developing an alternative sales channel, you’ll have a chance at a slight amount of sales channel diversification. But even then, it’ll be a shadow of what you could achieve by investing the same energy into a proper offer.

Finally, the sporadic nature of the income—and this is perhaps the worst part. ~80% of your income will come from launches, meaning you may make $30,000 one month and have to live off of that—combined with whatever residual you collect in the following months—until your next big offer in 6-12 months. And that’s only if you know how to launch a product at all.

If you think I’m wrong, don’t take my opinion—take it from Justin Welsh and Nicolas Cole, the most successful course-sellers I know who aren’t grifters. Both of them will tell you that you’re much better off investing in a proper service and, maybe down the line, adding a course as a side-income stream.

Creating (Qualified) Leads

We’ve cleared the fundamentals. Now comes the fun part: creating leads.

There are two ways of doing this on LinkedIn:

1. Content marketing (posting)

2. Outreach (sending DMs)

The top performers will combine both—here’s how:

Content Marketing

Content marketing is marketing with content. In this context, that means posting.

I’ve done this quite a lot, and it’s lead to me building over 220,000 followers since beginning (seriously) in mid-2022.

Ironically enough, lead generation isn’t the primary objective of posting.

While it’s certainly an effect of it (among other things), the primary outcome of you hitting “post” is brand awareness. In this case, awareness of both your personal brand and the company you represent (if any).

Every time I hit post, both myself and Soleo itself occupy just a bit more real estate in the minds of people around the world.

Thanks to the compounding effect of doing that for a long time, it’s resulted in some rather wonderful outcomes—outcomes that are just getting started.

Yes, that outcome often includes qualified leads. But it also includes podcast invites, sponsored post offers (which I turn down most every week), real-life networking opportunities (or virtual ones), and many more.

But fundamentally, I’m creating brand awareness. Specifically, it’s awareness of:

• The service(s) I offer

• The expertise I’ve earned

• The credibility I’m building (case studies, prominent clients, etc)

…all manifesting in a variety of very cool things.

However, impressions don’t create brand awareness in a vacuum.

Engagement bait (e.g. posts like, “Bosses should be nice! I’m very smart and cool!”) doesn’t create admiration from decision-makers; expertise-driven content does.

Don’t post stuff like this:

Post stuff like this:

Or this:

Or this:

…or anything else that clearly defines you as a credible, high-value authority in your industry.

When abroad, no matter where they are, people generally opt for chain hotels—Hilton, Hyatt, Marriot, etc—because they understand they can be relied on to hold a certain standard, while local hotels are a wildcard.

People will opt to work with you for the same reason—you’ve convinced them you can deliver consistently where others can’t.

By the way, this newsletter is content marketing. I could do weekly releases*, but I release these more occasionally when a genuinely awesome piece is ready—this channel is best for deep dives (a weekly phone-in post would be a huge waste).

*Some people have great weekly releases, this isn’t a knock on them

The goal is to establish myself as an uncontested ultra-top authority on all things LinkedIn. That’s the goal of my posts, too, of course, but as a rule, they have to be more bite-sized.

Outreach

Outreach represents the most proactive way of cashing in on your credibility and creating leads.

If you’re cooking up something good, there’s no reason to just sit around and hope the smell wafts around the neighborhood, enticing random people to walk in the door and see what’s for lunch.

You should be proactive about making people aware of your cuisine. Otherwise, there’s a very high chance you’ll just waste your time cooking.

On LinkedIn, you do this “proactive awareness” with connection requests and direct messages. This dovetails extremely nicely with content marketing because the brand awareness derived from that will accelerate your outbound results.

Prime example: I recently converted a venture-backed SaaS (Series C) into a client through a relatively basic outbound sequence.

I offered them a small sample of my service. They found it intriguing, spoke 1:1, and, after a brief deliberation, began working with me.

What made it work was, fundamentally, my credibility.

There’s no shortage of people offering some sort of done-for-you (DFY) LinkedIn service, but very, very few actually deliver. And pretty much nobody else has my level of credibility (followers, case studies, clients, etc). In many ways, I am in my own league.

So, once you’ve optimized your profile and started creating credibility-driven content, you need to start maxing out connection requests.

LinkedIn has a de facto limit of around 350-400 connection requests per month, which is a bit over ten per day. This is pretty trivial to fulfill manually—which you’ll need to do since LinkedIn is very sensitive to these sorts of automations.

How to Perform LinkedIn Outreach

Next, I’ll show you how to actually do the thing we’re talking about.

Building a List of Targets

First, purchase a Premium subscription. By default, you’ll be limited in your ability to view profiles, and LinkedIn will hard-limit you pretty quickly.

You’ll need a Premium Business subscription to get past this—but if you’re really serious about maximizing outreach, I recommend getting a Sales Navigator subscription.

Sales Navigator is a nice-to-have tool because it’s a pretty robust research platform.

You’ll need to build a list of targets, and using Sales Nav for LinkedIn outreach will be much more straightforward than using something like Apollo.

But Sales Navigator or not, start building your list of connection request targets.

I first recommend clearly defining your ICP (ideal customer profile). You can do so in a basic spreadsheet like this:

It’s nice to have this on paper—not just for your own benefit but also so a VA can build the list for you (if you don’t want to build it yourself).

Once you’ve defined your ICP, start building the actual list. The best research tool for this purpose is Sales Navigator, but other sales tools can work, too.

