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中国 AI 两周观察:硬件优势真实,软件叙事过热,创投筛选机制在错杀异类

这篇文章最有价值的判断是“中国 AI 的硬件优势比外界想得更硬”,但它对“中国创始人”和“中国软件”的悲观看法明显样本不足、VC 口味过重,结论有启发却不能照单全收。
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2026-03-26 原文链接 ↗
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核心观点

  • 硬件优势是真优势 作者对深圳和大湾区硬件网络的判断基本站得住,因为供应链密度、逆向工程能力、打样速度和本地化程度确实构成了西方难以短期复制的系统优势,这不是“便宜制造”那么简单,而是“工程迭代基础设施”。
  • 软件悲观有道理,但论证过猛 作者看空中国软件和模型商业化,这个方向判断并不离谱,因为闭源模型能力、GPU 约束、全球收入规模、产品被基础模型吞掉的风险都是真问题;但他把“中国软件整体弱”说得过于整齐,忽略了政企、本地部署、垂类工作流和区域市场差异。
  • 创始人筛选机制可能确实错配 alpha 作者最尖锐的判断是,本地教育体系和 VC 审美更容易奖励“标准优等生型执行者”,而不是“离群型原创者”;这个判断有现实解释力,因为很多真正做出代际公司的创始人确实不符合主流履历模板,但作者把“叛逆气质”几乎神化,也有浪漫化嫌疑。
  • 一级市场估值泡沫风险值得严肃对待 文中对模型公司和人形机器人估值的批评是全文最接近投资结论的部分,因为用稀缺公开标的给私募资产定价、依赖 IPO 窗口兑现、而商业化又明显滞后,这套机制本来就脆弱;即便具体倍数口径可能有误,泡沫信号依然明显。
  • 全球化中国团队是不对称机会 作者注意到很多中国创始人天然按全球市场设计产品,这个观察很重要,因为“中国产能/工程 + 全球市场/产品叙事”的组合确实可能跑出强公司;但这类机会依赖极强的团队结构,不是所有“先全球后中国”的团队都能成立。

跟我们的关联

  • 对 ATou 意味着什么、下一步怎么用 ATou 如果在看 AI 创业或合作机会,不能再只盯模型和 App 层,因为最硬的壁垒可能在供应链、交付和硬件迭代;下一步应把“是否有实体世界网络效应”加入项目筛选表。
  • 对 Neta 意味着什么、下一步怎么用 Neta 做判断时不能把“名校/大厂/论文”直接等同于原创能力,因为这篇文章最有用的提醒就是履历强不等于方向强;下一步可以把候选人和项目按“执行型卓越/原创型卓越”做双轴拆分。
  • 对 Uota 意味着什么、下一步怎么用 Uota 如果关注产品机会,应特别警惕“被基础模型顺手吃掉”的中间层产品,因为这类产品最容易看起来性感、实际上最脆;下一步可以用三问过滤:模型升级后还剩什么、平台为什么不做、护城河到底在哪。
  • 对三者都意味着什么、下一步怎么用 这篇文章最大的用法不是接受作者结论,而是接受他的反向筛选框架:主流共识里被高估的地方往往在软件叙事和公开估值,真正被低估的地方可能在硬件系统和非典型创始人;下一步讨论时应把“哪里是叙事资产,哪里是经营资产”分开看。

讨论引子

1. 中国 AI 真正长期可守的优势,到底是模型、应用,还是“硬件+供应链+执行”的复合系统? 2. VC 过度偏好标准履历,究竟是在错过 alpha,还是在理性规避“异类创始人”的高失败率? 3. 今天大量 AI 应用公司,哪些是在做独立产品,哪些其实只是等着被基础模型免费吞掉的过渡层?

