<![CDATA[The Generalist]]>https://www.generalist.comhttps://substackcdn.com/image/fetch/$s_!hCZr!,w_256,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2dfe63cd-67ea-49ba-92df-930520a822a0_500x500.pngThe Generalisthttps://www.generalist.comSubstackSat, 18 Apr 2026 12:27:31 GMT<![CDATA[How a 20-Person Startup Won Gold at the Math Olympiad—Tying With OpenAI & DeepMind (Tudor Achim, CEO of Harmonic)]]>https://www.generalist.com/p/how-a-20-person-startup-won-goldhttps://www.generalist.com/p/how-a-20-person-startup-won-goldTue, 14 Apr 2026 12:03:42 GMT

"Within 2 or 3 years, AI mathematicians will surpass human mathematicians for any specific mathematical task. I don't think it'll be a decade, like some people say." — Tudor Achim, CEO of Harmonic

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Tudor Achim is the co-founder and CEO of Harmonic, a startup working to solve one of AI’s hardest problems: mathematical reasoning. In July 2024, Harmonic achieved gold-medal-level performance on International Math Olympiad problems alongside systems from OpenAI and Google DeepMind—but with a key difference: every proof Harmonic submitted was formally verified. Tudor's path to Harmonic wound through competitive piano, computational biology, and autonomous driving. He studied at Carnegie Mellon's music preparatory school, worked on machine learning at Quora, briefly pursued a PhD before dropping out, and then co-founded an autonomous driving company, Helm.ai. Harmonic's core product, Aristotle, uses reinforcement learning and the programming language Lean 4 to solve problems and verify solutions.

In our conversation, we explore:

  • Why Tudor believes math is the fundamental toolkit to understand the world

  • How Harmonic uses hallucinations as a feature, not a bug

  • How Aristotle works and the applications beyond pure mathematics

  • The reinforcement learning process that lets Harmonic generate synthetic training data and solve problems humans have never attempted

  • Why Tudor believes AI could surpass human mathematicians on specific tasks within 2–3 years

  • Why the future of mathematics looks more like GitHub than academic journals

  • The alternating pattern between intellect leaps and data leaps throughout scientific history

  • How studying piano under an extraordinary teacher taught Tudor discipline and the value of sticking with hard problems

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Timestamps

(00:00) Intro

(03:34) From competitive piano to computer science

(06:28) The mathematical foundations of music (and why Tudor keeps them separate)

(08:24) Can AI ever create art with true intent?

(09:51) Early obsessions

(12:52) Defining intelligence

(14:49) Discovering machine learning’s potential at Quora

(17:30) Why Tudor chose computational biology for his PhD

(19:19) The decision to drop out and build Helm.ai

(22:55) The two breakthroughs that made mathematical AI possible in 2023

(25:28) The importance of Lean 4

(28:21) How Tudor and Vlad Tenev discovered they shared the same impossible dream

(32:35) Why formal verification became the core conviction

(34:21) The timeline for AI surpassing human mathematicians

(35:25) An overview of Aristotle: the world’s first always-correct mathematical agent

(38:12) Why Tudor says hallucinations are the engine of creativity

(39:30) The translation challenge from natural language to formal proof

(40:40) Reinforcement learning

(42:10) Why Aristotle is both faster and cheaper than alternatives

(43:34) Tradeoffs and use cases

(45:34) Math in AI now and what’s next

(47:38) Tying with OpenAI and DeepMind at the International Math Olympiad

(49:08) Democratizing AI and correctness

(53:13) Tudor’s 2030 thesis

(56:02) History’s alternating rhythm of thinking and measuring

(57:53) What Tudor has been wrong about

(58:52) What Tudor’s best at

(1:00:18) Final meditations

Follow Tudor Achim

LinkedIn: https://www.linkedin.com/in/tudorachim

X: https://x.com/tachim/with_replies

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]]><![CDATA[The Secret Art of Elicitation]]>https://www.generalist.com/p/confidentialhttps://www.generalist.com/p/confidentialFri, 10 Apr 2026 13:27:57 GMT

Friends,

You didn’t mind speaking with Hanns Scharff. No, it was better than that — you liked it. He spoke English well, for one thing, the product of years spent in South Africa and a wife from London. But that didn’t fully explain it either. He spoke softly (unlike the others), was good for a joke or a story, and when he directed his dark, thoughtful eyes in your direction, you didn’t feel fearful, but at ease.

You could almost forget that he was the Luftwaffe’s most effective interrogator. And you, his prisoner.

While the Nazi Party’s other torturers and wheedlers relied on threats and violence, Scharff found success with a more genteel approach, taking downed pilots on long walks in the Taunus hills northwest of Frankfurt, during which he seemed to avoid discussing military matters. Only later, in some cases much later, would prisoners realize what had happened.

One American pilot recalled such a stroll. Only after he and Scharff had wandered and chatted for a while did the German mention, almost in passing, that a chemical shortage seemed to have impacted American munitions: their tracer bullets now trailed white smoke rather than their usual red.

No, no, the American told him. That wasn’t caused by a chemical shortage; it was a matter of design. American tracer bullets shifted from red to white when a pilot was running low on ammunition. It was a kind of warning system.

There it was. By purposefully saying the wrong thing, Scharff prompted the pilot to correct him, all without asking a question. A pocket had been picked without the wallet’s owner even registering a rustle. The pilot would not realize what had happened until it was much too late.

This technique, and others like it, are the topic of Confidential by John Nolan, a 1999 book that is as fascinating as it is difficult to obtain. Though prized by intelligence officials and professional “elicitors,” Confidential is no longer in print and only available to buy second-hand. To grab my copy, I spent a few hundred dollars on eBay and waited weeks for it to arrive. All of which only adds to its strange allure, as if someone decided Nolan’s work was too useful to simply leave lying around.

Confidential is a wildly entertaining and impressively insightful book. In studying it closely these last few months, I’ve also come to believe it’s an important one. Though Nolan is ostensibly writing for the professional intelligence gatherer, his conversational techniques are useful to anyone, in any context. They are liable to make you more engaging and persuasive, as well as a better conversationalist.

It is also worth knowing when someone else is using them. Why did that salesperson seem to purposefully misspeak? Was I imagining it, or did that headhunter seem to disbelieve everything I said? What is it about this person that makes me want to open up so much? For founders working in sectors of national interest, Confidential will help you protect what you know. If you are building almost anything of note, there is a good chance that someone out there — whether in a bland concrete building, a glassy office tower, or a grassy tech campus — would love to understand it better than you’d like them to.

This is the second piece in an occasional series about books that change how you see everyday interactions. The first, on Keith Johnstone’s Impro, explored the invisible power dynamics in every conversation. Confidential picks up the other side of that coin: how information actually moves between people, and what a former spy figured out about making it move faster.

If you’d like to read more work like this — pieces that dig into overlooked ideas and the people behind them — a premium membership is $22/month or $220/year. Subscribe now.

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Lessons from Confidential

Like a character in Atlas Shrugged, the natural question when beginning Confidential is, “Who is John Nolan?”

The first thing to say is that this is the name you would want for a spy — a vaguely heroic sound being stirred into a bowl of porridge.

There are, fittingly, few details online, so we must rely on Nolan’s own telling. For twenty-two years, he worked as a spy. From the sparse available details, it seems Nolan spent time in some of the intelligence community’s more controversial programs, a background that lends Confidential both its authority and occasional chill.

After his time working for the government, Nolan founded a corporate espionage consultancy that advised business clients and gathered intel on their behalf. (One of the only articles I can find that mentions Nolan outside of Confidential covers an espionage campaign conducted by P&G against Unilever in 2000 to obtain the “secrets of shampoo.” Nolan’s firm was ostensibly the orchestrator.)

As part of his work, Nolan’s team relied on the psychological tools he outlines to extract sensitive information — all while being perfectly explicit about who they were. Beyond his team, Nolan also trained executives to use his techniques and protect themselves against him.

Nolan’s own “call to adventure” is a memorable starting point for the book. In 1960s New Jersey, Nolan started work as a typewriter salesman for a small local outfit, competing with a rep from IBM. Despite offering a superior product, Nolan struggled to shift them. While he flailed around trying to convince companies to have him in for an appointment, his rival was having companies call him - everyone knew that if you needed a typewriter, you went to “Big Blue.”

Sitting in a coffee shop one day, Nolan watched as the IBM salesman loaded typewriters into his station wagon. “In a brief moment of clarity,” Nolan came to a realization. Why bother to hunt and scrabble for customers when he could simply follow his rival and figure out who was in the market for typewriters?

For the rest of the day, he tailed the station wagon, watching it go from office to office. The next morning, he set out and visited every company, one after another, showcasing what his product could do. That week, he sold twelve typewriters.

Over the following months, he repeated the trick, shadowing the IBM rep a few days each week. He grew cocky enough to wait outside an office building and follow him an hour later. Without meaning to, Nolan stumbled into the world of intelligence gathering and had seen what it could yield.

This is the first of Nolan’s rollicking stories, but it would be wrong to classify this as a collection of yarns. Across Confidential’s 350 pages, Nolan outlines techniques of striking psychological acuity, interleaved with lessons from the history of espionage, and detailed examples. On a given page, you’re just as likely to learn about the subterfuges Johnson & Johnson deployed to defend the Tylenol market as to analyze the brilliant sinuousness of Sherlock Holmes’s questioning style.

For this piece, we’ll focus mainly on Part I: “Eliciting the Information You Want and Need.” Though the latter two parts offer interesting details, they primarily address how organizations can collect intelligence more effectively or protect against spies.

As the title of Part I suggests, it covers the art of “elicitation.”