Whatever you choose, use a Sheet like this to track them:

Once you’ve filled it with 100-300 targets, fire away.

“Should I send a message in my connection request?”

In my opinion, you should only attached a message in your connection request in two instances:

1. You have something genuinely meaningful to say (e.g. you met them at a party, you really like a specific piece of content they created, you’re a user of their software, etc.)

2. You have zero connections in common

Otherwise, I find it hard to develop something meaningful to say, consistently, that doesn’t seem templated and off-putting. Trying to do so will slow you down too much, too, and really won’t help you all that much

If someone hasn’t responded after 3-4 weeks, withdraw the connection request (you can do this from the invites menu).

They’re unlikely to respond beyond this period, and keeping your pending requests as small as possible is considered best practice for maintaining your “sender” reputation on LinkedIn.

Sending DMs

Once somebody accepts your connection request, wait at least 3-5 days before sending them a message. This gives them time to look at your profile and have your content appear in their feed before sending anything out.

This is a good time to mention that LinkedIn is a quality-over-quantity outreach platform—or at least it leans that way.

If you DM someone you’re connected to (or send them an InMail, which comes with Sales Navigator), there’s a 99% chance they’ll see it if they’re active on LinkedIn at all. That’s really awesome coming from cold email where a 30-40% open rate is considered extremely solid.

But it’s counteracted by the fact that you can only realistically reach out to 100-200 people each month—LinkedIn's biggest weakness as an outreach platform (it’s really meant for recruiters, who generally have the upper hand in outbound, thus making the outbound limit inconsequential).

This begs the question: what should you actually say? How do you make the most of your limited chances with your target market?

There’s a prevalent school of thought that effective outreach on LinkedIn means becoming best personal friends with the person, traveling to their wedding, and buying them a new puppy before you ever think about selling them anything.

To be frank, if you feel afraid to pitch people your services, you probably feel unconfident in your offer. If this is the case, your offer might suck, or you have so few case studies that it may as well suck as far as your target market’s concerned.

If you appear credible and authoritative, people will respond to your outbound. Many of my outbound messages are pretty basic,* but they work—again—because I’m extremely authoritative.

*Basic doesn’t mean spammy. I send short, concise, and conversational messages, generally referring to a case study and offering to send a free sample of my service.

I’ve tried very personalized outbound where I reference something specific about their accomplishments, a recent milestone, or a nuanced aspect of their business.

It never seemed to affect the response rate much, and the reason for this is extremely obvious: mature business owners can always recognize when they’re being pitched, no matter what you say.

With that in mind, you may as well get to the point. They’re either going to want your service or not. Outside of improving your offer, there’s really nothing you can do to change that.

Side note: the same rules don’t apply to long-term “dream clients” that would be life-changing if you were able to secure them as a client. There does exist a hyper-personalized mega value-add approach that is completely worth investing in, but that’s for another newsletter.

It’s the same way that a woman at a party knows that the men approaching her most likely aren’t making conversation for the fun of it—they perceive her as attractive and available and thus are pitching themselves as potential partners (even if they’re coy about it at first, opening with basic conversation).

Assuming they have basic respect and social competency, the woman is either going to be interested in a relationship or not, whether in general (general need for services) or with them specifically (interest in their services).

The “need” is almost completely out of their control—it either works out, or they need to move on. Sales is the same way in every medium (nobody runs ads expecting to convert everyone).

If you’re of the school of thought that success in sales depends entirely on your ability to build pseudo-social relationships with targets, you don’t need to be here. All you need to do is pitch your good friends and family on your services.

In this case, if the strength of the relationship is the “X factor,” you should have zero trouble in converting 100% of them to your services.

Obviously, that won’t happen because, most likely, 0% of them have a need for your services. There has to be a need. Welcome back.

The good news in sales is that everyone likes making money. If you offer a good service that offers your target market a transparently good chance of making more money, generating interest is not difficult, and people will respond to your outreach.

So just be respectful and to the point, knowing that your results almost completely depend on the strength of your offer and the authority you present with your profile.

For example, Sunny Bonnell.

Sunny is the co-founder of a world-renowned brand strategy agency that’s worked with Google, Virgin, the NFL, and other household names.

She also has 15,000 engaged followers and the blue Top Voice badge, as well as features on Bloomberg TV, Yahoo! Finance TV, and Cheddar TV.

If you’re the founder of a tech startup that’s just raised a Series A funding round and Sunny messages you something like…

Hey Jimmy Startup, congrats on the Series A. Just so you know, we started working with Unicorn after that same milestone, and thanks to the strategy and branding we built for them, they were acquired by Netflix for $40M five years later. Can I send you that case study?

…there’s a good chance you’re going to respond in the affirmative.

It’s overtly promotional, but because you recognize her authority, credibility, and ability to create an ROI an order of magnitude higher than what she invoices you for, you’re probably going to say, “Yes, I’d like to see that case study.”

She doesn’t need to send you a vicuña sweater from Loro Piana that includes a hand-written invite to The French Laundry coupled with a Delta One ticket to San Francisco, in which she’ll then mention the case study.

True, that probably would make you more likely to respond, but because of her credibility, it’s not necessary at all.

Now, keep imagining you’re that Series A founder. But instead of Sunny messaging you, it’s someone with a selfie profile picture, a low-quality portfolio, and no real case studies to speak of.

