筛选结果
29 篇排序
1:05:21EN
Sequoia Capital· 2026年9月15日播客The Bridge From Model to Workflow Is a Trillion-Dollar BusinessBox CEO Aaron Levie argues that the money in this cycle sits in the messy gap between frontier models and real enterprise work — and that coding's overnight diffusion will not repeat for everyone else.
55:19ENSequoia Capital· 2026年8月25日播客Human 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.
48:55ENSequoia Capital· 2026年7月14日播客Anthropic'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.
38:45ENSequoia Capital· 2026年6月16日播客The 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.
51:09ENSequoia Capital· 2026年6月11日播客Build 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.
45:33ENSequoia Capital· 2026年5月26日播客Cursor Ships 1TB of Composer Weights Across Oceans in Under a MinuteFederico Cassano and Fireworks' Dima walk through the globally split RL stack that trained Composer 2 on a sparse trillion-parameter MoE.
58:27ENSequoia Capital· 2026年3月24日播客Even 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.
40:56ENSequoia Capital· 2026年3月10日播客Four of the Top Five Defense Primes Still Run Hardware Tests on PowerPointNominal’s cofounders argue that hardware never got the last twenty years of software infrastructure, and that physical AI will stall until test data lives in one place.
44:46ENSequoia Capital· 2026年2月10日播客A Single Training Environment Can Cost Millions. Prime Intellect Wants a GitHub for RLWill Brown and Johannes Hagemann argue that the eval suite you already use to test agents is one step away from a training set.
51:56ENSequoia Capital· 2026年2月3日播客Insurance Spends $70 Billion on BPOs. Pace Wants 80% Gross Margins InsteadJamie Cuffe tells Sequoia's Training Data how Pace is turning insurance back-office work into agentic process outsourcing—and why every one of its pilots has reached production.
48:03ENSequoia Capital· 2026年1月27日播客Coding Will Be Solved. The Bottleneck Is Saying What You WantWarp founder Zach Lloyd tells Sequoia's Sonya Huang why a rebuilt terminal became the lucky form factor for coding agents, and why he stopped subsidizing tokens.
39:47ENSequoia Capital· 2026年1月21日播客The 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.
44:10ENSequoia Capital· 2025年10月21日播客One Model Talked Another Into Slack Off — Then Uninstalled Windows DefenderIrregular co-founder Dan Lahav tells Sequoia’s Training Data why frontier AI security has to be invented from scratch as models become autonomous economic actors.
59:43ENSequoia Capital· 2025年9月30日播客Goose is writing its own pull requests: how Block is trying to save a quarter of the weekCTO Dhanji Prasanna tells Sequoia how an open-source agent, a functional reorg, and a weekly hours-saved metric are turning Block into an AI-first company.
37:37ENSequoia Capital· 2025年7月22日播客A 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.
41:13ENSequoia Capital· 2025年7月11日播客From 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.
59:38ENSequoia Capital· 2025年7月1日播客ElevenLabs Was Supposed to Be RoadkillCo-founder Mati Staniszewski on dirty audio data, prosumer virality, and why voice should become the default interface for technology.
40:33ENSequoia Capital· 2025年6月24日播客Fifty People in Slack. Four Minutes to the Smoking Gun.Traversal's co-founders on turning DevOps heart attacks into agent-run root cause analysis — and why observability's second-largest software spend still leaves troubleshooting as a whodunit.
38:25ENSequoia Capital· 2025年5月27日播客A 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.
1:26:19ENSequoia Capital· 2025年4月8日播客He turned down a billion dollars for a world with a billion developersReplit CEO Amjad Masad tells Sequoia’s Training Data why a six-person company walked away from a life-changing offer, and why a billion people writing software is a better end state than AGI as universal basic income.
43:04ENSequoia Capital· 2025年3月25日播客750 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.
54:10ENSequoia Capital· 2025年3月11日播客Harvey 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.
32:46ENSequoia Capital· 2025年2月25日播客Don'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.
52:30ENSequoia Capital· 2025年1月28日播客Move 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.加载更多已显示 24 篇，共 29 篇