Jason Cohen:融资算术、AI定价与Build-to-Prod建议
Jason’s Takes on This Week’s 20VC: Meet 100 VCs, None-and-Done Beats One-and-Done, and Build-to-Prod Is Where I’d Make 10 Bets
提供了极具操作性的融资策略(如基金算术检查、路演名单规划)和AI SaaS的具体战术(路由层建设、收入风险建模),直接解决当下创业者的核心痛点。
The deeper cut on a week where capital concentrated harder than I’ve ever seen, and what founders should actually do about it
在资本集中程度远超我以往所见的一周,更深层的洞察,以及创始人真正应该采取的行动
Harry, Rory and I covered a lot this week: a $20M ARR profitable company that can’t get a meeting, Anthropic’s $16.8B quarter, CoreWeave’s 25% drop, Modal at $15.75B, and Berkshire doubling down on Bending Spoons. Here’s my cut for founders.
Harry、Rory 和我本周涵盖了大量内容:一家 ARR 达 2000 万美元且盈利的公司却连个会议都约不到、Anthropic 季度营收 168 亿美元、CoreWeave 下跌 25%、Modal 估值 157.5 亿美元,以及伯克希尔·哈撒韦加倍下注 Bending Spoons。以下是我对创始人的见解。
1. Top-Decile Numbers in an Unsexy Category Means 100 VC Meetings
1. 在不性感的赛道中达到顶尖十分位数意味着 100 场 VC 会议
For years, top-decile growth was an automatic term sheet. You’d walk into Rory’s office at Scale, he’d know every comp since the dawn of time, and if he believed in you, you walked out with a term sheet. That world is gone if you’re outside the 3-4 categories everyone wants.
多年来,顶尖十分位的增长率是自动获得条款清单(term sheet)的通行证。你会走进 Scale 公司的 Rory 的办公室,他了解自时间伊始以来的所有竞争情况,如果他相信你,你就能带着条款清单离开。如果你不在每个人都想要的 3-4 个类别之内,那个世界已经一去不复返了。
The company Harry met is $20M ARR, growing 6-7x, profitable. Crickets from the top firms. Someone will still fund it. It just won’t be the seven Benchmark partners. It will be a growth investor whose name isn’t Index or a16z, who sees it as the best deal of their quarter.
Harry 见面的这家公司 ARR 为 2000 万美元,增长 6-7 倍,且已盈利。顶级风投机构对此毫无反应(crickets)。仍会有人投资它,只是不会是 Benchmark 的那七位合伙人。而会是一家名字不是 Index 或 a16z 的成长型投资者,将其视为他们本季度的最佳交易。
My learning → If you’re vertical software or anything without “AI infra” in the pitch, plan the round like it’s 2009. Build a list of 100 investors, not 15. Budget 2-3 months. Treat the top 10 firms as a lottery ticket, not the plan.
我的心得 → 如果你是垂直软件或在推介中没有“AI 基础设施”字样,就按 2009 年的方式规划本轮融资。列出 100 家投资者的名单,而不是 15 家。预算 2-3 个月。将前 10 家顶级机构视为彩票,而非计划。
2. Know the Fund Math of Whoever You’re Pitching
2. 了解你正在推介对象的基金数学逻辑
A $5B fund raising every 18 months needs billion-dollar positions. Not billion-dollar exits. Billion-dollar gains on their stake. In their IC memo, a $1B gain is the B case. The A case is $25B+.
一只每 18 个月募集一次的 50 亿美元基金需要十亿美元级别的头寸。不是十亿美元级别的退出,而是其持股带来的十亿美元级收益。在其投资决策委员会(IC)备忘录中,10 亿美元的收益是 B 类案例,A 类案例则是 250 亿美元以上。
So when you pitch a $2B outcome to a mega-fund, you’re not being rejected on quality. You’re being rejected on arithmetic. Rory’s right that only a handful of funds can play this game, but those are exactly the ones founders chase first.
