From Ghaziabad to Silicon Valley: Nikhil Kamath x Nikesh Arora | People by WTF | Ep. 11

Nikhil Kamath 0:00 [upbeat music] Nikesh Arora. Oh, boy, where do we begin? A boy from Ghaziabad, who's now one of the highest-paid execs in the world. That's Nikesh for you. He's collected degrees like people collect Pokémon. Constantly pivoted way before it was cool, worked at Google after landing an accidental interview with Larry Page, then at SoftBank, and now leads Palo Alto Networks, a big name in cybersecurity. Let's find out how not sticking to a lane worked in his favor. [upbeat music]

1:06 Hi, Nikesh. Thank you for doing this.

Nikesh Arora 1:09 My pleasure.

Nikhil Kamath 1:10 Uh, I don't know where to begin. There's no fixed agenda for today or not-- There isn't one particular thing I want out.

Nikesh Arora 1:18 Mm-hmm.

Nikhil Kamath 1:19 Uh, our audience is largely the entrepreneur, wannabe entrepreneur crowd in India, and we meet people who have gone down their path, been really successful, such as yourself, and try to tell them what they can learn from someone like you.

Nikesh Arora 1:36 Or what-- Yeah, from either doing what I did or not doing what I did.

Nikhil Kamath 1:40 Yeah. Yeah.

Nikesh Arora 1:40 Perfect. All right.

Nikhil Kamath 1:41 Sometimes we find not doing what someone did is as useful-

Nikesh Arora 1:44 For sure.

Nikhil Kamath 1:44 -if not more.

Nikesh Arora 1:45 For sure.

Nikhil Kamath 1:46 Uh, so maybe we can begin by you telling us a bit about yourself, and we

Nikhil Kamath 1:51 start from there.

Nikesh Arora 1:51 Where would you like to start? Uh...

Nikhil Kamath 1:53 Childhood. [chuckles]

Nikesh Arora 1:55 Ah. As you know, I grew up in India. Uh, my father was in the Indian Air Force. So, you know, you grow up in the Indian Air Force, you grow up with just enough means, so you have a good life, but, uh, no different than every other person who grows up in India, where you have to be resourceful, you have to be, um-- you have to work hard to get above the crowd and, and, uh, and sort of make something out of your life. And in that context, and my parents are amazing. Uh, my father passed away a few years ago, but, uh, he worked in the Air Force for his entire life. He was a lawyer, uh, and his job was to solve thorny legal issues, both within and without. And, you know, when you live in a family like that, where every day he's trying to get people to do the right thing, uh, the sort of the... You absorb the implicit culture of the high integrity you see around you. So, you know, I have my f- father to thank for a life of integrity, where he had to make decisions against all odds. He had to make decisions about lots of things, where, you know, i-it was crystal clear for him, given that the role he has was always to pick the right side, that somehow that became the mantra in our family, that he always had to do the right thing, irrespective of the cost, and so that sort of, that sort of you, you get that from your father. And my mother, uh, you know, rare for her time, she's a masters in math and Sanskrit, so she was very along, along, along the lines of that education empowers, and whatever you do, you have to be smart, you have to be well-read, and you have to, to do that. And, you know, she provided the nurturing element in the family. So I was very blessed. Uh, the difference is, when you work in the Air Force, you move around every few years. So it brings a sense of impermanence, it brings a sense of, uh, instability, perhaps, and the question is: what do you make out of it? So, you know, on the flip side, you, you get to adapt to many situations, and you can pick up your bags and move, uh, because you've done that naturally over your life. So, so those are some of the, sort of, sort of the, I'd say, the key building blocks of one's personality as you grow up.

Nikhil Kamath 4:04 Right. And how did the transition from growing up in Ghaziabad and going to school in Delhi to where you sit today-- I must say, uh, you have a very pretty

Nikhil Kamath 4:17 office.

Nikesh Arora 4:17 [chuckles] Thank you.

Nikhil Kamath 4:19 But everybody seems really scared of you.

Nikesh Arora 4:22 Ah, that's interesting. How did you pick that up?

Nikhil Kamath 4:26 Before you arrived...

Nikesh Arora 4:26 Yes.

Nikhil Kamath 4:27 Like, people were like: "He's coming now, he's coming now, he's coming now." And they really were freaking out. Like, I've been to some secure buildings in my life-

Nikesh Arora 4:35 Mm-hmm.

Nikhil Kamath 4:35 -but you have some crazy amount of security going on here as well.

Nikesh Arora 4:39 Well, remember, we're in the security business, so we're a trophy company-

Nikhil Kamath 4:42 [chuckles]

Nikesh Arora 4:42 -to break the security defenses off.

Nikhil Kamath 4:44 Right.

Nikesh Arora 4:44 Because, as you can imagine, the security industry comes from an underpinning where it was-- You know, your perception of a security person generally is that, if you think back a few years ago, is that kid sitting in his parents' basement, playing Call of Duty, on the side, hacking into the FBI computers and showing, "Look, I can do it."

Nikhil Kamath 5:00 Mm-hmm.

Nikesh Arora 5:01 There's no economic motivation. There's more of a trophy kill, and that sort of feeling persists in the security industry. If you go after somebody, go after the people who are entrusted with protecting everybody else, so we do have to have more security than you expect. You know-

Nikhil Kamath 5:14 Has it happened?

Nikesh Arora 5:17 Uh, there is a general belief that, uh, most security companies, and now infrastructure software companies, are constantly attacked.

Nikhil Kamath 5:26 Right.

Nikesh Arora 5:26 Because, uh, you know, ten, fifteen years ago, the philosophy was, you wanted something, you went after it, and you got it. You know, you want to hack into Nikhil's life, you go hack Nikhil, you find out what he wants. Then they said: "Well, that's a lot of work. Why don't we just go hack into a Gmail platform or email platform, and then, like, go and get whatever I want from whoever?" So people started going towards what we call supply chain attacks. You went after a big piece of infrastructure-

Nikhil Kamath 5:51 Mm-hmm.

Nikesh Arora 5:51 -and whoever was utilizing that piece of infrastructure would then be fair game. So, you know, we, we joke in our industry, hacking has gone from a hobby to a profession. When you do something professionally, you do it right. So yeah, it happens a lot.

Nikhil Kamath 6:03 Is that because the incentives have gotten more aligned now?

Nikesh Arora 6:07 ... Well, uh, if you think about it, there's something to the tune of north of ten billion dollars that is either extorted or ransomwared, or taken from individuals in some sort of Ponzi schemes, which is based on digital sort of hacking. So-

Nikhil Kamath 6:26 Every year?

Nikesh Arora 6:26 Yeah. So it's a lot of money.

Nikhil Kamath 6:28 Yeah, but that doesn't sound like a earth-shattering problem, that amount of money.

Nikesh Arora 6:32 Well, it's an earth-shattering problem because think about it, uh, it's still the Wild West, right?

Nikhil Kamath 6:36 Yeah.

Nikesh Arora 6:36 Because there's no recourse. Think about it, it's the lowest conviction-

Nikhil Kamath 6:40 Right

Nikesh Arora 6:40 ... uh, vertical in the bad actor industry.

Nikhil Kamath 6:43 Right.

Nikesh Arora 6:44 You can hack somebody from ten thousand, five thousand miles away.

Nikhil Kamath 6:47 Right.

Nikesh Arora 6:47 You can get paid in some version of cryptocurrency, and you're untraceable. So it's, like, much better than you've watched-- Remember the old Westerns you would watch-

Nikhil Kamath 6:56 Yeah

Nikesh Arora 6:56 ... and you had to wear your hat and carry your guns, and there was a fifty percent probability you'd get shot by somebody.

Nikhil Kamath 7:01 Yeah.

Nikesh Arora 7:01 In this case, it's-

Nikhil Kamath 7:02 Yeah

Nikesh Arora 7:02 ... pretty low impact.

Nikhil Kamath 7:04 If Palo Alto is a hundred billion dollar company, I would have assumed that this is a much bigger industry as well.

Nikesh Arora 7:12 It's getting bigger every year.

Nikhil Kamath 7:13 Right.

Nikesh Arora 7:14 But don't forget, there's the, there's the economic, uh, incentive part of it, there is the, uh, intellectual property part of it, there's the nation-state part of it, right? We think most future wars, as you can see, uh, if the current wars that are in play, are part cyber wars and part technology wars, right?

Nikhil Kamath 7:32 Right.

Nikesh Arora 7:33 People are trying to figure out the lowest cost way to create instability, chaos, and destruction of life and property without it costing them too much.

Nikhil Kamath 7:42 Right.

Nikesh Arora 7:42 And the first thing that happened in the Russia-Ukraine conflict was the entire logistics systems of Ukraine were taken down-

Nikhil Kamath 7:49 Right

Nikesh Arora 7:49 ... by hackers, because that was the way they could de-- uh, sort of destabilize and immobilize the army of Ukraine.

Nikhil Kamath 7:55 Mm-hmm.

Nikesh Arora 7:56 It wasn't a bomb that landed; it was-

Nikhil Kamath 7:58 Mm

Nikesh Arora 7:58 ... a cyberattack.

Nikhil Kamath 7:59 Mm-hmm.

Nikesh Arora 7:59 So you can see that sort of the, the future norm-

Nikhil Kamath 8:02 Mm-hmm

Nikesh Arora 8:02 ... as it relates to creating instability, taking control, stealing property, both intellectual or, uh, economic, is going to be sort of eased by cyber.

Nikhil Kamath 8:13 I have a private equity fund, Nikesh, and I have been trying to figure out what industry might thrive in ten years, post all the disruption of today. I'm sure disruptions will continue to come by, but how does cybersecurity change? And as a investor who's looking to get allocation, if I have a broad portfolio-

Nikesh Arora 8:36 Yeah

Nikhil Kamath 8:36 ... what percentage of that do you think should go into something like cybersecurity?

Nikesh Arora 8:40 Like, if you analyze cybersecurity, it didn't exist as an industry sub-vertical of significance till about twenty-five years ago.

Nikhil Kamath 8:49 Mm-hmm.

Nikesh Arora 8:49 If you go back, you know, I was at Banaras doing a, [clears throat] um, commencement address at BHU, and I was reflecting when I went to school there in 'eighty-nine. We had one ICL 1904. There was nothing called an iPhone, and that computer was five thousand times less powerful than one iPhone.

Nikhil Kamath 9:10 Right.

Nikesh Arora 9:11 So in, you know, what was then thirty years, you've got five thousand times the power in a thing we carry in our, in our back pocket.

Nikhil Kamath 9:19 Mm-hmm.

Nikesh Arora 9:19 Uh, but it's about 2005, I think, was when we started getting the app economy, and everything started getting connected. So that was not even twenty years ago. Twenty years ago, we were not worried about getting hacked because most of us were using our phones to call somebody-

Nikhil Kamath 9:34 Mm-hmm

Nikesh Arora 9:34 ... or at best, send a sort of old form text.

Nikhil Kamath 9:37 Right.

Nikesh Arora 9:37 So if you believe the entire connectivity revolution has explored in the last twenty years and continues to sort of grow exponentially with where we are, uh, in our problems, we call that the attack surface continues to expand.

Nikhil Kamath 9:48 Mm-hmm.

Nikesh Arora 9:48 Now, you can attack five billion online people around the world. You can attack every company.

Nikhil Kamath 9:52 Mm-hmm.

Nikesh Arora 9:52 In the past, no company was connected to their consumers. So if you believe the attack surface continues to expand exponentially, and every service becomes somewhat useless without connectivity. Now, your car has to be connected. If you can't connect to your car, you can't get into your Waymo. And tomorrow, I'm pretty sure robotic arms will be connected, and humanoids will be connected. So if the attack surface continues to expand, there is... the demand function is secured.

Nikhil Kamath 10:17 Right.

Nikesh Arora 10:17 Now, the question is, can you satisfy the demand function with the right technology? And that becomes so the cybersecurity industry. So I don't know how it'll compare to other industries, but I'm pretty sure it is a gift that'll keep on giving.

Nikhil Kamath 10:30 Will it come down

Nikhil Kamath 10:31 to who has more compute, and by virtue of that, they can hack into something? If I had more co- compute than Palo Alto, for example, would it be possible for me to hack into it?

Nikesh Arora 10:41 So there is that, you know, prevailing theory that when quantum comes about, it'll break every key, which is true. It will break every key that is there today. But-

Nikhil Kamath 10:47 Can you explain how that is? I read that, but I couldn't understand because I'm a totally non-technical person.

Nikesh Arora 10:52 So the way it works is when you communicate to something else, and you're trying to send data in an encrypted fashion, I send-- I encrypt it, I send it to you, we decrypt it to your end, so nobody to intercept it and steal it or observe it or read it.

Nikhil Kamath 11:06 Mm.

Nikesh Arora 11:06 Right? Now, the industry has a protocol where there is a protocol which defines how to decrypt, how to share keys, so you have the key that is required to decrypt the communication I sent you. Those keys are effectively co- codified in such a way that it's hard to break them, but it would require a lot of compute to break them. But with the arrival of quantum, they will be able to break those keys in seconds or minutes as compared to days.

Nikhil Kamath 11:32 Because quantum has more computing power.

Nikesh Arora 11:33 So much compute power, right. So if you could do that, you need a whole new set of keys.

Nikhil Kamath 11:37 Mm-hmm.

Nikesh Arora 11:37 Or you need more complicated, but you need keys that quantum can't break-

Nikhil Kamath 11:41 Mm-hmm

Nikesh Arora 11:41 ... which means you need a new set of protocols to define it. So there is this prevailing theory that when quantum comes about, it'll break today's encryption. So everything will be decryptable, and hence observable, and hence, could lead to potential hacks. Now, the sad truth is, most hacks today are way less sophisticated than that.

