The Generalist

Mario Gabriele

“The future is already here. It’s just not evenly distributed.” The Generalist Podcast brings you weekly conversations with the people who live in these pockets of the future – visionary founders, prescient investors, and original thinkers. Each episode is designed to introduce you to new ideas, technologies, and markets and help you prepare for the world of tomorrow.

  1. The Token Budget Problem Nobody Is Talking About (Matan Grinberg, Co-Founder & CEO of Factory)

    vor 5 Tagen

    The Token Budget Problem Nobody Is Talking About (Matan Grinberg, Co-Founder & CEO of Factory)

    Matan Grinberg is the co-founder and CEO of Factory, an AI company valued at $1.5 billion that helps enterprises like Nvidia, Morgan Stanley, and Adobe automate software development through “Droids,” intelligent agents designed to streamline software engineering. Before Factory, Matan spent more than a decade in theoretical physics, studying string theory at Princeton and UC Berkeley. His work now centers on a different kind of complex system: how software gets built in an era of increasingly capable AI agents, open models, and shifting compute economics. In our conversation, we explore: How Emmy Noether’s theorem continues to shape Matan’s approach to technology, business, and AIWhy Matan believes there will always be more problems to solve, even as AI becomes more capableThe resource allocation problem facing CEOs as they balance headcount, compute, and token budgetsWhy Factory is betting on model independence and Matan’s take on the SpaceX-Cursor dealWhy Matan pushes back on conflating open models with “Chinese models” and wants a stronger open-model ecosystemThe identity crisis that followed Matan’s decision to leave physicsLessons from Factory’s first few years, including learning to push back and identify gaps in his own knowledgeFactory’s culture, values, and Matan’s partnership with co-founder Eno Reyes— Thank you to the partners who make this possible .tech domains: An identity for builders at their core. Brex: The intelligent finance platform. Persona: Trusted identity verification for any use case. — Transcript: https://www.generalist.com/p/the-token-budget-problem — Timestamps (00:00) Intro (03:50) Noether’s theorem explained (06:45) How the search for what’s conserved informs Matan’s work (10:53) Why there will always be more problems to solve (11:58) The resource allocation problem of the AI era (15:54) Factory’s mission: bringing autonomy to software engineering (18:28) How Factory decides what to build next (20:10) Why Factory abstracts away model choice (22:07) How Factory wins enterprise customers (23:15) Matan’s take on the SpaceX-Cursor deal (27:48) Why open-weight models matter (29:19) Anthropic’s Fable 5 release and the debate over AI guardrails (35:33) How Matan got into string theory (38:21) Working with Juan Maldacena (41:53) Startup founders vs. theoretical physicists (46:15) Rethinking physics and redefining his identity (51:29) Discovering AI and code generation (52:53) The origins of Factory (55:52) Lessons from Factory’s first few years (59:58) Learning to push back and finding the holes in his knowledge (1:03:17) Factory’s culture and values (1:08:11) Matan’s predictions for the future of AI and Factory (1:10:49) Final meditations — Follow Matan Grinberg LinkedIn: https://www.linkedin.com/in/matan-grinberg X: https://x.com/matanSF Website: https://factory.ai — Resources and episode mentions: https://www.generalist.com/p/the-token-budget-problem⁠ — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 17 Min.
  2. Own or Be Owned: Why Every Company Needs Its Own AI Model (Yash Patil, Co-Founder & CEO of Applied Compute)

    23. Juni

    Own or Be Owned: Why Every Company Needs Its Own AI Model (Yash Patil, Co-Founder & CEO of Applied Compute)