在中国待了两周,见了 AI 生态里的创业者、VC、以及上市公司 CEO。出发时对这个生态很看多,原本以为会看到世界级的 AI 人才用远低于西方的估值在做事。

离开时视角更细了。对硬件的看多超出预期,对软件更看空,也对中国创业者形成了一些出乎意料的判断。

创始人这个问题

我投资过的优秀创始人身上都有一套很像的指纹。独立思考、叛逆、强烈的能量、近乎偏执的专注。他们不会照着别人说的去做。他们不停追问为什么,拒绝借来的答案。他们做的决定,在外人看来匪夷所思,对他们自己却再自然不过。那种直接、毫不松懈的强度,往往会体现在一段长期的执迷与卓越记录里。他们的人生轨迹有一种尖峰感,在 VC 能见到的那片聪明人海里一眼就能分辨出来。

我见到的很多中国创始人却是另一种原型,这让我意外。

他们非常优秀。顶尖高校出身,在字节跳动或大疆工作过,发过 Nature 论文,手里有多项专利。在西方只有最顶尖技术人才才常见的成就,在这里几乎成了基本盘。工作也比我遇到的绝大多数人更拼。我们在各种时间、周末、跨城市开会。有位创始人甚至在妻子生产当天还来见我们!

但独立思考、叛逆气质、从零到一的愿景,更难遇到。创始人背景很像,路演更偏稳健,想法更多是对既有事物的漂亮 V2,而不是押注真正原创的方向。以中国技术人才的产量,我原本以为会遇到更多能讲出我从未听过的新点子的人。

我的判断是,中国教育体系能产出卓越,却很少给偏离主线留空间。它更容易培养出把已知问题执行到极致的创始人,而不是那种带着一个大家都没意识到的新问题突然出现的人。

VC 正在强化这种模式

更有意思的是,本地投资人正在主动把它越滚越大。

很多中国基金几乎把全部投资主张都建立在押注字节跳动或大疆出身的顶尖人才上。更看门第,不太在意棱角;更看资历,不太看信念。VC 自己的背景也很类似,多来自大厂,或咨询、投行这些路径,像十年前的欧洲 VC。

讽刺的是,历史上那些真正做出代际公司的中国顶级创始人,很多从来没在大公司待过。马云是英语老师,高考两次没考上。任正非离开军队后在 43 岁创办华为。刘强东从集市摊位卖货起步,做出了京东。王兴读博中途退学,从第一天起就一直在创业。最近的例子是梁文锋,他做出 DeepSeek 之前也没在别处工作过,只在自己的公司体系里做事。这些人都是离群者,是那种不那么被履历加持的类型,恰好是当下体系最容易略过的画像。

在这些人里找到真正的 alpha,回报很实在。只是现在看起来,几乎没人往那边找。

深圳与硬件生态

在中国看到的最震撼的东西,并不是某个创业项目的路演。

而是深圳的硬件地下世界。有些工坊里,工程师系统性地买来西方高端产品,一件件拆到元器件级别,用很方法论的精确度做逆向工程。离开时甚至不确定,西方多数硬件创始人到底明不明白自己在和什么竞争。这里的网络效应不是概念,它是实体的、密集的,而且是几十年积累出来的。

我们见到的创业者还用数据强调这一点。硬件输入里,超过 70% 来自大湾区,接近 100% 来自中国本土,这让迭代周期快到西方硬件公司根本匹敌不了。

我见到的大多数创始人都在用大疆那套打法。在一个细分领域做消费硬件,比如电动轮椅、割草机器人、下一代健身设备,把营收到 8 位数或 9 位数,然后利用用户基础或底层技术向相邻品类扩张。有些公司已经远比想象中大。我遇到的最令人印象深刻的公司是 Bambu,一家多数西方人没听过的 3D 打印公司。据说它年利润 5 亿美元,而且每年翻倍。

对中国软件更看空

离开时,对中国软件机会的怀疑比来之前更重。

在模型层面,中国开源做得确实出色。但闭源模型仍明显落后于西方最强者,而且差距大概率会继续拉开。CapEx 差距巨大。GPU 获取仍然受限。西方实验室也越来越倾向于打击蒸馏。营收数字把故事讲得很清楚。据报道 Anthropic 光是 2 月就做了 60 亿美元。中国最好的模型,ARR 也只是几千万美元量级。

在软件创业公司这边,最常见的画像是字节跳动出身的产品经理和研究员,做面向西方市场的 agentic 或 ambient 消费软件。人才没问题,但很多产品正好落在大实验室原生会出的范围里,距离被一次版本更新淘汰只差一步。更让我意外的是,放眼更广的软件领域,几乎看不到体量大、增长快的私营软件公司。在西方,除了模型公司,还有不少创业公司在以惊人的增速把 ARR 做到 9 位数甚至 10 位数,比如 Cursor、Loveable、ElevenLabs、Harvey、Glean。中国基本没有这一档爆发的私营软件公司。少数例外,例如 HeyGen、Manus、GenSpark,一旦真的做起来,最后也都选择离开了。

