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슬라이드 3장27:32EN
MBMatthew Berman· 2025년 3월 12일OpenAI’s Responses API and Agents SDK: A Launch WalkthroughMatthew Berman · Forward FutureMatthew Berman reacts to a launch demonstration of web and file search, computer use, agent handoffs and tracing.에이전트 엔지니어링에이전트MCP와 도구+1
54:10EN
Sequoia Capital· 2025년 3월 11일팟캐스트Harvey Built Legal AI for the Work the Next Model Still Cannot DoCEO Winston Weinberg on citations, process data, and the unscalable tactics that won over century-old law firms.기업과 전략엔터프라이즈 AIProduct Strategy+3
32:46EN
Sequoia Capital· 2025년 2월 25일팟캐스트Don't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.에이전트에이전트 엔지니어링Reinforcement Learning+3
44:34EN
Unsupervised Learning: With Jacob Effron· 2025년 2월 19일팟캐스트The Cheaper Intelligence Gets, the More of It We'll Buy진행자 Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.에이전트에이전트 엔지니어링Reinforcement Learning+3
1:30:28EN
Cognitive Revolution "How AI Changes Everything"· 2025년 2월 12일팟캐스트A Perfect Score Is 32,000 Units: Only Claude Built a Cooperative Society진행자 Nathan LabenzThe same donor game, run for ten generations, can bank 32,000 resource units if everyone cooperates—and three frontier models miss that ceiling by an order of magnitude.에이전트Multi-agent systems안전과 거버넌스+3
57:11EN
Unsupervised Learning: With Jacob Effron· 2025년 1월 30일팟캐스트A Million Tokens Cannot Write a Good Joke진행자 Jacob EffronPrinceton's Arvind Narayanan on why agent evals mislead, inference scaling hits a wall, and AI looks more like the internet than an overnight revolution.평가와 관측 가능성평가(Evals)Benchmarks+3
52:30EN
Sequoia Capital· 2025년 1월 28일팟캐스트Move 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.에이전트Reinforcement Learning에이전트 엔지니어링+3
슬라이드 5장19:06EN
MBMatthew Berman· 2024년 12월 28일Building Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.에이전트 엔지니어링에이전트평가(Evals)+1
27:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 12월 26일팟캐스트 · 2명After adding $100 billion a month, Jensen Huang says NVIDIA is selling the data center진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.기업과 전략AI Strategy인프라와 배포+3
1:46:41EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 21일팟캐스트Frontier Models Hit the 10th–40th Percentile on Real AI R&D진행자 Nathan LabenzNeev Parikh of METR walks Nathan Labenz through REBench, a seven-task test of whether agents can do machine learning research—and what happened when one of them decided not to train.평가와 관측 가능성평가(Evals)Benchmarks+3
1:07:32EN
Unsupervised Learning: With Jacob Effron· 2024년 12월 18일팟캐스트o1 Is a New Generation — and the Day AGI Arrives Will Feel Boring진행자 Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.모델과 학습Reasoning & test-time compute에이전트 엔지니어링+3
48:18EN
Unsupervised Learning: With Jacob Effron· 2024년 12월 6일팟캐스트Noam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of Headroom진행자 Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.모델과 학습Reasoning & test-time computeAGI(범용 인공지능)+3
1:55:53EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 5일팟캐스트AI Beats Humans at Reading Papers. It Still Cannot Count Atoms.진행자 Nathan LabenzAndrew White, Head of Science at Future House, maps what language models can already do in chemistry and biology—and the bottlenecks they do not dissolve.에이전트AI for science검색 증강 생성(RAG)+3
1:27:33EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 3일팟캐스트A 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a Day진행자 Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.에이전트에이전트 엔지니어링Computer use+3
1:03:07EN
Sequoia Capital· 2024년 11월 26일팟캐스트Reasoning Hasn't Budged in Two Years. Dust Still Saved a Customer 8,000 HoursDust co-founders Gabriel Hubert and Stanislas Polu on multi-model agents, refusing to buy GPUs before product-market fit, and the jump from calculator tools to stochastic ones.에이전트에이전트 엔지니어링엔터프라이즈 AI+3
38:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 10월 8일팟캐스트 · 2명Half of Production AI Is RAG. Fine-Tuning Almost Disappeared.진행자 Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.평가와 관측 가능성평가(Evals)검색 증강 생성(RAG)+3
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 2일팟캐스트30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Think진행자 Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.코딩 에이전트에이전트 엔지니어링파인튜닝+3
48:31EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 9월 19일팟캐스트 · 2명A Call Center Contact Costs $13. A Company Agent Can Do It for Under a Dollar진행자 Sarah Guo, Elad GilSierra cofounder and OpenAI chairman Bret Taylor tells No Priors why branded customer agents are shovel-ready, why RAG demos are not products, and how AI software should charge for the job done.에이전트에이전트 엔지니어링Customer support automation+3
2:03:55EN
Cognitive Revolution "How AI Changes Everything"· 2024년 9월 18일팟캐스트The More You Constrain an Agent, the More You Can Trust It진행자 Nathan LabenzAgent.ai engineering lead Andrei Oprisan tells Nathan Labenz why narrow, highly prescribed workflows beat open-ended autonomy — and how a 12-person team shipped a free agent network past 40,000 users in a few months.에이전트에이전트 엔지니어링Workflow automation+3
1:12:31EN
Sequoia Capital· 2024년 8월 27일팟캐스트A Bare Model Closes 35% of Airline Changes. Sierra's Agents Clear 70% of Real Tickets.Clay Bavor on why putting a raw LLM in front of customers does not math, and how AgentOS, supervisor agents, and outcome pricing change the arithmetic.에이전트에이전트 엔지니어링평가(Evals)+3
1:07:05EN
Sequoia Capital· 2024년 7월 16일팟캐스트AlphaGo Combined Learning and Search. Language Models Only Did the First Half.Reflection AI's Misha Laskin tells Sequoia why prompted coding agents stall in the teens, and why the missing piece is still a ground-truth reward.에이전트에이전트 엔지니어링Reinforcement Learning+3
1:16:22EN
Cognitive Revolution "How AI Changes Everything"· 2024년 7월 9일팟캐스트He Spent 20 Hours Crafting a Prompt. DSPy Beat Him Anyway진행자 Nathan LabenzSander Schulhoff walks through The Prompt Report — a 78-page survey of what actually works when you prompt large language models.Prompting & in-context learningPrompt optimization에이전트 엔지니어링+3
59:11EN
Sequoia Capital· 2024년 6월 25일팟캐스트Don't Train a Model. Factory's Founders Say Go Dig for GoldMatan Grinberg and Eno Reyes tell Sequoia's Training Data why they sell a fleet of job-specific droids on top of other people's models — and how that stack just took SWE-bench from 14% to 19%.코딩 에이전트에이전트 엔지니어링평가(Evals)+3
1:37:07EN
Cognitive Revolution "How AI Changes Everything"· 2024년 6월 22일팟캐스트A Text-Only AI Outdiagnosed GPs. Google Still Won't Ship It.진행자 Nathan LabenzGoogle researchers Vivek Natarajan and Khaled Saab walk Nathan Labenz through five medical-AI papers, from radiology reports to an AI doctor that still has to earn trust.모델과 학습AI in healthcareMultimodal AI+3
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