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3 diapositivas25:17EN
Peter Yang· 11 nov 2026PódcastPeter Yang splits Claude Code work between Opus and FableHe uses Opus for routine execution and reserves Fable for harder decisions, code audits and family-care coordination.Agentes de programaciónAI cost & performanceHuman-AI Collaboration
2 diapositivas19:44EN
OpenAI· 11 nov 2026What a managed agent harness has to do to keep workingCharlie, Steve · OpenAIOpenAI engineers explain remote sandboxes, long-running state and a human-approved flight rebooking demo.Agentes de programaciónAgent orchestration
1:24:54EN
Invest Like The Best· 11 nov 2026Pódcast · 2 vocesZach Reitano: US healthcare must answer to patientsInvitado: Zach Reitano · Presenta: Patrick O'ShaughnessyRo's founder argues for transparent prices and patient choice, and describes the company's 2022 reset.Public HealthCompany BuildingEntrepreneurship+1
1:13:14EN
Reid Hoffman· 11 nov 2026Pódcast · 3 vocesRonnie Chatterji: AI may change work before it changes job countsInvitado: Ronnie Chatterji · Presenta: Reid Hoffman, Aria FingerOpenAI’s chief economist expects productivity gains, but says attributing them to AI and managing uneven effects will take work.Future of WorkEconomicsAI Regulation+1
27:14EN
Bloomberg Live· 11 nov 2026John Kerry: Cheaper clean energy needs faster deploymentAaron Rutkoff, John Kerry · BloombergKerry argues clean energy can compete on price, while warning that permitting delays and climate damage add costs.EnergyGeopoliticsEconomics
59:16EN
Conversations with Tyler· 11 nov 2026Pódcast · 2 vocesTerence Tao: AI proofs make mathematical understanding more urgentInvitado: Terence Tao · Presenta: Tyler CowenTao explains why proof abundance may change research, education and the value of human explanation.MathematicsAI in Education
Diapositivas26:47EN
Every· 11 nov 2026Pódcast · 2 vocesDan Shipper: AI makes generating ideas cheap; people still choose what mattersPresenta: Natalia QuinteroThe Every co-founder uses one customer survey to explain why different perspectives can produce different work from the same model.Future of WorkHuman-AI CollaborationAI agents
3 diapositivas27:09EN
OpenAI· 11 nov 2026A six-week coding agent run and what it took to superviseOpenAI engineers describe a CI maintenance agent, long-running context and the cost of keeping it working.Agentes de programaciónAgent orchestration
3 diapositivas20:48EN
OpenAI· 11 nov 2026Sites adds personalized connectors and agent-friendly web appsKatia, John · OpenAIOpenAI demonstrates scheduled updates, per-user plugins and WebMCP in two Sites applications.Product engineeringMCPAgentes de programación
2 diapositivas29:37EN
Theo - t3․gg· 11 nov 2026Theo finds a security use for Gemini 4 Carbon despite coding frustrationsTheoHis tests show fewer false code-analysis claims than Argon, but latency and reliability still push him toward other models.Agentes de programaciónModelos y entrenamientoAI cost & performance+1
21:35EN
Masters of Scale· 11 nov 2026Pódcast · 2 vocesEric Ries: Why successful companies lose the purpose that made them workInvitado: Eric Ries · Presenta: Krista TippettRies argues that pressure from capital can erode a company’s mission, and that trust deserves a place in business decisions.Company BuildingCompany CultureLeadership+1
56:06EN
a16z· 11 nov 2026Mike Volpi: AI infrastructure can endure a market correctionRaghu Raghuram, Guido Appenzeller, Mike Volpi · Andreessen HorowitzThe former Cisco executive sees useful assets beyond the hype, but questions who will own them and how systems will evolve.Infraestructura y despliegueSemiconductorsVenture Capital
1:42:10EN
