How to Build a Successful Company in an Era of Disruption

0:00If you look at VMware's roughly 20 year history, the first decade was us disrupting and growing and the second decade was others coming after us to disrupt. I think large companies are very good at running many experiments. What their bad at is doubling down on an experiment works. The story is the strategy. Don't delegate the storytelling to anyone in the company. You go do it yourself because you need one voice. SAS broke it, but AI breaks it even further. You have to use binary language. We're failing in this area. These are the three things we need to do to succeed. And if we don't succeed, there's an existential threat.

0:38What does it take to lead and transform a large company during a technological wave? In this episode, A16Z's Martín Casado sits down with two of the most experienced operators in enterprise infrastructure. Ragu Ragaram, CEO of VMware, and G2 Patel, president and chief product officer at Cisco. They reflect on leading -pubarquet destruction from VMWare's early dominance and visualization to the rise of cloud containers in our AI. You'll hear lessons on how large companies can avoid losing touch with the front lines, why real transformation requires founder -like urgency, and how to structure for speed even at scale.

1:13Plus, we get tactical. How to ring fence innovation, win internal adoption, and navigate the new infrastructure demands of the AI era, from GPUs to bandwidth to secure scalable networks. Whether you're a founder, operator, or builder, this is a masterclass in driving change from the inside out. Let's get into it. As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16z fund. Please note that A16z and its affiliates may also maintain investments in the company's discussed in this podcast.

1:50For more details, including a link to our investments, please see a16z .com forward slash disclosures.

2:02So maybe just to kick it off at a high level, let's talk about running a large operation both as a disruptor and through a market transition or transformation. So it's over the U -regus. So this is when VMware came out, I remember like it was the late 90s and I could run like Linux on my windows and and it was the most amazing magical moment. And then it really changed the industry. I remember when we were picking up a $30 billion on our company, everybody was running it. It was a monopoly. But it also had to weather a number of transitions going forward. And so maybe just a bit about like mindset as a disruptor and then how that you evolved your mindset as a leader and then maybe of the org as you have to go through transformation yourself.

2:44Yeah, I would say if you look up VMware roughly 20 year history, The first decade was us disrupting and growing and the second decade was others coming after us to disrupt us. That's roughly the VMware history. There are three or four what I call weapons of mass disruption in our industry, especially on the infrastructure side. One is if you introduce a new piece of software that introduces a new abstraction, right? or a new usage model. Everything starts to aggregate around that. You are able to successfully bring about a new class of users that were previously not consumers. This is the classic innovative dilemma description, or a new business model.

3:28In the case of VMware, we did the first and the last one, meaning we bought about a new abstraction for the data center, for compute to be more specific, which was a software -based virtual machine. And then we had a business model that associated with software as opposed to hardware. And that was the core of the disruption. And because of the benefits of software, we were able to fundamentally change the usage patterns in the data center. And once you start to change the usage patterns and the behaviors of the practitioners, then you get locked in and the disruption is almost impossible to remove.

4:05And I would say those weapons of marriage disruption were used against us not intentionally. No, not actually. I mean, the two big ones that we faced, the first one of course was cloud. Yeah. And the second one was containers and Kubernetes, right? In the case of cloud, all the same elements were present. Yeah, yeah. I mean, initially Amazon AWS did not change the abstraction of a virtual machine. but everything else, the business model changed. And the most important change that AWS Battlewall was it made infrastructure available to developers without IT. That was the massive unlock of a whole new class.

4:47And we had no idea how to work with developers, right? We did not know the secrets of how to do that, I think. So that is the point. And then Docker and Kubernetes and things like that changed the packaging and the abstraction. Now, the interesting thing is the industry, nobody made money on either Docker Kubernetes. I mean, there were some startups, right? But really, there was no big company that was creating out of that. But the real fundamental disruption we had to fight against was the cloud. And the cloud disruption was so hard for us to fight because it brought in a new class of users for infrastructure.

