a16z Podcast - How to Build a Successful Company in an Era of Disruption
Episode Date: August 6, 2025What happens when a startup becomes a giant—and then has to reinvent itself all over again?In this episode, Martin Casado sits down with Raghu Raghuram (former CEO of VMware) and Jeetu Patel (Presid...ent and CPO at Cisco) for a deep, tactical conversation on scaling, disruption, and navigating transformation from the inside. They share hard-won lessons from leading two of the most iconic infrastructure companies in tech—through waves like virtualization, cloud, containers, and now AI.They cover:How to keep innovation alive inside large companiesWhy the best companies operate with a founder’s mindset, even without foundersThe difference between selling to buyers vs. practitionersWhy the story is the strategy, and how to tell it at scaleHow Cisco is rebuilding its startup DNA in the age of AIIf you're building or leading through a major tech wave, this episode is a playbook. Timecodes:0:00 Introduction 2:02 Weapons of Mass Disruption: Abstractions, Business Models, and Cloud 5:57 Cisco’s Missed Cloud Wave & Resetting for Innovation 6:39 Operating Like a Startup: Speed, Scale, and Leadership 10:00 Go-to-Market Challenges: Fencing Off Innovation 11:04 Organic vs. Inorganic Growth: Lessons from VMware 12:04 The 10x Rule and Competing with Incumbents 14:39 Structuring for Disruption: Two-Pizza Teams and Ideal Customer Profiles 18:43 Storytelling as Strategy: Galvanizing Large Organizations 19:42 The AI Wave: Consumerization and Infrastructure Demands 25:34 Founders vs. Operators: Leading Transformations 31:47 Product-Led Organizations: From Sales to Product Focus 34:35 The Future of Infrastructure: AI, Market Size, and Vertical Integration 39:34 Timing, Market, Team, Product, Brand, and Scale 41:19 Authenticity, Opportunity, and Final Thoughts Resources:Find Martin on X: https://x.com/martin_casadoFind Raghu on X: https://x.com/raghuraghuramFind Jeetu on X: https://x.com/jpatel41 Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that 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. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
Transcript
Discussion (0)
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 it.
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.
SaaS 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.
Ragu Raggerom, CEO of VMware and G2 Patel, EVP and GM at Cisco.
They reflect on leading through market disruptions from VMware's early dominance and visualism.
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 A16Z.com 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, Ragu.
So when VMware came out, I remember, like, it was the late 90s
and I could run, like, 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 transactions.
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?
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.
Yeah.
This is the classic innovator dilemma description
or a new business model.
So in the case of VMware, we did the first and the last one, meaning we bought about a new abstraction for the data center, right, 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.
And I would say those weapons of mass disruption
were used against us, not intentionally.
I mean, the two big ones that we face,
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.
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 bought about was it made infrastructure available to developers without IT.
That was the massive analog, 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 disruptions 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 wrote 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 at Cisco,
how you're thinking about navigating this.
Yeah, the obvious one is we missed the cloud wave.
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.
Yeah.
But you've lost the soul of the business, which is, are you innovating at a very impatient velocity?
Yeah.
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.
Yeah.
And I think about five, six years ago that had happened for us.
Yeah.
And we had to hit the reset button.
And let me tell you, like, 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?
As exactly.
Just throughout, like most of the people that are on my leadership team, a lot of them are ex-Ceos of acquisitions that we've had that are actually running these pieces.
And you have to have a combination of CEOs and people that know how to operate within the machine that is Cisco.
Yeah.
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 a thousand 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,
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.
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 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 going to have an advantage of getting to a disproportionate amount of velocity to get to market.
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 going to feel served, and then you're not going to go out and get to the level of money.
Okay, so let's think 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 lose 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,
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 a retool,
go-to-market product, everything for this new base,
even though 80% comes.
And so, I mean, I know, Ragu, you had to deal with this.
Like, how did you think about how you evolve the company,
not a technology disruption,
but even just catering to, like, a new base.
Yeah.
On the market side, the marketing side, the sales side.
Yeah, yeah.
What you said is spot on,
because when you're talking only to your best customers,
by definition, that's not right 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.
Yeah.
Right?
So if you 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 sales force
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
Nesira and networking
then you need to fence it off
and that's it's there
so interesting about VMware
it's one of the few companies
that actually did both pretty successfully
like V-SAN was storage.
Exactly.
You pulled it off, I don't know how.
And then Nassira was inorganic, and you pulled it off.
I didn't know how.
And so, like, any lessons of, like, inorganic, organic, 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, sort of a truth.
And in the case of V-San, you know,
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-market 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 VM where you say it's 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 at it from a different angle
and being at least in 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
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 you all know,
it was a different way of operating a network.
Yeah, yeah, totally.
So that was the value proposition.
Not necessarily 10x better.
It was something that could not be done
in a physical network at all.
What do you mean you can program the network?
What do you mean you can have virtual firewalls?
Yeah, yeah.
et cetera, et cetera, that scale at well.
I think it 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 Ragu 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 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
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 an 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, 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 disruptive.
Let's say you've decided not to do it inorganic.
You're doing it organic.
How do you think about structuring it?
So the way that we structured 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
version one product out to the market,
but they are not going to 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 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.
Exactly, yeah, yeah.
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 to start to occur.
But it takes a while.
Like, 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. 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 Corps would keep it out of the account? Is that what is?
Well, it would keep it out of the account because it's not going to go sell the Bank of America.
I'm like, yes, actually the wrong account to go sell it in as a version one product, because it's not ready for all of the capability.
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 to product market.
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 17,000 sellers and say to them,
you, 1,000 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 the,
larger companies, misleads people into thinking about, oh, my customers, J.P. Morgan, my
customer at Home Depot, exactly.