You wouldn’t respond. And even if they sent you the vicuña sweater, you’d probably assume it was fake. You surely wouldn’t go to meet them in the Bay Area.

This should be extremely comforting because it takes a load off the shoulders.

You don’t need to invest in the convoluted social selling processes many people cite as mandatory. You just need to not suck at what you do.

Unless you’re selling Park Avenue Tower units, competence and credibility are all you need to book calls with prospects—your sales skills are just an optimization.

Does your offer suck? Scroll back up and build a Ferrari LaFerrari offer.

Does your offer not suck? Then start sending messages—people will respond.

When people respond, get them into a 1:1 call. Then, pitch your services and convert them. Your revenue/added revenue will grow and grow and grow—to $25,000/month and beyond. Just keep putting in the work.

Yes, I’m leaving a lot of detail out, but this is a high-level overview of the process, and the little details of each part are best left for another day.

Rest assured that what’s written here is, fundamentally, all you need to do.

Conclusion

To reiterate, LinkedIn is the highest-leverage content marketing channel on the planet right now. It’s pretty darn good at outreach, too—as I mentioned above, I recently signed a Series C SaaS client through DMs.

That said, if you’re a leader at a business generating over $1M per year in revenue, you have zero time to devote to this with everything else on your plate.

And given that I’m extremely good at this, you should outsource it to me. If that interests you, please book a call with me here.

If that doesn’t describe you, but if you’d still like to work with me, please book a paid coaching call with me here.

In any case, I’ll see you in the next newsletter (coming when it’s ready).

Thanks for reading.

Update December 2025: I wrote this quite a while ago, and there have been some updates to my philosophy since. However, it’s still very useful, so don’t let that stop you from reading it.

I grew from 0 to 100,000 LinkedIn followers in less than 12 months.

Within the same year I started posting, LinkedIn allowed me to go from a part-time college student walking dogs to making over $10,000/month.

Almost exactly a year after starting to post consistently (July 2022), I made nearly $30,000 in a single month through income streams deriving from my LinkedIn presence (mostly ghostwriting).

I did this all on my own, with almost zero prior social media experience, minimal coaching from others, and completely self-initiated.

This wasn’t a one-off, either. I’ve successfully applied my learnings with over 20 different companies whose leaders I’ve ghostwritten for and countless others I’ve coached.

I have skin in the game because I don’t only actively do it for myself—now having well over 200,000 followers—but I actively apply it for some of the world’s most impactful people.

I have written for creators with much bigger audiences than me, managed LinkedIn for founders of some of the world’s fastest-growing startups, and just a plethora of people with unfathomably high net worth.

In this newsletter, I’ll explain the exact strategies I used to make all of this possible in five key steps.

Now, keep in mind that this guide isn’t a direct play-by-play of what I did. I’ve grown as a creator over time, and I don’t believe in everything I used to do to get to this point.

So, you're not only getting my playbook for extraordinary results, but you’re also getting the benefit of all my hindsight.

If you just do what I tell you, you can build a fanatically loyal and incredibly high-value audience without suffering the scapes and bruises I had to endure to acquire the knowledge.

If you implement all of this consistently, it is literally impossible not to create equally transformative—or even more transformative—results in your life (sustainably and realistically).

Let’s dive in.

1. Mentally Preparing Yourself to Succeed

Succeeding on LinkedIn requires a few foundational mindset shifts.

Not caring about people’s opinions

Many people's biggest concern about posting on LinkedIn—since it’s done with their real name and face, and they’re probably connected to people they know already—is what people will think of them.

Y’know, their friends, former classmates, and coworkers. But it is completely bonkers whacko crazy to care about what other people think.

0% of those people are going to do any of this for you. Letting people’s opinions prevent you from fulfilling your potential—here or anywhere else—is the peak of self-destructive behavior.

Whether they think it’s admirable or cringe, you shouldn’t care.

Pushing through slumps and slow progress

If you’re like most people, you probably have not consistently applied yourself to something that requires an extraordinary amount of self-initiative

When you’re working through school or a job, however hard it is, you always know exactly what to do at all times. It is very simple to succeed in those things, irrespective of how much work it takes.

But with LinkedIn, nobody is holding your hand.

You can read posts like this for advice, but I can’t do the work for you (unless you’re willing to pay thousands of dollars for ghostwriting, which is definitely an option if you have the budget)

You will probably get zero likes when you post for the first time.

When you post the second time, you’ll get zero likes, and when you post the 10th time, you’ll probably—you guessed it—get zero likes.

But one day, you will get a like. And if you stay consistent, it’ll become 2-3 likes. Then 10. Then 20. Then beyond, which is exactly how it was for me.

You have to learn to be consistent no matter what. There’s no replacement for it. This is the nature of audience building.

Even if your first post gets 100 likes—which I hope it does—you will eventually have a slump to push through. And push through, you must.

2. Defining Your Niche

You need to define a specific niche in which to build expertise and authority.

This isn’t just so you know what to post about; it’s so you build true fans who know they can rely on you for insightful information on a specific subject.

It’s okay to experiment with this—I’ve switched my niche several times—but you ultimately want it to be aligned with something you can monetize, which is probably going to relate to the industry you already operate in.

Example: my friend from high school just got pre-seed funding from Y-Combinator for his cybersecurity startup, which he built from expertise in his day job (which he still works in).

He’ll soon start posting on LinkedIn, and he’ll post specifically about topics related to his business.

