If 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 with running many experiments.
What they're 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.
What does it take to lead and transform a large company during a technological wave?
In this episode, A16Z's Martin Casado sits down with two of the most experienced operators in enterprise infrastructure Raghu Raghuram, CEO of VMware, and Jeetu Patel, President and Chief Product Officer at Cisco.
They reflect on leading pre-market destructions, from VMware's early dominance in visualization to the rise of cloud containers and now 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.
Plus 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 companies discussed in this podcast.
For more details, including a link to our investments, please see a16zcom forward slash disclosures.
So 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 I'll start with you, Raghu.
So when VMware came out, I remember it was the late 90s and I could run Linux on my windows and it was the most amazing, magical moment.
And then it really changed the industry.
I remember when it became a $30 billion 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.
Yeah, I would say.
If 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 us.
That's roughly the VMware history.
I mean 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, it's a piece of software that introduces a new abstraction, right?
Yeah, yeah. or a new usage model.
And 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 innovator's dilemma description, or a new business model.
So, in the case of VMware, we did the first and the last one, meaning we brought 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 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.
And I would say those weapons of mass disruption were used against us, not intentionally.
I mean, the two big ones that we faced, the first one, of course, was cloud.
And the second one was containers and Kubernetes, right?
In the case of cloud, all the same elements are 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 brought about was it made infrastructure available to developers without IT.
That was the massive unlock, right, of a whole new class.
And 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 or Kubernetes.
I mean, there were some startups, right?
But really, there was no big company that was created 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.
Cisco's been such an 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 the waves that Cisco did miss.
I'd love to hear about how you're thinking about as a leader, Francisco.
How are you thinking about navigating this?
Yeah, 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 got very good at the math of the business.
Everyone knows what the gross margin of the company is.
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?
And when that happens, it's something where you have to hit the reset button.
And I think about five, six years ago, that had happened for us.
And we had to hit the reset button.
And let me tell you what needs to happen when you hit the reset button, which is you have to make sure that you get people who have a founder's mentality.
As execs in the company or just throughout?
Throughout.
And 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.
You have to have a great zero to one practice.
You have to have a great one to 100 practice, and now 100 to 1,000 practice.
We're actually getting very good at saying in nine months can you get a product from zero to market.
And then in the three to four years, can you get it to a billion?
And if you can do that eight nine, 10 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.
I think large companies are very good with 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 too many TechCrunch 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 going to have an advantage of getting to a disproportionate amount of velocity to get to market.
But 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 is going to feel starved.
And then you're not going to go out and get to the level.
Okay, so let's think into this very specifically.
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 lose touch with the front lines.
I think Steve Sanofsky 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 and those customers are large enterprise and they've got very sophisticated needs and it just drives so much of the business.
And so you've got these deep relationships with a few customers and then a 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 Raghu, you had to deal with this.
Like how did you think about how you evolved the company?
Not a technology disruption, but like even just catering to, like a new base.
Yeah.
On the go-to-market side, 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.
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, right?
One is they fence off a different team to go approach this thing completely different allowed to break every rule in the book, right.
Or they go and buy, right?
So we have at various times done both, right?
There 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're, for example, going at a different user, like we were doing with Nasira and networking, then you need to fence it off, and that's... You know what's so interesting about VMware?
It's one of the few companies that actually did both pretty successfully.
Like, vSAN was storage.
Exactly.
You pulled it off.
I don't know how.
And then Nicira 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 going to work.
Obviously, everything starts from the product, right, for so many of us in the business.
It's sort of a truth.
And in the case of vSAN, to your example, it was a close adjacency, right, to the compute.
But it's a different buyer, right?
You tell me.
I mean, you're the expert.
Yeah.
In fact, we had two iterations on vSAN, right?
Initially, we said, hey, let's go after the storage buyer.
That did not work as well.
When we said, look, we're going to go expand the compute buyers per view.
I see.
Right?
Then it started working.
So the go-to markets start to match together, right?
And the other thing about going into existing categories is you've got to be 10x better.
You have to be 10x better.
So in the case of storage, we were 10x better than having an external storage, at least for VMware use cases.
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.
And so the asymmetry of coming at it from a different angle and being at least an order of magnitude better is something that you have to continue to keep pushing at and be the biggest skeptic.
