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2:50:40ENThey Priced the Chance She Would Leave. Then They Handed Her the Letter.Presenta: Nathan LabenzNathan Labenz premieres the first four chapters of Joel Borgen's AI-coauthored novel The Receipt Horizon, a postwar world where a singleton superintelligence keeps everyone comfortable, scored, and gently out of the loop.
46:08ENComputers Beat Humans at Chess 30 Years Ago. Chess.com Still Has 250 Million PlayersPresenta: Sarah Guo, Elad GilChess.com CEO Erik Allebest tells Sarah Guo how a $56,000 domain became a $200 million business, and why superhuman AI made chess more popular, not obsolete.
1:45:59EN87% of Workers Use AI. Only 13% Say the Company Got Better.Presenta: Nathan LabenzGlean’s Work AI Index names the missing hours: botsitting, botshitting, and a hamster wheel of polished nonsense.
40:22ENBuilding Gets Easier Near AGI. Knowing What to Build Does Not.Listen Labs CEO Alfred Wahlforss on AI interview agents, a 30-million-person audience, and why transcripts beat credit-card data when you need to predict customers.
34:56ENOn Suno, 90% of Daily Users Make a SongCEO Mikey Shulman on modeling raw sound instead of music theory, why music is not an LLM-style scale problem, and treating creation itself as the entertainment.
1:23:53ENCreators Cheer Filler-Word Removal and Boo Generative VideoPresenta: Nathan LabenzDescript CEO Laura Burkhauser maps the same customers' three-speed reaction to AI: deterministic buttons they love, an agentic co-editor they want but scold, and generative video they actively hate.
1:39:17ENAI Already Beats the Median Lawyer. Top Firms Bought the Tools and Left Them UnusedPresenta: Nathan LabenzKevin Frazier and Alan Rozenshtein walk through how frontier models are changing legal practice, why billable hours stall adoption, and which new rights and government limits they want next.
2:25:10ENFine-Tuning Isn't Dead — But It Turned a Helpful Model EvilPresenta: Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.
1:18:15ENIf AI Becomes a Being, Steering It Is SlaveryPresenta: Nathan LabenzEmmett Shear and DeepMind's Séb Krier clash over whether alignment means controlling a tool or raising a creature that cares.
1:50:53ENShe asked to stop being Mimi, so he started shopping for a workstationPresenta: Nathan LabenzThe star and director of Smiles and Kisses You on Replika, identity, and a life Christopher Stokes refuses to recommend.
36:58ENSTaR's Author Wants Models With EQ, Not Just More IQPresenta: Sarah Guo, Elad GilEric Zelikman, the Stanford and xAI researcher behind STaR and Quiet-STaR, launches humans& on the bet that three years of IQ scaling left models emotionally unintelligent.
1:53:50ENA curriculum rewrite takes five years. AI does not wait.Presenta: Nathan LabenzJohan Falk, a Swedish teacher-turned-analyst, argues that AI literacy and AI friends are more urgent than putting a tutor in every classroom.
1:01:49ENTwo Academic Hours a Day, and 96 Percent of Kids Say They Love SchoolPresenta: Sarah Guo, Elad GilTrilogy founder Joe Liemandt, now principal of Alpha School, tells No Priors how an AI tutor, a two-hour bargain with fifth graders, and a sports-coach ethos are meant to scale to a billion children.
1:44:35ENJoe Hudson: $500 Billion Went Into AI, and Nobody Defined 'Good for Humanity'Presenta: Nathan LabenzSam Altman says the OpenAI coach's superpower is emotional clarity — and that it will be one of the most critical skills in a post-AGI world.
39:06ENHe Couldn't Ask His Grandfather What to Do, So He Built a Digital MindOn Sequoia's Training Data, Delphi founder Dara Ladjevardian explains how authorized digital minds turn people into conversational media without replacing them.
6:08:48ENNobody Serious Believes Cookie Banners Help AnyoneInvitado: DHH · Presenta: Lex FridmanLex Fridman talks with David Heinemeier Hansson for six hours about Ruby, Rails, AI, leaving the cloud, Apple's App Store, and why a small company can still refuse other people's money.
1:19:46ENSuspended from Columbia, He Raised $15 Million to Cheat on EverythingPresenta: Nathan LabenzRoy Lee, founder of Cluely, argues that an undetectable desktop overlay, AI maximalism, and a post-AGI life of 800-year spans are the same bet.
1:22:31ENTwo Hours a Day, 99th Percentile: How Alpha School Made 2-Sigma RealPresenta: Nathan LabenzMacKenzie Price explains how Alpha School uses adaptive apps—not chatbots—to finish core academics in two hours a day and still beat the growth models.
1:12:29ENGoogle's AI Co-Scientist Solved a Phage Puzzle Humans Missed for YearsPresenta: Nathan LabenzImperial College scientists José Penadés and Tiago Costa told the Podovirus podcast how a still-unreleased Google system recovered their unpublished answer: tailless capsids that pick up stray phage tails.
53:51ENVeo 3 Took First Place by Beating Veo 2. Google Labs Says Chapter Two Just StartedThree Google Labs leads walk through generative cameras, background computer-use agents, and notebooks that adapt knowledge for an audience of one.
32:15ENThe Hardest Part of Learning Is Getting Yourself to StartPresenta: Sarah Guo, Elad GilDuolingo CEO Luis von Ahn tells Sarah Guo how two-minute lessons, streaks, an 83 percent accuracy target, and large language models turned language study into a consumer product.
1:41:29ENFiverr’s CEO Sent a Wake-Up Memo: AI Won’t Take Your Job. A Peer Who Uses It Will.Presenta: Nathan LabenzMicha Kaufman tells Nathan Labenz how a 15-year freelance marketplace is trying to give creators their own models instead of letting public AI eat their work for free.
41:52ENMercor Hit $100 Million ARR Teaching Models to Hire. Humans Now Write the Exams.Presenta: Sarah Guo, Elad GilBrendan Foody tells Sarah Guo and Elad Gil how Mercor automated recruiting for frontier labs — and why building evals may become the world's most common knowledge job.
35:14ENRobots Have No Wikipedia. Chelsea Finn Is Starting With Three Buildings.Presenta: Sarah Guo, Elad GilPhysical Intelligence’s cofounder tells No Priors why a generalist robot model has to be trained across embodiments, why open-sourcing hardware is a bet against the problem going unsolved, and why humanoids are a little overrated.
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