Chi-Hua Chien has spent more than two decades as an entrepreneur, but he thinks like a cultural anthropologist. As co-founder of Goodwater Capital, a firm focused exclusively on consumer and supplier technology, he has built a portfolio spanning entertainment, healthcare, fintech and live experiences — with investments in companies such as MIDI Health, Fever and Monzo. He was also, as a 27-year-old partner at Accel, the person who originally founded a six-person Harvard startup called The Facebook.
This ability to read human behavior at scale informs everything from his view that Americans will never trust an app for both their social lives and their finances to his belief that the gap between the most advanced AI model and what you can run on your phone — once as much as two years — will shrink to three months within the next year.
These days, he’s also willing to say out loud what only many in venture capital think: that model-level commercialization is already underway, and that the biggest winners of the AI era won’t be the companies that sell AI at all.
We talked last week. This interview has been edited for length and clarity.
Recently, more founders and investors are publicly sharing their grievances about VCs. What changed?
It’s part of the mimicry of everything — you see what’s happening in the political realm bleeding into the business side, and it’s probably also the sign of some market tipping. The reason you see some of these outspoken investors speaking out more publicly is because venture firms are largely verticalized, so the really big ones have enough capital that they’re not necessarily looking for partners. There used to be decorum around wanting to maintain good relations with other co-investors because you had to work with them at different points down the line. As companies have become larger and more vertically integrated, this need is diminishing.
What about “fast track” rounds – where companies invest a large chunk at one valuation and a smaller amount weeks later at a much higher one, making the headline number look more impressive than it really is? Is this really new? How widespread is it?
I think it’s been going on for quite some time. The best companies raise rounds very quickly — there can only be three to six months between rounds now, and valuations change very quickly… Valuations are advertised very aggressively as a way to demonstrate market leadership, attract talent, potentially foreclose competition. There is probably some element of froth, because what is most indicative of these quick financings is that there is far more demand than supply. An investor can come in, set a price, complete a financing, and then a few weeks later, there’s still excess demand—and the company can immediately price a new round at a higher price.
You’ve argued that infrastructure companies are commoditized and that applications enjoy most of the value over time. Are we already seeing this play out this cycle?
If you look at the desktop cycle, the web cycle and the mobile cycle, they all follow pretty consistent patterns. The infrastructure market caps actually peaked in the year 2000 — but fast forward 25, 26 years later, and in nominal dollar terms, the market cap of these infrastructure companies hasn’t surpassed the 2000 peak. In the internet age, infrastructure entrants generated $400 billion in new capitalization. App companies generated $3.1 trillion — 88% of new value. In the mobile era, it’s very similar: infrastructure generated about $700 billion, while app companies generated $3.7 trillion. Companies like Netflix, Spotify, Meta, Uber, Airbnb.
And [last week] you saw something very interesting: Google announced that its AI subscription product is dropping the price from $7.99 per month to $4.99 per month and doubling the storage. We’re already in the age of price competition — and companies like Google, with structural advantages in vertical integration and distribution, can begin bundling and price competition for the average consumer.
You keep coming back to personalization as a middle line. Is this what separates the next wave of winners?
Hyper-personalization is definitely key, because what does personalization get you? Done right, it gives you greater customer satisfaction, deeper loyalty and higher ARPUs over time.
We have entertainment companies in our portfolio—companies like Triumph and Ritten and Flow GPT—where the customer doesn’t say, “This is an AI application.” They say it’s an entertainment app. These companies are investing in $100 million, $400 million, $600 million ARR very quickly, with large margins, because AI makes the experience more customizable and more personalized — but it’s not the fundamental capability they’re selling.
We also have a women’s health company called Midi Health. One of the fundamental limitations in women’s health is that there are not as many providers well trained in hormone replacement therapy for perimenopausal women. Using artificial intelligence, they are able to substantially expand the delivery of care and treat hundreds of thousands of patients who would otherwise be unreachable. And they can do it affordably, which expands access to a previously supply-constrained market. You can play this forward in any limited supply category where human expertise is the bottleneck.
How far are we from AI that feels truly personal and atmospheric?
I don’t think we’re too far off. You can run AI models locally now on your phone that are just as good as the best models from about six months ago — and that lag is shrinking. You go back two years ago, the lag between what you could run on-premises and what was in the cloud with the frontier models might have been 18 to 24 months. It’s now six months. It will likely drop to three months this time next year.
What we don’t have yet are the use cases very well defined. You saw this on mobile — when the iPhone came out in 2007, people largely believed that it was going to be all web apps going mobile. It takes time for entrepreneurs to see around what is now possible.
What [LLMs do]if you extrapolate from how they work to what they do, it’s basically two things: They allow you to process large volumes of context and make sense of it all, and they allow you to personalize to the individual, affordably, with a feedback loop that makes the product better and better over time.
You watch Facebook try and fail for years to create a super app. Why is it so difficult to combine financial services and social entertainment for American consumers?
They’ve taken a lot of shots — Facebook Credits, launched in 2009… Facebook Pay, Libra… They’ve never managed to pull off a true super app. I think people have an intuitive perspective on trust, and there’s a trust gap between entertainment and social products, and commerce, banking, financial services — particularly in the Western world.
There is a seriousness to financial transactions that is very different from the frivolity of social media. And don’t get me wrong – this frivolity has created a trillion dollar company. But financial services is actually the complete opposite: while the public has very high time and relatively low monetization, financial services transactions have very high monetization and relatively low time. You don’t want to hang out in your banking app. You want to transact and be done — but with extremely high confidence in the security and reliability of that transaction. This psychological expectation from customers is very difficult to bridge.
Are you betting on people longing to connect in person as a reaction to all of this?
We really, really believe in it. What do people crave in a world where there is an infinite supply of digital content? They crave what is more limited, which is real human contact, real world experiences.
We have an investment in a company called Bump, based in Paris — from the original founders of Zenly, which was acquired by Snap… They’ve created an interface that allows people to interact in the physical world, catalyzed by digital information. We also have Fever, based in London and Madrid — effectively the Live Nation of Europe. They started with smaller, quirky events—candlelight concerts, the Bridgerton Experience—and have since gone mainstream.
I think we’re moving in the opposite direction from pure online consumption, and AI as an enabling technology, knowing where you go, who you hang out with, where you tend to spend time, can extrapolate a ton of relevant interests that make that real-world experience more useful and more personal. This is very exciting for us.
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