That’s where he has skin in the game, can build authority, and can translate the attention he creates to qualified leads for his business.

You don’t have to have a business to pick a niche, though. My sister posts sales content even though she’s an employee and currently has no meaningful ambitions to be an entrepreneur.

However, she has expertise in that field, and sharing sales content helped her just secure a new position at a company with a much higher growth ceiling.

I don’t want to put too much pressure on you, but it’s important to be very strategic about your niche on LinkedIn.

It’s very hard to start over if you build either a low-quality audience or an audience for something that you don’t want to write about in the future.

You can start a new channel on YouTube, Instagram, or TikTok. However, on LinkedIn, it’s tied directly to your identity. This makes it difficult to change course.

The best way to pick the right niche is to write something related to your current industry, broadly or specifically.

If you work at a software company, you can write about the specific thing your software does or the software industry as a whole.

Approaching niching this way means you’ll build a high-quality audience that’s ripe for monetization, just like Zach Wilson did with Data Engineering.

You’ll also notice that he has a huge audience despite being extremely technical.

This is proof that being as specific as possible isn’t an obstacle to building a large following; it’s actually highly conducive to it.

If you create generic content with the goal of “going viral,” you’ll be extremely forgettable.

But if you’re writing specifically on subjects in which you have skin in the game—a fundamental factor in being remarkable—you have a huge edge in standing out.

When I started on LinkedIn, I covered content writing and content marketing since I was a freelance B2B blog writer at the time.

My first post was about that, but eventually, I started posting about how I used AI for writing, which became very popular and since I built a huge following on LinkedIn, I just transitioned to focusing on the LinkedIn strategy itself since that’s what my business is.

3. Optimizing Your Profile

Your profile acts as the “landing page” of your LinkedIn presence.

When someone sees your post in their feed, your profile is the first place they go to get more context about you and what you do.

As a result, your profile needs to be optimized to capture attention and convert it. I’ll now go through each section of your profile and show you what to do with it.

Headshot

Your headshot is the first thing people see on your profile—both in your feed and when they open your page.

It’s not conceited to say that people are going to judge you by the quality of your profile picture. It’s just being realistic.

Showing up on LinkedIn with a low-quality phone photo is like showing up to a wedding in pajamas and flip-flops.

Sure, it’s better than nothing, but people will look at you sideways for doing it. So, do whatever it takes to take a good profile picture.

If you’re decent with a camera, feel free to set up your iPhone on a tripod, take a time selfie on a nice background, and spruce it up with Canva.

If you can get a professional headshot, I recommend you do.

A good headshot photographer doesn’t just have a nice camera, they understand lighting, angles, and expressions too, and will ensure you walk out with a world-class photo.

Finally, take 3-4 of your best candidates to Photofeeler, which is a free photo voting site where you can have people pick the best one (because crowd wisdom is much wiser than your own in this case; we’re really bad at picking our own photos).

Banner

If your profile picture is the first thing people see when opening your profile, your banner is the second.

One of my favorite banners is the one we made for UN/COMMON, one of our clients:

It’s on-brand, elegant, and showcases its branding in an elegant way.

Now, of course, you can write something that’s slightly more promotional without being cringe.

Justin advertises his course, but he does so in a way that just announces it exists and naturally inspires you to click through to his website to learn more about it instead of being like…

BUY MY COURSE NOW 50% OFF FOR A LIMITED TIME

That could give off flea-market vibes, which is the opposite of the premium brand he wants to foster.

He offers discounts, but he waits until you’re on the page to share that. To me, that makes it much more appealing.

Okay, now, how do you actually create your banner?

You can do it super easily in Canva—just search “LinkedIn banner” in its templates section, and a huge selection of pre-made templates with the perfect sizing will pop up.

You’re welcome to use another tool if you want, but Canva makes it so much easier.

I have a professional designer on my team who knows advanced tools like Figma and Photoshop, and we still use Canva as much as possible because it’s just so easy and has plenty of advanced features.

Tagline

Your tagline is the short introduction that accompanies your profile wherever it appears on LinkedIn.

This is arguably the second most important part of your profile—if not the most important—because it’s where you sum up the entire essence of your presence in 2-3 short sentences.

This is mine right now—though it’s obviously subject to change.

Leading with the “Founder” title provides some context of who I am. Then, “the highest level of LinkedIn strategy” talks about what I actually do.

And I think more than anything else, that’s what I exist to provide on LinkedIn and in this newsletter—non-generic, actionable LinkedIn strategy for people who need it.

My unfair advantage (in terms of standing out) is that I play LinkedIn at a higher level than pretty much anyone else because I manage not only my own presence but that of some of the world’s most cutting-edge organizations.

Of course, I emphasize that fact literally by clueing people in to who my clients are: highly-funded SaaSs (Series A, B, and C), YC-backed startups, and 8-figure marketing agencies.

That’s not exclusively who I serve, but it is the echelon of clients I serve. When I get to Series D/E startups and 9-figure companies, I’ll adjust it accordingly.

That’s just one example, however.

Adam Robinson, who, by the way, is one of the best examples of someone who absolutely understands how to leverage LinkedIn to its fullest potential, has a really excellent tagline.

Why? Because it…

• Advertises his position as the CEO of a well-known company (authority)

• Explain what his product is

• Concisely explains what it does in a way that makes it instantly appealing

And you basically need to follow the same model.