Because most people will tell you that they're 10x better when 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, right?
Yeah, yeah, totally.
So that was the value proposition.
Not necessarily 10x better.
It was something that could not be done on a physical network at all.
What do you mean you can program the network?
What do you mean you can have virtual firewalls, et cetera, et cetera, that scale it well?
I think really you have to 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.
And so that's why we chose different approaches in both cases.
The other thing that I would say to what Raghu said is you have to define very clear insertion points.
Because oftentimes- You mean in the market or in the company?
In the market.
Right?
So if you have an incumbent that's already in the market, that's entrenched pretty well, A large company will typically try to say OK, I'm going to go out and build something for the greenfield with an entire platform.
But the reality is the market's not greenfield.
It's brownfield.
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.
It's 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 one thing I've seen fail consistently again like you guys are way more expert than I am, 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.
It's just too hard.
And so what seems best is kind of ring fencing.
Yep.
Ring fencing works best.
And I think that...
And 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 disruptive.
Let's say you've decided not to do inorganic, 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 pizza 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.
And 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 going to be good at getting the entirety of the sales force of 17000 sellers in Cisco's case, to go out and get it.
So what ends up happening is you have to be very prescriptive of an ideal customer profile that you want to make sure that you start this with.
And 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.
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.
And when that happens, you start to see a snowball effect start to occur.
But 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, saying, it's not ready.
It's not a complete product.
No, it's actually ready for this segment of the market.
But you don't want to sell.
Would you do an overlay to help?
We would have an overlay sales team.
But the core would keep it out of the account?
The core would keep it out of the account, because it's not going to go sell to Bank of America.
I'm like yes, as actually the wrong account to go sell it in as a version one product because it's not ready for all of 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.
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.
And once you've got that ICP nailed and you've saturated that market or you're starting to saturate the market expand the ICP and then expand it again, and expand it again.
I think that's a very counterintuitive motion for large companies, because it's very hard to go to 17000 sellers and say to them you, 1000 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.
I think the term ideal customer profile sometimes, especially in larger companies, misleads people into thinking about oh, my customer is JP.
Morgan, my customer is Home Depot, et cetera.
That's the ideal use case profile.
The ideal practitioner profile.
Exactly.
The ideal practitioner profile.
So you've got to narrow cast it down to.
Right, 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?
Yeah, Cisco's got its mojo back.
It's got its mojo back.
Stock at all times high.
Congratulations.
Well, those things, you never know how these things go up and down.
But in general, we're pretty excited about the reception in the market.
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.
And most people want to come into the office wanting to win.
It's not like people are like, I'm going to book it in.
But what ends up happening is, When you have 95000 employees, you can tend to dissipate a message very quickly.
So one of the best pieces of advice I was given one of my board members when I took over this job as head of product, he pulled me aside.
He said, I'm going to give you one piece of advice.
And he was the ex-CEO of Northrop Grumman.
I 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.
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.
And so the story is so important.
The best in the world at this is Apple.
Yeah, of course.
Right?
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 95000 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 one step further and say the story is the strategy.
That is the strategy, yeah.
Right?
Because human beings, suddenly 95000 people together, are not going to understand five bullets right.
It is a story.
Yeah.
So something that's unique to this wave, this AI wave that Raghu, you've certainly seen, and maybe you saw a little bit of Box was it's really this kind of consumer-prosumer movement.
Which the internet was, right?
Which certainly Netscape was to begin with.
I mean, it was like, actually VMware was.
Just thinking about that right now.
You paid $199 and then $249 and downloaded the product.
I know, so I did.
I did it as a college student, right?
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...
It's the actual consumer.
Is it 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.
And it's 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 UAS.
It's almost like it's got this.
It rhymes with previous stuff, and so it makes us also think It's almost like whatever OpenAI did broke every single rule of what was done previously, and they've actually wildly succeeded.
So, I mean, I think this is a new skill for companies to learn as well.
You've got to, especially infrastructure companies or application companies.
You got to almost ignore IT right.
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, right?
And so what that means is that your product managers and everybody else that's trying to figure out what the product is has to really think about the end user from a direct reach point of view.
Right.
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 ChatGPT 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 one option for Cisco is whatever, you have a new data center, we'll sell you a new switch.
And it doesn't matter that a lot of the market is...
Like you could 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.
