20VC:Thrive 与 OpenAI 达成合作|Eventbrite 以 5 亿美元被收购|Databricks 以 50 亿美元融资、1340 亿美元估值:贵还是不贵?|为什么 SaaS 像日本,以及软件的 TAM 陷阱
- Databricks 以 1340 亿美元估值、32倍销售额交易,可能只是“价格合理”,而非便宜。 参照案例是 Snowflake:营收同为约 40亿美元、增速 28%、估值 800亿美元、销售额倍数 20倍;Databricks 增速则为 55%,且仍在加速。Rory O'Driscoll 提出的关键事实是:大规模再加速会击穿所有估值模型——“按定义,如果它持续再加速……它就是无限有价值”,而这正是今年 Anthropic 被阶跃式重估的原因。只有约 1/3 的公司能再加速一年,能持续两年的只有 1/10。
- Jason Lemkin 的直白推论是:“种子轮是给傻瓜玩的。” 按风险和时间调整后,1340 亿美元的 Databricks,或 Kleiner Perkins 投资时估值 1800亿美元的 Anthropic,可能胜过投后估值 6000万美元、需要承担 7-10 年期限风险的 Pre-C SAFE。公开市场上真正增速超过 30%的公司只有 1 家——增速 50%、盈利能力极强、销售额 80倍估值的 Palantir,因此根本没有公开数据集可用来给超高速增长定价。
- 大多数上市 SaaS 公司都陷入了“TAM 陷阱”:平均增速约 16%,为历史最低。 Rory 对这个谜题的解释是:CEO 们并不愚蠢;风险资本投出了太多公司,市场因此饱和——这就是他 2019 年那篇文章所说的“SaaS 饥饿游戏”。Zoom 是典型:所有需要账号的人都已经有了,“然后就结束了”。由此推导出的投资规则是:“只有 TAM 足够大时,溢价支付才有效。在有限 TAM 里,出价必须更紧。”
- 按席位收费正面临生存级挤压:所有公司的每名员工 ARR 都在上升,因此头部企业终究会用光席位。 HubSpot 的效率是 2021 年的 2.8倍,Salesforce 是 2倍,Microsoft 则“永久越过了员工峰值”。Jason 的比喻是:“SaaS 已经变得像日本”——这是一个很棒的经济体,但如果每个人只有 0.9 个孩子,席位总归有限。Rory 指出,效率提升或许解释了为什么 SaaS 倍数并未随增速一样大幅下跌。
- 安全正在成为 incumbent 的武器:Gainsight 被 Salesforce 锁了两周且没有解决时间表,Drift 在 700 人数据被下载、赎金要求覆盖 700 个组织(包括 Cloudflare)后“彻底死掉”,OpenAI 则永久移除了 Mixpanel。 Jason 认为,这可能是“企业的复仇”;Harry 则给出更犬儒的解读:先把安全当作切断第三方的理由,再销售自己的 agent 产品。
- Google 在不到 10 个月内复刻了 Lovable/Replit(尽管上线时没有数据库和 OAuth),Datadog 也在 24 个月内做出了 PagerDuty 竞品,而 PagerDuty 创立于 2008 年——“现在你甚至连一年都没有了”。 但 OpenAI 的 code red 被解读为“模型将无所不能”叙事的顶峰:“赢下 ChatGPT 战争,你就值 2 万亿美元。别再折腾那些小型垂直市场。”
- 下一轮 AI 浪潮,两人都会愿意赴约:让 AI 直接运营企业,而不是向企业销售软件。 Rory 的 Range 交易,是把财富管理、税务、信托沿着财富阶梯自动化。Jason 的亲身经历是,3 个信托耗时 11 个月,最后那位备受推崇的律师只是耸耸肩说:“我的大多数客户甚至都做不完。”如果 AI 能消除约 180万美元美国人平均退休金规模背后的摩擦,“你可以做出一家 200亿、400亿、500亿美元的公司”;而 Wealthfront 的命运正是 TAM 陷阱的警示。
- 快问快答的分歧值得保留:Rory 选 Lovable 胜过 Superbase(如果 vibe coding 是一个品类,前端就会拿走利润——“小赌一把还是押上全部”);Jason 选 Superbase,因为“难题令人安心”,数据库很难被替换——“这是增长的一年,但除此之外什么都没有……明年我想要一点防御性。”
1. Thrive × OpenAI:幂律效应加倍,但新闻已经过时
- Rory 拉远视角看,这次合作“并不重要”,因为 24 小时后它就不再是 OpenAI 的主线新闻。真正的主线是 code red——聚焦核心业务:推迟广告、推迟医疗 agent,“不受干扰”。“Google 3 年前对他们发布了 code red,现在轮到他们反过来对 Google 发布 code red。”
- Jason 对交易本身的判断是,OpenAI 投资 Thrive Holdings,“真正重要的 VC 交易就那么几笔……这是幂律效应加倍。它不仅是幂律效应,还取决于你如何安排自己的一周。”把基金变成控股公司,投入 10亿或 20亿美元,再进一步押注你有史以来最重要的第一号公司。
- Rory 认为赢家是 Thrive:他们在约 700亿美元那轮融资中重仓 OpenAI,在“两年前那场大惨剧”中站在 Sam 一边,如今获得巨大的光环效应。“风险投资的全部诀窍,是我们试图假装自己很重要,但内心知道,真正重要的是最优秀的公司。”至于 OpenAI 能得到什么,“就不那么清楚了”——他知道谁在公告发布时欣喜若狂,也知道谁的反应是“哦,随便”。
2. Databricks 1340 亿美元估值:增长溢价问题的现场算例
- 这组对比异常干净:Snowflake 上市公司营收约 40亿美元、增速 28%、估值 800亿美元(20倍);Databricks 传闻融资 50亿美元、估值 1340亿美元,对应 2025 年 41亿美元营收和 55% 增长。Rory 的判断是:“不便宜,但可能价格合理”——关键在于,为额外 25-30 个百分点的增速支付多少倍数;“如果这段额外增长能持续一段时间,额外增长的价值大得惊人——这是技术术语。”
- 公开市场可比公司帮不上忙:“真正增速超过 30%的上市公司只有 1 家”,就是 Palantir——增速 50%、盈利能力极强、销售额 80倍。Jason 认为,如果 Databricks 今天上市,它会是公开市场第二好的公司,当前价格“看起来差不多”。
- 真正击穿模型的是这个规模上的温和再加速——“我们以前根本没见过”。Rory 说,所有理性模型都假设增速逐步放缓;“按定义,如果它持续再加速……它就是无限有价值,因为数学就是这么算的。”基础模型难以估值,也是同一套逻辑:今年 Anthropic 在大规模业务上重新加速时,“所有人都意识到模型错了”,估值随之发生阶跃式重估。基准概率是:1/3 的公司能再加速 1 年,1/10 能再加速 2 年,而且很少有公司能从 50% 的增速基础上做到。
- Jason 的结论得到 Harry 附和:“种子轮是给傻瓜玩的。”按风险和时间调整后,Databricks,或 Kleiner Perkins 以 1800亿美元估值投进 Anthropic 的交易,都可能胜过“投后估值 60亿美元的 Pre-C SAFE”,因为后者要承担 7-10 年期限风险,确定性却低得多。
3. Snowflake 对 Databricks:不是共存,而是寡头厮杀——agent 正在改变数据游戏
- 对于 Databricks CRO Ron Gabrisko 所说的技术领先 5 年,Rory 认为 Ron 在 AI 原生数据工作上说得没错,但“两家公司不可能和平共存。他们大概互相讨厌——事实上,我们知道他们互相讨厌,因为他们会故意把销售活动安排在同一时间。”未来 10 年,两家公司会像 SAP 和 Oracle 当年长达 20 年的竞争一样“狠狠干一场”:利润率会受损,但谁也不会倒下,因为“关系型数据库的核心价值不会消失”。
- Jason 真正开放的问题是:Cursor、Lovable、Replit 这些 vibe 平台,现在都能直接访问 Snowflake 数据,而几周前还做不到。“当我可以用简单易用的 agent 访问所有数据,随心构建报告、分析和工作流时,会发生什么?我认为我们才走了这段旅程的 1%。”他不会押注反对任何一家管理海量结构化和非结构化数据的公司。
4. Agent 时代,CRM 会不会沦为哑数据库?意图不等于能力
- Jason 提到 Benioff 把 2000 人投入 Agentforce,认为这就是“未来本身”;Harry 的反驳很精准:“这说明了他的意图,但不能说明他的能力。”Jason 承认,Salesforce 可能还有约 2 年时间解锁这项能力,而对 Salesforce 来说,2 年并不长——按照传统节奏,这只是一个重大版本发布周期。
- Rory 判断,单应用 agent 会像 Microsoft 那样被 Salesforce 打包进产品;但如果企业希望 agent 横跨 5-6 个数据源,就会“把所有东西塞进 Snowflake,直接在上面运行 agent”,投入 500万美元和一批 Snowflake 或 Databricks,定制构建。Agentforce 可以拿到相当一部分市场,但高端市场会让系统集成商在未来 10 年赚得盆满钵满。
5. 安全成为 incumbent 的护城河——“企业的复仇”
- Jason 列出的案例包括:Gainsight 被 Salesforce 锁定 2 周,“没有已知解决时间”;Drift 遭遇入侵,700 人的数据被下载,黑客按每个实例索要数百万美元,5 个月前被逐出平台,如今“彻底死掉”;OpenAI 本周永久移除了 Mixpanel。作为平台所有者,他的升级逻辑是:第一次入侵,你会把锅甩给 PE 持有的供应商;“第二次,我可能开始锁死平台;第三次,我可能会说,‘我干脆自己拥有所有 agent。’”
- 他的担忧可以泛化:“当 agent 到处运行、处理我们的数据时……我总体上担心我们低估了安全和数据驻留问题。”有多少董事会会议是以 AI 时代的安全问题开场?“对我来说,接近 0 次。”而普通初创公司的 SecOps 团队规模,与如今开出的支票规模完全不匹配。
- Harry 把它进一步推向犬儒版本:“我用安全作为借口把你们全部切断,但你看,我这里正好有自己的 agent 产品,现在客户先生可以放心购买。”Jason 基本认同:“我认为这是最好的借口。”今年很少有 incumbent 实现实质增长,“这可能是企业复仇的一部分”。讽刺之处在于,两起入侵都来自成熟、由 PE 管理的 SaaS 公司,但真正会承受限制性政策后果的,却是新的 AI 公司。
6. Eventbrite 5 亿美元收购与 PagerDuty 问题:聪明资金认为 2 倍营收便宜得离谱
- Eventbrite 以约 5亿美元成交——对应 1.5倍营收、50% 溢价。PagerDuty 市值约 10亿美元,对应 5亿美元 ARR、增速 4%。Rory 解释了上市且估值便宜时的交易机制:有人提出 50% 溢价,“律师会来给你讲董事的受托责任”;除非你能证明公司会超过这份溢价,否则“你几乎只能接受”。
- 看多逻辑是,把 Semrush 也算进来——它两周前被 Adobe 收购——“聪明、老练的资金”正在表达一个判断:2 倍营收便宜得离谱,“我买了”。激进的 PE 公司可以收购 PagerDuty,再接入一家热门 AI 初创公司,把增速拉回 20%,然后“看起来像个英雄”。Jason 的检验问题是:“我们还没看到 pagerduty.com 和 pagerduty.ai 神奇地合并成一个赢家,对吧?”
