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Nikesh Arora on The Future of Token Costs | Memory Becoming the Moat & Why Enterprise AI Isn't Ready

Nikesh Arora is the Chairman and CEO of Palo Alto Networks, the global cybersecurity leader. Since taking over in 2018, he has transformed the company from an $18 billion market cap business into one worth more than $225BN with more than 21,000 employees globally. Previously, Nikesh was President and COO of SoftBank, where he worked alongside Masayoshi Son and helped shape the firm's technology investment strategy. ----------------------------------------------- Timestamps: 00:00 Intro 00:52 Brand vs Product 05:09 The Breadth vs Depth Problem With Frontier AI Models 09:18 Enterprises Are Still Getting AI Wrong 14:53 AI Guardrails Aren't Robust Enough 29:46 Claude Mythos Changed Everything: Finding in 6 Weeks What Would Take 6 Years 33:46 Should Governments Intervene on AI? A Discovery Process 35:09 If Nikesh Started Palo Alto Today: The Waymo vs Tesla Approach 45:00 Agentic Security: Why You Need a Gateway for All Agent Traffic 52:48 Miss One Trick You Survive. Miss Three - You're Obsolete 53:04 Is the SaaS Sell-Off Justified? 59:27 Are Chinese Open Source Models a Real Security Threat? 01:03:45 What Nobody Tells You About Having Money 01:08:52 How to Be a Great Father Without Sacrificing an Inch on Work 01:10:53 Quick-Fire Round ---------------------------------------------------------------------------------------------- Subscribe on Spotify: https://open.spotify.com/show/3j2KMcZTtgTNBKwtZBMHvl?si=85bc9196860e4466 Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-twenty-minute-vc-20vc-venture-capital-startup/id958230465 Follow Harry Stebbings on X: https://twitter.com/HarryStebbings Follow Nikesh Arora on X: https://twitter.com/nikesharora Follow 20VC on Instagram: https://www.instagram.com/20vchq Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/contact ----------------------------------------------- #20vc #harrystebbings #ai #perplexityai #aravindsrinivas #founder

Nikesh AroraguestHarry Stebbingshost
Jun 22, 20261h 16mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:00 – 0:52

    Intro

    1. NA

      I came to the United States with two suitcases, $200, and I was willing to do anything, anything at all to make sure that I made a life for myself because there was no way to go back. I was a security guard. I took notes for the disabled. I flipped burgers at Burger King. I had $200. I had to find a way of paying my tuition.

    2. HS

      In the hot seat today, we have Nikesh Arora, the CEO of Palo Alto Networks. They have a market cap of $225 billion. Nikesh is one of the most respected operators in technology.

    3. NA

      I think the long-term token pricing should be one-tenth of what it is today. Mythos, I think, ends up being an accelerant to cybersecurity. In technology, you miss one trick, you can survive. You miss two tricks, you're partly impaled. You miss three tricks, you could be obsolete.

    4. HS

      Ready to go? [upbeat music] Nikesh,

  2. 0:52 – 5:09

    Brand vs Product

    1. HS

      last time we did a show, um, I was 22 hours into a 24-hour fast, and I listen back now, and I, I just think, my word, you had the audacity-

    2. NA

      [laughs]

    3. HS

      ... to be with one of the OGs of this business and be hangry. Like, I was, I was hangry with you and short-tempered. [laughs]

    4. NA

      Well, the good news is I told you earlier when we were chatting, I have total memory loss. I have no recollection of what I said and what we talked about, so I have to go back to listen to it. Just happy to be here.

    5. HS

      It was a great show. We, we-

    6. NA

      [laughs]

    7. HS

      ... got on blissfully well.

    8. NA

      I believe you. [laughs]

    9. HS

      It was wonderful. I don't know what that was about. Um, we-

    10. NA

      I think we should stop doing podcasts remotely.

    11. HS

      I... Oh, God, I agree. I-

    12. NA

      I think we should force people to come in here once a year.

    13. HS

      Well, so, so, so I actually do.

    14. NA

      Good.

    15. HS

      And, and the nice thing about Size is they do.

    16. NA

      Good.

    17. HS

      But y- y- a, the only challenge is they actually sometimes come quite jet-lagged because they come, like-

    18. NA

      Yes, that's true

    19. HS

      ... for the day.

    20. NA

      That's true.

    21. HS

      And that's a little bit tough.

    22. NA

      Well then maybe you should do it at 11:00 PM.

    23. HS

      Maybe.

    24. NA

      Yeah. If you take people from California, it's a perfectly nice time for them at 10:00 PM or at 9:00 PM. Maybe you need to.

    25. HS

      Or maybe I need to adjust.

    26. NA

      Yes. Maybe.

    27. HS

      I'm the selfish one here. I was talking to Marc Andreessen-

    28. NA

      Not selfish. He's good

    29. HS

      ... about something with me. Marc Andreessen said... I've really actually embraced it. Haven't even got to the first question, but fuck it. Uh-

    30. NA

      [laughs]

  3. 5:09 – 9:18

    The Breadth vs Depth Problem With Frontier AI Models

    1. NA

      Yeah, look, I, I've been r- listening to some of your podcasts and I've been paying attention to what happens to market because I want to understand where all this settles down, not just because, you know, I want to understand it, but it also impacts how I build my own business, right? So you got these phenomenal frontier models, and they keep sort of leapfrogging each other. Every few days there's a net new model that's delivered by OpenAI or by Google or by, uh, our friends at, uh, Anthropic. And the question becomes, okay, fine, these models are moving into space. What do I need to build? What do I need to do with these models? And, you know, as we came to that Mythos moment when everybody was busy chasing Mythos, and that was kind of important, you realize even the best model has a high false positive rate. But for some reason, in the consumer space, we don't seem to care. You know, I was talking to my sister this morning. "So I just went to ChatGPT and asked these, all these questions. It was very helpful." So I guess, like, what happens is the consumers are way more tolerant of false positives because just, it's kind of always the person in the middle, right? There's always somebody who's Understanding what the model says and making their own judgment whether they believe the model or not, and somehow people get rid of some false positives, somehow people don't care about the false positives, some peo- sometimes people believe the false positives. So the consumer is highly tolerant on this notion of false positives, and doesn't seem to dis- distinguish, and it just seems to get better and better. I literally had Gemini produce an investment memorandum for something I was looking at. I looked at it. It looked pretty accurate. Give or take, I'd tweak a few things, but it seems passable. So on the consumer side, it's a breadth issue, right? It wrote an investment memorandum for me, which is cool. I would've had to hire a banker and a bunch of investment analysts that would've taken me days, and I did it in four minutes. So the breadth is there, which means it's my go-to place. And as you know, in consumer, if you become the go-to brand, talking about brands, it's hugely beneficial, right? Whether it's YouTube, like that's the only place to go look for streaming video, or Google, that's the only place to go do a search, it becomes hugely sort of multiplicative from a distribution perspective. So our frontier model friends are chasing the consumer brand, and the false positive doesn't matter. On the enterprise side, false positives matter a lot. They matter because if you imagine a future where an agent's gonna make independent decisions and act on it, you have zero tolerance for false positives. Now, take Waymo. In my view, Waymo is the biggest agentic product that is out there, because guess what? We've replaced a human being called a driver, right? All decisions are made by AI machine learning. It decides when to turn, when to stop, what to do. But think about the amount of edge case training it took to replace that human agent with effectively an AI-driven agent. I don't know, tens of billions of dollars. So that's what it takes to take one use case and train the hell out of it. And if you b- think about what happened there, they could've used the equivalent of an AI model, but then they built so much context and intelligence and edge case training and proprietary data to make that happen. That data is not available on the internet. You can't stick the next model of, you know, Anthropic into your Mercedes and say, "Okay, drive me home." It's not gonna be able to do it. And that's, that's the depth issue, right? Because you need the depth of the context and understanding and the intelligence in, around the model to make it useful for the truly agentic use case. So I just think there's this constant tension. The frontier models want the consumer attention because that drives post-training for models. It drives the consumer brand of the model. On the other hand, the real enterprise revenue is gonna come from use cases that are, require a lot more context. The one sort of standout use case we all know is coding, right? Coding is a universal activity. Everybody does it, so everybody's data is helpful in training the model, and that becomes sort of a large enterprise application. Hopefully, there's a few more out there, but I think that's the tension that I wrote about.