That was a consumer phenomenon.
And so is that kind of the way that— Yeah, I think the way that we think of ourselves is we are the critical infrastructure for the AI era.
Okay, so still in for it.
And then you have to look back and say, where is AI constrained? right now.
It's constrained in power.
It's constrained on compute.
It's constrained on the network.
Because if the packet is delayed getting to the GPU, the GPU is idle.
GPU is idle, that's like burning money, 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 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 today, probably an agent works autonomously for 20 minutes.
In the next six months, it'll work autonomously for maybe two hours or 10 hours.
And then it'll work for two months, and then two quarters, and then 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 1,000 employees and you add 10,000 agents, that's like having 11,000 employees.
That means you have to have your network bandwidth be equivalent to what can serve 11,000 employees.
And so you're going to just need to make sure that you have more infrastructure.
And so we are a direct benefactor of that.
And then the second area is keep it safe and secure.
Securing AI is going to be pretty important.
We actually have a core foundation on the safety side.
So those two become core foundational elements of the infrastructure.
The third one is data, and we've got Splunk.
I think you have to find those kind of foundational elements which say that, no matter what happens on the business model people are going to need as an infrastructure company, the beauty is your business model is not that complicated.
As there's a spike in demand and applications.
You're just going to need more infrastructure and you have to continue to sell the infrastructure to the people building it.
I mean, I think infrastructure traditionally has followed usage models, right?
So back to your consumer thing.
You really have to understand the usage pattern, whether it's human beings typing in chatbots.
I would say with Cisco, it's also just good to be king, right?
If you're in the network, whatever compute grows, the network grows.
Yeah, but it's not always during the COVID crisis.
I think it's great to have share, but if you stop innovating, you can actually start to see customers get frustrated.
And for about a six, seven-year period, we had just stopped innovating.
And I just don't think it was that productive for us.
And then getting back out to innovation right now.
For example, past 18 months we've probably done more innovation than the previous 10 years combined.
Our biggest challenge right now is sitting down with the customer and giving them the story that says here's where the innovation has happened.
When you sit down with them for 90 minutes, they love it.
Doing that for a million customers is really hard.
And so at scale, changing perception is hard.
And that's one of those things that it took us about a year and a half to do that.
One thing that's interesting about this AO, actually, Aaron Levy was sitting in that seat.
One of my best friends.
Yeah, he brought this up, which I thought was really good, which is during this wave.
You have a lot of the original founders still running the companies, right?
You've got Zuckerberg, and you've got Jensen, and you've got Olly Goodsey.
Like, there's many.
And so, like a founder we've seen many times with like the Reed Hastings effect, can like actually navigate a transformation because they know the team, they are product-focused.
They have the moral authority.
They have the moral authority.
They have support from the board.
I mean, they can do that.
I think, I mean, when you joined VMware, Diane was still running it, right?
Yeah.
Right?
And you were there.
So you've actually seen the founders do it.
But listen, I mean, you were CEO as a non-founder.
You guys have worked with non-founders.
Do you think it's a different job?
Yeah, there are a couple of things where a founder has a unique license.
Yeah.
Right?
Yeah.
But then there's the rest of it, which is how do you make the change happen?
Yeah.
Right?
Right.
Like, how did you think about it?
I mean, you were the CEO.
I mean, you've been in the company so long, maybe you were virtually a founder.
Actually, the first element of it is what is the technical and product credibility and license that your team is giving you right?
In my case.
Fortunately, I'd been there for a long time and driven a lot of the waves that VMware had went through.
So I had some of that.
But the other important thing that you need is early conviction on what to bet on, right?
Because founders get much more time.
The market gives them more time, their board gives them more time, their employees give them more time.
Non-founders for various reasons, and I don't know.
If you agree, you don't get the same amount of time.
So what you got to do is you got to develop very early conviction about what the bet is that is going to drive this transformation right.
And then what is the narrative behind it to your point earlier?
And then how do you drive that into every aspect?
The other part of it that you got to do, which founders naturally do, is I mean the overused phrase of the year probably is founder mode right?
You really got to own that.
Change every little aspect of it, right from every check-in to how, the way it gets to the market, right.
So those things are all common.
But you're absolutely right.
Founders have a better ability to do that because of the fact that they are founders and they're natural entrepreneurs.
I have a slightly different...
