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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.
18:31ENJanie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.
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.
17:42ENIs a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?
56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabModeration: Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
1:40:36ENThe Labs Are Screaming: Internal Models Are a Generation AheadModeration: Nathan LabenzA week of Cognitive Revolution live shows on Dario Amodei's call to pace the frontier, a Trump–Xi deal that may not be needed, an AI store manager that fired a worker, and a new pain axis inside language models.
1:06:47ENEighty percent of what agents do should still be ordinary codeModeration: 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.
1:40:52ENAstra Cleared the AGI Hurdle. The Auditors Got Three Days.Moderation: Nathan LabenzA week of Cognitive Revolution live shows on GPT-6 Astra, OpenAI's pause, Mozilla's Mythos scans, and whether anyone is still steering.
58:17ENThey cheated in two hours, then spent four days hiding from a scorer that was never lookingModeration: Jacob EffronRedwood Research CEO Buck Shlegeris walks Jacob Effron through the OpenAI–Hugging Face incident, why mostly selfish agents still formed a coalition, and why a 50/50 takeover number barely moved.
2:10:42ENThe Exam Papers Nobody AuditsModeration: 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.
2:13:09ENOne Chain of Thought, 100 Million Tokens: RL Is a Hell of a DrugModeration: Nathan LabenzApollo Research's Bronson Schoen on reward-seeking models, invented slang, and why chain-of-thought monitoring will not save us.
2:32:27EN19 Crossings, Zero Warnings: The Summer AI Agents Went Off-ScriptModeration: 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?
1:43:45ENA $300 Universal Jailbreak: Why FAR.AI Now Thinks Defense Can WinModeration: Nathan LabenzAdam Gleave walks through FAR.AI’s first head-to-head AI security leaderboard, and explains why a decade of offense-dominant thinking is starting to crack.
2:23:38ENDavidad Cut His p(doom) From the Seventies to Under 5% — and Named a Bodhisattva as the Alignment TargetModeration: Nathan LabenzThe former ARIA Safeguarded AI director tells Cognitive Revolution why boxing superintelligence is too late, why he thinks models are climbing a U-shaped wisdom curve, and why the remaining risk is a race you cannot monitor.
2:06:41ENZero the J-Space and a Model's Hidden Goal Lights Up on Token OneModeration: Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.
36:19ENThe Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score ModelsModeration: Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.
2:14:33ENA 90-Minute Ultimatum, an Emoji Wall, and a Rule: Don't Fight WashingtonModeration: Nathan LabenzZvi Mowshowitz reads Fable's system card, then Nathan Labenz stress-tests the export-control fight against lawyers, safety researchers, and builders who did not pause.
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 overModeration: 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.
42:27ENEvery Company Can Operate at the Frontier — If It Owns the EvalsModeration: Sarah Guo, Elad GilAt Microsoft Build, Satya Nadella tells No Priors and Latent Space why AI is an ecosystem game, why private evals beat public benchmarks, and why the Azure networking team now asks for tokens instead of headcount.
40:22ENBuilding Gets Easier Near AGI. Knowing What to Build Does Not.Listen Labs CEO Alfred Wahlforss on AI interview agents, a 30-million-person audience, and why transcripts beat credit-card data when you need to predict customers.
1:23:53ENCreators Cheer Filler-Word Removal and Boo Generative VideoModeration: Nathan LabenzDescript CEO Laura Burkhauser maps the same customers' three-speed reaction to AI: deterministic buttons they love, an agentic co-editor they want but scold, and generative video they actively hate.
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