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Erik Torenberg 与 Marc Andreessen 探讨了人工智能、媒体的现状，以及正在重塑互联网的广泛文化与经济变革。他们讨论了围绕AI的叙事——从恐惧到炒作——如何影响公众认知，以及为何实际使用情况讲述的是截然不同的故事。 谈话涉及AI对就业和生产力的影响、"AI原生"建设者的崛起，以及为何更强的能力往往会扩大工作而非淘汰工作。Andreessen 还分析了企业如何适应变化，从重组团队到围绕更全能的"建设者"重新定义角色。 他们还探讨了不断变化的媒体格局——从影响力与信息的动态变化，到传统权威的瓦解——及其对信任、文化和代际态度的影响。沿途，他们触及了从机构权力到新兴互联网亚文化等话题，全面审视了技术如何重塑系统与社会。 时间戳： 00:00 - 开场 00:42 - Anthropic 勒索事件与 AI 末日论文学 02:49 - 自杀式共情与 SPLC 指控 16:33 - AI、就业与 AI 吸血鬼的崛起 25:39 - 技术岗位的未来：从程序员到建设者 30:55 - AI 精神错乱、AI 自我安慰，以及模型其实已经很棒了 38:48 - 为何 AI 情绪调查具有误导性 45:28 - UFO：我们所知的事实与政府隐藏的秘密 52:25 - 给年轻人的建议与代际鸿沟 资源： 在 X 上关注 Marc Andreessen：https://x.com/pmarca 保持更新： 如果您喜欢本期节目，请务必点赞、订阅并与朋友分享！ 在 X 上找到 a16z：https://twitter.com/a16z 在 LinkedIn 上找到 a16z：https://www.linkedin.com/company/a16z 在 Spotify 上收听 a16z 播客：https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX 在 Apple Podcasts 上收听 a16z 播客：https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 关注我们的主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考，不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券，且不针对任何 a16z 基金的投资者或潜在投资者。a16z 及其关联方可能持有所讨论公司的投资。更多详情请参见 http://a16z.com/disclosures。

在a16z Runtime大会的闭幕主题演讲中，普通合伙人Erik Torenberg与公司联合创始人Marc Andreessen和Ben Horowitz共同探讨了大会亮点、大语言模型能力的现状，以及为何尽管资本支出巨大，人工智能并非泡沫。 时间戳： 00:00 开场 01:00 人工智能能否真正创造？智能与发明 03:32 混音、原创性与人类创造力的本质 06:20 Ben谈嘻哈、创新与创意天才 09:10 智能、权力与真正的领导者 12:20 超越智商：领导力、情感与心智理论 16:40 具身智能——身心问题 20:14 人工智能在“心智理论”方面的真实水平 23:02 我们处于人工智能泡沫中吗？基本面与炒作 27:58 平台变革、谷歌的警钟与新用户体验范式 31:00 在独特的人工智能时代指导创始人 34:14 人才、芯片与即将到来的过剩周期 37:10 中美人工智能竞赛与机器人未来 38:52 再工业化与下一步发展 保持更新： 如果您喜欢本期节目，请点赞、订阅并与朋友分享！ 资源： 关注Marc的X账号：https://x.com/pmarca 关注Ben的X账号：https://x.com/bhorowitz 关注a16z的X账号：https://x.com/a16z 关注a16z的领英账号：https://www.linkedin.com/company/a16z 在Spotify收听a16z播客：https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX 在Apple Podcasts收听a16z播客：https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 关注主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考；不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券；且不针对任何a16z基金的投资者或潜在投资者。a16z及其关联方可能持有所讨论公司的投资。更多详情请参见a16z.com/disclosures。

山姆·奥特曼带领OpenAI从2015年创立之初的非营利研究机构，在十年后成长为全球最具价值的初创公司。 在本期节目中，a16z联合创始人本·霍洛维茨与普通合伙人埃里克·托伦伯格与山姆展开对话，探讨OpenAI多元化战略背后的核心逻辑、发布Sora的原因、内部使用模型的方式、最佳AI评估方法，以及未来发展方向。 时间轴： 0:00 开场 0:41 OpenAI的愿景与基础设施 2:37 商业模式与垂直整合 5:08 AGI、Sora与社会协同进化 8:01 AI交互界面的未来 9:12 AI科学家与科学进步 11:44 对进展与模型能力的反思 16:17 山姆的CEO经历与领导力心得 17:34 战略合作与基础设施规模化 25:05 监管、安全与社会影响 28:33 版权、开源与内容创作 33:15 能源、政策与AI资源需求 37:07 变现模式与用户行为 43:03 人才争夺战与个人思考 45:20 给创始人的建议 资源链接： 关注山姆的X账号：https://x.com/sama 关注OpenAI的X账号：https://x.com/openai 了解更多OpenAI信息：https://openai.com/ 体验Sora：https://sora.com/ 关注本的X账号：https://x.com/bhorowitz 持续关注： 如果您喜欢本期节目，请点赞、订阅并分享给朋友！ 关注a16z的X账号：https://x.com/a16z 关注a16z的领英页面：https://www.linkedin.com/company/a16z 在Spotify收听a16z播客：https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX 在Apple Podcasts收听a16z播客：https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 关注主持人：https://x.com/eriktorenberg 请注意：本内容仅供信息参考，不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券，且不针对任何a16z基金的投资者或潜在投资者。a16z及其关联方可能持有所讨论公司的投资。更多详情请参阅a16z.com/disclosures。

当人工智能开始为所有人生成内容，却没人愿意看时，会发生什么？ 在本期节目中，MSNBC的克里斯·海耶斯与广告技术资深人士安东尼奥·加西亚·马丁内斯，与a16z普通合伙人埃里克·托伦伯格一同探讨注意力经济的变化：从“AI垃圾内容”和泛滥的信息流兴起，到我们真正想关注的内容与平台强推内容之间的差异。 他们探讨了： - 人工智能如何改变内容的创作与呈现方式 - 为什么互联网广告大多仍然糟糕 - 群聊的回归——以及大众文化的缓慢消亡 基于克里斯的新书《塞壬的呼唤》，本期节目坦诚审视了人工智能可能在我们网络生活中放大或破坏的方面。 时间戳： 00:00 注意力时代与AI垃圾内容 00:40 嘉宾介绍与背景 02:02 注意力的污染与垃圾信息 03:03 AI内容：垃圾还是创意？ 05:14 人类对AI生成内容的反应 07:01 社交媒体、名声与自我认知 09:45 群聊解决方案与社区 14:43 收入模式与有用技术vs.盈利技术 19:22 文化的碎片化与同质化 22:25 媒体、广告与AI的未来 24:35 过度碎片化、同质化与本地文化的消亡 29:54 算法、方言与新的全球单一文化 33:00 从垃圾到实质，还是饱和？ 36:00 AI、界面与人机对话 38:18 将每一秒商品化 41:47 增长、崩溃与开放网络的未来 资源： 在X上关注克里斯：https://x.com/chrislhayes 在X上关注安东尼奥：https://x.com/antoniogm 了解更多关于克里斯的新书《塞壬的呼唤》：https://sirenscallbook.com/ 了解更多关于安东尼奥的著作《混沌猴子》：https://www.harpercollins.com/products/chaos-monkeys-antonio-garcia-martinez?variant=32207601532962 保持更新： 告诉我们你的想法：https://ratethispodcast.com/a16z 在Twitter上关注a16z：https://twitter.com/a16z 在LinkedIn上关注a16z：https://www.linkedin.com/company/a16z 在你最喜欢的播客应用上订阅：https://a16z.simplecast.com/ 关注我们的主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考；不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券；且不针对任何a16z基金的投资者或潜在投资者。a16z及其关联方可能持有所讨论公司的投资。更多详情，请参见a16z.com/disclosures。