因此,当你向超级基金推介 20 亿美元的结果时,你不是因为质量被拒绝,而是因为算术问题被拒绝。Rory 说得对,只有少数基金能玩这个游戏,但恰恰是这些基金是创始人首先追逐的对象。
My learning → Before every pitch, divide the fund size by 20 and ask whether your realistic outcome gets them a position that size. If it doesn’t, you’re pitching the wrong fund, no matter how good the meeting feels.
我的心得 → 每次推介前,用基金规模除以 20,并询问你的现实结果是否能让他们获得该规模的头寸。如果不能,无论会议感觉多好,你都在向错误的基金推介。
3. One-and-Done Used to Be Nirvana. In the AI Era, It’s a Trap.
3. “一次性融资”曾是天堂。在 AI 时代,它是一个陷阱。
I used to love one-and-done. Raise a couple million, never raise again, no pressure, keep growing. Zapier is the canonical example: one real venture round, about $300M in revenue, generational in its own way, probably won’t IPO.
我曾经喜欢一次性融资。筹集几百万美元,再也不融资,没有压力,继续增长。Zapier 是典型例子:仅进行了一轮真正的风险投资,收入约 3 亿美元,以某种方式具有代际意义,可能不会上市。
But what if Zapier had raised nothing and the founders just split $200M a year? That’s 37signals. Once you have VCs on the cap table, dividending out profits gets hard. Buying them out from cash flow gets expensive. If an investor owns 30% and you pay 6x cash flow, you’ve tied up two full years of cash.
但如果 Zapier 一分融资都没拿到,创始人每年直接分掉 2 亿美元呢?这就是 37signals 的模式。一旦你的股权结构表(cap table)里有风投机构,通过分红来分配利润就会变得困难。从现金流中回购他们的股份则成本高昂。如果一位投资者持有 30% 的股份,而你按现金流的 6 倍进行回购,你就得锁定整整两年的全部现金流。
My learning → If you can get going without venture, do it. With AI cutting the team you need to get to $10M ARR, none-and-done is now realistic for a lot more founders than it was three years ago. One-and-done gets you the worst of both: a cap table that wants an exit and a business built not to have one.
我的心得 → 如果能不靠风险投资起步,那就别找。随着 AI 技术降低了团队实现 1000 万美元 ARR(年度经常性收入)所需的人数,‘零轮且一次性退出’(none-and-done)对更多创始人来说现在比三年前更现实了。而‘一轮且一次性退出’(one-and-done)则会让你两头受罪:既有一个渴望退出的股权结构表,又是一家本就不打算退出的公司。
4. Pick Seed Investors Who Can Carry You
4. 选择能带你走到最后的种子轮投资者
The portfolio company I mentioned raised about a $3M seed and plans to never raise again. It’s growing 15-18% a month, fully agentic, checks every box. Nobody wants to meet. That means its early investors may have to carry it, like the old days.
我之前提到的那家投资组合公司筹集了约 300 万美元的种子轮融资,并计划不再进行后续融资。它每月增长 15-18%,完全具备自主代理(agentic)能力,满足了所有条件。但没人愿意去见它。这意味着它的早期投资者可能不得不像过去那样继续支持它。
That only works if they have reserves and the conviction to use them. A lot of seed funds don’t. And the ones that are actually a multi-stage firm’s seed program will crush everyone else’s allocation and may not care about a $500M outcome.
但这只有在他们拥有储备金并有信心动用这些资金时才有效。许多种子基金并没有这样的储备。而那些实际上是多阶段基金旗下种子项目的机构,会挤压其他所有机构的分配额度,并且可能并不在乎是否达到 5 亿美元的退出结果。
My learning → Ask every seed investor two questions: what are your reserves per company, and what did you do the last time a portfolio company was growing well but couldn’t raise? The answer tells you whether they’ll carry you or just send a nice note.
我的心得 → 问每一位种子轮投资者两个问题:你们每家公司的储备金是多少?上次当一家投资组合公司发展良好却无法融资时,你们做了什么?答案会告诉你他们是会扶持你,还是只寄来一封客套的慰问信。
5. Take the Valuation That Wins the Day
5. 接受当天最能赢的估值
Anthropic was expected at $2T for its IPO. The talk dropped to $1.5T. Chamath’s take was right: raise whatever you need at $1.5T and move on. It’s just a valuation. Win the day.