- Rory 最尖锐的自白是:他们 10 年前看过 PagerDuty,“当时我们应该让他多付一点,因为他说得对”;IPO 后复盘发现,他们当年的模型对营收的预测“误差在 3% 以内”。“发生的一切,只是市场当时愿意为这项资产支付更多,而现在不愿意了。”真正令人恼火的是:“地球上每个运营团队都在用 PagerDuty。拜托,这里该加什么功能不是一目了然吗?赶紧做出来。”
7. TAM 陷阱:不是愚蠢,而是饱和
- Jason 把自我反省直接变成了论点:“我认为大多数上市 SaaS 公司都陷入了 TAM 陷阱。”上市 SaaS 平均增速约 16%——“从来没有人增长得这么慢。”“Aaron Levie 和 Drew Houston 们怎么就没看出 TAM 陷阱?那我们其他人还有什么希望?”
- Rory 的答案值得完整保留:可能根本没有答案。问题不在于 CEO 愚蠢,而在于风险资本投出了太多公司,市场因此饱和;等到你需要扩张时,另一个风险资本支持的 SaaS 公司已经占据了相邻市场。他在 2019 年把这写成了“SaaS 饥饿游戏”。Zoom 是典型案例:“所有拥有 Zoom 账号的人也都有 Team 账号,可怜的人们,然后就结束了……你必须做个新东西”;而那个显而易见的新方向——联络中心——他们没能做出来。
- 随之而来的组合管理规则是:“只有 TAM 足够大时,溢价支付才有效。在有限 TAM 里,出价必须更紧。”第二款产品也要比直觉认为的更早启动;复利效果最好的那家被投公司,“不断增加新产品,头 1-2 年每个产品只有几百万美元收入”,如今已经做到数亿美元。
- AI 的开放问题是:它能否切入人工预算,并支持数量级更高的定价——Gamma 每月 100美元,而 Canva 是 8美元;Cursor 是 500美元,而 Jira 是 3美元?Rory 提醒,劳动价值定价一旦出现“同一款 AI 软件有 3 家供应商,而且都愿意只收 100美元”,就会迅速被侵蚀。这还没有发生——“这是个非常好的问题。”
8. 席位、日本与效率棘轮
- 对于 Workday 所说的席位缩减是生存问题,Jason 不断回到 Jeff Lawson 关于摆脱席位模式的警告,以及自己的数据分析:HubSpot 的营收效率是 2021 年的 2.8倍,Salesforce 是 2倍,Microsoft 则“永久越过了员工峰值”。“如果你是领导者,终究会用光席位。”因此,本期节目的核心金句是:“SaaS 已经变得像日本……这是一个很棒的经济体,但如果每个人只有 0.9 个孩子,席位总归有限。”
- 自 2023 年初以来,他的运营门槛已经反转:当时是“我要你增加 200% 的员工,才能实现 100% 的增长”;现在则是“我想看到你明年在员工只增长 50% 的情况下实现 100% 增长”。一个需要 50 人的 CMO,或一个还需要增加 80 人的产品负责人——“我认为该分道扬镳了。”2021 年的那套 DNA,“可能仍在绝大多数高管脑中反复回响”。
- Rory 的总结是:软件按照交付的价值定价;席位只是可测量的代理指标,AWS 开始的用量模式更能追踪价值。如果 AI 完成了工作,按席位收费就变得无关紧要——Workday 可能最终采用每名被服务员工收取 X 美元,再加每名 HR 用户收取 Y 美元,但 HR 用户数量会减少。问题在于:“数座位上的屁股很容易……每次登录就是一个屁股。但当你试图衡量交付的价值时,就困难得多。”他还指出,效率提升或许解释了为什么 SaaS 倍数没有随增速一样压缩:低增长公司至少是“效率高得惊人”的公司。
9. 增长对效率——以及为什么赢家都不需要人
- Jason 被问到创始人是否必须同时交出增长和效率时说:“在我投资过的增长最快的公司里,没有人真正关心利润底线。”按照可能来自 ICONIQ 的数据,增长最快的 AI 公司即便推理成本很高,烧钱倍数仍然最低,因为营收增长跑赢了算力成本。蛮力扩张的路径已经关闭:“没有强劲的自然需求和大量 AI,你不可能在 10 个月内从 1 做到 100。”也许 Larry Ellison 或 Marc Benioff 能够足够快地招到人,其他人做不到。
- Rory 给出 3 类公司的地图:苦苦经营自由现金流的上市公司;和 Nvidia 一起烧钱的模型实验室——“没人会对 OpenAI 说‘要讲效率’,或者即便有人说了,他显然也没听”;以及 Gamma 这类应用层公司,它们的“增长牵引力领先于招聘能力,根本没有办法把钱花出去”。他不舒服的发现是:3 类公司都不需要人。“如果你是人,这可不是什么好消息。”他仍然是乐观派——“我认为失业这件事纯属胡扯”——但承认短期内劳动与资本的平衡更偏向资本。
10. Google 10 个月复刻 Lovable——但模型供应商的野心可能已经见顶
- Jason 亲自试用了 Google 的新产品:一个 Replit/Lovable 克隆版,上线时没有数据库和 OAuth——产品本身并不惊艳,大公司“优先级总是有限”。但真正重要的是速度:Google 不到 10 个月就完成发布;Datadog 在 24 个月内推出 PagerDuty 竞品,而 PagerDuty 创立于 2008 年。“现在你甚至连一年都没有了。”如果你能在一年内从 0 做到 2亿美元,就理应招来竞争,这不是一顿免费的午餐。
- Rory 的反向解读是,OpenAI 的 code red “近乎承认”核心使命需要集中 1 年时间——“你可能会听到的声音,是消费硬件产品稍微往后滑了。”董事会的逻辑是:“赢下 ChatGPT 战争,你就值 2 万亿美元。别再折腾那些可能只值几亿美元的小型垂直市场。”他的判断是:“模型将无所不能”可能已经见顶——编程可以,但不是每个垂直领域都可以。
11. 下一幕:让 AI 运营财富管理,而不是向财富管理销售软件
- Rory 对 Range 的判断是:不要向财富管理机构销售软件,而是直接自动化整个业务,并沿着财富阶梯向下渗透:税务(“英国现在已经超过 50%,还在继续上升”)、遗产、申报——这些是“知道怎么做但很复杂”的工作,目前由人工昂贵地完成,却可以用 AI 极低成本地完成。普遍规律是:“每当你看到只有非常有钱的人才拥有的产品,如果能找到办法把它交到我们其他人手里,我们也都会想要。”目标客户是医生、牙医、创业者——“比什么都不做复杂,但又不是能花 2万美元请律师的那种人。”
- Jason 的亲身经历强化了这个论点:3 个信托花了 11 个月,找的是一位备受硅谷推崇的信托律师;对方安慰他说:“好消息是,我的大多数客户甚至都做不完。”Morgan Stanley 真正的产品只有股票质押贷款——“他们会告诉你可以帮忙做信托,但其实不会。”如果 AI 能消除围绕美国人平均约 180万美元退休金的摩擦,“我认为你可以做出一家 200亿、400亿、500亿美元的公司。至少我会愿意去见一面。”
- 但他也用自己的 TAM 陷阱测试来审视这家公司:Range 会收取 8000-1万美元,而不是 3万-5万美元的“蠢货”替代方案——这不是 10 倍定价;理论上人人都能用、因此应该值 10万亿美元的 Wealthfront,在运营 17 年后仍然有真实的 TAM 上限。他给这个品类的建议是:“在证明之前,也许应该保持资本效率……如果你只证明了一半,就会完蛋。”Rory 认为这对所有创始人都非常准确:资本纪律应当与市场被认为有多火热成正比。
- Rory 为慢速复利型公司辩护:Wealthfront 收取 10bps,因此需要管理 1% 费率管理人的 10 倍资产,按定义就需要 10 年;但“未来 10 年或 15 年,那一代人会变富……它会成为一台复利机器”,就像 70 年代的 Schwab。他向 Harry 发起挑战:Schwab 大约在 1982-1983 年上市,如今市值 600亿-800亿美元——“说出 5 家在 1983 年上市、如今仍是科技公司的企业。”
12. Harry 的猛烈反驳:风险投资是一场争夺相关性的游戏
- Harry 直白描述新时代风险投资:LP 会被“令人难以置信的后续投资人、快速上调的融资轮和漂亮数字”吸引——“我宁愿玩这场游戏,也不想玩‘它终将发生’的游戏。”动量数据也支持他:Rory 把自己的数据向上修正——第一季度首轮独角兽中,已有 40% 完成后续融资。他最尖锐的说法是:Rory 是不是因为在 B 轮阶段“打不过” Andreessen、Founders Fund 和 Sequoia,才不得不选择那些不光鲜但能复利的公司?
