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My strong assumption is moving forward that we will actually need more engineers, not less.
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The goal is not efficiency.
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The goal is to be able to go out and make sure that we benefit from the original insights that AI generates that allow us to solve problems we could have never dreamt of solving before.
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Do you know how many people in their 50s how much money they would pay to [music] get back to being 19 if they could?
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This is a magical time to be alive in tech.
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Today I'm talking with G2 Patel, Cisco's president and chief product officer.
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We're going to discuss how G2 is bringing a founders mindset to Cisco, going allin on AI, what's happening inside the massive data center buildout that they're at the center of, and then we'll talk about what founders can learn from G2's incredible personal story.
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G2, thanks so much for being here. >> Thanks for having me. It's great to see you.
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you have this incredible background um from growing up in India, waiting tables at Sizzler to ending up as the president of one of the world's largest companies.
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But before we talk about all that um I want to talk about like Cisco today and your unique role and what you're doing there.
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The way I think about my role is my role is I just make sure that we help build the best products in the world that all of our customers can use at scale.
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What Cisco does though, which is even more interesting than what I do, is we think about us as the picks and shovels company during the gold rush.
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We are the AI infrastructure company or the AI era during this massive movement that's going on right now, which is a secular shift.
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And we want to make sure that we provide the right level of infrastructure so that it just AI just runs the way that you want it to and it runs securely and safely.
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And that description of Cisco, which I love, picks and shovels for the AI era, clearly you would not have described Cisco that way four years ago.
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So all of this is recent.
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This is a transformation of a very large company that's already was already operating enormous scale.
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Um, what has it been like to come in and try to transform an organization at this scale at that sort of time frame?
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>> You know, I think in these massive kind of shifts that happen in companies, uh, typically the leaders get an undeserved level of credit and the people that do the work don't get enough of the credit but the reality is is I didn't write a single line of code when we were doing this it is the team that did that u but what we did was we made
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sure that we actually set the right direction hired the right people in the right jobs made sure that we had the right kind of mechanisms to figure out what markets we're going to go pursue and do it with everyone feeling like they can they can win >> can you tell the story of how you ended up at Cisco and what you're doing there. >> So I ended up at Cisco. I was a box. I
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>> So I ended up at Cisco. I was a box.
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I was uh running product with um you know for Aaron uh Levy um who is a founder himself and so my entire kind of mental model got reinforced again when I came to box because I had started my own company years ago and then I went to EMC.
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EMC was a very large company.
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I'm like ah this is like very corporate and I went to box.
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I'm like, "Okay, this can be fun because you can actually operate just like I used to operate in my own company."
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And I think there's two kinds of people.
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There's folks that are very good functional leaders and they love being in their lane.
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Uh, no one tell me what to do in my lane.
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I'm not going to tell you what to do in your lane.
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And then there's people who've run some kind of business and they think of themselves as owners of the business and they are completely comfortable poking in other people's businesses all the time.
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And I tend to be of that ilk.
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And so I personally feel like when you have this founder mode approach, it's very good for wartime and it's very good for a time when the market's going through a shift, things are moving at a very fast clock speed.
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And what you have to do is you just have to make sure that you don't completely alienate the people who might not be in founder mode >> and kind of help them understand the benefit that if you do go in founder mode, we can actually operate at a very different frequency than what we've been operating so far.
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And so that's what we started doing at Cisco.
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And I feel like I tell my my peers and everyone at my company, I'm like, I feel like I'm a latestage co-founder of Cisco.
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I was 36 years late coming in, but I feel like I own the company and this is my company.
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And if um if anyone from the outside tries to um screw with the company, beware because I'm going to make sure I fight for it.
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And we got to make sure that we we take a lot of pride in the craftsmanship and what the company stands for. Everything is your job.
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And so if something's not working well well in sales, I'll go talk to the people over there.
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Something's not working well in marketing, I'll go to talk to the people over there.
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And I fully expect them to come poke holes in my business.
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>> Is this one of the reasons why you like to bring in former founders at Cisco?
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You know, I also recognize the um and appreciate the value of seasoned operators who are systems thinkers >> because if you had everyone at Cisco who was a founder, it'd be a show. >> Yeah.
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>> Uh so you have to make sure that you get you get a good balance.
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The way we've done it is we have um I try to call it a rule of thirds.
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So a third of my leadership team are people that know how to maneuver Cisco that are at scale operators.
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The second third are people that I bring in from the outside from competition from the market that are very market in >> uh that might not know how to maneuver Cisco but they're systems thinkers and they've operated at scale and then the third third are co-founders and CEOs of companies that we've acquired >> but those people we give them charters that are larger than the company that they've sold us.