That's the ideal.
Use case profile.
The ideal practitioner profile.
Exactly.
The ideal practitioner profile.
So you're going to narrow cast it down to 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, isn't
a product.
But I will tell you this, that once you start building products that start getting momentum
him 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 a smo back.
It's got its mojo back.
Stock it all the time.
Hi, congratulations.
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.
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.
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.
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. 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.
And so the story is so important. The best in the world of 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 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 one step further and say, the story is the strategy.
That is the strategy, yeah.
Right?
Because human beings, certainly 95,000 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 Regu, 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.
Actually, not, I just thinking about that right now.
You paid $1.99 and then $2.49 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 is 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've 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 chap-bought,
things that are actually quite different,
but I think we're used to thinking about the old AI,
not the U.S.
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 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've 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 can sell to IT or you can sell to, like,
Like, you know, whatever.
Security or marketing.
But like, this is literally individuals with credit cars 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, like, one option for Cisco is like, whatever, you have a new data.
Center will sell you a new switch, and it doesn't matter that, like, 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 the 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 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 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.
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.
It's 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 an agent's going to, today, probably an agent works.
autonomously for 20 minutes
in the next six months
it'll work autonomously for maybe
two hours or ten 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 a thousand employees
and you add 10,000 agents
that's like having an 11,000 employees
that means you have to have your network bandwidth
be equivalent to what can serve 11,000
and 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
of the people building it.
Yeah.
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 or...
I say, with Cisco, it's also just good to be king, right?
If you're in the network, like, whatever compute grows, the network grows.
Yeah, but, you know, 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.
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 Ali Goatsy.
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 focus.
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.
Like, do you think it's a different job?
Yeah, there are a couple of things where a founder has unique license.
Yeah.
Right?
Yeah.
But then there is a rest of it, which is how do you make the change happen?
Yeah.
Right.
Like, how did you think about it?
I mean, you were this 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.
The 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.
Yeah.
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've got to do,
which founders naturally do,
is, I mean, the overuse 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.
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 their natural entrepreneurs.
I have a slightly different,
like I agree with everything Ragu 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 was saying, 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 mental,
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.
Yeah, yeah, yeah.
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.
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 it 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.
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 conversation 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 start
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.
Githa, 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.
Right?
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 as 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 I didn't occur to me before
that both of you are product people
yeah of course right
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, any other transformation,
if it doesn't start from the product.
Yeah, I think so.
That's very interesting.
Do you manage, like, from products on out?
Absolutely.
I'm very public about this.
I usually think the product is a soul of the company.
And what we do is when we start thinking about the products,
So Cisco used to be a very sales-led company.
Well, I mean, John Chambers is the cost of the sales guy.
And what I give Chuck a lot of credit for is he said,
we have to become a product-centered company.
Really?
I wasn't aware of that.
And then Chuck's a sales guy, right?
Right, right, exactly.
And he said, gee, do 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 is to tell me this.
If you build a product that cures cancer,
you sell it in the Himalayas from 2.30 to 3.30 p.m. on Tuesday after
every third Tuesday of the month,
there will be a line out the door, right?
Because you're carrying 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 product leadership
I do find out 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.
Maybe, well, 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 a long term, right?
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.
Would love Raghu, your thoughts on the AI stuff.
I know it's pretty early.
Then I love to hear your thoughts.
So do you think this changes infrastructure?
Do you think it's large as the independent of infrastructure?
Do you think this increases, Tam?
Like, how do you think about this on a macro scale?
I think it changes infrastructure in an enormous way, right?
I mean, infrastructure always is a follower of the change.
Right, yeah, yeah, of course, yeah.
I mean, go back to Let'scape, right?
When the browser came out, we were running on, what, 4.8 kilowattoms or whatever.
And then look at the internet infrastructure today.
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.
Yeah, yeah, that's right.
And today, now you've got AI factories.
And like you said earlier in the talk, the bottlenecks of progressively moving every way.
So I think fundamentally, every layer changes.
It's not just compute.
We got high bandwidth memory changes, right?
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, right? 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 1,000 X, 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 like 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 like, for example, Microsoft Teams is a huge competitor for us.
we partnered with them and have them run on 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 the one lesson I've learned in 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 is a great, that's great advice.
That's why I asked Ragu 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.
Yeah.
By the way, I mean, on your point about the vertical integration,
I think that's an interesting industry debate, in my opinion.
Yeah, of course.
Because if you look at the last two industry waves, the PC and the cloud, right?
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, yeah.
So now, in this wave, it swooped to knots.
And so we'll see if this is the right model.
Yeah, yeah, for sure.
And we are starting on cyber security.
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.
And so I don't think the vertical versus horizontal is 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.
Okay, so listen, we're coming to the end of the time.
Listen, we've got two of the most story execs, elite execs, in infrastructure.
A lot of the people listen 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 in 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.
Yeah.
Get the timing right.
Right now, like, 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 control the entire market
is going to be really hard,
so you have to make sure you go after a large dam,
but address a step at a time.
And ideally, create the tam.
Don't go after an existing time.
It's even better.
Number three is team.
And oftentimes people will say,
well, this team trump market.
I actually think market always trumped steam.
Same.
My idea, this is Mark Andresen, I agree, yeah, yeah.
I think that's a 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 on 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.
Like, that's the problem is, like, people don't want to talk.
Authenticity is the big thing.
And I will say, like, the last thing for people that are, like,
looking at these disruptions and they seem a little bit scary.
In my experience, there's a lot more opportunity than not.
And so, like, 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 can, 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 to even a careful email.
That's right.
A very careful email that you would send.
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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