估值泡沫

尽管软件这条线不太乐观,泡沫依然真实存在,早期和后期都一样。

早期方面,尽管从字节跳动、DeepSeek、Moonshot 走出来的最顶尖人才,整体上仍明显比同级别的美国人才便宜,但中位数估值已经收敛。产品还没做出来的消费类创业公司,估值 1 亿到 2 亿美元很常见。Pre-seed 轮超过 3000 万美元也不稀奇。

后期的数字就更难自圆其说。Minimax 在公开市场的估值大约 400 亿美元,但 ARR 不到 1 亿美元,大约是 400 倍收入。智谱大约 250 亿美元,对应 5000 万美元收入。作为对照,OpenAI 估值最高的几轮融资大约是 66 倍 ARR,Anthropic 约 61 倍。

Moonshot 这样的私营模型公司,正在用这些公开市场可比标杆,在短短几个月内以 60 亿、100 亿、180 亿美元的估值融资。做过加密的人会很熟悉这种机制。投资人把私募估值拿去对标一个解禁前的公开市场价格。再者,智谱和 Minimax 之所以能维持在这种水平,也有一个原因,目前它们几乎是押注中国 AI 叙事的唯一公开敞口,因此自带溢价。随着更多公司上市,这种溢价会被稀释。最后,IPO 窗口常常说关就关,没有预警。对标的那个公开标价一旦先动了,就不一定来得及在套利完成前把价差吃到。

人形机器人赛道也处在类似的位置。中国大约有 200 家人形机器人公司,约 20 家融资超过 1 亿美元,几家估值到十亿美元级别。几乎都还没收入,多数计划在 2026 或 2027 年在香港 IPO。若这个市场真成立,中国的硬件优势让长期结果更容易看清。但商业化牵引很可能比当前融资节奏暗示的要慢,而且很难相信香港市场能承接管线里这么多估值数十亿美元的人形机器人公司。暂时不参与。

值得关注的不对称

还有一件没想到,几乎每位我见到的创始人,都是先做全球市场,再做中国市场。他们用 Claude Code,看 Dwarkesh,对旧金山的创业生态非常熟,很多时候比那些没怎么跟进的西方投资人还熟。

西方对中国的敌意,明显大于中国对西方的敌意。中国创业者并不觉得把中国的工程执行力和硬件纵深,与西方的市场进入和产品愿景结合在一起有什么矛盾。这样的组合如果在合适的创始团队里成形,会诞生一些真正了不起的公司。

我们关注的就是去找到这些创始人,那些不符合本地 VC 生态所偏好的标准履历模子的创始人。

特别谢 to @woutergort 把他惊人的中国人脉向我们开放,感谢 @PonderingDurian 组织这次行程,也感谢 Claude 耐心编辑我在飞机上的胡言乱语

链接 http://x.com/i/article/2036753780692135936

Spent two weeks in China meeting founders, VCs, and public company CEOs across the AI ecosystem. Went in bullish on the ecosystem, expecting to find world-class AI talent building at a fraction of Western valuations.

I left with a more nuanced perspective: more bullish on hardware than I expected, more bearish on software, and with some views on Chinese founders that surprised me.

The Founder Question

The great founders I've backed share a recognizable fingerprint: independent thinking, rebelliousness, intensity, obsessiveness. They don't do as they're told. They ask "why" constantly and refuse borrowed wisdom. They make decisions that look baffling to outsiders but obvious to themselves. And they have a visceral, relentless intensity that tends to manifest in a history of obsession and excellence. Their lives have a spikiness to them that stands out immediately from the sea of highly intelligent people you meet as a VC.

Many of the Chinese founders I met were a different archetype — and it surprised me.

They're extraordinarily talented — top universities, stints at Bytedance or DJI, Nature publications, multiple patents. The achievements that only the very top echelon of Western technical talent has, here they're table stakes. They're also harder working than almost anyone I've encountered. We had meetings at all hours, on weekends, across cities. One founder came to meet us the day his wife gave birth!