Even if you are familiar with this word, its place in the Nolan lexicon is particular and benefits from definition. When the author writes about elicitation techniques, he explicitly means the following:

Elicitation…is defined as that process which avoids direct questions and employs a conversational style to help reduce concerns and suspicions—both during the contact and in the days and weeks to follow—in the interest of maximizing the flow of information.

As Nolan explains, elicitation is expressly distinct from interrogation and interviewing. “Interrogation [is] obtaining what you want from someone who possibly has it, who has not admitted to having it, and who knows who you are and why you want it,” he writes. Meanwhile, “interviewing is the process of obtaining information from someone who probably has it, who has more or less admitted to having it, and who knows who you are and why you want it.” Interrogation is, by definition, adversarial, while interviewing tends not to be.

As you’ll see, elicitation is a subtler dance.

The worst way to get an answer might be a question

Read more

]]><![CDATA[30% Of Network Engineers Are Retiring. What Happens Next? (Anil Varanasi, Co-Founder & CEO of Meter)]]>https://www.generalist.com/p/the-case-for-autonomous-networkshttps://www.generalist.com/p/the-case-for-autonomous-networksTue, 07 Apr 2026 12:04:26 GMT

“I don't think Silicon Valley knows anything about networking anymore.” — Anil Varanasi

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Anil Varanasi, co-founder and CEO of Meter, is building a new kind of networking company for the AI era. Alongside his brother Sunil, he has helped raise more than $250 million to challenge incumbents like Cisco with a vertically integrated approach spanning hardware, software, deployment, and ongoing operations, all delivered through a utility-style model. His view is that networking has remained largely unchanged for decades, even as it has become foundational to everything from AI workloads to real-world infrastructure. Meter’s ambition is not just to improve existing networks, but to make them autonomous over time. Before starting the company, Anil and Sunil were deeply involved in filmmaking, a background that still shapes their philosophy of building with cathedral-level craft across every layer of the stack.

Together we explore:

  • The “burden of knowledge” and why progress is getting harder across fields

  • Why most companies over-index on technology and ignore business model innovation

  • The three ways companies create advantage: technology, delivery, and business model

  • How Meter’s trade-in model borrows from the automotive industry

  • Why networking should function like electricity or water—not hardware

  • Lessons from Japanese vending machine logistics for infrastructure deployment

  • The hidden coordination problem behind vertically integrated companies

  • Why Anil believes “common knowledge” is often wrong

  • How COVID forced Meter to abandon geographic constraints and scale nationally

  • The case for fully autonomous networks in a world of exploding demand

Thank you to the partners who make this possible

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Timestamps

(00:00) Introduction to Anil Varanasi and Meter

(03:52) The burden of knowledge and slowing innovation

(08:18) Losing creativity vs gaining expertise

(10:25) What Meter actually does

(13:26) Early life, immigration, and upbringing

(15:47) Parental influence

(20:03) Film, storytelling, and creative influence

(22:55) Why Anil didn’t pursue filmmaking

(25:44) Parallels between company building and filmmaking

(27:00) Early programming and building

(28:05) George Mason and understanding systems

(29:59) The dynamic of working with his brother as a co-founder

(34:03) His first business and lessons learned (or lack thereof)

(35:15) Lessons from successful companies

(38:16) Japanese vending machines and logistics insight

(41:10) Scrapping 18 months of work

(42:40) Conviction and long-term company building

(46:02) COVID shock and near-death moment

(49:59) Building hardware like a cathedral

(52:25) Rethinking the networking business model

(57:06) Build vs buy and transaction costs

(59:39) Networking as infrastructure and utility

(01:01:30) The case for autonomous networks

(01:03:25) Hiring, talent, and what actually matters

(01:06:15) Big unanswered questions (sleep, science)

(01:07:28) Rethinking education

(01:09:02) Infinite games and long-term thinking

Follow Anil Varanasi

LinkedIn: https://www.linkedin.com/in/anilcv

X: https://x.com/acv

Website: https://anilv.com

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[The Satya Nadella Playbook]]>https://www.generalist.com/p/satya-nadellahttps://www.generalist.com/p/satya-nadellaThu, 26 Mar 2026 14:47:36 GMT
Illustration by Tyler Comrie

Friends,

If Silicon Valley has any religion, it is that of the founder. Nowhere else puts as much faith in, nor grants as much latitude to, sovereign individuals attempting to build something from scratch. Only within this strip of approximately 35 miles might a broke 20-year-old in pajama pants and Adidas sliders command greater reverence than a celebrated researcher, diligent doctor, or decent executive. This is the strangeness of Silicon Valley and its genius.

The cult of the founder has enjoyed a fresh, febrile burst. Now, more than anytime in the last decade, operating in “founder mode” — the term popularized by Paul Graham’s post — is seen as synonymous with efficacy. Managers (that wretched, blighted species) are viewed not only as less productive but less legitimate, usurpers and meddlers that merely disrupt the glowing chi that stems from the central chakra of those who build.

Look across the tech landscape, however, and there is one manager that bears closer inspection: Satya Nadella. Since his appointment as Microsoft CEO in 2014, few executives boast a more impressive record. Given Microsoft’s current strengths, it is easy to forget the company Nadella inherited. Unlike Tim Cook, who stepped into an innovative organization still in the early innings of capitalizing on a new product category, Nadella stepped into a company that was culturally rotten, creatively blocked, and stuck with a sideways stock price. It is true that Ballmer had sown the seeds for a cloud computing renaissance, as we’ll discuss, but this was far from the finished article.

In the intervening 12 years, Nadella not only drove the company to a $3 trillion market cap but also oversaw an authentic internal revolution, expanded its product suite, and positioned Microsoft to keep pace in the AI era. He has done so while portraying himself as the consummate modern manager, fond of borrowing from the Buddha, and peddling the MBA-circuit bon mots of empathetic leadership and a “growth mindset.” Nadella’s own chronicle of his turnaround, Hit Refresh, is stuffed with such cheery banalities. While the great CEOs of the past and current generation are prone to fits of rage, savage dressing-downs, and impossible expectations, Nadella appears genuinely reasonable, a happy guru who would like you to work hard, sure, but don’t forget to take time for your family and maybe a restorative hobby.

How has he done this? How does a peacetime CEO win in a war zone? Can one really win at this scale without the animal intensity of Musk or Huang? Is the balmy public presentation the whole story?

To answer these questions, I have spent the past three months studying Nadella’s leadership from as many angles as possible. That includes Hit Refresh, Acquired’s two-part series on Microsoft before Nadella, a slew of podcasts and long-form articles, internal emails released in court filings, annual shareholder letters, and confidential expert interviews with former Microsoft executives.

What emerged is a nuanced portrait of how a manager built fresh power structures beneath him, constructed new mythologies, reset cultural norms, and developed founder-like authority.

This piece is part of The Generalist’s ongoing series of managerial “playbooks,” exclusively available to premium subscribers. You can find our previous editions on Elon Musk, Jeff Bezos, and Jensen Huang here.

Our mission, across all of these playbooks, is to reveal the real strategies legendary entrepreneurs use to build their businesses. These are often uncomfortable and in direct conflict with traditional managerial advice. However, if you believe progress depends on innovation, as we do, then understanding these principles, foibles included, is not only interesting but essential.

To unlock all four playbooks and everything else The Generalist has to offer, join us now for $22/month. You’ll get immediate access to our best long-form writing, company case studies, exclusive interviews, and private databases.

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Here is the Satya Nadella Playbook:

  1. Manifest authority through mythology.

  2. Borrow power from the old regime (even as you counterposition against it).

  3. Remake the aristocracy beneath you.

  4. Make it safe to fail.

  5. Once the narrative is set, use it as cover.

  6. Hone your sharpest knife.

  7. If you can’t win the future, at least don’t lose it.

In each section, we’ll unpack the strategies behind these principles and outline their benefits and tradeoffs.

What to expect

  • A 10,000+ word playbook of tech’s most effective non-founding CEO

  • How Nadella earned founder-like authority without founding anything

  • How Nadella dismantled Microsoft’s infamous stack ranking culture

  • The bathroom-break decision that opened Azure to Linux

  • The $2.5 billion acquisition that had nothing to do with productivity (and everything to do with distribution)

  • The licensing maneuver that imposed a 400% tax on competitors’ cloud customers

  • How a panicked 2019 email led to the $13 billion OpenAI bet

  • Over 100 hours of research, confidential executive interviews, and court filings distilled

…and much more. To unlock the full playbook and learn how a “safe pick” turned a stagnant giant into a $3 trillion force, join our premium newsletter today.

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Part I: The Inheritance

By definition, a non-founding CEO does not start from scratch. They enter an environment of someone else’s making and must transform it into something of their own. To understand how Satya Nadella changed Microsoft then, we must first grasp the state of the company he inherited. It was one just emerging from what became known as its “lost decade.”

A stalled stock

When Steve Ballmer stepped into the CEO role in January 2000, he was taking the reins of the most valuable company on the planet. Less than three weeks earlier, Microsoft had hit a peak valuation of $615 billion, with a stock price approaching $60.

When the crash came, Microsoft cratered, dropping below $250 billion. It was not the fall that was remarkable, but what happened after. Or rather, what didn’t happen after. In the years that followed, as other wounded tech players stabilized and then climbed, Microsoft stayed stuck, even as its underlying performance improved. During Ballmer’s reign, revenue compounded from $23 billion to $86 billion while operating income improved from $11 billion to $28 billion. And yet, the stock barely moved, flatlining at about $30 a share. Over a similar timeframe — between late 2000 and mid-2012, Apple snowballed from a $4.8 billion pipsqueak into a $541 billion behemoth. By the time Nadella’s reign began, Microsoft was firmly in its shadow.

