2026-09-19 00:52:30
Friends,
Dave Thomas had a confession to make: He was just fourteen.
Two years earlier, Thomas had come to Regas Restaurant in Knoxville, Tennessee, asking for a job at the counter. He’d told the owner he was sixteen. He was, in fact, twelve.
Money hadn’t been the only thing that motivated Thomas, though it mattered. Thomas harbored dreams of owning a restaurant of his own one day.
Working at Regas had not been easy, especially as a child. It stayed open 24 hours a day, and as an entry-level employee, Thomas was often given the overnight shift. At two in the morning, he’d find himself making hundreds of egg, ham, and tuna sandwiches for the day ahead. It got harder after the family moved to Oak Ridge, which added a bus commute to Thomas’s schedule. He eventually persuaded his parents to let him rent a room near the restaurant to cut down his commute, paying the $7 weekly rent from his own wages. He did all this while attending school, working at the Regas on weekends and during summer breaks.
That schedule had worn on him. “I was physically tired,” Thomas recalled, “but most of all I was tired of having lied to the people at the Regas who had done so much to give me a chance.”
So one night, exhausted, he broke down and told the truth, informing his manager of his real age. Gene surprised him with his response: they’d always suspected as much. “But you had such determination,” he added. “We just decided to let it go.”
Thomas would achieve his dream. On November 15, 1969, he opened the first Wendy’s restaurant, naming it after his young daughter. Today, Wendy’s is one of the world’s largest restaurant chains, with thousands of locations across 30 countries.
At first glance, Thomas’s confession is a classic founder’s tale. Here is the striving outsider, the child with holes in his shoes, working his way to the top and enduring pain others will not. It tells us something about Thomas in this way, showing us who he was as a child. More was expected of him, and he expected more of himself.
But there is something else to it, too. It reveals something about Thomas, yes, but about the world, as well. How feeble its rules can be, how hackable the system is if it finds something it needs or wants.
In the first two parts of Saplings, we focused on the ways in which life happened to legendary future founders. How did their surroundings cast them as outsiders? What impact did their family dynamic have on their ambition?
In Part III, the final part of our series, we will switch the focus, studying what came after. In particular, we will examine the patterns of how future entrepreneurs engage with the world around them, assessing how they acquire new information, take their first steps in the commercial world, clash with authority, and invent an adult identity.
Self-directed learners. When the world does not provide the desired education, the founder creates it for themselves.
Early to business. Ambition or circumstance pushes founders into the working world early, exposing them to industry and new responsibilities.
Skeptical of authority. School teachers, bosses, and the rules they impose are questioned and flouted as founders take risks and test the resilience of the systems around them.
Self-inventors. Founders see their capabilities and even their histories as malleable, evolving to meet circumstances.
As you will know by now, Saplings does not purport to explain everything about the individuals featured, or imagine that its observations are necessary to achieve entrepreneurial greatness. It does not attempt to make statistical observations or generalize across these populations. Rather, it is an accounting of the common patterns I find most meaningful, accompanied by my interpretation of them. Across the series, the goal is to study the formative years of extraordinary figures so as to better understand them, knowing that full understanding is not possible.
You can find Part I: Outsiders here, Part II: Unstable Ground here, and a discussion of our methodology here.
Some founders, like Colin Huang of Pinduoduo or Stripe’s Patrick Collison, excelled in academic environments. Others, like Richard Branson of Virgin or Fanatics’ Michael Rubin, struggled with traditional schooling. “I haven’t read a book since ninth grade,” Rubin confessed. “You send me three paragraphs. I’m tuned out before I start.”
Though we can make no statistical claims, anecdotal evidence does seem to cluster around the extremes. There are the super-achievers on one side and scholastic catastrophes on the other. It’s genuinely surprising to see how many founders were not simply middling students, but disastrous ones.
On the mathematics portion of the gaokao, for instance, China’s intense university entrance exam, Jack Ma scored 1 out of 120. The second time he took it, he improved markedly but still failed, logging an abysmal 19 out of 120. He passed on the third attempt, finally gaining acceptance to college.