But the independent thinking, the rebelliousness, the zero-to-one vision — it's harder to find. The backgrounds are similar across founders, the pitches more risk-averse, the ideas more often impressive V2s of things that already exist rather than genuinely original bets. Given the sheer volume of technical talent China produces, I expected to meet more people with ideas I'd never heard before.

My read is that China's educational system produces excellence but doesn't leave enough space for deviation. The output is founders who are exceptional executors of known problems, rather than the kind of people who show up with a problem nobody knew existed.

VCs Are Reinforcing the Pattern

What makes this more interesting is that local investors are actively compounding it.

Most Chinese funds have built their entire theses around backing the best alumni from Bytedance or DJI — pedigree over spikiness, credential over conviction. The VC profiles mirror this: most come from big company or consulting and banking backgrounds, similar to European VC a decade ago.

The irony is that historically the best Chinese founders — the ones who actually built generational companies — never worked at big companies at all. Jack Ma was an English teacher who failed his university entrance exam twice. Ren Zhengfei founded Huawei at 43 after leaving the military. Richard Liu started JD.com selling goods from a market stall. Wang Xing dropped out of a PhD and started founding companies from day one. Most recently, Liang Wenfeng built DeepSeek having never worked anywhere but his own firms. These were the outliers, the uncredentialed ones — exactly the profiles the current system would pass on.

There is real alpha in finding those profiles, and it seems to me very few are looking there right now.

Shenzhen and the hardware ecosystem

The most mind-blowing thing I saw in China wasn't a startup pitch.

It was Shenzhen's hardware underground — workshops where engineers had systematically acquired high-end Western products and were tearing them apart component by component, reverse engineering everything with methodical precision. I left genuinely uncertain whether most Western hardware founders understand what they're competing with. The network effects here are not theoretical. They are physical, dense, and decades in the making.

Entrepreneurs we met reinforced this point with data: more than 70% of hardware inputs sourced from the Greater Bay Area, close to 100% from China itself — enabling iteration cycles that Western hardware companies simply can't match.

Most founders I met were using the DJI playbook: build consumer hardware in a niche — electric wheelchairs, lawnmower robots, next-gen exercise equipment — scale it to eight or nine figures of revenue, then expand into adjacent categories leveraging either the customer base or the underlying tech. Some of these businesses are already far larger than you'd expect. The most impressive company I came across was Bambu, a 3D printing company most Westerners haven't heard of, allegedly doing $500M in annual profit and doubling every year.

Bearish on Chinese Software

I left more skeptical of the Chinese software opportunity than I arrived.

At the model layer, Chinese open source is genuinely impressive — but the closed models remain significantly behind the best Western ones, and the gap is likely to widen. The CapEx delta is enormous. GPU access remains constrained. Western labs are increasingly moving to crack down on distillation. And the revenue numbers tell the story clearly: Anthropic reportedly did $6B in February alone. The best Chinese models are in the tens of millions of ARR.

On the software startup side, the dominant profile is ex-Bytedance PMs and researchers building versions of agentic or ambient consumer software targeting Western markets. The talent is real, but many of these products sit squarely in the remit of what the large labs will ship natively — one release away from being made redundant. I was also struck by the absence of large, fast-growing private software companies more broadly. In the West, alongside the model companies, there are multiple startups already printing nine and ten-figure ARRs at extraordinary growth rates — Cursor, Loveable, ElevenLabs, Harvey, Glean. That tier of breakout private software company largely doesn't exist in China — and the few exceptions, like HeyGen, Manus, and GenSpark, ended up leaving once they did find it.

The Valuation Bubble

Despite the software picture, the froth is real — at both early and late stages.

At the early stage, while the very top talent coming out of Bytedance, DeepSeek, and Moonshot is still meaningfully cheaper than equivalent US talent, median valuations have converged. Pre-product consumer startups at $100-200M are common. Pre-seed rounds above $30M are unremarkable.

At the late stage, the numbers are harder to defend. Minimax is trading on public markets at roughly $40B on under $100M ARR — around 400x revenue. Zhipu at approximately $25B on $50M revenue. For context, OpenAI's peak fundraising rounds were priced at roughly 66x ARR. Anthropic's at roughly 61x.