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>> You said earlier that this way of operating is especially important in wartime.
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Do you feel Cisco is in wartime?
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I feel like Cisco is in wartime right now.
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Um in the sense that we have [snorts] we have made one of the most successful turnarounds that you've seen from a product perspective.
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Um I think we are now squarely in the AI infrastructure game.
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Uh which is something that no one would give us credit for three years 3 four years ago.
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But if you look forward the next 3 4 5 7 years um the amount of u opportunity that exists in front of us is so massive compared to anything that we've experienced before that we have to make sure that we can we can capitalize on
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all of that and that means that we have to operate at I I like to tell my team internally we should operate like the world's largest startup that means you have to operate at speed but with scale if If you just operate at ski at speed, then you're just a startup. If you just
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If you just operate at scale, then you're just the largest company.
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If you want to operate as a world's largest startup, it has to be with speed and scale.
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>> What are the key things you need to get right in the next few years to seize that opportunity?
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Let's assume right now that we have sub 2% of the of humans that are using agents in any kind of power user capacity and think about the fact that the entirety of infrastructure that gets produced today is getting consumed.
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We are short on infrastructure.
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We're supply constrained >> with only sub 2% of the people using agents.
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>> Imagine when 25 30 40 50% of the people start using agents.
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the amount of infrastructure you're going to need is going to be at a very different scale proportion that we have right now.
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And we want to make sure that we can help solve that problem.
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That's problem number one.
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Problem number two is these agents, in fact, this this week was a very interesting week because these agents are going to go rogue at times.
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They might actually have a mind of their own.
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It's actually harder and harder to distinguish between when an agent has uh is operating with malicious intent because of uh an adversary influencing the agent or poisoning the agent or an agent just thinks it's the right thing to do and they're just kind of, you know, diligently going out and following your goal command.
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>> The paperclipip optimizer problem. >> Exactly. Yeah.
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And so what we have to have is you have to have some kind of safety, security, and observability capabilities in place.
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Um, and so that's the second big problem that we want to solve is we want to make sure that AI is safe to use for everyone.
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And that that's that doesn't become this constant fear because of which people don't use AI.
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Uh, in fact, I think it's the other way around.
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If you if you don't use AI, you will be less safe.
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And and that is in that is true because most of the attacks are happening at machine scale.
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So you have to have the defenses at machine scale as well.
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So we're one of the largest you know networking companies in the world that provide the infrastructure.
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We are also one of the largest security companies in the world.
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We want to make sure that we do that.
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Then we are also one of the um you know one of the most significant kind of machine data companies in the world with Splunk. >> Oh that's right.
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And so the combination of those three should give us uh all of the underlying apparatus that's needed so that we can become critical infrastructure for the critical infrastructure companies for the AI era.
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>> You've gone all in on AI both in terms of investing in the AI and data center market but also in terms of bringing AI into Cisco to make all make everything more efficient.
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I'm actually really interested to learn what it looks like to adopt AI at a company the size of Cisco.
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It can't be around efficiency.
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The goal is not efficiency.
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The goal is to be able to go out and make sure that we benefit from the original insights that AI generates that allow us to solve problems we could have never dreamt of solving before which is very different from just get to be 20% faster at doing this or make sure that you have less people.
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In fact, my strong assumption is moving forward that we will actually need more engineers, not less as we move forward because every single time I've seen a step function improvement in AI, I've seen a bottleneck that's emerged that's a human bottleneck.
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You know, coding is automated, code review becomes a bottleneck.
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Code review is automated.
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Judgment on what to build and what not to build becomes a bottleneck.
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So, I I do feel like we we're going to need to have more people.
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But what what was interesting was getting 32,000 engineers and the rest of the company.
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One, to taste the honey, and two, not be fearful of the fact that if you use this, then you're going to actually be creating a trap for yourself or you might lose your job.
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Instead, what we did was we did something completely opposite.
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We guaranteed our employees that if you don't use AI, you will lose your job.
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>> And so, it it was a very different way to kind of approach the problem.
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That wasn't a very controversial statement to make because think about today if you had someone that didn't know how to use a PC or didn't know how to use the internet like would you ever hire them in a knowledge worker job? You would never.
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So it's not that controversial to say that if you are seeing a secular shift and if there's this massive platform that's going to get refactored with AI then anyone not using it is just not going to be that relevant.
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And so we always believe that there's going to be only two kinds of companies and two kinds of people.
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Ones that are very fluent and dextrous with AI and the others that are going to be really struggling for relevance.