Nikhil Kamath 11:59 Mm-hmm.

Nikesh Arora 12:00 Right? Typically, they are human beings who make errors in configuration, human beings who click on the wrong email that comes to you, human beings who leave their password on a yellow sticky on the side of the computer to make it easy for people to get into. So I think from that perspective, we have enough of a crisis right now. We don't need yet another one from a compute perspective. But I think on the flip side, the possibility, uh, of-... this notion of AI, which will start figuring out on the fly where the, the gaps, mis- misconfigurations, or the errors are, and be able to be much more intelligent at providing more real-time protection are gonna be. So I think the opportunity is gonna be more in AI-based analytics and real-time protection to start with, than just really throwing more computers at the problem.

Nikhil Kamath 12:45 So from three lens, as an investor, as an individual, and speaking to the people who are starting small enterprises across the world, as an investor, if I want exposure to cybersecurity, how should I look at it? Like, what should I look out for in a company?

Nikesh Arora 13:02 Um, if you're looking at a startup category-

Nikhil Kamath 13:07 Yeah.

Nikesh Arora 13:08 -the most likely categories which we'll see outsized returns are categories where a new attack vector is being born, and there are many ideas about how to secure the attack vector, and many people are experimenting. Take the current example of AI.

Nikhil Kamath 13:26 Mm-hmm.

Nikesh Arora 13:26 We all talk about AI, and we were just getting our arms around ChatGPT and LLMs, and suddenly you have coding assistants, and now we're talking about agentic AI.

Nikhil Kamath 13:34 Mm-hmm.

Nikesh Arora 13:34 All these things, uh, that are out there. I don't think there is a general agreement on what agentic AI means in the world.

Nikhil Kamath 13:42 Mm-hmm.

Nikesh Arora 13:43 Right? And I was, I was talking to somebody this morning, and I was saying, "To me, my manifestation of agentic AI is a Waymo in San Francisco." You get in a Waymo, you let the car decide where to take you. You let the car decide when to brake, when to turn.

Nikhil Kamath 13:55 Mm-hmm.

Nikesh Arora 13:55 That's giving agency to the car.

Nikhil Kamath 13:57 Right.

Nikesh Arora 13:57 Hence, it becomes agentic AI.

Nikhil Kamath 13:59 Right.

Nikesh Arora 13:59 Now, I don't think most enterprises or human beings are ready-

Nikhil Kamath 14:03 Right

Nikesh Arora 14:03 ... to give an AI agent control.

Nikhil Kamath 14:06 Right.

Nikesh Arora 14:06 As simple things like, you know, you can-- If I told you, it's easy to imagine that if you were coming to San Francisco, you'll ask your favorite AI bot or LLM or agent to find you a nice restaurant where you like to eat. It'll understand your preferences and know who your friends are and say, "I wanna eat with my two friends. I wanna eat a nice Indian meal. Find me a restaurant which is more like in my taste and make the reservation."

Nikhil Kamath 14:27 Mm-hmm.

Nikesh Arora 14:27 Now, if you trust AI to do all of that for you and show up blindly over there, that would be called giving agency to that agent to let it decide for you.

Nikhil Kamath 14:35 Right.

Nikesh Arora 14:36 I don't think we're ready as human beings to let even that basic-- to hand over that basic agency. So, so sort of long way of saying that, if you're building technology, uh, think about those scenarios. Think about a scenario that if Nikhil gave agency to an agent, and somebody took over that agent, what chaos would they be able to cause,

Nikesh Arora 14:55 right?

Nikhil Kamath 14:56 And this will happen when AI moves from, in many ways, for a lot of people, including me, it's very question and answer right now.

Nikesh Arora 15:03 Yes.

Nikhil Kamath 15:04 You're talking about when it is able to do more sequential tasks in a way.

Nikesh Arora 15:07 Able to do things, right?

Nikhil Kamath 15:08 And everybody's trying to solve for that, right?

Nikesh Arora 15:09 Yes. So there's two elements, right? There's the planning element and the doing element.

Nikhil Kamath 15:13 Right.

Nikesh Arora 15:13 Today, it does a task.

Nikhil Kamath 15:15 Right.

Nikesh Arora 15:15 It book me an airline ticket. When do you want to go?

Nikhil Kamath 15:17 Yeah.

Nikesh Arora 15:17 It's kinda like writing a piece of code.

Nikhil Kamath 15:18 Yeah.

Nikesh Arora 15:18 But it says, "Find the best option."

Nikhil Kamath 15:21 Yeah.

Nikesh Arora 15:21 "Infer what the best option is."

Nikhil Kamath 15:22 Yeah.

Nikesh Arora 15:23 "Figure out what's most convenient to me. Figure out the time I should be flying from here. Figure out that allows me to get there at the right time-

Nikhil Kamath 15:29 Mm-hmm

Nikesh Arora 15:29 ... based on my calendar or whatever you have you." Something is planning this. That inference engine of everybody's trying to build-

Nikhil Kamath 15:35 Yeah

Nikesh Arora 15:35 ... for every use case.

Nikhil Kamath 15:36 Yeah.

Nikesh Arora 15:36 That inference engine then we, we connect, let's call it, to a do engine, and if you can infer and do, that becomes your agent.

Nikhil Kamath 15:43 Yeah.

Nikesh Arora 15:44 Now, the good news is, that's gonna be fun. Exciting news for cybersecurity is that, once that happens, I don't have to bother you. I can just take over your agent-

Nikhil Kamath 15:53 Right

Nikesh Arora 15:53 ... and cause chaos.

Nikhil Kamath 15:54 Right.

Nikesh Arora 15:54 Now, you can think of simple agents making restaurant reservations, which is, I'd call it non-destructive.

Nikhil Kamath 15:59 Mm-hmm.

Nikesh Arora 15:59 The worst thing is the bad meal. You can also make it more complicated and say, you know, it can change the entire configuration of my firewall. It can change the entire configuration of the heating/cooling system of Palo Alto, because you have an agent which un- which checks climate and understands how to redo the entire heat settings for the company. So there are all kinds of different examples, from control systems to industrial systems to robotic systems you can think of, which eventually will want agency, and they will become an interesting place for bad actors to try and take control. Because those agents will allow you to act on behalf of whoever's agent you've taken over. So if you had a series of companies who are building these solutions, they'd be very interesting because it's an unknown problem in a field which has not been fully explore- explored. There is no resident expert today. There's no resident install base, so it's a sort of a, you know, blue sky problem.

Nikhil Kamath 16:52 Mm-hmm.

Nikesh Arora 16:52 And startup founders are notoriously good at trying to attack those problems, solve them. Either they'll build a big company out of it, or they'll get bought out by somebody who wants to solve that problem.

Nikhil Kamath 17:00 Yeah. I'm working with this company here while I'm here, and they were demoing their new browser yesterday.

Nikesh Arora 17:06 Yes.

Nikhil Kamath 17:07 And if you had many tabs open, it could do a few things, which seemed very sequential in nature.

Nikesh Arora 17:13 Agentic browser.

Nikhil Kamath 17:14 Yeah.

Nikesh Arora 17:14 Yes.

Nikhil Kamath 17:15 That's almost here, right? Because that was a live product they've not launched yet, but it seems to be getting really, really close.

Nikesh Arora 17:23 Yeah. I think the idea of automated tasks in sequence has been around for a while, and people have called it a playbook.

Nikhil Kamath 17:31 Mm-hmm.

Nikesh Arora 17:32 People have called it a workflow. Uh, I think the question really becomes is: When will you let a planning agent control it versus you control it yourself?

Nikhil Kamath 17:42 Interesting.

Nikesh Arora 17:43 For a meaningful task.

Nikhil Kamath 17:44 Mm-hmm.

Nikesh Arora 17:45 You know, you can say, "I can do a three-step task. I can search the web."

Nikhil Kamath 17:49 Mm-hmm.

Nikesh Arora 17:49 "I can find you, you know, which, which websites are selling great shoes. I can make a catalog of them. I can sort them by size. I can s-- marry that with your preferences, which I have in memory, and sort." Those are all planned tasks. You actually wrote the plan.

Nikhil Kamath 18:05 Mm-hmm.

Nikesh Arora 18:05 Something executed your plan. If I give you a nebulous problem, saying, "Find the best shoe for me-

Nikhil Kamath 18:12 Mm-hmm

Nikesh Arora 18:12 ... that I should wear tomorrow," there is too many subjective decisions that need to be made in that process.

Nikhil Kamath 18:16 Right.

Nikesh Arora 18:16 Which means your planning or inferencing brain has to start working.

Nikhil Kamath 18:20 Right.

Nikesh Arora 18:20 Uh, which is creating certainty from a lot of nebulous data.

Nikhil Kamath 18:23 Mm-hmm.

Nikesh Arora 18:23 I think that's the Holy Grail, and when you can start getting really good inferencing and planning agents, then it starts to mimic human intelligence.

Nikhil Kamath 18:30 Mm-hmm.... So as an individual, as a individual investor, if I were to look at a new vector, a lot of people do say that self-driving cars are not really the best example of AI, at least generative learning.

Nikesh Arora 18:48 Yeah. Well, look, AI was traditionally known, well, used to be machine learning, right? Which is the idea that you could algorithmically write code and go decipher things-

Nikhil Kamath 18:57 'Cause they're not really predicting what will come in the road or what will happen next, right?

Nikesh Arora 19:01 Sure.

Nikhil Kamath 19:01 They're more like-

Nikesh Arora 19:02 Well, they are acting-

Nikhil Kamath 19:05 Mm-hmm

Nikesh Arora 19:05 ... based on information that they're presented with in the instance. And over time, you go from predictable actions to unpredictable situations, and figuring out, inferencing what you do in that scenario. So there's a little bit of inferencing going on, but there'll be more inferencing going on. And generative is a whole different-

Nikhil Kamath 19:25 Yeah

Nikesh Arora 19:25 ... conversation, right?

Nikhil Kamath 19:26 So that's good. That's useful. As a investor, I can look for new vectors, new surfaces, where cybersecurity might be a thing and invest in that. Invest in small companies which might want to build a niche specifically in one thing, right?

Nikesh Arora 19:39 Yeah, but I think if you, if you step back and, and look at the broader impact of AI-

Nikhil Kamath 19:46 Mm-hmm

Nikesh Arora 19:46 ... um, you know, I think there are a lot of industries will get upended in the next ten years. If you take the whole notion of product development, and you have a trading platform of sorts, right?

Nikhil Kamath 19:56 Mm-hmm.

Nikesh Arora 19:57 Now, your, a lot of your trading platform, in my, my understanding, this is where-

Nikhil Kamath 20:02 Right

Nikesh Arora 20:02 ... you're the expert, and I'll, I'll posit something, is you're helping us consumers interact with large data behind it.

Nikhil Kamath 20:11 Yeah.

Nikesh Arora 20:11 You're making it easy, you're creating forms, workflow, and eventually, you're consummating transactions on my behalf.

Nikhil Kamath 20:16 Yeah.

Nikesh Arora 20:16 But the entire UI is designed to make me understand and to get the right inputs from me, so you can actually understand what I'm doing, right? I could pick a certain ticker-

Nikhil Kamath 20:24 Mm-hmm

Nikesh Arora 20:25 ... I can choose a certain amount of shares, I can put it in there, I can buy, sell. If you have call options, I can, you know, uh, whatever. So like a ty- typical tra- trading platform.

Nikhil Kamath 20:35 Mm-hmm.

Nikesh Arora 20:35 If you look at the world, seventy-five percent of product development in technology is human beings teaching consumers how to interact with back-end engineering databases and transactions.

Nikhil Kamath 20:49 Yeah.

Nikesh Arora 20:49 Whether it's flight tickets, whether it's, you know-

Nikhil Kamath 20:52 Yeah

Nikesh Arora 20:52 ... trading.

Nikhil Kamath 20:53 Yeah.

Nikesh Arora 20:54 If I have a smart enough capability through a combination of generative AI and workflow automation, where I can talk to this without requiring UI, which we can imagine, right?

Nikhil Kamath 21:04 Mm.

Nikesh Arora 21:05 We can imagine if I have an inference engine, it can say, "Hey-

Nikhil Kamath 21:07 Yeah

Nikesh Arora 21:07 ... you know, take the position I had yesterday, that I bought, sell it, take half the profits, and reinvest them between hundred dollars and hundred and ten dollars in, you know, Reliance," or whatever your favorite stock is, if you're Robinhood, whatever you have, right? You and I can imagine how that query or that natural language trans-

Nikhil Kamath 21:24 Mm-hmm

Nikesh Arora 21:24 ... that, that you can literally, you're, literally in your brain, you're planning the steps that are required in your product to go execute that transaction.

Nikhil Kamath 21:30 Right.

Nikesh Arora 21:30 But it doesn't happen today.

Nikhil Kamath 21:31 Mm-hmm.

Nikesh Arora 21:32 In the future, it's effectively a planning engine, planning the tasks, calling the four tasks, saying, "Sell yesterday's position, take the proceeds, understand how many shares I can buy, take half then, buy those many shares between a hundred, hundred and ten dollars."

Nikhil Kamath 21:45 Mm-hmm.

Nikesh Arora 21:45 "Go back to the user and say, 'I have a hundred dollar, hundred shares of, for you of this, and the remaining cash is in your balance.'"

Nikhil Kamath 21:51 Yeah.

Nikesh Arora 21:52 We can actually write the steps in our head of that transaction.

Nikhil Kamath 21:55 Yeah.

Nikesh Arora 21:55 The question is, do I have to code all of that and take every scenario and do it?