    2. HS

      When you think about the workflows and the way that enterprises are engaging with AI, specifically models, what extent do you think we will be locked in a frontier model dominant world versus a, the majority of enterprise workflows can be done with open source, and we will be more cost-efficient moving towards them most of the time?

    3. NA

      I

  4. 9:18 – 14:53

    Enterprises Are Still Getting AI Wrong

    1. NA

      think more than half the enterprises are still not getting it right on the use of AI perspective. I think we're still busy trying to incorporate AI into our current business practices. So how do I take what I do today, use a little bit of AI, get marginally more efficient because I don't wanna do this the old way? I think the opportunity is to rethink your workflow fundamentally with AI. Um, that's where the true benefit's gonna come. And I think the winners in the long term will be people who actually rethink their companies with AI, not people who adapt their current workflows marginally with AI.

    2. HS

      How can you do that if you're an enterprise? I, so we, we have-

    3. NA

      You can. You can.

    4. HS

      We have thousands of CEOs of big enterprises that listen. That sounds great. What do I do? Do I do a brainstorming session?

    5. NA

      No, I think, like, there, there's gonna be perhaps two or three different categories. Like, one category is, let's take the workflows of today, where we have workflows around ERP, we have workflows around sales, team management, we have workflows around human resource management. There are existing workflows which have been SaaSified, as in some software company decided we all have common processes. Let me build a container where these common processes can be marginally customized by enterprise. They can code their workflow into my SaaS application, and we're off to the races. Now, that workflow required a lot of human judgment and human an- interaction. The software is not intelligent. It's been coded, right? You define input, you define output. I do the input, I know what the output I'm gonna get. The idea is imagine workflows where, you know, in the hiring process, most of your workflows are containers. Imagine where AI actually is helping you make judgments. If I put every CV into AI and say, "These are the 20 people you should interview. This-- look to the CV, you should ask this person these following questions," sends a note to Harry saying, "Interviewing this person, ask the following 10 questions because your three other colleagues only asked the following five. We needed no false positives to human beings." So AI could be hugely helpful in informing and making the process more intelligent. But that requires us to give up human control and let AI do 80% of the thinking for us. That's not how we're doing it right now. All we're doing is, "Let's take this invoice. Let's scan it, abstract the data, put it into AI and say, 'Look at that. It's happening 20% faster.'"

    6. HS

      Do you think we are willing to give up that human control? You see cases like MattersToday, where I think 1,700 people have signed a petition that they are unwilling to let it track their mouse and keystroke behavior. We are seeing resistance to giving the data.

    7. NA

      I would tell them two points. I think two different points. I think mass collection of data to inform AI is a little dangerous because people see the outcome of what that's gonna happen, right? And I've heard of companies where people are, you know, using cameras to track people folding laundry and ironing clothes because they wanna be able to trace, train physical AI in the future to do those things. So that part aside, I think on the enterprise side We can actually run a business much more effectively and efficiently if we decide where we are willing to relinquish control to AI. Perfect example, marketing, right? Anything that is required to train a marketing model is already out in the public domain. By definition, marketing is public domain, right? If you didn't market it, it's not in the public domain. So I have the best training data in marketing. I don't need to train an AI model with more marketing content. I may need to train it for tone of voice and what my brand is, and I'm pretty sure an AI model, if I throw my marketing collateral into it, will tell me, "This is not consistent with your brand if I look at all the things you've been talking about the last ten years." I think some people have done that. They've actually analyzed earnings scripts of companies and said, "The last 20 years, what has company X done, and when does the CEO start getting away from a topic because perhaps it's not going so well?"

    8. HS

      [chuckles]

    9. NA

      So this is really smart. They can do that stuff. So it's the best marketing training database in the world, the frontier models. Why do I need 400, 600 people in marketing? Because my biggest problem in marketing is I have 600 people, but I'm not sure they all fully understand how to consistently deliver my tone of voice, my value proposition, and how not to break my brand by having different collaterals in public domain.

    10. HS

      You have 600 people in marketing?

    11. NA

      Give or take on 21,000 people. Uh, well, it's not gonna be 600.

    12. HS

      No. What is it gonna be?

    13. NA

      I don't know. My rule of thumb is that in the next three years, we'll probably have half the people in GNA-type activities in companies, things like marketing, things like finance, things like HR, because there's a lot of process management there, and a lot of process management can be made more intelligent using some version of an adapted future AI application, for lack of a better word. So SaaS applications will give way to AI applications, the difference being SaaS applica- applications have no opinion, AI applications will have opinions. That's a fundamental rethink we need from a workflow perspective.

    14. HS

      Can you just help me out? AI applications will have opinions. What does that mean in terms of how you use them, in terms of the output that they have? What, what, what?

    15. NA

      Everything, right? Like, uh, the... You're a scholar, whether you wanna call it an AI assistant, AI marketing assistant, AI HR assistant, it's gonna say, "I looked at your copy. It sucks."

    16. HS

      [chuckles]

    17. NA

      "That's not good enough. It's not consistent with tone of voice. Here's what I would recommend." This has an opinion. That'll make my average employee much smarter than they were today. Then I don't need so many of them because they're doing most of the work for you.

    18. HS

      What would you say to the people that say, "You're wrong. We won't see that halving of those functions, and actually, marketing teams will create more copy, more content, be in more places"?

    19. NA

      No, like, I think the places where people could be wrong is how many technical resources we need in the future. I think we need more, not less.

  5. 14:53 – 29:46

    AI Guardrails Aren't Robust Enough

    1. NA

      I think there's this fallacy people believe we're gonna have less people working because AI's gonna take over our jobs. I don't believe that. I think what's gonna happen is-- You, you can't imagine the number of people on my team who want more technical resources, more AI-savvy resources, because they wanna do exactly these things. It's like, "Well, I've got an amazing project to transform marketing. I've got an amazing project to transform HR." "What do you need?" "Oh, I need more people who understand how to prompt frontier models, build harnesses, bring proprietary data into play, bring moats. I need more compute, more storage, because I wanna learn everything." So I think we're gonna need more technical resources. I think we're gonna need more sales resources because if your product's really good, you need more people to go out there and cover the universe because not enough people know about it. I'm in Europe. I met 20 customers last week. I still see half of them don't know all the stuff we have. I'm like, "Dude, we've been around for 20 years. Why is my team not out there pounding the pavement and telling them everything we do?" And the problem is not enough time in a day because I'm too busy dealing with some arcane piece of software at work which I have to go feed. Well, if I had that software be really intelligent, it'd tell me what to do.

    2. HS

      In terms of wanting more technical resources, tokens I would put in the more technical resources camp.

    3. NA

      [chuckles]

    4. HS

      How do you think about effective token allocation today? You're seeing very different camps from your Matters and Ubers and Microsofts who put in budgets to your free-for-all be creative. How do you approach it?

    5. NA

      Look, I know this whole world of token maxing has kind of gone topsy-turvy with the whole conversation around how many tokens people are using. The challenge right now is 90% of the enterprise employees are not AI savvy. They're not. They have to learn. I can't send them to university, right? There's no course you can take at any school anywhere. They have to be able to learn of their own. I think we're back to a Darwinian moment where everybody has to figure out who's really good. Now, you've seen people like Bryan Armstrong and Jack Dorsey go out and say, "I'm gonna decimate my organization, and I'm gonna start building from scratch." And they've gone to some version of 30, 40% less people because they've figured out there's no redemption. "I can't train these people. I'm gonna just find the people who are gonna come in and help me do this stuff." That's one model. The other model is sort of gradual. We've been hiring people only through hackathons now, right? And we see natural attrition of 2%, give or take, a month, and we just replace them with people who actually are AI-savvy people we hire from hackathons. Give me 12 months, I'll have, I'll have sort of transformed 20, 25% of my team. Give me three years, I'll have hopefully enough AI-savvy people working at Palo Alto. So there are two different ways to get there. I think part of what you're seeing in the token maxing world is people are learning. People are experimenting. The risk is your smartest employee [clears throat] who knows how to use the AI really well could be using 20 times the tokens that an average employee uses. And if you get into this whack-a-mole moment saying, "Oh my God, I'm gonna stop people spending too many tokens," you actually will hurt the best AI-savvy people more than you will hurt the average employee.