Anthropic 原本预计其 IPO 估值为 2 万亿美元。后来传闻降至 1.5 万亿美元。Chamath 的观点是正确的:在 1.5 万亿美元的估值下融到所需资金,然后继续前行。这只是一个估值数字。赢得当下最重要。
The same applies at every stage. A billion is the new $100M at Series B. But if you stretch to the top number and your growth slows from 300% to 70%, you wake up inside a great company that’s simply priced wrong.
这一原则适用于各个阶段。在 B 轮融资中,10 亿美元是新的 1 亿美元门槛。但如果你为了追求最高估值而强行拉伸,导致增长率从 300% 放缓至 70%,你就会发现自己身处一家优秀却定价错误的公司之中。
My learning → Pick the valuation you can comfortably grow into in 18 months, not the one that tops TechCrunch. The extra 30% on the headline price isn’t worth a flat or down next round.
我的心得 → 选择一个你在 18 个月内能够舒适地成长起来的估值,而不是那个登上 TechCrunch 头条的最高估值。 headline price(头版价格)上额外的 30% 并不值得以下一轮估值持平或下跌为代价。
6. Your AI Revenue Has Less “R” in It Than You Think
6. 你的 AI 收入中带有“R”(Recurring/持续性)的部分比你想象的要少
Anthropic’s quarter was unprecedented. But developers aren’t loyal. The share swings between Anthropic, OpenAI, open weights and brand-new entrants just since this show started have been enormous. It wouldn’t shock me if Anthropic’s revenue share is down 10% a year from now while the business is still great in absolute terms.
Anthropic 的季度表现史无前例。但开发者并不忠诚。自该展示活动开始以来,Anthropic、OpenAI、开源权重模型以及全新进入者之间的份额波动巨大。即使 Anthropic 的收入份额从现在起每年下降 10%,而其业务在绝对值上仍然很棒,我也不会感到惊讶。
If that’s true for the best AI company in the world, it’s true for your usage-based AI product too.
如果这对全球最好的 AI 公司都成立,那么对你基于用量的 AI 产品也同样成立。
My learning → Don’t model AI revenue like classic B2B ARR. Run a plan where 20-30% of usage revenue is at risk to a cheaper or better alternative in any 12-month window, and know what you’d do if it happens.
我的心得 → 不要像经典 B2B ARR(年度经常性收入)那样为 AI 收入建模。制定一个计划,确保在任意 12 个月的时间窗口内,有 20-30% 的使用量收入面临被更便宜或更好的替代品取代的风险,并清楚一旦发生这种情况你该怎么做。
7. Route Your Models Like Replit Does
7. 像 Replit 那样路由你的模型
Replit flipped its default from Opus and Fable to OpenAI. The press called it a breakup. It wasn’t. We use Replit 14-15 hours a day. They have their own router, and OpenAI was 30-40% cheaper for roughly the same output. Next week it may flip back.
Replit 将其默认模型从 Opus 和 Fable 切换到了 OpenAI。媒体称之为“分手”,其实并非如此。我们每天使用 Replit 14-15 小时。他们有自己的路由系统,而 OpenAI 在产出大致相同的情况下便宜了 30-40%。下周它可能会切回去。
The bigger tell: Replit, Lovable, Base44 and v0 are each around $1B in revenue, with extremely cost-sensitive customers at every tier. They have the strongest incentive on Earth to route well. None of them moved users to Kimi. That tells you more about open-weight quality in production than any benchmark.
更大的信号是:Replit、Lovable、Base44 和 v0 的营收均约为 10 亿美元,且每个层级都有对成本极度敏感的客户。它们拥有地球上最强的动力去做好路由选择。它们都没有将用户迁移到 Kimi。这比任何基准测试更能说明生产环境中开放权重模型的质量。
My learning → If you’re building on LLMs, own a routing layer and re-test your defaults monthly. A 30-40% COGS swing on the same quality is the difference between a 50% and a 70% gross margin business.
