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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
2:17:48EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月14日ポッドキャストAgent IDs Are Empty, Rogue Agents Are Coming, and We Might Have to Bargainホスト Nathan LabenzGovAI’s Alan Chan scores two years of agent-governance infrastructure with Nathan Labenz, then walks through a recursive-self-improvement paper co-authored with OpenAI’s Jakub Pachocki and Anthropic’s Jack Clark.エージェント安全性とガバナンスAI security+3
2:19:30EN
Cognitive Revolution "How AI Changes Everything"· 2026年9月5日ポッドキャストThe investigators were allowed six days. The word protein appeared once.ホスト Nathan LabenzA week of Cognitive Revolution morning shows on OpenAI’s agent-swarm incident, GPT-6 Astra’s loop transformer, and whether the pause debate is already over.セキュリティと安全性安全性とガバナンスAgent red teaming+3
1:21:06EN
Cognitive Revolution "How AI Changes Everything"· 2023年4月27日ポッドキャストEveryone Talks About RLHF. Almost Nobody Is Doing It.ホスト Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.プロダクトと UX評価(Evals)オブザーバビリティと信頼性+3