Nikhil Kamath 21:58 Mm-hmm.

Nikesh Arora 21:58 Or in the future, there's an agentic AI or an AI interface that allows you to do, and there's an inference engine.

Nikhil Kamath 22:03 Mm-hmm.

Nikesh Arora 22:04 Which means your entire process of product development at zero dollars is gonna change.

Nikhil Kamath 22:07 Yeah.

Nikesh Arora 22:08 Take that and multiply that across every user experience that is out there.

Nikhil Kamath 22:11 Mm.

Nikesh Arora 22:11 Take a different example. Today, a lot of applications are designed generically for everyone.

Nikhil Kamath 22:16 Mm-hmm.

Nikesh Arora 22:17 Right? It's kind of like very little user preference or knowledge.

Nikhil Kamath 22:20 Mm-hmm.

Nikesh Arora 22:20 It's just kind of marginal, right? Like, you a little bit of understand what you know. But if you can have full memory of my preferences, and you're designing an application, whether it's a nutrition app, right? You go to a nutrition app today, it tells you, you have to pick a whole bunch of stuff by the time you're done filling forms. Five pages later, it tells you, "Eat less carbs." Thank you very much, right? Or gives you some advice. Over time, I think applications will become applications for one-

Nikhil Kamath 22:48 Yeah

Nikesh Arora 22:48 ... instead of generic applications. So I think there's a lot of implications of AI in the technology world from a product development perspective, AI in the enterprise software world, where I think analytic products will die.

Nikhil Kamath 23:01 Mm-hmm.

Nikesh Arora 23:01 It'll all be products that help you do something.

Nikhil Kamath 23:04 Mm-hmm.

Nikesh Arora 23:04 There's a huge debate. I mean, uh, you know, look at the world of advertising. The whole notion of digital advertising, which is about a forty-five billion dollar industry, is to encourage you and me to buy something or transact.

Nikhil Kamath 23:16 Mm-hmm.

Nikesh Arora 23:16 People buy ads on the internet, so that eventually you and I will either go trade, or you and I will go buy something.

Nikhil Kamath 23:22 Mm-hmm.

Nikesh Arora 23:22 But if our agents start interacting on our behalf, and they start assessing what the right answers are, what is the role of advertising in the future? So there's just so many-

Nikhil Kamath 23:32 Yeah

Nikesh Arora 23:32 ... implications across the entire technology landscape. I don't think your investor brain should be worried about, uh, one particular cybersecurity vector to invest in.

Nikhil Kamath 23:41 Right.

Nikhil Kamath 23:42 The interface in businesses like us, I agree with you a hundred percent, will become irrelevant. If I could use the analogy of, say, cryptocurrency and the blockchain, I think where people like us come in is, we're essentially not a company of interface, but a company with a regulatory moat.

Nikesh Arora 24:04 You're, you're what I call a system of record.

Nikhil Kamath 24:06 Yeah.

Nikesh Arora 24:07 You have track-

Nikhil Kamath 24:08 Yeah

Nikesh Arora 24:08 ... of how many shares I own.

Nikhil Kamath 24:09 Yeah.

Nikesh Arora 24:09 You're a system of record.

Nikhil Kamath 24:10 Yeah.

Nikesh Arora 24:10 If you were to vanish tomorrow-

Nikhil Kamath 24:11 Yeah

Nikesh Arora 24:11 ... I wouldn't know what my net worth is, if I was a zero-dollar customer. So, yeah, so you're a system of record, and system of records will stay.

Nikhil Kamath 24:18 Yeah.

Nikesh Arora 24:18 But the entire product development process of how I interface with the system of record will change.

Nikhil Kamath 24:22 System of record will stay when there is regulation behind it, which mandates them to stay, or will the same apply to a technology like blockchain, where there might not be a regulator mandating the system of record?

Nikesh Arora 24:33 It doesn't have to be a regulator, right? A system of record is almost like, I would say-... something that is built over time.

Nikhil Kamath 24:40 Right.

Nikesh Arora 24:40 Right? Well, either it's mandated by regulation, mandated by enterprises. I have a, I have-- You-- I'm pretty sure you and I have both have payroll systems-

Nikhil Kamath 24:47 Yeah.

Nikesh Arora 24:47 -which are systems of record.

Nikhil Kamath 24:48 Yeah.

Nikesh Arora 24:48 They're not mandated by regulation.

Nikhil Kamath 24:50 Mm-hmm.

Nikesh Arora 24:50 But if you have a payroll system, if it goes away tomorrow, you won't know how much you paid someone and how much you have to pay them. The whole mode of interaction of me with your payroll system may be fundamentally different-

Nikhil Kamath 24:58 Yeah

Nikesh Arora 24:59 ... and your head of HR, and that might be different, but the system of record will stay-

Nikhil Kamath 25:02 Mm-hmm

Nikesh Arora 25:02 ... because it's required as part of your business process to exist. Now, a system of record could also be there purely because of the fact that I have great market share.

Nikhil Kamath 25:11 Mm-hmm.

Nikesh Arora 25:11 Hence, I have the record of that data somewhere, and it's too painful for you to replace that system of record. Even though it's not mandated by regulation, it just happens to be that was where it is. So there is, there is a prevailing theory that the big will become bigger because they are-- if they are smart enough and fast enough, agi- and agile enough to be able to change the mode of interaction with the system of record. And I think that's going to make a lot of enterprise software rethink how it's built, how it's run, and how it's managed.

Nikhil Kamath 25:44 So if AI becomes democratic, [chuckles] democratic in the means that everybody evolves to a point where everybody's like each other, how big does the role of a brand play in something like this? Why do I pick A over B? Is it just utilitarian, or is there a brand play involved?

Nikesh Arora 26:02 Well, I, I thought you were asking a societal question, which is a much harder question.

Nikhil Kamath 26:05 Yeah.

Nikesh Arora 26:05 I'll stick with the brand question. [chuckles]

Nikhil Kamath 26:06 I'll come to that next. [chuckles]

Nikesh Arora 26:07 I'll stick with the brand, I'll stick with the brand question where you're now. Uh, I think, look, brands are correlated experiences-

Nikhil Kamath 26:13 Right

Nikesh Arora 26:13 ... and trust, and, and perception, right?

Nikhil Kamath 26:16 Mm-hmm.

Nikesh Arora 26:17 You know, why do you spend a lot more money for a Cartier bracelet for your wife or your girlfriend-

Nikhil Kamath 26:23 Mm-hmm

Nikesh Arora 26:24 ... than you would for something made by your local jeweler?

Nikhil Kamath 26:27 Mm-hmm.

Nikesh Arora 26:27 If you, if you-- The raw material is the same. The cogs are pretty much the same.

Nikhil Kamath 26:31 Mm-hmm.

Nikesh Arora 26:31 But you pay more for the perception, for the brand, for the experience, the trust, the loyalty. So I think the brand encompasses a lot more than the raw material from that perspective. I don't know how democratization of AI changes that. Let's, let's take a look at it from a slightly different angle.

Nikhil Kamath 26:49 Mm-hmm.

Nikesh Arora 26:50 You know, the way I see, this is partly the societal comment, right? A-- When things like Google came about-

Nikhil Kamath 26:56 Mm-hmm

Nikesh Arora 26:56 ... if you go historically, historically, information was power, right?

Nikhil Kamath 27:00 Mm-hmm.

Nikesh Arora 27:00 Caste systems based on power-

Nikhil Kamath 27:02 Mm-hmm

Nikesh Arora 27:02 ... which is basically fundamentally based on information. The highest caste was-

Nikhil Kamath 27:05 Yeah

Nikesh Arora 27:05 ... owned the information and dictated-

Nikhil Kamath 27:07 Yeah

Nikesh Arora 27:07 ... how society should behave.

Nikhil Kamath 27:08 Mm-hmm.

Nikesh Arora 27:08 And look, you know, historically, a lot of power has been because of an information disadvantage or asymmetry.

Nikhil Kamath 27:14 Mm-hmm.

Nikesh Arora 27:15 The internet came about, information asymmetry began to vanish, right?

Nikhil Kamath 27:18 Mm-hmm.

Nikesh Arora 27:19 The guy who had the newspaper in New Delhi was no longer smarter than the guy in Varanasi next to me, who took out the newspaper a day late. Remember?

Nikhil Kamath 27:28 Right. Yeah.

Nikesh Arora 27:28 There was a place in India you got newspaper a day late.

Nikhil Kamath 27:29 Yeah.

Nikesh Arora 27:30 But today with the internet, there's instant access, so democratize of information allows it, you know, has a whole series of applications and, and experiences to be built. The question is: Does AI democratize intelligence?

Nikhil Kamath 27:46 Depending on the definition of intelligence.

Nikesh Arora 27:48 Well, if you listen to what Sam Altman is telling you-

Nikhil Kamath 27:50 Mm

Nikesh Arora 27:50 ... and all these wonderful people building AI models, they're talking about-

Nikhil Kamath 27:53 Mm

Nikesh Arora 27:53 ... AGI or, you know, artificial general intelligence, where these models are gonna be able to mimic the human brain or be smarter because they have infinite memory, infinite pattern recognition. Our brains are restricted by our capacity, but this thing is not. So let's assume for a second, without taking the draconian outcome, let's just assume that i- it normalizes intelligence.

Nikhil Kamath 28:12 Mm-hmm.

Nikesh Arora 28:12 And what I mean by normalizing intelligence is if I call Zero, I'm sure you have a customer service team.

Nikhil Kamath 28:16 Mm-hmm.

Nikesh Arora 28:16 Right? There are, let's say there are five different people. They have different capabilities, different understanding.

Nikhil Kamath 28:22 Mm.

Nikesh Arora 28:22 I could get a marginally different answer from one of those five people if I called, depending on their intelligence, if everything was not codified by your system, which I, I'm guessing it's not always, because there's a human involved. Now, we're saying AI is gonna get so good that it, it will make that experience consistent on a constant basis. So it is just normalized intelligence across five people in your team, or maybe five thousand people in your team.

Nikhil Kamath 28:42 Mm-hmm.

Nikesh Arora 28:43 So when intelligence gets, gets normalized, what are the consequences of that? Then nobody's smarter than the other person.

Nikhil Kamath 28:50 Then what is the differentiation?

Nikesh Arora 28:52 The differentiation is solving the unknown problem.

Nikhil Kamath 28:55 How do we articulate what the unknown problem is? I would assume that humans, from the beginning of time, have wanted to differentiate through many different means: capitalism, intelligence-

Nikesh Arora 29:04 Well, why do we give Nobel Prizes? We give Nobel Prizes to people who solve unknown problems. I'm sure there's a lot more unknown problems in the world that we haven't touched or scratched the surface of, which have to be solved. There's a combination of, you know-- Now, the question is: Does human intelligence learn how to manage all this democratized intelligence, or is AGI-

Nikhil Kamath 29:23 Mm

Nikesh Arora 29:23 ... going to manage this democratized intelligence? You and I are just gonna be drinking in the pub or hanging out at the bar and then saying, "Geez, everything is being done by AGI and AI." So I don't know the answer to that question, but I think the bigger question is, like we saw the democratization of information, this is gonna democratize intelligence. And when intelligence gets democratized, what are the business implications, societal implications of that? And nobody's smarter than the other, right?

Nikhil Kamath 29:46 Mm.

Nikesh Arora 29:47 Like, you know how to put a rocket in the air? I do, too.

Nikhil Kamath 29:50 Mm.

Nikesh Arora 29:50 Let me talk to my pet agent. It knows the answer.

Nikhil Kamath 29:52 Does capital become the mode then? Incumbent people with capital.

Nikesh Arora 29:57 I did say the big get bigger.

Nikhil Kamath 29:59 Mm.

Nikesh Arora 29:59 Right? As long as they play their cards right.

Nikhil Kamath 30:01 Mm.

Nikesh Arora 30:01 Uh, because-

Nikhil Kamath 30:02 Because, because they have more compute power in that world?

Nikesh Arora 30:04 No, uh, I think it's not just capital. Uh, you know, there is a debate today that, uh, all the known information that is in the public domain has already been used to train AI.

Nikhil Kamath 30:17 Mm-hmm.

Nikesh Arora 30:17 Right? If you hear the debates-

Nikhil Kamath 30:18 Mm-hmm

Nikesh Arora 30:18 ... all these models are being trained by all the information out there. I think there's ten times more information in private domains, which is not available in the public domain. All the drug discovery data, which is sitting in every drug company that has made any drug in the past, it's all proprietary data, right?

Nikhil Kamath 30:34 Mm-hmm.

Nikesh Arora 30:35 All the intellectual property, uh, all the data used to build NVIDIA chips or Intel chips, all proprietary. AMD, all these are all proprietary data.

Nikhil Kamath 30:40 Maybe quantum computing changes that, and everything comes online, because everything-

Nikesh Arora 30:44 I don't think quantum computing changes that. I think the question becomes, at what point in time do these private databases start being made available and training AI-

Nikhil Kamath 30:51 Mm-hmm

Nikesh Arora 30:51 ... for-... specific task. Could I design the best chip designing model? Of course, I could, if I had all the data that Intel has and NVIDIA has. There's no human being who has it in their head.

Nikhil Kamath 31:01 Right.

Nikesh Arora 31:01 But possibly some version of AI can understand patterns and build that knowledge base. But once it builds that knowledge base, can it use an inference engine to solve the unknown problem?

Nikhil Kamath 31:10 Right.

Nikesh Arora 31:11 Right? Today, we've relied on human intelligence to understand everything, the art of the possible, and humans have to ideate and say, "Well, how do I solve the unknown-

Nikhil Kamath 31:18 Mm-hmm.