- Rory 的答案是两者都做,但筛选标准只有一个:大结果的确定性,因为“工程学有一条规则:你的准确度只取决于最不准确的变量”。其他一切——估值、时间——都可以调整。他认可 Peter Thiel 的版本:“真正重要的,是你能不能在这里做出一家大公司……一旦我按这个标准筛选,就不能再在阶段、行业上设任何狗屁规则。我只想要大的。”
- 他保留了 20 年前一位 LP 说过的创伤性金句:“不存在蓝领风险投资。”你不是按价值做选择,而是在按大结果的确定性做选择。
13. 快问快答:Lovable 与 Superbase 让全桌在风险哲学上分裂
- Rory 选择 Lovable(60亿美元)胜过 Superbase(50亿美元):vibe coding 要么是一个品类,要么不是——“如果它不是一个品类,两家公司都会完蛋”;如果它是,前端就会拿走利润(Lovable 收 20美元,再付 2美元给 Superbase)。“既然如此,还不如小赌一把,而不是押上全部。”
- Jason 选择 Superbase,“因为稳定性……难题令人安心。”没错,它是“Postgres 的一个分支……这件事可以被重新做一遍——Neon 做到了,Databricks 还花了 10亿美元买下它”;但数据库极难被替换,而在经历了“增长的一年,但除此之外什么都没有”之后,他对明年的态度是:“我想要一点防御性。我真的只想要一点难得要命的问题。”
Rory O'Driscoll
Google did a code red 3 years ago on them, and now they're doing a code red back. How much extra in multiple do you pay for how much extra in growth?
Jason Lemkin
The majority of the private SaaS companies, I think, are in a TAM trap.
Rory O'Driscoll
Overpayment only works when the TAM is huge.
Jason Lemkin
Mm.
Rory O'Driscoll
In finite TAMs, you gotta bid more tightly.
Jason Lemkin
Has SaaS become like Japan?
It's a great economy, but if everyone only has 0.9 kids, there's only so many seats to go around. I think in the fastest-growing companies that I've invested in, no one gives a rat's ass about the bottom line.
This is amazing. I've done 20VC for 10 or 11 years, and I love it. I love it so much. But then we started doing these shows with Jason and Rory, and not only did I realize this is my passion, but I realized that no one actually ever liked me in the first place.
They just freaking love Rory, and they learn SaaS from Jason. So this is going to be a live pod, which makes me inherently nervous and excited at the same time.
We're going to start with Thrive partnering with OpenAI. How did we think about this partnership? Over to you guys.
1. OpenAI Goes Code Red
Rory O'Driscoll
The quick answer would be, we'll definitely talk about it, but it doesn't matter. I think the interesting thing, Harry, is that that's not the OpenAI story anymore. That's the OpenAI story from a day ago, and the OpenAI story today is almost the exact opposite.
It's the code red: focus on the core. It's almost a statement that says, “All the other things we've been doing, we ain't doing them now. We're just going to be fixing our core product.” They're even pushing ads and agents for healthcare back, really going all in on no distractions.
So while I think this is an interesting announcement, and we'll definitely talk about it in a second, the zoom-out comment is that 24 hours later, that's not the zeitgeist at OpenAI anymore. The zeitgeist is: Google did a code red 3 years ago on them, and now they're doing a code red back.
Jason Lemkin
The one thing that's kind of interesting about it is that it's a reminder—and this can be a little soul-crushing as a founder—that there are only a couple of deals that matter to VCs. You'll see a VC stay on a board for 20 years, and you'll see them always hanging out with this one CEO, and Thrive has a lot of winners, right? But this is a big winner.
So anything you can do to go deeper with those founders on your 1 or 2 winners, it's power law on steroids. It's power law with what you do with your week. It's power law with your deal flow. So I don't totally get who's giving each other how much equity, but I think it's about going as deep with your winner as humanly possible.
Okay, this is OpenAI investing in Thrive Holdings.
Rory O'Driscoll
Yeah.
Yeah.
Jason Lemkin
But it's the same people. It's still going deep on your winners. It's, “I'm turning my VC fund into a holding company. I'm putting $1 billion or $2 billion over there, and then I'm going even deeper with the No. 1 company that I've ever invested in.”
Rory O'Driscoll
If we're going to go on to the specifics of it, first of all, I think it's a great deal for Thrive because Jason's right. The whole trick in venture is we try and pretend we matter, but in our hearts we know our best companies matter, and the best marketing you can do is get as close as possible to your biggest deals.
And Thrive, to give them huge credit, put a bunch of money into OpenAI in that—I think it was a $70 billion round—and were there for Sam in the great fiasco of 2 years ago. So my guess is he's pretty darn loyal.
This is a chance for them to get a halo effect as they go on this initiative. We'll talk about the specifics of the initiative in a second, but it's a huge halo effect. As your last speaker said, you go in with the OpenAI moniker and you get some real attention. So it's awesome for Thrive.
I agree, the advantage to OpenAI is much less clear. I'm not sure they're putting in money. In one of the press releases, they said they're going to get a lot of specific data from some of these verticals that Thrive is pushing into, but my guess is I know who was ecstatic this morning when that was announced and who was like, “Yeah, whatever.” That's pretty clear.
2. Databricks Tests Venture Math
Okay. We said about the importance of our winners and, Rory, you humbly said that it's all about our star founders. Databricks is one of the stars of the last generation or this generation. They're rumored to be raising $5 billion at a $134 billion valuation. It's 32x 2025 sales, which are $4.1 billion. They're at 55% year-on-year growth.
Is this actually cheap? How did we analyze this one?
Rory O'Driscoll
Well, I wouldn't call it cheap, but possibly reasonably priced. It's actually very convenient right now because the direct competitor, Snowflake, is public at roughly the same revenue—around $4 billion—growing at 28%, valued at $80 billion, so 20 times revenue.
And so it poses very nicely the big-picture venture question: How much extra in multiple do you pay for how much extra in growth? Right here is the worked example. It's like you can buy a profitable company doing $4 billion with 28% growth at 20 times, or you can buy an unprofitable but faster-accelerating company at 32 or 33 times.
And is that extra 25% of growth? Because Databricks is growing, allegedly, at 55%, not 25%. So you're getting 25% to 30% of extra growth. And the question is, is that worth it?
First of all, do you agree that's fundamentally the question you're asking? How much extra revenue multiple do you pay for how much extra growth? Would you agree, Harry?
I agree with that.
Rory O'Driscoll
And I think very quickly, because if you do the math, there are a bunch of ways you can do it. What you say to yourself is, if that extra growth lasts for any length of time, extra growth's worth a shit ton, to use a technical term.
That compounding keeps going, so if that growth persists for 3 or 4 years, then maybe that extra premium is worth every dollar and then some.
Then you start saying to yourself, how much extra for how much extra growth? You look at the public markets to figure it out.
Jason Lemkin
Mm.
Rory O'Driscoll
And then you discover something really funny, and Jason's talked about this. There is literally only 1 public company growing more than 30%, and that's Palantir. For the record, that's growing at 50%, wildly profitable, and valued at 80 times sales. So you just don't have a data set publicly to assess this.
Jason Lemkin
I think the simple answer is it would be the second-best public company if it were public today. It seems about right. The crazy thing is it continues to modestly accelerate. It's just something that we haven't seen before, and it's something we all have to adjust to—that you can continue to accelerate at this scale. It justifies all the craziness we see in venture, at least for now, because the headroom is still there.
Rory O'Driscoll
I totally agree, Jason. I'd forgotten that. The re-acceleration changes everything, because I was going to say, when you develop that model of how much extra is 55 worth versus 25, you make some assumption of gradual deceleration and gradual convergence, because that's the only rational thing to do. Then you can come up with a number. It's a high-revenue multiple, but it's still a number.
When stuff starts re-accelerating at scale, it's almost hard to figure out the model. By definition, if it continues to re-accelerate, just for the record, it's infinitely valuable, because that's just what the math says. So it's probably not going to be infinitely valuable, but it just points out the power of re-acceleration at scale. If you could even stipulate going from 50 to 55 to 60 at scale, oh my God, there's huge value.
It's actually the same dynamic that's why it's hard to value the big foundation models. When Anthropic went through that bout of re-acceleration this year at scale, everyone realized the model was wrong, and they just had to raise their estimates and raise the value. That's why you saw that step-function increase in valuation.
Look, you said re-acceleration is really hard. We see it in maybe 1 in 3 companies for a single year. Only 1 in 10 does it for 2 years. I've very rarely seen re-acceleration when you're already at 50%, for God's sake. No, you're exactly right, Jason. That's the killer fact here that makes it hard.
So you end up saying to yourself some version of, how big is the TAM? Because in the end, the only thing that stops something that's re-accelerating at scale is when you hit the wall of, well, you've sold to everyone. It's the Zoom effect.
Jason Lemkin
Yeah. It just also reminds you that seed's for suckers.
When you actually look at the certainty that you have that Databricks has a 3 to 5X from here, you're absolutely right. When you think about the opportunity cost of, I can put my money here or here, risk-adjusted and time-adjusted, you could make a very coherent case that it is a better deal to put your money into a Databricks, or like Kleiner Perkins did with Anthropic at $180 billion—
Jason Lemkin
Yeah.
—than it is to put your money into a much less certain Series B with a 7-to-10-year duration from there.
Jason Lemkin
Yeah. Or just a pre-C deal at 60 post on a SAFE. It's hard. Databricks seems like a better deal.
60 post?
Jason Lemkin
Yeah.
It's quite cheap for a—
Jason Lemkin
Quite cheap.
3. Snowflake Fights Databricks
Honestly, it's getting worse. Snowflake is up year-to-date 60%, and we're seeing the re-acceleration of Databricks. Do they both just grow into absolute monsters? Can they peacefully coexist? Do you think one takes the majority of market share? I had Ron Gabrisko, their CRO, on our 20Sales podcast, and he was like, “Databricks' technology is 5 years ahead,” which I thought was a really interesting statement. Do you think they peacefully coexist? Does one take a monopoly? How does that look?
Rory O'Driscoll
Ron was correct. They came from slightly different places at slightly different times. Snowflake originally was very much your SQL data warehouse in the cloud. It was a few years earlier than Databricks, which originally, I think, was the Kafka product and all about moving data, with more AI use cases even out of the gate. So he is correct in that.
No one's going to coexist peacefully. They probably hate each other—in fact, we know they hate each other because they time their sales events to overlap with each other. I would say, differently, they're not going to, quote-unquote, peacefully coexist. They're going to struggle and fight against each other for the next 10 years, just like SAP and Oracle fought against each other for the last 20. They're going to eat each other's lunch, and it's going to be a grind.
I don't think either of them folds from here. It's hard to imagine. The core value of relational databases isn't going away for transactions, so the Snowflake asset is money good. Separately, I think Ron is correct: Databricks has more of an advantage in brand-new, AI-centric data manipulation and data movement applications.
So both are in good, adjacent, overlapping markets. They want a bit of each other's market. They're just going to slug it out. It probably means at some point that some of those margins get dinged a little bit, but you've seen it before. You've seen it, as I say, with Oracle, Sybase, and Informix. You've seen it with Workday, SAP, and Oracle. This is just what most enterprise software markets tend to be: oligopolies, and they tend to punch each other for 10 years.