    Yash Patil is the 23-year-old founder and CEO of Applied Compute, a $1.3 billion company helping businesses train custom AI models on their own data: smaller, cheaper, and purpose-built for the work they actually do. Before founding the company, Yash dropped out of Stanford and spent two years at OpenAI working on post-training infrastructure and Codex. He left with one core conviction: every company that runs its critical workflows on someone else’s model is building on shifting sand. Applied Compute is his answer to that problem, already serving customers including DoorDash, Cognition, and Mercor. In our conversation, we explore: Why “own or be owned” is becoming existential for any company that relies on frontier AI modelsWhat it was like inside OpenAI the weekend the board fired, and then reinstated, its CEOWhy post-training is where competitive advantage is now being built, and what reinforcement learning with verifiable rewards actually isWhy evals have become the new production environment, and why companies will never share them with frontier providersHow a specialized model built for DoorDash outperformed frontier models on a narrow, high-value taskWhy cost, not capability, is now the primary driver pushing companies toward custom modelsWhy Yash believes AI’s transformation of the economy will unfold over decades, and why near-term fears about mass job displacement are misplaced— Thank you to the partners who make this possible Brex: The intelligent finance platform. Guru: The AI source of truth for work. Persona: Trusted identity verification for any use case. — Transcript: https://www.generalist.com/p/own-or-be-owned-why-every-company — Timestamps (00:00) Introduction (03:50) Fable 5 and the case for owning your own models (09:22) Why Applied Compute is betting on custom AI models (12:30) Yash's early influences and first projects (17:42) His brief time building at Stanford (19:29) Leaving Stanford for OpenAI (25:58) Inside OpenAI during Sam Altman's firing (28:18) What Yash admires about Sam Altman (29:43) Teaching models to reason (35:39) The core insight behind Applied Compute (39:40) How Applied Compute works with its customers (45:55) Why model training never ends (48:56) Why not every task needs a frontier model (51:25) The culture and people of Applied Compute (54:50) Applied Compute's training infrastructure (58:43) The coming compute crunch and other predictions (1:03:48) Final meditations — Follow Yash Patil X: https://x.com/ypatil125 Website: https://yashpatil.me LinkedIn: https://www.linkedin.com/in/yash-s-patil — Resources and episode mentions: https://www.generalist.com/p/own-or-be-owned-why-every-company⁠ — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 8 Min.
  3. What America Is Missing Between Sanctions and Nuclear War (Bryon Hargis, Co-Founder & CEO of Castelion)

    2. Juni

    What America Is Missing Between Sanctions and Nuclear War (Bryon Hargis, Co-Founder & CEO of Castelion)

    Bryon Hargis is the co-founder and CEO of Castelion, a defense startup building low-cost hypersonic missiles designed to be manufactured at scale. Before founding Castelion, Bryon spent more than a decade at Johns Hopkins Applied Physics Laboratory and nearly six years at SpaceX, where he worked on national security space programs and saw firsthand how iterative engineering and manufacturing speed could reshape aerospace. Castelion’s first missile, Blackbeard, is slated for integration on the Navy’s F/A-18 Super Hornet in roughly a year. — In our conversation, we explore: Why Bryon believes building missiles is paradoxically essential to maintaining peaceThe game theory behind warfare and why tit-for-tat strategies require credible middle-ground responsesHow China’s 2021 hypersonic test revealed not just a capability gap but a manufacturing and cost advantageWhy traditional aerospace processes—optimized for low risk and high cost—can’t compete with rapid iterationWhat Bryon learned in his first week at SpaceX (after 12 years in traditional aerospace)Why building a carrier-based, air-launched hypersonic missile as a first product was the hard but right choiceHow focusing on manufacturability and cost over maximum capability can produce more effective deterrenceWhy the person who adapts faster in warfare always wins, and how that shapes Castelion’s philosophy— Thank you to the partners who make this possible .tech domains: An identity for builders at their core. Ahrefs Brand Radar: Find your brand in AI results. Persona: Trusted identity verification for any use case. — Timestamps (00:00) Intro (04:01) Why America needs hypersonic missiles (07:13) China’s edge in hypersonics (12:05) The missing middle ground in deterrence (18:05) Preventing warhead ambiguity (19:40) How hypersonics differ from ballistic missiles (25:05) The economics of defensive vs. offensive systems (28:21) How SpaceX differs from traditional aerospace (37:40) Why Bryon chose to build in defense over space (42:42) Key factors that drove Castelion’s success (48:28) Designing Blackbeard, Castelion’s first hypersonic missile (1:01:06) The importance of lower costs and quicker manufacturing (1:10:04) Book recommendations — Follow Bryon Hargis LinkedIn: https://www.linkedin.com/in/hargsb X: https://x.com/hargsb — Resources and episode mentions: https://www.generalist.com/p/what-america-is-missing-between-sanctions — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 16 Min.
  4. “Our Goal Is to Build an Electrical Engineer.” (Davide Asnaghi, Co-Founder & CEO of Diode)