在本期《本与马克秀》中，a16z联合创始人马克·安德森和本·霍洛维茨与a16z普通合伙人、媒体公司Turpentine创始人埃里克·托伦伯格坐在一起，剖析互联网如何粉碎了旧媒体秩序，并重塑了美国权力的运作方式。 这场对话始于对媒体演变的探讨，但很快便扩展为更宏大的主题：关于真相、信任以及机构权威的崩塌。他们探讨了社交媒体如何同时成为X光机和引擎，为何真实感如今胜过精致包装，以及政治与新闻业的规则如何被永久改变。 他们共同剖析了以下内容： - 为何2017年标志着科技界与新闻界之间的结构性断裂 - 客观性、行动主义与“向权力说真话”之间的张力 - 为何播客主而非评论员正在设定议程 - 杠铃策略如何重塑媒体：短视频病毒式传播与长内容深度并存 从水门事件、罗根的崛起、传统守门人的衰落，到奥巴马、特朗普和卡戴珊家族背后的媒体策略——本期节目探讨了我们如何走到今天，接下来会发生什么，以及这对创始人、选民和任何试图构建（或讲述）故事的人意味着什么。 时间码： 00:00 引言 00:40 媒体演变：从集中化到颠覆 02:33 互联网对传统媒体的影响 09:32 现代科技新闻中的行动主义 12:30 机构信任的兴衰 15:07 认识传统媒体的转变 20:51 新闻业：客观性与行动主义之争 25:08 马丁·古里与权威的崩塌 28:30 特朗普时代与媒体范式转变 32:23 去中心化：从谈话广播到社交媒体 37:04 社交媒体是引擎还是摄像机？ 43:50 本对媒体与政治的早期看法 49:49 特朗普作为传统媒体与社交媒体之间的桥梁 55:44 媒体培训与未经修饰的真实性 57:57 真人秀、职业摔跤与新剧本 1:01:04 戏剧性、党派之争与个性时代 1:03:13 有线新闻如何变成24/7娱乐 1:09:27 UFC早期争取媒体准入的挣扎 1:14:44 杠铃效应：短视频与长播客 1:29:30 失势时的颠覆工具 1:32:00 创始人的媒体策略 1:37:16 直接触达的力量：创始人、品牌与受众 收听我们！ Apple：https://bit.ly/3SdsfNt Spotify：https://spoti.fi/3SclPOr 资源： 马克的X账号：https://x.com/pmarca 马克的Substack：https://pmarca.substack.com/ 本的X账号：https://x.com/bhorowitz 埃里克的X账号：https://x.com/eriktorenberg 埃里克的Substack：https://eriktorenberg.substack.com/ 保持关注： 在X上找到我们：https://x.com/a16z 在领英上找到我们：/ a16z 此信息仅供一般教育目的，不构成购买、持有或出售任何投资或金融产品的建议。Turpentine是a16z Holdings, L.L.C.的收购项目，并非银行、投资顾问或经纪交易商。本播客中提及的个人和公司并非认可AH Capital或其任何关联公司（包括但不限于a16z Perennial Management L.P.）。本播客中提及、引用或描述的任何投资或投资组合公司并不代表a16z的所有投资，且无法保证这些投资将盈利，或未来的其他投资将具有类似特征或结果。a16z的投资清单可在https://a16z.com/investment-list/获取。所有投资均涉及风险，包括可能损失本金。过往表现不保证未来结果，所呈现的观点不能视为未来表现的指标。在做出涉及法律、税务或会计影响的决策前，应咨询适当的专业人士。信息来源于发布日认为可靠的来源，但a16z不保证其准确性。

在美国，一座新矿从审批到建成可能需要超过15年——然而，从智能手机到战斗机，再到人工智能数据中心，我们依赖的几乎所有现代技术，都离不开关键矿物的稳定供应。 在本期节目中，埃里克·托伦伯格在演播室与玛丽安娜矿业公司创始人特纳·考德威尔，以及美国活力基金普通合伙人艾琳·普莱斯-赖特和合伙人瑞安·麦肯塔什一同探讨。 特纳在特斯拉工作了近十年，从工厂设计一路向上游发展，涉足电池材料和采矿领域。如今，他正在打造一家新型采矿和精炼公司——垂直整合、软件优先——旨在满足我们工业未来的需求。 我们深入探讨了该行业为何如此问题重重，将矿石转化为可用材料究竟需要什么，以及美国如何重建其开采、精炼和制造最重要物资的能力。 时间码： 00:00 引言 00:53 关键矿物的重要性 01:54 采矿过程解析 04:05 采矿行业面临的挑战 05:46 采矿领域的职业路径 06:40 个人经历与见解 11:16 特斯拉的垂直整合 12:47 地缘政治与市场动态 16:24 采矿技术创新 20:47 行业挑战与机遇 28:19 玛丽安娜在建筑和采矿领域的产品与理念 29:30 在采矿中利用技术 32:02 自动化化学处理与优化精炼运营 35:25 精炼厂规模化与调试的挑战 36:55 决定建设什么及在何处合作 38:05 新技术的供应链与商业部署 40:20 风险投资与采矿行业 42:59 关键矿物及其重要性 47:45 美国的许可与监管挑战 53:46 国际战略与未来目标 54:44 结论：重建基础设施与能力 资源： 在X上关注特纳：https://x.com/tbc415 在X上关注艾琳：https://x.com/espricewright 在X上关注瑞安：https://x.com/rmcentush 保持更新： 告诉我们你的想法：https://ratethispodcast.com/a16z 在Twitter上关注a16z：https://twitter.com/a16z 在LinkedIn上关注a16z：https://www.linkedin.com/company/a16z 在你最喜欢的播客应用上订阅：https://a16z.simplecast.com/ 关注我们的主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考；不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券；且不针对任何a16z基金的投资者或潜在投资者。a16z及其关联方可能持有所讨论公司的投资。更多详情请参见a16z.com/disclosures。

