00:01:47 · Nikesh Arora
[00:01:47] S0: Well, first of all, thank you for having me here. Appreciate it. And thank you all for braving the rain and showing up here. I hope this is useful for you. I think in terms of inspiration and in terms of how to bide your time until the right thing hits you, one of the challenges with extremely smart people is they can apply themselves to any problem and put their heart and soul into it and do a great job for it. Many people, I'm guessing everybody in this room believes they're smarter than the average person. That's why you're here. I think everyone. Okay, well, don't forget they're here. Eventually, if everybody believes they're smarter than the average, there's a problem, but that's a different mathematical problem. We'll deal with that later. But if you were to apply yourself to something, and if I said, here are options, three options one, two, and three, you could say, I could do all of them. I can start the world's best restaurant. I can start the world's best airline. I can build the best video model with beating Sora, L and M, etcetera. So the question really becomes is, what can you connect with and how tractable the problem is and how patient are you? I think to your point about patience and patience, you said earlier when we were talking, there are too many companies being started. I think we sometimes get waylaid or trapped by the idea that somebody else is getting traction so quickly. Therefore, I must get traction quickly. And then the risk is then you end up building a feature. You end up building a part solution to the problem. You're not solving the real problem. In our times, can always point to Elon Musk and say, look, he didn't take an easy problem. He said, we're going to go to Mars. Sounds like a hard problem. They said, I'm going build an electric vehicle or go build an autonomous vehicle or Waymo did that. Those are hard problems. They're ten, fifteen, twenty year horizon problems requiring tons of capital. And you almost feel like, holy shit, how am I going to even get started in that direction and solve something that big? That's at one extreme. And the other extreme, you think you can go program something really quickly, and in six months, you'll have a product market fit. In twelve months, you'll have 100,000,000 ARR. So the answer is somewhere in the middle.
00:03:51 · Nikesh Arora, Aditya Agarwal
I'm not sure that there's a moat for a company that built 100,000,000 ARR in the first seventeen months or twenty months. Maybe that moat may exist, may not exist, may get obliterated by the next person. Or maybe it becomes a competitive advantage because you got out first and you captured all the market and that became... You became the winner in that space. [00:04:12] S1: You know, it's interesting, Nikesh. If I look at, for instance, when you when you joined Google, it must have been 30,000,000,000 in market cap? [00:04:20] S0: 18, but it was counting. [00:04:21] S1: 18 was... Exactly. So it's kind of... You know, it's obviously close to what? $3.54000000000000 today, something like that. And then when you joined Palo Alto Networks? [00:04:32] S0: Coincidentally, '18. [00:04:33] S1: '18. Coincidentally, On its way to the big one. So in some ways, when you joined them, they were kind of like a fraction of the size that they were, but they had some scale. So were you joining them for what they already had? Were you joining them for, in some ways, the latent potential energy, some combination? And what was your version of patience and impatience as you got to those? Maybe Palo Alto Networks, I think you've talked a little bit about this. You kind of came in as not knowing a ton about cybersecurity. What did you see kind of before you joined?
00:05:08 · Nikesh Arora
[00:05:08] S0: Well, I think Google, I joined because I needed a job. And it turned out to be an amazing company and has gone to $4,000,000,000,000 in market cap or thereabouts. And so there was no more genius. In hindsight, I can justify it. I can tell you all the great things. But at that point in time, I need to get out there, get myself a real job, and that was a great job I got and it was amazing. I think it had a market opportunity bigger than most. At that point in time, digital advertising was 2% of advertising. Today, 60% to 70% of all advertising. So you could see that there's going to be huge opportunity. You could see consumption. You could think about commerce, etcetera. And I think we're at the beginning of a similar trend with AI. I think for the next fifteen years, every industry will get transformed with AI. So whatever you're thinking of is not big enough. Whatever you're thinking of is too small and too specific. There's tons and tons of opportunity. I think that's the parallel you can draw. I think it just had tremendous amount of tailwinds. And then I think Google's secret sauce is they were able to execute in multiple dimensions across the board. In Palo Alto, similarly, when I started, we were 1% market share in our sector. And generally, it's 1% market share in this sector. And the sector is going grow at 10% a year for the next foreseeable future. Then you have the opportunity of getting from 1% to something bigger. And if you do the math of enterprise, for those of you who are interested in enterprise companies, the math of enterprise generally tells you that if you get critical mass, get escape velocity. You get to be big enough, then you get a field force that is big enough that allows you to have a larger and larger share of wallet of a customer. So we earn from 1% approximately 6% or 7% now. And there's no reason why we shouldn't be 20%, 30% market share in our segment. And if that's true, that makes us a much larger business.