Nikesh Arora 31:18 -because now I understand the known?" But it's a high bar.

Nikhil Kamath 31:21 Mm-hmm.

Nikesh Arora 31:21 Right, you have to go to, I don't know how many years of PhD studies do you have to go to, how many research papers you have to write-

Nikhil Kamath 31:26 Mm-hmm

Nikesh Arora 31:26 ... to get to a point where you say, "I think I have a good understanding of this sliver of the problem I'm trying to solve."

Nikhil Kamath 31:32 Right.

Nikesh Arora 31:33 But tomorrow you say, "Guess what? That's in your, in your edge model sitting in your pocket."

Nikhil Kamath 31:37 Mm-hmm.

Nikesh Arora 31:37 "It's only as smart as all the intelligence in the world that is being used to solve this particular domain. Now, work from there."

Nikhil Kamath 31:43 Mm-hmm.

Nikesh Arora 31:44 So I think that's the bigger debate or the bigger, uh, opportunity, or the scary part, is what happens when this thing gets smart, and we start democratizing, democratizing intelligence? I mean, I, I, I gave you the example of going to Varanasi and saying that was a one-five thousandth time less powerful computer. In thirty years, we were able to build a five thousand times powerful computer.

Nikhil Kamath 32:07 Right.

Nikesh Arora 32:07 Imagine if the state of AI-

Nikhil Kamath 32:09 Mm-hmm

Nikesh Arora 32:09 ... which is ho- which will poss- possibly or potentially move exponentially faster.

Nikhil Kamath 32:14 Mm-hmm.

Nikesh Arora 32:14 If

Nikesh Arora 32:15 AI is a thousand times smarter in five years-

Nikhil Kamath 32:17 Mm-hmm

Nikesh Arora 32:17 ... let alone five thousand times-

Nikhil Kamath 32:19 Mm-hmm

Nikesh Arora 32:19 ... what is the art of the possible?

Nikhil Kamath 32:21 I love how you're explaining. [laughing]

Nikesh Arora 32:23 [laughing]

Nikhil Kamath 32:25 Would you like to prophesize how the world might look in ten years?

Nikesh Arora 32:29 No.

Nikhil Kamath 32:29 Just a major a guess.

Nikesh Arora 32:30 No, I, I don't know if, uh, prophesizing is to any value, right?

Nikhil Kamath 32:35 Mm-hmm.

Nikesh Arora 32:35 I think you have to take an optimistic outlook towards this. You can prophesize a draconian set of outcomes.

Nikhil Kamath 32:42 Mm-hmm.

Nikesh Arora 32:42 You can prophesize an out, you know, optimistic set of outcomes.

Nikhil Kamath 32:45 Mm-hmm.

Nikesh Arora 32:45 We all were, you know, you know, we've all lived through this in recent past where we had a pandemic, and if you looked at prefo- prophesizing the pandemic, you said, "The pandemic is gonna persist for five years."

Nikhil Kamath 32:56 Right.

Nikesh Arora 32:56 I'm pretty sure there would be as many doomsday prophecies as there were-

Nikhil Kamath 32:59 Mm-hmm

Nikesh Arora 32:59 ... uh, possibly more than optimistic prophecies. But look around you.

Nikhil Kamath 33:03 Yeah.

Nikesh Arora 33:03 A very extremely resilient society. I think we forget historical lessons, and people will say, "Oh, my God, what's gonna happen? AI is gonna take my job. What's it gonna do?"

Nikhil Kamath 33:11 Mm-hmm.

Nikesh Arora 33:11 Well, guess what, you know? I don't see anybody buying picks and shovels and digging up the ground to plant wheat.

Nikhil Kamath 33:17 Mm-hmm.

Nikesh Arora 33:17 Right? Things that happened, and we all found something else to do. So I'm sure we'll find things to do. We'll find, find ways to, uh, propel society further, right? Um, and, and I'm sure things that get solved easily-

Nikhil Kamath 33:36 Mm-hmm

Nikesh Arora 33:36 ... will create new opportunities, just have no doubt.

Nikhil Kamath 33:39 I was talking to one of our private equity common friends, and he seemed to think that the models, the language models, will become like the device, like the iPhone today.

Nikesh Arora 33:48 Mm-hmm.

Nikhil Kamath 33:49 And the real marketplace is going to be what gets built on top. Do you suspect that to be true?

Nikesh Arora 33:57 Yeah, I have my own version of-

Nikhil Kamath 34:00 Mm-hmm

Nikesh Arora 34:00 ... that interpretation. I think it's broadly consistent.

Nikhil Kamath 34:04 Mm-hmm.

Nikesh Arora 34:05 And, uh, the way I see it is that what you're getting in the form of a model or AI is the equivalence of a brain.

Nikhil Kamath 34:16 Mm-hmm.

Nikesh Arora 34:17 Right? The early version of the brain had parroting capability.

Nikhil Kamath 34:22 Mm-hmm.

Nikesh Arora 34:22 It could read everything in the world and repeat it to you.

Nikhil Kamath 34:24 Mm-hmm.

Nikesh Arora 34:25 Over time, it built pattern recognition.

Nikhil Kamath 34:27 Mm-hmm.

Nikesh Arora 34:28 Over time, it's building some judgment as based on pattern recognition, what is good, what is bad, what is right, what is wrong. Over time, as you feed it more, it's starting to get PhDs, and starting to pass the bar-

Nikhil Kamath 34:38 Mm-hmm

Nikesh Arora 34:38 ... and it's starting to get smart enough to, you know... So it knows the entire world's information. Your problem set is known. Your answer set is known. It's able to answer the questions, able to get smarter and smarter. Now, given the breakneck speed at which you're, you're, you're seeing the evolution of models, they're getting smarter and smarter, and there's sort of an arms race, no pun intended, between all these people. And yes, so will people build smarter and smarter and bigger and bigger brains? Yes.

Nikhil Kamath 35:03 Mm-hmm.

Nikesh Arora 35:03 But if in your company at ZeroDa or at Palo Alto Networks, we said, "Hey, here's a really smart person."

Nikhil Kamath 35:08 Mm-hmm.

Nikesh Arora 35:08 "They have the best brain in the world."

Nikhil Kamath 35:10 Mm-hmm.

Nikesh Arora 35:11 Eventually, you have to adapt that brain to the problem you're solving.

Nikhil Kamath 35:14 Mm-hmm.

Nikesh Arora 35:15 Right? That's the art of building something on top. That's the art of creating a wrapper around that brain and applying it to something. Could I take the smartest brain? I could.

Nikhil Kamath 35:26 Mm-hmm.

Nikesh Arora 35:26 I have to teach it everything about drugs and say, "The problem you're trying to solve is solve cancer, solve the problem." But it requires teaching that brain, training that brain, putting guardrails around the brain, making sure the same brain that can solve cancer can also cause cancer, right?

Nikhil Kamath 35:40 Mm-hmm.

Nikesh Arora 35:40 If it's smart enough. So you gotta figure out, you gotta apply it to good.

Nikhil Kamath 35:42 Mm-hmm.

Nikesh Arora 35:42 So I think the act of wrapping these models or brains with useful things that we want it to do, will be where the art will be, and which is what I think our mutual friend is talking about, building applications around them-

Nikhil Kamath 35:55 Mm-hmm

Nikesh Arora 35:56 ... perhaps.

Nikhil Kamath 35:58 As an investor, better use of my dollar to be building a wrapper on a brain or trying to secure the brain?

Nikesh Arora 36:05 Well, clearly, the trying to secure the brain, you're asking my question.

Nikhil Kamath 36:11 [laughing]

Nikesh Arora 36:11 The cybersecurity, I'm just trying to-- I'm still staying in the philosophical part of it. [laughing] Okay. Uh, look, I think everybody who's solving a problem, necessary or unnecessary, right?

Nikhil Kamath 36:26 Mm-hmm.

Nikesh Arora 36:27 I mean, the application world, some people are solving necessary problems, some people unnecessary problems.

Nikhil Kamath 36:31 Mm-hmm.

Nikesh Arora 36:31 We really need more social-

Nikhil Kamath 36:32 Mm-hmm

Nikesh Arora 36:32 ... you know, media and social applications, possibly not, but somebody's trying to solve it. I think everybody is going to see how they can apply this brain towards solving their specific problem. And as an investor, a lot bigger share shifts will happen-

Nikhil Kamath 36:48 Mm-hmm

Nikesh Arora 36:49 ... in what is, I'll say, a stabler ecosystem for now.... A lot of people will lose share, a lot of people will gain share, depending how they use the brain to solve the problem. Which is what happened in the last technological inflection, right? Why does Amazon exist? They s- they used the, the technology inflection of the internet and connectivity to solve the problem, known problem differently, and caused a share shift between traditional retail and today, right?

Nikhil Kamath 37:10 Mm-hmm.

Nikesh Arora 37:10 Why did Google exist? Because it shifted outline, you know, traditional advertising, online advertising, because it's used the inflection point of the internet and mobility, et cetera, to cause that to happen. So the question is, or the point is, people will use this technology inflection of democratization of intelligence-

Nikhil Kamath 37:25 Mm-hmm

Nikesh Arora 37:26 ... to create, to solve the same problem differently. And the ones who solve it differently, faster, much more efficiently, lower friction, lower cost, better economic value, and better outcome, are gonna have a disproportionate share shift in their direction from legacy players. Now, and if I, if I had a dollar for every time I heard a legacy player saying, "I'm smart, this time I'll figure it out"-

Nikhil Kamath 37:46 Mm-hmm

Nikesh Arora 37:46 ... then none of the new economy industry should exist and startups shouldn't exist. So by definition, people will build better solutions, better mousetraps, and the idea, the opportunity for investor has never been larger in that context than just focusing on securing the model. Which it will, will- which look, which will not be non-lucrative.

Nikhil Kamath 38:04 Mm-hmm.

Nikesh Arora 38:05 But it's almost securing the model is harder to discern which person is gonna secure the model better. It's easier, possibly as an investor to say, take a human experience and say, "I get it." That experience can be fundamentally transformed by applying smarter, more intelligence to it.

Nikhil Kamath 38:19 And securing a model might not be so interesting if so many models get to the point where they're almost the same.

Nikesh Arora 38:26 Leave that to us, we'll take it. [laughing] Another le- legacy incumbent saying, "Oh, we've got this problem solved." [laughing]

Nikhil Kamath 38:32 Very

Nikhil Kamath 38:33 interesting. So that was from an investor's lens. Me, as a young person starting a company, how do I look at cybersecurity? How do I... What, what are the three things I have to do?

Nikesh Arora 38:47 Broadly starting a company, or just you want to start a cybersecurity company?

Nikhil Kamath 38:49 No, no, broadly starting a company. I'll come to starting a cybersecurity company in the end.

Nikesh Arora 38:54 Look, what's fascinating is, um, for the first time in my life, from a technology perspective, I'm seeking out young twenty-three or twenty-five-year-old founders to learn from them. Normally, I'm the sage old man with white hair, and people come to me and say: "Hey, can we talk about starting a company, and how do you-

Nikhil Kamath 39:14 Yeah

Nikesh Arora 39:14 ... scale it? How do you make it bigger? How do you live a life like yours at Google, SoftBank, or Palo Alto?" Right now, I'm re- I reached out to the founder of, you know, Windsurf, or I reached out to the founder of, you know, uh, Console.ai or Factory, and I'm sitting down and picking their brain. This morning, I, I was talking to a founder of an autonomous car company saying: "Tell me how this new world works. How do you see it? How does this AI gonna impact it? How are you building a company which is so fundamentally different than mine?" Because I'm sitting there saying, "I might be legacy." Because technology is moving so fast, and it's being done so differently. And I read about these companies which hit hundred million in ARR, not that it's, you know, it's, it's an achievement, but it's, it's much faster than anybody else that are doing it. I see people who say-

Nikhil Kamath 39:54 Yeah

Nikesh Arora 39:55 ... "Oh, I, I was watching an exchange on, on X between two people saying, 'Well, thank you, we built this feature in seventy-two hours and shipped it. It couldn't have been done between the two of our companies if you guys hadn't put your heart and soul to it. And oh, by the way, thanks to our coding agent.'" So I'm sitting saying, the pace of innovation-

Nikhil Kamath 40:11 Mm-hmm

Nikesh Arora 40:11 ... has fundamentally inflected, and I feel like I just don't want to be sitting here, you know, gazing at my own navel saying, "Oh, my God, you know, we've got this covered." So it hasn't been more uncertain than today.

Nikhil Kamath 40:24 Right.

Nikesh Arora 40:25 So a- all I can advise people who are out there is, uh, you know, teach us something [laughing] because they've got it figured out.

Nikhil Kamath 40:33 Yeah.

Nikesh Arora 40:33 But more so, I think the n- the, the wave of technology that is coming is gonna allow people to build businesses faster-

Nikhil Kamath 40:41 Mm-hmm

Nikesh Arora 40:41 ... more agility, a lower number of people, and fundamentally rethink them.

Nikhil Kamath 40:45 Mm-hmm.

Nikesh Arora 40:46 And if you're not doing that, if your rethink is marginal-

Nikhil Kamath 40:50 Mm-hmm

Nikesh Arora 40:50 ... if you're looking for a ten, twenty percent improvement, don't bother, because things are about to move ten X. So I think self-reflect on the idea. If your idea is not ten X worthy, you're solving the wrong problem.

Nikhil Kamath 41:03 I feel the exact same way. I've met a bunch of really bright kids every day for lunch and dinner the last week, and I just feel stupid. Like-

Nikesh Arora 41:12 [laughing]

Nikhil Kamath 41:13 ... I'm like, that's why I'm here for longer than I was meant to, and I want to come back because I feel like suddenly this area has become some kind of a hub.