Read more

]]><![CDATA[Why One Superintelligence Is More Dangerous Than a Thousand (Vincent Weisser, CEO & Co-Founder of Prime Intellect)]]>https://www.generalist.com/p/why-one-superintelligence-is-morehttps://www.generalist.com/p/why-one-superintelligence-is-moreTue, 24 Mar 2026 12:05:42 GMT

“I would argue the biggest risk is actually locking in a very narrow monoculture for superintelligence. One superintelligence is much less safe than infinite superintelligence.” — Vincent Weisser

Listen or watch now on
YouTube, Spotify, or Apple Podcasts

Much of the fear around AI centers on misalignment – the idea that powerful systems might act against human interests. Vincent Weisser worries about something different: what happens if advanced AI systems are perfectly aligned with the interests of a small group of institutions? That concern led him to co-found Prime Intellect, a startup building open infrastructure for training and deploying advanced AI models. Before Prime Intellect, Weisser helped organize Vitalik Buterin’s Zuzalu experiment and worked in decentralized science, where he helped unlock roughly $40 million in funding for unconventional research. Today, he’s applying that same open ethos to AI, working to ensure the tools that shape superintelligence remain broadly accessible rather than concentrated in the hands of a few.

In our conversation, we explore:

  • Why Vincent believes multiple superintelligences are safer than one

  • The intellectual influences that shaped Vincent’s thinking about intelligence and progress, including David Deutsch and Nick Bostrom

  • Prime Intellect’s evolution from distributed compute infrastructure to frontier model training and reinforcement learning tools

  • Why Vincent believes open and decentralized science could accelerate discovery

  • The Zuzalu experiment and what it suggests about the future of scientific communities

  • The role of aesthetics and craft in building technology

  • Why Europe might have a cultural advantage in a post-superintelligence world

  • Vincent’s predictions for the next five years of AI

Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings.

Brex: The intelligent finance platform.

Rippling: Stop wasting time on admin tasks, build your startup faster.

Explore the episode

Timestamps

(00:00) Introduction to Vincent Weisser

(03:28) The book behind Prime Intellect’s name

(07:35) The case for suffering

(09:35) An overview of Prime Intellect

(13:03) Why open source models matter

(21:18) Vincent’s intellectual influences

(25:17) Early years in the startup scene

(31:48) Funding science outside traditional institutions

(41:22) The past 6 months of AI progress

(43:45) Deciding to build Prime Intellect

(46:55) Why GPUs were the right starting point

(51:39) Training models on Prime Intellect

(59:48) Why beauty matters

(1:03:48) The Zuzalu experiment

(1:06:27) Prime Intellect’s AGI Easter egg

(1:11:13) Predictions for the next five years

(1:15:09) Final meditations

Follow Vincent Weisser

LinkedIn: https://linkedin.com/in/vincentweisser

X: https://x.com/vincentweisser

Goodreads: https://www.goodreads.com/user/show/69248416-vincent-weisser

Website: https://primeintellect.ai

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[Why Robots Still Struggle With Simple Tasks (And What Might Finally Change That) | Karol Hausman, Co-Founder & CEO of Physical Intelligence]]>https://www.generalist.com/p/karol-hausman-physical-intelligencehttps://www.generalist.com/p/karol-hausman-physical-intelligenceTue, 17 Mar 2026 12:03:46 GMT

Listen or watch now on
YouTube, Spotify, or Apple Podcasts

Karol Hausman is the co-founder and CEO of Physical Intelligence, a robotics company building a general-purpose “AI brain for the physical world.” The company has raised more than $1 billion in funding to develop foundation models that allow robots to operate across many machines, environments, and tasks rather than being programmed for a single purpose. The core thesis: the same scaling dynamics that transformed language models may also unlock robotic intelligence. But only if you resist every commercial pressure pushing you toward specialization. The central challenge isn’t mechanical design. It’s intelligence: how robots learn, generalize, and interact with a physical world that is far harder to simulate than it is to describe. Before launching Physical Intelligence, Karol worked at Google Brain and Stanford University, studying robot learning alongside researchers Sergey Levine and Chelsea Finn, who later became his co-founders.

In our conversation, we explore:

  • How growing up in a small town in Poland and watching Star Wars sparked Karol’s fascination with robots

  • The moment a lecture from Sergey Levine convinced him to abandon his PhD research direction and pivot fully to deep learning

  • Why robotics has historically lagged behind breakthroughs in language models

  • The case for building a general “AI brain” for the physical world rather than a single specialized robot

  • The role of real-world data in training robots, the limits of simulation, and how deployment could create a powerful data flywheel

  • The return of reinforcement learning and the parallels between human learning and robot training

  • The unique challenges of physical intelligence and why robots must operate with far higher reliability than language models

Thank you to the partners who make this possible

Brex: The intelligent finance platform.

Granola: The app that might actually make you love meetings.

Explore the episode

Timestamps

(00:00) Intro

(04:05) Karol’s early fascination with robots

(07:38) How Karol relates to Fei-Fei Li’s biography

(08:52) What inspired Karol to build better robots

(11:19) Philosophical influences

(15:33) Parallels between The Inner Game of Tennis and robotics

(18:21) Karol’s entry point to robotics and PhD program

(25:49) Combining robotics with LLMs: The Taylor Swift demo

(30:48) The 1970s SHRDLU AI experiment

(32:33) Founding Physical Intelligence

(35:13) How Lachy Groom got involved

(39:40) How research shapes what Physical Intelligence builds

(45:22) The importance of real-world data

(49:07) The return of reinforcement learning in robotics

(53:31) The risk of commercializing too early

(55:47) Finding the right partners for the business

(57:13) Open research questions

(1:00:00) NVIDIA’s simulation engines

(1:01:57) The surprising speed of progress

(1:04:16) Reliability in robotics

(1:07:31) Compensating for missing senses

(1:12:28) Book recommendation

Follow Karol Hausman

LinkedIn: https://www.linkedin.com/in/karolhausman

X: https://x.com/hausman_k

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[America’s Electric Power Grid Is Broken. This Startup Is Trying to Fix It. (Zach Dell, co-founder & CEO of Base)]]>https://www.generalist.com/p/americas-electric-power-grid-is-brokenhttps://www.generalist.com/p/americas-electric-power-grid-is-brokenTue, 10 Mar 2026 12:03:39 GMT

“You must get comfortable with the notion that a lot of really smart people you respect are going to explain to you in excruciating detail why this is not going to work...You have to be able to see through that and have a clear vision in your mind for why it is going to work.” — Zach Dell, co-founder and CEO of Base

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For decades, America’s electrical system has rewarded utilities for building more infrastructure, not for lowering costs. The result is a grid that expanded but rarely improved. Zach Dell, co-founder and CEO of Base, is building a different kind of power company. In under three years, Base has grown into a vertically integrated business valued in the billions. It combines home batteries and software to store electricity when it is cheap and deliver it when demand spikes. Dell’s interest in energy began long before Base. In college, he tried to lease a Hawaiian lava field for a solar project. He also experimented with anaerobic digestion systems in India and worked at Blackstone and Thrive Capital, where he met his co-founder. His bet is simple but ambitious: the next phase of the grid will come from increasing utilization rather than constantly building new infrastructure.

In our conversation, we explore:

  • How a failed college solar project and early energy experiments in India pulled Zach into the power industry

  • The lessons he absorbed from his parents, including truth-seeking, reinvention, and competitive endurance

  • How the U.S. grid’s regulatory structure discourages innovation and why Texas’s deregulated market creates space for new power companies

  • Why batteries are best understood as a time-shifting technology that increases grid utilization and reduces total system costs, not simply as energy generators

  • Base’s “make, move, store, sell” framework for thinking about the full power stack

  • How Base aims to become the first beloved energy company

  • How Zach identified Justin as a world-class operator and built the trust needed to go all-in together on a non-obvious idea

  • How aggressive AI adoption is compressing cycle times and why slow adopters risk falling behind

Thank you to the partners who make this possible

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Brex: The intelligent finance platform.

Explore the episode

Timestamps

(00:00) Introduction to Zach Dell and Base

(03:06) The Hawaiian lava field solar project and early energy curiosity

(07:58) Investing vs. operating

(09:31) Lessons from Phil Jackson on aligning talented teams

(15:24) Lessons from his parents

(19:19) The loneliness of solo founding and the value of co-founders

(21:49) Justin’s strengths as a co-founder and how their partnership formed

(30:55) Why Base became the obvious focus

(32:21) The original vision and the three reversals

(35:49) The American power grid and what makes Texas different

(40:39) Why batteries matter and what Base is building

(41:44) How Base works in two market types

(45:59) Base’s core product

(47:43) The software behind Base’s battery network

(49:14) Base’s partnerships with battery cell makers

(50:43) The Gen 2 hardware mistake and the lesson in risk management

(52:00) Dino’s strengths as Head of Hardware

(53:20) Base’s positioning as grid infrastructure

(55:39) Building a beloved energy brand

(58:45) How hiring at Base has evolved

(1:01:54) AI workflows at Base

(1:03:44) Zach’s dedicated deep work time

(1:06:29) Final meditations

Follow Zach Dell

LinkedIn: https://www.linkedin.com/in/zach-dell-a631a554

X: https://x.com/ZachBDell

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]]><![CDATA[Infinite Games]]>https://www.generalist.com/p/infinite-gameshttps://www.generalist.com/p/infinite-gamesThu, 26 Feb 2026 14:58:49 GMT

“To be prepared against surprise is to be trained. To be prepared for surprise is to be educated.”