    19. Mai

    “Our Goal Is to Build an Electrical Engineer.” (Davide Asnaghi, Co-Founder & CEO of Diode)

    Davide Asnaghi is the co-founder and CEO of Diode, a Brooklyn-based startup using AI to design and manufacture circuit boards in the United States. Before Diode, Davide worked on Apple’s Special Projects Group and spent time in Hong Kong and Shenzhen studying Asia’s electronics manufacturing ecosystem. That experience convinced him that PCB design, despite powering everything from smartphones and satellites to medical devices and autonomous systems, remained one of the most overlooked layers of the tech stack. Since its founding just two years ago, Diode has landed Physical Intelligence and Saronic as customers and partnered with Anthropic to help Claude become a better electrical engineer. The company’s ultimate ambition: to make hardware as nimble as software. In our conversation, we explore: Why the West outsourced PCB manufacturing to Asia in the 2000s and why bringing it back matters for American competitivenessWhat Shenzhen’s manufacturing culture does better than Silicon Valley (and what the U.S. can learn from it)How Diode’s models can one-shot much of schematic design and compress hardware timelines from months to weeksThe three-week YC pivot that transformed Diode from a design validation tool into a full-stack manufacturerWhy circuit boards are the “forgotten middle child” between silicon and softwareHow Diode partners with Anthropic to make LLMs better electrical engineersWhat it takes to build a hardware company in 2025—and why the talent bar must stay incredibly highHow Italian, American, and Chinese cultures shaped Davide’s approach to entrepreneurship and manufacturing— Thank you to the partners who make this possible .tech domains: An identity for builders at their core. Guru: The AI source of truth for work. Brex: The intelligent finance platform. — Transcript: https://www.generalist.com/p/our-goal-is-to-build-an-electrical-engineer — Timestamps (00:00) Intro (04:15) Why Davide calls himself a copper merchant (05:53) Diode’s mission to rebuild PCB manufacturing in the U.S. (07:58) What success looks like (09:00) Growing up in northern Italy and spending a year in Minnesota (13:14) Why Italy produces fewer venture-backed founders (15:30) Why Hong Kong accelerated Davide’s learning (19:09) Silicon Valley vs. Shenzhen (22:05) What Davide learned in Apple’s Special Projects Team (24:11) Why Davide left Apple after two years (26:54) Meeting his co-founder, Lenny (29:32) How Davide uncovered the need for better PCB design and manufacturing (33:23) PCB manufacturing in Asia, and Diode’s approach (41:29) The YC pivot that changed Diode’s business (44:39) Inside Diode’s customer journey (48:10) Where the value is in electronics manufacturing, and Davide’s AGI thesis (51:30) What separates a working board from a great one (55:32) Where Diode fits in the electronics stack (59:55) Diode’s early near-death moment and long-term vision (1:02:30) Diode’s exceptionally high bar for hiring (1:04:48) Where Davide gets his best ideas (1:07:00) Final meditations — Follow Davide Asnaghi LinkedIn: https://www.linkedin.com/in/d-asnaghi X: https://x.com/davideasnaghi GitHub: https://hexdae.github.io — Resources and episode mentions: https://www.generalist.com/p/our-goal-is-to-build-an-electrical-engineer⁠ — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 12 Min.
  5. Investing Like A Mystic: How Cyan Banister Finds Outliers (Co-Founder of Long Journey Ventures)

    5. Mai

    Investing Like A Mystic: How Cyan Banister Finds Outliers (Co-Founder of Long Journey Ventures)