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And so we just made it very very clear for people that if you happen to be in that second camp because you're not using AI, chances are that Cisco is the wrong place for you.
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And therefore what you should do is go all in.
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And we will give you all the tooling and all the support to go all in.
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And initially we actually gave everyone unlimited tokens to just start using it because the way I think about it is you have to get it's like riding a bicycle.
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You have to first get familiar with something then you have to get good at it and then you can become efficient with it. >> Yeah.
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>> But if you try to go efficiency first you'll never get familiar or you'll never get good.
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And so we started doing that got a lot of initial resistance from a lot of folks.
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The first few months were rough.
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And the the seinal moment for me was I have this one engineer who's engineering leader in my team, one of the most amazing people.
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And he is always a skeptic.
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He's always going to tell me, Ju, those ideas are crazy.
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I don't think it's going to ever happen.
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And he called me one day in the evening and he was as sincere as he could be.
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And he said to me, hey, I just want to let you know I was wrong. You were right.
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The models are moving at a pace now.
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And I had some benefit because you know Kevin wheels on our board and I had some you know kind of I I knew some people within the ecosystem that every time I talked to someone in a startup world um I was getting a very different set of data than I was I was I was getting internally.
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getting internally. And so Will says to me finally this has now moved where we have now taken and refactored like you know half a million lines of code and we were able to refactor it into like 120,000 lines of code or something >> and so 5x improvement and we were able
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to do that within like 2 weeks >> you know and so one you are right that this is actually going to move really fast >> so I can't just think about what we have today I have to think about the fact of where is this going going to be in 3 months from now, not a year from now, 3 months from now. And assume that and
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And assume that and start making the changes today.
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>> But second is I'm also feeling very anxious about the fact that this might mean a lot of bad things for people and we might have to make a lot of changes in our staff.
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>> And I'm like or we can actually motivate everyone >> to make sure that we can um we can all get better as a result of the use of this.
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Then you know it just kept compounding.
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We actually became the first design partner with uh with OpenAI and Codex.
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They gave us some FTEEs and then I to this date um every um I think it's every two or three weeks now uh I sit down with my entire leadership team of engineering and then their FDES and we talk about like what went right, what went wrong in the past two weeks and um it it was just very clear to people that I'm just not going to let this one go.
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And I think that's in large companies, there's a few things where you have to go top down.
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Most things it's going to be pretty hard to go top down, but a few things that you think are religion, you have to go top down and you have to just make sure that you're unrelenting on those. And AI was one of those.
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>> We've all seen how AI is transformative for software development, but Cisco does a lot of hardware development.
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>> Y >> are you seeing the same impact on the hardware development side or is that still a in the in the future?
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So the Cisco does software, hardware, and silicon.
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And each one of them have a different kind of adoption cycle.
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So on the hardware side, you're starting to see um good kind of design patterns that are starting to emerge now.
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U but it's not quite as much as software.
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Software at the clock speed is really fast.
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fast. silicon there's a level of intentionality of not going allin by the team because they're very concerned about making sure that the data and the IP >> does not leave and then before you know it someone else has replicated it >> right >> you know and so on the silicon side we
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had gone a little bit slower but now um I think with the models getting better um with open weights models being there having our own infrastructure all of that I think it it's going to change but we we have to compress rest the cycle time for silicon. The thing that's
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The thing that's interesting in our business is we are a full stack, right?
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Like we build silicon, we build photonics, we build systems, hardware, software, the entire stack.
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Each one of the elements and layers of the stack have a different planning cycle.
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So silicon is a 5year planning cycle.
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What I do today uh I have to make sure that I know what's going to happen for atcale production 5 years from now and then make the appropriate investments today. >> That's bananas.
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How can you possibly do that in the AI?
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AI is only three three years old.
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think about the entire um manufacturing cycle of not just the silicon but silicon to systems to SDKs to taking it out to the market.
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You have to make sure that you start because in order to build the silicon you have to build the IP for the silicon like certis and all those pieces and those take actually um you have to build them up ahead of time.
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So like there's a sequencing that needs to happen in silicon that cannot happen within a matter of like you know you can't just say go build a chip in 12 months and you can build a chip it just won't be that good.
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Hardware tends to be um you know 18 to 24 month planning cycle maybe 30 months in some cases because of supply chain because we think about it we're doing this at scale for very large volumes of um of units.
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You go to software and operating system.
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That is a 12 month planning cycle, maybe 18month planning cycle.
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Then you go into models and agents and apps.
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Now you're into a three-month planning cycle, maybe a weekly planning cycle.
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And we have to make sure that that codeesign full stack actually has all of those things working in harmony.