5:27Cisco's been a session iconic company for so long. I mean, it really rode the internet wave and then it rode the data center wave. It's been incredibly successful at riding multiple waves. It feels like it's hard to make a wave. Like you can't do that, but once they happen, you can ride them and capitalize on it and we're clearly seeing one right now with AI. So it seems to me like a great opportunity for Cisco, again, to figure out what to do. So I'd love to hear how you're thinking about, like the waves that Cisco did miss. I'd love to hear about how you're thinking about as a leader at Cisco, go, how you're thinking about navigating this?

5:57Yeah, the obvious one is we missed the cloud wave. Right. If you take a step back and go, every large company that's successful has to have gone through a startup phase because every large company was a successful startup at some point in time. But what ends up happening though is at some point when a company gets large, they lose touch with the front lines. Yeah. And you get into this mode where you get very good at the math of the business. Everyone knows what the gross margin of the company is. Yeah. But you've lost the soul of the business, which is, are you innovating at a very impatient velocity, and a very fast velocity so that you can continue to keep discontinuously leapfrogging?

6:36And when that happens, it's something where you have to hit the reset button. Yeah. I think about five, six years ago, that'll happen for us. Yeah. And we have to hit the reset button. And let me tell you, like, what needs to happen when you hit the reset button, which is, for sure. You have to make sure that you get people who have a founder's mentality. As execs in the company, or just throughout any... As execs? Just throughout, like most of the people that are on my leadership team, a lot of them are XCEOs of acquisitions. Oh, that's great. That we've had that are actually running these pieces.

7:04And you have to have a combination of CEOs and people that know how to operate within the machine that is Cisco. But the CEOs can put pressure by being impatient about saying, this doesn't make sense, I'm not moving fast enough. And then the people that know how to navigate Cisco are able to then guide them through and if you can make a good team out of those two people, magic starts to happen. And so where we've really started to see the tempo pick up is operating, like we internally have a mantra that says, operate like the world's largest startup, make sure that you're operating at speed but scale.

7:39You have to have a great zero to one practice. You have to have a great one to one hundred practice and now one hundred to a thousand practice. We're actually getting very good at saying, in nine months getting get a product from zero to market. And then the three to four years can get it to a billion. And if you can do that eight, nine, ten times, you've actually got a pretty healthy additive book of business that you didn't have before. And you can either create a category or you can make sure that you write a category that's been created. I think you can do both of those. It takes a little longer to create a category.

8:13I think large companies are very good at running many experiments. What they're bad at is doubling down on an experiment works. That's where the startups are good. they'll just focus on one problem. And then the other thing that we usually see where things fail in a large company is, if you read one to many tech crunch articles, you will build a zero to one product that does not keep in mind your route to market that you have available to you. And you have to make sure that you can actually ride the route to market that you have. So you can say, if I can build 10 products that actually leverage my route to market, then I'm gonna have an advantage of getting to a disproportionate amount of velocity to get to market.

8:49But if I don't leverage the route to market, and if I try to build a new route to market for every single one, then the sales team's gonna feel starved, and then you're not gonna go out and get to the level. Okay, so let's take into this very specific, I think many people don't appreciate how complex this exact thing is for a large company. So actually, you said something that I think is exactly right, which is like large companies do to touch with the front lines. I think Steve Sinovsky has this great model of this, which is for any disruption, you will have these incumbents, And the incumbents, let's say 80 % of the dollars comes from 20 % of the customers.

9:23And those customers are large enterprise and they've got like very sophisticated needs and it just drives so much of the business. And so they've got these depolationships with a few customers and then the new disruption has. And they're with those customers, they're not with the front lines, which tends to be different. And so now you've got to retool, go to market, product, everything for this new base, even though 80 % comes. And so I mean, I know Regu, you had a deal with us. like how did you think about how you evolve the company, not technology disruption, but even just catering to a new base.