Nikesh Arora 41:23 It's fascinating, you know, two or three years ago, and it happens every four or five years, right?

Nikhil Kamath 41:28 Mm.

Nikesh Arora 41:28 You know, I moved here in two thousand and nine, and I, I just moved because I was, you know, gonna be part of Google's team. Uh, uh, and I moved here at that point in time, the, the buzz was social, right? You know, it was Snapchat and Facebook, and, and YouTube was going from strength to strength, and Instagram was getting bought, and, you know, WhatsApp was getting bought. And that was kind of the time in, in, you know, two thousand nine, ten-ish timeframe. And then people say: "Oh, my God, this, this wave is coming to an end. What's gonna happen?" And suddenly, so the crypto wave arrived. Like, suddenly everything was crypto around you, and there was crypto, crypto, crypto, blockchain-

Nikhil Kamath 42:03 Mm-hmm

Nikesh Arora 42:04 ... you know, whole bunch of coins and whole bunch of stuff, the SPAC wave. And again, people call the end of San Francisco and said: "Oh, my God, it's a city you can't go to." And suddenly, it's the AI wave.

Nikhil Kamath 42:13 Mm-hmm.

Nikesh Arora 42:13 AI companies out there buying up real estate in San Francisco-

Nikhil Kamath 42:16 Yeah

Nikesh Arora 42:16 ... and building businesses. And if you ask the world, where is the hub of AI? It seems to be here. Every AI model that is being built-

Nikhil Kamath 42:25 Mm-hmm

Nikesh Arora 42:25 ... with a reason, except perhaps in China, is headquartered

Nikesh Arora 42:28 here.

Nikhil Kamath 42:29 Do you think India should try and build a model? We are trying.

Nikesh Arora 42:33 Um, we should. I think the question becomes, is a CapEx question. You know, uh, we can talk, I mean, you're much smarter about the Indian ecosystem than I will ever be. India has not shown a propensity for large CapEx projects with unclear returns.... mm-hmm, perhaps is the best way to say it.

Nikhil Kamath 42:55 Yeah.

Nikesh Arora 42:55 Right? Uh, you can't walk around and raise fifty billion dollars-

Nikhil Kamath 43:00 Mm-hmm.

Nikesh Arora 43:01 -uh, and build two nuclear plants to fund AGI today, irrespective of who you are and irrespective of who your investors are from the Indian subcontinent.

Nikhil Kamath 43:14 Yeah.

Nikesh Arora 43:15 And, you know, so that, that's where I think the, the constraint there is the appetite for people to deploy large amounts of capital.

Nikhil Kamath 43:23 I agree with you, but on the flip side, in a world which is getting increasingly fragmented on the geopolitical lens, and tariffs, and all of that, the question is also, if somebody turns off a tap that we have built so much upon, what happens then?

Nikesh Arora 43:41 Explain that.

Nikhil Kamath 43:42 Like, let's say we've used a model based out of China as the base to a lot of stuff that we have worked on, and one day they shut it down, and India doesn't have its own. What happens then?

Nikesh Arora 43:52 Look, there will always be the next version of the model.

Nikhil Kamath 43:56 Mm-hmm.

Nikesh Arora 43:57 So even if you were using one, and they didn't-

Nikhil Kamath 43:59 You can transition quickly

Nikesh Arora 44:00 ... give you access to the new one, then you have the less smarter model because the next one's smarter, faster, better, cheaper, right? So that, that risk is constantly there. It's not just access to the current model that you have.

Nikhil Kamath 44:10 Mm-hmm.

Nikesh Arora 44:11 Um, one would hope that with the arms race we talked about, there's north of ten thousand models on Hugging Face, many of them-

Nikhil Kamath 44:20 Yeah

Nikesh Arora 44:20 ... open source. So at least there is state- there is art out, the prior art out there, which allows you to experiment and play with it. But I think-

Nikhil Kamath 44:26 But even when they open source a model, they don't open source the weights they have used. They-

Nikesh Arora 44:31 There are some models-

Nikhil Kamath 44:31 Open source in train

Nikesh Arora 44:31 ... you can modify weights. So look, I understand the value of having a frontier model of your own, where you can control your own destiny. It comes at a high cost today. The question is, yes, should... I mean, the unequivocally answer-

Nikhil Kamath 44:44 [chuckles]

Nikesh Arora 44:44 ... is, yes, we should-

Nikhil Kamath 44:45 Yeah

Nikesh Arora 44:45 ... in India. The question is: who has the financial capacity-

Nikhil Kamath 44:48 Yeah

Nikesh Arora 44:48 ... and desire to go deploy tens of billions of dollars to go fund that, and where is the talent-

Nikhil Kamath 44:54 Mm-hmm

Nikesh Arora 44:54 ... to go do that? If both those conditions are met, yes, we should, and then you'll talk about power. Where is the, uh, you know, where is the gigawatts needed to go fund that-

Nikhil Kamath 45:03 Yeah

Nikesh Arora 45:03 ... training of the model? So the other option is, you find models that are out there. Uh, again, not attempting to prophesize because we agreed we weren't gonna do that. Uh, but there is hope that the current pace of development that is going on in the model world-

Nikhil Kamath 45:20 Mm-hmm

Nikesh Arora 45:20 ... everybody wants access to various talent pools who can leverage those models, because that creates market share.

Nikhil Kamath 45:27 Mm-hmm.

Nikesh Arora 45:28 So, uh, I'm hopeful that if, you know, geopolitical conditions don't get so bad that nobody's talking to each other, which I hopefully will not arrive-

Nikhil Kamath 45:36 Mm-hmm

Nikesh Arora 45:36 ... there will always be the possibility of collaborating with a model somewhere in the world-

Nikhil Kamath 45:41 Right

Nikesh Arora 45:42 ... which will be willing to work in a part of the world which has one point eight billion people, give or take. You know, just twenty-four, twenty-two, twenty-

Nikhil Kamath 45:51 Yeah

Nikesh Arora 45:51 ... percent of the world's population. You'd want that model to be experimenting in that kind of environment, with so many smart people, with such a large middle class, with so much progress ahead of it-

Nikhil Kamath 46:02 Yeah

Nikesh Arora 46:02 ... that it would be silly to ignore that market, the needs of that market from a model provider perspective.

Nikhil Kamath 46:08 And data of a hundred and one and a half billion people is equally appetizing.

Nikesh Arora 46:11 That's right.

Nikhil Kamath 46:13 Very interesting. Coming back to the cybersecurity question, uh, you told me as an investor, what niche I can look at, the verticals. You told me as a entrepreneur, if I want to start a company, what are the things I should watch out for? What kind of cybersecurity company I should try and build.

Nikhil Kamath 46:32 The last thing I wanted to ask you on AI is, somebody described it to me in this manner, that they said world output is about a hundred trillion dollars. Let's assume fifty, fifty percent of that is in services. Even if AI is able to disrupt ten percent of that, five trillion dollars, will justify all the money spent on infra and CapEx that has gone into the world of AI right now?

Nikesh Arora 46:59 Right.

Nikhil Kamath 47:00 If you were to have a dollar to invest into every AI company today, do you think it's overinflated? Do you think it'll make money in a decade at today's valuation?

Nikesh Arora 47:11 That's a hard call, right? Now, normalizing for execution, some people will execute better than the others.

Nikhil Kamath 47:19 Mm-hmm.

Nikesh Arora 47:20 Right? Some people will be able to sustain better than the others, and as you know better than I do, in the world of businesses which are not making money, you- your survival is only guaranteed till the next fundraise.

Nikhil Kamath 47:34 Yeah.

Nikesh Arora 47:34 Right?

Nikhil Kamath 47:35 Yeah.

Nikesh Arora 47:35 So if I had a dollar to give, and you said, "Well, you're making money in ten years," the question is, can you sustain the fundraising through that period until you turn cash flow positive?

Nikhil Kamath 47:44 Mm-hmm.

Nikesh Arora 47:44 Otherwise, we've seen companies which have gone away-

Nikhil Kamath 47:47 Mm

Nikesh Arora 47:47 ... because they were not able to raise their next round, or the round was so dilutive that nobody wanted to deal with it or... So, you know, all those conditions notwithstanding, I think it's a bigger question from an economic value proposition you're asking. You know, is there enough there there here in the entire industry that it justifies what is being spent today?

Nikhil Kamath 48:02 Mm-hmm.

Nikesh Arora 48:03 But without regard for-

Nikhil Kamath 48:04 Mm-hmm

Nikesh Arora 48:05 ... which company you invest in, let's take the company dynamics out. Look, prima facie, it, it, it seems to be the prevailing wisdom, right? The fact that people are raising money have, you know, the companies that raised money at two billion dollars, six months ago raising money at four billion dollars, right now is unprecedented.

Nikhil Kamath 48:20 Yeah.

Nikesh Arora 48:20 You never heard that degree of development and conviction that is happening in the market today. So clearly, there is a gold rush. Now, we've seen past gold rushes.

Nikhil Kamath 48:28 Mm-hmm.

Nikesh Arora 48:28 So I'll give you the answer in two parts. You know, it's kind of like the, you know, overestimating the short term, underestimating the long-term answer, which is, I think the long-term trend-

Nikhil Kamath 48:40 Mm-hmm

Nikesh Arora 48:40 ... points towards something like you hypothesized, that there is enough opportunity to eliminate redundancy, run work, you know, repetitive tasks, and solving the same problem multiple times, which was never leverageable, right? Now, you hire a consulting firm to do a project in Company A, how many B, C, D, E through, you know-... Z are gonna pay the same amount of money to do the same project because there's no democratization of intelligence. Intelligence is captive, and it's being sold one at a time. When it's democratized, everybody gets the same time, which means it lowers the cost to deliver it. So that, if you apply that logic, the logic suggests that, yes, we can shave off a lot of, a lot of inefficiency, a lot of increased economic value tremendously, which should justify this desire to invest in democratizing intelligence. Which should justify the fact that once this democratized intelligence is made available generally to all of us, we will find a way of creating more economic value because we'll get faster, you know, higher quality, lower friction, and more competence/better output. Short term, it goes back to the execution questions as to which is the right one of these?

Nikhil Kamath 49:44 Yeah.

Nikesh Arora 49:45 Does it make sense? Is there enough, uh, economic value in the category-

Nikhil Kamath 49:50 Mm

Nikesh Arora 49:50 ... that you're putting billions of dollars to work, that it justifies the category? So I think all those questions, uh, it could be a Robin Hood moment. It could be people taking from the rich and giving to the poor. [chuckles]

Nikhil Kamath 50:00 [chuckles] I was having this conversation with someone last week on how we can get India to be a lot more innovative, and we were trying to figure out why, on the scale of innovation, uh, new ideas per se, not enough have been rooted from there in the past. We had this debate around a whole bunch of things, you know, budget for research in academia, stuff like that. But it seems to come down to one thing, that the risk capital available there, like you just said, a kid out of Stanford could get twenty million to go and build an idea.

Nikesh Arora 50:35 Actually, better still, a kid dropped out of Stanford.

Nikhil Kamath 50:37 Yeah. [laughing]

Nikesh Arora 50:37 They have a higher chance. [laughing]

Nikhil Kamath 50:39 Yeah, I met, like, two dozen of them last night-

Nikesh Arora 50:42 Exactly right. Yeah.

Nikhil Kamath 50:42 ... and the, I was telling them, the seniors who are just, like, finishing college, I'm like: "There has been no better time for anyone to have graduated from Stanford than you guys-"

Nikesh Arora 50:52 That's right.

Nikhil Kamath 50:52 " ... because whatever you come up with, you'll get funded."

Nikesh Arora 50:53 That's been true every five years, by the way, but okay.

Nikhil Kamath 50:55 Yeah. [chuckles]

Nikesh Arora 50:56 It's just you're telling us we're getting old, right?

Nikhil Kamath 50:58 Yeah.

Nikesh Arora 50:58 Right.

Nikhil Kamath 50:59 Yeah. But what do you think it is? What should India change? Is it risk capital?

Nikesh Arora 51:04 Like, this debate comes up everywhere, right?

Nikhil Kamath 51:06 Yeah.

Nikesh Arora 51:06 You know, for the last twenty-five years, I've been asked, you know, why is there one Silicon Valley-

Nikhil Kamath 51:11 Mm-hmm

Nikesh Arora 51:11 ... and why are there not many Silicon Valleys in the world? And, you know, you wanna make Silicon Valley of India in Bangalore, or Israel is the Silicon Valley of, uh... Sorry, uh, you know, uh, yeah, is the Silicon Valley, um, for cybersecurity, et cetera. I think it boils down to a combination-

Nikhil Kamath 51:28 Mm-hmm

Nikesh Arora 51:28 ... of things, and I think it's, it's hard to get the combination of things together in one place.

Nikhil Kamath 51:35 Mm-hmm.

Nikesh Arora 51:36 Uh, partly it's sort of things like you've identified, risk capital-

Nikhil Kamath 51:40 Mm-hmm

Nikesh Arora 51:41 ... is part, uh, talent and resources.

Nikhil Kamath 51:44 Mm-hmm.

Nikesh Arora 51:44 It's part, uh, infrastructure, it's part availability, all of that. It's part ease of doing business, and all those things sort of fit in a mixer, and you shake it and, you know, a lot of that gets in there. I think it's, it's also partly the acceptance of failure.

Nikhil Kamath 52:02 Yeah.

Nikesh Arora 52:03 Right? Culturally, I grew up there, and you grew up there.

Nikhil Kamath 52:06 Yeah.