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And if you can figure that out as a company, you have a very strategic mode in the sense that you've been able to figure out all these different layers that work well together from an IP.
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That's that's very hard for other people to do and replicate.
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>> Is it possible to speed up those cycles now that AI is here? >> Absolutely.
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All of them will get compressed.
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But when I say planning cycle, I don't just mean how long does it take to build it.
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I I mean from idea to at scale production with billions of dollars in revenue.
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Speaking of chips and hardware and this whole supply chain, I want to talk about the data center buildout because there's this incredible historic event happening.
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We're building more stuff than we built in a in a in a a generation and you're at the center of it.
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Can you talk about the role that Cisco is playing in this huge data center buildout?
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huge data center buildout? So in data center buildouts by the way everyone knows the role the GPU plays and what had happened was when you just started seeing these transformers come about these transformers would fit on a single
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GPU and so the the training runs would be pretty simple and then uh you had more parameters and those GPUs needed to scale and so you had eight GPUs within a server and so you now went into a server but those GPUs were all interconnected within a server. Then you had racks of
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Then you had racks of servers, GPUs got interconnected with an arocco server working coherently like one, you know, kind of giant machine with um things going and then racks started scaling to rows because you now had multiple rows of racks that needed to be worked together within a large data center.
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Um and that required what they call scale out networking, not just scale up networking for um um for for rack level scaling.
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And now what you have is because there's such a huge power constraint and power shortage, you can't always bring all the power to where the data center is.
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So what you do is you go to wherever the power is available.
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And so you might have data centers that are hundreds of kilometers apart that need to then work like one completely um logical unit.
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>> Oh, two different physical data centers separated by hundreds of miles that need to beworked together as if they were in the same building.
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>> As as if they were in the same building as if they were the same computer. >> Wow.
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>> That requires a whole different family of networking called scale across networking.
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For within a data center you might have scale out networking and for within a rack you have scale up networking.
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We are largely focused on scale out and scale across and we do not just the silicon and the switch trays for connecting the GPUs together but we also do the photonics which is the optics.
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We started our business selling to hyperscalers two years ago for AI workloads and we thought we'd do we'd give the market uh this tree of guidance and said we'll do a billion dollars in orders taken. >> We ended up at 2. 3 billion in year one.
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>> So the next year we said well let's double it instead of 2.
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3 let's do like 5 billion.
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Last year which was a Q4 that just ended month ago uh we ended up at 9 billion. >> Wow.
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Both years you doubled the very optimistic projections that you made. >> Yeah.
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And so we basically went from zero to 9.
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3 billion >> billion >> in a matter of two years. >> Wow. >> Right.
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And so that's the speed at which this is moving.
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We still have so much share to go out and capture.
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It's a complicated business.
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$63 billion in revenue, hundreds of products um that we have to kind of make sure that we maneuver in the right way.
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>> But the 9 billion out of the 63 billion total is like quite material for a brand new business line. nine billion in orders.
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That takes a while to get to revenue, but >> I see. Yeah. Got it. >> But but you're right.
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It's it's it's starting to get to be meaningful and it's exciting because it's you're right in the thick of things >> and the market is so huge.
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A g a a gigawatt of capacity would cost about anywhere between it used to be 35 billion now it's like close to $50 billion uh is what a gigawatt of data center capacity would would cost to build.
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And about 10 to 15% of that tends to be networking.
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Largely it's in the GPU and but there's a huge amount of complexity in you know you have to build out the shell and you have to build out the power permits for that and the you walk into a data center it impresses upon you on how complicated when you make a query on your prompt to say give me a pizza recipe.
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What happens behind the scenes to get that to you within um a second or two?
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>> Because the buildout is so extreme.
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Some people have wondered whether we are overbuilding.
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Are we >> categorically not? And let me tell you why.
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And people try to equate this.
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Firstly, in AI there are no priors.
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So I do fundamentally believe that and this is one of the big mistakes people make is they keep going back to an experience they've had.
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I think one of the most important skills to learn um in AI is unlearning because your past experience can be a huge liability.
21:53
But people typically will try to equate this to the dotcom boom days.
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Oh my goodness, there was so much infrastructure buildout that happened.
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What was happening during that time is you were building out infrastructure and you were hoping that demand would catch up to the supply.
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Right now, no matter how much infrastructure you're building, >> it's getting consumed almost instantly.
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So it's there's no patch of time like you're supply constrained despite the exponential growth that looks like a vertical line.
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So I do feel like from that perspective I don't think that there's a um there's a huge um overbuild.
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In fact I think it's the other way around if sub 2% of the people are using agents and these agents are so consumptive on average an agent is 450% more consumptive on network bandwidth than a human would be.
