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1:23:01ENThe Meteor Is Coming: Intercom's Paul Adams on Going All In on AI게스트 Paul Adams · 진행자 Lenny RachitskyIntercom's chief product officer talks about the failures that shaped him, how Intercom ripped up its strategy after ChatGPT, and the simple frameworks he uses to decide what to build.
1:24:30ENFrom Curation to Recommendation to Generation: Spotify's Gustav Söderström on Rethinking Product게스트 Gustav Soderstrom · 진행자 Lenny RachitskySpotify's co-president and CPO/CTO explains the AI DJ, a bruising homepage redesign, why squads gave way to VP-level autonomy, and what generative music might mean.
1:14:03ENThere Is No Marketing Playbook: Krithika Shankarraman's DATE Framework게스트 Krithika Shankarraman · 진행자 Lenny RachitskyThe first marketing hire at OpenAI and Stripe explains why diagnosing your own problem beats copying other companies' tactics.
1:17:44ENStart at Chapter One: Casey Winters on Executive Communication, Unsexy Work and Growth Loops게스트 Casey Winters · 진행자 Lenny RachitskyEventbrite CPO Casey Winters shares what he has learned about product leadership, simplicity at scale, strategy as the great career filter, and the current state of growth.
1:41:26ENThe AI Scouting Report, Part 3: What AI Can Already Do, Who Will Win, and Why Nathan Labenz Wants Caution on Scaling진행자 Nathan LabenzNathan Labenz closes his AP-course tour of AI with capabilities, market moats, jobs, law, safety plans and a stance on what to do next.
57:21ENGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build Next진행자 Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
1:27:30ENFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lecture진행자 Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.
18:02ENYour Career Is the Most Important Product You'll Ever Ship진행자 Lenny RachitskyA product-leadership framework for navigating dozens of jobs, building career stories, avoiding burnout, and turning reputation into opportunity.
12:01ENThe Big Nap: Why Eric Weinstein Thinks the Pandemic Ends 75 Quiet Years게스트 The Big Nap · 진행자 Lex FridmanIn an April 2020 conversation, Eric Weinstein and Lex Fridman discuss what a global crisis reveals about collective action, fragility, and the institutions we treat as museum pieces.
1:05:15ENTaming the Long Tail: How Waymo Builds a Self-Driving Factory진행자 Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.
54:05ENServal's Jake Stout on Outbuilding ServiceNow: Mirror the System of Record, Bet on Code, and Ship Before the Incumbent Can Book a Meeting진행자 Jacob EffronHow an AI-native employee-support startup attacks a legacy ITSM incumbent with velocity, code-generated workflows and a permissions-first architecture.
1:27:15ENPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement Learning진행자 Lex FridmanOpenAI's John Schulman walks through the core methods of deep RL, from the score function estimator to TRPO and DQN, and says when each one is worth using.
1:25:34ENShipping in Days: How Claude Code's Head of Product Runs a Team at AI Speed진행자 Lenny RachitskyCat Wu, Head of Product for Claude Code and Cowork at Anthropic, explains how the PM role, hiring, tooling and culture change when features go from idea to users in a week or less.
1:24:38ENPlant Seeds, Don't Pour Concrete: Alex Komoroske on Gardening Your Way Through the LLM Era게스트 Alex Komoroske · 진행자 Lenny RachitskyA former Google and Stripe strategist explains why LLMs are "magical duct tape," how organizations lie to themselves, and why gardeners beat builders when the playbook is changing.
1:39:22ENRust-Proofing a Company: Eric Ries on Why Success Corrupts and Governance Protects진행자 Lenny RachitskyThe author of The Lean Startup explains why good companies go bad, and the charters, trusts and habits that keep a mission intact.
1:07:20ENRiding the Lightning: What Hypergrowth Companies Share, According to Atlassian's Former Marketing Chief게스트 Carilu Dietrich · 진행자 Lenny RachitskyCarilu Dietrich draws on her years at Atlassian and her advisory work with fast-growing B2B companies to explain how to build a career, a brand and a growth engine.
45:27ENThe Agent State: How AI Flattened the Adversary Pyramid and Why Defenders Need Their Own Frontier Models진행자 Sarah Guo, Elad GilCrowdStrike CEO George Kurtz explains how low-skill attackers now wield nation-state tradecraft through AI agents, and how CrowdStrike and Nvidia are training security-specific models to fight back.
1:22:50ENRadical Self-Inquiry: Jerry Colonna on Growing Up Without Feeling Like Crap게스트 Jerry Colonna · 진행자 Lenny RachitskyExecutive coach Jerry Colonna explains why leadership and resilience come from honest inner work, not just practical skills, and how unexamined childhood patterns quietly shape our teams and companies.
1:25:49ENShip Weekly, Cut Scope, and Keep a Secret Roadmap: How Captions Builds in the AI Era진행자 Lenny RachitskyGaurav Misra explains how a modern AI startup turns constant model progress into weekly shipped products, technical debt as leverage, and talking-video tools for non-professionals.
1:55:04ENMining the Computational Universe: Stephen Wolfram on What AI Can and Can't Be Told to Do게스트 Stephen Wolfram · 진행자 Lex FridmanIn a talk for MIT's AGI course, Stephen Wolfram connects Wolfram Alpha, simple programs, computational irreducibility and the problem of telling machines what humans want.
1:09:56ENWhen Anyone Can Build Anything, Taste Becomes the Product Job진행자 Lenny RachitskyCodex desktop lead Andrew Ambrosino on how AI has inverted product development, why roles are blurring but shouldn't vanish, and where Codex and ChatGPT are headed.
1:19:21ENVapnik's Case for Learning by Predicates, Not Just by More Data진행자 Lex FridmanIn an MIT lecture, Vladimir Vapnik argues that complete statistical learning needs two mechanisms, data and invariants, and that choosing smart predicates is where intelligence lives.
58:57ENWhen the Model Learns to Look Around: Apollo Research on Testing o1 for Scheming진행자 Nathan LabenzApollo Research founder Marius Hobbhahn explains how his team probed OpenAI's o1 for deception, what it found, and why the trajectory worries him more than the model itself.
1:36:17ENUnderstaff on Purpose, Never Be Chill: Matt MacInnis on Leading Rippling Through Entropy진행자 Lenny RachitskyRippling's chief product officer and longtime COO explains why extraordinary outcomes demand extraordinary effort, and the frameworks he uses to hire, set process and keep intensity high.
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