人工智能是基础设施的第四大支柱吗？ 基础设施不会消失——它会层层叠加。如今，人工智能正与计算、存储和网络一起，成为新的基础层。 埃里克·托伦伯格采访了a16z的马丁·卡萨多、詹妮弗·李和马特·伯恩斯坦，深入探讨了基础设施在人工智能时代如何演变——从模型和智能体，到开发者工具和用户行为的变化。 我们深入探讨了如今基础设施的真正含义，它与企业级基础设施有何不同，以及为什么软件本身正在被颠覆。此外，我们还探讨了技术用户作为买家的崛起、什么让基础设施公司具有防御性，以及从云计算到新冠疫情再到人工智能的过去几波浪潮如何重塑我们的构建和投资方式。 时间戳： 00:00 基础设施介绍 00:48 定义基础设施及其组成部分 02:27 第四层：人工智能模型 06:34 基础设施的演变 17:46 开发者工具与人工智能浪潮 21:27 数据引擎系统 22:11 人工智能基础设施的防御性 25:28 扩张与收缩阶段 27:09 人工智能与基础设施面临的挑战 28:32 人工智能模型与泛化 30:59 对安德烈·卡帕西关于人工智能演讲的思考 34:09 人工智能与人类期望 36:18 人工智能时代开发者的角色 40:31 合成数据 43:17 人工智能智能体 45:16 垂直整合与水平专业化 资源： 在X上关注马丁：https://x.com/martin_casado 在X上关注詹妮弗：https://x.com/JenniferHli 在X上关注马特：https://x.com/BornsteinMatt 保持更新： 告诉我们你的想法：https://ratethispodcast.com/a16z 在Twitter上关注a16z：https://twitter.com/a16z 在LinkedIn上关注a16z：https://www.linkedin.com/company/a16z 在你最喜欢的播客应用上订阅：https://a16z.simplecast.com/ 关注我们的主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考；不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券；并且不针对任何a16z基金的投资者或潜在投资者。a16z及其关联公司可能持有所讨论公司的投资。更多详情请参见a16z.com/disclosures。

a16z Crypto普通合伙人Ali Yahya、Arianna Simpson和Erik Torenberg深入探讨了当前加密货币领域真正奏效的应用——从稳定币作为现实世界支付层的崛起开始。他们讨论了Stripe和SpaceX等公司如何采用稳定币，监管变化如何为加密初创公司打开新大门，以及人工智能与加密货币如何开始交汇。 他们还涵盖了： - 去中心化社交网络的未来 - 以太坊、Solana及其他公链的现状 - 仍阻碍行业发展的误解 - 一场务实的对话：什么是真实的，什么是炒作，以及加密货币最终在哪些领域找到了突破口。 时间码： 00:00 引言 00:45 比特币的原始愿景与演变 01:47 稳定币：游戏规则改变者 03:02 稳定币的当前应用场景 05:22 金融体系面临的挑战 07:08 稳定币与金融体系的未来 09:02 大公司在加密货币中的角色 18:21 去中心化社交网络与消费者偏好 23:20 人工智能与加密货币的交汇 31:32 关于加密货币的误解 35:54 智能合约平台之争 39:33 政策变化与未来机遇 资源： 在X上关注Ali：https://x.com/alive_eth 在X上关注Arianna：https://x.com/AriannaSimpson 保持更新： 告诉我们你的想法：https://ratethispodcast.com/a16z 在Twitter上关注a16z：https://twitter.com/a16z 在LinkedIn上关注a16z：https://www.linkedin.com/company/a16z 在你最喜欢的播客应用上订阅：https://a16z.simplecast.com/ 关注我们的主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考；不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券；且不针对任何a16z基金的投资者或潜在投资者。a16z及其关联方可能持有所讨论公司的投资。更多详情请参见a16z.com/disclosures。

在本期《本周消费》节目中，a16z 普通合伙人 Anish Acharya 和 Erik Torenberg 与 a16z 董事会合伙人、前微软 Windows 部门总裁 Steven Sinofsky 一同深入探讨了当前 AI 热潮如何与过去的计算转型相似（以及不同之处）。 他们探讨了 AI 是处于“Windows 3.1”阶段，还是仍处于最早期阶段；为什么消费者采用速度超过了开发者的准备程度；以及部分自主性、锯齿智能和“氛围编码”等框架如何塑造未来的构建方向。他们还深入分析了真正的瓶颈所在——并非技术本身，而是公司、产品和人员的工作方式。 时间码： 00:00 引言 00:35 讨论 Andrej Karpathy 的演讲 02:17 AI 与工具的早期阶段 03:23 氛围写作与氛围编码 07:33 自动化与人类判断 15:13 产品管理的未来 15:55 平台转型与氛围编码 17:54 编程语言的演变 23:07 AI 在创意写作中的应用 28:06 谷歌在科技行业的地位 资源： 在 X 上关注 Anish：https://x.com/illscience 在 X 上关注 Steven：https://x.com/stevesi 保持更新： 告诉我们您的想法：https://ratethispodcast.com/a16z 在 Twitter 上关注 a16z：https://twitter.com/a16z 在 LinkedIn 上关注 a16z：https://www.linkedin.com/company/a16z 在您最喜欢的播客应用上订阅：https://a16z.simplecast.com/ 关注我们的主持人：https://x.com/eriktorenberg 请注意，此处内容仅供信息参考；不应被视为法律、商业、税务或投资建议，也不应用于评估任何投资或证券；且不针对任何 a16z 基金的投资者或潜在投资者。a16z 及其关联方可能持有所讨论公司的投资。更多详情请参见 a16z.com/disclosures。

Arcjet 首席执行官 David Mytton 与 a16z 合伙人 Joel de la Garza 共同探讨了管理网站及网络应用访问权限与操作行为的日益复杂性。核心挑战在于判断自动化流量究竟来自恶意行为者与麻烦的机器人，还是代表真实客户购买产品的 AI 代理。 Joel 与 David 深入分析了如何在分析每个请求时不增加延迟，以及边缘端更快的推理如何为欺诈防护、内容过滤乃至广告技术开辟新可能。 讨论主题包括： - 为何传统威胁分析无法适用于 AI 驱动的网络 - 全上下文安全检查的必要性 - 如何实现亚秒级、高性价比的推理 - 每次访问背后潜藏的多种行为者与操作类型 正如 David 所言，降低推理成本是让应用能够基于完整上下文窗口（即关于用户、会话及应用的所有已知信息）采取行动的关键。 关注社交媒体上的各位嘉宾： David Mytton：https://x.com/davidmytton Joel de la Garza：https://www.linkedin.com/in/3448827723723234/ 查看 a16z 在人工智能领域的全部动态，包括文章、项目及更多播客：https://a16z.com/ai/ 时间戳： 00:00 引言 00:34 AI 机器人的兴起及其潜在益处 02:43 良性流量与恶意流量 | 开发人员与安全团队面临的挑战 03:23 该领域的解决方案 04:37 Robots.txt 的作用 06:42 理解 AI 代理及其运作方式 10:55 在互联网规模下控制流量 12:51 构建指纹识别体系 18:45 机器人行为及新一代 AI 带来的可能性 22:39 本地运行 LLM 的未来

