[Highlight] Eric Yuan & Reid Hoffman on Startups vs. Big Tech in the AI Era

0:00Where do startups and large companies kind of have, and I think AI changes the landscape a little bit, but the principle is still the same which is in the things that large companies are the big, you know, they're big. search idea, like I'm just going to do desktop search. Now that's different than chat, GPT and so forth. But desktop search, and I'm going to go after that. That's not a good idea. Because it's like, okay, Google and then even Bing and all the rest. Now being said, all these large companies have lots of efforts. And so you go, well, but wait a minute. Google is doing this over here or Amazon is doing this over here or whatever.

0:48You go, actually, in fact, If it's not in the core set and it doesn't leverage the key assets that the large company has, it is broadly potentially available to startups because startups can take risks, do go to market, move faster, be much more focused, you know, because there's a bunch of things that the large companies will simply not take risks about that's outside the core three, five things that they're doing. You know, maybe one is a top line. And so you can view all that stuff. And so it kind of comes to a score of, you know, do I actually have a really bold idea? Is there a really smart risk?

1:26Do I have a go-to-market? Do I have a distribution possibility? Usually distributions, one of the hardest things to get to. And so I think there's a broad range. And part of what to build on Eric's comment on, look, with AI, you can make a whole bunch of new things. You might see something that other people don't see. You might see, have a speed and a risk of like, I'll build it and I'll deploy it and I'll see what happens. Like just building and deploy it doesn't happen in the large companies. It can happen in startups, right? And kind of see kind of what's going on. And so that's the kind of thing that I think is a very broad surface.

2:01And part of the thing that I love about being a tech investor is the things that I hadn't thought about that someone shows up and goes, oh, my God, that's amazing. There's like the Airbnbs. It's like, oh, whoa, that's a great idea. And Reed, you were doing startups for so many years, building startups, investing in startups. Now that you spent the last few years on the Microsoft board, I guess, has that given you a new appreciation of the power of big platforms like Microsoft? Or are you newly energized by the opportunities for startups in a world where big tech is so dominant? or how has that changed your mind at all in terms of the surface area for startups now that you have such an intimate view of Microsoft?

2:42Well, the short answer is both. And so, you know, part of it is this question of, you know, Microsoft has a bunch of assets that make it a very challenging competitor in certain arenas, you know, large scale enterprise, you know, kind of, you know, productivity software, a bunch of that kind of stuff, you know, like has a bunch of things and makes it hard for a startup to do. On the other hand, like even take some of the things that where you'd say Microsoft is a natural advantage, like coding, you know, with not just GitHub, but Visual Studio and a bunch of other things. And it's, you know, coding, you know, the Microsoft basic and tools goes all the way back to the very beginnings of the Microsoft concept of being a software factory.

3:32And you look at it, you go, okay, cursor. Okay, Claude Code. Okay. And so the range of availability for doing compelling stuff with startups is actually, in fact, much broader than most people think. It doesn't mean that there aren't really central things like what's happening with ChatGPT and the OpenAI Microsoft work and what's happening with Copilot. And Microsoft's putting a lot of energy into how does this upgrade the core things that Microsoft's there with like Microsoft Office and Active Directory and other kinds of participation in it. And so that's challenging for a startup. But on the other hand, there's a huge range, much broader than most people think for a startup.

4:19So that's the reason why the answer is both. Yeah, Eric, do you want to, I'm going to switch topics, but anything you want to comment on there? No, I'm really right on. I totally agree. So, you know, even for our company size, 7 ,500 employees is very slow. I think startup, you know, you leverage the AI tools with 20 people. You can build a lot of things so fast. You can disrupt anyone you want now with AI tools. Yeah, indeed. And that's why it's such an exciting time to be an entrepreneur. and we're thrilled to back so many of them with your guys' support. Reid, you've been thinking about AI for a long time.

4:55Both of you have, but Reid, let me start with you. You've seen different hype cycles. You helped get OpenAI started before people really cared about OpenAI. What have you changed your mind about in the last six to 12 months, given that broad context and all the things you've seen and your moments of excitement, moments of doubt? And it could be a small tactical thing or a bigger picture thing around anything related to AI? Well, it'll be a little bit of a two-faced thing. So look, one of the things that I still believe generally, so it's did believe and do believe, and then I'll put the change of belief in the frame of that, which is the way that adoption will happen is kind of in this kind of stuff, generally technology is slow than fast.