I agree with everything Raghu said, but I also feel like I've never been a founder.
I have never felt like I'm not a founder of any company I worked for.
I would say you sure feel like a founder.
I feel like I founded Cisco and this is my company and I'm going to make sure that we make it successful.
And I think that owner's mentality is actually what's more important in my mind than a founder.
And the way that I think about the owner's mentality is you've got to make sure that you're extremely impatient.
You always remind yourself you're running out of time.
You always market in rather than company out.
And you don't tolerate any level of mediocrity and you don't try to win a popularity contest.
Because you'll never win it.
And especially the larger the company gets.
It actually is a very dangerous trap to fall into, because a lot of people will tell you what you want to hear.
And so you almost have to work hard to surround yourself with people that are almost excessive critics, where they might actually have an extreme version of.
They look at everything that's wrong with you and keep nitpicking on it.
And you need to have some of those people around you that can tell you that, so that you are constantly getting better.
But I feel like I've never been a founder and I always feel like I'm always an owner of the company I'm in.
The other thing is, I think finding the truth is especially hard in a large company.
It's so hard, yeah.
And that's another place where I think founders can get to the bottom of things more easily.
And by the way, on that one, that's a really important point.
In large companies especially, we start to create versions of the truth and then start believing those versions of the truth.
And that happens so frequently and seeking the truth and going down to the facts of what is, in fact, not working.
What ends up happening is and especially, you know, at a company like Cisco.
One of the things that Cisco is really amazing at is it's a very compassionate culture.
Yeah.
One of the things that Cisco is not that great at, because of the fact that it's a very compassionate culture, is we might not actually have very direct conversations sometimes.
And so you have to make sure that when something is not good, You sit people down and say we're failing.
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.
And I need and expect you to do this to make sure that that happens.
And I feel like it's very unnatural for people when someone comes in and then starts doing that initially.
And you have to just break every mode of hierarchy.
So I'll give you an example.
When I first joined, I said, let's start doing design reviews with the WebEx team.
And they're like, what are you talking about?
This is a member of the executive leadership team.
Geetha, you're too senior.
We don't need to do design reviews.
Then they started doing design reviews.
And the senior vice presidents would come in and do design reviews with me.
I'm like no, I need to make sure that the designer And the PM and the engineer are actually doing the design reviews.
And so then they started working with and doing eight meetings for prep before they came to me, because every layer would be the prep.
That is a very common disease.
Yeah.
And so then one of the guys who was there said, stop this madness.
His name is Ty.
He's a great engineer.
And he said, we're going to learn when G2 learns.
And this is a safe space.
And all of us are editors.
We keep our titles out.
Let's just start to make sure that we edit the code that's going to ship.
And the moment that happened, there was an unlock in the team.
And everyone started thinking differently.
Because then it became a safe space.
And we were just critiquing each other's ideas.
They were telling me I was wrong.
I was telling them they were wrong.
We were just debating back and forth.
And the titles were left outside the room.
And that created this magical, purely the best idea wins.
And I think in a large company, best idea wins happens very seldom.
So you have to make sure you fight that urge to say, rank wins.
It's like the best idea has to win.
It just occurred to me I don't know why it didn't occur to me before that both of you are product people.
Yeah, of course.
I mean nothing against people with other specialities, and they're all phenomenally difficult to acquire expertise in many of these corporate domains.
But you cannot navigate this AI transformation, or for the matter of any other transformation, if it doesn't start from the product.
Yeah, I think so.
That's very interesting.
Do you manage from products on out?
Absolutely.
I'm very public about this.
I usually think the product is the soul of the company.
And what we do is when we start thinking about the products.
Cisco used to be a very sales-led company.
I mean, John Chambers is the constant sales guy.
And what I give Chuck a lot of credit for is he said, we have to become a product-centric company.
Really?
And then Chuck's a sales guy, right?
And he said Gito, we have to make Cisco a product-led company and you have to start from the product.
And every single time a product guy started bitching about why the salesperson wasn't selling well, he said well, you know, if you build a good enough product that has market pull, you're never going to complain about enablement.
If you build a product that cures cancer, one of my mentors used to tell me this.
If you build a product that cures cancer, you sell it in the Himalayas from 230 to 330 pm on Tuesday afternoon every third Tuesday of the month.