    Cyan Banister has built one of the most distinctive early-stage track records of the last fifteen years, with early bets on companies like Uber, SpaceX, DeepMind, Niantic, and Postmates. Today, she is co-founder and general partner at Long Journey Ventures, where she backs what she calls “magical weirdos.” Banister describes herself as a professional daydreamer, running constant thought experiments and paying close attention to signals others ignore. In this episode, she explains how that mindset translates into investing, and why many of her best opportunities have come from observation, curiosity, and a willingness to look in unlikely places. In our conversation, we explore: Cyan’s philosophy of treating life as a series of experimentsThe strange, profound experiences that led her to question and ultimately move beyond her atheismHow scanning Wi-Fi networks in a Four Seasons café led her to Flock Safety, last valued at $8.4 billionLong Journey Ventures’ “Biz, Tizz, and Rizz” framework for identifying exceptional founders and why the trifecta is rareHow AI will enable the age of the polymathWhy she believes brain-computer interfaces are closer than most people thinkWhy she says Pokémon Go was “the closest we ever came to world peace”Why she lives part-time in a retirement community and her vision for a more connected future— Thank you to the partners who make this possible .tech domains: An identity for builders at their core. Brex: The intelligent finance platform. Persona: Trusted identity verification for any use case. — Transcript: https://www.generalist.com/p/investing-like-a-mystic-cyan-banister — Timestamps (00:00) Intro (03:51) Never playing the game you appear to be playing (07:18) Practicing childlike wonder as a daily discipline (10:08) Questioning belief after her stroke (13:30) Cyan’s metaphysical experiments (23:24) Non-local consciousness and creativity (27:22) Investing with extreme openness to signals (29:05) The importance of timing in investing (32:26) Meeting Travis Kalanick (34:19) Finding Flock Safety through a chance encounter (38:23) The summer of Pokémon Go (what worked and what didn’t) (39:55) Human nature and what makes something "stick" (42:15) Brain-computer interfaces and AI’s accelerating effect (52:53) “Biz, Tiz, Riz:” her framework for evaluating founders (59:20) Why Cyan lives in a retirement community part-time (1:03:50) A unique way of finding books that speak to you (1:08:44) Final meditations — Follow Cyan Banister: LinkedIn: https://www.linkedin.com/in/cyanb X: https://x.com/cyantist Newsletter: https://uglyduckling.substack.com Website: https://cyanbanister.com — Resources and episode mentions: https://www.generalist.com/p/investing-like-a-mystic-cyan-banister — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 13 Min.
  6. The Future Of Drug Discovery Is 4 Billion Years Old (Viswa Colluru, Founder & CEO at Enveda)

    21. Apr.

    The Future Of Drug Discovery Is 4 Billion Years Old (Viswa Colluru, Founder & CEO at Enveda)

    For decades, drug discovery has shifted away from nature and toward biology-first approaches. Viswa Colluru believes that shift was a catastrophic mistake. His company, Enveda Biosciences, has raised over $500 million to build a “search engine for nature’s chemistry.” The mission is personal: he grew up around his father’s pharmacy in India and later lost his mother to a treatable cancer whose medicine his family couldn’t afford. Many life-changing medicines, including morphine, aspirin, and metformin, originated in nature, but there has never been a reliable, scalable way to systematically explore its chemistry. Colluru founded Enveda in 2019 with $55,000 of his own savings to change that. The company has since identified 18 drug candidates, with three now in clinical trials. In our conversation, we explore: Why the pharmaceutical industry abandoned nature (and why that was a massive mistake)How Enveda built a system to decode unknown molecules in natureThe deeply personal story of his mother’s battle with leukemia and how it shaped his life’s workWhy old ideas, from immunotherapy to natural products, often hold the most latent potentialHow Enveda developed 18 drug candidates for about $1 million each instead of $10-15 millionEnveda’s three leading drug candidates targeting eczema, obesity, and ulcerative colitisWhy first-in-class medicines capture the vast majority of returns in pharmaWhat competitive table tennis taught him about building companies— Thank you to the partners who make this possible Brex: The intelligent finance platform. Ahrefs Brand Radar: Find your brand in AI results. Persona: Trusted identity verification for any use case. — Timestamps (00:00) Introduction to Viswa Colluru (03:57) His father’s pharmacy and early exposure to Western and Ayurvedic medicine (07:06) Early pull toward technology (09:29) His mother’s leukemia diagnosis (14:24) Studying Biotechnology (16:07) Graduate school (17:55) Studying immunotherapy when it was unfashionable (24:23) Innovation vs. novelty (27:24) Lessons from table tennis (32:05) Joining Recursion (37:10) Learning urgency and courage (40:42) What launched Enveda (45:40) The limits of reductionist drug discovery (49:53) Chemistry-first approach (52:17) Raising $225K and investing $55K personally (56:04) Initial studies and targets (1:04:30) Three categories of leading drugs: Eczema, obesity, ulcerative colitis (1:13:27) Why GLP-1s are not the whole answer (1:18:27) Enveda’s long-term vision (1:21:31) Book recommendation — Follow Viswa Colluru LinkedIn: https://www.linkedin.com/in/viswacolluru X: https://x.com/viswacolluru — Resources and episode mentions: https://www.generalist.com/p/the-future-of-drug-discovery — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 23 Min.
  7. How a 20-Person Startup Won Gold at the Math Olympiad—Tying With OpenAI & DeepMind (Tudor Achim, CEO of Harmonic)