    6. HS

      And by the way, I think the best talent will want to go where they will be best equipped-

    7. NA

      True

    8. HS

      ... with the most expensive frontier models-

    9. NA

      True

    10. HS

      ... the biggest budgets. I think that'll almost be like an employee benefit-

    11. NA

      Yes

    12. HS

      ... for a while.

    13. NA

      Possibly, but I think part of the challenge is, you know, right now everybody's experimenting in everything, and you have to figure out what is it that I need to build as an enterprise and what can I get off the shelf? Right? If I can get an AI-based thinking application that does marketing for me, I don't need to build it. It's a generic problem everybody needs to solve. I can tweak it, I can customize it just the way I did with SaaS applications, but I don't need to build mine from scratch. So I've made sure that everything my team is building is proprietary to us. This is where do we have unique, distinguished knowledge that we bring to bear, which nobody else can do on the outside? Let's put that, let's package it, let's use it. Where it's gonna be a generic AI application 12 months, 24 months from now, let's just wait.

    14. HS

      So you have a free-for-all on tokens, so to allow your team to do the best?

    15. NA

      Uh, we have a use judiciously [chuckles] model for tokens. It's not a free-for-all. Free-for-all sounds like you can go token max the hell out of it. We have to use it judiciously, and we keep track of it to see what people are doing, and if we find somebody who's using it well, we won't constrain them. If we find somebody's gone a little off the top, over the top, we'll find a way to cap it.

    16. HS

      Benioff said the other day that he spends $300 million on Anthropic a year for his devs, and that works out to be about 3.8% of developer salary spend, uh, average. Um, if it stays there, the valuations of Anthropic and OpenAI are grossly overvalued, and if it moves to 20%, they're actually very undervalued, and if it becomes what Brandon at McCaw said, which is, "We'll spend as much on tokens as we do on salaries," they're grossly undervalued. Grossly undervalued. I wanna talk about where you think percent of developer salary spend on tokens will be in three years.

    17. NA

      Um, that's still a narrow lens for me. If I abstract, if I step back today, um, there's not enough compute for what the world is demanding. Unequivocally not enough compute, right? Can't buy compute. Compute is costing 2 to 3X or 4X more than it used to cost two years ago. There's not enough compute. That scarcity of compute and that excess cost required to build and deliver compute, which allows us to go make AI useful, is causing the constraint and forcing pricing, right? Because-- And interestingly, I think more than half of the compute is going to feed the consumer, which is a fundamentally loss-making entity right now. Like, I don't think any of the frontier models make any money in trying to get you and me to use ChatGPT or, you know, Claude or Gemini every day. It's free. That's a lot of compute. Imagine there's billions of people around the world using for all kind of queries every day. That's sucking away half the compute, which is making no return. Guess where the pressure goes? The pressure goes on the other half of compute, which is being used for coding in enterprise applications. So now you're saying enterprise applications coding have to pay until we build transaction models or advertising models on the consumer side, because they're not ready. Now, you could say, well, that happened in search too, right? Google Search was around. That happened to YouTube. People used a lot of YouTube, a lot of compute, but it wasn't paying for itself. The problem is the compute requirements and the cost is now 10X of that when we were in that era versus today. So that's forcing token prices to go up. I think the long-term token pricing should be one-tenth of what it is today. When that happens, you will see that people will consume more. You can decide if 3.8 or 15.8 is not, not sure we can tell the answer right now, 'cause pricing will move very drastically in the next three to five years. I think at some point in time-

    18. HS

      S-sorry to interrupt you. So you think we'll see dramatic reductions in token pricing?

    19. NA

      I think so. I think in the next three to five years, we will see a reduction in token pricing. I think at some point in time, the consumer use of AI will get constrained by these frontier AI companies because they have enough post-training data, more than they need, and each user is inherently unprofitable in their activities they do on Frontier AI Models.

    20. HS

      Do you not think they just build advertising engines like OpenAI is doing now to pay for that business?

    21. NA

      You know, that's an interesting question. It has to come from somewhere. When I started Google in 2004, we were 2% of the global advertising revenue, and global advertising revenue was estimated between $500, $600 billion. I think online is about 70% by last count of total advertising revenue, and I don't think the overall number has changed by more than 3% a year or 5% a year. So I don't think the total advertising pie is gonna increase. You've already taken away 60, 70% of the advertising pie in the online world. Unless you tell me there's gonna be explosion at the top where more people are gonna spend more money in marketing, that money that you're hoping to fund consumer AI from advertising will have to come from current advertising revenues. So I don't think that changes the equation drastically to make the consumer profitable. I do think there's an opportunity that AI ends up taking more transaction revenue, which has not been under the purview of AI.

    22. HS

      Can you explain that to me?

    23. NA

      Well, think about the marketing chain, right? Like, we do advertising. Advertising is inherently efficient. What's the best conversion rate you get in online advertising, you think?

    24. HS

      One, one and a half percent.

    25. NA

      That's fine. The rest-- The thing, the best of breed is 7 to 10%.

    26. HS

      Wow.

    27. NA

      Sometimes. But the average probably 1.5 to 2%-

    28. HS

      Yeah

    29. NA

      ... which means 85 to 90% of marketing is wasted, right? So now if you get really smart, you have memory, you have context, and you get smarter in targeting Harry when he's trying to buy something out there in the world, then your conversion rate goes up, right? If you look at the entire value from the time you decide to buy something till the end, you get the product. You know, you take the case of consumer goods. Today, I wanna say the cost of consumer goods is probably in the 5 to 8% of total, you know, list price. The 92% is distribution and marketing. It's highly inefficient. So you could imagine a world where AI makes marketing really effi-efficient, and you get more dollars coming from traditional marketing into the online world because it's coming in the form of transaction.

    30. HS

      If tokens get cheaper-

  6. 29:46 – 33:46

    Claude Mythos Changed Everything: Finding in 6 Weeks What Would Take 6 Years

    1. NA

      Mythos ended up... I think ends up being an accelerant to cybersecurity.

    2. HS

      Yeah.

    3. NA

      I think what happened when you saw Mythos came out, it demonstrated that all the training we've been giving these models on how great code is written, uh, the models are able to turn around and say, "Well, I also know how to find bad code." So what happens is you point the gun the different way, and the model says, "Oh my God, look at all this code that you have. There are so many flaws in it." As we talked about the challenges, like every model, it also suffers from false positives. So if you're an offensive actor, and I point the model against, let's just say, 20 VC enterprises, and I go look at everything you've done, somebody's left a WebSocket open, somebody's done some mess up in IP addressing, et cetera. So it finds the flaws outside in. That allows the bad actor to go figure out how can they daisy-chain vulnerabilities and get into your infrastructure. It's not good enough from a defensive perspective because I can't use a model and say, "Go take every vulnerability you found and build a patch and go patch my system and protect me." 'Cause guess what? It's gonna patch 30% of things which are not wrong. Who knows what that's gonna do to blow up your infrastructure? So when Mythos came, we looked at it, we treated it with respect, we ran it against our code. We discovered it finds bad stuff much faster than humans can. We found in six weeks what would've taken us five to six years. So we got it. We ran around, we patch it, but, you know, Claude Code helps build the patch, but you still have to run it through human evals, through testing, through production testing, through sandboxing, to see does this patch break anything in the infrastructure. Only then after six weeks were we able to go patch everything. Now, so what does this mean? This means that every enterprise better fix their stuff faster. Because if I point the next generation of models against your infrastructure, it's gonna find security flaws, security vulnerabilities, misconfigurations, things that you've not been paying attention to. So it creates a bit of an urgency on the parts of the customers to improve their cybersecurity posture, which I think generally is a good thing for cybersecurity companies.