9:57Yeah, I mean, what do you say to the marketing side, the sales side? Yeah, what you said is spot on, because when you're talking only to your best customers, by definition, that's not where the disruption is coming from. Yeah, right. And like any other large company, you get really good at talking to your best customers, and that's where all the incentives are as well. which is why companies deal with it in one of two ways. One is they fence off a different team to go a process thing completely different, allow to break every rule in the book. Are they going by? So we have at various times done both.

10:35There are certain classes of innovation where you can get by what I would say is close adjacencies, where if you're building a product that's closely adjacent to your original product, You can take it from zero to one through the existing Salesforce, right? Because it's going exactly at the same user. But if you have, for example, going at a different user, like, we were doing with the Nisira and the networking, then you need to fence it off. And that's... You know, so interesting about VMware. It's one of the few companies that actually did both pretty successfully. Like, VSAN was storied. Exactly.

11:06You pulled it off, I don't know how. And then Nisira was inorganic and you pulled it off, I didn't know how. And so like any lessons of like inorganic organic like the complexities Yeah, I mean, I think you have to be very careful where organic is gonna work obviously Everything starts from the product right for so many of us in the business. Yeah, sort of a truth and In the case of V sound to your example, it was a close adjacency Right to the computer. It's a different buyer, right? You tell me you're the expert. Yeah. In fact, we had two iterations on V -SAM. Initially, we said, hey, let's go after the storage buyer that did not work as well.

11:50When we said, look, we're going to go expand the compute buyer's perv. Then it started working. So the go -to -market start to match together. The other thing about going into existing categories is you've got to be 10x better. Yeah, 10x better. So in the case of storage, we were 10x better than having an external storage, at least for VM where you taste, right? And so that's why that worked. And by the way, that 10x better is a very counterintuitive thing for large companies to think about because they always think about catching up and no one wins by playing catch -up. Yeah. Right? And so the asymmetry of coming out from a different angle and being at least in order of magnitude better is is something that you have to continue to keep pushing out and be the biggest skeptic.

12:35Because most people will tell you that they're 10x better and they're actually 15 % better and 15 % doesn't create an extraction of an incumbent. Just to finish that thought in the case of networking as we all know, it was a different way of operating a network. So that was the value proposition. I don't necessarily tell Xperia, it was something that could not be done on a physical network at all. What do you mean, it can program the network? What do you mean, it can have virtual firewalls? Yeah, yeah, etc. That's scale as well. I think it really you understand the nature of the disruption that you're bringing to the market and then tailor the rest of the go to market around it.

13:08And so that's why we chose different approaches in both cases. The other thing that I would say to what Rago said is you have to define very clear insertion points because often you meet in the market or in the company in the market. Right. So if you have an incumbent that's ready in the market that's entrenched pretty well, a large company will typically try to say, okay, I'm going to go out and build something for the green field with an entire platform, but the reality is the market's not green field, it's brown field. So you have to identify an insertion point where your competitor might be there and then over time you have to make sure that you extract the competitor, which is not something that's intuitive to people.

13:42So like, oh, I'm going to compete with them. It's like, no, you actually have to coexist first before you can displace. And so that requires a very open ecosystem based mentality, which large companies sometimes can tend not to have. So what I think I've seen fail consistently, again, like you guys are way more expert with an IAM, but is this kind of notion of, if a engineer spends one day a week experimenting, then maybe they'll come up with a great idea that changes the company. It just feels like that tends to not have enough momentum behind it to do something big. You know, I've also seen fail, which is like, you know, you take one large org, and you say you've got to do two things, you've got to do the new thing and the old thing.

14:21It's just too hard. And so what seems best is kind of ring fencing, Yeah, like a bit. And I think that in Cisco in particular, has a lot of experience with this type of stuff. And so how do you think, let's say you're like in the AI wave, you're doing something destructive, let's say you've decided not to do it in organic, you're doing it organic, how do you think about structuring it? So the way that we structure it is, you'll think of a two -piece, a team initially that you start with. Really small. And that team has agency, that team has air cover from the very top, all the way up to the top of the food chain.

