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19:43ENJack 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.
20:55ENJesse Hall:语音智能体要为对话而优化,而非只看排行榜Jesse Hall · LiveKitLiveKit 的 Jesse Hall 解释了为什么语音智能体必须像实时系统一样接受评测:听清用户、允许打断、在工具调用期间继续对话,并在用户真正听到声音之前控制延迟。
35:19ENSallyAnn 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.
15:27ENWhat 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.
19:37ENJay 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.
1:25:56ENClaude 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.
35:39ENCompute 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.
1:06:47ENEighty 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.
1:05:21ENThe 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.
2:10:42ENThe 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.
5:15:51ENDHH 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.
55:19ENHuman 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.
2:32:27EN19 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?
2:06:11ENLindy 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.
1:56:40ENThe 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.
48:55ENAnthropic'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.
38:45ENThe 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.
1:44:28ENFable 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.
51:09ENBuild like the model will eat your harness in a yearLogan Kilpatrick, who leads Google AI Studio and the Gemini API, tells Sequoia's Sonya Huang why agent scaffolding is a 12-month asset, why coding already feels like narrow superintelligence, and why Google is optimizing for outcomes instead of eyeballs.
1:22:36ENA Thousand Researchers, a Million AIs: Frontier Labs Start Talking About the BrakesPresenta: Nathan LabenzThe first week of AI in the AM follows OpenAI's timeline for an ML-intern model this year and a human-level AI researcher by early 2028 — and the closed-door meeting where labs admitted they might one day need to slow down together.
2:33:35ENA security researcher audits the AI stack that booked a week of guestsPresenta: Nathan LabenzNathan Labenz walks Daniel Miessler through a 1GB second brain, two named AI employees, and the blast-radius rules that should govern them.
41:09ENAfter Agents Leak Tokens and Wipe Databases, Onyx Trains Small Models to Watch the Big OnesPresenta: Sarah Guo, Elad GilTwo years ago enterprise security buyers told Maxim Bar Kogan he was too early. Now Fortune 10 companies are calling a sub-100-person Israeli startup because they cannot stop agent adoption — only reduce the chance the next action is illegitimate.
45:33ENCursor Ships 1TB of Composer Weights Across Oceans in Under a MinuteFederico Cassano and Fireworks' Dima walk through the globally split RL stack that trained Composer 2 on a sparse trillion-parameter MoE.
1:01:14ENThe Model Eats the Scaffolding: How Google Plans to Ship Agents EverywherePresenta: Nathan LabenzThree years after the leaked “no moat” memo, DeepMind’s Gemini leads walk through 3.5 Flash, Omni, and the shared agent harness now running through Google’s products.
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