5:37And it's slow because people are slow to adopt new things, especially in work and all that. And then fast when they're operating on a competitive clock, they're like, oh shit. You're like, I'm going to be beaten out by company X or person Y or something else and kind of undo that. And so that's how I've generally been thinking about AI adoption. What I think, though, is still interesting is the AI adoption has been slower than I've anticipated in various ways. Like when you go and ask people about like what do they do for AI in their own personal life, very few of them or work life are as advanced as just Eric is.

6:15Like, think about, like, just about every public company could do what Eric did with earnings announcement. And I don't know if there's another one other than Eric. I mean, it's a great question. I actually want to take that as a to-do. Do we know, Eric, are you like the first public company CEO in history to do what you just did yesterday? Yes. First of all, as a public company. I know there's another friend as a private company. Yeah. Yeah. That's awesome. So, that's fantastic. Congratulations. And so it takes a, like at the moment, very forward individuals and it's simply all there, but people aren't doing it.

6:48And so it's one of the reasons why, like in multiple ways, I'm always trying to drive my own AI use for myself and for my team to be more, you know, advantaged and like companies on the board of and else, because it's like, look, the tools are not perfect at doing everything. Like you can't say, oh, go invest for me. It doesn't work that way. But like, like in everything I'm doing, I'm thinking, hey, how do I get really amplified by doing this? And I do like multiple, you know, AI things for work for my own work every day. And so that's, I think, been slower. There's a bit of a slower adoption curve from the masses than maybe you anticipated, given how powerful these tools are.

7:36That's exactly right. And I don't think it'll be slower forever. I just thought it would have kicked off more strongly already. And Eric, have you seen that within either enterprise users of Zoom or consumer? What's been the adoption rate of your AI feature set? Has anything surprised you there? I think, first of all, I completely agree with Reid. But on the other hand, also say, you know, for any new technology, right, from Internet or mobile or AI, I think the consumer adoption is always the first one, always faster than enterprise. I still remember early days, I carry my both iPhone and BlackBerry for two and a half years.

8:14And finally, I dropped my BlackBerry and only use iPhone. I think today most of consumers, they benefit a lot from using chat GBT. But also we have a lot of AI features, a lot of companies announce a lot of AI innovation features. But enterprise adoption rate always is slow. You know, I think at least two or three years behind a consumer adoption. The reason why, because you take a Zoom AI feature, for example, when you're working together with our enterprise customers, legal team, security team, data retention policy, compliance, a lot of things you needed to make sure they feel comfortable. They take some time.

8:50But however, I feel like in between, between consumer and enterprise, there's a sweet spot, which is developers. They are part of enterprise, but they're not a part of enterprise. And I think of building something to do to target developers, is always, I think probably right away, if you feel like very slow. Otherwise, no matter how good your technology is, Whenever there's a new technology paradigm shift, it's always slow for enterprise to embrace. Yeah, that's a great point on developers being early adopters. Eric, when you talk to CEOs of companies every day who are Enterprise Zoom customers, we have a lot of founders on this call who are selling AI products to enterprise.

9:36What have you learned or what advice would you give to a startup CEO when talking to a company and pitching some AI application? What have you learned these last few years selling your AI feature set into your enterprise customer base? I think if you want to target any of the customers, make sure, right? And be patient. That's one. The two is even if, let's say you start ahead of any other competitors, you've got to think about, hey, what if other competitors catch up? So what you can do to make sure, even if the enterprise customers, they may not deploy your solution fully, but think about how to make sure the enterprise customers are part of your innovation cycle.

10:18Meaning they can help you generate more data. The data also very unique for you, right? And also the data they are not going to give to any other competitors. So down the road, when they fully embrace your solution, competitors, they cannot catch up because you ought to have a bunch of data that's very unique to you. That's extremely important. That's number one. Number two is focus on maybe some vertical market with some domain expertise and knowledge. And also you can live with AI. Any generic big AI companies, they cannot build that. Other competitors want to catch up. They may not have a similar domain knowledge or expertise.

10:55Right? I think those two, or maybe even for enterprise department, don't build a horizontal product. It's very hard. Other competitors or big ones, you know, they can, you know, probably, they can build something and give it for free. Yeah. Maybe engineer or sales any department.