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53:44EN
Sequoia Capital· 18 ago 2026PódcastThe Biggest Bug in Today’s Models Is That the Weights Never ChangeTuring Award winner Rich Sutton and Khurram Javed founded Oak Lab to build agents that keep learning after they ship — and they call synthetic data a big mistake.AgentesContinual learningReinforcement Learning+3
Diapositivas0:28EN
Theo - t3․gg· 18 ago 2026Theo on Working Without Opening a TerminalTheo Browne · Ping LabsA reboot helped Theo realize that a more readable, organized interface had changed his coding workflow.Developer productivityFlujos de desarrollo y pruebasProducto y UX
1:09:44EN
20VC with Harry Stebbings· 17 ago 2026Pódcast · 2 vocesAndrew Macdonald on Uber’s Membership Strategy, Autonomy and AIInvitado: Andrew Macdonald · Presenta: Harry StebbingsUber’s president and COO discusses marketplace incentives, autonomous vehicles, the company’s China exit and the challenge of measuring AI’s value.MarketplacesProduct StrategyAutonomous Driving+2
6 diapositivas31:17EN
Theo - t3․gg· 17 ago 2026Why Theo Moved From Terminals to Graphical Agent WorkflowsTheo Browne · t3.ggTheo Browne explains how parallel coding agents changed his tool preferences, and why he helped build the open-source T3 Code interface.Agentes de programaciónFlujos de desarrollo y pruebasDeveloper productivity+2
4 diapositivas9:15EN
Matthew Berman· 17 ago 2026Six Open-Source Projects for Local AI, Agents, and 3D DesignMatthew Berman · Forward FutureMatthew Berman tours tools for running and training models, giving agents new skills, coordinating work, browsing, and generating 3D meshes.Open-source ecosystemsAgent skillsLocal inference+2
1:25:13EN
Cognitive Revolution "How AI Changes Everything"· 16 ago 2026PódcastA $500 Lamp Cut TB Transmission 90 Percent. Almost Nobody Buys OnePresenta: Nathan LabenzAerolamp's Misha Gurevich and Vivian Belenky walk Patrick McKenzie through far-UVC at 222 nanometers: the lab science, the safety case, and why the bottleneck is awareness rather than physics.SeguridadPublic HealthBiosecurity+3
1:20:47EN
20VC with Harry Stebbings· 15 ago 2026Pódcast · 2 vocesMatt Swulinski on Building and Measuring a Product-Led Growth EngineInvitado: Matt Swulinski · Presenta: Harry StebbingsThe growth leader shares lessons from Superhuman, Wispr Flow and Viktor on paid acquisition, creative testing, referrals and AI-assisted workflows.Growth StrategyProduct-Led GrowthAI in sales & marketing+2
Diapositivas0:18EN
Theo - t3․gg· 14 ago 2026Theo Discusses Elon Musk’s Grok 4.7 PreviewTheo Browne · Ping LabsTheo reacts to Musk’s August 2026 claims about the next Grok model, its training and an expected release window.Foundation ModelsModelos y entrenamientoAI Strategy
7 diapositivas31:58EN
Theo - t3․gg· 14 ago 2026Claude’s AI Watermarks and the Limits of Detecting Generated ContentTheo Browne · t3.ggTheo Browne examines Anthropic’s marking plans, the challenge of text watermarks, and what signed provenance can and cannot establish.AI SafetyPrivacy & data governanceAI Regulation+2
9 diapositivas13:09EN
Matthew Berman· 14 ago 2026AI News: Ultrafast Inference, Claude Watermarks and New ModelsMatthew Berman · Forward FutureMatthew Berman reviews an ultrafast coding preview, text watermarking, Grok Bot, open-weight models and Computer History.InferenceOpen-weight modelsAgentes de programación+2
2:06:11EN
Cognitive Revolution "How AI Changes Everything"· 14 ago 2026PódcastLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models BannedPresenta: Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.AgentesAgent memoryIngeniería de contexto+3
3:36:13EN
Zhang Xiaojun Podcast· 13 ago 2026Pódcast · 2 vocesNVIDIA’s Ming-Yu Liu on Cosmos, Physical AI, and Creating New MarketsInvitado: Ming-Yu Liu · Presenta: 张小珺NVIDIA research VP Ming-Yu Liu explains how a decade of generative-model research led to Cosmos 3, a world foundation model for Physical AI. He also shares what he learned from Jensen Huang about long-term bets, teamwork, and building markets instead of fighting over existing ones.World modelsRoboticsAI research+2