Jason Lemkin
In our little corner of the world that is scale-ups and start-ups vis-à-vis Snowflake, the one thing I do know is we're just starting to learn what we can do with our data with agents. Even Snowflake is still learning. When we had the CEO of Snowflake at SaaStr Annual in May, he was just starting to talk about how they were going to use agents, right? Fast-forward to today: a couple of months later, all the vibe platforms can now directly access Snowflake data.
Yeah.
Jason Lemkin
We could fire up our Cursor, Lovable, or Replit and just build an app right now while we're here and access our Salesforce data. What will that mean to access that data? What will that mean for how we think about CRM, how we think about where we host it, and how we access it? I'm just not smart enough to even predict what that means in a year, because that wasn't even possible a couple of weeks ago.
Now, can you access every bit of data in Snowflake or Databricks in a Fortune 500 company? I assume the answer is no. But that is an epic change, and I can't even predict the slope of the curve next year, right? What happens—I know we overuse this word “agentic”—when I can use easy-to-use agents where I don't need a lot of engineers to access all of my data any way I want, and build any report, any analytics, or any workflow from that?
I think we're 1% on this journey, but the amount that agents will empower our data—we're just learning.
If I were to push you honestly and ask the question, will we see our CRMs—your Salesforces, your HubSpots—become databases which agents sit on top of and feed off?
Jason Lemkin
Yeah.
Or will these platforms move with the agentic world, build their own, and not become mere databases alone? Which one is the likely outcome?
Jason Lemkin
I think the fact that Marc Benioff has put 2,000 people on Agentforce tells you the future right there. He's already got 2,000 people on it.
Well, it tells you his intentions. It doesn't tell you his ability.
Jason Lemkin
We are still early in enterprises, and I think Salesforce in particular has 2 years to unlock all this capability, with the rate of change. It's just—because 2 years is not a lot of time at Salesforce. Traditionally, that's a major release.
Snowflake—
Yeah.
Jason Lemkin
—turned out to have time. There is more time in the older enterprises. Where that breaks for those that have massive amounts of data, I am not smart enough to predict. I would not bet against anyone that is managing a huge amount of structured and unstructured data. I wouldn't bet against anyone.
Rory O'Driscoll
What will probably happen is, if you want to build agents that are just using your CRM data and you're a Salesforce shop, just like Microsoft was able to bundle Microsoft products, you'll probably take the agent from Salesforce and get a combined thing.
But I think, and to Jason's point, I think enterprises that want to build more powerful agents—where we're not just drawing the data from 1 app, i.e. Salesforce, but drawing the data from maybe 5 or 6 different sources—the more likely architecture for that is some version of stuffing it all in Snowflake and then running an agent directly against that.
As you were talking earlier, Jason, about what you think with Snowflake, I remember one of the things we did 5 or 6 years ago that turned out in retrospect to be very smart: just literally to stuff all the data in Snowflake across all the systems, so over time you have access to that.
So if I'm a large enterprise and I want to use my internal—let's say a bank—I want to use my deposit system plus my Salesforce system plus something else. At a certain size, it won't work easily in just Salesforce, so you'll want to do what every large enterprise has done since the dawn of time: build some apps yourself.
And if agents become strategically important enough for super-big companies, then they'll throw $5 million and a bunch of Snowflake at it—or Databricks—and just build it themselves. So there's no doubt that Agentforce can get a fair slug of the market, but I'm also sure that at the high end there'll be a bunch of wonderfully bespoke projects that will make systems integrators rich for the next decade.
4. Security Favors Incumbents
Everything we're doing right now in AI is very exciting, but I've been thinking a lot about how Gainsight's been locked out of Salesforce for 2 weeks. I've been thinking a lot about how OpenAI just permanently kicked Mixpanel off its platform this week for a security breach.
I really think that with agents running everywhere with our data, the people who can securely manage that data and the people who have secure, or seemingly secure, agents may win. We're willing to bend some rules in the age of AI. We're willing to bend some rules to move quickly. I think security is going to benefit the incumbents.
I think we're going to be worried that our agents are depositing our data in 100 different places. It's crazy. I love Nick and the Gainsight team, but essentially their app has been down for 2 weeks with no known resolution time. Salesforce has kicked them off the platform. They kicked Drift off 5 months ago. Drift will never come back. It is dead. It is completely dead.
I think about those things, and I think about where all these agents are taking our data. I might want my agents from Salesforce, Snowflake, and Databricks. When things change, we get very excited about new vendors because the incumbents can't do it. Inherently, we take a little bit of risk, and we try to contain that risk in a pilot or in a less critical source of data. We always try to measure the risk at the beginning.
But this is our sensitive data flowing, and it may not matter for your average startup, but I generally worry we're underestimating security and data residency in general. I just worry, and I feel bad. I just couldn't imagine going through this at Gainsight.
Do you think the world—and big companies—are more unforgiving now? Over the last 10 or 15 years, a lot of companies have had breaches. Do you think this was more serious?
Jason Lemkin
It is more serious. Drift had the security breach. 700 folks' data were downloaded, and now a pirate group is asking for millions of dollars for each instance. Then this happens again with Gainsight.
I can't speak for Salesforce or the team—I mean, $45 billion—but I would be more conservative with who I let touch my data. We could say it's an OAuth issue or whatever, but I don't want this ever happening again. One time, we can blame Drift because it got acquired by one PE firm that got acquired by another PE firm—
Yeah.
Rory O'Driscoll
But 2 times, I might start locking down my platform. The third time, I might say, "I'm just going to own all the agents." I'm done with these risks. I don't know, but it's getting worse.
When people want to steal your data and ransom you for $1 million across 700 organizations, including Cloudflare, how big is the SecOps team at most startups you work with? 50? 100? How big was the latest deal you did? How big is the security team?
And the funny thing is, Rory, both the examples you cited are mature first- and second-generation SaaS companies, not brand-new AI-first companies. What you're saying is that new companies might get tagged with the consequence of a more restrictive security policy, even though you could argue it was older companies that, in both cases, were PE-managed that actually caused the problem. Life is unfair, but there you go.
Jason Lemkin
In AI, probably just before we started doing this, it kind of felt like the enterprise was going to win, that ServiceNow and everybody was going to win, and then it doesn't feel like that at all. Then we saw all the numbers take off, and basically very few incumbents grew materially this year. This could be a piece of the revenge of the enterprise.
Are you cynically suggesting that a large enterprise software company could say, "I'm using security as an excuse to cut you all off, but lo and behold, I have my own agent product right here, which you can now safely buy, Mr. Customer"?
Jason Lemkin
I think it's a good excuse. If you don't want Glean slurping all your data, I get it. If I don't want all of it going out of Slack or whatever, many incumbents—I think it's the best excuse there is. The existential risk is just too much to the vendor. It's not worth it.
I don't know how many board meetings you guys have been in where the first half of the presentation was how we're going to be more secure in the age of AI, but for me, it's been close to zero.
5. Public SaaS Gets Repriced
So we spoke about Databricks' growth. I do want to take the flip side of that, which is a less positive or optimistic side. PagerDuty: 2×, a $1 billion valuation at $500 million ARR, 4% growth.
We just saw—it's not on the schedule, so this is where Rory gets nuts at me because I just add stuff without asking him and then expect him, on a whim, to come up with something. Normally, we can edit out pauses, but now he's going to be extra pissed with me. Welcome to my life.
Eventbrite, they've been acquired for $500 million?
Jason Lemkin
Yeah.
Yeah?
Jason Lemkin
That's a premium, right? Yeah, so that's 1.5× revenue.
1.5× revenue.
Jason Lemkin
With a 50% premium.
With a 50% premium.
Rory O'Driscoll
Wow.
So, new news today, and we can take PagerDuty because it's so fresh, having that Eventbrite news. It's hard to ask for such immediate thoughts. How do we think about this very harsh new reality, given the lack of growth and the subsequent pricing from it?
Rory O'Driscoll
I'll surprise you, Harry. I'll cover both despite the complete lack of notice. I think there are 2 separate things, and one perhaps is a positive.
One is a fact about being public. When you're public and your stock is floating around at a low valuation, you're just very vulnerable to this. Someone comes into view, and you're not growing quickly. They offer you a 50% premium, and the board gets called in. The lawyer gives you the speech about fiduciary duties, and if you can't come up with a convincing reason why you can build better value than that premium, you're forced to take it. It's a tough place to be.
I can imagine the conversation at Eventbrite. I can imagine the conversation 2 weeks ago at Semrush, and I'm sure PagerDuty is thinking about the same thing. Two things to say, though, at a wider level. The first is, let's start with the positive. Someone else—very smart money—thinks these things are worth buying, and I think they're looking at it and saying, "You, Mr. Seller, haven't created value here, haven't found growth, and I think we can."
If you look at the 3 companies we're talking about, let's lump in Semrush because they were acquired 2 weeks ago by Adobe. Jason and I disagreed, but we definitely felt someone like Adobe could do something with that asset. I'm not sure what direction Eventbrite could take, but PagerDuty has an obvious set of next products, including AI agentic products around downtime resolution, that feel obvious to me.
Frankly, I wouldn't be surprised if an aggressive PE firm said, "Oh my gosh, I can buy this thing. I can then buy some small, hot AI startup, put them together, get this thing back to 20% growth, value it at 10×, and look like a hero." The positive would be that other people—smart, savvy money—look at these assets and say, "2× revenue is stupidly cheap. I'll have that."
Jason Lemkin
I hope so. I hope there's more deals. We see General Catalyst and others doing this: let's add AI to services businesses. We see a lot of talk of this.
But right now, we're not seeing a lot of these mashed-together legacy companies at hundreds of millions in B2B and hot AI startups magically flipping into a 20× or 15× ARR company. I'm not saying it's not coming, but we haven't seen PagerDuty.com and PagerDuty.ai magically mashed together into a winner yet, have we?
Rory O'Driscoll
No, we haven't. And you're right, Jason. But the funny thing is, I like PagerDuty. We looked at the deal 10 years ago. My then-new partner wrote a term sheet. We should have let him pay a little more because he was right. We love that market.
I remember the investment memo from 10 years ago, and it said clearly, "Summary: This is a great market. It's going to tap out, and you have to add a whole series of add-on products around managing the process of downtime or security breaches, managing the process of getting something back up." We didn't have it at the time, but now, obviously, you can add AI-enabled operational resolution.