    4. HS

      This is not fundamentally bad. Like when we just, like, summarize what you just said, it allows you to weaponize bad actors to find holes, but isn't good enough to provide the solutions.

    5. NA

      Well, look, the solutions are there. Solutions are there. Uh, the challenge is getting-- sometimes getting the attention and focus of the customer saying, "Listen, I gotta go fix my stuff because it's important." What this has done is it's lit a fire under the security practitioners around the world saying, "This thing is not good. This is gonna weaponize the bad actors. I better make sure my defenses are in place." Now remember, the way cyber defense is done is it's fundamentally just-- cybersecurity is two fundamental things, right? One thing is, if it's bad and I'm at the gate, I'll stop it, which means you have to have somebody at the gate. Now, we have 150 million sensors in the world where we stand at the gate protecting our customers. So if I can find a way of infusing AI at the gate and taking all these vulnerabilities and finding a way to protect you, I'm good. I don't have to chain the gatekeeper because there's no Claude endpoint agent that exists out there. There's no OpenAI endpoint agent that exists out there that I can replace Palo Alto or the other people in the space with. The problem is not at the gate. What happens is, despite all the perimeter defense you put in, things come in, things leak in, people make mistakes, people-- passwords get breached. You know, there are vulnerabilities people get in through. Then the question becomes, "All right. Oh, shit. The bad actor's in my infrastructure. How quickly can I find him and get rid of him or her?" That becomes an AI task. That becomes the same conversation we're having so far is, "I need context. I need intelligence. I need to know what this means." So creating the context, that intelligence within the enterprise of what this intrusion means and how to protect against it becomes a challenge. This is the AI cybersecurity challenge. Something we, you know... Again, this is-- not trying to here to pitch my book, but we spent five years trying to build that capability inside enterprises, so in the net-net, it ends up being an accelerant. Does that mean I have everything I need? Not everything. Does that mean I need to get AI models to start helping me? Yes. So we're gonna infuse more AI into our defense infra- infrastructure.

    6. HS

      Do

  7. 33:46 – 35:09

    Should Governments Intervene on AI? A Discovery Process

    1. HS

      you think it is good or bad to have government intervention when you have models as powerful as we have them?

    2. NA

      I think we're going through a discovery process. Um, I think this notion of guardrails has not been built robustly enough because these models seem to be easy to get past. Remember the early days when you used to read about somebody had this conversation with a model and found a way to, you know, albeit the guardrails because it asked questions differently, and the model was able to get sort of jailbroken.

    3. HS

      Yeah, yeah.

    4. NA

      It became a hobby amongst people, and like they had all kinds of conversation with models. This is the same challenge. How do you make sure that you can put enough guardrails around AI model that you built to make sure it's only used for the purpose that you had, right? That's the challenge that there is. I think the guardrailing needs to get better. To the extent the government feels the guardrails aren't robust enough and is trying to tell us it's a national security issue, I need to go fix the guardrails. But the thing is, it's a simple matter of trying to fix or treat the guardrails as a real problem and solve it.

    5. HS

      Is it possible?

    6. NA

      I'm hoping it is.

    7. HS

      I hope it is, too. If you were starting, this was-- I spoke to one of the world's best cyber investors who will remain nameless 'cause he asked some spicy questions, too. Um-

    8. NA

      Oh, okay. He asked questions from me?

    9. HS

      Yeah, he asked questions from you.

    10. NA

      Oh, good. All right.

    11. HS

      He asked some interesting ones. Uh, but he asked if you were to start Palo Alto Networks or a cyber company again today, starting today in the age of AI, what would you do differently that you're not doing

  8. 35:09 – 45:00

    If Nikesh Started Palo Alto Today: The Waymo vs Tesla Approach

    1. HS

      now?

    2. NA

      The paranoia I have-- If I look at self-driving, there are broadly two or three approaches out there, right? One was, "My car is not gonna have a human in it." It's called Waymo, right? "I'm gonna keep pounding it. I'm gonna keep pounding it, training it until it learns by itself to drive, and no human should be holding the steering wheel ever when my customers are in it," right? You see it's out there. Many cities have Waymos. I saw one down the street from here. So that's one way of doing product development. And what you do is every edge case gets discovered. You build training around it. Every experience is a learning experience. You build training around it. You keep training it, you keep training it, you keep training, get to a point of total autonomy. The other version is, "I'm gonna start taking segments of the driving and start automating that segment where I get really comfortable, so my car drives 50% of the time. The other 50%, the human gets in on the edge cases." That's my Tesla, right? Tesla used to drive just the highway for me. Now it's getting better at, you know, other streets. It's slowly getting better. But still, I'm holding the steering wheel very often, and it'll tell me, "You're not paying attention. Look at this. Look at the camera, otherwise you can't drive." And I know FSD gets better, but that's another way to get there, okay? I'm gonna keep training. I'm gonna fix this. I'm gonna start working the edge cases as my business continues to evolve. The third one is I'll infuse some degree of self-driving into my car because I've come from the addi- traditional model of having amazing cars, great V8 engines, beautiful sleek cars, and I'm not into the technology aspect. Or you see them out there on the street. We have all three versions out there.

    3. HS

      Mm-hmm.

    4. NA

      My fear is, do we all need to stop and start thinking the Waymo way as enterprises, or is there room for the Tesla approach to self-driving in our businesses, right? Because we have an existing set of customers to satisfy who are not gonna take kindly from me saying, "You know, guess what? I changed my product. It's right 80% of the time, and I'm gonna take another three years to train the product to be right 100% of the time," right? So my fear is, am I pivoting fast enough in my product strategy that over time my products become more self-driving than they are today, or do I need to go faster? And can I get there by automating or AI-enabling certain parts of my product where I can apply the models that are capable to do certain aspects of cybersecurity today and keep doing the others through machine learning and managing S cases-- edge cases through machine learning, or is it time for me to pivot? My view right now is it-- you have to have the Tesla approach if you're an enterprise that is building AI-infused capability. But you can't have the approach of traditional car manufacturers, which are trying to stick a little bit of AI and sort of AI-washing their cars and saying, "I'll get there eventually."

    5. HS

      Would you like to do the Brian Armstrong, Jack Dorsey? I, I, I often think a good question is what would you like to do but you're held back from doing?

    6. NA

      Different courses for different horses, right? I don't think in our business we can go implode the organization because I don't think the underlying application software is there. I don't think all the things that we've talked about that we need to get done are ready from an AI software perspective.

    7. HS

      Mm.

    8. NA

      Uh, I don't wanna build a lot of software that is proprietary to me for things that should be available for everyone. I don't wanna build an AI marketing stack. I don't wanna build an AI HR stack. I don't wanna build an AI ERP stack. I'm hoping that somebody goes and does that much more effectively and efficiently for the world at large. Perhaps it's the next iteration of Salesforce, the next iteration of SAP, or the next iteration of Workday that is gonna help me do that because I do believe it needs to become more intelligent. We talked about it needs to be more AI-enabled or AI-controlled. Uh, I do wanna build things that are part- particular to me. They-- where I have all the information, all the intelligence, the context, and the memory from an organizational perspective. I think the right way to get there is to hold people accountable, and I run a meeting twice a week now called AI AO. It's kind of funny. It's like Old MacDonald Had a Farm. AI AO, because everybody in my company wants to do AI. So if you use it as a converging function, as a convergence to-- as a function to do brainstorming across my team. How do we think about this? Why are we building this? 'Cause I have to-- AI-

    9. HS

      What happens in that meeting?