There will be a line out the door, right.
Because you're curing cancer.
So it's like, what you have to do is you have to build a great product and make sure that there's enough pull.
And I feel like we are probably 70 of the way there now at Cisco where – everyone originates by thinking about what's the product and how are we going to add value?
I feel like companies go through three stages.
They go through the product stage, the sales stage, and the operations.
And there's actually leaders for each one of these stages.
Like, the same person can do all of them, but they have very different requirements.
The danger zone seems to be that you've got the operations CEO during a transformation because it's such a product and they've got to go ahead and reset.
And so I do think that having founders tend to always be product because, like you, have to go to that stage.
But I do think that like product leadership.
If you look across any large Silicon Valley company or, for the matter, outside Silicon Valley, where the leaders or the companies have successfully navigated the transition.
I don't think you can think of an example.
I'm guessing 90% of the time.
There's a few people maybe touched by divinity like John Chambers, but there's very few of them.
The one thing that I've never understood in large companies is the one thing that definitively does not work as a formula is saying I'm in a tech space and I'm going to cash call this business and not innovate, and I think I'm going to do great.
Like, that never plays out in the long term.
But it is so common.
But it's so common.
And I've never understood that.
It becomes a self-fulfilling prophecy.
Yeah, 100%.
It does.
It's like, just keep innovating.
And it's a very simple formula.
Just keep outdoing yourself and doing better every day.
And we have this line internally we use.
Just get 1.27% better every day from what you were yesterday.
And in a year, you'll be 100x better.
There's a power of compounding.
I would love, Raghu, your thoughts on the AI stuff.
I know it's pretty early, and I'd love to hear your thoughts.
Do you think this changes infrastructure?
Do you think it's largely independent of infrastructure?
Do you think this increases TAM?
How do you think about this on a macro scale?
I think it changes infrastructure in an enormous way.
I mean, infrastructure always is a follower of the change.
Of the workload, yeah, of course.
I mean, go back to Netscape, right?
When the browser came out, we were running on, what, 4.8 kilobaud modems or whatever it was, right?
And then look at the internet infrastructure today, right?
Yeah, yeah.
I remember the transition from the wiring closet to the data center, remember?
Yeah, exactly.
These mega data centers actually drove switching.
Yeah, I mean, the neural net was created on a gaming chip, right?
Yeah, that's right.
And today now you've got AI factories and, like you said earlier in the talk, the bottlenecks are progressively moving every way.
So I think fundamentally, every layer changes.
It's not just compute.
We've got high bandwidth memory changes.
Obviously, the networking changes.
The storage access patterns are changing.
So every part of what we think of conventional infrastructure is changing, but the layer below that is changing as well.
I mean, this whole business at the end of the day is power to tokens.
And so everything that's in between the power to tokens, starting from power generation to the token output, is dramatically changing.
Do you buy that this is 10x step up in market size?
It's 10x step up in market size because the applications are 10x step up in market potential.
Because they're replacing labor, they're replacing, I mean, they're GDP enhancing.
Whereas previous generations, while there were tremendous advances in productivity, they were not to this scale.
I think actually infra, from a market size as well as a scale perspective, is more like 100 to 1000x, not 10x in infrastructure scale.
You will find probably two to three orders of magnitude.
And I think one of the things that we are extremely obsessed about is It's really important, when you do something like this, that the vertical integration is super important.
So we build our own silicon ASICs.
We have our own network infrastructure.
We have our own security platform.
We've got our own kind of models that we're building in certain cases, because I think the models are going to get smaller and more bespoke.
We have our own data platform.
We have our own observability stack.
And I think that working well together.
But being completely open to the ecosystem is super important in AI.
And right now I feel like Those structural changes on how companies think about an open ecosystem will be challenged quite a bit, because you have to partner with your largest competitors and be unapologetic about it and make sure that you don't let the internal forces stop you from doing that.
One of the best things we've done in the past five years is we've completely opened up to our competitors.
And for example, Microsoft Teams was a huge competitor for us.
And we partnered with them and have them run natively on our devices.
Hundreds of millions of revenue has accreted because of that for us.
That's awesome.
And it wouldn't have happened if we had not opened it up.
And one lesson I've learned on that is when someone owns more than 20 share in the market and you don't integrate with them, you're just excluding yourself from the market.