The direction was clear and is clear. So you're right, Jason, they haven't done it. But I think that's just a disappointing outcome, let's just say. I think the direction of travel should have been clear, and if you'd been able to add it, I think—we talk a lot about how distribution is the huge advantage in software. Literally every ops team on the planet uses PagerDuty. For God's sake, it's pretty obvious what to add here, people. Get it done.
6. The SaaS TAM Trap
Rory, have your views—and Jason's too—on market size changed as an investor? Given what you just said, every ops team on the planet uses PagerDuty, and it's a $1 billion valuation. A 10% holding would be $100 million back. It's just a very sobering reality. Has your view on market size changed when investing today, given where else you can put your money and the sizes of those markets that we're seeing with your Lovables and your Replits?
Jason Lemkin
I see more and more folks who I thought would grow out of a small TAM not grow out enough.
Rory O'Driscoll
When I started as a B2B founder quite a while ago, everyone seemed to grow out of small TAMs for the most part. Some better than others, but it felt like we had time, and it felt like you had 4 or 5 years to figure it out at each stage, and you could see it coming. And now that the average public SaaS company is growing at 16%, it feels like no one figured this out. We’ve never grown more slowly, right?
We literally just looked at this chart in my presentation earlier. No one’s ever grown this slowly. So if the public guys can’t figure this out, I know the next generation of the kids should do better than the adults, but I’m worried that the majority of the public SaaS companies didn’t figure this out. The majority of the public SaaS companies, I think, are in a TAM trap.
How did the Aaron Levie and the Drew Houston and the others not figure out the TAM trap? And I love them, right? I love Aaron. How did we not all figure out the TAM trap? What hope is there for the rest of us?
Jason Lemkin
I can give you a clear answer on that. First of all, I think it’s a great division of the discussion into the TAM trap for existing companies, and then what does it mean for the new AI companies, and then maybe, third, what does it mean for venture. But let’s start on the first one: the SaaS TAM trap.
You keep saying, Jason, “How did they not figure it out?” Let me just offer a different perspective. Maybe there’s no answer. In other words, there are so many SaaS companies, it’s not that everyone was an idiot and couldn’t find the market. I don’t believe that at all. I believe that we made so many companies that we saturated the markets, and by the time you got to the point where you needed to expand beyond your market, in many cases there were other venture-backed SaaS companies in the adjacent market, so you just ran out of room.
I did a blog post on this in 2019 called “Hunger Games in SaaS.” Many of these markets—it’s not that some of the CEOs you cited are idiots, it’s that you have high penetration of the markets. Take the quintessential one you and I talk about all the time, Jason: Zoom. Everyone who needed a Zoom account has one, and everyone who has a Zoom account has a Teams account, the poor bastards, and they’re done, right? There’s nothing more to sell.
You’ve got to build a new thing. And the initial, quote-unquote, obvious new thing for Zoom pre-AI was that whole contact center business, and they couldn’t get that acquisition done, and there were already incumbents in the space. So I think pre-AI you ran out of TAM, right? So, Harry, to your question, as we’ve said many times, overpayment only works when the TAM is huge.
Mm.
Jason Lemkin
In finite TAMs, you’ve got to bid more tightly. It’s so funny, I’m going to give an anecdote about PagerDuty. When they went public and we did our internal autopsy, because you do, I looked at the model we’d underwritten 5 or 6 years ago, and we were accurate within 3% on the model prediction of revenues. All that happened was the market was just willing to pay more for the asset, and now it’s not.
So I think, in the existing space, it’s the TAM constraint, and I think you just have to be careful on price. Now, the question on the new markets, which I think is believable and credible, is: Does the AI labor expansion save us all and allow us to reach higher on price and still get these huge TAMs, or are we going to be in the same place 8 years from now? That’s the—actually—multi-trillion-dollar question, as it turns out.
Rory O'Driscoll
Well, I think there are 2. One is: Can AI allow us to tap more into labor budget, right? I think the second one, and I was trying to summarize this earlier today, is: Can AI provide so much value that you can charge an order of magnitude more than you could charge before? Gamma charging $100 a month instead of the $8 I pay for Canva, right? Or Cursor charging $500 a month when I pay $3 for Jira.
Jason Lemkin
Right.
Rory O'Driscoll
So you wonder, can we do that? And we don’t talk about Zoom much. When I think about Zoom, I can’t think of a better technical founder running a company than Eric. I can’t figure out—
Jason Lemkin
No.
Rory O'Driscoll
—someone I respect more on every level as a human, as an engineer, as a leader, than Eric. There’s a mean question, and I don’t deserve to even ask it because you spoke about it: Why didn’t they capture more TAM? Why didn’t they find a way to add 4 billion of note-takers when there’s a trillion note-takers? Why didn’t they?
And I don’t know the answer. It’s not because you’re not one of the smartest people in the industry thinking about this for a decade, but there was no great second act yet. Going back to your point, I worry.
Jason Lemkin
Well—
Rory O'Driscoll
I worry. And this is why I tell founders to take their exits and then say no because they can go bigger, but by default, take it.
Jason Lemkin
So many things in that to unpack. One is the multi-product thing. I think one of the big takeaways we’ve had is the need to be thinking about that second product much earlier than you would’ve thought. You don’t want to wait till you hit—what was that expression? Yes, I loved it.
Rory O'Driscoll
It was good, but I’m forgetting. What did we call it?
Was it TAM trap?
Rory O'Driscoll
The TAM trap.
Jason Lemkin
TAM trap.
Rory O'Driscoll
The TAM trap.
Jason Lemkin
Don’t wait till they hit the TAM trap. I mean, we were thinking—actually, we were comparing 2 of our portfolio companies—
Rory O'Driscoll
The book.
Jason Lemkin
—and we would say one of them has compounded really well because it’s continually added a new product that, for the first year or 2, is a couple of million dollars, but layered it in and now many hundreds of millions. So I think watching that TAM trap is key.
But the other thing you said, and it was in the speaker notes too, is on the AI pricing: If you’re pricing versus labor or value created, you’re getting enormously great prices because you’re saving a lot of labor. And I think you said in the speaker notes, what happens when there are 2 or 3 of these companies and the competition goes from, “Hey, I’m saving you $1,000 of labor a month,” to, “Yeah, I’m saving $1,000 of labor, but there are 3 providers of the same AI software, and they’re all willing to do it for $100.”
So your ability to get $500 gets eroded, and do you start seeing that happen in AI very quickly? That’s a good, that’s a super question. I mean, it hasn’t yet, I think.
7. Seats Become Existential
Speaking of the pricing challenges that we have here, we have Workday coming out saying seat reductions are an existential threat. We had Jeff Lawson from Twilio on the show with the 3 of us, and he said that we are unwaveringly going to see the movement away from seats, and that is going to happen. Can companies still price by seat in the age of AI? Is Workday inherently as threatened, and right to be concerned by this existential threat?
Rory O'Driscoll
If folks haven’t watched it, it’s worth rewatching. He was so good, right? And he made that comment that Twilio, especially if he were still CEO, would have been somewhat insulated from that because it’s based on usage, right? And in fact, Twilio is seeing a little bit of a resurgence; it has seen some reacceleration.
And he said he was very worried about seats, but he said, “I hadn’t been in the game in a little while, and I’ve been doing AI and working in my shop.” It has resonated in my mind since because he is right, and everyone is shrinking headcount in tech, at least. Even if they’re not shrinking headcount, ARR per employee is going to keep going up.
I crunched all the data before this morning. Everyone is going up. HubSpot is 2.8 times more efficient than in 2021. Salesforce is 2 times more efficient. Microsoft has said they’re already past peak employee, permanently past peak employee. We’re all going to figure out how to get more ARR per employee, and if you’re a leader, you’re just going to run out of seats, right? Mark was kind of aware of this when he did the pod too.
So I don’t have the answers. In the early days, it probably doesn’t matter, right? Your model is your model, and seats work well in some places, but it is existential. We are just going to get more and more efficient.
One of my biggest worries for investments is when startups aren’t getting more efficient. I’m not talking about profitability. That’s an investment. I’m talking about when their teams get more bloated as they scale. I kind of am out.
When I go to a board meeting and a CMO says, “Well, I could do that, but I need 50 people,” or a product guy says, “The reason we’re late is I need another 80 people on the product and engineering team,” I think it’s time to part ways. Give them a nice package and a good recommendation.
Jason’s going, “Can we get AI to replace you?”
Jason Lemkin
I want to see you grow 100% next year with 50% headcount growth.
Yeah.
Rory O'Driscoll
I think that’s healthy today. The way through early 2023 was, “I need 200% headcount to grow 100%,” and there’s still a lot of that DNA in the ecosystem. It’s still ricocheting around, probably in the majority of executives people will talk to.
So I think, with all these things, I don’t think the seat is dead, but as time goes by, I get more and more worried that it feels like Japan, like our population is organically shrinking. Has SaaS become like Japan?
That’s another time—
Rory O'Driscoll
It’s a great economy, but if everyone only has 0.9 kids, there are only so many seats to go around.
Jason Lemkin
So, Harry, first of all, my camera is right in front of your smiling face, so I literally haven’t seen you. I’m going to slide the camera—oh, there he is.
Rory O'Driscoll
Is it still okay on your side? Because I just miss seeing you, Harry.
You miss seeing me?
Rory O'Driscoll
Yeah.
Oh, that's sweet.
Jason Lemkin
How does Rory moving his computer change how he sees you? Am I missing something in AI video technology?
Rory O'Driscoll
No, I just know that—
Jason Lemkin
Doesn't the camera have to move?
Rory O'Driscoll
I know. Don't be a smartass, Jason.
Jason Lemkin
I'm not being a smartass. Harry's with me.
I was expecting something to change, and it's like Rory's moving.
Rory O'Driscoll
No, I'm moving back there. Gotcha.
Jason Lemkin
Okay. We'll let it go.
Rory O'Driscoll
I'm assuming it's working, and we're continuing. I want to come back to the last comment first—your comment on 2:1—and you're exactly right. As I think about it, I hadn't thought of it until you said it, but in 2021, every discussion was some version of, “Look, to get that extra 10 points of growth, we're going to be twice as inefficient at the margin as we were overall,” and the result of that is that overall efficiency has deteriorated. What you're saying now is that at the margin, we're trying to be twice as efficient, not inefficient, at the margin.