Explain the value you offer in the most concise way humanly possible. Some people will give you set formulas to follow, which is fine to start with, but really, there is no formula for this.

Marketing is about sticking out. You need to frame your value in a way that makes you remarkable—literally, worth remarking upon.

I say, “I’m practicing LinkedIn strategy at the absolute highest level.” That is very interesting to people who are very interested in LinkedIn if I can back it up with evidence (which I do).

In the above example, Adam identifies people who visit your website.

That is incredibly monumentally freaking interesting to literally everyone with a landing page. And, of course, he shares his expertise related to that sort of thing in his posts.

Just explain your value proposition as concisely and as interesting as possible. There really is no formula for this beyond the principle of the thing. Just say something that’s interesting (while being honest, obviously).

Other stuff

Now, that’s not absolutely everything there is about profile optimization.

There’s also your…

• CTA button

• About section

• Prior experiences

• Recommendations

• Featured links

• Profile URL

…and more. But that would be getting way far away from the point of this newsletter, which is a (relatively) concise overview of the principles of building an increasingly massive, high-quality following.

I did teach that 80% of what matters is building an audience, and we’ll circle back to the other stuff in another issue of LinkedUp, so subscribe for more if you haven’t yet.

Subscribe now

4. Publishing Content

Congratulations—you’ve now laid the foundation for a successful LinkedIn presence.

All that’s left for you to do is build your audience, which is the whole purpose of this post.

You do that with … posting.

So next, I’m going to show you how to do an amazing job at that.

What a good post isn’t

A good LinkedIn post is not what gets the most attention possible from the general public; it’s what gets the most attention possible from your target market.

Because just “getting engagement” on LinkedIn is not particularly hard. All you need to do is post ultra-generic engagement bait appealing to the widest possible audience.

I’m not going to cite specific examples (because I’m not going to shame anyone publicly), but currently…

• A list of the top 10 AI tools

• Links to free leadership courses from Harvard and Yale

• Some cheesy quotes about motivation

…will always get engagement from someone.

If you’ve used LinkedIn for literally any amount of time, you will know exactly what posts I’m talking about (and the obscene amount of engagement they currently get).

But there’s a problem with these sorts of posts: they don't build true fans who appreciate your exercise in a meaningful way.

They are building unqualified, empty followers who will never convert into clients and customers. This is a sucker’s game.

Creating engagement slop is an almost literal Faustian bargain: you sell your profile’s soul in exchange for gratifying your ego, and like all short-term thinking, it always comes back to bite you.

So don’t learn this the hard way.

Listen to what I’m saying because there is a literal army of would-be gurus ready to sell some sort of solution for “going viral” in the fastest way possible.

It’s an easy sell for them—especially if they have perceived authority—because it appeals to your most primal desires to have strangers think you’re cool and funny, and maybe they’ll give you money, too (spoiler alert: they won’t).

Those people do not want you to make money; they do not care about you, your success, or your happiness.

I want you to use your LinkedIn presence to create financial freedom and play a literal infinite game that never stops making your life better year by year. Listen to what I am telling you because I actively do this for other people; I don’t just teach it.

So, every time you sit down to write a post, you should ask yourself:

“How can I provide as much value as possible to my target market in the most interesting way possible?”

Here’s how:

What does good content look like?

What does providing value actually look like? It’s easier to show you:

This is a post by one of my clients, Micah, covering a crucial topic in his industry: how your site’s user experience design has to be guided by hard data, or it’ll cost you a massive amount of sales.

It showcases his expertise by outlining specific ways ecommerce stores can improve their user experience design, and uses a nice visual to explain the idea concisely.

You can create a visual template like this (in your own style, of course) very quickly in Canva and reuse it every day.

Now, notice the example I’m using here isn’t some generic viral post with 50,000 likes; it’s a targeted post aimed at a specific audience with the goal of converting them into clients.

For the record, I have at least two posts with over 50,000 likes and, I think, a dozen or two with over 10,000 likes.

But most of them were very generic, aimed at a broad audience, and, as a result, did not create any meaningful amount of leads—basically zero, to be precise.

Justin Welsh, who has been the #1 LinkedIn creator for years, actually relayed the same information to me—his most “viral” posts have always produced zero or close to zero attributable sales.

This is not because going viral is inherently bad, but when something goes viral on LinkedIn, it’s usually because it appeals to a very broad—and thus diluted—audience.

That’s why I produce targeted content pretty much exclusively. As a result, I’m continually building a high-quality audience that’s ripe for monetization.

Speaking of monetization, this is another great post by my friend Connor Gillivan, who runs a search engine optimization agency.

He often uses visuals to explain concepts in SEO, and it’s almost always a big hit with his audience.

This post explains a pretty basic concept in SEO—he obviously can go into a lot more detail, and sometimes he does—but that’s on purpose because his target audience has limited SEO knowledge and contracts his SEO services for precisely that reason.

Jake Ward also creates SEO content, which is usually also high-level for similar reasons.

This post, where he showcased some of the most common SEO mistakes, was a great balance. It was understandable enough for a layman audience while technical enough to sufficiently showcase his expertise in his field.

If you think you can’t create graphics like this, you absolutely can. Again, Canva makes this super easy (though a little time-consuming).

If your goal is to make the best impression on a specific target audience—which it absolutely should be—I recommend taking the time to create visuals or have them created for you.