    14. Apr.

    How a 20-Person Startup Won Gold at the Math Olympiad—Tying With OpenAI & DeepMind (Tudor Achim, CEO of Harmonic)

    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 worldHow Harmonic uses hallucinations as a feature, not a bugHow Aristotle works and the applications beyond pure mathematicsThe reinforcement learning process that lets Harmonic generate synthetic training data and solve problems humans have never attemptedWhy Tudor believes AI could surpass human mathematicians on specific tasks within 2–3 yearsWhy the future of mathematics looks more like GitHub than academic journalsThe alternating pattern between intellect leaps and data leaps throughout scientific historyHow studying piano under an extraordinary teacher taught Tudor discipline and the value of sticking with hard problems— Thank you to the partners who make this possible Brex: The intelligent finance platform. Guru: The AI source of truth for work. Rippling: Stop wasting time on admin tasks, build your startup faster. — Transcript: https://www.generalist.com/p/how-a-20-person-startup-won-gold — 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 — Resources and episode mentions: https://www.generalist.com/p/how-a-20-person-startup-won-gold⁠ — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 5 Min.
  8. 30% Of Network Engineers Are Retiring. What Happens Next? (Anil Varanasi, Co-Founder & CEO of Meter)

    7. Apr.

    30% Of Network Engineers Are Retiring. What Happens Next? (Anil Varanasi, Co-Founder & CEO of Meter)

    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 fieldsWhy most companies over-index on technology and ignore business model innovationThe three ways companies create advantage: technology, delivery, and business modelHow Meter’s trade-in model borrows from the automotive industryWhy networking should function like electricity or water—not hardwareLessons from Japanese vending machine logistics for infrastructure deploymentThe hidden coordination problem behind vertically integrated companiesWhy Anil believes “common knowledge” is often wrongHow COVID forced Meter to abandon geographic constraints and scale nationallyThe case for fully autonomous networks in a world of exploding demand— Thank you to the partners who make this possible .tech domains: An identity for builders at their core. Granola: The app that might actually make you love meetings. Brex: The intelligent finance platform. — Transcript: https://www.generalist.com/p/the-case-for-autonomous-networks — 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 — Resources and episode mentions: https://www.generalist.com/p/the-case-for-autonomous-networks⁠ — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.

    1 Std. 11 Min.
Alle anzeigen (46)

Trailer

Bewertungen und Rezensionen

Info

“The future is already here. It’s just not evenly distributed.” The Generalist Podcast brings you weekly conversations with the people who live in these pockets of the future – visionary founders, prescient investors, and original thinkers. Each episode is designed to introduce you to new ideas, technologies, and markets and help you prepare for the world of tomorrow.

Informationen

  • Erstellt von
    Mario Gabriele
  • Jahre aktiv
    2025 - 2026
  • Folgen
    46
  • Bewertung
    Anstößig
  • Copyright
    © Mario Gabriele
  • Sendungswebsite
    The Generalist

Das gefällt dir vielleicht auch