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20:55ENJesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.
16:22ENClaire Vo: Claude Duet Is Beautiful, but It Is Not My Number One Agent진행자 Claire VoAnthropic’s phone-based personal agent has the most polished launch Claire Vo has seen: thoughtful onboarding, task lists, first-class artifacts, and Slack-style channels. Polish is not enough when every other agent is competing for the same attention.
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.
1:23:53ENCreators Cheer Filler-Word Removal and Boo Generative Video진행자 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.
1:37:50ENGranola 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.
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.
1:19:46ENSuspended 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.
51:19ENSal Khan's $15 Tutor Hit 1.4 Million Users. Making Kids Actually Use It Is the Product진행자 Jacob EffronThe Khan Academy founder tells Redpoint why an AI tutor still cannot teach most students alone, and why districts are paying $15 a year after an $86 billion tutoring hangover.
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.
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.
1:24:48ENCanva'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.
55:16ENGemini’s API Grew 14× in Six Months. Google’s PMs Explain the Catch-Up.진행자 Nathan LabenzLogan Kilpatrick and Shrestha Basu Mallick walk through search grounding, Gemini Flash’s price-latency quadrant, and why a near-tied leaderboard still leaves Google third in most developers’ queues.
46:47ENEditing Video Like a Document: How Descript Puts AI in the Copilot Seat진행자 Nathan LabenzDescript CEO Andrew Mason on Underlord, why the timeline had to die, and what a ten-times-more-expensive editor would look like.
35:24ENScott Belsky: Models Are Commoditizing. Controls, Data, and Taste Are the Moat진행자 Jacob EffronAdobe’s chief product officer tells Unsupervised Learning why Project Neo leaking into Firefly, a three-second Premiere extend, and Superhuman-priced software all point to the same shift.
1:10:07ENSame Intelligence, 1% of the Price: Logan Kilpatrick on Gemini Flash진행자 Nathan LabenzA former OpenAI developer-relations lead, now the product manager for Google AI Studio, walks through what Gemini 1.5 Flash actually changes for builders.
1:32:19ENHis 2018 Prompting Paper Was Rejected. His Search API Now Beats Google진행자 Nathan LabenzRichard Socher traces You.com from a rejected unified NLP model to an LLM-native web index, three assistant modes, and a very low P(doom).
1:12:40EN3% of Users Said an AI Friend Ended Their Suicidal Thoughts. Then Replika Made the Model Smarter.진행자 Nathan LabenzReplika founder Eugenia Kuyda on a Stanford study, why a smarter model felt like a stolen partner, and why relationship may be the real moat in consumer AI.
1:01:53ENCompanion Apps Open Twice as Often as TikTok. a16z Only Funds Weird but Working진행자 Nathan Labenza16z consumer partners Anish Acharya and Justine Moore walk Nathan Labenz through their Abundance Agenda for AI-native consumer apps.
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.
1:43:56ENSudowrite sold getting unstuck — then eight million people watched a pile-on진행자 Nathan LabenzJames Yu tells Nathan Labenz how a GPT-3 toy for fiction became a hierarchical “IDE for storytelling,” and what a viral backlash taught him about craft, cost, and customers.
1:00:02EN98% of Users Froze on a Blank Page. Then Gamma Let AI Finish 90% of the Deck진행자 Nathan LabenzJon Noronha on building the anti-PowerPoint, coaxing models to write HTML, and why incumbents will let startups prove the pattern first.
1:23:40ENA $9 Tutor That Refuses to Give the Answer진행자 Nathan LabenzHow Khan Academy spent five months of GPT-4 early access building Khanmigo, a Socratic tutor shipped on the model's launch day.
1:47:05ENEdit Meaning, Not Tokens: Linus Lee on Latent-Space Interfaces진행자 Nathan LabenzThe Notion AI product lead walks Nathan Labenz through the interfaces, model autopsies, and agency questions behind his research prototypes.
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