It’s ideal to post at least one or two each week in addition to the “normal” written content, which is obviously much more straightforward to produce.

Your goal isn’t likes and comments (though they will come if you’re doing a good job); it’s to impress a specific audience as thoroughly as possible.

The quality of your content is your remarkability factor.

It’s what makes people think about you after they’ve finished reading your post and eventually convert into customers of your products and services.

How often should you post?

This is why, starting out, you should only post as often as you can make quality content. Don’t feel pressured to post every away starting out.

Focusing on quality will be difficult at first, but you’ll immediately start building systems that enable you to produce quality content more efficiently.

The ultimate goal is quality content at the highest possible scale, 1-2x per day.

This means scaling the effect of impressing your target audience as much as possible, which leads to creating as much revenue as possible.

If you’re shoveling out generic viral bait every day, you will not convince people to invest in your products and services in any meaningful amount.

A huge rookie mistake to LinkedIn—and social media in general—is assuming all big accounts are rich. I can assure you that they are not.

I’m actually willing to bet that statistically, probably somewhere around 80-90% of LinkedIn accounts with over 100,000 followers produce less than $50,000 per year in revenue directly attributable to LinkedIn

In all likelihood, that’s being very generous.

But I’ve seen plenty of accounts with a few thousand followers producing well over 5 figures each month. How’s this possible?

Because those people are writing to impress people who can actually produce revenue for them. Write for the people who write your checks—that’s basically my catchphrase at this point.

Of course, being targeted doesn’t mean you can’t create a large audience. If you’re consistent enough—I’m talking over years—you can build tens of thousands of devoted fans (or more).

But please, please, please do not fall into the trap of trying to take shortcuts with empty viral bait. You only want true fans, not empty followers.

5. Building a Valuable Network

One of LinkedIn’s greatest strengths is how easily you can use it to create an unbelievably valuable network

It’s better at this than Twitter and YouTube, especially now.

As you grow your following of true fans who recognize your expertise in your niche, you also need to steadily build a network of people who make you smarter and passively create opportunities for you by virtue of being high-agency people.

This is just as important as building a quality following. Why?

Because having resourceful people in your network exposes you to much more valuable information and opportunities than riding solo.

This won’t necessarily get you tons of new followers (though it certainly won’t hurt), but it is extremely important for making the most of your time on the platform.

Because when you’re by yourself, you’re in a bubble, and thus suffer the extreme tunnel vision that comes from being one person doing one specific thing.

You need smart people around you, or you will be doomed to sit and watch people doing similar things to you grow much faster (because they are networking).

There is nothing more dangerous to your growth than existing purely in the extremely slim slice of awareness that is your daily life.

Here’s how to fix that by building a valuable network:

Connection requests

After you’ve optimized your profile and started producing quality content that establishes yourself as an authority in a given field, you’ve already done 90% of the work of networking (establishing yourself as someone worth networking with).

Valuable people don’t want to connect with people they perceive as non-valuable.

Not because they’re conceited (well, sometimes), but because their time is genuinely valuable, and they literally can’t afford to give it to everyone who asks.

But if you’re out doing cool stuff in public, valuable people will want you around them. It’s literally that simple.

So start sending connection requests to other people at a relatively similar audience level to you who are actively creating targeted, audience-facing LinkedIn content with the presumed goal of creating revenue rather than just farm engagement.

You don’t want to network with people who are just farming engagement.

They still haven’t unlocked the most basic principles of content creation, which means they will be a drag on your development. You want to network with smart people who are actually doing something productive with their content.

For example, Teddy Mitrosilis is someone I’ve become acquainted with recently.

He co-founded a B2B personal branding agency and uses his content to generate leads for it. This agency’s service is adjacent to mine, so it’s a really good person to network with—we both benefit from our mutual knowledge exchange.

How to “lock in” relationships

Once you’ve connected to a valuable person, move the relationship forward in some way; otherwise, it’s all for nothing.

A great way to do this is to offer to set up a 1:1 coffee chat—virtually by default, but literally if they happen to be near you. If you’ve succeeded in establishing yourself as a valuable resource, they are likely to accept.

My favorite strategy for retaining valuable people in your network is to get them all to participate in a strategy group chat.

The common goal is to trade LinkedIn growth expertise, but of course, it’s also an opportunity to swap knowledge about anything else.

As a bonus, you get the added bonus of being seen as a “connector” whom valuable people love and have a habit of rewarding.

But the best possible thing you can do? Combine both of these strategies.

Set up a 1:1 with them, then invite them to your nascent group chat. You’ve then created an extremely memorable interaction with you both, leading to a relationship that will last a very long time. And it’s so easy, too.

Reaching your “aspirational” connections

Now, there are inevitably going to be some people who you want to connect with, but there’s too much of a value gap between you two to make a relationship mutually beneficial in the same way your “normal” connections are.

This is because the perceived value you have to offer is much less than the perceived value they have to offer.

But it’s really important that you successfully connect with people who are ahead of you because networking with them and acquiring their knowledge will help you skip years—if not decades—of struggle and toil.

I don’t want to sound conceited, but just to hammer the point home, the reason I was making multiple six figures by the time I was 23 was specifically because I borrowed the knowledge of people who were ahead of me—both through their public material and direct interactions with them.

So it’s crucial that you not only identify these people but actively make moves to connect with them.

For example, I’d love to network with Alex Hormozi.