So you're exactly right. Everyone's efficiency is creeping up, and I think that's obviously—and independently—totally correct and super insightful when you said it. It might explain why, even though the growth rates of the public companies have gone down significantly, the valuations and the revenue multiples have not gone down as much. I think it's because, in return for slower growth, SaaS companies are at least getting wildly more efficient SaaS companies.
It's not one-for-one, as we've discussed, but at least it's better than nothing. Going back to the existential threat from Workday, I think software prices on value delivered, and when you couldn't measure value, all you had was per-seat pricing. Therefore, that's what people went with: everyone has to access the software, and everyone pays so much.
Then you had usage pricing, starting with AWS, which was inherently a more rational way for buyer and seller to allocate value. It tracked value more closely. I think the trend in everything is just to get more efficient. I think that's how capitalism works.
To the point that if you're using AI to deliver value, and if the AI is doing the work, it's going to be super hard to have a per-seat model because it's irrelevant. I don't think it will be as irrelevant for a lot of Workday as it will be for some others. There are other areas—for example, some areas of Salesforce—where you can imagine that, to the extent you entirely automate an SDR team, it's going to be hard to have a per-seat SDR model.
My guess is Workday will still be able to have some kind of X dollars per month for each employee served, and then Y dollars per month for HR staff actually using the software. But there probably will be fewer HR staff using the software, to your point, Jason, because if half the make-work that HR was doing is now done by AI, you're not going to get the same price. Therefore, maybe you have to charge on the value delivered versus simply the seats, and that's a more complex calculation.
I think that is true—all our companies are wrestling with this. You deliver a ton of value in AI, and maybe now you get the innovation budget and no one cares. But 1 or 2 years from now, you're going to have to link, as a startup, your pricing to the value delivered, and you're going to have to measure it. It's a lot harder to measure value than seats. You can count butts in seats pretty easily. Every login is a butt. When you're trying to measure value delivered, that's tricky.
Can we just go back to the growth and efficiency element? I always think that, when you're creating content, you have to think of your customer. And the customer—
Rory O'Driscoll
Yeah.
—that I always have in my head is the founder on their way to work, or the operator on their way to work, listening to our podcast or watching it. They're hearing, “I want growth, growth, growth.” And now they're hearing, “I also want efficiency, efficiency, efficiency, and 2 million per employee for Gamma and Lovable, at whatever it is.”
Do we just need both now, and is it a higher expectation to meet the bar for VCs? Or, when you're looking at those 2, is it, “I want growth above everything, and I'm fine to see less efficiency in the early days”?
Jason Lemkin
I think in the fastest-growing companies that I've invested in, no one gives a rat's ass about the bottom line. That's a different metric than how you scale today, right? And Rory made this point: there are actually fewer and fewer companies that are true outperformers.
As soon as your top portfolio company outperforms, everyone wants to give it $100 million today at every board meeting. No one really cares about efficiency per se, as long as they can get their money into the deal. So I don't think that's the issue. I think we're confusing the fact that everybody is just generating more revenue per employee.
But when you look at this, as we've talked about before, the likely ICONIQ data from earlier in the year shows that the fastest-growing AI companies—even with high inference costs, even with high AI costs—have the lowest burn multiples because their revenue is growing so much faster than the inference costs. I think that's what we're hoping for: that companies have never gotten to $100 million ARR more quickly.
If you do, I don't think we care how you get there anymore. I don't think that we care—
Yeah.
Jason Lemkin
—but we know deep down that hiring 1,000 people isn't the way to get to $100 million in a year. You can't hire them that quickly. As Maggie said, they're not all going to be great. So you literally can't brute-force $100 million in 10 months with humans.
Maybe Larry Ellison or Marc Benioff could, but I don't think anyone else. There's just not enough calls and enough time. You can't go from $1 million to $100 million in 10 months without massive inbound demand and a lot of AI.
Rory O'Driscoll
Yeah. I think you should break it up into a couple of areas. In fact, as we think about it, Jason, it's given me an insight into your eternal question on employment. Big picture, divide it up into AI startups and mature companies. The comment on ARR efficiency—efficiency per ARR—is very much a mature-company comment.
If you're a public company and you're only growing 10% or 15%, you better be kicking off cash or you'll be in trouble real quickly. Even if you are kicking off cash, you'll still get grief, but those are the companies that are optimizing their ARR per employee and are just focused on FCF—free cash flow. That's a very different set of people, with a very different set of dynamics, than the AI startups.
Public companies are grinding on efficiency, which means, as you say, lower employment and all that stuff. Now, when you come to the private AI companies, I think there are 2 categories. The small number of companies that are taking huge amounts of capital need it for model development, and primarily it's not for humans; they've got to spend it with NVIDIA.
So no one's telling OpenAI, “Be efficient,” or, if they are, he's clearly not listening. To a rounding error, those companies, as Jason said, are able to get all the money they want, spend it on compute, have relatively small headcount relative to their size, and no one's saying, “Be efficient.” They're just saying, “Grow quickly.”
Then, separately, at the app layer, you're seeing something slightly different, and Gamma's a good example of that. The interesting thing is that, because of this amazing new capability—for lack of a better word, call it foundation models—there are people in app land building a product, shipping it, and getting such traction that the traction is ahead of their ability to hire.
I mean, literally, there's no way to spend the money, right? We're seeing some of these app companies be astonishingly capital-efficient, especially at the early stages. Gamma's a great example of that. You ship the product, it's freaking amazing, people buy it, and they give you credit cards.
By the time you get around to hiring a sales force, you're doing so much money already that you're kicking off cash. At the app level, not all the time—I think some companies at scale are spending. But we're seeing the combination of hyper-growth and reasonable margins—not as good as SaaS, but still 60%. If you have that, then you have quite an attractive profile.
Not all of them are that way. Obviously, the coding companies have margin issues. But a lot of the companies are getting a long way on not a lot of capital and definitely not a lot of employees. So I think those are the 3 categories.
The interesting thing, Jason, is that this goes back to something you've been talking about and I've been trying to figure out the answer to: what's going on with employment? What's the consequence? I've been more, “It'll all be fine in the end,” and I still stand by that.
But the interesting thing, when I listed those 3 categories, is that the 1 thing they all have in common is that they don't need people. The big companies can't have people because they've got to be efficient. The model companies don't need people because they just need geniuses and GPUs. The small AI app startups are growing so damn quickly that they can't hire people. That's not great if you're people.
It's not.
Rory O'Driscoll
Overall, I'm an AI optimist. I think all this unemployment thing is bullshit. But in the near term, what you recognize is that it's a tough-ish market for employees in the tech marketplace. The labor-versus-capital discussion is that you need more capital relative to labor at the moment.
8. Google Enters Vibe Coding
The topic we have to discuss—we talk about Replit the whole time—
Jason Lemkin
Yeah.
With Lovable. But then Google has come out with a competitor. I think we've always been waiting for Google and ChatGPT to come out with one, and it's been very good. It's tied to Gemini, which has obviously blown past a lot of people's expectations.
When we look at this, how do we analyze it? Is this a case of an incumbent waiting for enough traction in a market and then going, “Thank you very much, Mr. Startup. I'm going to come in now with great models and distribution, and it's game over”? Or have they actually left it too late, and Lovable and Replit have built enough user base, enough brand, and enough brand trust that there is still a real dominant threat to Google's new product?
Jason Lemkin
Well, look, for what it's worth, I did try it. They launched this week. They launched a Replit-Lovable clone with no database and no OAuth. They said it's coming soon. Sometimes that's okay for a big company, so we'll see.
One thing that hasn't changed in the age of AI is that big companies only have so many priorities. They can introduce a lot of little tests, but at the end of the day, it takes a lot of energy in a big company to keep a big initiative going because there's so much else to support. So we'll see. It wasn't impressive in itself.
On the other hand, Google launched its competitor in less than 10 months, so you don't get 5 years anymore. Datadog just launched its PagerDuty competitor in the last 24 months. When was PagerDuty founded? 2008. You don't get that much time now. Now you don't even get a year.
The incessant pace of cloning and competition does worry me. If you only get months before the big guys come into your space when you blow up, it should make sense, right? If you go from $0 to $200 million in a year, you should attract some competition. It's not a free lunch, right?
But is there something that we take from this, like Rory just did? You do a GC AI, I think it is, where we're like, “Okay, they're not going to go into GC AI, but they are going to go into Lovable. They are going to go into Decagon. They are going to go here.”
There are themes where they're going to go, and there are themes where we're like, “They”—the model providers. The core question is: Where will model providers go in the application layer and threaten our businesses?
9. AI Finds New Venture Markets
Jason Lemkin
This is not—I mean, competing with coding tools is not that big of a jump, right?
Rory did a deal, I think, in the last week, or scaled it, that I really liked personally, even though I didn't examine it. You did sort of an AI for wealth management or asset management, right?
Rory O'Driscoll
Yeah.
Jason Lemkin
I love this for a lot of reasons. I have some questions. But Google isn't going to copy that. They're not going to copy automating trusts, estate planning, investment advice, tax efficiency, your investment legacy planning, or—maybe it doesn't do all of that.
Those are spaces where you have incumbents, but maybe you have some space to run, right?
Rory O'Driscoll
Agreed. The model provider is not the constraint there. For the record, I'd say I don't think the model provider will be the competition in many apps.
Going back to where I started, I think the OpenAI Code Red this morning was frankly tantamount to an admission that we need to do our core mission for the next year, and probably less futzing around with other things. That sound you might hear is the consumer hardware product slipping out a little.
I do believe that more of these apps are defensible. I think the model providers will be there. I think coding is obvious. But even when you get much beyond that, I think if I were on the board of OpenAI, it would be like, “Win the ChatGPT wars and you are worth $2 trillion. Let's not fuss around with little vertical markets that can be worth a couple of hundred million bucks. Why are you even talking about this?”
Especially when everybody poked poor old Google, and Microsoft said, “We'll make them dance.” OpenAI kind of laughed at them, and now they're poking back. You put all your effort behind that.
I think we may have seen peak “the models are going to do everything.” They're going to do coding, but are they—I don't know if they're going to expand into all these verticals at that level.
Thank you, Jason. On Range Wealth Management, I think the interesting comment—and, again, we're always loath to just push our investments—is that the big-picture story there is: Can you use AI not to sell software to wealth managers, but to automate the business of wealth management?
This is the key sentence that I like, because I hate the words “wealth management.” The idea is that you can go much further down the wealth continuum and give people the same kind of product that the super-rich get in terms of managing your stuff and managing your taxes, which, as Harry knows, in the UK are now north of 50% and getting higher.