- James Carse, Finite and Infinite Games

Friends,

Evolutionary biology has the concept of “allopatric speciation,” the process that occurs when a species develops separately from those on the mainland. Saved from some evolutionary pressures and exposed to oth…

Read more

]]><![CDATA[Everyone Is Betting on Bigger LLMs. She's Betting They're Fundamentally Wrong. (Eve Bodnia, Founder & CEO of Logical Intelligence)]]>https://www.generalist.com/p/everyone-is-betting-on-bigger-llmshttps://www.generalist.com/p/everyone-is-betting-on-bigger-llmsTue, 24 Feb 2026 13:03:32 GMT

“AGI should be just like natural intelligence. Something which plans, something which is able to predict, produce new knowledge, be cheap and efficient, and be adaptive to the environment. It should reason, it should not mimic.” — Eve Bodnia, Founder & CEO, Logical Intelligence

Listen or watch now on
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Eve Bodnia is the co-founder and CEO of Logical Intelligence, which is developing energy-based reasoning models (EBMs) as an alternative to large language models. She argues that LLMs, which operate by recognizing and recombining patterns within language space, are structurally incapable of genuine reasoning. Eve's alternative: Kona—an EBM that reasons in abstract latent space, learns rules about the world rather than surface patterns, and can interface with language models as one output channel among many. Eve traces the core ideas behind her architecture to decades of work in symmetry groups, condensed matter physics, and brain science—fields that share, as she explains, the same underlying mathematics. In a public demo, Kona solved a complex reasoning task for roughly $4 in compute, compared to an estimated $15,000 using frontier LLMs. With Yann LeCun serving as founding chair of its technical board, Logical Intelligence sits at the center of a small but growing effort to rethink AI beyond language-based models.

In our conversation, we explore:

  • Why Eve believes LLMs can’t truly extrapolate knowledge, even at larger scale

  • What energy-based reasoning models are—and where the “energy” concept comes from

  • The $4 vs. $15,000 benchmark, and what it tells us about the cost of guessing vs. knowing

  • How Logical Intelligence showed spontaneous knowledge transfer at just 16M parameters

  • Why systems like chip design, surgical robotics, and power grids need more than probabilistic AI

  • What formally verified code generation means for the future of programming

  • Why the math behind particle physics also explains how the brain filters signal from noise

  • How meeting Grigori Perelman as a teenager shaped Eve’s views on ego and ownership in science

  • Why Eve believes humans must remain the constraint-setters in advanced AI

  • How meditation, piano, and Eastern philosophy support her creative process

Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings.

Persona: Trusted identity verification for any use case.

Explore the episode

Timestamps

(00:00) Introduction

(03:03) Eve’s encounter with Grigori Perelman

(05:38) Why bizarre people are Eve’s favorite people

(06:56) Her early obsession with math and physics

(09:02) The manifold hypothesis and language

(11:54) The Kekulé Problem

(14:05) Eve’s upbringing and her CERN research in high school

(17:40) Eve’s academic path

(20:36) Symmetry in nature

(22:58) Spirituality and creativity

(27:00) Theory vs. experiment

(29:03) Uncovering a critical gap in AI models

(33:45) What Logical Intelligence is building

(35:50) Logical Intelligence’s use cases

(42:08) Energy-based models explained

(45:06) LLMs vs. EBMs

(48:01) AGI defined

(51:22) Kona’s knowledge extrapolation

(53:20) The team behind Logical Intelligence

(58:09) Early investors in Logical Intelligence

(58:50) Feynman’s influence on Eve’s work

(1:01:15) How Eve sustains her creativity

(1:03:42) Final meditations

Follow Eve Bodnia

LinkedIn: https://www.linkedin.com/in/eve-bodnia-351b41355

X: https://x.com/evelovesolive

Website: https://logicalintelligence.com

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[How Bolt Survived An 85% Revenue Crash And Became Europe's Ride-Hailing Champion (Markus Villig, Founder & CEO) ]]>https://www.generalist.com/p/how-bolt-survived-an-85-revenue-crashhttps://www.generalist.com/p/how-bolt-survived-an-85-revenue-crashThu, 19 Feb 2026 13:03:12 GMT

“We don’t care that we’re from a small country. We’ve always had the view that if we work harder and [make] smarter decisions, we can beat [any] company in the world, regardless of how big they are.”

Listen or watch now on
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In 2013, on an Estonian island of just 10,000 residents, a teenager borrowed €5,000 from his parents and decided to take on Uber. Twelve years later, Markus Villig leads Bolt, a company operating in 50+ countries, generating nearly €3 billion in revenue, and standing as one of the only European tech companies competing at true global scale. Rather than going head-to-head with incumbents in their strongest markets, Bolt expanded through underserved cities, emerging economies, and overlooked segments of urban transport. When COVID erased 85% of its revenue in weeks, the company didn’t retreat; it staged a kind of corporate “eucatastrophe,” pivoting into food delivery across nearly 20 countries in what became a company-wide sprint. That same bias toward action now shapes Markus’s broader agenda: investing in defense tech for Estonia and Ukraine, pushing for capital markets reform, and advancing a contrarian thesis on autonomous vehicles.

In this conversation, we discuss:

  • How growing up in Soviet-occupied Estonia shaped Markus’s ambition and moral clarity

  • How Bolt’s European ethos and long-term focus on driver retention became a structural advantage

  • The marketplace models and capital discipline that allowed Bolt to outmaneuver better-funded rivals

  • Why Bolt found breakout success in African markets after failing in 12 Western countries

  • The 85% revenue collapse during COVID and the rapid food delivery pivot that reshaped the company

  • Bolt’s partnerships with Stellantis and Pony.ai and its long-term bet on autonomous vehicles

  • Why Ukrainian and Eastern European startups are often outperforming their Western peers

  • Markus’s blueprint for closing Europe’s tech deficit and building globally competitive companies

Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings

Brex: The intelligent finance platform.

Persona: Trusted identity verification for any use case.

Explore the episode

Timestamps

(00:00) Intro

(03:32) How The Lord of the Rings shaped Markus’s worldview

(05:52) Bolt’s underdog story and its existential turning point

(10:22) Estonia’s startup DNA and its imprint on Bolt

(13:38) Europe’s ambition problem

(17:23) Europe’s defense tech gap

(23:09) The need for capital market reform in Europe

(25:13) Bolt’s origin story

(36:35) Frugality as strategy

(38:24) What running Bolt actually demands

(41:27) The hidden costs of being too lean

(42:50) Bolt’s shift to experimentation

(44:10) Bolt’s micromobility strategy

(45:50) How Bolt found the right markets

(50:44) The Serbian mob story

(54:00) Markus on venture capital and lessons from Klarna’s board

(55:40) Why Bolt never sold

(57:08) Bolt’s autonomous vehicle (AV) strategy and key partnerships

(1:05:50) The concept of culture-market fit

(1:07:48) How Bolt operates: writing, hiring, reading, and more

(1:13:15) Markus’s personal strengths

(1:14:15) What people get wrong about business

(1:16:27) Final meditations

Follow Markus Villig

X: https://x.com/villigm

LinkedIn: https://www.linkedin.com/in/markusvillig

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[Lessons of a First-Time Fund Manager]]>https://www.generalist.com/p/lessons-of-a-first-time-fund-managerhttps://www.generalist.com/p/lessons-of-a-first-time-fund-managerThu, 05 Feb 2026 15:47:00 GMT

Friends,

Four years ago, I set out to raise my first venture fund. The result was Generalist Capital, a $15 million vehicle to invest in a small collection of (hopefully) legendary companies.

The beginning of this year marks something of a turning point. After closing on a few investments, Generalist Capital officially moved from the deployment phase to management and harvesting. That makes it a fitting moment to share the lessons learned along the way. Though venture capital is awash in content, in my view, there’s too little introspective writing on the mental game of fund management. Below, you’ll find my attempt to distill the most important lessons I’ve learned so far. To that end, these are best seen as the lessons of a first-time fund manager, relating primarily to the challenges of starting a fund and establishing an initial viable strategy.

Naturally, the gravity of these lessons will depend on information I cannot give you: my long-term performance as an investor. It will likely take another six to ten years to discover how promising a portfolio I have built with Generalist Capital, and even longer to know definitively if I am any good. As of our last update to LPs, Generalist Capital was performing in the top 10-15% in its vintage, but the data suggests that it takes about six years for a fund to settle into its terminal quartile. There’s still a long way left to run and too much uncertainty to read much into this. I am afraid that this is the best I can offer you.

Let this serve as a reminder, then, if any were needed, that you should take my lessons with a grain of salt. I have achieved little, and every investor must learn to play their own game. Though I hope they spark new ideas for you, these are just the observations of one manager at the beginning of what I hope proves to be a long career.

  1. If this is your first time managing a fund, be extremely skeptical of your early investment urges. You’re probably overly keen to validate your existence to your LPs.

  2. The best companies can go under the radar for a long time. When other VCs asked which of my investments I was most bullish about, I told them freely. It still took several years for a Tier 1 firm to lead a round into the company.

  3. You do not have to wait for a round. If you have enough to offer a company, they’ll find a way to bring you aboard ahead of a formal raise. When you see a startup you love, try to make something happen.

  4. Don’t assume you know your level. New managers often think they can’t get access to rounds led by Tier 1 VCs. With the right pitch, you may be closer than you think.

  5. It’s very rare you see everything you want in a startup: founder, market, traction, and so on. When you do, write a much bigger check than you ordinarily would.

  6. The first investor has a unique relationship with a founder. You can build good relationships no matter when you invest, but the first check in earns a special level of trust.