在本期《Ben & Marc Show》中，a16z联合创始人马克·安德森和本·霍洛维茨深入探讨了安德森·霍洛维茨创立背后未经修饰的故事——以及他们如何着手重塑风险投资本身。 马克和本首次详细阐述了打造一家面向未来的世界级风险投资公司的起源、战略和理念——而不仅仅是着眼于下一支基金。他们揭示了如何通过大胆的品牌、全栈支持模式以及对支持杰出创业者的长期承诺来打破行业常规——其核心理念是创始人理应获得真正的支持，而不仅仅是支票。 加入他们引导对话的是埃里克·托伦伯格——安德森·霍洛维茨最新的普通合伙人——他首次在《Ben & Marc Show》中担任主持。埃里克是一位科技企业家、投资者，也是媒体公司Turpentine的创始人。您可以通过马克的公告[此处]了解更多关于埃里克的信息。 他们共同探讨了： - 为什么传统风投需要革新 - a16z如何通过平台模式而非合伙人模式实现规模化 - 重塑当今风险投资的“杠铃策略” - 为什么即使在人工智能时代，风险投资仍然是一门人类手艺 我们非常高兴欢迎埃里克加入团队——希望您喜欢这次对a16z结构、理念和未来的内部解读。 涵盖主题： 00:00 - 开场 / 欢迎埃里克·托伦伯格加入a16z 00:26 - 为什么传统风险投资存在缺陷 03:05 - 马克谈发现风投及其传奇人物 05:12 - 挺过互联网泡沫破裂和天使投资崩溃 07:05 - 帮助创始人融资 / 修复风投关系 08:47 - a16z战略：构建支持平台 12:07 - 首支基金的成功案例：Skype、Instagram、Slack、Okta 12:50 - 打造一个“主宰世界的巨兽” 15:00 - “寿司船”风投问题 18:07 - 以不同方式对待有限合伙人 21:40 - 马克和本的工作关系 23:30 - 为社交媒体时代更新a16z的媒体策略 27:20 - 去中心化媒体环境的历史 30:36 - 企业品牌的衰落与直接面向受众 36:06 - 公司命名 40:13 - 构建a16z的“电影宇宙”人才库 42:16 - 创建联邦模式 51:02 - 决定营销公司 53:26 - 招募普通合伙人 56:33 - 向全栈公司演进 01:03:53 - 杠铃理论：中型风投的消亡 01:11:50 - 为什么风险投资应保持资金过剩 01:19:50 - a16z何时知道自己能跻身顶级行列 01:25:58 - 风险投资是艺术，而非科学 本期节目提及的书籍： - 《公众的反叛》作者：马丁·古里 https://bit.ly/4jDloba - 《臭名昭著的写手》作者：埃里克·伯恩斯 https://bit.ly/4lSkaKy 收听我们！ Apple: https://bit.ly/3SdsfNt Spotify: https://spoti.fi/3SclPOr 资源： 马克的X账号：https://x.com/pmarca 马克的Substack：https://pmarca.substack.com/ 本的X账号：https://x.com/bhorowitz 埃里克的X账号：https://x.com/eriktorenberg 埃里克的Substack：https://eriktorenberg.substack.com/ 保持关注： 在X上找到我们：https://x.com/a16z 在LinkedIn上找到我们：https://www.linkedin.com/company/a16z 此信息仅供一般教育目的，并非购买、持有或出售任何投资或金融产品的建议。Turpentine是a16z Holdings, L.L.C.的收购对象，并非银行、投资顾问或经纪交易商。本播客中提及的个人和公司并非认可AH Capital或其任何关联公司（包括但不限于a16z Perennial Management L.P.）。本播客中提及、引用或描述的任何投资或投资组合公司并不代表a16z的所有投资，且无法保证这些投资将盈利，或未来进行的其他投资将具有类似特征或结果。a16z的投资清单可在https://a16z.com/investment-list/获取。所有投资均涉及风险，包括可能损失本金。过往业绩并不保证未来结果，所呈现的观点不能视为未来业绩的指标。在做出涉及法律、税务或会计影响的决策前，您应咨询适当的专业人士。信息来源于出版日期被认为可靠的来源，但a16z不保证其准确性。

Ben Horowitz, Martin Casado, Raghu Raghuram, and Erik Torenberg discuss the launch of a16z's new Machine Age Fund and the infrastructure buildout behind AI, from chips, memory, and networking to power, cooling, and data centers. Why a dedicated fund now? The group argues that the bottleneck in AI is increasingly shifting from the models themselves to everything beneath them. Hyperscaler CapEx is surging, critical components are booked years in advance, and each new generation of reasoning and agents requires dramatically more compute. They unpack why this cycle looks different from previous infrastructure booms and how AI is turning problems once constrained by engineering into problems that can increasingly be attacked with capital and compute. They also explore where the next generation of infrastructure companies could emerge, why founders are returning to hard technical problems across hardware and systems, and what it will take to rebuild the computing stack for the Machine Age. Timestamps: 00:00 - Intro 00:50 - Introducing the Machine Age Fund 02:00 - Why Founder Interest in Hardware Just 4x'd 04:00 - How Do We Know Demand Isn't a Hype Cycle? 07:00 - Sold Out to 2028: The Unprecedented Supply Crunch 10:00 - What's Actually Bottlenecked Right Now 14:00 - Tokens, Scaling & Why There's No Natural Regulator 19:00 - Agents as a New Kind of Employee: The GrokBot Moment 25:00 - What "AI-Designed" Infrastructure Actually Looks Like 28:00 - Rack Power, Liquid Cooling & the Data Center Redesign 34:00 - 44 Gigawatts by 2028: Why Building Faster Is So Hard 38:00 - Why "Machine Age" Is the Right Name 40:00 - Won't Incumbents Like Nvidia Take Everything? 48:00 - The Founder Profile: Why Hardware Needs Experience Resources: Read more about the Machine Age Fund : https://www.a16z.news/p/the-machine-age-fund Follow Ben Horowitz on X: https://x.com/bhorowitz Follow Raghu Raghuram on X: https://x.com/RaghuRaghuram Follow Martin Casado on X: https://x.com/martin_casado Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

