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44:57EN

a16z· 2026年11月2日ポッドキャスト · 3 人Tutor Intelligence CEO Josh Gruenstein on Building Robots for Real WorkMCRRJGゲスト Josh Gruenstein · ホスト Martin Casado, Raghu RaghuramJosh Gruenstein joins Martin Casado and Raghu Raghuram to discuss human tutors, robot manufacturing and the economics of factory automation.RoboticsAI agentsインフラとデプロイ+2

スライド 7 枚40:04EN

GOTO Conferences· 2026年11月2日Sophia Drossopoulou: Verifying Trusted Code in an Open WorldSophia Drossopoulou · Imperial College LondonCapabilities, scoped invariants and explicit trust assumptions help reason about effects when trusted code calls unknown objects.Code review & verificationProgramming LanguagesSoftware engineering

スライド 4 枚51:06EN

GOTO Conferences· 2026年11月2日Kent Beck: Build AI Programming Tools for Human NeedsKent BeckThe “genie” can amplify healthy or unhealthy development practices. Beck calls for tools that preserve learning, connection and future options.コーディングエージェントSoftware engineeringDeveloper productivity+1

1:07:22EN

Latent Space· 2026年11月2日ポッドキャスト · 3 人Building Legal AI Agents Without Seeing Client Data: Legora's Jacob LauritzenSwBCJLゲスト Jacob Lauritzen · ホスト swyx, Basil ChathaLegora's CTO explains how its team evaluates legal agents, designs review workflows and builds around the confidentiality of client matters.AI agentsエンタープライズ AI評価（Evals）+2

スライド 3 枚20:39EN

AI Engineer· 2026年11月2日Sagar Batchu: Authorizing AI Agent Actions Before They Reach an APISagar Batchu · SpeakeasyA proposed governance path combines agent identity, permission ceilings, policy decisions and audit records.エージェント認証AI security安全性とガバナンス+1

スライド 2 枚20:15EN

AI Engineer· 2026年11月2日Will Brown on Training Models That Learn From Organizational WorkWill Brown · Prime IntellectPrime Intellect’s Will Brown describes how traces, evaluations and human decisions could support continual learning alongside frontier models.Continual learningAI Product Management評価（Evals）+2

スライド 5 枚18:33EN

AI Engineer· 2026年11月2日Zack Proser: Build a Factory to Help Others Tell Their StoriesZack Proser · WorkOSA WorkOS blog assistant and a bedtime-story app show how AI tools can share expertise while humans retain responsibility.CreativityContent StrategyAI agents+1

1:02:12EN

20VC with Harry Stebbings· 2026年11月2日ポッドキャスト · 2 人Modal CEO Erik Bernhardsson on Inference, Compute and Building an AI PlatformHSEBゲスト Erik Bernhardsson · ホスト Harry StebbingsErik Bernhardsson discusses GPU capacity, open models, sandbox growth and why Modal is expanding beyond a single infrastructure product.InferenceAI platform engineeringインフラとデプロイ+2

1:32:16ZH

硅谷101· 2026年11月2日MaxInsights 袁宇光：如何生产机器人第一视角训练数据ゲスト 袁宇光 · ホスト 陈茜从头戴设备、全球采集网络到模型评估与部署，袁宇光解释机器人数据生意的扩张及质量挑战。RoboticsData quality & curationScaling Laws+1

スライド 2 枚27:55EN

AI Explained· 2026年11月2日AI Safety, Model Releases and the Limits of UnderstandingAI Explained examines lab forecasts, safety commitments and competing model results, then argues for multiple safeguards as capabilities advance.AI Safety安全性とガバナンスModel Interpretability+2

スライド 3 枚18:57EN

AI Engineer· 2026年11月2日Andrew Norrish: Code Context for AI-Era Incident ResponseAndrew Norrish · SourcegraphA Sourcegraph engineer describes review pressure and bounded workflows for investigating, preventing and fixing incidents.コーディングエージェントオブザーバビリティと信頼性開発ワークフローとテスト+1

スライド 5 枚15:44EN

AI Engineer· 2026年11月1日Yijia Liang on Building Office-Compatible Engines for Finance AgentsYijia Liang · Compound AICompound’s approach combines shared agent inboxes, document engines and cited access to large data rooms.エージェント工学Software engineeringDeveloper productivity

スライド 5 枚16:37EN

AI Engineer· 2026年11月1日Nick Nisi: What a Fruit Fly Code Reviewer Reveals About Human ReviewNick Nisi · WorkOSA simulated fruit fly becomes an unlikely code reviewer—and a starting point for a team-owned automated review pipeline.開発ワークフローとテストコーディングエージェントSoftware engineering+1