  7. Contrary to what you might expect, the best companies are not easier to access as round sizes grow. Competition escalates as they succeed, often through late growth.

  8. The best investors often need little more than a sentence to explain why they’ve invested in a company. The longer and more convoluted your investment rationale is, the more skeptical you should be of it.

  9. Find your pace. A generation of managers has been conditioned to deploy vintages in 18-24 months. There is nothing wrong with taking twice as long, or more.

  10. Just because a deal is hot does not mean it is good. Don’t let other people’s urgency influence your desire.

  11. Remind yourself: the best venture firms in the world make a majority of bad investments. Don’t index on a buzzy name.

  12. Conversely, if some of the best investors in the world are backing a startup you don’t consider promising, look again, extremely closely. There’s a good chance you’re missing something important.

  13. Remember, the best investors in the world ≠ the best known investors. Calibrate accordingly.

  14. Don’t assume the best opportunities will land in your lap. Outbound sourcing is a necessity.

  15. Progress is never linear. A company that you had more or less written off can suddenly catch light, and one that was on a breakout trajectory can easily stall or stumble.

  16. Don’t push your anxiety onto your founders. It’s not your job to let them know of every new company that pops up in their space.

  17. If you’re asked for advice, give it honestly, but recognize that you have 0.01% of the context a founder has.

  18. Fight for every dollar. Getting an extra $10K into a breakout company can make a huge difference for a small fund.

  19. Founders respond to conviction. Earnestly explaining to an entrepreneur why you’re excited about their business and showing a desire to move quickly can overcome any number of natural disadvantages.

  20. Be skeptical of a pitch that looks too rational. Great companies often have something paradoxical about them. If something doesn’t quite make sense, that’s a good indication you should lean in, not out.

  21. Be careful you don’t get stuck correcting your last mistake. If you invested too little in a startup that has just started to break out, don’t triple the size of your next check to compensate. Consider each opportunity anew.

  22. If you’re not positioned to catch a wave, don’t chase it. You could burn an entire vintage on second-and third-rate AI companies.

Read more

]]><![CDATA[The Private Company Bringing Nuclear Enrichment Back to America (Scott Nolan, CEO of General Matter)]]>https://www.generalist.com/p/the-private-company-bringing-nuclearhttps://www.generalist.com/p/the-private-company-bringing-nuclearTue, 03 Feb 2026 13:03:34 GMT

“We [the U.S.] went from controlling something like 86% of global enrichment capacity to effectively last place.”

Listen or watch now on
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Roughly 20% of the U.S. power grid runs on nuclear energy. A quarter of the fuel behind it is headed toward a hard stop. In this episode, I sit down with Scott Nolan, founder and CEO of General Matter, to unpack why uranium enrichment has quietly become one of the most consequential industrial bottlenecks of the 21st century.

While at Founders Fund, Scott spent over a year searching for an American enrichment company to back. When he couldn’t find one, he decided to build it himself. Less than a year after emerging from stealth, General Matter secured a historic enrichment site in Paducah, Kentucky, and was awarded a $900 million Department of Energy contract—marking one of the first serious efforts to rebuild domestic enrichment capacity ahead of the 2028 ban on Russian supply.

In this episode, we discuss:

  • Why enrichment is the missing link in America’s nuclear supply chain

  • How the U.S. went from controlling 86% of global enrichment capacity to effectively none at commercial scale

  • The science behind uranium enrichment and why it matters for next-generation reactors

  • Why Scott applied the SpaceX playbook to nuclear after more than a decade in venture capital

  • How General Matter is revitalizing the historic Paducah, Kentucky enrichment site

  • The significance of General Matter’s $900 million Department of Energy contract

  • The bipartisan political support for expanding nuclear energy

  • Why Scott believes nuclear energy could grow 3-4x by 2050

  • The parallels between America’s space and nuclear industries

Thank you to our sponsor, Persona: Trusted identity verification for any use case.

Explore the episode

Timestamps

(00:00) Introduction to Scott Nolan

(02:24) General Matter’s mission to rebuild U.S. enrichment

(05:08) How the U.S. lost its edge

(06:24) The nuclear fuel cycle explained—and where enrichment fits

(08:31) Scott’s background: From SpaceX and Founders Fund to General Matter

(13:56) Lessons from SpaceX

(17:50) How Scott’s focus evolved over 13 years at Founders Fund

(21:00) How Scott landed on nuclear enrichment

(25:58) Why nuclear energy was off the radar—until recently

(30:10) Finding the right partner: Scott and Lee’s collaboration

(32:04) What downblending means and why it matters

(33:30) How U.S. uranium enrichment quietly came to an end

(38:34) The Russian uranium ban and the 2028 supply cliff

(40:38) How General Matter plans to compete

(43:09) Building a world-class team

(46:03) The market for enriched uranium

(49:30) Future bottlenecks

(50:56) What the U.S. needs to actually scale nuclear energy

(51:32) Uranium supply constraints

(54:16) LEU vs. HALEU: the fuels powering old and new reactors

(57:49) Why 20% enrichment is a critical threshold

(59:30) Why General Matter chose Paducah, Kentucky

(01:04:35) Legislation and executive orders easing nuclear friction

(01:07:06) The $900 million Department of Energy award

(01:11:08) Why mission matters most

(01:14:12) Final meditations

Follow Scott Nolan

X: https://x.com/ScottNolan

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[The Generalist’s Productivity Stack (2026)]]>https://www.generalist.com/p/productivity-stack-2026https://www.generalist.com/p/productivity-stack-2026Thu, 22 Jan 2026 15:41:21 GMT

Friends,

Last January, on a whim, I shared a few of the productivity methods I’ve found effective in maximizing my output while building The Generalist. It was driven by a geekish obsession with tiny optimizations, a love for adopting niche tools, and a real belief that the environment you make for yourself impacts the work you are capable of.

To my surprise, it became one of The Generalist’s most popular pieces. With January in full swing and the year still stretching in front of us, I decided to sit down and outline the new tools and methods I’ve found effective over the past year. It turned into quite a collection. You’ll find 26 tools I recommend (both digital and analog) and 8 practices I’ve found invaluable.

I’ve avoided repeating last year’s recommendations (though I still use them), so if you’re as into these kinds of hacks and optimizations as I am, you may want to read that piece, too.

Tools

An exhaustive list of the programs, apps, extensions, and physical objects I recommend.

Read more

]]><![CDATA[Programming Sunlight: How Reflect Orbital Is Building Satellites to Redirect Light From Space (Ben Nowack, Founder & CEO)]]>https://www.generalist.com/p/programming-sunlight-ben-nowackhttps://www.generalist.com/p/programming-sunlight-ben-nowackTue, 20 Jan 2026 13:03:59 GMT

“It’s either sunny or it’s not sunny, and there’s not much you can do about that—but we’re trying to change that for the first time ever.” —Ben Nowack

Listen or watch now on
YouTube, Spotify, or Apple Podcasts

Most energy conversations start with scarcity. This one starts with abundance. Sunlight powers nearly everything on Earth, directly or indirectly. And yet we have almost no control over when or where we get it. Ben Nowack thinks that’s a solvable problem. Ben is the founder and CEO of Reflect Orbital, a company building satellites designed to redirect sunlight from space—not as a thought experiment, but as a product. The company nearly died before it worked. Eight months in, Ben had $300 left and was living in a garage. He made a deliberate decision to go $50,000 into credit card debt to finish critical tests. At one point, he was down to $21 of available credit. A month later, Reflect raised its first round. Today, the company is preparing to launch its first revenue-generating satellites. This is a conversation about building conviction, finding the real market, and what changes when a fundamental resource becomes programmable.

In our conversation, we explore:

  • How Reflect’s satellites work

  • The surprising pivot from energy to lighting applications that made the business immediately viable

  • Ben’s remarkable journey from building RC planes and X-ray machines in high school to founding Reflect

  • Why previous attempts at space mirrors failed and what’s changed to make this possible now

  • The near-death moment when Ben went $50,000 into credit card debt to keep his vision alive

  • How Reflect plans to scale from moonlight-level brightness to potentially powering solar farms

  • The company’s first satellite launches planned for this year, and their path to a full constellation

  • The wide range of applications, from emergency response to municipal lighting to agriculture

Explore the episode

Timestamps

(00:00) Introduction to Ben Nowack

(02:26) What Reflect Orbital is building

(05:07) How the satellite constellation works

(08:00) What Reflect is launching this year

(10:35) Finding early markets

(13:43) Ben’s childhood and early building experiences

(22:04) What Ben learned working for startups

(28:03) High school projects: X-ray machines, rocket engines, and fusion reactors

(33:14) The eureka moment that led to Reflect

(35:24) Early validation of the idea

(38:35) The Russian space mirror experiments of the 1990s and what’s changed

(42:31) Partnering with Tristan Similac as co-founder

(45:05) Baiju Bhatt’s involvement

(47:04) Why Reflect isn’t pivoting to space-based data centers

(50:54) Common misconceptions about Reflect’s technology

(55:11) Why programmable light is valuable

(1:01:28) Initial target markets

(1:03:42) The future markets for Reflect

(1:07:33) Reflect’s company culture and operational philosophy

(1:12:05) Surprises and struggles in building Reflect

(1:14:56) Putting the idea to the test

Follow Ben Nowack

LinkedIn: https://www.linkedin.com/in/ben-nowack

X: https://x.com/bennbuilds

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

]]><![CDATA[Nothing’s Carl Pei on Building a $1B Smartphone Company, Why He Left OnePlus After 10 Days of Retirement, and Why He Thinks About Death Every Week]]>https://www.generalist.com/p/nothings-carl-pei-on-building-a-1b-smartphone-companyhttps://www.generalist.com/p/nothings-carl-pei-on-building-a-1b-smartphone-companyTue, 13 Jan 2026 13:03:26 GMT

“As humans, one of our superpowers is creativity. Both on an individual level, but also on a species level. And by creativity, I mean the ability to solve problems.” —Carl Pei

Listen or watch now on
YouTube, Spotify, or Apple Podcasts

Carl Pei is the founder of Nothing, the consumer electronics company known for its distinctive transparent design language across smartphones and audio products. Before launching Nothing in 2020, Carl co-founded OnePlus, where he spent seven years helping build it into a major smartphone brand. But Carl’s instincts as a builder showed up much earlier. As a teenager, he taught himself to code by building Pokémon fan sites, all while moving between China, the U.S., and Sweden. That combination of early creation and constant change shaped a founder comfortable with uncertainty—and deeply motivated by questions bigger than products. Carl thinks often about time and mortality, is skeptical of early retirement, and believes creativity is humanity’s real advantage. In an industry obsessed with optimization, he’s focused on making technology feel meaningful again.