You want to be able to manage your affairs, file your taxes, and handle a whole ton of work that's done expensively by humans but can be done really cheaply with AI, because it really is just: follow the law, fill in the forms, do the work. Hopefully, the idea there is that you automate a lot of that, and then you can deliver a high-quality product to a much broader marketplace.
One of the big-picture things I think is always true in investing is that whenever you see a product that only really rich people have, if you can find a way to get that in the hands of the rest of us, we all want it too.
Just on—what do we call it? The terrible TAM?
Jason Lemkin
The TAM trap.
I know. Yeah.
Jason Lemkin
On the wealth management—what's the vendor called? Sorry, I should know.
Range.
Jason Lemkin
Range? I love it. I get the problem. Anyone who's lived it, who's gone through any of this stuff, could talk about it. But I think you do have to be smart about the TAM, right?
They're going to charge $8,000 to $10,000 for something that you pay a bunch of numbnuts $30,000, $40,000, or $50,000 a year for now if you're wealthy, right? Maybe more. But it's not 10 times the price of the existing product. You just have to be smart, because you can pretend everyone in the world will pay you $10,000, but you also have to be rational to avoid a TAM trap, right?
Wealthfront's trying to go public, right? In theory, maybe it's a comp. In theory, Wealthfront should be a $10 trillion company. I mean, everyone could use this product, right? But in reality, there is some TAM limitation for Wealthfront, right?
Rory O'Driscoll
I totally agree. It's all about segmentation. I love Wealthfront. As a comment here, I really love Wealthfront and Betterment. Those are companies I really love, because, again, it's back to the same thing.
Wealthfront was saying that even paying 50 or 70 bps to someone to manage your money is crazy, because we can just put it in this automatic thing and do it automatically for 10 bps. The thing about those businesses, to your TAM comment, is that they actually take a long time to build, because the whole value proposition is: We're charging you less, and you just get to compound more.
In the end, they're lovely businesses. We looked at Betterment 10 years ago, and we figured it would take about this long—10 years—to just build. Remember, if you're charging 1% of assets, $1 billion is a lot of money. If you're only charging one-tenth of that, you need $10 billion to get to the same place. If you're targeting people with less money, by definition it takes longer.
These businesses take a long time to build. But I think when they do, they're way more powerful than some so-called wealth manager who's really good because he takes you golfing and gives you a PowerPoint once a quarter about how badly your money is doing, and he's really sorry.
Jason Lemkin
Or even better, they ask me if I want exposure to private equity and venture. That's the main value I get from Morgan Stanley.
“Hey, Jason, it's your advisor this quarter. I can get you into a hot venture fund you've never heard of.” SaaStr's Lemkin fund. The returns are negative at the moment, but it's a lengthy J-curve, and it's a hot deal.
It's a 3-and-30.
Jason Lemkin
Yeah.
3-and-30, and it's—
Jason Lemkin
3-and-30. Triple-layered SPV. Have you ever looked at my account? Do you know anything about me?
Okay, I didn't, actually. Sorry, I didn't mean to be divisive. I didn't like this deal. I saw this and thought, “Oof, God.” Sorry, and, you know—
Jason Lemkin
I didn't see it.
Why didn't you like it?
Jason Lemkin
likely Merrill.
What?
Jason Lemkin
Just—
Wait. Just pause. One: very old. But we're looking at Wealthfront—what, 17 years?
Jason Lemkin
Yeah.
Index and every good investor in there. How big is that, in the opportunity-cost world that we live in?
Jason Lemkin
The important question is: Why does—well—
There is a gap. There's Wealthfront and Vanguard at the bottom. I want to hear Rory's thoughts. And then there's the world's crappiest product, which is Goldman Sachs and Morgan Stanley, which take 1% of your assets and do nothing I can see other than give you loans, which are very valuable, right? For folks who don't know.
Literally, if you're sitting on $50 million of NVIDIA stock right now, you can sell it and pay $25 million in tax, or a bank will give you a loan. Now, it's not cheap today—it's 6%—but that's a lot better than 50% if you can deploy it. That's the only product I know.
They'll tell you they'll help you with your trusts. They don't. They refer you to someone who doesn't call you back. They'll tell you they'll help you with your taxes, and they'll tell you, "We're not allowed to talk about taxes." So they can't really do anything except give you a loan.
There is such a gap in the middle if AI can do estate planning, taxes, and all this. So, Rory, challenge me if I'm wrong. The question is: if AI enables it, then something that was shitty, to Harry's point, might become great if AI lets you do it, right? It might become great.
Rory O'Driscoll
First of all, you just nailed it. That is exactly the value proposition. You deliver trust, you deliver estate, you deliver all taxes. When you have to file your taxes, the fact that you do your estate with one person, your taxes with another person, and your wealth management with a third one is absurd. It should all be under one roof. But I want to go back to your comment, Harry, on Wealthfront.
Yeah.
Rory O'Driscoll
Because, again, I'm always uneasy just pushing our company. So let's talk about, I think, an excellent company that's not ours. Yes, it's taken a long time to compound to here, right? But not everything is tech-first, where the adoption cycles are 5 years. I think when you launch an investment in a company like Wealthfront, the adoption cycle of something like that is going to be 10 or 15 years. So, in my view, it's just on track.
And the financials are lovely, because at scale, asset management is a wonderful business. They are providing a cheaper product than anyone else at 10 bps, and they've lined up a bunch of millennials and whatever the generation a little bit older, 30-year-olds and 40-year-olds. Over the next 10 or 15 years, that generation is going to get rich. They're going to get rich with Wealthfront, they're going to keep their money there, and it's going to be a compounding machine.
Just like Charles Schwab was a compounding machine when they started in the '70s with cheap brokerage. It took a long time. They went through a lot. They were actually owned by BofA and then spun out in the '90s. I was there. But in the end, it just compounds, because over time, the only good thing is it does compound. Early on, wealth management in any form is a tough business, because it takes a long time to build. But when it does build, and Wealthfront is over that gap now, it's going to be there for the next 30 years in, frankly, a way that a lot of pure tech companies won't.
I get you on the compounding machine, and I share your view on the beauty of those businesses. But actually, you're competing for dollars against the same people, like your Kleiner Perkins or your Andreessen Horowitz, where LPs can put money in their funds or your funds at a Series B and C stage, and they are in Glean, and they are in Replit, and they are in the races to $100 million faster than we've ever seen. Those LPs will be going, "Those funds are more exciting." And you're going, "No, but it's compounding. Charles Schwab 2.0 is coming. I promise you. Watch the pod."
Jason Lemkin
I don't know that that's 100% true, though, Harry. I think it's 80% true, right? I think if you're going in to raise capital for your fund, and you're being compared to Glean and everything else, as long as you have the numbers, LPs are actually kind of excited if you have a slightly different way to get there. Slightly different—as long as you have top 10% numbers.
Do you think so, though? If you've got companies that are... Actually, to your point and to our point, bluntly, growth rates are so much higher, and growth expectations are so much higher. If it is a slower compounder, the next round is less certain than ever. It's less guaranteed.
Jason Lemkin
Yeah, but LPs are looking backwards. If you're sitting on multiple high-performing funds, you're going to get a fair amount of flexibility today.
Right? I think the point is that it's hard not to be seduced by the hottest deals today.
LPs love to see great follow-on investors. Well, Sequoia came into this, and Andreessen.
Rory O'Driscoll
I want to push back a little. I do take on board your point, and there's no doubt that the velocity of validation is super strong for AI companies right now. If you want to do a deal with the highest probability of a step-up in the next 6 to 9 months, you should do an AI company that's raised at a $1 billion pre, because 40% of the unicorns in Q1—I said 23% last week, and one of my colleagues corrected me—it's 40%. Forty percent of the unicorns that raised in Q1 as a unicorn for the first time have already had a follow-on round.
So I think, Harry, you're exactly right. If you want to buy short-term momentum, that's a great place to play. And it's not just short-term momentum; it's also driven by great performance. So yes, that's absolutely a good slug of what you're doing.
But in the end, the biggest uncertainty is not, can you get a markup? That's nice. The biggest uncertainty in the end is, can you build a big company here or not? And there are so few times when you can say, "I believe you can build a big company here," that you shouldn't then screen out and say, "Oh, I can build a big company, but it might take a little too long."
Because there's a rule in engineering that you're only as accurate as your least accurate variable. In other words, if you have 6 or 7 variables that go into something, your accuracy is determined by the thing you know has the widest variance. And if you have high certainty that something can be a company, that's the hard thing to do.
If you've got that, you can adjust for valuation, you can adjust for time, et cetera. I would love to be in Wealthfront, for example. I think it's just an awesome company. And even if you get in, I think that will compound, and you'll hold it, and 15 or 20 years from now—
And this is going to sound pejorative to AI. It's not. I love that space. It's where I play most of the time. Okay, let's do it this way, Harry. I think Schwab went public in either '82 or '83. It's public today. It's worth $60–80 billion. Name me 5 tech companies that went public in 1983.
Dude, are you fucking kidding me? I was born in '96.
Rory O'Driscoll
But my point is this: tech companies, they come quick and most of them go quick. Now, by the way, if I'd said 1986, you could have come back to me and said Microsoft, Oracle, and Sun. If I'd said, I think, '82, you could have said Apple. That's why I think I picked '83.
The point is that these singular, different companies—they're a little like, you know, mid Andros [?]. These companies that are off the beaten track and they're just a different thing, they often take longer to compound, but they end up with more empty space. As I say, Schwab has compounded for 3 or 4 decades, and God, I do wish you were in it.
Sorry, I didn't mean... I just think we're playing a relevance game, and I think this is the honest truth about new-age venture. We're playing a relevance game where companies raise 4 rounds in a year, where media matters more than ever before—duh, all of us here—and where you're like, "Oh, it's slow compounding coming soon."
Rory O'Driscoll
I didn't say slow, by the way.
It's just a tougher game. And I think LPs are seduced by incredible follow-on investors, quick up rounds, and numbers, still. I'd rather be playing that game than the "It's coming" game.
Rory O'Driscoll
And you're right, Harry. You should do that, provided you also write about the underlying investments. So if you play that game and you're wrong about the investments, then you'll just be the guy who did a load of high-priced rounds in a deal that didn't work.
So I agree with you, but, again, I go back to my comment. When you have high certainty that a big company can be built here, you weight that more highly than everything else. I think, actually, Peter Thiel—as with all intelligent venture comments, when you go back long enough, you discover Peter Thiel made them already—I think he said somewhere in his book something to the effect of, "All that matters is, can you build a big company here?"