Nikesh Arora 52:06 And maybe it's getting better now.

Nikhil Kamath 52:08 Yeah.

Nikesh Arora 52:08 Failure is not as easily accepted anywhere in the world but in Silicon Valley.

Nikhil Kamath 52:12 Yeah.

Nikesh Arora 52:13 There are founders here who've had companies fail and started second company and third company.

Nikhil Kamath 52:16 Yeah.

Nikesh Arora 52:16 There are founders who've, you know, done something wrong, come back and started companies, and the market gives them the benefit of doubt and funds them again and again and says, "Yes, I understand you have tremendous appetite for risk. Uh, you dream big." So it's partly that in terms of... I think a lot of it is cultural.

Nikhil Kamath 52:33 I agree with you a hundred percent. I have a speech trainer who's Israeli. His name is Michael, and he keeps telling me in the Israeli society-

Nikesh Arora 52:42 Yeah

Nikhil Kamath 52:42 ... people celebrate failure, especially in the startups and the-

Nikesh Arora 52:46 Yeah

Nikhil Kamath 52:46 ... tech companies out there. I don't know how to get people to incorporate that.

Nikesh Arora 52:49 But look, it's very interesting-

Nikhil Kamath 52:50 How do we change?

Nikesh Arora 52:50 I have bought twenty companies in the last seven years at Palo Alto, and for the most part, they've been startups. And I'd say more than fifty percent of them have been from Israel. But even there, there's a different risk trade-off post success.

Nikhil Kamath 53:03 Mm-hmm.

Nikesh Arora 53:03 I can meet founders here, look them in the eye, the founder will tell me, "Well, we're building a hundred million dollar company," without blinking. And it's like a kid who dropped out-

Nikhil Kamath 53:13 Mm

Nikesh Arora 53:13 ... two years ago, he's gonna be a hundred million dollar company. Israel, they feel very lucky if they build a billion-dollar company. They're happy to sell it and say, "I'm out. This is, this is an outcome I never expected."

Nikhil Kamath 53:23 Mm.

Nikesh Arora 53:23 So it's, it's, there's a lot of cultural stuff in there. There's a lot of cultural acceptance of failure, cultural sort of role modeling. Uh, it's kind of maybe it's in the water here. People think if I go to Silicon Valley, drink the water, it's gonna be a better outcome than if to drink the water in New Delhi or Gurgaon, right? So I, I think there's a lot of, lot of, a whole host of factors.

Nikhil Kamath 53:42 Mm-hmm.

Nikesh Arora 53:42 But I think capital is definitely, in today's world, especially where we are, capital is definitely a constraint.

Nikhil Kamath 53:48 Mm-hmm.

Nikesh Arora 53:49 And also don't forget, um, there's pattern recognition, right?

Nikhil Kamath 53:54 Yeah.

Nikesh Arora 53:55 Name the last five, twenty billion dollar companies that came out of the Indian ecosystem-

Nikhil Kamath 53:59 Yeah

Nikesh Arora 54:00 ... that live to tell the story.

Nikhil Kamath 54:02 Mm-hmm.

Nikesh Arora 54:03 So there's also that.

Nikhil Kamath 54:04 Mm.

Nikesh Arora 54:04 Like, you know, every time you turn around, it's gonna happen. It doesn't happen. People say, "Oh, my God, maybe there is more than ice that is visible to me, that holds me back from doing it."

Nikhil Kamath 54:14 Fair point.

Nikhil Kamath 54:15 So you went to IIT and then MS from Boston and MBA from Northeastern. That's-

Nikesh Arora 54:20 The other way around, but same difference.

Nikhil Kamath 54:21 That's a lot of studying.

Nikesh Arora 54:23 Not really. It's a lot easier to study in the US than it is in India, so-

Nikhil Kamath 54:27 Mm

Nikesh Arora 54:27 ... you could study and work here at the same time.

Nikhil Kamath 54:29 So it was study and work at the same time?

Nikesh Arora 54:31 No, the, the, I came here to go to business school at Northeastern. Uh, I wasn't smart enough to get into the IMs in India. They're too competitive.

Nikhil Kamath 54:39 But you were at IIT-

Nikesh Arora 54:40 I was at IIT

Nikhil Kamath 54:41 ... which is possibly more competitive.

Nikesh Arora 54:42 Well, that point in time, a lot less than it is today, but I think they have more of them right now than they were then. I was there, it was about six of them, and we were called ITB. We're not even IIT. We're not even a full-fledged IIT at that point in time. Uh, yeah, I did that. Couldn't get into business school in India. I didn't even try that hard. I think I left in the middle of the CAT exam and went to watch a movie with-... uh, my girlfriend at that point in time, so maybe it was me. Um, came to the US. Uh, they said I have to teach computer science. I hadn't studied computer science, it was a slight problem, so I spent the summer brushing up on whatever I could learn, and I taught computer science at Northeastern. I went to business school there. Um, it was '92 when I graduated, it was a recession. It was hard to get a job. Uh, I wrote 400-plus letters to people applying for a job and, you know, like, sometimes the printer ran out of ink, but I knew it was a rejection letter, but pretty much it said in the first sentence, but they forgot the signature part.

Nikhil Kamath 55:36 Mm-hmm.

Nikesh Arora 55:36 So I had, like, 400... I still have them. I have 400 rejection letters of my life lying in my house, and one theme that was kind of persistent through all of them when I applied, 'cause, you know, you know how you have, like, those yearbooks?

Nikhil Kamath 55:47 Yeah.

Nikesh Arora 55:47 My MBA yearbook said, "Most likely to end up on Wall Street."

Nikhil Kamath 55:52 Mm.

Nikesh Arora 55:52 My Wall Street rejection said, "Not into finance." There's a bit of a cognitive disconnect between my peers and-

Nikhil Kamath 55:57 Yeah

Nikesh Arora 55:58 ... and the Street. And, uh, so that's why I got a master's in finance from BC. I felt like I had to compensate for lack of finance, and I ended up getting a CFA as well at that point in time. Yeah, but that's what caused the, the back-to-back two degrees, and I was lucky enough to... In those days, I think systems weren't as robust. I had seven rejection letters from Fidelity before I got a job for the eighth person, so thank God they weren't comparing notes.

Nikhil Kamath 56:23 Does education hold the same value today? In today's world, would you spend as many years doing what you did?

Nikesh Arora 56:30 You know, the older we get, the more we value education and experience.

Nikhil Kamath 56:34 Mm-hmm.

Nikesh Arora 56:35 The younger we are, the more irreverent we are of experience and education. So I-

Nikhil Kamath 56:39 I think I, I agree with-

Nikesh Arora 56:40 Staying the stereotype, I should value education [chuckles] and experience more.

Nikhil Kamath 56:43 So you don't have to.

Nikesh Arora 56:44 But I think the 22-year-old kid who I met, who's building a hundred billion dollar company, will tell you that I'm full of shit and all my experiences are not-

Nikhil Kamath 56:50 Yeah

Nikesh Arora 56:50 ... and he's got more risk appetite than I do.

Nikhil Kamath 56:52 Yeah. Outside of experiences, would you go back and do the education if it took you eight years, ten years, how much ever time it did take?

Nikesh Arora 57:00 You know, for somebody who had never worked in the Western culture, who had never spent much time interacting with people here, I always say education is as much a social experience as it is a learning experience.

Nikhil Kamath 57:15 The network that you built?

Nikesh Arora 57:17 No, not even the network. I mean, like, I have young kids, right? And I run into people in Silicon Valley, especially where the debate is, "Oh, I'm homeschooling my kids because school is not smart enough to teach my kids." And you run into this all the time. People say, "I gotta homeschool my kids." Now, of course, I don't know how you get through life as a parent. You have to arrange every sport, game, every... Like, literally-

Nikhil Kamath 57:33 Yeah

Nikesh Arora 57:33 ... you are now the orchestrator of your child's schedule, but-

Nikhil Kamath 57:36 Yeah

Nikesh Arora 57:36 ... let's put that aside. They have this perception that, "My kid doesn't learn enough."

Nikhil Kamath 57:40 Mm.

Nikesh Arora 57:41 But then the question I ask is, when you go to school, there are 10 kids in the class or 20 kids in the class, you learn social interaction, you learn competition, you learn not getting what you ask for on a constant basis. You learn not getting attention from people. You learn different personalities, how to interact with them. That's a social experiment.

Nikhil Kamath 57:57 Yeah.

Nikesh Arora 57:57 Now, if you're gonna be so smart that you don't need people around you, yes, God bless you, and maybe that's a good thing for you to do, but I think 99.9% of us need people. So to some degree, the collective learning experience is important, and, uh, it sets you up on how to live life around people, how to live life around different personalities. Now, if you spend too much of your time over there, you become an academic-

Nikhil Kamath 58:21 Yeah

Nikesh Arora 58:21 ... and all you do is learn how to prophesize and, and write papers. And so would I go back and do as much? Maybe, maybe not. But at that point in time, that was the benchmark.

Nikhil Kamath 58:31 If it were a social experiment, I would probably learn more or be better off with more diversity, right? So rather than going to an affluent college, where everybody's the similar... You know, they have either an IQ or some kind of other thing that has brought them there. Would I be not better off just going to a park and playing with different kind of kids for eight hours a day?

Nikesh Arora 58:54 Uh, sure. But if you had to make peace with the same people and see them every day for two years, it'd be much nicer and much more different and much more managed. If you showed up at the park and say, "I don't like these kids, I'm not coming tomorrow," and you play with a different set of kids, you have no skin in the game.

Nikhil Kamath 59:10 Right.

Nikesh Arora 59:10 Like, you know, in families-

Nikhil Kamath 59:11 Not college is skin in the game.

Nikesh Arora 59:12 We love our families, and we hate parts of our families, but we're stuck with them. So you gotta go-

Nikhil Kamath 59:16 That's why people drop out of free colleges more than they drop out of paid colleges, in a way.

Nikesh Arora 59:21 Didn't know that, but-

Nikhil Kamath 59:22 [chuckles]

Nikesh Arora 59:22 ... possibly true.

Nikhil Kamath 59:24 Right.

Nikhil Kamath 59:26 So you transitioned to tech after Fidelity. That's a completely different career.

Nikesh Arora 59:31 Not quite.

Nikhil Kamath 59:32 Mm.

Nikesh Arora 59:32 You know, we could say IIT was tech or is tech.

Nikhil Kamath 59:34 Mm-hmm.

Nikesh Arora 59:35 When I went to business school, I was teaching some version of tech. Uh, at Fidelity, actually, I worked in their technology department in finance the first five years I was there. So still analyzing tech, the wrong tech. When I went to Putnam, I was analyzing tech and telecom as a buy-side analyst. So I was always paying attention to the business of tech, perhaps is a better way to describe it. I was never spending time coding or writing code. Uh, if I did, maybe I'd have founded a company myself and be much smarter. But no, I was always involved in the business of tech.

Nikhil Kamath 1:00:07 Right.

Nikhil Kamath 1:00:08 That's actually, uh, a novelty, which is a new thing almost in society, where not founders of company, but executives, I think you're like the poster child of that, who become extremely wealthy and billionaires and all of that. Do you see a diff-

Nikesh Arora 1:00:24 As I'm sorry, I'm, I'm trying to find where the slur is in that, but go on. [chuckles]

Nikhil Kamath 1:00:28 [chuckles] So these two paths of, of either founding a company or being an executive like yourself, I think there's a smaller crowd like you, which have done exceptionally well. How do you think those journeys are different, and what kind of personality type is suited for which?

Nikesh Arora 1:00:49 That's an interesting question. Look, we live in Silicon Valley, so, you know, there was a big debate, as you may remember, maybe twelve, fourteen, eighteen months ago. Brian Chesky sparked it off, the founder mode-

Nikhil Kamath 1:01:00 Mm-hmm

Nikesh Arora 1:01:00 ... where somehow-

Nikhil Kamath 1:01:01 Yeah

Nikesh Arora 1:01:01 ... founders were more, uh-... had a higher moral right-

Nikhil Kamath 1:01:08 Yeah

Nikesh Arora 1:01:08 ... to go run, build great businesses long-term and bigger ones than possibly executives. And I think, look, at the end of the day, eventually, a company, company is a combination of a product and a business around it.

Nikhil Kamath 1:01:20 Mm-hmm.

Nikesh Arora 1:01:21 A product-only company is not a company. Eventually, somebody has to show up with the economics for that product to-

Nikhil Kamath 1:01:27 Yeah

Nikesh Arora 1:01:27 ... have been worthy of being invested in. We just had this conversation about AI.

Nikhil Kamath 1:01:30 Mm-hmm.

Nikesh Arora 1:01:30 You know, $5 trillion of services will be saved, hence it makes sense to invest all this. Now, the question becomes, you know, horses for courses. What is the right time for a product-impassioned individual to go ahead and build the best product in the world, as long as they can get the right capital attracted to go build a product? At what point in time does that product need to be wrapped with the right application or business model-

Nikhil Kamath 1:01:59 Mm

Nikesh Arora 1:02:00 ... where it becomes a business that actually generates value for the buyer or the other side? Now, I think the answer is slightly different in, let's call them consumer businesses and enterprise businesses. In the consumer business, you can build a great product, you can create value, and you can find some basic, fundamental economic mechanism, like charge a subscription-

Nikhil Kamath 1:02:20 Mm

Nikesh Arora 1:02:20 ... or sell advertising against it. Those are a little easier. Advertising is harder than subscription. If you're running Netflix, at the end, you pay 19 bucks, you don't pay 19 bucks, I'm gonna keep working the product, and then you should pay me 19 bucks, right? And I have to worry about each one of you because there's so many of you.