我的心得 → 如果你正在基于 LLM(大型语言模型)构建产品,请掌控路由层并每月重新测试你的默认设置。在同等质量下,30-40% 的 COGS(销货成本)波动,意味着毛利率是在 50% 还是 70% 之间的差异。
8. Build-to-Prod Is the Most Important Category in Software
8. Build-to-Prod(构建至生产环境)是软件中最重要的类别
Everyone is building 10-14 hours a day in Claude Code, Cursor, Replit. The code is pretty darn good. It’s never production-ready. The time to review, test and harden it is still an order of magnitude more than the time to generate it. The engineer builds the feature on their phone at a barbecue and spends the next three days fixing it.
每个人都在 Claude Code、Cursor、Replit 中每天构建代码 10-14 小时。生成的代码相当不错,但从未达到生产就绪状态。审查、测试和加固代码所需的时间仍然是生成代码时间的数量级倍数。工程师可能在烧烤聚会上用手机构建了功能,然后花接下来的三天时间来修复它。
Generation is a solved-enough problem. Let Sam and Dario fight over it every day. We all benefit. The open question is how anything gets from “works in dev” to production. That’s where I’d make 10 bets today, knowing some may get killed by Anthropic. Claude Code Review launching proves the point rather than ending the category.
代码生成是一个已经足够解决的问题。让 Sam 和 Dario 每天为此争斗吧,我们都从中受益。真正悬而未决的问题是,如何让代码从“开发环境中可用”进入生产环境。这是我今天愿意下注十个方向的领域,尽管其中一些可能会被 Anthropic 扼杀。Claude Code Review 的发布证明了这一点,而非终结了这个类别。
My learning → If you’re building in the coding stack, build for the 90% of time spent after the code is written. If you’re a team shipping with AI, budget review time explicitly: when we scope a feature now, the build is the small number.
我的心得 → 如果你在构建编码工具栈,请专注于代码编写后那 90% 的时间投入。如果你是使用 AI 进行交付的团队,请明确预算审查时间:当我们现在规划一个功能时,构建只是其中很小的一部分。
9. Don’t Build a Company That Exists Because Someone Else Needs It For Now
9. 不要建立一个仅因他人暂时需要才存在的公司
CoreWeave dropped about 25% in a week. It exists because Nvidia needs it to exist right now. It isn’t producing silicon or software nobody else can. Oracle is renting excess capacity because it can’t sell enough enterprise software. Those are B-tier assets, and B-tier assets get hit hardest by every shock.
CoreWeave 在一周内下跌了约 25%。它的存在是因为 Nvidia 目前需要它存在。它并没有生产其他人无法生产的硅片或软件。Oracle 出租过剩产能是因为它卖不出足够的企业软件。这些属于 B 级资产,而 B 级资产在每次冲击中受到的打击最重。
Founders build B-tier companies all the time without realizing it: the wrapper a platform tolerates, the integration a partner hasn’t gotten around to building.
创始人一直在不知不觉中打造B级公司:那些平台容忍的包装层,或合作伙伴尚未着手构建的集成。
My learning → Write down the one thing you do that your biggest partner or supplier couldn’t do themselves in 12 months. If the honest answer is “nothing, they just haven’t prioritized it,” your valuation multiple and your shock risk should reflect it.
我的学习心得 → 写下你做的、而你最大的合作伙伴或供应商在12个月内无法自行完成的一件事。如果诚实的答案是“没有,他们只是还没优先考虑”,那么你的估值倍数和冲击风险也应据此反映。
10. AI Versions of Low-Multiple Categories Will Settle Toward Their Peers
10. AI版本的低倍数类别将向其同行靠拢
Marketing tech is the worst public category. HubSpot and Klaviyo aren’t dying and trade under 3x revenue. Braze was the best exit in public GTM at about 6x. Now look at the agentic players in those same categories raising at 40x+.
营销科技(MarTech)是最糟糕的公开市场类别。HubSpot 和 Klaviyo 并未衰落,且交易价格低于营收的3倍。Braze 曾是公开市场中表现最好的GTM退出案例,估值约为6倍。如今看看同一类别中的代理型玩家(agentic players)以40倍以上估值融资的情况。
更进一步:量化金融体系
看懂新闻只是起点——沿量化金融路径,把它变成能交付的工程能力