00:06:53 · Aditya Agarwal
[00:06:53] S1: Perhaps to come back to to Google for a second before we inevitably turn to AI and cybersecurity, it's interesting. I I always believe that the best antidote for any kind of organizational problem is winning. If you're winning, it kind of solves and kind of papers over all cracks. And it's often hard to know what an organization is from the outside. And most of the external narratives, they're not wrong. It's just kind of very hard to kind of capture the zeitgeist of a company internally. But if you, from your benefit of kind of the amazing run that you had there, what are some non obvious, like, non kind of externally talked about reasons why Google continued to be so good for so long. Like, the longevity in terms of innovation is also quite rare. Right? Like, oftentimes, you can build a good thing, you can milk it for a long time, have a good company, but they kept on building good things. And what lessons can you draw from that for entrepreneurs?
00:07:46 · Nikesh Arora
[00:07:46] S0: If you abstract and you think about all the companies you admire and pick your favorite, whether you like Facebook or you worked there, you worked at Waymo, you worked at Google, or you worked at Tesla where you did, most companies take on the form of the leader. Think hard. Company culture, especially where there are dominant founders or prominent founders, a lot of the company's values are closely aligned with the way the founder behaves, the founder thinks. And it's normal because you know what? Everybody in the company is trying to impress the founder or their management to try and make them feel that they understand them and they work like them. So over time, the cultural values of companies become very consistent with the founders. Or CEOs, they're long tenured CEOs. So in that context, I think what was amazing at Google was Larry was product obsessed and nothing else mattered. But he said to me, I still remember my first meeting with him, he became CEO. He says, you run business. I'm like, I'm told by the board you're doing a really good job. I had a whole PowerPoint deck ready. Was ready to walk him through all the amazing things we were doing in the team, all 18,000 of us and flipping through every page in painstaking detail. He didn't want any of it. He's like, you know, I'm sure if I had two hours, I could make you do your job 10% or 20% much better. I just don't have two hours and I'm too busy doing product. So I just bit my tongue saying, hey, let me know when you have two hours. So he didn't care about most things other than product because he said no company in tech became great because they had great go to market. They became great because they had amazing products. And if you think of the history of technology, a lot of the car wrecks or the mishaps or companies that are no longer relevant, they became irrelevant because their product no longer mattered. And it's blindingly obvious. It stares you in the face. Yet technology company after technology company ends up at a certain point in time just declining and dying because somehow they're trying to do everything else as well as the product part. But your product's commoditized, everybody else has the same product, and somebody else goes out and discovers something amazing. So what Google has consistently done is been able to be really good at great products.
00:09:55 · Nikesh Arora, Aditya Agarwal
And coupled with that, Larry was obsessed with hiring the right people. I remember, I'm trying to think back, I want to say the first 10,000 or 15,000 employees, Larry read every hiring pack himself, and he would throw 10 to 15% of the recommendations out of the window, and there was no appeal. You couldn't go back and get the same person hired if Larry rejected that person. And he read every packet to the first 15 to 20,000 hires by himself. Eventually, he ran correlation tests with my decision and other periods of mine. And depending on who had above 95% hit rate, you got the right to hire more people yourself. I hit 98% because we used to model his behavior. And if you translate, he's going to reject these following five, he's going get these 15. And sometimes you could say the five that he rejected, we already knew he was going to, but you need these five to get the 15. That was him. He was product obsessed. He was obsessed with getting the right people in the company. I think that shows that Google has always been that place which hired really great people and built really good products. There's sort of one last story. There's like [00:10:59] S1: Please, please.