    10. NA

      Everybody comes and shares how they're adapting to the new world of AI. What are they doing from a product development perspective? How are they thinking about it? How are they including agents in their co-- in their, in their products? How are they gonna go build the backend infrastructure? How do we think about how they're using tokens? How do we think about the capability of resources? Remember, for me to transform a 21,000 people organization, I have to get the hearts and minds of the leaders to make sure we're all swimming in the same direction or pulling in the same direction. So this is my way of ensuring the top 15 or 20 technical leaders in my company are pulling in the same direction. What will the direction be? And, and as you know, if there's no expert, then a group of smart people do better than an expert. I don't think there's an expert for future enterprise design yet in terms of here's the blueprint, like you said. As a VC, you're saying, "Holy shit, where's the value gonna accrue? Is it gonna be in models? Is it gonna be in the application layer?" Trust me, we have to have a point of view on that stuff and what's gonna emerge in the future before I can start re-transforming my company. Like, how should I build my products?

    11. HS

      Are your leaders AI-pilled? I, I interview CROs as well, some of the best CROs, some of the best CPOs, and in all honesty, the bigger the company, the less AI-pilled, AI-maxed they are.

    12. NA

      I-

    13. HS

      To the extent where one the other day, a public company doing 5 billion-plus in revenue, CRO goes, "You know, we don't have that AI talent internally, but we'll, we'll, we'll bring it in."

    14. NA

      Yeah, like un-- I discovered this in 2004 when I was in Europe. I ran Google Europe. I used to go around and meet CEOs, and there was this fad where CEOs would hire this 24-year-old sherpa. They were called the a- the, the, uh, web sherpas or internet sherpas, right? It's like chief internet officer. Remember those companies had chief internet officers at one point in time.

    15. HS

      I was eight, so no. [chuckles]

    16. NA

      You're eight. You don't remember. Well, it's used. We've seen this movie before, and sometimes it's fine to have seen this movie before. And the task of the chief internet officer was to make sure the organization was ready for the internet because I'm too busy in my traditional business, and I don't know who Amazon is. I don't know who Google is, so this wonderful 24-year-old who understands this stuff is gonna help be my savior. And then CEOs would wash their hands about the internet because they have this wonderful team of people who would be frustrated because they can't get anything done because nobody's giving them attention. The risk of that happening is true with AI as well. I'm so busy doing what I did yesterday, I have no time to think about tomorrow, so meet my chief AI officer, who was probably a researcher at some amazing university before and has low execution skills. So until I can get my leadership to understand and agree the extent of the AI challenge and the AI opportunity, we're not gonna make progress.

    17. HS

      What specifically are you not focusing on today because of the burdens of today's problem?

    18. NA

      Look, everything. When you go talk to a product manager in any large company, I'm pretty sure they have a product roadmap that exists in their heart and their hands. It's just six months or 12 months long. I gotta go fix all these things. I'm like, what's interesting is in the six to 12 month thing, there's nothing called agents in there. How come, like, the world is talking about agentifying everything, and your product roadmap doesn't have that? I'll get to it once I get this done because it's what customers want right now. I'm like, "Nope, that doesn't work." How do I get you to do more agentic work? How many people are you gonna free up doing development the way you're doing it today, so I can use that excess resource to go make new things happen? So those are all important conversations. I can have them one at a time across 14 or 20 people, or I can have them twice a week with them, and people demonstrate how they are. And what's fascinating, remember You have to make sure your leaders are ambitious. You have to make sure they're competitive. You have to make sure they wanna win. You have to make sure that they have a learning mindset. When they watch their peers around them do cool shit, they wanna show up with cool shit the next time. So for me, it's getting 14 people together and saying, "Hey, Harry, tell me today, what have you done for AI in the last three days since I last talked to you in your organization?" And whatever motivates you, whether the fear of Nikesh asking you three days again what you did or your sort of inherent learning ambition, or it's your team pushing you, you will show up with something. And then you'll see what the other guys are doing and say, "Oh my God, I'm doing a lot," or, "I'm not doing enough." So it creates a little bit of Darwinian competition amongst them. It creates this urge to go embrace this new technology, and I think hopefully I get 14 people fully motivated, and then they go do that to the next set of people. 'Cause I need to transform from the top down, not from the bottom up on this topic. There's a bottom-up experimentation, of course, right? People using tokens to see who's really good at it. That allows me to find the best talent. So just gotta find a way of transforming 20,000 people over the next two years in that direction.

    19. HS

      Bottoms up, top down. You gotta get into these organizations. That, that sounds naughty. [laughs]

    20. NA

      [laughs] So, you know, I wish I was a VC. I could sit down and podcast and talk about stuff and-

    21. HS

      Clearly I need to get out more when that's... [laughs]

    22. NA

      [laughs]

    23. HS

      Um, I just sit in this dark room all day, Nikesh, I'm sorry. Um-

    24. NA

      It's all good.

    25. HS

      Uh, the question is: how do you get in effectively, and how do you get implementation and adoption done well? I've had guests on the show say before, "You cannot do enterprise adoption without FDEs today." And then I've had Matan come on the show, f- our friend from Factory, and say, "If you need FDEs, you have a shit product." Bold, and I love Matan, and I, I think it was a great clip, so grateful for the virality that that came with that.

    26. NA

      Got it. Okay. Is that, that went viral?

    27. HS

      That one did very well, yeah. Shyam from Palantir then obviously chimed in and-

    28. NA

      Of course

    29. HS

      ... my job is to create a discussion. Um, what is true and what is right? Do you have to have FDEs to sell into enterprise?

    30. NA

      So I think what, what is true is we've only been chasing the enterprise dream for AI for the last, what?

  9. 45:00 – 52:48

    Agentic Security: Why You Need a Gateway for All Agent Traffic

    1. NA

      12 months?

    2. HS

      Mm.

    3. NA

      At best.

    4. HS

      Mm.

    5. NA

      If you think about everything that happens on a weekly basis, we see new things come which we don't quite fully un- understand and grasp, right? We're all busy trying to get our arms around LLMs and how they're gonna be great for chatbots to talk to our customers as an enterprise, and suddenly agents showed up. It's like, "Oh, my God, I gotta figure out agents. They're gonna start working internally. Agents are gonna do a lot of stuff." I'm pretty sure you could still have a agent fest and have everybody tell you what an agent does. You'll still walk out and say, "I'm not quite sure that his agent or her agent is the same as what the last guy said." So because AI is moving so fast, I don't think the products are fully there yet. Like, the enterprise products at the application layer don't exist in their entirety-

    6. HS

      Mm

    7. NA

      ... because we haven't been tested against the enterprise ask. So FDE is a short form for saying, "My product's not fully there because it's evolving as the technology evolves. I'm gonna send some people across who are gonna sit in your office and build my product while I adapt it to your needs." That's what it is, right? That's what we saw from Palantir. That's what we're seeing from all these companies. So what you're saying is, "I'm gonna send my product engineers or developers to your or enterprise. They're gonna build my product." You get it if you do it right. Again, FDE is a different version. Some people are just trying to get you to consume AI, which is actually not an FDE. It's just a sa- technical sales consultant who's trying to help adoption. On the other hand, an FDE truly is somebody who actually brings the code back from a customer site and goes back to your product. I say, "Listen, I built this at the customer site because they had this need. We should incorporate this into our product because everybody's gonna need it." That's an FDE in my mind. So I think FDEs are needed for the short term because remember, all the enterprise AI startups are hungry for revenue. For some reason, we've created this notion that, "Don't worry, just keep, keep selling it. There's a huge sort of pent-up demand around AI applications. Sell it before the product's fully ready." That's what we're seeing.

    8. HS

      Do you think that's right?

    9. NA

      I think that's the case. I think as we think things evolve in the next 12 to 24 months, people will switch from one set of products to another because something will emerge as a better product. Look at the coding conversations, right? How many coding companies have you heard of the last 24 months? I think we had Windsurf, we had Devon, we had-- which is now Cognition. W- Windsurf got sold.

    10. HS

      Mm-hmm.

    11. NA

      So those are the early guys in coding. They don't exist in their then form. Now you've got Codex and Claude and Antigravity. You got Factory doing SDLC. You've got Cognition doing SDLC. So you can see as the market evolves, people who have concentrated on different parts of the value chain around coding are getting formed. The products are getting more and more formed over time, and who knows in two, three years who's gonna be the leader in that space? Because the product's not fully ready when you start.

    12. HS

      Do you wanna make a bet on who will?