18:52EN

AI Engineer· 2026年11月1日Hahnbee Lee and Lincoln Murr on Documentation and Payments for AI AgentsHahnbee Lee, Lincoln Murr · MintlifyAs agents increasingly read docs and use services, Mintlify and Coinbase describe the importance of accurate content, APIs, payment permissions and maintenance.エージェント工学Agentic commerceDeveloper productivity

1:27:47EN

Lenny's Podcast· 2026年11月1日ポッドキャスト · 2 人Hector Serrano on Building a Paid Creator Program at Wispr FlowLRHSゲスト Hector Serrano · ホスト Lenny RachitskyHow a creator-led growth team recruits, compensates and supports paid UGC creators—and uses founder storytelling alongside ads.Growth StrategyCreator EconomyContent Strategy+1

1:09:46EN

PragerU· 2026年11月1日Rob McCoy and Shabbos Kestenbaum on the Ten Commandments, Family and FaithShabbos Kestenbaum, Rob McCoy · PragerUA Christian pastor and an Orthodox Jewish host discuss the religious meaning of the commandments and their application to family, community and public life.ReligionPhilosophy

スライド18:45EN

AI Engineer· 2026年11月1日Ramakrishnan Lokanathan: Evaluate the AI Agent’s Job, Not Just Its AnswerRamakrishnan LokanathanA practical framework for testing complete AI workflows, combining human feedback and regression checks with more challenging evaluations.エージェント工学AI SafetyMachine Learning

27:34EN

Latent Space· 2026年10月31日ポッドキャスト · 3 人Joseph Kim on Building AI Tools for Financial WorkSwRiJKゲスト Joseph Kim · ホスト swyx, RichardOpenAI’s Joseph Kim discusses data, human review, taste and evaluations in building a financial-services product.金融 AIエンタープライズ AI人による検証（HITL）+2

17:42EN

PragerU· 2026年10月31日Tanya Tsikanovsky on Homelessness and Local Politics in West HollywoodShabbos Kestenbaum, Tanya Tsikanovsky · PragerUThe City Council candidate discusses housing, immigration and identity after a public comment at a Los Angeles council meeting.Political Philosophy

2:38:15EN

PowerfulJRE· 2026年10月31日ポッドキャスト · 3 人Joe Rogan with Francis Foster and Konstantin Kisin on Politics, Purpose and Life After AIJRFFKKゲスト Francis Foster, Konstantin Kisin · ホスト Joe RoganThe TRIGGERnometry hosts join Rogan for a wide-ranging discussion of online outrage, politics, religion, work and the future of AI. Their political and historical assertions include speculation and are presented as the speakers’ views.Political PhilosophySocial MediaHuman-AI Collaboration+1

24:30EN

a16z· 2026年10月31日ポッドキャスト · 4 人Kurtis Blow, Nas and Rev Run on Hip-Hop’s Early DaysNaKBRRRSゲスト Kurtis Blow, Rev Run, Roxanne Shanté · ホスト NasThe artists trace a path from Harlem and Bronx parties to mentorship, touring and a song that connected generations.HistoryCreativityStorytelling

1:26:42EN

Cognitive Revolution "How AI Changes Everything"· 2026年10月31日ポッドキャスト · 7 人AI:AM on Alignment, Memory Chips and an Agent-Run EconomyNLPNAADOゲスト Anastasios Angelopoulos, Debo Olaosebikan, Samvit Ramadurgam, Michael Freeman, Sagar Vaze · ホスト Nathan Labenz, Prakash NarayananThe Cognitive Revolution’s hosts examine reported model behavior, new memory hardware, work and cyber risk with guests from Arena, Kepler, Union, ServiceNow and Mistral.評価とオブザーバビリティAI AlignmentAI security+2

スライド 8 枚21:39EN

AI Engineer· 2026年10月31日Jeff Smith on Safer Database Access for AI AgentsJeff Smith · OracleOracle’s Jeff Smith explains why generated SQL can be misleading and shows how reviewed reports, schema context and database-level controls can limit agent risk.Natural-language database queriesMCP とツールコンテキストエンジニアリング+2

26:05EN

Latent Space· 2026年10月31日ポッドキャスト · 2 人Aman Singh on AI Agents for Long-Running Financial Work at ArcaRMASゲスト Aman Singh · ホスト Richard MacManusArca’s AI platform lead explains its agent harness, persistent memory, human approvals and verification layers.エージェント工学金融 AI安全性とガバナンス+2

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