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We're conducting the same exact task.
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Now think about trillions of agents, >> right?
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>> Um, and now think about most of your tasks getting conducted by agents where they're going to have to make sure that they keep enriching context.
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You have a skills file, you have a markdown file, you know, you've got the GStack from Gary, and it's going to keep going back and forth.
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Like, there's going to be a lot of back and forth that happens.
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>> It's going to be a lot of tokens. >> Yeah.
23:00
Speaking of agents, I heard that you've recently become a fan of using your own personal agents.
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I'm curious, what what is what does your usage of agents look like?
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So, I've been using it for a while, but instinct was the force multiplier for me.
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And this is just like 4 days ago. I I suck at email. Really suck at email.
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Like I I had 171,762 emails or something just like 5 days ago.
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146,000 of them were unread. >> Okay. >> I used instinct.
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I took the leap of faith and said, "You know what?
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I'm going to go give it my personal email access." Uh I have 200 emails. Wow. Yeah.
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>> It blasted through your entire inbox.
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>> It took care of everything. It told me what to do.
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It actually moved things and archived them in the right way.
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If I needed something, it would bring it back.
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It actually summarized my news news for me from all the sources that I was getting.
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I I was feeling even though I didn't really do email that much, I there was a part of me subconsciously that was feeling overwhelmed.
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And I just feel better that wow, I'm I'm on top of that now.
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All of a sudden, I'm checking email.
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I'm like, why am I checking email?
24:07
M because it's fun to check email when you have three emails.
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>> It really ties back to the the point about the data center buildout never being sufficient cuz like think about the tokens to go through 140,000 emails and figure out what to do with it.
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This is where I feel like I just don't think it is unfortunate in some way that the level of kind of um exaggeration that happens on oh my goodness this is a bubble everything's going like you might still have the two conditions can hold true.
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conditions can hold true. You will have a secular shift where this is going to completely fundamentally change the way that people live and that's going to require a lot of infrastructure and you will also have some companies that are very frothy in valuation because from
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time to any any kind of massive platform shift like this you will have a ton of experimentation that goes on and only a few of those are going to win not not all of them win and so there will be some frothiness in the valuation but that does not constitute in my mind a bubble. bubble is if that secular shift
25:03
bubble is if that secular shift itself is questioned and I think it's very hard to go out and argue for that.
25:10
>> So um it's been in the news recently this um open AI agents went rogue compromised hugging face and and other places.
25:18
What are what are your thoughts on what's happening with AI safety now?
25:22
And also how does that play into like deploying AI at a large like missionritical enterprise?
25:28
>> Yeah, I think it's a great question.
25:28
>> Yeah, I think it's a great question. One of the things that I would say right now is it is going to be the defining um you know kind of topic of our time right now in the next um next few years because the constraint and infrastructure was a
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really big deal and we were talking about a lot about is there compute available that's still a problem but a much much larger problem is whether or not I can trust these systems that I'm going to delegate all my work to and all my personal life to. The difference
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The difference between trusted delegation and untrusted delegation is the difference between market leadership and complete abject bankruptcy >> in my mind.
26:04
So like I think we have to make sure that we actually get through that and that requires uh a bunch of things and we are actually Cisco is working a lot on making sure that we can provide a whole agentic security platform that we'll we'll we are making available to the market.
26:21
are making available to the market. Uh that everything from having full visibility on what goes into a model to identity for non-human identities and inventorying what agents are running within your environment to actually doing validation on the models itself um which includes algorithmic red teaming to say can you uh jailbreak this model and if you do jailbreak it and you asked
26:46
it a question that you didn't want it to um have it have a response or if you had the agent conduct an action that you didn't want it to conduct, how can you intercept that and make sure dynamically at runtime you can put you can enforce
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guardrails that entire apparatus we actually make available including the security side but also the observability side um and we fuse it together and I think that's it's one of the most important issues of our times. >> It's very cool that you're building it
27:12
>> It's very cool that you're building it not just internally but you're actually going to build it as a product.
27:16
>> No, we have it available in the market.
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In fact, we have a product called AI defense which is the core foundation of that that we launched a year and a half ago.
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It's doing ex exceptionally well and um we just need to make sure that we get to more and more of it and that was only done for the chat era.
27:29
done for the chat era. So we did that initially for the model and then we extended that to agents and so now what we have is dynamic monitoring of agents at all times and you know if you ask an agent for a refund it shouldn't be giving you three times the amount that
27:45
you paid for the for the pair of shoes you know and that's something that happens all the time in in the retail industry and so that's we acquired a company called Galileo um there were folks from Deep Mind and um and Uber that um that came along And then those folks have done a great job. Uh they're
28:01
Uh they're part of the Splunk team and they've done a great job on it.