Private model companies like Moonshot are using these public comps to raise at $6B, $10B, and $18B in the span of a few months. Crypto investors will recognise the dynamic. Investors are comparing private valuations against a pre-unlocks public mark. In addition, part of what's holding Zhipu and Minimax at these levels is that they're currently the only way to get exposure to the Chinese AI narrative, which commands its own premium. That changes as more companies come to market and dilute it. Finally, IPO windows have a habit of closing quickly and without warning — there's no certainty you'll be able to close the arb before the mark you're comparing against has already moved.

The humanoid space is in a similar place. Roughly 200 humanoid companies in China, around 20 having raised more than $100M, several in the billions — nearly all pre-revenue, most planning HK IPOs in 2026 or 2027. If this market is real, Chinese hardware dominance makes the long-run outcome fairly legible. But commercial traction is likely to take longer than the current fundraising cadence implies, and I'm skeptical HK markets can sustain the number of multi-billion dollar humanoid companies currently in the pipeline. I'm staying out for now.

The Asymmetry Worth Paying Attention To

One thing I didn't expect: almost every founder I met is building for the global market before the Chinese one. They use Claude Code. They watch Dwarkesh. They know the SF startup landscape in detail, often better than Western investors who haven't been paying close attention.

The West is considerably more hostile toward China than China is toward the West. Chinese founders see no contradiction in combining Chinese engineering execution and hardware depth with Western go-to-market and product vision. That combination, when it comes together in the right founding team, will produce some genuinely remarkable companies.

Finding those founders — the ones who don't fit the credentialed mold the local VC ecosystem has optimised for — is what we’re focused on.

Special thank you to @woutergort for extending his amazing China network to us, to @PonderingDurian for organising the trip, and to Claude for patiently editing my plane ramblings

在中国待了两周,见了 AI 生态里的创业者、VC、以及上市公司 CEO。出发时对这个生态很看多,原本以为会看到世界级的 AI 人才用远低于西方的估值在做事。

离开时视角更细了。对硬件的看多超出预期,对软件更看空,也对中国创业者形成了一些出乎意料的判断。

创始人这个问题

我投资过的优秀创始人身上都有一套很像的指纹。独立思考、叛逆、强烈的能量、近乎偏执的专注。他们不会照着别人说的去做。他们不停追问为什么,拒绝借来的答案。他们做的决定,在外人看来匪夷所思,对他们自己却再自然不过。那种直接、毫不松懈的强度,往往会体现在一段长期的执迷与卓越记录里。他们的人生轨迹有一种尖峰感,在 VC 能见到的那片聪明人海里一眼就能分辨出来。

我见到的很多中国创始人却是另一种原型,这让我意外。

他们非常优秀。顶尖高校出身,在字节跳动或大疆工作过,发过 Nature 论文,手里有多项专利。在西方只有最顶尖技术人才才常见的成就,在这里几乎成了基本盘。工作也比我遇到的绝大多数人更拼。我们在各种时间、周末、跨城市开会。有位创始人甚至在妻子生产当天还来见我们!

但独立思考、叛逆气质、从零到一的愿景,更难遇到。创始人背景很像,路演更偏稳健,想法更多是对既有事物的漂亮 V2,而不是押注真正原创的方向。以中国技术人才的产量,我原本以为会遇到更多能讲出我从未听过的新点子的人。

我的判断是,中国教育体系能产出卓越,却很少给偏离主线留空间。它更容易培养出把已知问题执行到极致的创始人,而不是那种带着一个大家都没意识到的新问题突然出现的人。

VC 正在强化这种模式

更有意思的是,本地投资人正在主动把它越滚越大。

很多中国基金几乎把全部投资主张都建立在押注字节跳动或大疆出身的顶尖人才上。更看门第,不太在意棱角;更看资历,不太看信念。VC 自己的背景也很类似,多来自大厂,或咨询、投行这些路径,像十年前的欧洲 VC。

