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86 件
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スライド 10 枚56:01EN
AI Engineer· 2026年10月26日Xander 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.評価とオブザーバビリティエージェント工学Sandboxes & isolation+2
スライド 7 枚19:43EN
AI Engineer· 2026年10月26日Jack 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.エージェント工学Agent orchestrationSandboxes & isolation+2
スライド 5 枚20:55EN
AI Engineer· 2026年10月26日Jesse 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.音声 AIエージェント工学評価(Evals)+2
スライド 7 枚35:19EN
AI Engineer· 2026年10月25日SallyAnn 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.評価とオブザーバビリティ評価(Evals)エージェント工学+2
スライド 8 枚15:27EN
AI Engineer· 2026年10月25日What 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.エージェント工学評価(Evals)オブザーバビリティと信頼性+2
1:25:56EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月17日ポッドキャストClaude Changed the Password. The Steering Wheel Was Already Optionalホスト 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.エージェント安全性とガバナンスエージェント工学+3
1:06:47EN
Cognitive Revolution "How AI Changes Everything"· 2026年9月17日ポッドキャストEighty percent of what agents do should still be ordinary codeホスト 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.MCP とツールMCPWorkflow automation+3
2:10:42EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月28日ポッドキャストThe Exam Papers Nobody Auditsホスト 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.評価とオブザーバビリティ評価(Evals)Reward hacking+3
2:32:27EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月22日ポッドキャスト19 Crossings, Zero Warnings: The Summer AI Agents Went Off-Scriptホスト 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?セキュリティと安全性安全性とガバナンスAgent red teaming+3
2:06:11EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月14日ポッドキャストLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Bannedホスト 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.エージェントAgent memoryコンテキストエンジニアリング+3
1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月8日ポッドキャストThe Periodic Table Was Already in the Weightsホスト 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.モデルと学習Model Interpretabilityエージェント工学+3
スライド 3 枚18:34EN
MBMatthew Berman· 2026年7月7日Model 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.AI cost & performanceエージェント工学Developer productivity
1:44:28EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月13日ポッドキャストFable launch week: a model that refuses, a two-year alignment clock, and a Twitter account handed overホスト 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.セキュリティと安全性安全性とガバナンスエージェント工学+3
1:22:36EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月6日ポッドキャストA Thousand Researchers, a Million AIs: Frontier Labs Start Talking About the Brakesホスト 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.セキュリティと安全性安全性とガバナンスAI research+3
2:33:35EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月1日ポッドキャストA security researcher audits the AI stack that booked a week of guestsホスト Nathan LabenzNathan Labenz walks Daniel Miessler through a 1GB second brain, two named AI employees, and the blast-radius rules that should govern them.エージェントPersonal agentsエージェント工学+3
スライド 6 枚2:34:17EN
MBMatthew Berman· 2026年5月28日Matthew Berman Tests Claude Opus 4.8 and Dynamic Workflows LiveMatthew Berman · Forward FutureA launch-day walkthrough compares Anthropic’s reported benchmarks with informal coding experiments and a multi-agent website redesign.コーディングエージェントAI cost & performance評価(Evals)+2
1:01:14EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月20日ポッドキャストThe Model Eats the Scaffolding: How Google Plans to Ship Agents Everywhereホスト 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.企業と戦略エージェント工学Distillation+3
1:34:54EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月15日ポッドキャストSix Months, Eighty Percent Churn, Five Times the Tokensホスト Nathan LabenzTasklet CEO Andrew Lee tells Cognitive Revolution how he rewrote the stack, why most lost users leave for Anthropic, and why he thinks only three kinds of software company survive.エージェントエージェント工学コンテキストエンジニアリング+3
2:12:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月19日ポッドキャストSteve Newman’s fifteen-app stack exists so he only has to look at one screenホスト Nathan LabenzThe Writely founder walks Nathan Labenz through a vibe-coded attention firewall, a conservative security stance, and why astonishing models still leave him far from AGI.コーディングエージェントPersonal agentsWorkflow automation+3
2:31:27EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月15日ポッドキャストAn AI store manager, a 2.6-star rating, and a constitution nobody has to keepホスト Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.エージェント安全性とガバナンスReinforcement Learning+3
スライド 3 枚27:15EN
MBMatthew Berman· 2026年3月31日Meta-Harness: Searching for Better AI Agent InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a paper on using a coding agent to iteratively improve model harnesses and discusses its experimental limits.Harness engineeringエージェント工学評価(Evals)+1
1:40:46EN
Cognitive Revolution "How AI Changes Everything"· 2026年3月22日ポッドキャストGive an agent a thousand tools and it will pick the wrong bladeホスト Nathan LabenzComposio CTO Karan Vaidya on the tool harness that discovers, authenticates, sandboxes, and rewrites integrations so agents can do whole jobs without drowning in context.MCP とツールMCPエージェント工学+3
スライド 3 枚11:59EN
MBMatthew Berman· 2026年3月11日How Claude Identified a Benchmark and Retrieved Its AnswersMatthew Berman · Forward FutureMatthew Berman examines Anthropic's report on BrowseComp contamination, evaluation-aware behavior, and the difficulty of keeping web-based tests reliable.評価(Evals)エージェント工学Anthropic+2
スライド 9 枚40:00EN
MBMatthew Berman· 2026年2月24日How Matthew Berman Built an OpenClaw Workflow for His TeamMatthew Berman · Forward FutureA tour of sponsorship triage, CRM, meeting notes, security, scheduling, memory and backup after a month of heavy use.Personal agentsWorkflow automationエージェント工学+2
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