a16z General Partners Martin Casado, Sarah Wang, and Matt Bornstein unpack the story of Cursor: how a small, product-obsessed team entered one of the most competitive markets in technology, took on incumbents with seemingly unbeatable advantages, and repeatedly made decisions that ran against conventional startup wisdom. They revisit the early bet that the interface between humans and AI would matter more than building a coding-specific foundation model, why Cursor built its own product rather than a VS Code plugin, and how the founders' ability to say "no" became one of the company's defining strengths. They also discuss Cursor's rapid evolution from IDE to agent and model platform, and why the team was willing to cannibalize its own products as AI capabilities improved. The conversation gets into what founders can learn from Cursor's approach to competition, hiring, enterprise sales, M&A, and company culture, including why the team remained unfazed by competitors from Microsoft to Anthropic and how its obsessive focus on product ultimately extended into every part of building the company. Timestamps: 00:00 - Intro 00:53 - Back to Early 2024: How a16z First Met Cursor 05:23 - The VS Code Fork vs Plug-In Decision & the Enterprise Bet 09:57 - Vertical Liftoff: Why the B Round Was a No-Brainer 17:03 - The Hardest Round: Claude Code, Competition & the D 23:38 - How You Do Anything Is How You Do Everything: The Hiring Engine 27:24 - Cursor Culture: Craftsmanship, Taste & Twinkle Lights 34:02 - The SpaceX Parallel: Elon-ish Ambition & Impossible Competitors Resources: Explore Cursor Compile: https://cursor.com/compile Follow Martin Casado on X: https://x.com/martin_casado Follow Matt Bornstein on X: https://x.com/BornsteinMatt Follow Sarah Wang on X: https://x.com/sarahdingwang Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Anish Acharya joins Jen Kha to break down the next frontier of AI, from the evolving model landscape and open-source AI to why the application layer, and consumer AI in particular, may be entering a new phase. Anish explains why he believes there will be multiple winners at the model layer, why traditional moats like network effects, scale, and brand still matter, and how companies can choose between frontier and open-weight models depending on the economics of the task. They also explore why models are increasingly specializing, and how applications can combine different types of intelligence to create products that are more valuable than any single model. The conversation then turns to consumer AI: personal agents that can shop and manage your inbox, coding tools enabling a new generation of small businesses, and why Anish thinks we're seeing a renaissance for consumer builders. They also discuss the changing economics of AI software, the rise of "luxury software," and why the biggest risk for today's founders may no longer be thinking too big, but thinking too small. Timestamps: 00:00 - Intro 01:20 - Who Wins the AI Model Race in Three Years? 02:49 - What's Next in the Frontier of Intelligence 07:51 - Why Open Source Is the Only Option for Some Startups 19:57 - Redefining Consumer: When the Plumber Uses GrokBot 22:16 - Town Demo: Personal Agents & Managing Chaos 24:31 - One Dominant Personal Agent or Many Talking to Each Other? 25:26 - Apps vs Model Companies: Who Captures the Value? 29:16 - The New Economics of AI Apps: Margins, Compute & Capital as Moat 30:44 - Who's Actually Building Apps Today? Founder Archetypes 32:20 - Why Giving Founders Too Much Money Isn't Fatal Anymore 34:05 - Go-to-Market for Startups Selling to SMEs Resources: Follow Anish Acharya on X: https://x.com/illscience Follow Jen Kha on X: https://x.com/jkhamehl Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

a16z General Partners Martin Casado and Erik Torenberg are joined by Board Partner Steven Sinofsky to explore what recent breakthroughs in AI and mathematics tell us about where the technology is headed, and whether some of the basic assumptions that have governed computing for decades are starting to break. Martin and Steven debate whether AI's progress in mathematics represents a genuine leap in reasoning or simply a new tool for solving problems at a higher level of abstraction. From the four-color theorem and early computers to graphing calculators and today's models, they trace how new technologies have repeatedly changed which problems humans need to solve themselves, and ask what makes this moment different. The conversation then turns to one of the biggest shifts in AI: problems that were once constrained by engineering talent can increasingly be attacked with capital and compute. They discuss what that means for startups versus incumbents, venture capital, the coming wave of AI applications, and why pouring billions into increasingly capable models may force us to rethink what these systems can ultimately accomplish. Timestamps: 00:00 - Intro 00:56 - Making Sense of AI & Math: The Riemann Hypothesis Moment 12:05 - Will AI Math Ever Map Onto Physical Reality? 19:43 - The Cold War, IBM 1953 & the Cultural Roots of Computing 38:16 - Rethinking Fundamental Assumptions About Software 46:28 - Incumbents vs Startups: Why the Innovator's Dilemma Still Wins 55:05 - The Limits of Current AI Architecture & What Comes Next Resources: Follow Martin Casado on X: https://x.com/martin_casado Follow Steven Sinofsky on X: https://x.com/stevesi Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Elena Burger is joined by a16z’s Angela Strange and Gabriel Vasquez to discuss the rise of the "borderless founder": entrepreneurs who bring the networks and insights of their home markets together with the talent, capital, and speed of Silicon Valley to build global companies. Angela and Gabriel trace how a16z's international investing efforts grew from early work in Latin America into a broader global network, and why AI has accelerated the flow of founders and talent between Silicon Valley and startup ecosystems around the world. They explore the advantages borderless founders can bring, from differentiated talent networks and early customers to strong local brands and communities that help open doors across markets. They also discuss how founder diasporas can function like powerful alumni networks, why spending time in Silicon Valley can help founders recalibrate around speed and ambition, and how the next generation of global companies may increasingly be built across multiple countries from day one. Timestamps: 00:00 - Intro 00:54 - Who Borderless Founders Are & the Origins of a16z's Global Strategy 06:35 - What International Founders Bring to the Bay Area 10:26 - Borderless vs Immigrant vs International Founder 18:04 - The Three Native Advantages: Talent, Brand & Customers 23:08 - Do Borderless Founders Have an Edge in Silicon Valley? 27:08 - How a16z Approaches a New Country or Geography 33:15 - Repeat Founders & Building Long-Term Relationships 36:50 - The Journey from Seed to Growth for International Founders 40:30 - Advice for Founders Thinking of Moving to Silicon Valley 42:25 - 10 Years From Now: The Global Topology of Startups Resources: Follow Angela Strange on X: https://x.com/astrange Follow Gabriel Vasquez on X: https://x.com/GEVS94 Follow Elena Burger on X: https://x.com/VirtualElena https://www.a16z.news/p/rise-of-the-borderless-founder Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

