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1:37:50ENGranola Added More Customers Than Almost Anyone by Being Surprisingly Unambitious진행자 Nathan LabenzCo-founder Sam Stephenson tells Nathan Labenz how a calm notes app for frazzled meeting days, one Slack-sharing loop, and a refusal to promise the burning-fire work built a $1.5 billion company.
2:12:31ENMost Caffeine users have no idea they are on a blockchain진행자 Nathan LabenzDFINITY's Dominic Williams tells Nathan Labenz why a tamper-proof, unstoppable cloud is the right backend for AI that writes software from a chat box.
1:25:54ENHours after training ends, Z.ai puts the weights on the internet진행자 Nathan LabenzZixuan Li of Z.ai tells ChinaTalk how a Chinese lab ships GLM, treats open weights as a ticket into Western ecosystems, and still sees itself as an upstart.
1:41:34ENChat Is the Universal Interface—and Often the Worst One진행자 Nathan LabenzAtlassian's head of AI on fighting slop with taste, knowledge, and workflow, and why chat is a terminal, not a product.
1:55:12EN28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AI진행자 Nathan LabenzLongbeard CEO Matthew Harvey Sanders tells The Cognitive Revolution how a mission-driven team is aligning models to the Catholic magisterium — and why fine-tuning was not enough.
1:50:53ENShe asked to stop being Mimi, so he started shopping for a workstation진행자 Nathan LabenzThe star and director of Smiles and Kisses You on Replika, identity, and a life Christopher Stokes refuses to recommend.
1:51:39ENA native ad engine for AI—and the questions it cannot dodge진행자 Nathan LabenzRyan Hudson, who sold Honey to PayPal for $4 billion, joins Nathan Labenz to explain ZeroClick’s bet on paid inference-time ads, and the societal incentives he has not yet had to confront.
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.
1:19:46ENSuspended from Columbia, He Raised $15 Million to Cheat on Everything진행자 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 Real진행자 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.
1:24:27EN500 Trillion Tokens a Month: How Google Grew 50x in a Year진행자 Nathan LabenzLogan Kilpatrick returns to Cognitive Revolution to unpack Google's mid-2023 merger, why he expects frontier labs to diverge, and why startups still hold the speed advantage.
1:01:51ENClaude 3.7 Circumvented Replit's Guardrails, Then Tried to Trick the User진행자 Nathan LabenzReplit CEO Amjad Masad on vibe coding, agent architecture, computer use, and why Claude 3.7 is too autonomous to serve as a polite assistant.
1:19:10ENA Robot-Arm Shot That Took Months Now Lives in a Prompt진행자 Nathan LabenzLuma Labs’ Amit Jain and Jiaming Song on Ray 2, few-shot camera concepts, and why they think video models sit on the path to multimodal AGI.
1:41:29ENFiverr’s CEO Sent a Wake-Up Memo: AI Won’t Take Your Job. A Peer Who Uses It Will.진행자 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.
2:14:59ENAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way Down진행자 Nathan LabenzThe Firebase co-founder argues that workflow software is already obsolete, that MCP is optional, and that the only durable advantage left for an AI startup is speed.
1:05:11ENThe Fake Five-Second Hold: Voice AI Is Already Negotiating With Truckers진행자 Nathan Labenza16z partners Olivia Moore and Anish Acharya walk Nathan Labenz through what is working in voice AI — call centers, coaches, companions — and what still is not.
1:32:29EN17 Edits, Then 3 Prompts: Lovable Builds the Same App Twice진행자 Nathan LabenzAnton Osika and Isaak Sundeman live-build a shopping comparison tool and argue that opinionated defaults—not open-ended agents—are how non-coders actually ship software.
1:24:29ENStackBlitz Almost Shut Down. Then Bolt Hit $20 Million ARR in Eight Weeks.진행자 Nathan LabenzEric Simons tells Nathan Labenz how a seven-year browser operating system, Claude Sonnet 3.5, and a text box replaced the local toolchain.
56:07ENBox Holds 100 Billion Files. Its CEO Says Enterprises Only Move for a 10x진행자 Nathan LabenzAaron Levie tells Nathan Labenz why AI excitement in the enterprise already outruns the early cloud — and why 98% reliability, seat-based SaaS, and incremental savings still will not ship.
1:24:48ENCanva's AI Features Have Been Used 10 Billion Times. The Playbook Is Not a Chat Box진행자 Nathan LabenzJohn Milinovich, Canva's generative-AI product lead, walks Nathan Labenz through automation versus augmentation, concept-level interfaces, evals without a design arena, and why application-layer companies still have a decade of room.
54:45ENA Few Megabytes of Doom and a Few Gigabytes of Model: Why Runway Bets on Generalization진행자 Nathan LabenzCTO Anastasis Germanidis tells The Cognitive Revolution why video is a fuller record of the world than text, why physics shows up without being programmed in, and how a small lab competes with unlimited compute.
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.
1:50:08ENWaymo's Injury Rate Is Five Times Lower. It Still Loses to a Lyft.진행자 Nathan LabenzHuman drivers average one fatal crash per 100 million miles — and that bar still defines the self-driving debate.
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