The Generalist

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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Transcript: https://www.generalist.com/p/how-a-20-person-startup-won-gold

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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

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Follow Tudor Achim

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

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

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Resources and episode mentions: https://www.generalist.com/p/how-a-20-person-startup-won-gold⁠

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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Thank you to the partners who make this possible

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

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Transcript: https://www.generalist.com/p/the-case-for-autonomous-networks

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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

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Follow Anil Varanasi

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

X: https://x.com/acv

Website: https://anilv.com

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Resources and episode mentions: https://www.generalist.com/p/the-case-for-autonomous-networks⁠

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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.

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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

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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.

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Transcript: https://www.generalist.com/p/why-one-superintelligence-is-more

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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

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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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Resources and episode mentions: https://www.generalist.com/p/why-one-superintelligence-is-more⁠

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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Thank you to the partners who make this possible

Brex: The intelligent finance platform.

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

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Transcript: https://www.generalist.com/p/karol-hausman-physical-intelligence

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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

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Follow Karol Hausman

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

X: https://x.com/hausman_k

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Resources and episode mentions: https://www.generalist.com/p/karol-hausman-physical-intelligence

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings

Brex: The intelligent finance platform.

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Transcript: https://www.generalist.com/p/americas-electric-power-grid-is-broken⁠

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Timestamps

(00:00) Introduction to Zach Dell and Base

(02:08) The Hawaiian lava field solar project and early energy curiosity

(07:03) Investing vs. operating

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

(14:27) Lessons from his parents

(18:20) The loneliness of solo founding and the value of co-founders

(23:45) Justin’s strengths as a co-founder and how their partnership formed

(29:55) Why Base became the obvious focus

(32:08) The original vision and the three reversals

(34:58) The US power grid and what makes Texas different

(39:19) Why batteries matter and what Base is building

(41:12) How Base works in two market types

(45:10) Base’s core product

(46:50) The software behind Base’s battery network

(48:20) Base’s partnerships with battery cell makers

(49:51) The Gen 2 hardware mistake and the lesson in risk management

(51:08) Dino’s strengths as Head of Hardware

(52:36) Base’s positioning as grid infrastructure

(53:29) Building a beloved energy brand

(58:01) How hiring at Base has evolved

(1:01:10) AI workflows at Base

(1:03:00) Zach’s dedicated deep work time

(1:05:54) Final meditations

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Follow Zach Dell

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

X: https://x.com/ZachBDell

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Resources and episode mentions: https://www.generalist.com/p/americas-electric-power-grid-is-broken

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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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.

—

Transcript: https://www.generalist.com/p/everyone-is-betting-on-bigger-llms

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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

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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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Resources and episode mentions: https://www.generalist.com/p/everyone-is-betting-on-bigger-llms⁠

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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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.

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Transcript: https://www.generalist.com/p/how-bolt-survived-an-85-revenue-crash

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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

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Follow Markus Villig

X: https://x.com/villigm

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

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Resources and episode mentions: https://www.generalist.com/p/how-bolt-survived-an-85-revenue-crash

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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

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Transcript: https://www.generalist.com/p/the-private-company-bringing-nuclear

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Timestamps

(00:00) Introduction to Scott Nolan

(03:11) General Matter’s mission to rebuild U.S. enrichment

(05:06) How the U.S. lost its edge

(06:28) The nuclear fuel cycle explained—and where enrichment fits

(08:30) Scott’s background: From SpaceX and Founders Fund to General Matter

(13:54) Lessons from SpaceX

(17:32) How Scott’s focus evolved over 13 years at Founders Fund

(20:57) How Scott landed on nuclear enrichment

(25:55) Why nuclear energy was off the radar—until recently

(30:07) Finding the right partner: Scott and Lee’s collaboration

(32:01) What downblending means and why it matters

(33:26) How U.S. uranium enrichment quietly came to an end

(38:32) The Russian uranium ban and the 2028 supply cliff

(40:38) How General Matter plans to compete

(43:05) Building a world-class team

(46:38) The market for enriched uranium

(49:31) Future bottlenecks

(50:53) What the U.S. needs to actually scale nuclear energy

(52:40) Uranium supply constraints

(54:14) LEU vs. HALEU: the fuels powering old and new reactors

(57:01) Why 20% enrichment is a critical threshold

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

(1:04:34) Legislation and executive orders easing nuclear friction

(1:09:42) The $900 million Department of Energy award

(1:11:00) Why mission matters most

(1:14:12) Final meditations

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Follow Scott Nolan

X: https://x.com/ScottNolan

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Resources and episode mentions: https://www.generalist.com/p/the-private-company-bringing-nuclear

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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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

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Follow Ben Nowack

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

X: https://x.com/bennbuilds

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Resources and episode mentions

—People—

• Vladimir Syromyatnikov: https://en.wikipedia.org/wiki/Vladimir_Syromyatnikov
• Tristan Semmelhack on LinkedIn: https://www.linkedin.com/in/tristan-semmelhack-6a1ba0149
• Baiju Bhatt on LinkedIn: https://www.linkedin.com/in/bprafulkumar
• Marc Andreessen on X: https://x.com/pmarca
• J.P. Morgan: https://en.wikipedia.org/wiki/J._P._Morgan
• Ric Burton on LinkedIn: https://www.linkedin.com/in/richardjburton

—Other resources—

• Reflect Orbital: https://www.reflectorbital.com
• Zipline: https://www.zipline.com
• Cassegrain: https://en.wikipedia.org/wiki/Cassegrain_reflector
• Advanced Composite Solar Sail System (ACS3): https://www.nasa.gov/mission/acs3
• Znamya: https://en.wikipedia.org/wiki/Znamya_(satellite)
• Aetherflux: https://www.aetherflux.com
• Elon Musk’s post on X about building a sentient sun: https://x.com/elonmusk/status/1985048731818094950
• Denali: https://en.wikipedia.org/wiki/Denali

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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

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

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Transcript: https://www.generalist.com/p/nothings-carl-pei-on-building-a-1b-smartphone-company

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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

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Follow Carl Pei

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

X: https://x.com/getpeid

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Resources and episode mentions: https://www.generalist.com/p/nothings-carl-pei-on-building-a-1b-smartphone-company

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].