讽刺的是,历史上那些真正做出代际公司的中国顶级创始人,很多从来没在大公司待过。马云是英语老师,高考两次没考上。任正非离开军队后在 43 岁创办华为。刘强东从集市摊位卖货起步,做出了京东。王兴读博中途退学,从第一天起就一直在创业。最近的例子是梁文锋,他做出 DeepSeek 之前也没在别处工作过,只在自己的公司体系里做事。这些人都是离群者,是那种不那么被履历加持的类型,恰好是当下体系最容易略过的画像。

在这些人里找到真正的 alpha,回报很实在。只是现在看起来,几乎没人往那边找。

深圳与硬件生态

在中国看到的最震撼的东西,并不是某个创业项目的路演。

而是深圳的硬件地下世界。有些工坊里,工程师系统性地买来西方高端产品,一件件拆到元器件级别,用很方法论的精确度做逆向工程。离开时甚至不确定,西方多数硬件创始人到底明不明白自己在和什么竞争。这里的网络效应不是概念,它是实体的、密集的,而且是几十年积累出来的。

我们见到的创业者还用数据强调这一点。硬件输入里,超过 70% 来自大湾区,接近 100% 来自中国本土,这让迭代周期快到西方硬件公司根本匹敌不了。

我见到的大多数创始人都在用大疆那套打法。在一个细分领域做消费硬件,比如电动轮椅、割草机器人、下一代健身设备,把营收到 8 位数或 9 位数,然后利用用户基础或底层技术向相邻品类扩张。有些公司已经远比想象中大。我遇到的最令人印象深刻的公司是 Bambu,一家多数西方人没听过的 3D 打印公司。据说它年利润 5 亿美元,而且每年翻倍。

对中国软件更看空

离开时,对中国软件机会的怀疑比来之前更重。

在模型层面,中国开源做得确实出色。但闭源模型仍明显落后于西方最强者,而且差距大概率会继续拉开。CapEx 差距巨大。GPU 获取仍然受限。西方实验室也越来越倾向于打击蒸馏。营收数字把故事讲得很清楚。据报道 Anthropic 光是 2 月就做了 60 亿美元。中国最好的模型,ARR 也只是几千万美元量级。

在软件创业公司这边,最常见的画像是字节跳动出身的产品经理和研究员,做面向西方市场的 agentic 或 ambient 消费软件。人才没问题,但很多产品正好落在大实验室原生会出的范围里,距离被一次版本更新淘汰只差一步。更让我意外的是,放眼更广的软件领域,几乎看不到体量大、增长快的私营软件公司。在西方,除了模型公司,还有不少创业公司在以惊人的增速把 ARR 做到 9 位数甚至 10 位数,比如 Cursor、Loveable、ElevenLabs、Harvey、Glean。中国基本没有这一档爆发的私营软件公司。少数例外,例如 HeyGen、Manus、GenSpark,一旦真的做起来,最后也都选择离开了。

估值泡沫

尽管软件这条线不太乐观,泡沫依然真实存在,早期和后期都一样。

早期方面,尽管从字节跳动、DeepSeek、Moonshot 走出来的最顶尖人才,整体上仍明显比同级别的美国人才便宜,但中位数估值已经收敛。产品还没做出来的消费类创业公司,估值 1 亿到 2 亿美元很常见。Pre-seed 轮超过 3000 万美元也不稀奇。

后期的数字就更难自圆其说。Minimax 在公开市场的估值大约 400 亿美元,但 ARR 不到 1 亿美元,大约是 400 倍收入。智谱大约 250 亿美元,对应 5000 万美元收入。作为对照,OpenAI 估值最高的几轮融资大约是 66 倍 ARR,Anthropic 约 61 倍。

Moonshot 这样的私营模型公司,正在用这些公开市场可比标杆,在短短几个月内以 60 亿、100 亿、180 亿美元的估值融资。做过加密的人会很熟悉这种机制。投资人把私募估值拿去对标一个解禁前的公开市场价格。再者,智谱和 Minimax 之所以能维持在这种水平,也有一个原因,目前它们几乎是押注中国 AI 叙事的唯一公开敞口,因此自带溢价。随着更多公司上市,这种溢价会被稀释。最后,IPO 窗口常常说关就关,没有预警。对标的那个公开标价一旦先动了,就不一定来得及在套利完成前把价差吃到。