28:05
>> Can you take us back to your early career and help us understand how growing up where you did and the early jobs that you worked like led you to be in this unique position to have such a transformative impact.
28:17
Now >> when I look back now, I was very fortunate.
28:20
At the time, it didn't seem like I was very fortunate, but my dad was a high stakes con man.
28:27
>> He was like Bernie Maidoff.
28:27
uh he would swindle people for money.
28:30
Uh at some point it got dangerous for me to live in India.
28:34
Um and there were people who were looking to kidnap me. He had a mistress.
28:39
That mistress had committed suicide.
28:39
I didn't want to stick around. >> Oh my goodness.
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>> You know, it was it was you could make a movie out of that that that that part of my life.
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And so what I decided to do and my he was very abusive to my mother and I was very close to my mother.
28:52
And so both of us escaped and she decided to um you know uh live in um a place that was undisclosed and I said let me just go out and check out America and see if I can check out some schools and all of that. Came over here. >> How old are you? >> I was 19 at the time. 1991, right?
29:10
And so uh I came here, my uncle put me up for a while, waited on tables at a fine dining establishment called Sizzler.
29:19
um average tip of a dollar and um you know there were a few seinal things that happened during that time that really gave me a mental reframing because I was a terrible student in school.
29:33
Um I wasn't really that you know I was a black sheep of the family in the sense that a lot of my cousins were all very smart academically and I was not and so I always had this kind of inferiority complex.
29:44
I used to stutter and so I would always stay quiet.
29:46
would always stay quiet. um I couldn't say hello when I picked up the phone and so there was all of these kind of things that were happening and then I started waiting on tables and I'm like boom you have to figure out a way to entertain or you will not make money and then I came
30:00
um you know when I was over here I was in undergrad I came across this company docu and they wanted to give me an internship because my professor said to me hey you might want to get an internship here she was my mentor in school and she was great and so she um made an introduction And so I I got a job as an intern. Like
30:17
Like few months later, the guy comes to me, the founder, and says, "Well, we're going to my original investor is going to um leave.
30:24
We're going to buy them out."
30:26
I'm like, "Oh, I want in."
30:29
And they're like, "Well, each one of us put putting in a quart million dollars.
30:32
You can put in a quart million dollars and you can have in."
30:34
I went to one of my the people I knew and uh he was um he was a banker and I asked him like, "I need a quart million dollars."
30:42
And he said, "Why do you need a quarter million dollar?"
30:45
So I'm like, I'm going to buy this company.
30:46
He goes, "What are you going to do when you buy the company?" I'm going to run it.
30:48
Now remember, I wasn't a founder of this company. I was an intern.
30:52
>> You were you were an intern.
30:52
You were still in college at the time.
30:55
>> I had just The first loan I took was 10,000.
30:57
The second loan I took was 250,000, but the first loan I took, I was still in college. I was minimum wage. >> Yeah. >> Right.
31:04
And I said, "Give me give me some money and I'll pay it back to you." He said, "10% interest."
31:08
I ran that business for 17 years and now it's like a sub $5 million company.
31:12
you stayed there for 17 years.
31:16
>> It was in some ways my biggest mistake in my career um because not because the company wasn't good is because the business model did not align with what I wanted to do in life and what and sometimes you know like our CEO Chuck tells me he's like grew once you actually go public um you can't alter your business model that much.
31:38
Your business model is your business model.
31:39
takes it takes a lot of effort to alter your business model.
31:41
But when you're when you're in a services business, this was kind of a market research company and a services business.
31:49
And I loved software and I loved Silicon Valley.
31:52
And I used to come here and I had an apartment in Russian Hill for a while.
31:57
And I would come here and I'd just be enamored with the people in Silicon Valley.
32:00
And I'm like, I want to go work with these folks because the decision they make and that start button in Windows is going to be affecting billions of people and I want to be that person, you know.
32:10
Um, but I I never really was getting that same level of uh satisfaction from that.
32:16
But I stayed on there because of ego.
32:18
And this is the other lesson I'll give to founders.
32:20
I stayed on there because I had this ego that I will never work for someone else. This is my own company. I'm my own boss.
32:28
I don't want to work for someone else.
32:30
biggest mistake I made >> because ego drove my decision rather than learning driving my decision.
32:34
So finally I decided to go work at EMC and the guy who hired me at EMC is still my coach.
32:41
Um, and we were having dinner.