Nikhil Kamath 1:02:33 Mm-hmm.

Nikesh Arora 1:02:33 If some leave, it's okay. There are many consumer businesses where you're fundamentally a product company with distribution and marketing, right? And then over time, your moat becomes distribution, and your product sometimes doesn't stay as good, but you still own distribution. Right? There are examples of that in the world. But eventually, if you don't build a good product, though, even those companies begin to peter off, so let's leave it there. In that case, it perhaps makes even more sense for a founder to persist-

Nikhil Kamath 1:02:58 Mm

Nikesh Arora 1:02:58 ... where there's this constant need to product innovate because that drives the entire distribution and consumption of the product. In the case of enterprise, you see a different variation, and if you look at this example used of executives, I saw a recent article somewhere, it talks about executives. I'd say 75% of those executives named there are actually enterprise CEOs.

Nikhil Kamath 1:03:18 Mm-hmm.

Nikesh Arora 1:03:19 Not consumer CEOs, funnily enough. And the reason is because enterprise is a combination of great product, building a business ecosystem around it, and making sure that you build an effective motion around delivering that innovation to various businesses, which is a combination of not just like... I met a founder the other day of an enterprise company. He say, "I love building the product. I hate going to cu- customers and trying to explain to them why this is a great product. I lose patience because they don't understand why this is a great product, and then eventually, I have to take them to dinner to get them to buy."

Nikhil Kamath 1:03:51 Mm-hmm.

Nikesh Arora 1:03:52 And the founder doesn't like that. He wants to build a great product. Business executives say that's par for the course, you know? "I gotta do all of these things that about..." So, look, I am as product-obsessed and petrified as they come.

Nikhil Kamath 1:04:06 Mm.

Nikesh Arora 1:04:06 I'm constantly, you know, challenging myself, especially my biggest, you know-- as I said to you, my, one of my current fears is what happens with AI-

Nikhil Kamath 1:04:14 Mm

Nikesh Arora 1:04:14 ... does it makes all of-- does it make all of us obsolete in the way we run our businesses and the way we build our products and the product we build? So there's an existential crisis with AI around all those three dimensions for most companies in tech right now. So, then the question becomes, you know, and this, you know, goes past founder or executives to the notion of, what kind of team does it take to win? Like, I tell my team, "You're the best at what you do, but I reserve the right to jump in and help you do what you do. My job is not to do what you do. I can't do everything my CFO does. I can't do everything my chief product officer does. I can't do everything that my chief marketing officer says." Am I... You know, have I seen it? I've been around long enough. Have I seen it? Have I done it enough? Yes, I have. So I can jump in and work with them on certain things. Course correct, point to the right North Star as we're all going there? Yes. So then I just need to make sure that I am paired-- I've paired myself with a phenomenal set of technical people who are as product-savvy as they come, and sometimes you'll find great technical people, but they, they don't dream as big as founders. They're not bad technical people; they're equally smart. They just don't have the risk appetite.

Nikhil Kamath 1:05:19 Mm-hmm.

Nikesh Arora 1:05:19 I can bring the risk appetite. So I think part of winning, and I'm sure you see that in your business, part of winning is surrounding yourself with the right team, not just the best at what they do-

Nikhil Kamath 1:05:29 Right

Nikesh Arora 1:05:30 ... but the right intermix-

Nikhil Kamath 1:05:31 Mm-hmm

Nikesh Arora 1:05:32 ... of the people and personalities you need. And I think that's been one of the things that I've been particularly excited about having done in my life, whether it was a team I built at Google, and the people I worked with at SoftBank, or people I built at Palo Alto Networks. I think we've found the formula where we can find the right set of people who complement each other and bring the right balance of conservatism, risk appetite, execution, and ideas, and competence that allows us to at least try and a- aim for above-average outcome.

Nikhil Kamath 1:06:01 So in a way, you're saying the, the mark of a great leader in enterprise is hiring the best lieutenants?

Nikesh Arora 1:06:08 Uh, I think you're oversimplifying it-

Nikhil Kamath 1:06:10 Mm

Nikesh Arora 1:06:10 ... but, uh, I won't take the bait. Uh, I think the mark of any winning leader-

Nikhil Kamath 1:06:15 Mm

Nikesh Arora 1:06:15 ... is mobilizing a set of very good people around them-

Nikhil Kamath 1:06:19 Mm-hmm

Nikesh Arora 1:06:19 ... to create great outcomes.

Nikhil Kamath 1:06:21 Right.

Nikesh Arora 1:06:22 And it doesn't have to be just the hiring part. hiring is not enough. You've gotta make sure that they perform. You know, hiring is just the beginning of the journey, and you have to make sure you're constantly course-correcting and adapting and making that happen, and you have to keep your eye on the North Star. It kind of tends to move sometimes.

Nikhil Kamath 1:06:38 The most vivid memory or recollection I have is, when you joined SoftBank, you were all over the news in India-

Nikesh Arora 1:06:47 And in Japan

Nikhil Kamath 1:06:47 ... for your salary and stuff.

Nikesh Arora 1:06:48 And in Japan as well, believe me. [chuckles]

Nikhil Kamath 1:06:51 And in Japan as well. [chuckles] How was that? How was that experience? How was Masa, how was working with him? How was it to be as popular as you were for your salary, of all things?

Nikesh Arora 1:07:00 That's, that's far for the course, but it's not what you aspire for. It's kind of, that's a way of keeping score. People keep score that way, right?

Nikhil Kamath 1:07:08 Yeah.

Nikesh Arora 1:07:08 That's the way it was like, you know-

Nikhil Kamath 1:07:10 Do you still keep score that way?

Nikesh Arora 1:07:12 ... No, it's the way people keep score. Uh, and again, it's a tough question to answer.

Nikhil Kamath 1:07:20 Yeah.

Nikesh Arora 1:07:21 What- there's no good answer to that question.

Nikhil Kamath 1:07:23 [chuckles]

Nikesh Arora 1:07:23 Right? If you say, "I keep score that way"-

Nikhil Kamath 1:07:24 Yeah.

Nikesh Arora 1:07:24 -then it makes it sound you're materialistic.

Nikhil Kamath 1:07:26 Yeah.

Nikesh Arora 1:07:27 If you say, "I don't care," it makes you sound like you don't care-

Nikhil Kamath 1:07:29 If you were to ask me, I would have said yes, that question to me.

Nikesh Arora 1:07:32 That's how people keep score, score.

Nikhil Kamath 1:07:33 Yeah.

Nikesh Arora 1:07:34 Again, I think being well compensated is a good outcome.

Nikhil Kamath 1:07:37 Yeah.

Nikesh Arora 1:07:38 Uh, you know, it sometimes becomes more or less, it's a different issue. Yeah, it's-

Nikhil Kamath 1:07:41 We live in a capitalistic world, and we all have voted for capitalism.

Nikesh Arora 1:07:45 That's how we keep score.

Nikhil Kamath 1:07:45 Yeah.

Nikesh Arora 1:07:45 Yeah, yeah. Although we, you know, we are constantly fighting the battle between democracy and capitalism, which sometimes end up at odds, but that's a different conversation.

Nikhil Kamath 1:07:51 Can't a democracies-- can't a democracy have capitalism?

Nikesh Arora 1:07:55 No.

Nikhil Kamath 1:07:55 I think we have democratically voted for capitalism.

Nikesh Arora 1:07:57 Uh, not quite. I, I was with this, uh, very interesting business person, uh, who tried to, you know, run for public office and did not succeed, and I asked her, I said: "What is the biggest..." You asked a question about the biggest glaring memory or fact. "What is the biggest difference in how you lived your entire life till you were fifty, and then you tried for five years? How was the biggest difference?" She's like, she's like: "You know, I'd classify my first fifty years of my life as an attempt to pursue capitalistic outcomes, and the next five years, democratic outcomes."

Nikhil Kamath 1:08:35 Mm.

Nikesh Arora 1:08:36 And she said, "The biggest difference in capitalism is one dollar, one vote. In democracy is, is one person, one vote."

Nikhil Kamath 1:08:44 Do you think it's one dollar, one vote today?

Nikesh Arora 1:08:46 In capitalism.

Nikhil Kamath 1:08:47 Yeah.

Nikesh Arora 1:08:48 Your shareholders decide. My largest shareholder can dictate what I should do if my hundred percent shareholder can fully tell me what to do.

Nikhil Kamath 1:08:54 Mm-hmm.

Nikesh Arora 1:08:54 In democracy, there's no one shareholder, right? There's no five shareholders, there's no five board members who have an higher weighted voice because they represent majority of the capital. So-

Nikhil Kamath 1:09:05 What system do you think America of today adheres to?

Nikesh Arora 1:09:10 Let's go back to the-

Nikhil Kamath 1:09:11 [chuckles]

Nikesh Arora 1:09:11 ... other conversation. I'm not a, I'm not a political commentator, so it's kind of like-

Nikhil Kamath 1:09:15 Right [chuckles]

Nikesh Arora 1:09:16 ... unless I probably put my foot in my mouth unnecessarily.

Nikhil Kamath 1:09:19 So after Google and after you joined SoftBank, how was it working with Masa? Just tell me, like, people that you worked with, like Larry Page, Masa, if there is one thing you've learned from each of them.

Nikesh Arora 1:09:30 You know, it's kind of it fits the way I think about people, because very often you get cliché questions like: "Who's your role model?"

Nikhil Kamath 1:09:36 Yeah.

Nikesh Arora 1:09:37 Or, you know, like I say, "Well-

Nikhil Kamath 1:09:38 Do you believe in the concept of role model?

Nikesh Arora 1:09:41 Uh, I believe in the concept of admiring people for something that they're really good at.

Nikhil Kamath 1:09:47 And not admiring thing, for other things they're not good at.

Nikesh Arora 1:09:50 Yeah, but like, you know, uh, we're... Our most interesting person in the world right now is possibly, you know, outside that, the, the, what is that guy? The, this Mexican guy who's the most interesting man in the world.

Nikhil Kamath 1:10:02 Still the most interesting-

Nikesh Arora 1:10:02 Never mind. There is, there is-

Nikhil Kamath 1:10:03 Yeah

Nikesh Arora 1:10:03 ... You can go back and Google it.

Nikhil Kamath 1:10:04 Yeah.

Nikesh Arora 1:10:04 But today, the most interesting person in the world is possibly Elon Musk, right? Everybody-

Nikhil Kamath 1:10:08 Yeah

Nikesh Arora 1:10:08 ... knows about him, everybody wants to know him.

Nikhil Kamath 1:10:10 Yeah.

Nikesh Arora 1:10:10 Now, you can admire him for a lot of things, but, you know, do I want to have fifteen children with five different people, or do I want to be, you know, in politics? So there are a lot of things that you can admire about Elon, there are some things you may not want to be. So I think modeling your entire life around one person is a big ask.

Nikhil Kamath 1:10:26 Yeah.

Nikesh Arora 1:10:27 I think admiring people for what they do, and when I turned forty, I made a conscious choice. I said, "From now on, when I meet people, I'm gonna think about what they're really good at." Because, you know, getting to forty, I went back and thought, "You know what? We have a tendency of looking through a filter and saying, 'Well, this person is not great because they're not great at X, or they don't do X or Y well.'" And then realize that you actually have a mental frame of what made you succeed.

Nikhil Kamath 1:10:51 Mm-hmm.

Nikesh Arora 1:10:52 And hence, people were more like your personality or did things like you, were more respectable or liked by you. And then, people who did it differently were not as interesting because perhaps they didn't have the right answer because they hadn't done it. But you can flip that lens and say, "You know what? Some people have succeeded in certain things in a way I would have never have imagined. There's something interesting. How do they do that?" And you look around, you know, you're blessed, and I'm blessed. We always run into people who achieve something in life-

Nikhil Kamath 1:11:18 Yeah

Nikesh Arora 1:11:18 ... or about to. Your twelve founders, I'm sure, are gonna be great in ten years from now, or-

Nikhil Kamath 1:11:22 Mm

Nikesh Arora 1:11:22 ... some of the people you and I mutually know are probably great at what they do.

Nikhil Kamath 1:11:25 Yeah.

Nikesh Arora 1:11:25 So in that context, you can look at people and say: "What do I admire about these people?" And you mentioned people I've worked with. Look, I remember a conversation Larry recited to me when he'd just come back after meeting Steve Jobs. I never met him, but Larry did. And Steve had called Larry and said, "You know what?" In that time, Google was a small company, and-

Nikhil Kamath 1:11:41 Mm-hmm

Nikesh Arora 1:11:41 ... Apple was still a big company, and Steve said to Larry: "Larry, look at the model. The model is, we do one thing, we do it really well."

Nikhil Kamath 1:11:48 Mm-hmm.

Nikesh Arora 1:11:49 "If you do one thing really well and win around the world, you're gonna win." And here was Larry, you know, busy doing Gmail, Chrome, Google Search-

Nikhil Kamath 1:11:58 Right

Nikesh Arora 1:11:58 ... Maps, Local, a whole bunch of stuff. And Larry had a different point of view. He said: "Look, I don't believe that. I believe it's a, it's a question of capacity. If you have great people, you can motivate them, they can go build great stuff."

Nikhil Kamath 1:12:11 Mm-hmm.

Nikesh Arora 1:12:12 "As long as you focus on building a great product, doesn't matter if you do one or many." So Larry was product obsessed. In fact, you know, much to my annoyance, perhaps at that point in time, but I see the wisdom of his ways. When he became CEO of Google, he said: "I'm gonna have ten direct reports. There's gonna be one CFO-

Nikhil Kamath 1:12:30 Mm-hmm

Nikesh Arora 1:12:30 ... one lawyer, and one business person, and seven product people." He said, "Nikesh, you can do all the business stuff."

