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1:06:47ENEighty percent of what agents do should still be ordinary code진행자 Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.
2:23:43ENHe Bought an Android, Two SIMs, and Left Claude Watching His Inbox진행자 Nathan LabenzNathan Labenz asked a dozen friends how to visit China and got two irreconcilable answers.
2:12:51ENSteve Newman’s fifteen-app stack exists so he only has to look at one screen진행자 Nathan LabenzThe Writely founder walks Nathan Labenz through a vibe-coded attention firewall, a conservative security stance, and why astonishing models still leave him far from AGI.
1:27:01ENThe $16 Trillion Services Market Is Being Bought, Not Sold To진행자 Nathan LabenzMarc Bhargava of General Catalyst explains how AI-enabled rollups turn low-margin service firms into compounding, software-like businesses.
1:28:48ENDoctors code at 45%. The model beat them by 12 points — then 4,000 physicians had to try it once.진행자 Nathan LabenzAmbience Healthcare and Cleveland Clinic walk through the AI scribe that cut pajama time, climbed ICD-10 with reinforcement fine-tuning, and won 75% voluntary use.
3:08:35ENo3 isn't AGI. Zvi Mowshowitz still put p(doom) at 70 percent진행자 Nathan LabenzOn his ninth visit to The Cognitive Revolution, Zvi Mowshowitz argues that OpenAI's o3 is a tool-use leap rather than AGI, then explains why he raised the probability of AI catastrophe anyway.
55:05EN400,000 Customers, 100 Million AI Tasks: Zapier’s CEO on Making Computers Do More Work진행자 Nathan LabenzWade Foster tells Nathan Labenz how a no-code automation company absorbed LLMs, cloned its CEO with a prompt, and is trying to turn a DIY toolkit into packaged solutions.
2:03:55ENThe More You Constrain an Agent, the More You Can Trust It진행자 Nathan LabenzAgent.ai engineering lead Andrei Oprisan tells Nathan Labenz why narrow, highly prescribed workflows beat open-ended autonomy — and how a 12-person team shipped a free agent network past 40,000 users in a few months.
1:51:00ENStart With Ten Gold Examples: A Three-Step Playbook for AI Automation진행자 Nathan LabenzThe day after OpenAI opened GPT-4o fine-tuning, Nathan Labenz unpacks a three-year method for choosing work, extracting tacit judgment, and raising model performance.
2:00:03ENPatients Rated GPT-4 More Empathetic Than Doctors진행자 Nathan LabenzAzeem Azhar of Exponential View maps the AI S-curve for Nathan Labenz: why the past always looks flat, why empathy went first, and what a million times more compute would actually change.
1:50:57ENTwenty-Eight Days After GPT-4, an AI Designed and Ran a Chemistry Experiment진행자 Nathan LabenzGabe Gomes and his Carnegie Mellon students built Coscientist, a language-model agent that plans, codes, and executes real experiments on a remote cloud lab.
1:18:39ENThe GPT-4 Red-Teamer Who Got Unstuck by a Mediocre Outline진행자 Nathan LabenzDan Shipper shows Nathan Labenz how to use ChatGPT as a copilot for thinking, not as a ghostwriter for his own voice.
1:30:21ENA Million DALL-E Images, Distilled into Twelve Minutes of Film진행자 Nathan LabenzWaymark’s Stephen Parker and Josh Rubin walk through how they turned stills from DALL-E 2 into The Frost, a narrative short, and what the next generation of video models changes.
39:02ENAI’s product advantage is consistency. Its real weakness is getting conned.진행자 Nathan LabenzNathan Labenz updates the Cognitive Revolution scouting report: jailbreaks, resume automation, Med-PaLM’s 40% radiology win, and what might follow Transformers.
1:30:29ENGPT-4 Wins Ten Times More Bill Fights: DoNotPay's Robot-Lawyer War진행자 Nathan LabenzGPT-3 thanked Comcast for twenty dollars off. GPT-4 said that was not enough — and the robot lawyer called it an arms race.
1:10:11ENTrying ChatGPT is not the same as using it진행자 Nathan LabenzRachel Woods of The AI Exchange tells Nathan Labenz what she learned from more than a hundred company calls: start inside the business, skip the annual tool contract, and expect to be using only a sliver of what the models can already do.
58:26ENSeventy Percent of the Inbox Is a Pitch: Matt Welsh on the First Wave of AI Agents진행자 Nathan LabenzThe Fixie.ai founder maps copilot versus delegation, the missing appendages into our systems, and why agents will need guardrails, memory hygiene, and probably an earpiece.
1:25:46ENDon't Make the Tools Agentic: Flo Crivello on What Production Agents Actually Need진행자 Nathan LabenzThe Lindy CEO tells Nathan Labenz that most working agents are intelligent workflows with human-designed control flow — and that scaffolding may still matter even if AGI arrives.
1:11:47ENThe Three-Hour Battlefield: Rahul Vohra on Why Email Survives and Agents Will Inherit the Inbox진행자 Jacob EffronSuperhuman's CEO explains how AI features are designed, why email addresses remain company infrastructure, and how agents may federate across the tools professionals live in.
19:31ENBuild the Factory, Not Just the Product: How Ramp Chases Bottlenecks Across the Whole Development Loop진행자 Lenny RachitskyRamp CPO Geoff Charles walks through the AI agents his team built for every stage of product development, and what they mean for the PM's role.
1:04:35ENOscar Health's AI Playbook: Translate the Bureaucracy First, Then Reinvent Care진행자 Jacob EffronMario, Oscar Health's CTO and co-founder, explains how a regulated insurer deploys LLMs today and what stands between healthcare and AI doctors.
1:46:35ENHire Your Agents Like Employees: Claire Vo's Field Guide to Running Nine OpenClaws진행자 Lenny RachitskyClaire Vo explains how she went from losing her family calendar to OpenClaw to running a team of specialized agents across her business, podcast, course and household.
17:32ENOver-Automating, Googling Doctors and Neural Nets: George Hotz Reviews Programming Memes진행자 Lex FridmanLex Fridman and George Hotz rate printed programming memes, and the jokes turn into candid talk about testing, hiring, social media and the power of neural networks.