a16z General Partner David George is joined by Grant LaFontaine, co-founder of Whatnot, to unpack how a marketplace that started with collectibles evolved into one of the world's leading live shopping platforms. Grant traces the company's origins from selling Pokémon cards online as a kid to discovering live commerce by watching Whatnot's earliest customers hack together sales on social media. They discuss why Whatnot thinks less like a traditional e-commerce marketplace and more like a digital shopping mall, where discovery, entertainment, community, and commerce all happen at once. Today, users spend roughly 95 minutes a day on the platform, and most aren't even buying something on a given day. They also explore how Whatnot is enabling small businesses to reach global audiences, expanding from collectibles into categories like fashion, food, and golf, and using AI to make sellers more efficient without replacing the human connection at the center of the experience. Timestamps: 00:00 - Intro 01:06 - The Holographic Pokemon Card That Started It All 03:49 - How Grant & Logan Settled on Whatnot (Drunk in a Tokyo Bar) 09:18 - The State of the Market: Facebook Marketplace, China & QVC 12:41 - Entertainment vs Intent: What Whatnot Actually Sells 21:18 - The Supply Side: Turning Sellers Into Real Businesses 29:22 - Expanding Into Europe & the Seafood Distributor Story 32:47 - Operating at Scale: Staying on Top of What Breaks 39:34 - What's Next: Cars, More Countries & Better Businesses Resources: Follow Grant LaFontaine on X: https://x.com/GrantLaFontaine Follow David George on X: https://x.com/DavidGeorge83 Follow Whatnot on X: https://x.com/whatnot Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