Akio Morita, the future founder of Sony, ranked 180th in a class of 250 students as a middle-schooler. Only after a year of study with private tutors was he accepted to the science department of a prestigious high school. He was reportedly the “lowest-ranking graduate” ever to make that leap.
There is no one type of mind, or single sort of student, that predicts an exceptional entrepreneur.
There is, however, a pattern across these and other archetypes: self-directed learning. Whether their ambient environment supplies the right intellectual influences or not, founders go out and build the curriculum they want for themselves. They may do so unconsciously, and often it will look like play.
As a boy in Houston, Howard Hughes built a wireless radio set from old doorbell parts and other scraps. When he was refused a motorcycle, he decided to build one himself, strapping a car motor to his bicycle. Little stood between Hughes and his desire to learn and build.
A four-year-old Vitalik Buterin’s favorite toy was already the computer. His father recalled a young Vitalik spending his afternoon experimenting with shapes and colors in Microsoft Paint and plugging different formulas into Excel.
2026-09-08 20:02:32
"No ego is extremely important to make the best decisions possible. That is another thing I saw in Elon – he would be extremely passionate, but then presented with new information, he'd be like, well, okay, that was a quick switch." – Scott Morton, Founder and CEO, Revel
Listen or watch now on
YouTube, Spotify, or Apple Podcasts
Scott Morton is the founder and CEO of Revel, a software platform for testing and controlling complex hardware systems. Before founding the company in 2024, Scott spent nearly a decade at SpaceX building control software for Falcon 9 and Starship. That experience helped him recognize a broader problem: while rockets, nuclear systems, supersonic aircraft, and other advanced machines have grown increasingly sophisticated, the software used to test and control them is often fragmented and decades old. Revel was created to close that gap. The company has raised $180 million, was reportedly valued at just over $1 billion, and counts Impulse Space and Radiant Nuclear among its customers. Its platform scales from small benchtop tests to industrial systems with hundreds of thousands of telemetry channels. Revel has also created its own programming language, RevelCode, designed to combine performance and accessibility with the runtime safety required for high-stakes physical systems.
In our conversation, we explore:
How AI can accelerate high-consequence software teams without replacing rigorous testing and review
Why hardware test and industrial-control software still relies on tools created in the 1980s and 1990s
What Scott took from Elon Musk about betting on teams before you know the answers
Why Revel created its own programming language
The “runtime safe” philosophy: what it means and why it matters
Revel’s one-to-many model and the hardware frontiers it’s touching
The strategic case behind Revel’s $150 million Series B
How Revel’s edge showed up in an industrial-control bake-off
How Scott hopes to preserve Revel’s engineering culture as it scales toward 500 people
Revel’s long-term mission – and what it means for the hardware renaissance
(00:00) Intro
(02:04) Why no one will vibe-code a nuclear reactor
(04:15) Revel’s engineering edge
(05:27) What Revel actually does
(06:34) Why industrial software has stagnated
(07:52) Why previous startups couldn’t crack it
(10:26) The limits of building control software in-house at SpaceX
(15:20) Lessons from nearly a decade at SpaceX
(20:22) Why Revel built RevelCode
(24:46) Will Revel open-source the language?
(25:25) Scott’s early projects and builder mentality
(32:28) Where his drive comes from
(33:50) What Scott took from Elon – and what he chose to leave behind
(36:02) Scott’s standards as CEO
(38:56) Scaling from small tests to industrial systems
(43:40) Deploying Revel and the hiring bottleneck
(45:23) How Revel finds and assesses talent
(46:21) Emerging frontiers in hardware
(49:36) Revel’s unusually smooth trajectory
(51:05) How AI fits into Revel’s platform
(52:42) Revel’s long-term vision
(54:18) Final meditations
LinkedIn: https://www.linkedin.com/in/scott-morton-68334a15
Our Mathematical Universe: My Quest for the Ultimate Nature of Reality: https://www.amazon.com/Our-Mathematical-Universe-Ultimate-Reality/dp/0307744256
Elon Musk on X: https://x.com/elonmusk
Jess Winssinger on LinkedIn: https://www.linkedin.com/in/jwinssinger
Revel: https://www.revel.io
SpaceX: https://www.spacex.com
Palantir: https://www.palantir.com
Anduril: https://www.anduril.com
Starship: https://www.spacex.com/vehicles/starship
The Hedgehog and the Fox: https://en.wikipedia.org/wiki/The_Hedgehog_and_the_Fox
Impulse Space: https://www.impulsespace.com
Star Trek: The Next Generation: https://www.imdb.com/title/tt0092455
I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.
Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
2026-08-18 20:05:09
“Money, quantifiable, is larger than AI, it's larger than food, it's larger than oil and gas, it's larger than municipal water supplies. It's larger than government spending. It's larger than defense. It's all of these combined.” —Farooq Malik, CEO of Rain
Listen or watch now on
YouTube, Spotify, or Apple Podcasts
Farooq Malik is the co-founder and CEO of Rain, a financial infrastructure company powered by stablecoins. Growing up in an immigrant family, Farooq saw firsthand the friction involved in moving money across borders. Alongside co-founder Charles Yoo-Naut, Farooq spent years building infrastructure before stablecoins became mainstream, betting that tokenized money would eventually become a foundational layer of the global financial system. Today, Rain powers card issuance, payments, and other financial products built on stablecoin rails, helping companies move money faster and operate across markets.
In our conversation, we explore:
How stablecoins combine the advantages of cash and electronic money
The barriers that still make moving money across borders expensive and inefficient
The parallels between being an immigrant and being an entrepreneur
How Farooq and Charles met through On Deck and decided to build together
What Rain gained by building before the market was ready
How Rain earned the trust of early partners who later became customers
What The Art of War taught Farooq about patience
The misconception that stablecoins are only for emerging markets
Why the payments market is big enough for multiple winners
Why he believes Rain’s infrastructure is well positioned for a future shaped by AI agents
Brex: The intelligent finance platform.
(00:00) Intro
(02:46) An overview of Rain and global-first financial infrastructure
(06:57) The barriers to moving money and how technology can reduce them
(15:34) How stablecoins behave like cash
(18:46) The economic opportunity of a more efficient monetary system
(22:06) How Farooq’s childhood as an immigrant shaped him
(26:00) Farooq’s first entrepreneurial venture
(29:11) Lessons from Farooq’s career before founding Rain
(36:09) Connecting with Charles through On Deck
(39:51) From Sign and Wire to Rain
(42:18) Why Rain bet on stablecoins
(47:25) How a Rain card works
(49:15) How Rain thinks about its business
(51:12) Lessons from The Art of War
(54:30) Rain’s approach to hiring and management
(55:47) Why the US is a stablecoin hub
(59:10) Why there’s room for more than Stripe
(1:03:39) How Farooq and Charles stay aligned with limited meetings
(1:05:54) Rain’s most critical mantras
(1:08:56) Why Rain is ready for AI agents
(1:12:30) Final meditations
LinkedIn: https://www.linkedin.com/in/fhmalik
Website: https://fhmalik.com
The Art of War: https://www.amazon.com/dp/1599869772
Pierre Omidyar on LinkedIn: https://www.linkedin.com/in/pierre-omidyar-bb10687b
Charles Yoo-Naut on LinkedIn: https://www.linkedin.com/in/charlesnaut
Rain: https://www.rain.xyz
Revolut: https://www.revolut.com
Rise: https://www.riseworks.io
Airwallex: https://www.airwallex.com
Stripe: https://stripe.com
“Margaritaville”: https://southpark.cc.com/episodes/9do3gw/south-park-margaritaville-season-13-ep-3
Wired: https://www.wired.com
On Deck Founder Fellowship: https://joinodf.com
Lehman Brothers: https://en.wikipedia.org/wiki/Lehman_Brothers
Booz Allen: https://www.boozallen.com
Sign and Wire: https://www.signandwire.com
Bridge: https://www.bridge.xyz
Universal Basic Income (UBI): https://en.wikipedia.org/wiki/Universal_basic_income
I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.
Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
2026-08-14 00:21:22
José Ferrera wanted his money. A week earlier, the farmhand had labored in the orchards of Luigi Giannini, picking fruit. Though he’d received some payment, he’d been stiffed by a dollar. Or, at least that was his story.
On August 14, 1876, he traveled back to the Giannini farm with a shotgun in hand. Perhaps Ferrera had only wanted to scare Luigi, but as their voices rose near the Giannini family home, he raised the barrel and killed the man.
A few paces away stood a six-year-old Amadeo Giannini. As Ferrera fled, the boy rushed to his father’s side. There was nothing he could do.
The evening of Luigi’s funeral, after the house had emptied, Amadeo’s mother, Virginia, held her son and explained that the world, and his place in it, had changed. “This is the last time I take you on my knees. From today, you are the man of the house.”
It was in such circumstances, freighted with responsibility, attuned to mortality, that Amadeo grew up, eventually becoming one of the most important entrepreneurs of his era. In 1904, he founded the institution that would become Bank of America.
Not all great entrepreneurs endure such tragedy in early life. But a large number of those studied were born or raised amidst real instability, real turmoil, whether that meant the death of a parent or sibling, sudden shifts in material fortune, or frayed familial dynamics. From a young age, these children learned that life could be fickle and cruel, that one’s hand could change suddenly, and, perhaps, that the remedy was to happen to life rather than allow it to happen to you. In Part II of Saplings, our study of the early lives of legendary founders, we focus on the home, and the inherited stresses that recur most frequently.
Early loss. Many entrepreneurs become acquainted with death early, losing parents or siblings. This shortens their childhood, disrupts the family dynamic, and produces a deep sense of mortality.
Disappointing fathers, dynamic mothers. When entrepreneurs were raised with two parents, often one has a much greater influence. A relatively common pattern is for the father to disappoint, while the mother provides support and drive.
Earned love. The withholding of approval from a parent is common. In some instances, a parent does not merely withhold affection, but actively doubts their child’s worth or ability. In either variation, this seems to produce a strong desire in the child to over-prove their ability or worth to compensate.
Status in motion. Rather than entrepreneurs clustering in certain economic classes, the dominant pattern is change. Founders often lived through shifting fortunes, viscerally experiencing the mobility of status.
Imposed mythologies. Often, entrepreneurs are burdened with a family’s expectations. They are tasked with redeeming past failures, restoring a lineage, or justifying the sacrifices of parents and siblings. From an early age, identity and destiny is thrust upon them.
Though noted in previous editions of this series, Saplings does not purport to explain everything about the individuals featured, or imagine that its observations are necessary to achieve entrepreneurial greatness. It does not attempt to make statistical observations or generalize across these populations. Rather, it is an accounting of the common patterns I find most meaningful, accompanied by my interpretation of them. Across the series, the goal is to study the formative years of extraordinary figures so as to better understand them, knowing that full understanding is not possible.
You can find Part I: Outsiders here, and a discussion of our methodology here.
Across the sample population, death visits with such regularity that you are forced to remind yourself: these were different times. Many of the founders studied were born before the 20th century or in less stable geographies. To lose a sibling in 1850s New York or a parent during China’s Great Famine was simply much more common than it would be in the San Francisco of the 1990s. It may not have made a child feel quite as different from their peers perhaps or quite as alone. But there is no reason to imagine it would have hurt less. Their home life was still changed irreparably, perhaps more so than in modern contexts.