14:50And what you have to do, because there's enough antibodies that'll be there, that'll argue why that's not a good idea and it should be part of the core. That you have to make sure that that team is protected from that and is just focused on go drive it. Now, they might be good at getting a version one product out to the market, but they are not gonna be good at getting the entirety of the sales force of 17 ,000 sellers in Cisco's case to go on and get it. So what ends up happening is you have to be very prescriptive of an ideal customer profile that you wanna make sure that you start this with.

15:21And this is where I feel like not losing touch with the front lines, this is one of the best ways to not lose touch with the front lines. You start with a zero to one project, start from the bottom because you never start a zero to one project from the largest financial services institution. Exactly, right? You start from the bottom. And when you do start from the bottom, you give that team enough freedom, enough agency. And then over time, construct enough incentives in the different teams for making that thing successful. Yeah. And when that happens, you start to see a snowball effect start to occur.

15:54But it takes a while. One of the things we learned that failed the first couple of times we did this was we'd have the version one of the product out and then the field would just reject it. It's not ready. It's not a complete product. It's no. It's actually ready for this segment of the market. But you don't want to sell what you do an overlay to help. We would have an overlay sales team. But the core would keep it out of the account. Is that right? What would keep it out of the account? Because it's not going to go sell the Bank of America. I'm like, yes, as actually the wrong account to go sell it.

16:23And that's a version one product. Because it's not ready for all the capabilities that are needed there. I don't need to have a data center in China for my first billion. And so just being very clear on where you're going to actually make sure that you, so what we do is, now when you have an incubation team, they have two jobs. Build a great product and define an ideal customer profile. Yeah. And really make sure that in that ideal customer profile, you have initial adoption and a repeatability of a go -to -market opportunity creation motion after you've got the product market fit very, very clearly defined.

16:57And once you've got that ICP nailed and you've saturated that market where you're starting to saturate that market, expand the ICP and then expand it again, expand it again. I think that's a very counterintuitive motion for large companies because it's very hard to go to a 17 ,000 sellers and say to them, you, one thousand of the sellers, I'm only going to go train you on it. Yeah. So it gets to be a little hard to do. Yeah. Yeah. I think the term ideal customer profile, sometimes especially in larger companies, missly it's people are thinking about all my customers, JP Morgan, my customer home deal.

17:31That's the ideal. The ideal practitioner profile. Yeah. Yeah. The ideal practitioner profile. Yeah. So you're a narrow casted down to. Right. Who's the person that's going to wake up every day using that thing that you're going to build? And then revolve all of your practices around that from go to market, of course, into product. But I will tell you this, that once you start building products that start getting momentum in a large company, the company starts regaining a spring in their step. And I think Cisco is going through this right now, right? Like we were like, it's got a small job at stake.

18:01It's got a small job at stake. It's talking all the time. Hi, congratulations. Well, those things you never know how these things are up and down. But in general, we're pretty excited about the reception in the market. But the most gratifying thing is when you go into the internal audiences, and you can feel the spring and the step on the employees. And why is that? Because we're starting to win again. Yeah. And most people want to come into the office wanting to win. It's not like people like I'm going to book it in. But what ends up happening is when you have 95 ,000 employees, you can tend to dissipate a message very quickly.

18:34Yeah, so one of the best pieces of advice I was given one of my board members when I took over this job as Had a product he pulled me aside. He said I'm gonna give you one piece of advice Yeah, and he was the X CEO of Northrop Grumman. He said what's that? He's like don't delegate the storytelling to anyone in the company You go do it yourself because you need one voice That's great and it doesn't mean that I'm the best presenter in the world but If one person doesn't tell the end -to -end story who actually owns it You start to fracture the story, and once you fracture the story, man, you start losing control of it.

