Show Notes
I'm thrilled to share this very special episode of The Generalist—one I've been looking forward to for a long time. Today, we tackle one of the most urgent questions of our time: What should computing look like in the age of AI?
I'm joined by two extraordinary guests: Alan Kay, a pioneer of modern computing whose vision helped shape the personal computer revolution, and Anjan Katta, founder of Daylight, who's building a radically reimagined personal computer designed for deep thinking in our AI-saturated world. This conversation has been months in the making, and I couldn't be more excited to bring these two brilliant minds together.
We explore how artificial intelligence is reshaping our relationship with computers, whether current computing paradigms serve us well as AI becomes ubiquitous, and what new models of human-computer interaction we might need to thrive alongside intelligent machines.
This is a conversation about reclaiming agency in an age of algorithms—and imagining computing tools that amplify human intelligence rather than replace it. I think you're going to love it.
We explore: • Why Alan believes the "computer revolution" commercialized in the wrong direction, missing the deeper humanistic vision of early computing pioneers • How the structure of information, from pagination to platforms, shapes the way we think • How Daylight is creating a reading and writing-focused device that helps access our "prefrontal cortex" rather than our "lizard brain" • The concept of a magical medium, and how computing might help us become our best selves • Why Marshall McLuhan's media theories predicted our current technological predicament decades before it happened • The critical difference between intelligence and wisdom in computing systems, and why wisdom should be our focus • How thoughtful constraints in computing design can lead to better thinking and more meaningful interaction • The urgency of developing systems thinking in a world facing complex challenges • And much more — Transcript: https://thegeneralist.substack.com/p/why-the-real-computer-revolution-never-happened — Thank you to the partners who make this possible Augment Code: AI coding assistant that pro engineering teams love. Brex: The banking solution for startups. Generalist+: Essential intelligence for modern investors and technologists. — Timestamps (00:00) Intro (05:17) The computer revolution we never got (and what we got instead) (11:45) The value of writing and the impact of the printing press (21:34) The addition of pagination and the evolution of arguments (24:53) Why Anjan calls his idealized version of computing a magical medium (29:00) Alan’s work at PARC and early conceptions of personal computing (32:02) Moore’s Law and the impact of reality TV (37:41) How Bob Barton and Marshall McLuhan influenced Alan (42:31) The problem with labels and what Anjan found surprising about Alan (46:02) How much help is too much help? (48:18) Marvin Minsky's military robot story and the history of misunderstanding AGI (51:50) What we need help with and why wisdom is hard to scale (54:19) How Daylight approaches computing with humility and thoughtful constraints (59:13) Alan's reflections on the Dynabook concept and personal computing vision (01:01:11) The timeline of building Daylight and the idealism behind the project (01:03:14) The urgent need for different thinking (01:06:40) A second shot at rebuilding computing from the ground up (01:11:57) Final meditations — Follow Alan Kay LinkedIn: https://www.linkedin.com/in/alan-kay-12a627b/ Quora: https://www.quora.com/profile/Alan-Kay-11 — Follow Anjan Katta LinkedIn: https://www.linkedin.com/in/anjan-katta-250b232b4/ X: https://x.com/anjankatta — Resources and episode mentions: https://www.generalist.com/p/why-the-real-computer-revolution-never-happened — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
More from The Generalist
Pete Florence and I began by agreeing that his company has an excellent name. Generalist builds AI for robots, including models that can begin learning a new task from a single demonstration. We talked about dexterity, the strange business of gathering physical experience for a machine, and what we might build if robots could do much more of the work. — Every timestamp 00:00 Intro 02:24 GEN-1.5 and one-shot learning 08:55 What makes a task difficult 10:53 Dexterity in robotics 14:53 Matt Mason’s definition of a hand 17:34 Giving robots a sense of touch 20:30 Growing up in a family of technologists and scientists 22:46 What drew Pete into robotics 27:38 Generalist’s founding thesis and what sets it apart 32:17 Protecting simplicity 35:01 How Generalist’s data collection has evolved 35:30 Generalist’s scaling philosophy 39:53 Generalist’s build-versus-buy philosophy 42:15 Balancing general intelligence with commercial deployment 44:24 Why Pete is betting on dexterity 47:33 The durability of the robotics application layer 49:09 Open-weight robotics models and data flywheels 50:52 Geopolitics, safety, and alignment 52:42 The parallels between teaching humans and robots 1:00:05 The timeline for robotics progress and adoption 1:03:37 Book recommendations — Transcript: https://www.generalist.com/i/220756708/transcript — Pete’s complete reading list The Score Takes Care of Itself: My Philosophy of Leadership: https://www.amazon.com/Score-Takes-Care-Itself-Philosophy/dp/1591843472 Wooden on Leadership: How to Create a Winning Organization: https://www.amazon.com/Wooden-Leadership-Create-Winning-Organization/dp/0071453393 — Other resources Generalist: https://generalistai.com GEN-1.5: https://generalistai.com/blog/gen-1.5 Proprioception: https://en.wikipedia.org/wiki/Proprioception Cutaneous receptor: https://en.wikipedia.org/wiki/Cutaneous_receptor Fukushima nuclear accident: https://en.wikipedia.org/wiki/Fukushima_nuclear_accident The bitter lesson: https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson.pdf GEN-1: https://generalistai.com/blog/gen-1 — Where to find Pete Florence LinkedIn: https://www.linkedin.com/in/peteflorence X: https://x.com/peteflorence Website: https://www.peteflorence.com — Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
Jaan Tallinn is a founding engineer of Skype and Kazaa, and a co-founder of the Cambridge Centre for the Study of Existential Risk and Future of Life Institute. For more than fifteen years, he has been among the most consistent voices arguing that advanced AI poses an extinction-level risk to humanity.
Liam Fedus and Dogus Cubuk are the co-founders and co-CEOs of Periodic Labs, a startup building “synthesis superintelligence.” In practice, that means an AI system that closes the loop between hypothesis, experiment, and learning.
Scott Morton is the founder and CEO of Revel, a software platform for testing and controlling complex hardware systems. Before founding the company in 2024, Scott spent nearly a decade at SpaceX building control software for Falcon 9 and Starship. That experience helped him recognize a broader problem: while rockets, nuclear systems, supersonic aircraft, and other advanced machines have grown increasingly sophisticated, the software used to test and control them is often fragmented and decades old. Revel was created to close that gap. The company has raised $180 million, was reportedly valued at just over $1 billion, and counts Impulse Space and Radiant Nuclear among its customers. Its platform scales from small benchtop tests to industrial systems with hundreds of thousands of telemetry channels. Revel has also created its own programming language, RevelCode, designed to combine performance and accessibility with the runtime safety required for high-stakes physical systems.
Farooq Malik is the co-founder and CEO of Rain, a financial infrastructure company powered by stablecoins. Growing up in an immigrant family, Farooq saw firsthand the friction involved in moving money across borders. Alongside co-founder Charles Yoo-Naut, Farooq spent years building infrastructure before stablecoins became mainstream, betting that tokenized money would eventually become a foundational layer of the global financial system. Today, Rain powers card issuance, payments, and other financial products built on stablecoin rails, helping companies move money faster and operate across markets.