AI Sells Labor, Not Software — Legendary Investor Elad Gil

Yeah. And I'm wondering how you orient yourself as an investor to stress test those types of dogma. It's really hard because you often end up... You start out with some set of beliefs. You think something's interesting. Or maybe you invest in it, maybe you start a company in it. And then it turns out the thing you think is really interesting turns out to be really hard and you get killed. And then 5 years later a company comes up that actually does it and wins.

And the question is why? Why did the thing suddenly work when it didn't before? Or there's 10 attempts to do X and then suddenly is it that technology got good enough? It could be a regulatory change. It could be a market shift. It could be whatever. An example be Harvey AI Legal where selling to law firms traditionally has been awful. And Harvey's not much broader than that, right? They also have very strong enterprise adoption and lots of different people using them in different ways, but the dogma was always like building stuff for law firms is crappy as a business and you should never do it. But what AI did is it shifted things from selling tools to selling work product or selling units of labor. That's really the shift in generative AI. We're going from seats and we're going from software and SaaS and we're moving into a world where we're selling human labor equivalents. We're selling work hours or labor hours or whatever you want to call it.

of cognition. And so, Harvey is effectively helping really augment lawyers in different ways. And part of that's a knowledge corpus, but a lot of it is this tooling that really helps lawyers achieve the goals that they have in different ways in a collaborative manner in some cases. And so, this is a fundamentally different type of product from what people were selling before. And so, it opened up the market in a way that the market wasn't open before. There's actually a broader conversation around is the world market limited or founder limited in terms of entrepreneurial success. The Y Combinator school of thought is that we just don't have enough founders, and if we had 10 times as many founders, we'd have 10 times as many big companies. And there's an alternate school of thought, which is how many markets are actually open in any given moment in time, and those are the ones where you can build big companies. Cuz if the market isn't open to innovation or change or whatever or hasn't is undergoing a shift, you can't really build anything or anyhow, so why do it? And the striking thing about AI is it's opened up tons and tons of markets that were closed for a long time. And it's opened it up because of capabilities, but it's also opened it up because every CEO is asking themselves, 'What's my AI story?' And there's way more openness to try things than I've ever seen in my life. And so, we have this odd moment in time where things are massively available for founders to do new things. And if you're an AI company and you're not seeing explosive growth quickly, something's fundamentally broken. Because the markets are so open that you can suddenly grow at a rate that you've never grown before. There's always been cases of companies that just go like this. But again, you look at the ramps of OpenAI and Anthropic, and it's the fastest ramps to tens of billions ever. Percentages of GDP, it's like crazy.

I mean, there's a few different ways to think about it. One is like, some people take the framework of why now. What's shifted now that makes it something interesting market because people have been trying to do things for a long time in every market. And so, that may be a regulatory shift, right? Some Samsara, the fleet management company benefited from the fact that somebody was regulation around needing in-cab monitoring of drivers. So, you had some of the cameras watching people so they don't fall asleep while they're driving trucks on the road, right? And so, that was their entry point to that start building out a suite of software. But, it was a regulatory shift. Sometimes there's technology shifts, like what's happening in AI. And the crazy thing about the AI shift is the foundation models instantly plugged into a massive set of markets, which is basically all enterprise data and information and email and just all white collar work was suddenly available to AI. Cuz it was the perfect market for that. It also plugged into code, which is a type of white collar work. So, it's just suddenly it just inserts into language and language is used everywhere in in enterprises as well as in consumer. And so, there's just a massive market to tap into and transform or set of markets. Robotics is a little bit different from that because even if you had the world's best robotic model, the submarkets that already have robotic hardware are quite small on a relative basis. And so, you don't have that instant runway that you would with language unless you come up with something new there. That's kind of an aside that I think robotics is really interesting and be important. It's more just that nuance of like what's that instant thing you plug into commercially. And then, there's regulatory shifts and technology shifts, there's incumbency or company shifts, competitive shifts. A company may blow itself up, it may get bought by a competitor. One company I'm I'm excited about on the security side is called In-Q-Tel and they're basically competing in part with Hashi. Hashi got bought by IBM. Anytime you get bought by IBM, you slow you slow down a lot usually. Suddenly it creates more opportunity for a startup. So, I I feel like there are these different things that can change at a given moment in time.