19:07And so the story is so important. The best in the world at this is Apple. Yeah, of course. Yeah, that's good. And you just want to be like 10 % as good as Apple. And I think we're really getting obsessed about that. And right now it's starting to work because the clarity with which you can galvanize 95 ,000 people, when that starts to happen, you can start to feel a tempo in the business that's just very different. Yeah, in fact, I'll go on step further and say the story is the strategy. That is the strategy. Yeah, right because Human beings suddenly 95 ,000 people together. Yeah, I'm not gonna understand five bullets, right?

19:41It is a story Yeah, so something that's unique to this wave to say I wave that regu you've certainly seen and maybe saw a little bit of box Was it's really this kind of consumer? Pro -sumer Which the internet was right which certainly that scape was to begin with I mean it was like actually VM was actually not I just think about that right now, but like... You paid $199 .99 and then $29 .99 and downloaded the product. I did, I did it as a college student. And a lot of the companies being impacted are not consumer companies. I mean, they're like deep enterprise companies. And so how do you think about navigating a wave where the buyer's not just like ICP for...

20:20It's the actual consumers. Like you sell to the people who sell to them? Yeah, I mean, I think firstly, Because danger, I would say for enterprises, even for startups, is to look at this AI wave in the lens of previous waves. Yes, for sure, maybe there are some applicable lessons. This thing is so big and so different that you got to look at it from first principles. It is particularly dangerous because we have, like it didn't work in the past, but we created businesses around it. So like we have these kind of old like AI chatbot things that are actually quite different But I think we're used to thinking about the old AI not the US.

20:57It's almost like it's got this it rhymes with Previous stuff and so it makes us also think it almost like whatever open AI did broke every single rule of what was done previously And they've actually wildly succeeded. So I mean, I think this is the new skill to learn for companies to learn as well Yeah, you've got to especially Infrastructure companies our application companies You got almost ignored IT That is the selling to the seller who's selling to the buyer internally. That chain is forever broken. I mean, SaaS broke it, but AI breaks it even further. And so what that means is that your product manager is in everybody else, it's trying to figure out what the product is, has to really think about the end user from a direct range point of view.

21:42Right, but there's different buyers like you could sell to IT or you could sell to like, you know, whatever. Security or marketing, but like, this is literally individuals with credit cards that are not developed even developers are a bit of a central buyer that we understand how to sell to but this is like rando you know employee asking chat gbt to write an email. It's very different right it seems like Cisco's been able to navigate these because. The network is such a point of leverage if every user uses something the network Tam grows and so like one option for Cisco is like whatever you have a new data center will sell you new switch.

22:17and it doesn't matter that a lot of the market is, like you can argue like the entire web is something that Cisco did a phenomenal job with the data center switching and like it didn't go sell to consumers, I was a consumer phenomenon. And so is that kind of the way that, yeah, I think the way that we think of ourselves as we are the critical infrastructure for the AI era. Okay, so still in for you. And then you have to look back and say, where is AI constrained? Yeah, right now. It's constrained in power, it's constrained on compute, it's constrained on the network. Yeah, because if the packet is delayed getting to the GPU, the GPU is idle.

22:49GPU is idle. That's like burning money, you know, especially in the training runs. So you have to make sure that you actually have a very, very efficient packet flow going over there. So you'll low latency, high performance, high energy efficiency, infrastructure on the networking side. Super important on training. As you have more agents in the work, your inference demand is not going to be spiky. It's actually going to be sustained because in agents going to today probably an agent works Autonomously for 20 minutes. Yeah In the next six months it will work autonomously for maybe two hours or Ten hours and then it'll work for two months and then two quarters and two years the longer you work you have a sustained persistent demand for inferencing and Your capacity of network appetite is going to go up quite exponentially because if you have a thousand employees and you add 10 ,000 agents that's like having 11 ,000 employees.