    13. NA

      No, you do that. [laughs]

    14. HS

      [laughs]

    15. NA

      You do it for a living. I just need a good one my teams can use. I don't need to make a bet.

    16. HS

      Uh, I, I, I love that, and, and I agree. Can I ask you, how do you choose who you decide to help? You, you know, I spoke to your daughter Aisha before, and she said one thing that... No, Aisha, lots of things that many people don't know about you. Um, but she said, "One is you help a lot of people, a lot of founders, and you ping them."

    17. NA

      Yes.

    18. HS

      How do you choose who you ping and who you help? Matan obviously being one of them.

    19. NA

      Well, my current paradigm, as I told you, is this market is moving so fast that based on what you read, that open claw comes out. Suddenly there's this thing that people can have agents. There was a moment if you heard, if you saw, there was agentic browsers, remember? We don't hear about them much, but there was a moment when everybody was gonna have an agentic browser. Your browser was gonna be your computer, and that's gonna be-- sort of do all the agentic tasks. When I hear about these things, I'm trying to assess Which one's gonna work? If it works, how does it impact my product portfolio? What do I need to build in anticipation of this technology becoming mainstream? And that window from the idea to execution is shortening in the AI world, as you can see, right? Like, the way these companies are coming out and getting formed in 12 months and 24 months and getting 100 million ARR is probably the fastest ever. Which means if that's what my enterprise customers are using, I have to figure out a way to secure that stuff. Well, my team doesn't fully understand all this stuff, so I'm busy listening to podcasts, listening to people, watching people tweet, watching people on LinkedIn, saying, "This is an interesting technology," pinging the founder. So my first step is to ping somebody who's doing something interesting, which I don't fully comprehend. They seem to be getting to a degree of success, which gets me-- gives me a feeling this could be something relevant, perhaps not this company, but the construct that they're working on, the concept they're working on.

    20. HS

      I'm an investor. In a world of investing, in a world of uncertainty, you go later where there's more certainty.

    21. NA

      Yes.

    22. HS

      Uh, we spoke about this downstairs. Um, y- you know, I have that luxury in terms of a [chuckles] sizable mandate to do that. You have that luxury too in terms of the benefits of scale and acquisition budget. Can you not just sit on the sidelines and wait for the right things to percolate and then buy them at a billion?

    23. NA

      Yes and no. Um, yes, we can wait. Uh, that doesn't mean I don't need to learn. If I'm not paying attention to eight different players in the space, which I'm sure you do, too-

    24. HS

      Mm-hmm

    25. NA

      ... if I'm not paying attention to eight of them, trying to see who succeeded, why, what did they do wrong, what did the guys who got it right do, it's very hard for me to assess what made it work. Was it a fundamental-- Like, it was a bad idea. The technology is bad. Like, agents are not good. So agents are not gonna work. It could be that. Or this company didn't implement it right. The agents are still a phenomena. Somebody else is gonna execute it right. I need to understand the underlying technology for sure for, for-- to make sure that my team's thinking about it, and do we adopt it, adapt it, and secure it in the future, right? We bought a agentic AI company, Gateway, to, um-- six months ago. Didn't cost a lot of money. But I figured I was saying, "Listen, if everybody's gonna agentify the enterprise, how are we gonna know how many agents are running around the enterprise? How are we gonna keep track of them? How are we gonna govern them? How are we gonna secure against them?" I said, "The only way to do that logically is to find a way to aggregate agent traffic somewhere." If it goes through a certain gateway, a firewall, or some router, I can watch all the traffic, and I can stop an agent from acting. That's the only way it works. So I said, "The first thing you need to be able to do agentic security is to have some sort of a gateway." So we bought a gateway product. Now, I got it at the right price. If I wait, look at what's happening now. Suddenly people are waking up to the idea we need some sort of a router or a gateway that all traffic needs to go through because of optimization reasons, because of routing reasons, because of token maxing reasons.

    26. HS

      Would you have paid double?

    27. NA

      Maybe. It wasn't a big price, but, you know, I could have paid double. That's not the point. The point is, look, things I buy, either they're gonna help me 10X or 100X, or it's gonna fail spectacularly. It doesn't matter if I paid one or 2X at that point in time. Of course, I shouldn't be paying 2X and having it fail spectacular all the time, but the one, 2X doesn't make a difference. The one is to 10, one is to 100 is what you do. That's what we'd like to do as well, not from a economic return perspective, from a business value perspective in our, in our business.

    28. HS

      Are you more involved in corp dev today than you've ever been?

    29. NA

      No, I've been always more involved [chuckles] in corp dev. This is not a problem.

    30. HS

      Is that normal?

  10. 52:48 – 53:04

    Miss One Trick You Survive. Miss Three - You're Obsolete

    1. HS

      A lot of SaaS providers are feeling obsolete today. Their share price is telling them they're obsolete. Do you think that the majority of SaaS vendors have been oversold, or do you think that is an accurate reflection of where markets are moving?

    2. NA

      I think what the

  11. 53:04 – 59:27

    Is the SaaS Sell-Off Justified?

    1. NA

      market is telling us is that the system of work or the systems of record will see a re-imagination of workflows, as you and I talked. So going from software that doesn't have an opinion to software that has an opinion and expresses an opinion and also does a lot of work for the human so the human doesn't have to do repetitive tasks. I don't think those AI applications have been created. I think the SaaS versions exist. We all use them. I think at some point in time we'll see AI applications that do a lot of the tasks and workflow gets reimagined. I do think a lot of SaaS has built a lot of analytical capabilities that sit on top of the systems of work and system of record. I think it's a lot easier to abstract that data into some large data lake and have LLMs analyze that data for you and give you the answers. So I think the analytic world is getting reshaped already, where you can see people like Snowflake or Glean or Databricks, all these people boast enterprise data lakes where you can bring the data and run LLMs against it and get you much more synthesized analytics and outcomes than you ever had before. I think the third question, which we started off with, is, like, people are not sure how many people are gonna work in these enterprises in the future. So if you take the, the confusion of how many seats are gonna survive in the SaaS world, if you take the confusion around analytics are gonna get done differently, and system of work gets reimagined, so I don't know what the right valuation is.

    2. HS

      What do you mean analytics done differently? And so I'm-- Again, I- I'm-- Disclaimer, I'm a podcaster first.

    3. NA

      Oh, you get it. Yeah, yeah. You're a-

    4. HS

      I'm a podcaster, so-

    5. NA

      ... successful investor managing lots of people's money. That's true.

    6. HS

      Uh, but disclaimer, podcaster.

    7. NA

      Got it.

    8. HS

      Uh, I understand the seats question.

    9. NA

      Yes.

    10. HS

      I understand the workflow. Can you just help me understand the analytics?

    11. NA

      Well, if you look at most SaaS software, right? In the past many years, once you're fully deployed at a company, then somebody says, "Listen, I've got all this cool data about all your employees in my HR system, and I can help you get more insight in the HR system." Or if you take a Salesforce-

    12. HS

      Yeah, yeah, true

    13. NA

      ... they have a Salesforce marketplace with 300 apps you can use, which are analytical apps that feed off your own System of record, go-to-market data, it helps you analyze that data

    14. HS

      Do y- do y- you know Neil Mehta?

    15. NA

      Yes, of course.

    16. HS

      Yeah, I love Neil. I think he's-

    17. NA

      I do too. Great guy

    18. HS

      ... one of the most phenomenal people. Um, I'll never forget him being in London at Christmastime, and it was like, I think it was Christmas Eve or the day before, and he was spending time with me going through my pre-seed portfolio.

    19. NA

      Right.

    20. HS

      I think that just shows the hunger that he has for learning the day before Christmas.

    21. NA

      He wants to catch the school early company-

    22. HS

      Yeah

    23. NA

      ... so he can make lots of money like it. Yeah.

    24. HS

      But just so intent on finding the next thing. Um, and he always says the one question is like, "Are the company's best days ahead or behind it?" And that's a very helpful one.

    25. NA

      That's a great question. Good question. Yes.

    26. HS

      Are Salesforce's best days ahead or behind it?