Even adjusting for the different risks of other eras and locations, it is striking how many of these entrepreneurs lost a parent early. Stan Shih (Acer), Amadeo Giannini (Bank of America), Larry Hillblom (DHL), George Eastman (Kodak), Fred Smith (FedEx), Jerry Yang (Yahoo), Carlos Slim (América Móvil), Jorge Paulo Lemann (3G Capital), Aristotle Onassis (Olympic Maritime), Harland David Sanders (KFC), James Dyson, Lorenzo Zambrano (CEMEX), Jim Casey (UPS), Li Ka-Shing (CK Hutchison), Frank Lowy (Westfield), Alfred Krupp all lost parents in childhood or adolescence. Konosuke Matsushita (Panasonic), Howard Hughes, Wang Chuanfu (BYD), Coco Chanel, and Leonardo Del Vecchio (Luxottica) were literally or functionally orphaned. Many more lost a parent in early adulthood.
This is to say nothing of the siblings lost. John Rockefeller, Enzo Ferrari, Milton Hershey, and others all lived through the death of a brother or sister.
Larry Ellison experienced a stranger kind of destabilization. Over dinner one night, when Ellison was around twelve years old, his parents shared a piece of trivia: he was adopted. “That was it. They didn’t give me any details,” Ellison reported later. “It was like ‘Tonight we’re having meat loaf, and, by the way, you’re adopted.’” Ellison did not contend with the death of a parent, but in an instant, the narrative of life that stood beneath his feet was ripped away.
As with Amadeo Giannini, for many founders, the death of a parent results in inheriting the deceased’s responsibilities. Jorge Paul Lemann was fourteen when his father was struck down by a streetcar. Immediately, he is described as becoming the “man of the house.”
Li Ka-Shing, founder of the conglomerate CK Hutchison, was given similar instructions. As his destitute father lay dying of tuberculosis, he told his fifteen-year-old son that “a man must have ambitions.” With tears running down his cheeks, Li made a promise: “Father, don’t worry. I will learn to do business and make lots of money.” Within three years, young Li had gone from sweeping factory floors to a star salesman, bringing in more money than his family needed.
In such instances, it’s evident that the parental death serves as the beginning of a quasi-adulthood, carrying with it greater expectations and ambition. It pushes the bereaved child to enter the wider world earlier and to rely on themselves.
It may also create a certain obsession with mortality. Ted Turner, founder of CNN, was tormented by his father in life (discussed in Part I) and death. When Ted was twenty-four years old, his father agreed to sell a chunk of his business, then committed suicide the next day. It was up to the younger Turner to undo the sale and right the ship.
Even as Ted Turner outstripped his father commercially, he remained fixated on his demise. “He talks about death incessantly,” a friend of Turner’s remarked. “Over the years, killing himself was a high-priority topic of conversation. Most of the time he was flippant about it. He would talk in this joking way about how, if things did not work out, he could always sell the business, how all he needed was a roof over his head and some food. Then he would say, ‘If things get really bad, I can always kill myself.’ He could not go several days without talking about suicide.”
If there is an upside to an obsession with mortality, it may be that it creates internal urgency. If you understand, deeply understand, that life can end at any moment, you may be more predisposed to make the most of one’s own. To take greater risks, to drive a little harder, to push to leave something tangible behind.
2026-08-04 20:03:37
“The potential to create or manipulate life with AI could reinvent nearly all of biology, but it also carries inherent risk. We’ve seen just a taste of this on the natural-language and chatbot side. Giving AI the power to generate and create life carries a certain level of responsibility.”
— Eric Nguyen, Co-founder and CEO, Radical Numerics
Listen or watch now on
YouTube, Spotify, or Apple Podcasts
Eric Nguyen is the co-founder and CEO of Radical Numerics, an AI research lab that has raised $50 million to train models directly on biological data. Before starting the company, Eric helped develop Evo and Evo 2, large-scale genome language models trained on unlabeled DNA sequences. Radical Numerics is now building models that can connect information across DNA, RNA, proteins, epigenetics, and other parts of biology, rather than treating each as a separate problem. Researchers have already used Evo to generate viable bacteriophage genomes, and Eric says Radical Numerics’ newer model, Omnii, matched key findings from two years of Alzheimer’s wet-lab research in a matter of days. He also believes these tools could make it easier to create dangerous pathogens, which is why the company is working on both biological design and biodefense.