32:45
>> EMC, huge company, >> huge company, [laughter] 60,000 people, right?
32:49
Uh, I'm going from like 25 people to 60,000 people. He's hiring me as a CTO.
32:55
Um, and we're having dinner uh like this across the table.
32:58
I'm like, his name is Rick Devonoodi.
33:00
And I said, Rick, uh, you got to pay me more because, you know, I've had 17 years of experience.
33:07
He said, Ju, you don't have 17 years of experience.
33:09
You have one year of experience 17 times over.
33:13
>> Come work for me and in the first year I'll give you 17 years of experience.
33:17
>> I learned more from him in the first year than I did in the 17 years running my own business.
33:22
It was absolutely magical.
33:26
>> I hated working for him during that time.
33:28
>> But after we left and I went to Box, there's this person that I is my co-founder in life.
33:34
I think of like you know she is um she's my head of operations.
33:38
I don't take a job without her.
33:39
Her and I would always be like, what would Rick do at this point?
33:43
>> And we kept asking ourselves that.
33:43
And so that was a great mentor to have. Um then I went to Box. Box.
33:50
We took that business from 200 to 800 million during my time there.
33:54
I I ran all product by the end of it.
33:56
Then I was going to go run advertising for a fang company.
34:02
>> Not at all anything to do with Cisco. >> Yeah.
34:05
I had accepted the job, but the kind of offer they were going to give to Jesse, who was with me, was not the right offer for her.
34:13
And she was my co-founder in life.
34:16
Like, I was not going to go anywhere without her because she stuck with me the whole time.
34:18
Um, and so I'm like, "Okay, so I need to figure out what to do."
34:23
Um, and literally happen stance, Chuck calls me the next day >> and says, "Hey, you should probably think of coming here."
34:32
And I told him, I'm like, "Hey, look, I'm already already accepted this job."
34:35
And he said to me, he's like, "That company will do well with or without you, but if you come to Cisco, the trajectory will be shaped based on what you do."
34:44
And then it was like, "So, he gave us two offers within 9 days."
34:48
So, you knew that the company was willing to work at a very fast clock speed.
34:52
The question I asked him was, I'm like, "How much freedom are you going to give me to just be very products?"
34:57
Uh, and he said, "Yeah, we'd love you to be product obsessed."
35:00
And so we did that and before you know it like you know Cisco um um became the place where I think I got some of my in my career the largest amount of growth I've had is probably in the past six years.
35:15
What are some lessons that you share with you know someone who is like you at 19 or so perhaps even growing up in in in in India or someplace outside of of the valley where they're not where they're they're looking in from the outside.
35:30
I think the the first lesson I would say is um your upper limit is typically bound by your own ambition rather than um the um any other kind of factor.
35:44
It's not generally your ability.
35:47
I'm a very averely intelligent person.
35:50
Um I didn't have a fancy degree from a fancy school.
35:52
Uh but I was hungrier than everyone else.
35:55
And so I still um am hungrier than most people I work with, not because they're not hungry, but because I just feel like I don't want to let them down.
36:05
And so I'm just going to keep keep going at it.
36:06
And there's no one who can tell me that I'm not putting in the time.
36:10
And that I think is the first thing is put in the time, think really big and have very bold uh ambitions because if your imagination like imagination can tend to curtail us much more than we give it credit for you know if you have your goal that's this big chances you'll never get here but if you have your goal that's over here and if you get here that's pretty good you know and so that's a pretty important uh you know dimension to keep in mind.
36:35
The second one is business is a team sport.
36:40
business is a team sport. Take pride in longevity of relationships that you can build where you have actually made other people successful as a function of you and that I think will go a really long way and if you think that way from the time you're 19
36:57
boy the advantage that you have is tremendously high you know um and then the third area that I usually tell founders about is this notion of power of compounding like you just have to get 1 27% better today than yesterday and within a year you're 100x better. And if
37:14
And if you do that for 10 years, like that's pretty good.
37:19
And 10 years in the grand scheme of things, >> it feels like a long time when you're 19.
37:25
>> Like Sam Alman had this blog he had written once, the days are long, but the decades are short.
37:30
>> I read that every every year.
37:32
>> It's an amazing blog post.
37:33
>> It is one of the best blog posts he's written.
37:34
Yeah, like Jeff Bezos will say like the ability for someone for a founder to think in a 20-year window versus a 3-month window changes the quality of decisions you make materially.
37:50
And if you think about the the the really big entrepreneurs that we all respect, think about Jensen, think about Elon Musk, um none of them were accused of thinking in very short-term windows.
38:01
I mean, they grinded it out for a long time.
