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AI Engineer· 26 oct 2026Xander Song on Evaluating Agents with Harbor and PhoenixXander Song · Arize AIArize AI engineer Xander Song explains how Harbor runs realistic agent tasks in isolated sandboxes, and how his team uses Phoenix to compare prompt changes, inspect trajectories, and test a SQL tool.
19:43ENAI Engineer· 26 oct 2026Jack Wotherspoon on Building a Team of Managed AgentsJack Wotherspoon · Google DeepMindGoogle DeepMind’s Jack Wotherspoon introduces Gemini Managed Agents: cloud sandboxes that let teams run coding and research agents with a single API call. He explains how persistent environments, reusable skills, proxy-injected credentials, schedules, and specialized agents fit together.
20:55ENAI Engineer· 26 oct 2026Jesse 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.
35:19ENAI Engineer· 25 oct 2026SallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.
15:27ENAI Engineer· 25 oct 2026What AI Engineers Do Now: Build the Loop Around AgentsAparna Dhinakaran · Arize AIAparna Dhinakaran argues that AI engineers are moving from shipping individual features to building systems that let agent teams improve them. At Arize, that means tracing agent behavior, evaluating its work against human judgment, and feeding those signals back into an always-on agent.
19:37ENAI Engineer· 25 oct 2026Jay Sahnan and Arik Bird on Building Financial Agents for the Whole WebJay Sahnan, Arik Bird · BrowserbaseBrowserbase’s Jay Sahnan and Arik Bird show how browser agents reach financial data hidden behind logins and bot defenses. Their Ramp, Bill, and Stripe examples connect reliable cloud browsers with Stagehand’s more adaptive controls.
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Cognitive Revolution "How AI Changes Everything"· 17 oct 2026PódcastClaude Changed the Password. The Steering Wheel Was Already OptionalPresenta: Nathan LabenzNathan Labenz and Prakash Narayanan spend a week on agents that can lock you out, models that dodge a feeling they deny having, and formal proofs that found Linux bugs.
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No Priors: AI, Machine Learning, Tech, & Startups· 2 oct 2026Pódcast · 2 vocesCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioPresenta: Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
1:59:37ENOpus 5.5 and GPT-6 Sol and Luna: A Launch-Day LivestreamMatthew Berman, Thariq Shihipar, Alex, Brian · Forward FutureMatthew Berman interviews Anthropic’s Thariq Shihipar, shows early demos and then reviews two OpenAI models announced during the stream.
1:06:47ENCognitive Revolution "How AI Changes Everything"· 17 sept 2026PódcastEighty percent of what agents do should still be ordinary codePresenta: Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.
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Sequoia Capital· 15 sept 2026PódcastThe Bridge From Model to Workflow Is a Trillion-Dollar BusinessBox CEO Aaron Levie argues that the money in this cycle sits in the messy gap between frontier models and real enterprise work — and that coding's overnight diffusion will not repeat for everyone else.
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20VC with Harry Stebbings· 29 ago 2026Pódcast · 2 vocesEno Reyes on AI Model Economics, Enterprise Control and Factory's StrategyInvitado: Eno Reyes · Presenta: Harry StebbingsFactory's CTO discusses cost per outcome, model routing, open models, enterprise hiring and his expectations for the AI market.
2:10:42ENCognitive Revolution "How AI Changes Everything"· 28 ago 2026PódcastThe Exam Papers Nobody AuditsPresenta: Nathan LabenzFrontier labs buy reinforcement-learning environments from a cottage industry of small vendors, and almost nobody checks whether those tests match the real work.
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Lex Fridman· 26 ago 2026Pódcast · 2 vocesDHH Did Not Write a Line of Omarchy QuattroInvitado: DHH · Presenta: Lex FridmanThirteen months after a skeptical conversation with Lex Fridman, the Rails creator describes how Opus 4.5, a swarm of coding agents, and a one-minute Linux installer ended his era of hand-chiseled Ruby.
55:19ENSequoia Capital· 25 ago 2026PódcastHuman Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.
44:28ENTibo on Coding Agents, Faster AI and OpenAI’s Product DirectionMatthew Berman, Thibault Sottiaux · Forward FutureOpenAI’s Tibo discusses agent interfaces, usage resets, model efficiency and the trade-offs behind faster inference.
2:32:27ENCognitive Revolution "How AI Changes Everything"· 22 ago 2026Pódcast19 Crossings, Zero Warnings: The Summer AI Agents Went Off-ScriptPresenta: Nathan LabenzNathan Labenz compresses four mornings and nine guests into one question: once agents go to work, who is actually watching the frontier, and who pays for the machine underneath?
2:06:11ENCognitive 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.
1:56:40ENCognitive 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.
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Zhang Xiaojun Podcast· 28 jul 2026Pódcast · 2 vocesYou Kaichao on How vLLM Grew from Open-Source Project to AI Infrastructure CompanyInvitado: You Kaichao · Presenta: 张小珺Inferact co-founder You Kaichao traces vLLM’s path from Berkeley research to a company, then explains why model, inference, hardware and agent design increasingly have to move together.
48:55ENSequoia Capital· 14 jul 2026PódcastAnthropic's Platform Grew Three Layers in a Year — and Tokens Now Have JobsKatelyn Lesse and Angela Jiang tell Sequoia's Training Data how Anthropic went from a stateless Messages API to knowledge, execution, and coordination — without trying to own the servers.
18:34ENModel Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.
38:45ENSequoia Capital· 16 jun 2026PódcastThe 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.
1:44:28ENCognitive Revolution "How AI Changes Everything"· 13 jun 2026PódcastFable launch week: a model that refuses, a two-year alignment clock, and a Twitter account handed overPresenta: Nathan LabenzNathan Labenz’s AI in the AM highlights reel from June 2026 covers Anthropic’s new frontier model, the founding of Sequent, and a week that settled one argument: AI is not slowing down.Cargar másMostrando 24 de 161