    27. NA

      I don't know. That depends on how they execute from here on.

    28. HS

      If I were to paint a bad case for you-

    29. NA

      Mm-hmm

    30. HS

      ... what would that be?

  12. 59:27 – 1:03:45

    Are Chinese Open Source Models a Real Security Threat?

    1. HS

      see a huge amount of incredible open source models-

    2. NA

      Yes

    3. HS

      ... which are being used extensively, stay at a much cheaper cost. Do you think the proliferation of Chinese open source models is something to be concerned by or is an inevitable feature of a burgeoning ecosystem?

    4. NA

      So for a second, let's play the thought experiment.

    5. HS

      Mm-hmm.

    6. NA

      Take the word China out for a second.

    7. HS

      Mm-hmm.

    8. NA

      Answer the question.

    9. HS

      Do I think open source models-

    10. NA

      Yeah.

    11. HS

      No.

    12. NA

      You think open source-- I don't know what you're saying.

    13. HS

      I, I, I don't think open source models are a, a dangerous, uh-

    14. NA

      Right. So does it matter where they come from?

    15. HS

      Yes.

    16. NA

      Okay. So you're not worried about open source models. You're worried about Chinese open source models.

    17. HS

      100%. Uh, I'm not saying I'm not-

    18. NA

      Remember, there's a large tech company which also had open source models for a while.

    19. HS

      Sure.

    20. NA

      Right? So it's interesting to watch open source models. I think the question becomes in the future, do we end up with, you know, horses for courses? Do we end up with models that are very task-specific and very helpful in certain tasks, and do we always need to use this mega Frontier AI model for everything? And you already see that with ElevenLabs and, you know, the voice models that are out there which are specific to a task, and they probably do that task better than what the Frontier AI model does. So over time, if you believe the world bifurcates into many task-specific models which are gonna be useful for that task, that task-specific model could be better training across a depth in a vertical space. That's gonna happen with physical AI, for example. I don't think physical AI will be as easy as having a generic Frontier model because there's no consumer use case for physical AI, right? It's a depth use case only. So the question is, is your physical AI model that helps you fly planes gonna be the same physical AI model that helps you drive cars? Most likely not. Will it be the same physical AI model that does robotic manufacturing? Probably not. So you're gonna see depth in these models. So you're gonna s- gonna see a world of bifurcated models. There's some sort of orchestration layer As we've talked about, and you're busy finding orchestration layer companies that can allow you to pick the best model for the right task, that those orchestration layers have to get smarter and smarter. They have to understand the context, they have to understand the memory, they have-- So the question is, do I store my memory and context in the orchestration layer, or do I sto-store that in the frontier model? So-

    21. HS

      Which one do you think it will be? I know I'm the investor, I should know, but I don't.

    22. NA

      No, I li-- I think the, the challenge is right now the frontier models know this problem, and they're aggressively moving to incorporate memory and context into their models because they understand that's the mode. And the challenge is you have to pay for it twice. If you say, "No, I don't wanna use your memory and context," the model may not be usable if you use an orchestration layer. The orchestration layer today is not as well funded as these models. The risk is you end up in architecture where the model has a lot of context, and you cannot be model agnostic. You actually be model captive to get maximum efficacy and value for what you want to get done, right? It's not like, it's like you have a choice. You have to go all in on the model or you can't go all in on the model. You can't do with one what you can do with the other, and if you wanna do it with the other, you have to redesign an entire application that is deeply embedded with the capabilities of the second one. So in the world of bifurcation and horses or sort of courses, I think open source is a good thing because it allows you to play the cost curve, right? You don't need the smartest model to do the smartest thing. So open source is good. Whether it comes from a certain country or not, the question becomes, you know, what, what backdoors are you worried about that these open sources model ha- models have? What are you worried about that-- And that's true for any nation state, right? If there's a nation state sponsored open source model, what are the backdoors? Can I get in? Does the model wake up one morning and it's got a sleeper agent in it, it starts sending all the data somewhere else? Those are questions. Those can be secured. That's why you come to Palo Alto, to help you secure the models.

    23. HS

      Always gotta secure your backdoors. [laughs]

    24. NA

      [laughs] I don't know. What, what kind of night did you have? [laughs] Clearly this is not a hangry night. This is a different kind of night that I'm dealing with. [laughs]

    25. HS

      It's Monday morning. [laughs]

    26. NA

      Got it. All right.

    27. HS

      Just terrible.

    28. NA

      Back to work. [laughs]

    29. HS

      Um, t-too-

    30. NA

      What is the best time for me to show up here? [laughs]

  13. 1:03:45 – 1:08:52

    What Nobody Tells You About Having Money

    1. HS

      I've got two questions, then we'll do a quick fire. One is, um, uh, with the incredible success you've had, um, you've made a lot of money. Um, and, and just a question I have is like, what does no one know about having money that they should know? Like one thing for me is I've become much more impatient, and we have very different... You're, you're far more successful than me. I've become way more impatient. No one told me I'd become impatient. I, I'm used to a good quality of, of everything, and now when it's not that, I'm very pissed. I don't like that in myself. I-- But no one told me it would happen.

    2. NA

      What are you gonna do to fix it?

    3. HS

      Therapy. [laughs]

    4. NA

      [laughs] This is the common Western solution.

    5. HS

      Yeah. [laughs]

    6. NA

      Yes. [laughs] Have somebody else tell you. You come back saying, "Oh, I must feel better now because I told somebody that I was going to therapy."

    7. HS

      My therapist told me I should put myself first more often.

    8. NA

      And you came back to being impatient because that's how you put yourself first, more important. Believe in yourself, right? Is that what you're supposed to do?

    9. HS

      Yeah, yeah.

    10. NA

      Optimize for yourself.

    11. HS

      Yeah. Put myself first.

    12. NA

      Be confident in yourself.

    13. HS

      And it was your dad's fault. [laughs]

    14. NA

      Oh my God. Is that what your therapist told you?

    15. HS

      Yeah, yeah, yeah.

    16. NA

      It must be British.

    17. HS

      Always. Yeah.

    18. NA

      Okay.

    19. HS

      Um, but no one told me that. I, I kinda wish they had done. Uh, what, what does no one tell you about having money that they should?

    20. NA

      I think it's not about money as much as it's about, it's about success. Remember, we all follow Maslow's hierarchy. I came to the United States with two suitcases, $200, and I was willing to do anything, anything at all within reason or the right side of the law, to make sure that I made a life for myself because there was no way to go back. I was gonna use a different word, but I'm not gonna use it because you'll go crazy again. So-

    21. HS

      [laughs]

    22. NA

      [laughs] There's no going back, right? It was a one-way ticket, which I did not have. I had no recourse. So I was willing to do whatever it took. I took notes. I, you know, became a security guard. I tried to pump gas for a weekend.

    23. HS

      You became a security guard?

    24. NA

      Yeah, when I came to the United States, I was a security guard. I took notes for the disabled. I flipped burgers at Burger King. I had $200. I had to find a way of paying my tuition.

    25. HS

      Which was, w-was one quite transformative to your mindset? Did you hate them? Did you love them? Like, what was that like?

    26. NA

      It had to be done. It's karma. This is when you come from Eastern philosophy, it's karma, right? It's destiny. This is what you need to do to break your destiny, so you do that. So you don't worry about what you have to do. Now, at that point in time, there was no-

    27. HS

      Did you always know you were gonna be successful?

    28. NA

      I don't know. Who knows? Nobody knows they're gonna be successful. You just come in and do your best and hope for the best and see what happens. So that's very Eastern, Eastern philosophy, right? You b- you believe in karma, destiny. How do you manage billions of people in the world? You make sure they believe in destiny. If they believe in destiny, then say, "Oh, this must be what was my destiny in the end. I tried my best. This is where I ended up." That is better than your therapist. Just, like, keeps you centered, saying, "Okay, I tried my best. I gave it everything I had, but perhaps this is what God intended for me." Do you find that hard to believe?

    29. HS

      If you were my therapist, I don't think I could afford you, though. That's the problem.

