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55:19EN
Sequoia Capital· 2026년 8월 25일팟캐스트Human Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.에이전트Search & retrieval에이전트 엔지니어링+3
53:44EN
Sequoia Capital· 2026년 8월 18일팟캐스트The Biggest Bug in Today’s Models Is That the Weights Never ChangeTuring Award winner Rich Sutton and Khurram Javed founded Oak Lab to build agents that keep learning after they ship — and they call synthetic data a big mistake.에이전트Continual learningReinforcement Learning+3
48:55EN
Sequoia Capital· 2026년 7월 14일팟캐스트Anthropic's Platform Grew Three Layers in a Year — and Tokens Now Have JobsKatelyn Lesse and Angela Jiang tell Sequoia's Training Data how Anthropic went from a stateless Messages API to knowledge, execution, and coordination — without trying to own the servers.에이전트에이전트 엔지니어링Agent orchestration+3
38:45EN
Sequoia Capital· 2026년 6월 16일팟캐스트The 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.에이전트Multi-agent systems에이전트 엔지니어링+3
51:09EN
Sequoia Capital· 2026년 6월 11일팟캐스트Build like the model will eat your harness in a yearLogan Kilpatrick, who leads Google AI Studio and the Gemini API, tells Sequoia's Sonya Huang why agent scaffolding is a 12-month asset, why coding already feels like narrow superintelligence, and why Google is optimizing for outcomes instead of eyeballs.에이전트에이전트 엔지니어링Harness engineering+3
58:27EN
Sequoia Capital· 2026년 3월 24일팟캐스트Even a dumber AI can win science if it never leaves the labGinkgo Bioworks CEO Jason Kelly tells Sequoia why autonomous labs, not smarter models, will change how experimental science gets done.에이전트AI for science에이전트 엔지니어링+3
39:47EN
Sequoia Capital· 2026년 1월 21일팟캐스트The Context at Step 14 Isn't in the CodeLangChain cofounder Harrison Chase on why long-horizon agents finally work—and why traces, harnesses, and first-draft workflows matter more than scaffolding.에이전트컨텍스트 엔지니어링에이전트 엔지니어링+3
35:45EN
Sequoia Capital· 2025년 8월 26일팟캐스트Six Years of Revenue, Then Four Times That in Eight Monthsn8n CEO Jan Oberhauser tells Sequoia how two bets — becoming an AI-agent builder, then deleting the leads metric — turned a workflow tool into a default orchestration layer.에이전트Company BuildingWorkflow automation+3
37:37EN
Sequoia Capital· 2025년 7월 22일팟캐스트A dozen people, 28 minutes, and one shared desktopThe OpenAI trio behind ChatGPT Agent explain how Deep Research and Operator became a virtual computer that can reason for half an hour and still ask you before it spends money.에이전트Computer use에이전트 엔지니어링+3
41:13EN
Sequoia Capital· 2025년 7월 11일팟캐스트From 49 Multiplications to 48: DeepMind’s AI Rewrites a Fifty-Year Math RecordPushmeet Kohli explains how AlphaEvolve couples Gemini with evaluators to invent algorithms, prove old conjectures, and change which scientific problems are even worth attempting.에이전트AI for scienceMulti-agent systems+3
38:25EN
Sequoia Capital· 2025년 5월 27일팟캐스트A thousand airplanes will never train an AI engineerFormer Airbus CTO Paul Eremenko explains why physical-world engineering still has no coding-AI moment, and how P-1 AI's agent Archie is supposed to get there anyway.에이전트에이전트 엔지니어링Synthetic data+3
43:04EN
Sequoia Capital· 2025년 3월 25일팟캐스트750 Million Excel Users, 30 Million Engineers: Wordware's Bet on Word ArtisansFilip Kozera tells Sequoia why English is the assembly language of LLMs, and why the people who win will be the ones who can encode taste into structured prompts.에이전트에이전트 엔지니어링Prompting & in-context learning+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
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
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
49:14EN
Sequoia Capital· 2024년 9월 17일팟캐스트Humanoid robots fell from $1.5 million to $30,000. The GPT-3 moment is still a verbNvidia’s Jim Fan tells Sequoia how three kinds of data, a humanoid bet, and a System-1 motor-control model could unlock general-purpose robots.에이전트RoboticsScaling Laws+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
49:50EN
Sequoia Capital· 2024년 6월 18일팟캐스트Unconstrained agents captivated Twitter. Custom ones are what ship.LangChain founder Harrison Chase tells Sequoia’s Training Data what an agent actually is, why AutoGPT stalled, and which cognitive architectures reach production.에이전트에이전트 엔지니어링Agent orchestration+3