46:08EN
No Priors: AI, Machine Learning, Tech, & Startups· 13 ago 2026Pódcast · 2 vocesComputers 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.Empresa y estrategiaCompany BuildingProduct Strategy+3
8 diapositivas25:31EN
Theo - t3․gg· 13 ago 2026Grok 4.6: Better Agent Benchmarks, With Tradeoffs in Speed and CostTheo Browne · t3.ggTheo Browne tests Grok 4.6 on design, games and real code, weighing reported benchmark gains against his experience of slower and costlier tasks.Agentes de programaciónEvaluacionesAI cost & performance+2
1:29:42EN
20VC with Harry Stebbings· 13 ago 2026Pódcast · 3 voces20VC on AI Competition, Founder Control and Software ValuationsInvitado: Jason Lemkin, Rory O’Driscoll · Presenta: Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate how AI is reshaping software markets, talent, infrastructure and investor incentives.SaaSAI StrategyVenture Capital+2
3:12:58EN
Lex Fridman· 12 ago 2026Pódcast · 2 vocesOne Cold Shower, Twenty Champions: How Khabib Nurmagomedov Was ForgedInvitado: Khabib Nurmagomedov · Presenta: Lex FridmanIn a Makhachkala school gym, seventy men shared one shower, and the water was only cold.Martial ArtsCombat SportsCoaching+3
3:36:13ZH
Zhang Xiaojun Podcast· 12 ago 2026Pódcast · 2 voces刘洺堉:Cosmos 世界模型与物理 AI 的长期路线Invitado: 刘洺堉 · Presenta: 张小珺从图像生成、研究管理到 Cosmos 3,英伟达研究负责人讨论如何为物理 AI 构建基础。World modelsRoboticsAI research+2
Diapositivas1:07EN
Matthew Berman· 11 ago 2026Matthew Berman on Relay: Routing Coding Work Across ModelsMatthew Berman · Forward FutureA short demonstration of a free coding skill that assigns planning, implementation and review to different models. Its cost comparison is one example, not a guarantee of savings or equivalent quality.Agent orchestrationAgentes de programaciónAI cost & performance+2
4 diapositivas37:02EN
Matthew Berman· 11 ago 2026Matthew Berman on Zuckerberg’s AI Vision and the Problem of Unequal ComputeMatthew Berman · Forward FutureA review of Meta’s case for widely distributed superintelligence asks whether access to the same models can overcome disparities in compute and energy.AI StrategyOpen-weight modelsSeguridad y gobernanza+2
9 diapositivas51:15EN
Theo - t3․gg· 11 ago 2026How Theo Refined His AGENTS.md and Skills From Real Agent FailuresTheo Browne · t3.ggTheo Browne explains how he audits agent sessions, writes project guidance and shares skills across machines without treating his configuration as a template.Agent skillsIngeniería de agentesFlujos de desarrollo y pruebas+2
Diapositivas0:31EN
Theo - t3․gg· 11 ago 2026Theo on Writing Skill Descriptions as TriggersTheo Browne · Ping LabsTheo argues that a skill description should help a model decide when to load the skill, rather than contain the entire procedure.Agent skillsIngeniería de contextoIngeniería de agentes
1:08:25EN
20VC with Harry Stebbings· 10 ago 2026Pódcast · 2 vocesAlex Atallah on OpenRouter, Model Competition and AI MarketplacesInvitado: Alex Atallah · Presenta: Harry StebbingsThe OpenRouter CEO discusses inference providers, open-weight models, enterprise safety and the economics of routing.Model routing & gatewaysInferenceOpen-weight models+2
6 diapositivas18:17EN
Theo - t3․gg· 8 ago 2026MCP’s Stateless Redesign: What Changed and Why Theo Is OptimisticTheo Browne · Ping LabsThe July 2026 MCP specification replaces protocol sessions with self-describing requests. Theo examines the benefits, examples, and the problem of migrating older clients and servers.MCPAgentes de programaciónInfraestructura y despliegue+2
1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 8 ago 2026PódcastThe Periodic Table Was Already in the WeightsPresenta: Nathan LabenzGoodfire CTO Dan Balsam tells Nathan Labenz how concept manifolds, predictive data debugging, and a $1,000-a-month research agent are turning interpretability into a product.Modelos y entrenamientoModel InterpretabilityIngeniería de agentes+3
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