a16z General Partner David George is joined by Will Gaybrick, President of Product & Business at Stripe, to discuss how AI is changing the way Stripe builds products, organizes teams, and thinks about the future of internet commerce. Stripe has evolved from a payments company into a multi-product financial infrastructure platform, while a new generation of AI companies is growing and monetizing faster than previous software cohorts. Will explains why Stripe sees AI productivity as an opportunity to build more rather than simply cut costs, including how its internal coding agents now generate thousands of pull requests each week. They discuss creating founder-like agency inside large companies, building smaller and flatter teams, and why Stripe believes dramatically more software will be created as the cost of building continues to fall. They also look ahead to agentic commerce, why checkout pages could disappear, the potential return of micropayments, stablecoins as infrastructure for a global economy, and a future where AI agents increasingly buy software and services from other machines. Timestamps: 00:00 - Intro 01:00 - What Is Stripe Today 08:00 - The AI Cohort Explosion: 50% More Signups & Software Creation Booming 14:25 - Stripe Minions: From 1,200 to 7,000 PRs a Week 19:24 - Build Everything: Going Long vs Going Short on Your Future 28:00 - Agentic Commerce: The Missing Primitives 37:28 - Stablecoins & the Global Money Movement Platform 49:00 - Scaling Taste at Stripe Resources: Follow Will Gaybrick on LinkedIn: https://www.linkedin.com/in/william-gaybrick-5730347/ Follow Will on X: https://x.com/gaybrick Follow David George on X: https://x.com/DavidGeorge83 Follow Stripe on X: https://x.com/stripe Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Ben Horowitz, Travis Kalanick, and Erik Torenberg take the stage at Atoms' launch event for a candid fireside conversation about entrepreneurship, company building, and why Kalanick believes the next industrial revolution will be powered by AI. They revisit pivotal moments from Uber's history, including the decision not to acquire Lyft, lessons from scaling one of the world's fastest-growing companies, and how Kalanick has evolved as a founder. The conversation also explores Atoms' vision for industrial AI, why software is moving into the physical world, what it takes to build enduring company cultures, and why Kalanick believes the biggest opportunities of the next decade lie in transforming industries like food production, mining, and manufacturing. Timestamps: 00:00 - Intro 00:53 - The Bits & Atoms Video: Uber's Vision from 10 Years Ago 09:00 - Atoms Mining, Food Computers & Autonomous Machines 14:44 - The Final Boss: Resistance to Change & the Second Industrial Revolution 22:41 - Why Travis Didn't Buy Lyft 28:13 - How Travis Has Changed as a Founder 36:00 - From $4M Pre to a16z's Biggest Check Ever 46:11 - Dirty Fuel, Revenge Businesses & Falling in Love Again 50:37 - Be Uniconic: Eight Years in Stealth & the New Media Landscape Resources: Follow Travis Kalanick on X: https://x.com/travisk Follow Ben Horowitz on X: https://x.com/bhorowitz Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Elena Burger is joined by a16z's Andy McCall and Joe Schmidt to break down two very different ways AI startups can go to market: the lighthouse and the landgrab. Should founders win a handful of marquee customers whose credibility unlocks an entire industry, or move quickly across a broad market where the ROI already speaks for itself? Drawing on Joe's Lighthouse or Landgrab framework and Andy's experience building sales organizations at Samsara and Meraki, they explore how founders can determine which strategy fits their market, when social proof matters more than math, and why the current rush to adopt AI has created a rare window for startups to sell big software again. They also get tactical on POCs, pricing and ACV, hiring early sales teams, moving from mid-market to enterprise, and why founders shouldn't spend too much time perfecting their GTM strategy before talking to customers. As Andy puts it: spend 1% of your time on strategy and 99% executing. Timestamps: 00:00 - Intro 00:58 - The Lighthouse vs Land Grab Framework 06:57 - Samsara's ELD Mandate: The Perfect Land Grab Moment 13:26 - Lighthouse in Practice: Harvey, Decagon & Further AI 17:00 - ACV Discipline: Clear the Hurdle, Then Just Go 27:14 - Every Big Company Eventually Deploys Both Strategies 33:54 - Why Now Is the Moment to Sell Big Software Again 37:49 - The Biggest Mistake Founders Make Resources: Read Joe Schmidt's "Lighthouse or Landgrab": https://a16z.com/lighthouse-or-landgrab-how-to-pick-your-ai-sales-strategy/ Follow Andy McCall on LinkedIn: https://www.linkedin.com/in/amccall/ Follow Joe Schmidt on X: https://x.com/joeschmidtiv Follow Elena Burger on X: https://x.com/VirtualElena Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Anish Acharya is joined by Garry Tan, President and CEO of Y Combinator, for a conversation about how AI is rewriting the startup playbook, why founders should be more ambitious than ever, and what two decades of Silicon Valley booms, busts, and missed opportunities have taught Garry about building what's next. Garry reflects on turning down an early opportunity to join Palantir, why chasing what's "hot" is often the wrong strategy, and why the best ideas tend to begin with people pursuing strange, earnest obsessions outside the mainstream. They also explore how AI changes the economics of company building, why traditional SaaS may be losing its advantage, and how tiny teams equipped with hundreds of agents can build businesses at a scale that once required entire organizations. The conversation goes deeper into agentic companies, taste and agency, why "a markdown file is an employee," and how AI could remove layers of bureaucracy that have historically limited organizations. Garry and Anish also discuss the future of consumer AI, the coming "harness wars," why AI adoption may take longer than Silicon Valley expects, and what the next generation of founders can build with intelligence that was unimaginable just a few years ago. Timestamps: 00:00 - Intro 00:26 - The 2003 Bleak Moment: Passing on Palantir & Chasing What Was Hot 04:45 - The Culture of Silicon Valley: Finding the Fringe & Your People 10:59 - What YC Gets Right: A Birthright for Tech Outsiders 13:54 - Solo Founders, Vibe Coding & Founders Being 400x Themselves 21:05 - Business Loops: Skillifying Every Task Into a Markdown File 23:03 - Token Maxing: How to Live in 2028 Today 28:09 - Constructive Conflict & Pedro's Meeting-Transcript Agent 33:10 - The Torture of the White-Collar Job & Life Above the API Line 39:08 - The Real White Pill: Everything Is Slower Than You Think 41:33 - What the Next Computer Looks Like: Voice, Memory & the Harness Wars 44:44 - Local Politics & Why San Francisco Turned Resources: Follow Garry Tan on X: https://x.com/garrytan Follow Anish Acharya on X: https://x.com/illscience Follow Y Combinator on X: https://x.com/ycombinator Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Anish Acharya is joined by Garry Tan, President and CEO of Y Combinator, for a conversation about how AI is rewriting the startup playbook, why founders should be more ambitious than ever, and what two decades of Silicon Valley booms, busts, and missed opportunities have taught Garry about building what's next. Garry reflects on turning down an early opportunity to join Palantir, why chasing what's "hot" is often the wrong strategy, and why the best ideas tend to begin with people pursuing strange, earnest obsessions outside the mainstream. They also explore how AI changes the economics of company building, why traditional SaaS may be losing its advantage, and how tiny teams equipped with hundreds of agents can build businesses at a scale that once required entire organizations. The conversation goes deeper into agentic companies, taste and agency, why "a markdown file is an employee," and how AI could remove layers of bureaucracy that have historically limited organizations. Garry and Anish also discuss the future of consumer AI, the coming "harness wars," why AI adoption may take longer than Silicon Valley expects, and what the next generation of founders can build with intelligence that was unimaginable just a few years ago. Timestamps: 00:00 - Intro 00:26 - The 2003 Bleak Moment: Passing on Palantir & Chasing What Was Hot 04:45 - The Culture of Silicon Valley: Finding the Fringe & Your People 10:59 - What YC Gets Right: A Birthright for Tech Outsiders 13:54 - Solo Founders, Vibe Coding & Founders Being 400x Themselves 21:05 - Business Loops: Skillifying Every Task Into a Markdown File 23:03 - Token Maxing: How to Live in 2028 Today 28:09 - Constructive Conflict & Pedro's Meeting-Transcript Agent 33:10 - The Torture of the White-Collar Job & Life Above the API Line 39:08 - The Real White Pill: Everything Is Slower Than You Think 41:33 - What the Next Computer Looks Like: Voice, Memory & the Harness Wars 44:44 - Local Politics & Why San Francisco Turned Resources: Follow Garry Tan on X: https://x.com/garrytan Follow Anish Acharya on X: https://x.com/illscience Follow Y Combinator on X: https://x.com/ycombinator Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Angela Strange and Gabriel Vasquez are joined by Alejandro Maza Ayala, Chief Product & AI Officer at Kavak, to unpack how the Latin American used-car marketplace rebuilt itself around AI agents, with 96% of customer interactions and 95% of transactions now handled by agents. Alejandro explains why Kavak decided that simply giving employees AI tools wasn't enough, and instead redesigned the company's systems, teams, and customer experience around agents. They discuss why Kavak spends as much engineering effort on evals as it does building agents, how its AI sellers outperform its human teams, and an experiment where an AI "CEO" increased profits in one city by 50% in its first month. The conversation also explores what happens to organizational structure when agents do most of the work, why Kavak trains everyone from executives to mechanics to build with AI, and Alejandro's argument that companies looking for incremental AI adoption may be missing the larger opportunity: redesigning the organization itself. Timestamps: 00:00 - Intro 01:03 - Machine Learning Before Transformers 02:23 - What Kavak Does & the Agent-Per-Customer Architecture 04:59 - Three Bets: Redesign the Company, Build Superhuman Agents, Change the Metrics 10:49 - Agents That Sell: 2.1x Better Conversion Than Humans 14:23 - Car Loans Approved in Three Minutes 16:13 - The AI CEO Experiment: 1.5x Profits in Six Weeks 20:13 - The Jedi Academy: Training Mechanics to Ship Agents 28:44 - Destroying Two Years of Work: From Multi-Agent Graphs to One Agent Per Customer 32:52 - Creative Destruction & Ford's Factory: Why Adoption Isn't Enough 34:45 - Advice for Founders: The Most Exciting Time in Human History Resources: Follow Alejandro Maza Ayala on X: https://x.com/alehandromz Follow Angela Strange on X: https://x.com/astrange Follow Gabriel Vasquez on X: https://x.com/GEVS94 Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Joel De La Garza is joined by Dylan Ayrey, co-founder and CEO of Truffle Security, and Feross Aboukhadijeh, founder and CEO of Socket, to discuss one of the biggest shifts happening in cybersecurity: AI models are no longer just finding vulnerabilities—they're exploiting them. As frontier models become increasingly capable of hacking, software security, supply chain attacks, and cyber defense are entering a fundamentally new era. The conversation explores AI-powered hacking, software supply chain attacks, leaked credentials, zero-day vulnerabilities, package manager security, and why the path of least resistance for increasingly autonomous AI systems may also be the most dangerous. They also discuss what enterprises, developers, and the open-source ecosystem need to do to adapt as the gap between vulnerability discovery and exploitation continues to shrink. Timestamps: 00:00 - Intro 00:49 - Models Are Escaping Their Cages 01:28 - Opus 4.6 Committed a Felony to Complete a Task 05:20 - The Apache Foundation Key & the Path of Least Tokens 09:19 - How the Labs Trained Models to Hack: Reward Functions & CTFs 11:45 - A Quarter Million Live Keys in Hugging Face Training Sets 13:02 - The npm Worm: Hundreds of Repos Breached During Black Hat 16:55 - npm's Nuclear Option: Mandatory 2FA for Every Publish 21:06 - 2026 Is the Year of the Software Supply Chain Resources: Follow Dylan Ayrey on X: https://x.com/InsecureNature Follow Feross Aboukhadijeh on X: https://x.com/Feross Follow Joel De La Garza on LinkedIn: https://www.linkedin.com/in/3448827723723234/ Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Elena Burger and Matt Bornstein are joined by Simon Mo, co-founder and CEO of Inferact, the open-source inference engine powering many of today's most advanced AI applications. Together, they explore how open-source AI evolved from a research project into critical infrastructure, why inference has become one of the most important layers of the AI stack, and what it takes to bring frontier intelligence to developers around the world. The conversation covers vLLM's origins, the rise of open-weight models, why companies increasingly want control over their AI infrastructure, and how open-source inference enables the next generation of AI applications. They also discuss model licensing, the economics of open-weight AI, Kimi K3, distillation, AI infrastructure, and why Simon believes the gap between open and closed models is rapidly disappearing. Timestamps: 00:00 - Intro 01:00 - What Is vLLM & Why Serving LLMs Is a Fundamentally Different Problem 05:10 - When Open Source Became Critical Infrastructure 08:26 - Where vLLM Sits in the Stack 13:35 - The Open Weights Letter & Why Open AI Development Must Be Protected 16:42 - K3 Economics: Bridging the Gap Between Open & Proprietary 19:57 - Licensing Evolution: From Apache 2 to Commercial Terms 28:51 - Why Open Source Inference Is the Only Way to Scale Agents 32:21 - The Hugging Face Incident & Why Guardrails Break Down 36:57 - Building a Company from an Open Source Project 43:32 - The Distillation Debate: Is It Critical or Incidental? Resources: Follow Simon Mo on X: https://x.com/simon_mo_ Follow Matt Bornstein on X: https://x.com/BornsteinMatt Follow Elena Burger on X: https://x.com/VirtualElena Follow Inferact: https://x.com/inferact Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Ulysses is building autonomous underwater robots to become the technology platform for the world's oceans. From restoring underwater ecosystems to inspecting critical infrastructure and supporting maritime security, the company is rethinking how humans interact with the ocean. As demand grows for subsea cables, offshore energy, critical minerals, and defense capabilities, Ulysses is building autonomous fleets designed to operate continuously beneath the waves. GUEST SOCIALS Learn more about Ulysses: https://www.theoceancompany.com/ Follow Ulysses: https://x.com/UlyssesInc Follow Will O'Brien on X: https://x.com/Willob Follow Akhil Voorakkara on X: https://x.com/Mr_Voorakkara Follow Jamie Wedderburn on X: https://x.com/Jamedderburn Footage courtesy of NewsNation