But at this point in time, even with everything I’ve accomplished thus far, the gap between my current perceived value and his perceived value is an actual Grand Canyon’s width in distance.

His talking to me for an hour would literally cost him tens of thousands of dollars in productivity—if not more.

But just because someone is currently out of your reach doesn’t mean it’ll stay that way forever.

For example, Justin Welsh is the person who inspired me to start posting on LinkedIn regularly.

I always wanted to network with him, but in my first several months of posting, the value gap between us, in his favor, was too large to make it realistic.

But over time, I closed that gap, and now we’re not only connected, but we’re actually friends who speak regularly.

How is that possible?

Well, there are three ways to connect with someone who’s (currently) very far ahead of you:

1. Giving them a lot of value for free

2. Offering a service that’s valuable to them

3. Paying them for their time

I’ll break down each.

Giving them a lot of value for free

Straight up, just do something for them that would cost a “normal” person money.

For example, Dickie Bush, who now makes $10,000,000 each year with his online businesses, got his first big break by getting a mention from Tim Ferris in his newsletter, who, if you don’t know, is a legendary podcaster.

He did this by compiling some of Tim Ferris’ knowledge from his extensive listening to his show and sharing it publicly, which Ferris then found and shared.

However, while potentially very effective, this method is less predictable because there’s no guarantee that they’ll see it.

Offering a service that’s valuable to them

My position as a LinkedIn agency owner puts me in the extremely unique position of having high agency people not only seek me out but literally pay me for their time.

This is not normal, but it’s reality. I get people worth millions—tens of millions—on calls to talk. Then, I send them an invoice.

On my current trajectory (with the case studies and referral network I’m building), I’ll eventually be doing this for people worth hundreds of millions—or billions (or at least the people who report to them).

How’s this possible?

Because I do something that not only do they not know how to do it, but they couldn’t be bothered to do it themselves even if they wanted to.

I will literally tell any prospective client, before I’ve even fully qualified them, anything they want to know about my operation (outside of actual confidential info like who my private clients are).

At Soleo, there are no secrets; there is only execution. And that’s what they pay me for.

But if you’re building a service from scratch, you won’t be able to benefit from this from the start.

You’ll be working—or should be working—on a performance basis for mediocre clients who run lukewarm businesses for which you struggle to get results (because their businesses' suckiness handicaps your own effectiveness as a contractor).

But those are the only people who will accept you starting out.

And if you grind that phase out and start building case studies, eventually, the heavy hitters will start knocking on your door (or they’ll at least answer when you knock).

At that moment, the service that makes you money becomes a vehicle for accelerating your network growth. Isn’t that cool?

Paying them for their time

This one’s pretty straightforward. Most people will accept money for their time if the offer is right.

They’ll either advertise this directly (like I will in this newsletter), or if you DM/email them asking for a paid call—optimally pitching a generous amount—they’ll probably accept.

If leveraged effectively, this can have a massive ROI. If you show up to calls with people years ahead of you with a list of problems you need guidance on, they can help you skip years of frustration.

I don’t think this one needs too much fleshing out, but I’ll emphasize the fact that you really, really need to invest in education right now more than you need to invest in stocks and bonds (metaphorically, that’s not financial advice).

If you want to grow on LinkedIn and make money from it, you should book a 1:1 LinkedIn strategy call with me.

Book a 1:1 Call With Me

In just one hour, I can realistically change the entire trajectory of your life by teaching you to leverage LinkedIn to its full potential based on your individual goals.

Closing Notes and FAQs

This has been a very high-level overview of the principles I followed to grow to 100k (quality) followers and beyond, but it’s more than specific enough for you to action right now.

At the risk of sounding cliche, the greatest tip I can give you is to just get started.

This all fundamentally started when I made a very intentional decision to keep posting on LinkedIn every day no matter what, because I knew what rewards stood on the other side, and continue to stand on the other side, of that level of tenacity.

So just do it.

Now, to close off, I want to answer some of the most common questions I receive about LinkedIn growth that I didn’t cover fully here.

How important is commenting?

There’s a school of thought going around that you literally cannot grow on LinkedIn without writing at least 20 heartfelt Shakespeare-tier comments each day.

I do not know where this came from, but I suspect the authors just want you to comment on their posts while they sound smart for saying so.

In any case, commenting has never been a meaningfully attributable part of my growth (receiving comments has; I’ll cover that in a second). It’s bordering on superstition.

I guess it can be useful for building your first few thousand followers, but maxing out your connection requests is a more reliable vehicle for that (which you should be doing, yes).

I do recommend commenting on 3-6 creator peers in your niche each day for the sake of networking and maintaining relationships—but not for the sake of farming followers.

What is totally recommended is replying to commenting on your posts.

Starting out, you should reply to 100% of comments (outside of trolls; just block them), and then 50% of comments as it starts to become tedious.

I dearly wish I could respond to all of the comments on my posts, but it’s just not possible at this time. I’m very thankful for each and every comment, as you should be, too.

I don’t know if this has an effect on the reach of your posts (I suspect it does to a small degree), but it’s mostly important for fostering true fans and showing that you care.

As long as you respond to comments, people will keep showing up to comment in increasingly large numbers.

Over time, you’ll build what the industry calls “Reply Guys”—people who respond to your post as quickly as possible in hopes of being noticed by you, being noticed by your audience, or both.