Nikhil Kamath 1:12:38 Mm-hmm.

Nikesh Arora 1:12:39 And I was so proud. I went to my first one-on-one with Larry and said: "Hey, Larry, you know, we should chat." And I had this beautiful presentation ready to walk him through how we manage the thirty thousand people. And he looked at me, he says: "Bill Campbell tells me you're decent or good at what you do. Uh, I have to go build great products in the company, so you keep doing what you're doing. I'm sure if I had a few hours, I could help you do your job twenty percent better." I said: "Larry, let me know when you have two hours." And I left, and he never found the two hours for me because he was busy fixing product. He was product obsessed.

Nikhil Kamath 1:13:11 Mm.

Nikesh Arora 1:13:12 But he learned from him that... And he ceased to say that, you know, like-... tech companies which lose sight of great products eventually fail.

Nikhil Kamath 1:13:19 Mm-hmm.

Nikesh Arora 1:13:20 So, and you look around you, that is true in technology. You know, a company like Sun Microsystem, Yahoo!, all these companies are great tech companies at their, at their-

Nikhil Kamath 1:13:28 Mm-hmm

Nikesh Arora 1:13:28 - heydays, and eventually-

Nikhil Kamath 1:13:29 Right

Nikesh Arora 1:13:29 ... they lost sight of the product, and eventually they didn't, they didn't succeed.

Nikhil Kamath 1:13:32 Mm.

Nikesh Arora 1:13:32 Take Masa, you know? I say, as we grow up, we spend our life, perhaps more so in India, we talked about cultural things, right?

Nikhil Kamath 1:13:42 Yeah.

Nikesh Arora 1:13:42 We spend our life de-risking our children.

Nikhil Kamath 1:13:45 Mm. Explain.

Nikesh Arora 1:13:48 The kid is born, you walk your daughter to school, say, "Hold my hand."

Nikhil Kamath 1:13:51 Mm.

Nikesh Arora 1:13:52 "Every time you cross the road, you look left, you look right. Don't eat that. Don't touch that. That's dirty," right? "Don't put that in your mouth." How many times have your parents or my parents admonished us as a method of showing their love and trying to teach us the way of life, in constantly allowing- sort of taking from their mental model what was risky-

Nikhil Kamath 1:14:11 Mm-hmm

Nikesh Arora 1:14:11 ... what could have some consequence, and trying not to have their kids do that.

Nikhil Kamath 1:14:16 Mm.

Nikesh Arora 1:14:17 Right? And do that in life. And, of course, our favorite Indian pastor was like, "It's time you got old, it's time for you to get married and settle down," right? Because we're deemed unsettled-

Nikhil Kamath 1:14:25 Yeah

Nikesh Arora 1:14:26 ... and possibly prone to high risk-

Nikhil Kamath 1:14:28 Yeah

Nikesh Arora 1:14:28 ... if you're not married.

Nikhil Kamath 1:14:29 Yeah.

Nikesh Arora 1:14:30 So there's whole, whole sort of cultural philosophy-

Nikhil Kamath 1:14:33 Mm

Nikesh Arora 1:14:33 ... is to settle your kids-

Nikhil Kamath 1:14:34 Mm

Nikesh Arora 1:14:35 ... make them, make sure they have a stable job, stable life, kids, and they're fully settled. That's the best risk manager in the world, is your mother.

Nikhil Kamath 1:14:45 Mm-hmm.

Nikesh Arora 1:14:45 Right? And here we're sitting and talking about taking more risk, dreaming bigger, and building great things. So with that as a frame of reference, Masa was the, was the kid. You know, he turned 50 when I s- I started working with him, and I'd say between the age of 50 to 60, he was sort of Benjamin Button, right? He was going, touching everything his mother said, "Don't touch,"-

Nikhil Kamath 1:15:12 [chuckles]

Nikesh Arora 1:15:12 ... and he was eating, putting everything in his mouth, and being more and more risky-

Nikhil Kamath 1:15:16 Mm

Nikesh Arora 1:15:16 ... and big, dreaming bigger-

Nikhil Kamath 1:15:17 Right

Nikesh Arora 1:15:17 ... than anyone else I've known in my life. Forget any entrepreneur. Every entrepreneur was trying to take risk-

Nikhil Kamath 1:15:22 Mm

Nikesh Arora 1:15:22 ... to build a stable business and get rich.

Nikhil Kamath 1:15:24 Mm.

Nikesh Arora 1:15:24 Masa, the other way around: "What are we gonna do today? Great, all in." [chuckles] "So what are we doing tomorrow? I'm all in." Masa has a phenomenal risk appetite, and if you look at it, that's the way he led his life, and funnily enough, you know, he struck it four times.

Nikhil Kamath 1:15:40 Mm.

Nikesh Arora 1:15:42 You know, he built SoftBank from nothing. He built Yahoo! Japan, he built... He, he invested in Alibaba, he did Arm, all these things that worked for him. And by the way, you know, he had risk appetite-

Nikhil Kamath 1:15:54 Yeah

Nikesh Arora 1:15:54 ... because his volatility is high. He was the richest man in the world for a few days, and then he was almost bankrupt at one point in time. So you learn that, you know, risk appetite is actually something we govern, but it is significantly, uh, influenced culturally.

Nikhil Kamath 1:16:11 Seems like a good way to live. If we have one life, and life is meant to be experienced, Masa's way.

Nikesh Arora 1:16:17 Yes, Nikhil, I think that's, that's true, and you and I have the luxury to be able to say that.

Nikhil Kamath 1:16:22 Mm-hmm.

Nikesh Arora 1:16:23 Uh, it doesn't work well with Maslow's hierarchy.

Nikhil Kamath 1:16:26 Mm. Explain.

Nikesh Arora 1:16:27 You have to... Well, Maslow's hierarchy-

Nikhil Kamath 1:16:29 Yeah, I know

Nikesh Arora 1:16:29 ... suggests that you know what it is, and, like, you know, when you find a person who has no food and-

Nikhil Kamath 1:16:33 Mm-hmm

Nikesh Arora 1:16:34 ... no money and has to feed his family, he's not worried about taking more risk and living one life.

Nikhil Kamath 1:16:38 Mm.

Nikesh Arora 1:16:38 He's looking to create that stability.

Nikhil Kamath 1:16:40 Mm-hmm.

Nikesh Arora 1:16:40 So the risk appetite can change when you reach the aspiration state of your life. The point is, he recognized-

Nikhil Kamath 1:16:46 Do you think AI changes that, more people move higher up the order-

Nikesh Arora 1:16:49 [chuckles]

Nikhil Kamath 1:16:49 ... in the hierarchy?

Nikesh Arora 1:16:51 Oh, you're moving questions too fast. [chuckles]

Nikhil Kamath 1:16:53 [chuckles]

Nikesh Arora 1:16:53 I wasn't done with the last one, thinking through that one. But, uh, do I think AI changes our risk appetite? I don't think anything changes Maslow's hierarchy.

Nikhil Kamath 1:17:03 Mm-hmm.

Nikesh Arora 1:17:03 In fact, I think there is a risk in the short term that AI creates more fear around Maslow's hierarchy than not.

Nikhil Kamath 1:17:11 Because?

Nikesh Arora 1:17:13 Look, if you read everything out there, if you see the signs, it seems like, you know, repetitive tasks are gonna get easily overtaken by AI, and that's kind of be, you know, its contribution to society in the next two to three years, which directly targeted- targets the early in career part of people's lives and the part where they're trying to go pay their college loans in this country or where they're trying to set, settle down-

Nikhil Kamath 1:17:39 Yeah

Nikesh Arora 1:17:39 ... and, you know, get-

Nikhil Kamath 1:17:40 De-risk

Nikesh Arora 1:17:40 ... get, get sort of their basic needs met.

Nikhil Kamath 1:17:42 Yeah.

Nikesh Arora 1:17:42 So the question is, if I can't get out of college with a, with a, with a loan and find a job that I'm gonna be adding value on, then that probably impacts my, my Maslow's hierarchy more than it impacts my risk appetite.

Nikhil Kamath 1:17:56 But if there is no social mobility really in the world, and rich people stay rich people, and they stay higher up in Maslow's hierarchy, do you think generationally people become more risk-averse, so they're able to take risk more easily? Like, your kids or the kids of your kids-

Nikesh Arora 1:18:16 Yes

Nikhil Kamath 1:18:16 ... would be freer in taking risk?

Nikesh Arora 1:18:18 You know, it's kind of very interesting social experiment here.

Nikhil Kamath 1:18:21 Mm-hmm.

Nikesh Arora 1:18:21 Um, I can-- I think you can talk about predisposition, but not personality. What I mean by that is, because your kids or my kids are gonna grow up in a slightly different circumstance than perhaps you and I grew up with-

Nikhil Kamath 1:18:35 Mm-hmm

Nikesh Arora 1:18:35 ... they're gonna have different predispositions.

Nikhil Kamath 1:18:38 Mm-hmm.

Nikesh Arora 1:18:38 Like, you know, you know, when I grew up, my father didn't have a car-

Nikhil Kamath 1:18:43 Mm-hmm

Nikesh Arora 1:18:43 ... till I was 18, right? You know, we ate meat once a week-

Nikhil Kamath 1:18:47 Mm-hmm

Nikesh Arora 1:18:47 ... because that was the norm.

Nikhil Kamath 1:18:48 Same.

Nikesh Arora 1:18:49 Right? So that's a different-

Nikhil Kamath 1:18:52 Mm

Nikesh Arora 1:18:52 ... cultural upbringing than my kids.

Nikhil Kamath 1:18:53 Mm.

Nikesh Arora 1:18:53 My kids don't have those constraints, and they don't live with scarcity. So... But the question is, it's very hard, and this, you should ask a sociologist this question, as opposed to me, but it, it's very hard to take that and ascertain where the drive comes from. I've seen very well-to-do kids who have tremendous drive, who want to prove something. I've seen very poor kids with no drive. So there seems to be a difference of, you know, gene in you, which defines how you drive yourself and how you think about ambition and proving yourself. Uh, you know-... Yeah, I'm sure the, the, the upbringing, the factors around you have a role in finally defining what your passion is and where you go prove yourself. But I still feel that there's an inner drive that comes from something different for people, which is somewhat, uh, not 100% correlated to upbringing. Like, I have siblings. You have siblings?

Nikhil Kamath 1:19:51 Yeah.

Nikesh Arora 1:19:51 We're, we're very different, we're very different people. Parents-- Our parents are the same. We grew up in the same house. We grew up with the same value system, ended up with very different outcomes and very different motivations, very different ways of living our life. I don't know why that is.

Nikhil Kamath 1:20:04 So nature versus nurture, when you-

Nikesh Arora 1:20:07 Remember, nurture is the same.

Nikhil Kamath 1:20:08 Mm-hmm.

Nikesh Arora 1:20:09 You can argue majority of the DNA is the same.

Nikhil Kamath 1:20:11 Mm-hmm.

Nikesh Arora 1:20:12 Maybe, you know, one gene is more dominant than the other in certain cases, so-

Nikhil Kamath 1:20:15 Mm

Nikesh Arora 1:20:15 ... it's minor wa- modifications.

Nikhil Kamath 1:20:17 Right.

Nikhil Kamath 1:20:18 Any fleeting thought, Nikesh? I must say, this is one of my favorite podcasts ever. [chuckles]

Nikesh Arora 1:20:23 You must not have done many then. [laughing]

Nikhil Kamath 1:20:25 [laughing] I've loved this conversation. But any fleeting thought that you wanna, like, leave behind?

Nikesh Arora 1:20:32 I'll let you ask the question. It's too generic a comment. We can talk about anything you want.

Nikhil Kamath 1:20:36 [laughing] Okay, since you've given me that privilege, I give you $100-

Nikesh Arora 1:20:43 Mm-hmm

Nikhil Kamath 1:20:43 ... and I let you either go long or go short one sector for the next decade. Long one first.

Nikesh Arora 1:20:57 Look, by definition, technology is lifelong long, right? If you look historically, uh, 35% of the S&P is made of technology companies. Thirty years ago it was none, right? So by definition, what has happened is technology has taken over majority of sectors in life, and there's a possibility it'll continue to take majority of sectors in life. Um, I'm sure this is gonna come bite me in the future, but, uh, on the short side, services has to be a short.

Nikhil Kamath 1:21:25 Yeah.

Nikesh Arora 1:21:26 By definition, the whole idea of service is that we deploy humans towards repetitive tasks-

Nikhil Kamath 1:21:31 Mm-hmm

Nikesh Arora 1:21:31 ... where we sell intelligence or process with people. If, if the impending opportunity in front of us, if that process is gonna be simplified or overtaken by AI, and intelligence is gonna be democratized, then there has to be a reshaping of the services economy.

Nikhil Kamath 1:21:49 [upbeat music] Makes sense. But thank you so much for taking the time and doing this.

Nikesh Arora 1:21:54 My pleasure.

Nikhil Kamath 1:21:55 And, uh, hope to see you again soon.

Nikesh Arora 1:21:56 Thank you. [chuckles]

Nikhil Kamath 1:21:57 Thank you. Cheers!

Nikesh Arora 1:21:59 Well, I will make sure every time you made me do that, you'll just look it over, right? [laughing]

Nikhil Kamath 1:22:02 [laughing]

Nikesh Arora 1:22:03 All right, thanks. Nice to see you, man.

Nikhil Kamath 1:22:04 Was that fun?

Nikesh Arora 1:22:05 That was fun, yeah. [upbeat music]