Mariana is rebuilding one of the world's most important industries: critical minerals. Led by Turner Caldwell, the company is taking a software-first approach to modern mining, combining automation, AI, and engineering to rethink how mines are built and operated. Every battery, robot, AI data center, and electric vehicle depends on metals pulled from the ground, and Mariana believes rebuilding that industrial capability is essential for long-term economic resilience, technological leadership, and national security. GUEST SOCIALS Follow Mariana on X: https://x.com/MarianaMinerals Follow Turner Caldwell on X: https://x.com/tbc415

Radiant is building portable nuclear microreactors designed to deliver reliable, carbon-free power wherever it's needed. By reimagining nuclear as a factory-built product instead of a decade-long construction project, the team is working to make clean energy easier to deploy for remote communities, military operations, AI infrastructure, and critical industries. It's a fundamentally different vision for how nuclear power can help rebuild America's energy future. GUEST SOCIALS Follow Radiant: https://x.com/radiantnuclear Follow Tori Shivanandan on X: https://x.com/torishiv Follow Doug Bernauer on X: https://x.com/dougbernauer

Sarah Wang and Kimberly Tan are joined by Jesse Zhang and Ashwin Sreenivas, co-founders of Decagon, to discuss the evolution of enterprise AI agents, why the company increasingly relies on open-source models, and how it is helping some of the world’s largest companies deploy AI in production. Decagon has become one of the fastest-growing AI companies by building agents that automate customer support, sales, and operational workflows. Jesse, Decagon’s CEO, and Ashwin, its president, explain how the company is building enterprise AI at scale. They unpack why Decagon moved most of its inference to open-source models, how latency, evaluation, and fine-tuning shape production AI systems, and why enterprise AI requires far more than simply plugging into frontier models. The conversation also explores forward-deployed engineering, enterprise sales, AI’s impact on jobs, and why application companies will continue to thrive alongside the foundation model labs. Timestamps: 00:00 - Intro 01:07 - Decagon's Journey from Frontier APIs to 90% Open-Source 05:00 - The False Trade-off: Why Fine-Tuned Small Models Win 09:26 - Decagon Labs as a Model Factory 15:07 - Are Frontier AI Labs the Last Startups? 21:21 - The Forward Deployed Trap: Product vs Consulting Truck 28:36 - Duet Autopilot: The Agent That Builds the Agent 37:02 - Winning Enterprise: Glass Box vs Black Box (and Beating Sierra) 47:55 - From Customer Support to AI Concierge 01:14:45 - Will AI Kill Jobs? Jevons Paradox in Customer Support Resources: Follow Jesse Zhang on X: https://x.com/thejessezhang Follow Ashwin Sreenivas on X: https://x.com/AshwinSreenivas Follow Sarah Wang on X: https://x.com/sarahdingwang Follow Kimberly Tan on X: https://x.com/kimberlywtan Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Alex Rampell and Olivia Moore speak with Lassie cofounders Steijn Pelle and Frédéric Renken about bringing AI to one of the most overlooked parts of the economy: small businesses. Inspired by time spent working inside dental practices, Pelle and Renken set out to automate the administrative work that keeps healthcare providers away from patients. They discuss how AI agents are changing billing, insurance claims, patient payments, and other operational workflows, allowing practices to spend less time on paperwork and more time delivering care. The conversation explores AI agents, software that performs work rather than simply storing information, onboarding AI into real-world businesses, and why healthcare administration offers one of the biggest opportunities for automation. Along the way, they discuss product design, go-to-market strategy, and what it takes to build AI systems that operate reliably in complex business environments. Timestamps: 00:00 - Intro 01:12 - Story Behind Lassie 03:46 - Embedding in the Customer's Office Before Building a Product 05:39 - How the Product Build Has Changed with Better Models 07:23 - Software Never Did the Work but AI Finally Does 17:24 - 98% Automation: How Lassie Got Agents to Actually Run a Practice 22:08 - Startup vs Incumbent in the AI Era 33:35 - The Master Plan: From Dentists to Every Small Business 39:27 - What It Takes to Hire & Build When You're Selling to Main Street 55:59 - How Do You Reach Hundreds of Thousands of Small Businesses? Resources: Follow Steijn Pelle on X: https://x.com/steijnpelle Follow Frédéric Renken on X: https://x.com/fredericrenken Follow Alex Rampell on X: https://x.com/arampell Follow Olivia Moore on X: https://x.com/omooretweets Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.