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슬라이드 7장35:19EN
AI Engineer· 2026년 10월 25일SallyAnn 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.평가와 관측 가능성평가(Evals)에이전트 엔지니어링+2
슬라이드 8장15:27EN
AI Engineer· 2026년 10월 25일What 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.에이전트 엔지니어링평가(Evals)관측 가능성과 안정성+2
2:17:48EN
Cognitive Revolution "How AI Changes Everything"· 2026년 10월 14일팟캐스트Agent IDs Are Empty, Rogue Agents Are Coming, and We Might Have to Bargain진행자 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.에이전트안전과 거버넌스AI security+3
2:19:30EN
Cognitive Revolution "How AI Changes Everything"· 2026년 9월 5일팟캐스트The investigators were allowed six days. The word protein appeared once.진행자 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.보안과 안전안전과 거버넌스Agent red teaming+3
1:21:06EN
Cognitive Revolution "How AI Changes Everything"· 2023년 4월 27일팟캐스트Everyone Talks About RLHF. Almost Nobody Is Doing It.진행자 Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.제품과 UX평가(Evals)관측 가능성과 안정성+3