人形机器人赛道也处在类似的位置。中国大约有 200 家人形机器人公司,约 20 家融资超过 1 亿美元,几家估值到十亿美元级别。几乎都还没收入,多数计划在 2026 或 2027 年在香港 IPO。若这个市场真成立,中国的硬件优势让长期结果更容易看清。但商业化牵引很可能比当前融资节奏暗示的要慢,而且很难相信香港市场能承接管线里这么多估值数十亿美元的人形机器人公司。暂时不参与。

值得关注的不对称

还有一件没想到,几乎每位我见到的创始人,都是先做全球市场,再做中国市场。他们用 Claude Code,看 Dwarkesh,对旧金山的创业生态非常熟,很多时候比那些没怎么跟进的西方投资人还熟。

西方对中国的敌意,明显大于中国对西方的敌意。中国创业者并不觉得把中国的工程执行力和硬件纵深,与西方的市场进入和产品愿景结合在一起有什么矛盾。这样的组合如果在合适的创始团队里成形,会诞生一些真正了不起的公司。

我们关注的就是去找到这些创始人,那些不符合本地 VC 生态所偏好的标准履历模子的创始人。

特别谢 to @woutergort 把他惊人的中国人脉向我们开放,感谢 @PonderingDurian 组织这次行程,也感谢 Claude 耐心编辑我在飞机上的胡言乱语

链接 http://x.com/i/article/2036753780692135936

Spent two weeks in China meeting founders, VCs, and public company CEOs across the AI ecosystem. Went in bullish on the ecosystem, expecting to find world-class AI talent building at a fraction of Western valuations.

I left with a more nuanced perspective: more bullish on hardware than I expected, more bearish on software, and with some views on Chinese founders that surprised me.

The Founder Question

The great founders I've backed share a recognizable fingerprint: independent thinking, rebelliousness, intensity, obsessiveness. They don't do as they're told. They ask "why" constantly and refuse borrowed wisdom. They make decisions that look baffling to outsiders but obvious to themselves. And they have a visceral, relentless intensity that tends to manifest in a history of obsession and excellence. Their lives have a spikiness to them that stands out immediately from the sea of highly intelligent people you meet as a VC.

Many of the Chinese founders I met were a different archetype — and it surprised me.

They're extraordinarily talented — top universities, stints at Bytedance or DJI, Nature publications, multiple patents. The achievements that only the very top echelon of Western technical talent has, here they're table stakes. They're also harder working than almost anyone I've encountered. We had meetings at all hours, on weekends, across cities. One founder came to meet us the day his wife gave birth!

But the independent thinking, the rebelliousness, the zero-to-one vision — it's harder to find. The backgrounds are similar across founders, the pitches more risk-averse, the ideas more often impressive V2s of things that already exist rather than genuinely original bets. Given the sheer volume of technical talent China produces, I expected to meet more people with ideas I'd never heard before.

My read is that China's educational system produces excellence but doesn't leave enough space for deviation. The output is founders who are exceptional executors of known problems, rather than the kind of people who show up with a problem nobody knew existed.

VCs Are Reinforcing the Pattern

What makes this more interesting is that local investors are actively compounding it.

Most Chinese funds have built their entire theses around backing the best alumni from Bytedance or DJI — pedigree over spikiness, credential over conviction. The VC profiles mirror this: most come from big company or consulting and banking backgrounds, similar to European VC a decade ago.

The irony is that historically the best Chinese founders — the ones who actually built generational companies — never worked at big companies at all. Jack Ma was an English teacher who failed his university entrance exam twice. Ren Zhengfei founded Huawei at 43 after leaving the military. Richard Liu started JD.com selling goods from a market stall. Wang Xing dropped out of a PhD and started founding companies from day one. Most recently, Liang Wenfeng built DeepSeek having never worked anywhere but his own firms. These were the outliers, the uncredentialed ones — exactly the profiles the current system would pass on.

There is real alpha in finding those profiles, and it seems to me very few are looking there right now.

Shenzhen and the hardware ecosystem

The most mind-blowing thing I saw in China wasn't a startup pitch.

It was Shenzhen's hardware underground — workshops where engineers had systematically acquired high-end Western products and were tearing them apart component by component, reverse engineering everything with methodical precision. I left genuinely uncertain whether most Western hardware founders understand what they're competing with. The network effects here are not theoretical. They are physical, dense, and decades in the making.