In our conversation, we explore:

  • The origins of Nothing’s transparent design language and how it helps differentiate the brand in a mature, competitive market

  • Carl’s childhood fascination with mortality and how it continues to drive his ambition today

  • Nothing’s multiple near-death experiences, from 80% defect rates on first products to fundraising struggles

  • Why India has become a crucial market for Nothing’s smartphone business

  • How Nothing approaches community involvement, including letting users invest alongside VCs

  • The company’s approach to integrating AI features without overhyping the technology

  • Carl’s admiration for Genghis Khan’s management style and talent acquisition approach

  • The future of consumer electronics beyond smartphones

Thank you to our sponsor, Guru — The AI source of truth for work

Explore the episode

Timestamps

(00:00) Introduction to Carl Pei and Nothing

(02:44) Nothing’s long-term vision

(06:33) How existential thinking shapes Carl’s motivation

(10:12) Why Carl’s planned sabbatical ended after ten days

(12:35) Carl’s international upbringing

(16:02) Entrepreneurial experiments in China

(19:10) Carl’s competitive nature and attitude toward school

(25:30) Lessons from seven years at OnePlus

(28:07) Taking a break at age 31

(30:50) Carl’s fundraising strategy

(33:26) Why Carl chose London for Nothing’s HQ

(35:12) Lessons from Genghis Khan

(38:38) Nothing’s first near-death moment

(42:56) Nothing’s product evolution and breakout hits

(45:24) Partnering with Teenage Engineering

(49:28) Design inspirations

(51:36) How Nothing recruits talent

(53:42) Nothing’s approach to marketing

(56:51) How India became a key market

(59:48) Why Nothing created CMF

(1:02:12) Why Carl is bullish on India

(1:03:32) How Carl thinks about AI

(1:07:05) Rethinking ads based on community feedback

(1:09:05) How Nothing leverages community

(1:11:23) Why AI hardware is struggling

(1:13:37) Carl’s thoughts on the future of consumer electronics

(1:15:10) Philosophies that shape Carl’s worldview

(1:16:45) Final meditations

Follow Carl Pei

LinkedIn: https://www.linkedin.com/in/getpeid

X: https://x.com/getpeid

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]]><![CDATA[What to Watch in 2026 ]]>https://www.generalist.com/p/what-to-watch-in-2026https://www.generalist.com/p/what-to-watch-in-2026Fri, 09 Jan 2026 13:49:14 GMT🌟 Happy 2026! There’s never been a better time to join our premium newsletter and invest in yourself. It’s designed to make you a better founder, investor, and technologist. Members get access to the strategies, tactics, and wisdom of exceptional investors and founders. Today’s piece is a subscriber-only edition.

Friends,

The world is not waiting to start the year.

In just over a week, we have seen that the world of 2026 will not be the same as that of 2025. Trump’s actions in Venezuela are the most naked illustration of this fact, revealing the changing nature of power and shifts in spheres of relative influence.

Technology is not immune to such developments, and, indeed, is a key input. Even with January just getting its footing, our sector is in motion: in a span of just a few weeks, Jensen Huang struck a $20 billion deal for Groq’s talent and IP, revealed Nvidia’s upcoming Rubin architecture, and saw China order its domestic companies to pause purchases of H200 chips. Meanwhile, DeepSeek released research rethinking AI training, ChatGPT launched a dedicated health product, Meta is attempting to purchase Chinese-founded startup Manus, and Anthropic is raising $10 billion at a $350 billion valuation.

All of this is happening against the backdrop of growing unease about AI valuations and the possibility that we are in the midst of a rapidly inflating bubble primed to burst.

As a reminder: it is January 9th.

To try and grasp what (else) 2026 might have in store, particularly with regard to tech and venture capital, I reached out to a collection of more than 45 elite investors and thinkers. I asked each of these people to answer the question: What company, market, or trend do you think is most worth paying attention to in 2026?

Below, you will find their answers, organized into seven themes. It includes entries from legends like Reid Hoffman, Kirsten Green, Gili Raanan, and Aydin Senkut, as well as those I consider the sharpest thinkers from the next generation. It is, in a sense, a collection of futures. A cadre of possible paths that may or may not unfurl. In big and little ways, I hope that they make you a little more aware of what may happen and where opportunities might lie.

As was the case with last year’s edition, I compiled this piece with the express goal of creating something that more than justifies the cost of The Generalist’s premium subscription on its basis alone. Given the insights I’ve gleaned from it already, I believe we’ve achieved that for anyone who works in venture capital, actively angel invests, or is considering starting a company. I suspect it will also be of great use to operators who want to understand how their respective industries could develop.

Here’s what to expect:

  • The robotics company helping with data center buildouts

  • A voice AI company poised to come out of stealth

  • The African fintech following Nubank’s trajectory

  • Where China is poised to outcompete America

  • A potential landmark in nuclear energy

  • An AI myth gets exposed

  • The startups poised to win in Latin America

  • The under-the-radar search startup used by Cursor

To set yourself up for the best possible 2026, join our premium subscription for just $22/month today. It’s designed to make you a radically better investor for a teeny fraction of the cost of a traditional investing intelligence service.

Subscribe now

Again, my hope and goal is that this piece alone repays the cost of a year’s subscription.

PS. You know this already, but for the avoidance of doubt: this is not investment advice. This is intended to surface new ideas and guide you toward interesting topics. Most submissions focus on private companies, but please heed this, particularly for those that highlight a crypto project with a public token. These tend to be hyper-volatile assets. You should always make investment decisions based on your own research.

I. The physical world wakes up

AI’s most impressive feats have typically occurred on screens. That may be changing. Robots are learning by watching humans, excavators are moving dirt without drivers, and the robotics sector is splitting into two worlds: one of hype, another of quiet deployment.

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]]><![CDATA[Modern Meditations: Immad Akhund]]>https://www.generalist.com/p/modern-meditations-immad-akhundhttps://www.generalist.com/p/modern-meditations-immad-akhundThu, 18 Dec 2025 14:22:49 GMT
Illustration by Eleanor Taylor

Friends,

How often do you think about the Mongolian Empire?

For Mercury CEO, Immad Akhund, the answer seems to be “surprisingly often.” For our final interview of the year, I asked the founder of one of my very favorite products to share his latest obsessions, contrarian opinions, and favorite reads.

As well as outlining the h…

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]]><![CDATA[Bubble Memory: A CEO’s Reflections on the Dotcom Boom and Bust]]>https://www.generalist.com/p/steve-casehttps://www.generalist.com/p/steve-caseThu, 11 Dec 2025 16:20:24 GMT
Illustration by Eleanor Taylor

Friends,

Perhaps no one experienced the dotcom boom and bust quite as viscerally as Steve Case. The founder of Revolution began the decade as an executive at a small software company called Quantum Link, and ended it as the CEO of a behemoth: AOL.

It is hard to overstate just how important a company AOL was at the start of the millennium. Unless you were already of working age and minded towards tech and business, there’s a good chance you haven’t calibrated its size appropriately. AOL was a giant. Between its IPO in 1992 and the start of the new millennium, its stock appreciated approximately 80,000%, reaching a peak of $222 billion in December 1999. By that point, it had eclipsed many of the business world’s biggest companies, surpassing Disney, IBM, McDonald’s, and Berkshire Hathaway. At the time, AOL was larger than Boeing and General Motors combined.

It was also wildly significant and influential, responsible for opening the internet up to a new generation of users and making it fun to use. The AOL of that era pioneered many of the user experiences and behaviors that make up the modern web, from screen names to instant messaging.

In January 2000, AOL looked set for another decade of dominance. On the tenth of that month, it announced a planned merger with Time Warner. Remarkably, AOL was the senior partner, receiving 55% of the combined $350 billion entity. Again, the scale of the deal is hard to comprehend unless you lived it. At the headline valuation, AOL Time Warner became the fourth largest company on the planet – a figure greater than “the output of Russia or the Netherlands.”

What came after is the subject of much study and coverage. The market crashed, the merger failed, and not long after, Case stepped down as AOL CEO. By 2005, Case publicly argued in favor of the two companies splitting, and at the end of the decade, that came to fruition. Though there were strong strategic merits to an AOL-Time Warner union, it proved to be a marriage that suited neither party.

It seems as if we are in yet another torrid cycle and potentially one of greater magnitude than that which Case surfed. A recent analyst report argued that the current AI bubble is 17x greater than its dotcom corollary, and 4x larger than the 2008 financial crisis. (We can hope it will be more productive than the financial crash, at least.)