38:06
The only difference is grind it out when the business model actually makes sense, but don't do it like what I did and grind it out in a business which doesn't actually fit your ambitions.
38:17
Because my business, the one that I ran, was great for a lifestyle business.
38:21
>> It was terrible to go change the world.
38:24
I wanted to go change the world.
38:24
You know, that's the wrong business to be in to go change the world.
38:28
But if you want it to be a good lifestyle business and have it be a thing that provided wealth for your family, fantastic. Keep doing that. That's great.
38:36
And by the way, none of those are wrong answers.
38:38
of those are wrong answers. It just happens to be that the one that I my ambition did not align with the with the model of the business which is the other thing you have to keep in mind is does your ambition align with what you're actually doing right now where you are
38:52
going to get fulfilled when you look back when you're 80 and say you know what I feel very good that this is how I spent my time I think that's a question we should keep asking ourselves and for the younger folks I always tell them time's going to pass by so fast I never thought I'd 55, you know, I never thought I'd be called uncle. I never
39:11
I never thought I would have a kid >> and I never thought that she would say, "Dad, you're old, you know, [laughter] and bald."
39:18
Uh, and so like those things sometimes give you a lot of humility that you have to make sure that you don't take time for granted and spend the time in the places that actually really matter.
39:31
>> What advice would you have for entrepreneurs or for people who are coming into an organization like Cisco and trying to transform it the way that you do? I'll give you the story.
39:38
So when I I I hadn't gone back to India from the time I um left India 1991 I left. My dad died in 2004.
39:46
I'd gone to see him for 48 hours once before he died.
39:49
But then I hadn't gone back until 2017.
39:52
So for any kind of practical purpose from 1991 to 2017 I hadn't spent that much time in India.
39:59
I took my daughter there.
39:59
We went to the Taj Mahal and there's this tour guide. His name is Raj.
40:03
He's showing us the Taj Mahal.
40:06
guy seemed like a really good product guy.
40:08
He knew every single detail about his product, which was the experience he was selling about the Taj Mahal.
40:12
But then people would keep walking by and he would actually bust out in different languages, Mandarin and and German and French and Spanish.
40:18
And at some point I'm like, "Dude, how many languages do you speak?"
40:23
He gave me like some ridiculously large number like 12 or 14 languages or something like that.
40:29
And so I said, "That's that's crazy."
40:31
It's like, well, you know, I want to honor the people that come here because um they come here and I should not be presumptuous enough to think that they're going to speak my language, I should speak their language.
40:40
I mean, that's very noble. Clearly a smart dude.
40:45
Uh I'm thinking to myself, I'm like, "This guy is smarter than anyone.
40:47
I used to work at Box at the time.
40:49
Anyone that I work with, he's making probably $10 a day.
40:53
I'm sitting here in Silicon Valley." Uh and why is that?
40:55
Because I happen to have a platform and he doesn't, right?
40:59
I have a platform of education.
41:02
I have a platform of America.
41:04
I have a platform of tech.
41:04
I have a platform that just gives me the affordance of opportunity that he didn't get.
41:10
And so, no matter how smart he was, no matter how hard he's working, he's having a hard time breaking away from the pack.
41:18
If you happen to be afforded a platform, my only ask of people is don't squander it.
41:25
And as a founder um you know like we could all look at all the things as glass half empty and these are the things that we don't have but man we are all living in one of the most special times and if you're 19 or 20 or in the earlier part of your career in this moment in time during the movement in AI do you know how many people in their 50s how much money they would pay to get back to being 19 if they could?
41:55
This is a magical time to be alive in tech.
41:57
This is a great time to actually make an impact in the world.
42:00
And if you are spending your time associated with YC, which is one of the finest organizations I think, which is why I love working with you folks, you would be nuts not to just bust your tail and do everything you can.
42:16
Not for any other reason, not for making the money, but because the impact you will have on society at large will be so gratifying when you're older that it'll be something that's worth doing.
42:28
And if you happen to sell your company to a large company, don't get cynical going to a large company.
42:34
Go learn things that the large company teaches you because all those large companies at some point in time were startups.
42:40
And if you are successful, you will eventually be a large company.
42:46
And don't dislarge companies.
42:46
Actually learn how to make large companies operate with a level of, you know, kind of hutah.
42:52
And then you'll you'll actually be able to benefit from that as well.
42:57
and go in with an extreme level of curiosity and regardless of which way you go but but know that you're afforded the platform and very few people in the world look at the 8 billion people very few people are afforded a platform like we have [music] >> GI that's such an inspiring note to end on thank you so much for joining us >> thank you for having me it was