In our conversation, we explore:
What AI models can learn by treating DNA as a language
Why reading scientific papers is not the same as learning directly from biological data
How Eric’s unusually free-range childhood shaped the way he follows his curiosity
Why biology may have more useful data than researchers know how to use
How Radical Numerics plans to connect information across DNA, RNA, proteins, and other biological systems
Where the company sees early opportunities in drug discovery, diagnostics, synthetic biology, and biodefense
Why testing AI-generated biology in the lab is still slow and difficult
How models that design biological systems could also help detect dangerous or manipulated pathogens
How to make powerful biology models safer without eliminating the capabilities that make them valuable
Ahrefs Brand Radar: Find your brand in AI results.
Brex: The intelligent finance platform.
Guru: The AI source of truth for work.
(00:00) Intro
(03:35) An overview of Radical Numerics
(06:35) From protein models to modeling all of biology
(11:08) Why they started with DNA
(15:04) The process of mapping DNA as a language
(19:47) What’s unknown, and how we learn from novelty
(26:24) The limits of language models in biology
(31:15) Eric’s free-range upbringing and path to his PhD program
(41:20) Applying long-context models to DNA and meeting his co-founders
(46:36) Biology’s untapped data opportunity
(49:02) Why biology needs multimodal AI
(55:30) How better general LLMs benefit Radical Numerics
(57:19) The challenges of biological verification
(1:02:05) Making biology more concrete
(1:04:51) Radical Numerics’ strategy and early use cases
(1:07:26) Balancing safety with capable AI models
(1:15:47) What success in biodefense looks like
(1:18:09) Final meditations
LinkedIn: https://www.linkedin.com/in/nguyenstanford
Website: https://erictnguyen.com
Biohazard: The Chilling True Story of the Largest Covert Biological Weapons Program in the World--Told from Inside by the Man Who Ran It: https://www.amazon.com/dp/0385334966
Blitzed: Drugs in the Third Reich: https://www.amazon.com/Blitzed-Norman-Ohler/dp/1328915344
Greg Brockman on LinkedIn: https://www.linkedin.com/in/thegdb
Eric Horvitz on LinkedIn: https://www.linkedin.com/in/erichorvitz
Radical Numerics: https://www.radicalnumerics.ai
Genome modelling and design across all domains of life with Evo 2: https://www.nature.com/articles/s41586-026-10176-5
AlphaFold Protein Structure Database: https://alphafold.ebi.ac.uk
A new frontier in generative genomics with Omnii: https://www.radicalnumerics.ai/blog/omnii-health-preview
On the Red Circle: What it’s really like to give a TED talk: https://erictnguyen.substack.com/p/on-the-red-circle-what-its-really
I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.
Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
2026-07-11 02:09:57
Welcome to another edition of Generalist Intelligence, the weekly intelligence briefing that delivers situational awareness in 20 minutes or less. To unlock the full briefing, join as a member.
This week, we examine surging memory prices, Meituan’s US-chip-free breakthrough, and a surprising data center bottleneck.
— Mario
“There is only one proved method of assisting the advancement of pure science — that of picking men of genius, backing them heavily, and leaving them to direct themselves.”
— James Bryant Conant, the chemist who ran America's wartime science, writing to the New York Times in August 1945
How much?!
Samsung is pushing for another memory price increase of up to 20% for next quarter, on top of around 90% in Q1 of 2026, and 50-60% in Q2. That’s three consecutive quarters of major price hikes for DRAM, the type of memory chip that go into everything from your phone to AI servers, driven by data centers buying up nearly all available supply. For the first time in years, memory makers like Samsung, SK Hynix, and Micron hold real pricing power, which will show up in their margins and, eventually, in the price of every laptop, phone, and car you buy. For AI infrastructure, it’s a growing tax on anyone trying to build or scale compute that isn’t a hyperscaler with the leverage to lock in supply years in advance.