A bubble is a strange environment in which to live. It is an even stranger one in which to build a business. How do you keep your feet on the ground when the world beneath is rushing past at a thousand miles an hour? How can you hold fast to reality when wide-eyed investors, gasping for breath, paint ever more fantastical futures in front of you and shove your pockets full of cash? Where is the boundary? Is there really such a thing as a horizon?

We believe that “this time is different,” and there is truth in that. We do not live in a perfectly iterated game. The board has changed, fresh players have stepped onto it, and new moves are always being invented. But it is more naive to pretend the past has nothing to teach us. In fundamental ways, today’s founders face the same set of challenges as their late 90s forerunners. How do you build a team at warp speed? Is it possible to scale a culture when you’re growing exponentially? How can you make smart acquisitions and avoid the most common missteps? What role should partnerships and business development play when you’re forging a new category?

As I thought about these questions, I realized that perhaps no one is better suited to speak from experience than Steve Case himself. And so, I asked him to reflect on his journey at AOL, the similarities and differences between that era and ours, and the lessons founders should heed. We also discuss what it was like to compete head-to-head against Bill Gates, the strategic necessity that drove the Time Warner deal, and the similarities between Jeff Bezos and Steve Jobs.

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An Interview with Steve Case

To start, I’d love to connect the two eras we’re talking about and the lessons we might take from them. How much does the current AI wave remind you of the dotcom bubble?

It has some similarities, but some differences, too.

Like the internet, AI has been many years in the making. When you look at AI, some of the core technologies can be traced back to something like 70 years ago. This is not a new idea. It just took that time for it to become a mainstream consumer phenomenon. Obviously, over the last ten to twenty years, a lot of companies have integrated AI. Most of the apps we use on our phones rely on AI to some extent. The difference is that nobody called it AI. But it was driving recommendation engines and so on; it was just more of a back-end, invisible thing. It only became an in-your-face visible technology with the success of ChatGPT.

That timing dynamic reminds me of the dotcom era. The gold rush mentality does too. People feel that this is the next big thing, and they don’t want to miss out, which leads to investors pouring a lot of money into companies. A few of those will be wildly successful, many will be OK, and a good number will also probably end up hitting the wall and going out of business, which is what happened with the internet.

Clearly, AI as a core technology and platform is going to have a comparable or greater impact to the internet. It has the ability to transform industries and society in very fundamental ways, but there will be a mix of successes and failures.

A final point I’d make is about government and policy. What most people don’t appreciate about the internet is that the United States wouldn’t have been the leader it was with respect to that technology were it not for a series of government decisions: first, you have the government’s decision to fund the Defense Department’s ARPANET, which basically became the internet. Next, there was the Justice Department’s decision in 1984 to break up AT&T into seven regional operating companies, which drove communication costs down and made the internet much more affordable. Third, there was the decision by the FCC to mandate open access for the telephone networks so that they had to let AOL and others plug into them. And, finally, in the early 90s, Congress passed a law opening up the internet to consumers and businesses. Up until that point, it had been restricted to government agencies and educational institutions.

It’s easy to forget these things, but if they hadn’t happened, the internet would not have evolved the way it did. In the case of AI, it’s really important that we figure out what that policy overlay should be. How do you make sure that while the technology is being developed, you don’t over-regulate and stifle innovation? Europe has historically made the mistake of focusing too much on what might go wrong and, as a result, stifles what might go right.

At the same time, though, because AI is so ubiquitous already (versus the internet, which grew slowly before mass adoption), some engagement, some policy guardrails are necessary now.

What might some common-sense guidelines look like?

One of the lessons from the internet is that you need to mandate open access. When it comes to AI, I think we need to make sure the big platform companies are essentially required to have open access. We don’t want to create a system that just allows the big companies to dominate; we have to force them to open their networks and keep them open for new companies to participate and innovate.

You had the rare experience of building what was considered the most significant company of its time during a historic bull market. It remains to be seen to what extent AI is a bubble, but I suspect the lessons you learned building AOL during the dotcom boom are deeply relevant for today’s founders.

As a jumping-off point, how did you manage your mental game during that period? AOL went from a relatively small company to one of the most important on the planet in a short period of time. The company must have been changing noticeably almost every day.

Part of my job was to be a shock absorber for the rest of the company. As the CEO, you have to even out the highs and lows for people. When things are going great, remind them about the risk. I used to call that “delegating paranoia.” When things are down in the dumps, remind them of why you have a bright future. There were plenty of moments like that at AOL – we’d be on the cover of a magazine with the headline saying “AOL is going to go under for XYZ reason.” It’s your role to provide that balance so that people can focus on the overall mission.

It probably helped that it took more than a decade for us to get real traction. I joke that AOL was a ten-year-in-the-making overnight success. The time it took us probably gave all of us, including me, more perspective and humility when all of a sudden it was this go-go-go momentum. It helped me not buy into all the positives or all the negatives.

Beyond that, you have to surround yourself with good advisors, including board members. They were helpful in making sure we were taking a step back at the right times and not just focusing on the day-to-day so much that we missed something. You have to learn to look at the company not just as a snapshot but as a movie that’s playing out.

I imagine that one of the biggest challenges of scaling that fast is finding enough great people who understand what you’re building, and creating the right structure to get the best out of them. Although AI founders today can probably get more leverage on people than during the 1990s, great talent is still essential.

What was your approach to recruiting and organizing talent, and how did it evolve with the business?

Well, it definitely evolved. In the early days, when we were just a couple dozen people, it was about surrounding ourselves with true believers. This was before people knew what the internet was, so there weren’t that many people interested in it. We were looking for people who wanted to be a part of the journey and could add value to it.

When headcount got into the hundreds, we started to be a bit more precise in terms of the roles we needed. You start to run searches for roles and look in a more structured, disciplined way.

When we got into the thousands, and things really started accelerating, I realized that as the CEO, I couldn’t be involved in everything. And so I needed to shift my mindset to spend the majority of my time on recruiting. It might not have been 50% of my actual hours, but it was more than 50% of my attention.

A lot of my job in those days was not just promoting AOL but evangelizing the internet. I’d travel a lot and speak at a lot of conferences – Allen&Co in Sun Valley and others. I always had my radar on: Who’s going to be there? Are there people who might be partners in a way that works for us and works for them? Is there anyone I’m really impressed with that I can convince to leave what they’re doing and join us?

Every meeting I was in, every conference I was attending – whatever it was that I was doing – looking for great people was always on my agenda. With the right people and the right focus, anything is possible.

You mentioned that as the company scaled, you felt you couldn’t do everything anymore. The pendulum in tech seems to have swung towards CEOs feeling like they should micro-manage more and have their hands on every part of the business. Why did that feel like the wrong fit for you?

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]]><![CDATA[Why Being a Generalist VC Is a Competitive Advantage (Aydin Senkut, Founder & Managing Partner at Felicis Ventures)]]>https://www.generalist.com/p/why-being-a-generalist-vc-is-a-competitive-advantagehttps://www.generalist.com/p/why-being-a-generalist-vc-is-a-competitive-advantageTue, 09 Dec 2025 13:03:49 GMT

“Every single good thing happened in my life on the back of some disappointment or failure. Those rejections became rocket fuel.” — Aydin Senkut

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Thank you to our sponsor, Guru: The AI source of truth for work.

Two decades ago, Aydin Senkut was a first-time fund manager with a thin track record to show prospective backers. LPs didn’t believe a solo GP, especially one without experience at a legacy firm, could build a lasting franchise.

They were wrong. Today, Felicis is a Silicon Valley mainstay on its 10th fund, a $900M vehicle. Across its history, Felicis has backed a slew of winners, including Shopify, Canva, Crusoe, and dozens of other billion-dollar outcomes. Rather than specialize over time, Aydin has remained a true generalist, investing across markets and cycles. In this conversation, we dig into the frameworks, stories, and philosophies that shaped Felicis into what it is — and where Aydin believes the next decade of technology is heading.

We explore:

  • How growing up in Turkey with entrepreneur parents shaped Aydin’s approach to risk and investing

  • Lessons from working alongside Larry Page and Sergey Brin during Google’s early days

  • Why Felicis deliberately chose a generalist strategy when most VCs were specializing

  • How international experience became a competitive advantage in finding global winners

  • The mathematical case for portfolio diversification (50-70 companies per fund)

  • Why valuation concerns are often overblown when revenue growth is exponential

  • Felicis’s aggressive AI investment strategy and what other investors are missing

  • The future of robotics and physical AI through companies like Skild AI

  • Why learning and adapting rapidly is Felicis’s constitutional principle

Explore the episode

Timestamps

(00:00) Introduction

(03:09) How Aydin made his way to Silicon Valley

(06:15) What he learned from his entrepreneurial parents

(08:55) Learnings from the early days at Google

(15:05) The childhood roots of his investing philosophy

(16:31) Why rejection became a catalyst for his venture career

(19:28) Strategy behind Felicis’s first $41M fund

(25:44) How his international background became an investing edge

(28:17) How Aydin approaches diversification at scale

(32:08) How he sizes investments based on conviction

(33:15) Generalist vs. specialist investing

(38:23) Why founders are the foundation

(42:48) Why success may look different than expected

(43:46) The Felicis journey

(48:18) Why Felicis is going all in on AI

(54:54) Why entry point matters less than potential

(57:33) How the AI bubble debate misses the point

(59:47) What makes Skild AI a standout company

(01:04:58) The AI bets Felicis missed

(01:07:55) How missing Airbnb and Uber led to backing Adyen

(01:11:20) Final meditations

Follow Aydin Senkut

LinkedIn: https://www.linkedin.com/in/aydins

X: https://x.com/asenkut

Resources and episode mentions

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People

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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.