You're actually not doing anything to displace that vendor.
And I think in AI, that's going to get even more and more prominent.
That's great advice.
That's why I asked Raghu whether I could insert into the hypervisor, and he ended up buying the company.
That was the only way that was possible.
Because he said no.
By the way, I mean on your point about the vertical integration.
That's an interesting industry debate in my opinion.
Because if you look at the last two industry waves the PC and the cloud it was all about horizontal disaggregation.
Maybe.
Maybe.
Listen, it's a timeline question.
So they horizontally started.
Google makes chips now, man.
So then they, over time... That's where I was going.
Okay, okay, sorry.
So now, in this wave, it's soup to nuts.
And so we'll see if this is the right model.
Yeah, yeah, for sure.
And we are starting on cybersecurity.
We are starting to etch security into the silicon.
Yeah, yeah, cool.
And it'll just have a very different performance kind of output than what you'd have otherwise.
Totally.
I do think that there are signs of horizontalization also, by the way, in this AI wave.
So, for example, the open source AI models are actually pretty successful.
And there are separate inference platforms.
So I don't think the vertical versus horizontal has played out yet.
It's just so fast and so furious.
But that's why you have to make sure that if you do the vertical, you have to be very horizontally friendly.
No, that was a great, I mean, actually, I love that.
That was a great point.
So, okay, so listen, we're coming to the end of the time.
Listen, we've got two of the most storied execs, elite execs in infrastructure.
A lot of the people listening to this are in companies navigating this transition.
Maybe they're not as big as VMware or Cisco, but like maybe just a few words of how do you think about navigating these and the opportunity as a bit of guidance.
I'll give the founders, which I think is kind of the heart and soul of America and the world.
Actually is the startup ecosystem.
And I think it's really important that we keep it vibrant.
I would say that's a six-part formula that I use on what's really important, in descending order, on how you should think about building a great company.
Number one and the most important thing is timing.
Get the timing right.
Right now, don't fight the megatrend.
Make sure that everything that you do actually has AI as a tailwind.
Otherwise, you're not going to win.
Timing is number one.
Number two.
Make sure you go after a very large market that you can attack a step at a time.
If you try to go out and swallow the entire market, it's going to be really hard.
So you have to make sure you go after a large TAM, but address it a step at a time.
And ideally, create the TAM.
Don't go after an existing TAM.
It's even better.
Number three is...
And oftentimes people will say, well, does team trump market?
I actually think market always trumps team.
And this is not my idea.
This is Mark Andresen.
I agree.
I think that's valid consensus, by the way.
It's consensus right now.
Market always trumps team.
Market always wins.
Number four is product.
I think you have to build a great product.
In my mind, there's three parts to a product.
Build a product that people love, that they talk to their friends and family about, because that's the only way you get to hundreds of millions of users.
Number two, get adoption and really understand retention and why it happens.
And number three, get to commercial relevance, otherwise it's a science experiment.
So timing, market, team, product.
Number five is brand.
You've got to build a brand that's actually identifiable, and don't try to have too much noise in the system.
Just one message over and over again.
And number six is you've got to have scale distribution, otherwise it doesn't work.
I mean, we don't have time to explore it, but the last two are very, very different today than how you do it.
By the way, this is again a challenge for large companies, right?
In fact, this very medium that we are on turns out to be one of the biggest brand building mediums ever right.
And it can't be too scripted.
That's the problem is that people don't want to talk.
Authenticity is the big thing.
In my experience, there's a lot more opportunity than not.
And so in a way like run towards the fire in this case.
I do actually think it's interesting when people say well, you know the AI thing is going to like, you know humans are going to be deemed irrelevant.
It's like I think we are so far from a point where humans are not going to be able to add value to society.
I mean, come on like, once cancer is solved and like whatever, once I could like simply pay my taxes, then we could have a conversation.
Kind of like an argument.
I have to pinch myself saying, are we actually having this argument?
Because right now—
I can't write a full board presentation with AI just yet.
I mean, until I could go to the DMV easily.
I mean, come on, man.
Forget a board presentation, just even a careful email.
A very careful email that you would send to a customer to close a deal or whatever it is.
There's a lot of upside going on.
Well, listen, thank you so much for joining us.
This was a lot of fun.
Absolutely.
Thank you for having us.
Thanks.
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