Entrepreneurs we met reinforced this point with data: more than 70% of hardware inputs sourced from the Greater Bay Area, close to 100% from China itself — enabling iteration cycles that Western hardware companies simply can't match.

Most founders I met were using the DJI playbook: build consumer hardware in a niche — electric wheelchairs, lawnmower robots, next-gen exercise equipment — scale it to eight or nine figures of revenue, then expand into adjacent categories leveraging either the customer base or the underlying tech. Some of these businesses are already far larger than you'd expect. The most impressive company I came across was Bambu, a 3D printing company most Westerners haven't heard of, allegedly doing $500M in annual profit and doubling every year.

Bearish on Chinese Software

I left more skeptical of the Chinese software opportunity than I arrived.

At the model layer, Chinese open source is genuinely impressive — but the closed models remain significantly behind the best Western ones, and the gap is likely to widen. The CapEx delta is enormous. GPU access remains constrained. Western labs are increasingly moving to crack down on distillation. And the revenue numbers tell the story clearly: Anthropic reportedly did $6B in February alone. The best Chinese models are in the tens of millions of ARR.

On the software startup side, the dominant profile is ex-Bytedance PMs and researchers building versions of agentic or ambient consumer software targeting Western markets. The talent is real, but many of these products sit squarely in the remit of what the large labs will ship natively — one release away from being made redundant. I was also struck by the absence of large, fast-growing private software companies more broadly. In the West, alongside the model companies, there are multiple startups already printing nine and ten-figure ARRs at extraordinary growth rates — Cursor, Loveable, ElevenLabs, Harvey, Glean. That tier of breakout private software company largely doesn't exist in China — and the few exceptions, like HeyGen, Manus, and GenSpark, ended up leaving once they did find it.

The Valuation Bubble

Despite the software picture, the froth is real — at both early and late stages.

At the early stage, while the very top talent coming out of Bytedance, DeepSeek, and Moonshot is still meaningfully cheaper than equivalent US talent, median valuations have converged. Pre-product consumer startups at $100-200M are common. Pre-seed rounds above $30M are unremarkable.

At the late stage, the numbers are harder to defend. Minimax is trading on public markets at roughly $40B on under $100M ARR — around 400x revenue. Zhipu at approximately $25B on $50M revenue. For context, OpenAI's peak fundraising rounds were priced at roughly 66x ARR. Anthropic's at roughly 61x.

Private model companies like Moonshot are using these public comps to raise at $6B, $10B, and $18B in the span of a few months. Crypto investors will recognise the dynamic. Investors are comparing private valuations against a pre-unlocks public mark. In addition, part of what's holding Zhipu and Minimax at these levels is that they're currently the only way to get exposure to the Chinese AI narrative, which commands its own premium. That changes as more companies come to market and dilute it. Finally, IPO windows have a habit of closing quickly and without warning — there's no certainty you'll be able to close the arb before the mark you're comparing against has already moved.

The humanoid space is in a similar place. Roughly 200 humanoid companies in China, around 20 having raised more than $100M, several in the billions — nearly all pre-revenue, most planning HK IPOs in 2026 or 2027. If this market is real, Chinese hardware dominance makes the long-run outcome fairly legible. But commercial traction is likely to take longer than the current fundraising cadence implies, and I'm skeptical HK markets can sustain the number of multi-billion dollar humanoid companies currently in the pipeline. I'm staying out for now.

The Asymmetry Worth Paying Attention To

One thing I didn't expect: almost every founder I met is building for the global market before the Chinese one. They use Claude Code. They watch Dwarkesh. They know the SF startup landscape in detail, often better than Western investors who haven't been paying close attention.

The West is considerably more hostile toward China than China is toward the West. Chinese founders see no contradiction in combining Chinese engineering execution and hardware depth with Western go-to-market and product vision. That combination, when it comes together in the right founding team, will produce some genuinely remarkable companies.

Finding those founders — the ones who don't fit the credentialed mold the local VC ecosystem has optimised for — is what we’re focused on.

Special thank you to @woutergort for extending his amazing China network to us, to @PonderingDurian for organising the trip, and to Claude for patiently editing my plane ramblings

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