And literally he said, "Because it's so hard to find them, they have no other rules." Because their perspective is, once I filter for that, I can't have any bullshit rules on stage or on sector. I just want big. And it's what gave them the courage to do biotech, defense, and software.
We're not as brilliant as that, obviously, but I think it's some version of that rule, which is: when you see a company that can be big and you see it's tracking to be big, prioritize that over hype and FOMO.
Rory, can I be absolutely savage? Do you have to be in that slow-compounding, picking world? Because there are 2 worlds in venture. There's the obvious and really, really competitive: insane growth, really, really obvious. And then there's, "I'm gonna be smarter, pick the compounder, see beauty where others don't."
Do you have to be here, respectfully, because you're sitting in the Valley at Series B, and you're against Andreessen, Founders Fund, Sequoia, and you can't beat them?
Rory O'Driscoll
I think you have to do both, and you can do both. I think, again, going back to my comment, I'm not sitting here going, "I want to filter for X, Y, or Z.
I want to filter for great companies. Then I have to win them. You're right. If you're identifying a great AI company in XYZ space, then you're going to find way more competition, which means either you'll lose or you'll win and you'll pay the market price to win, which won't be cheap.
And that's one way to make money. That's most of what we do. But you can also go and look at a space where you go, “Oh, I think this is interesting and differentiated.” As long as I have the same conviction on the ultimate outcome, you can do both, right?
Again, it's back to the—you're trying to apply a momentum and hotness rule, and I'm trying to apply a “will there be a big company in the end?” rule. I get the interim consequences. To be very clear, someone said it to me 20 years ago as an LP, right? He said, “There's no such thing as blue-collar venture.”
It was a brutal comment, but I think it's your point, Harry, right? You see what I'm saying? It's like there's no such thing as off-value, randomly non-cool stuff. At the end of the day, we're building high-growth companies, and you're not going to make it on value. You're not trying to choose on value. You're trying to choose on certainty of a big outcome.
Jason Lemkin
For what it's worth, it might be a fool's errand to invest in things that you're just very interested in. But I think there is an advantage to it. And I'll tell you what I'm interested in for ’26 and ’27.
This is why I like Rory's investment. I know this sounds obvious, but AI for coding is great, but we didn't even figure that out. Claude figured that out. Cursor didn't figure this out. Replit, Lovable, and Bolt didn't figure it out. I can tell you the story: Claude figured it out.
Anthropic—the guys, once they quit OpenAI, they figured it out, and everyone grafted onto this, including Gamma. What I like is the next generation. Can AI take large markets, like wealth management, that don't work today? Can AI really, for real, with Claude 7 and everything, utterly disrupt it? I think that can be huge.
Rory O'Driscoll
Mm.
Jason Lemkin
Agreed.
Rory O'Driscoll
Right?
Jason Lemkin
And I'll give you an example. I set up 3 trusts. The wealth management didn't help at all. Then I went to the lawyers, and it took me 11 months to set up 3 trusts.
I said, “I'm really frustrated this took too long,” to this guy who's a celebrated trust lawyer in Silicon Valley. He's like, “Well, good news: most of my clients never even finish them.”
I'm not saying momentum investment isn't the right thing today. If you can come in with AI and magically take every single frustrating part, how many Americans are affected by this? I think the Wall Street Journal just said today the average American retiring has $1.8 million in cash and equity.
If you can take all the friction out of that—all the friction out of retirement, wealth management, investing, trusts, redeploying QSBS and everything—because of AI, I think you could build a $20 billion, $40 billion, or $50 billion company. I would at least want to take the meeting.
This is something that, if AI can solve some of the biggest headaches that we see that maybe you don't see every day—maybe they're in environmental compliance, maybe they're in other things—but it's at least worth the meeting to see if it can utterly disrupt how it's done.
Rory O'Driscoll
I totally agree.
Jason Lemkin
Right?
Rory O'Driscoll
And I really like the pitch here, which is: you're saying it's not the ultra-wealthy. They have a million people who'll flatter them and do their work for them and charge them a gazillion dollars. It's the entrepreneur, the doctor, the dentist who's earning good coin.
We discussed earlier that dentists and doctors are well paid, but their affairs are modestly complex. They don't want to screw up their Roth IRA withdrawal. They want to leave their house to the kids. They don't want to have a big estate tax problem.
Those are the kinds of things—more complex than nothing, but not where you can spend $20,000 on a lawyer to fix it—that I think are a huge market. I'm sure people in the UK notice—
It's not paying—
Rory O'Driscoll
Let me finish. In the US, unlike the UK, everyone has to file their own taxes, which is just one thing. I've paid taxes in Ireland, England, and the States, so I know the different systems.
Everyone has to file this god-awful tax return every year, and the minute your affairs get even mildly complex—you do a rental property, you have a distribution, you have a capital gain because of an investment you made in a restaurant—suddenly your tax affairs are complex. If you screw it up, you end up paying more money.
Those are the people who need that kind of mass-market wealth advice on how to handle their affairs better. Right now, it's a disparate group of attorneys and accountants, and it's quite messy.
I do think AI, like a lot of other markets, is a little like healthcare. There's a whole bunch of knowable but nonetheless complex information that has to be assembled and marshaled, and at the right time, the person who has the question has to get the right answer.
That question can be, “What form of cancer is this, based on the CT scan?” Or, “How much do I owe to the US government based on these facts?” But you want the right answer at the right time, and it turns out machines do that a lot better than humans.
My takeaway is you need a new wealth manager, dude. Seriously.
Rory O'Driscoll
Okay, we need to have—Harry.
I'm not just doing the “don't have that.”
Rory O'Driscoll
Harry.
I can introduce you to—
Rory O'Driscoll
Harry, not everyone has a wealth management problem, Harry. How about we focus back on the problems of the people—the founders who are trying to build wealth—rather than you as a rich guy trying to spend it, okay? Come on.
I'm a humble podcaster, Rory.
Rory O'Driscoll
Boo.
Jason Lemkin
I believe that AI will disrupt some of these categories and build huge businesses. I believe it. Maybe be capital-efficient until you prove it.
If Rory's deal does $100 million, growing 150% or 200%, everyone will flood into this, okay? And say it made no sense back in the day.
Not every founder can directly compete with Cursor as a founder. We have to play to our strengths. I might have invested just because I'm passionate. Maybe it was a bad idea. I'm into it. But you might have convinced me: maybe just don't spend all of it.
I think they did—
Jason Lemkin
Maybe be a little more conservative.
Did they not bring you into the deal?
Jason Lemkin
They did not bring me into the deal.
Oh, he brought me in.
Jason Lemkin
Yeah. They did not bring me into the deal.
Rory O'Driscoll
I think—shut up, Harry, because Jason's made a really important point that I think is relevant to our wider founders.
Your discipline as a founder on capital is exactly proportional, in part, to how hot the market is perceived to be. If you're playing a game that's in a market where you need to make progress before you can raise, then you don't have the ramp for a raise-before-Friday strategy. You have the capital discipline to prove your point.
In the end, if you prove it, you'll get the capital. But I think, Jason, that was a frankly spot-on comment. We could send you as our board member. Literally: “Here, guys, build value. If you prove it, the world will be beating a path to your door. But if you half-prove it, you'll be screwed.”
I think that's a great note to close on.
Jason Lemkin
There's no quick-fire?
10. Hard Problems Beat Hype
One quick-fire: Superbase is now at $5 billion. Lovable is at $6 billion. Obviously, Lovable uses Superbase for every instance. Would you rather be in Supabase, or would you rather be in Lovable?
Rory O'Driscoll
I'll say Lovable, and I'll tell you why. I think Supabase is benefiting from the trend of vibe coding, and Lovable is a bet, fundamentally. It's in the front end, monetizing on vibe coding.
One of 2 things happens. Either vibe coding is a category or it's not. If it's not a category, both of them are screwed. If it is a category, Lovable gets more of the money than Supabase, just because it's the front end and it gets, I don't know, $20, and they pay $2 of it to Supabase. Some version like that.
If you're in a highly risky category, the dumb bet is to be, “Well, if I win, I get a little, but if I lose, I lose 100%.” You may as well be in for a penny versus in for a pound, as we would say in the UK.
The thing about the Lovable bet is, if you win, you're going to win big, which of course is why a smart young man like you is in Lovable, Harry. I thought I'd put in one pitch for you there, dude.
Thank you so much.
Jason Lemkin
I would take Superbase.
Uh—
Jason Lemkin
No, I'll tell you why.
Okay.
Jason Lemkin
For what it's worth, this is how I'm feeling today because of stability. I think Superbase is a harder problem to solve.
Right now, today, this is where I'm conservative. There's just so much change. I don't know what Google's going to do. I would just prefer a harder problem today.
Even if my returns were the same or lower, I'm sleeping fine. But I'm anxious about cloneable stuff. Hard problems are reassuring. At the end of the day, Superbase is just, I think, a fork of Postgres.
It’s open source that they’ve redone.
Yeah.
Jason Lemkin
It can be done again. Neon did it, then Replit—although Databricks bought them for $1 billion. But databases are a hard problem. You can only lose so much data. You can only have so many issues. You have to figure this out.
And five years of investing in a database that everybody uses—it isn’t so easy to churn and leave your database, right? This is what I’m thinking going into next year, if we want to close. This was a year where we tolerated a lot of churn. We only cared about growth. This was the year of growth, and so is next year. But I’d love a little defensibility. I would just love a few hard frigging problems.
We’re past the thin-wrapper layer, but I’m going to ask: What are you picking between Lovable and Supabase?
Oh, dude, I’m Lovable all the way, baby.
Jason Lemkin
Lovable all the way. We’d love to lead this even better.
Harry is loyal to his paycheck.
The loveliest thing about this is that we knew each other well before, but the friendship that we have as a three now, having done this show, is just freaking awesome. Honestly, it’s one of the highlights of my week, doing this show every week.
I’ve never said this to both of you guys, but I so appreciate the friendship that we have. Thank you for doing the show with me, because it’s always so much fun. I learn so much, and I get so many messages from founders who learn so much. So thank you for putting up with me, both of you. I know it’s not always easy.
Jason Lemkin
Yep.
But you’re awesome.
Jason Lemkin
And thanks to everyone who stuck it out to the end. We appreciate it.
Rory O'Driscoll
Take care, guys. Next year in London, I promise.