Jane Street· 11 nov 2026How quickly could AI improve itself? Four forecasters disagreeYaron Minsky, Jaime Sevilla, Ege Erdil, Ryan Greenblatt, Daniel Kokotajlo · Jane StreetOne forecaster puts AI research automation at 50% by 2028; another sees a slower path as more likely, with a real chance of rapid progress.AGI TimelinesAI researchAI Safety+2
3 diapositivas18:18EN
Matthew Berman· 11 nov 2026Fable 5.2 leads a week of model releases, but cost changes the choiceMatthew Berman · Forward FutureMatthew Berman compares Fable and Gemini Carbon, reviews smaller models and discusses Nvidia’s investigation.Machine LearningAI agents
3 diapositivas12:38EN
AI Engineer· 11 nov 2026How Duolingo uses agents to add tests without skipping human reviewKush Agrawal · DuolingoA scheduled pipeline raised iOS coverage by generating tests, repairing CI and routing pull requests to engineers for approval.Agentes de programaciónFlujos de desarrollo y pruebasSoftware engineering
1:03:19EN
Stanford Online· 11 nov 2026Manage AI sources: retrieve selectively and withhold context when usefulCynthia Bailey · Stanford UniversityStanford lecturer Cynthia Bailey explains when to retrieve documents, leave context out and guard against instructions hidden in sources.RAG y conocimientoIngeniería de contextoPrompt injection+1
2:55:43EN
PowerfulJRE· 11 nov 2026Pódcast · 3 vocesPaddy Pimblett on fighting, weight cuts and the lightweight divisionInvitado: Paddy Pimblett · Presenta: Joe RoganPimblett explains his Saint Denis finish, his difficult recovery from ankle surgery, and why he refuses to fight teammates.Combat SportsMartial ArtsJiu Jitsu+1
4 diapositivas48:20EN
Theo - t3․gg· 10 nov 2026Fable 5.2 is powerful, but Theo Browne still prefers Opus for everyday codingTheo Browne · T3After a day of tests, Browne compares benchmarks, usage limits and the mistakes that still require a human reviewer.Agentes de programaciónBenchmarksModelos y entrenamiento
43:35EN
Silicon Valley Girl· 10 nov 2026Isomorphic Labs’ Max Jaderberg on narrowing drug designs with AIInvitado: Max Jaderberg · Presenta: Marina MogilkoThe researcher explains virtual screening, real laboratory checks and why agent performance must be measured against useful outcomes.Drug DiscoveryAI for scienceAI agents+2
4 diapositivas38:50EN
AI Engineer· 10 nov 2026LinkedIn’s self-improving agent first had to fix its judgesZiwei Guo, Saloni Gandhi · LinkedInA prompt-optimization loop improved a career agent, but unreliable evaluators required human calibration first.Ingeniería de agentesEvaluaciones y observabilidadAgent orchestration+1
12:48EN
AI Engineer· 10 nov 2026Brian Douglas: Turn agent corrections into reusable review knowledgeBrian Douglas · Paper ComputeThe Paper Compute developer captures expert pushback in coding sessions and tests ways to reuse it during review.Agentes de programaciónFlujos de desarrollo y pruebasSoftware engineering+1
59:06EN
a16z· 10 nov 2026Dharmesh Shah: Find startup opportunities beyond the AI labs’ pathJoe Schmidt, Dharmesh Shah · Andreessen HorowitzHubSpot’s co-founder explains how to test narrow ideas, build around customer work and use AI without relying on a temporary model gap.AI startups & small teamsProduct StrategyIA empresarial+2
Diapositivas12:20EN
AI Engineer· 10 nov 2026Ayush Bhardwaj: Agent workarounds are feedback for your CLIAyush Bhardwaj · Allos AIAn audit of coding sessions shows where output, errors and stale instructions force agents to improvise.Agentes de programaciónFlujos de desarrollo y pruebasIngeniería de agentes+1
1:46:17EN
The Knowledge Project Podcast· 10 nov 2026Pódcast · 2 vocesJon McNeill on Tesla’s speed: delete steps before automatingInvitado: Jon McNeill · Presenta: Shane ParrishThe former Tesla president explains the sales bottleneck, product feedback and five-step simplification method behind rapid growth.LeadershipDecision MakingProduct Management+2
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