46 episodes
The Token Budget Problem Nobody Is Talking About (Matan Grinberg, Co-Founder & CEO of Factory)
2026-06-30 | 1h 16 mins.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 AI
Why Matan believes there will always be more problems to solve, even as AI becomes more capable
The resource allocation problem facing CEOs as they balance headcount, compute, and token budgets
Why Factory is betting on model independence and Matan’s take on the SpaceX-Cursor deal
Why Matan pushes back on conflating open models with “Chinese models” and wants a stronger open-model ecosystem
The identity crisis that followed Matan’s decision to leave physics
Lessons from Factory’s first few years, including learning to push back and identify gaps in his own knowledge
Factory’s culture, values, and Matan’s partnership with co-founder Eno Reyes
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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.
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Transcript: https://www.generalist.com/p/the-token-budget-problem
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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
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Follow Matan Grinberg
LinkedIn: https://www.linkedin.com/in/matan-grinberg
X: https://x.com/matanSF
Website: https://factory.ai
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Resources and episode mentions: https://www.generalist.com/p/the-token-budget-problem
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.Own or Be Owned: Why Every Company Needs Its Own AI Model (Yash Patil, Co-Founder & CEO of Applied Compute)
2026-06-23 | 1h 8 mins.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 models
What it was like inside OpenAI the weekend the board fired, and then reinstated, its CEO
Why post-training is where competitive advantage is now being built, and what reinforcement learning with verifiable rewards actually is
Why evals have become the new production environment, and why companies will never share them with frontier providers
How a specialized model built for DoorDash outperformed frontier models on a narrow, high-value task
Why cost, not capability, is now the primary driver pushing companies toward custom models
Why Yash believes AI’s transformation of the economy will unfold over decades, and why near-term fears about mass job displacement are misplaced
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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.
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Transcript: https://www.generalist.com/p/own-or-be-owned-why-every-company
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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
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Follow Yash Patil
X: https://x.com/ypatil125
Website: https://yashpatil.me
LinkedIn: https://www.linkedin.com/in/yash-s-patil
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Resources and episode mentions: https://www.generalist.com/p/own-or-be-owned-why-every-company
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.What America Is Missing Between Sanctions and Nuclear War (Bryon Hargis, Co-Founder & CEO of Castelion)
2026-06-02 | 1h 16 mins.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.
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In our conversation, we explore:
Why Bryon believes building missiles is paradoxically essential to maintaining peace
The game theory behind warfare and why tit-for-tat strategies require credible middle-ground responses
How China’s 2021 hypersonic test revealed not just a capability gap but a manufacturing and cost advantage
Why traditional aerospace processes—optimized for low risk and high cost—can’t compete with rapid iteration
What 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 choice
How focusing on manufacturability and cost over maximum capability can produce more effective deterrence
Why the person who adapts faster in warfare always wins, and how that shapes Castelion’s philosophy
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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.
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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
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Follow Bryon Hargis
LinkedIn: https://www.linkedin.com/in/hargsb
X: https://x.com/hargsb
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Resources and episode mentions: https://www.generalist.com/p/what-america-is-missing-between-sanctions
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.“Our Goal Is to Build an Electrical Engineer.” (Davide Asnaghi, Co-Founder & CEO of Diode)
2026-05-19 | 1h 12 mins.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 competitiveness
What 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 weeks
The three-week YC pivot that transformed Diode from a design validation tool into a full-stack manufacturer
Why circuit boards are the “forgotten middle child” between silicon and software
How Diode partners with Anthropic to make LLMs better electrical engineers
What it takes to build a hardware company in 2025—and why the talent bar must stay incredibly high
How Italian, American, and Chinese cultures shaped Davide’s approach to entrepreneurship and manufacturing
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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.
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Transcript: https://www.generalist.com/p/our-goal-is-to-build-an-electrical-engineer
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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
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Follow Davide Asnaghi
LinkedIn: https://www.linkedin.com/in/d-asnaghi
X: https://x.com/davideasnaghi
GitHub: https://hexdae.github.io
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Resources and episode mentions: https://www.generalist.com/p/our-goal-is-to-build-an-electrical-engineer
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.Investing Like A Mystic: How Cyan Banister Finds Outliers (Co-Founder of Long Journey Ventures)
2026-05-05 | 1h 13 mins.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 experiments
The strange, profound experiences that led her to question and ultimately move beyond her atheism
How scanning Wi-Fi networks in a Four Seasons café led her to Flock Safety, last valued at $8.4 billion
Long Journey Ventures’ “Biz, Tizz, and Rizz” framework for identifying exceptional founders and why the trifecta is rare
How AI will enable the age of the polymath
Why she believes brain-computer interfaces are closer than most people think
Why 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
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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
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Follow Cyan Banister:
LinkedIn: https://www.linkedin.com/in/cyanb
X: https://x.com/cyantist
Newsletter: https://uglyduckling.substack.com
Website: https://cyanbanister.com
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Resources and episode mentions: https://www.generalist.com/p/investing-like-a-mystic-cyan-banister
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email jordan@penname.co.
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About The Generalist
“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.
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