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]]><![CDATA[54 Books to Read In 2026]]>https://www.generalist.com/p/54-books-to-read-in-2026https://www.generalist.com/p/54-books-to-read-in-2026Thu, 04 Dec 2025 16:19:27 GMT

Friends,

This is one of my favorite questions to ask:

If you had the power to assign a book for everyone on Earth to read and understand, what would you choose?

Long-time supporters of The Generalist will know it’s my preferred way to wrap up a Modern Meditations interview or a podcast episode. So, why do I like it so much? Isn’t it just a convoluted way of asking “What’s your favorite book?”

Not quite. (Though that is a pretty great question too, no matter how staid.) There is, I find, something useful about framing the prompt in this way, and asking people not just what books they liked but those they considered deeply important. Plenty of authors can grant us pleasure, but which ones created works that truly merited the world’s attention?

It also opens up the possibility for all kinds of enjoyable subplots. Will someone indulge in the hypothetical chance to promote their own work, thereby locking in a casual 8 billion in new book sales? How might they tilt humanity toward their philosophical or aesthetic preferences? Does it seem utterly unanswerable to them, given the swarm of wonderful books the world contains? Will they reject the premise outright, as a mini-autocracy dressed up as a parlor game? Each of these answers says something, I think, about the way a person reasons.

Over the years, this question has been the source of much joy, intrigue, alpha, and wisdom to me. And so, as we near the end of this year, I took the time to compile every recommendation we’ve received across The Generalist’s written and audio interviews into a single guide, lightly edited for readability. Since it contains no recommendations or musings of my own, I feel I can say with a straight face that it is quite a wonderful document, containing the preferred reads of an eclectic but stunningly accomplished group of people. MacArthur “genius” grantees mingle with multiple Midas List winners, prominent ethical philosophers, legendary entrepreneurs, and extreme biohackers. People who have built new cities sit alongside complexity scientists, a stone’s throw from a computer science legend and former professional poker player. So read on to discover what Alan Kay, Tyler Cowen, Reid Hoffman, David Krakauer, Laura Deming, Bryan Johnson, Katherine Boyle, and others think the world should read.

As you consider how you want to spend your time in 2026, I hope this collection might provide inspiration and open some new avenues for your curiosity to explore.

The “best fund you’ve never heard of” is hiring

Two years ago, The Generalist published its case study on Hummingbird. It was the story of a fund that had studiously avoided publicity, while putting together one of the most impressive track records in the asset class, all by focusing obsessively on finding the top 0.1% of founders. It became our most popular piece at the time.

As I shared with readers earlier this year, I became so intrigued by Hummingbird’s psychological approach that I took on a venture partner role. In part, I saw it as a chance to continue studying how the most interesting fund I’d come across functioned from the inside. How exactly did they interact with founders? What questions did they ask? Why? What traits did they look for at an even more granular level?

Since spending more time with the team in this capacity, I’ve been struck by just how deep Hummingbird’s craft goes. (Hopefully, I can share some of these discoveries in a future piece.)

For now, though, an opportunity: Hummingbird opened the application for its analyst program a few weeks ago. It’s exactly the kind of role I would have wanted to discover earlier in my venture career and, based on my experience, a rare one. If you’re interested in learning a differentiated investing lens at one of the best-performing funds in the world, you can apply here.

As you can probably tell from the above, I think it’s a rather good opportunity. Now, onto the piece.

Learn more

54 Books to Read In 2026

Reid Hoffman, Greylock

If this is a one-shot opportunity, then I’d probably want to pick a book that has a proven track record for timelessness and universality – in other words, something that I believe could make a lasting impact on the greatest number of readers.

So I think I’d choose Viktor Frankl’s account of his life in a Nazi concentration camp, Man’s Search for Meaning. Originally published in 1946, it’s a book that readers continue to find relevant, decade after decade, because of its emphasis on how, even in circumstances of unimaginable suffering and inhumanity, where despair is a perfectly rational response, we can still find ways to be resilient and resourceful. The key is to maintain hope for the future and a sense of purpose that goes beyond the alleviation of our own suffering and is instead enmeshed in the human connections and relationships that give our lives meaning.

Roelof Botha, Sequoia Capital

The book I hand out to people is Man’s Search for Meaning by Viktor Frankl. Frankl was a Holocaust survivor, and the book doesn’t detail the horrors of what he endured, but it talks about the insight he had into human nature.

There are competing views of what motivates us. There’s the hedonistic view that we pursue pleasure. Then there’s Adler, who thought we pursue power, and that’s where we derive value and meaning in our lives. Frankl developed logotherapy based on the belief that purpose is what drives us. That purpose could be a mission, a family member, or a pursuit. But there’s something that keeps us going.

Frankl had this insight before he went into the concentration camps, but it was honed by his experience there. He saw, for example, that the death rate in the camp increased around Christmas and the New Year. Not that any of the captives were Christian, but it was a remembrance of time with family. People lost hope during those windows and basically gave up on life because they had no reason to live anymore. Frankl has this phrase, “Someone who has a ‘why’ will bear almost any ‘how.’”

When we think about our own personal life experiences, I think we need to understand meaning. Because money is not going to bring you happiness. It buys luxuries, but it’s not going to bring you happiness. I think it’s very important for people to define their personal happiness.

When it comes to building a company, mission-driven companies just do better. You can’t staple a mission onto a company if it’s inauthentic. It has to be truly authentic. Natera is a good example. It started with the CEO wanting to help people have healthy babies, and though it’s expanded, it remains such a mission-driven company. That mission defines the kind of decisions they make inside the company and gives people comfort when they’re pulling all-nighters or doing incredibly hard work to remember the purpose they’re serving.

Claire Hughes Johnson, Stripe

To the Lighthouse is an iconic novel. On one level, it’s about a family, but it’s about much more than that. It’s about death, existence, the human condition – and how we can be so close to someone without really knowing them.

From a formal perspective, Woolf immerses you in her characters’ innermost thoughts without using much dialogue and creates a dreamlike state. From the reader’s perspective, you’re surfing different perspectives, different inner monologues, and the passage of time. Nearly a hundred years after it was published, it’s a work that still feels innovative and disruptive.

Chris Miller, Author of Chip War

I really admire Dan Yergin’s The Prize. It’s a history of the last two hundred years through the lens of the most important industry of that period: oil. It’s got it all: the personalities, business, geology, politics, and wars that defined that period. I think you could do no better in understanding why the world is structured the way it is than by reading that one book.

Rebecca Kaden, Union Square Ventures

I’d choose Pale Fire by Vladimir Nabokov. It’s a wild, unusual book by an unusual person and author. It’s structured as a fictional 999-line poem and then a fictional line-by-line annotation of it. It requires a lot of choices at every turn – including how to read it (the poem and then the annotation? Flipping back and forth?). So it makes you work for it. But at heart, it’s an incredible work about the relevance of stories, how thin the line is between our reality and the narratives we tell ourselves, and the importance of those narratives for sustenance. It’s also about imagination and creation, and that whole worlds can be created by powerful ideas. It asks the reader to constantly figure out what is real and what is not, or to give up and accept the uncomfortable state of not knowing, thereby embracing the story. I love reading across genres, but nothing deepens my thinking and takes my mind to new places like great works of fiction.

Toby Ord, Oxford University

Practical Ethics by Peter Singer is a really good, no-nonsense approach to thinking about ethics. It really helps show you how to reason about all kinds of issues with an open mind, without assuming that our current ethical intuitions are the be-all and end-all.

In that vein, Derek Parfitt mentions that there’s really only been a couple of generations in which people have made what he calls “non-religious ethics” their life’s work. If you look at the whole history of philosophy, almost all ethical discussions occurred within a religious context where the set of possible answers had to align with what had been thought thousands of years earlier. There had really only been a couple of exceptions. And only a short period of time since that kind of inquiry became more widespread. Parfitt saw that as a reason to be optimistic about the possibility of making substantial moral progress.

Sara Seager, MIT

I would choose The Giver. It’s required middle school reading in parts of America. That’s actually how I came across it: discovering it when my kids were in school. It’s absolutely astonishing. You’re reading this book set in what is supposed to be a utopia. But partway through, there’s a crack in the facade.

I feel like we’re all living in a bubble of this kind, and every once in a while, there’s a crack. It’s our job to look through the crack and figure out what it means for us and those around us.

Martin Casado, a16z

I’d pick The Weirdest People in the World by Joseph Henrich. It basically says that the Protestant Revolution changed the way we associated ourselves and each other. We used to be very, very tribal, which impacts trust. The Protestant Revolution forced nuclear families and separation, and those shifts required us to be pro-social.

It has a second thesis on how free markets produce pro-social behavior. The reason I’d choose it is that if you look at the long arc of humanity, the ultimate enemy is entropy. That never goes away, and I don’t think any single tribe solves that. So you need pro-social behavior to actually undertake planetary-level innovation, and to do that, we need to understand how we operate when it comes to trust, coordination, and cooperation.

Beyond that, I’d mention David Deutsch’s The Beginning of Infinity, Taleb’s Statistical Consequences of Fat Tails, Hamming’s The Art of Doing Science and Engineering, Fukuyama’s The End of History and the Last Man.

Fukuyama has since recanted on the view in the book, but it’s this Hegelian take on humanity, the conclusion of which is that liberal democracy is the end of history. I think that’s being questioned right now, but Fukuyama does such a great job of outlining the Hegelian perspective and showing there is this evolution of humans, and we are continuing to get better. Fukuyama thought that maybe we’d arrived; the conclusion now is that we haven’t. But I love the idea that, as a species, we’re improving how we interact, how we make policies, and how we socialize.

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