While I don’t like how diminutive this term comes across (I don’t reduce anyone taking the time to thoughtfully respond to my content as a “reply guy”), this tier of fans showing up in your comments section shows you’re doing something right in terms of providing value, some way or another.

Comments also, algorithmically, are very important (at least at the time of this writing).

While LinkedIn has introduced a partial “For You” suggestion system (that may become much more prevalent in the future), the system for serving impressions is still mostly referral-based.

This means that impressions spread via your network commenting and liking them after the algorithm theorizes that you’ll be interested in them (nobody fully knows how this happens, so don’t ask or listen to anyone who says they do).

Speaking of which…

How does the LinkedIn algorithm work?

It doesn’t matter.

Just write for human psychology, and you won’t have to worry about it.

Like all other social algorithms (more or less), the LinkedIn algorithm is doing its best to represent the interests of viewers so that they spend more time on the platform.

It will get better at this over time, too, much to the dismay of people who rely on “algorithm hacks” to grow.

If you create valuable content, the algorithm will reward you. It may not happen overnight, but it’s a certainty on a long enough timeline.

Does this answer disappoint you? It shouldn’t because I’m saving your LinkedIn life with it.

People who build their audiences based on algorithm hacks ALWAYS ALWAYS ALWAYS have the rugs pulled from under their feet sooner or later when the platform—LinkedIn or wherever—adjusts the algorithm to better suit human psychology over gimmicks.

If you’ve ever seen one of those LinkedIn accounts with hundreds of thousands—or even millions—of followers that get barely two dozen likes per post, this is what happened to them (outside of the cases where people literally bought followers).

They built their audience based on selfies, “the homeless guy on the street I gave $10 to turned out to be the CEO I interviewed with,” and whatever yesteryear’s big “growth hack” was.

The same thing will happen to people currently posting today’s latest “growth hack”—Instagram visuals that will change your life, the top 10 Harvard AI TED Talks, etc.

People who have followed me for a while will know that I went through a 6-7 month phase where I did something similar to this.

It was a golden handcuffs situation because I received massive amounts of engagement while successfully creating leads (since my service is LinkedIn-related).

However, I eventually saw the light when I realized I was only creating empty engagements while burning/not creating true fans, thus endangering my long-term success.

I switched back to targeted content and, thankfully, still had a large audience for this, and I am continuing to grow.

Others aren’t so lucky—there are people out there who have permanently ruined their profiles with empty engagements, and the only realistic solution for fixing it is to reset their accounts.

This is why this post is about the principles I actively believe in rather than an actual play-by-play of my journey.

I don’t want you to replicate my journey; just take my advice now that I actively practice.

How do I make money with LinkedIn?

This is an extremely important topic, but I’m having to opt not to cover it in this newsletter as a standalone topic because I just have no room to do it sufficiently—it’s a topic for its own post.

However, I’ll give you a start.

The most reliable way to make money with your LinkedIn presence is to direct the attention you’ve created to a related service you offer.

This is why it’s so important to keep your content targeted and related to your expertise: you want to monetize it.

You can’t post pictures of your dog every day and turn around and start hocking a marketing course—even if you’re really good at it—because you don’t have an audience that recognizes your expertise in that field.

I create LinkedIn meta content because I run a LinkedIn-related agency.

If you run a cold email agency, you should be writing about cold emails.

Are you a fractional CMO? Write about marketing.

And if you want to build a sales training agency, for goodness sake, write about sales. 

Then, create some sort of funnel—either organic traffic to a landing page, organic traffic to the newsletter to a landing page, or some variation of that—to capture and convert it.

You can try to sell digital products on the side—like courses and cohorts—if you want, but I don’t recommend this for pretty much anyone as a primary income source except the largest of creators who have spent years building dedicated audiences (and even then, eh).

You can make good money with them, don’t get me wrong (I have, after all), but it’s heavily reliant on maximizing engagement and running very strategic launch campaigns, and your income will come in sporadic bursts with launches, rather than the sustainable, predictable, growing income services are capable of producing.

If I sold LinkedIn courses as a primary income source, I could make decent money with it, but with a much lower ceiling than my agency's infinite ceiling since organic traffic would be my only way of creating sales (besides ads). 

And it’d be much less predictable and sustainable, too. You can pop the champagne on a $100,000 product launch and make a chump change on the next.

Just look at what happened with people selling courses on Twitter—there are people who used to consistently make multiple six figures on courses there that are now job hunting thanks to the algorithm changes that have occurred there.

A lot of those people are refugees on LinkedIn now.

Is this a rule? Definitely not—just look at the consistently gargantuan income Nicolas Cole and Justin Welsh make on consumer-level educational products year after year.

But in my opinion, it’s something to aspire towards rather than immediately endeavor towards.

Both of those examples have audiences on multiple platforms—including extremely massive newsletters—anyway.

It's not realistic for 99% of people to replicate that model when there are much more straightforward monetization options available. I'd wager Nicolas and Justin would offer you the same advice.

The End

So yeah, that’s pretty much it. I just dropped an absolutely bonkers amount of value, and if you read it all the way to the end, you’re a champ. I don’t need to say much else.

Here are my asks, though:

You should subscribe if you haven’t already done so.

If you want to chat 1:1, go ahead and book a coaching call.

Finally, if you’re a B2B founder who wants to create qualified leads through visibility on LinkedIn, let’s talk about contracting my services.

That’s all I’ve got—see you next time.