    30. NA

      But see, this is free. You're getting to-

  14. 1:08:52 – 1:10:53

    How to Be a Great Father Without Sacrificing an Inch on Work

    1. NA

      Yeah, this is the hardest problem in the world. I think there's, what, 20, 30 billion people who have been born since the beginning of civilization, yet there's no AI that can train us on what we need to specifically do to create the outcome we'd like to create [laughs] 'cause way too many variables, right? There are all kinds of people in the world, and I'm sure their parents, some of the parents are amazing, some of the parents are not as amazing. So I think part of it is you can do your best from your perspective, and I think kids absorb a lot by watching you, your work ethic. They watch your values to see how you interact with them because y- my daughter probably has a better sense of who I am as a person than anything I could tell her because she spends time around me. She sees me interact in every sort of micro situation, what makes me impatient, what makes me patient, what makes me do certain things. At the end of the day, if your child believes that you have the best intention for them, I think that goes a long way.

    2. HS

      I totally get you. It's, uh... I had a guest on the show, and they said, "Watch, um, National Geographic if you wanna be a good parent." And I said, "What?" And they said, "Look at the elephants." The, the children follow, and so if you want your child to be nice to waiters, be nice to waiters. If you want them to work hard-

    3. NA

      Yes

    4. HS

      ... work hard.

    5. NA

      Yes. But that's true in organizations too, by the way. Organizations take on the form of the leader. I'm pretty sure if you close your eyes and you rattled off, you know, five or six attributes of a company and said it's a company, has a founder, and say, "How do you compare the company's cultural values vis-a-vis the founder?" And you'd find a remarkable resonance between the two things. Companies act... Because remember, the organization's trying to please the founder 'cause they figured out that's the way to achieve success. If my CEO is impatient, if my CEO is exacting, if my CEO is ambitious, my CEO suffers no fools, gets stuff done, then that must be what they want to reward. So you suddenly find if you-- This, again, depends if he has the right values or not. You told me a story about a guy who had different values, and they had to shut the company down. But if you have the right values, people will watch your behavior and want to emulate your behavior.

  15. 1:10:53 – 1:16:37

    Quick-Fire Round

    1. HS

      I wanna do a quick fire 'cause otherwise I'll take up all of your time. Um, what is a belief that is held by most top investors and founders in Silicon Valley today that you think is wrong?

    2. NA

      My concern would be at this point in time, given the, um, pace at which technology's evolving, given the uncertainty in terms of what's gonna work, what's not gonna work, I worry that it might be too much euphoria and a bit of FOMO going around in terms of, "Oh my God, if I don't invest in something that's interesting and the right founder, I'll be left out." And because people have seen this happen. Look at what's happening at Anthropic, right? If you missed the first round, the second round, the third round, the fourth round, the fifth round, then you look like a guy who doesn't have money. Now, you had 20 years to invest in SpaceX. You had three to invest in Anthropic. That pace is fundamentally different. I'm sure as many people are happy that SpaceX finally went public, as many people are probably sitting there saying, moping, saying, "Damn, I should have done the Anthropic round two years ago when they showed up on my doorstep." So I think there's a lot of FOMO coupled with euphoria on the other side, and I think the risk is that we think every company that is gonna show up now is gonna be the next Anthropic, so we better get into it.

    3. HS

      My next one to you is any moment, any board meeting, what was the biggest, "Oh, shit," in a board meeting?

    4. NA

      I got a very interesting, an insight from one of my board members. Um, as you know, we're prolific buyers of companies because I'm constantly paranoid that if we haven't built it, somebody else is gonna build it, so we better go acquire it and find the team to go get it done. And, uh, there's one particular acquisition. It took a lot of effort to get the founders to the table, get them to agree, grind through diligence, figure out whether it's gonna work or not. And it's, it was a substantive amount of money, relatively speaking, hundreds of millions of dollars, close to almost a billion dollars. And I call one of my board members, and I said, "Hey, what do you think about this?" He said, "You're calling me. You don't call me all the time about all the acquisitions you do, so this must, this one must be different." I said, "No, it's not different. I'm just thinking hard about it. It's taken a lot of effort." He says, "Go for a long walk. Ignore all the effort you put in." He said, "Because sometimes what happens is you confuse effort with wanting to get the outcome 'cause you spent a lot of time and effort trying to get it, then you feel like when you get it, you better take it because you put all the effort in." And he says, "You haven't spent a dollar yet. You just put in three months of effort. But remember, once you put the dollar, then it becomes yours. It's your job to make it successful. So you still have one more chance to decide if you want it or not. I'd go for a very long walk and say, 'If this walked in the door right now and there was zero effort involved, all I had to do was write the check, would I take it or not?'"

    5. HS

      Forget the sunk cost.

    6. NA

      Yes.

    7. HS

      You have the same in the investing business. You spend so long-

    8. NA

      Yes. Yes. You spend a lot of time, you're like, "Oh my God, I'm the one getting the term sheet and nobody else has it. I nailed it. I've beaten out eight VCs to it." The question is not how many VCs you bor- beat to get the deal, the question is if this deal, can this deal stand its own merits, and would you invest in it if there was no competition?

    9. HS

      What's the best advice you've ever been given?

    10. NA

      The best advice that the really old man gave me on a flight once was, "You know, life is simple. If you wake up in the morning, you're really excited about going to do what you do for a living, you're blessed. And if you're done after a long day and you're really excited to go home to your family, you're blessed."

    11. HS

      [laughs] I do wanna end on a note of-

    12. NA

      Do you like that?

    13. HS

      I do. I do. And I actually tweeted last night, I hated school when I was a kid. Sunday nights was the worst.

    14. NA

      Yes.

    15. HS

      And like my Sunday night last night was like thinking about our show and the conversation. What a great Sunday night. What a great Monday morning.

    16. NA

      I was, I was, I was not sure where you were gonna go with that. [laughs]

    17. HS

      No, no, no. Like what a, how lucky am I?

    18. NA

      There you go.

    19. HS

      Seriously.

    20. NA

      Yes.

    21. HS

      It's amazing. Um, final one. What are you most excited for? When you look forward next five to 10 years, what are you most excited for? Is it becoming a grandparent maybe? I'm, I've just seen my mother become a grandmother. It's amazing. She's amazing. Is it the health benefits? You know, I'm so excited that AI might be able to solve multiple sclerosis, which my mother has. That'd be incredible.

    22. NA

      You never know what tomorrow's gonna bring you. So it's, the only way I've been able to do everything I do is not to get too hung up on what's gonna happen to me in a year from now or five years from now, because that's too far. I think you wake up in the morning, you have an amazing day, and you know, you're, everything's working around you. Your kids are happy, your family's happy. You enjoy what you do. You have good friends. And I was at a different sp- place the other day, earlier this week, and they asked me like, "You're not a 996 CEO, what do you do?" And I said, "Look, I try to make sure that I can find something to enjoy every day." Because I have enough things to worry about. I could really get myself in the wrong head space by worrying about a lot of things. I run cybersecurity, for crying out loud. You know? I, I live off the fact that somebody's gonna hack somebody at some point in time. My phone rings saying, "Can you help us?" It's like, "Why didn't you spend the money before? But can I help you?" I say, "I can help you." So I think it's a, it's a state of mind thing. Can you get your state of mind to be optimistic, positive, and one of gratitude and happiness every day? If you can, it's gonna be great. But guess what? If health benefits come, you know, I, I can start being Benjamin Button, be amazing. If my kids are continuing to be happy and successful, it'd be amazing. If my mother, you know, lives for 150 years and she's happy, it'd be amazing. There are so many amazing things that happen and perhaps may not happen. So let's just focus on tomorrow.

    23. HS

      Nikesh, I so appreciate you being willing to come back-

    24. NA

      [laughs]

    25. HS

      ... for a second. I mean, after the first, when I suggested it, I was like, "There's no chance he's doing this." [laughs]

    26. NA

      [laughs] Good thing I have to go back and listen to the first one now.

    27. HS

      But thank you so much. You've been incredible.

    28. NA

      Thanks for having me

Episode duration: 1:16:37

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