 From Sand Hill Road to the heart of Silicon Valley, it's theCUBE, presenting the People First Network, insights from entrepreneurs and tech leaders. Well, Ron, I'm John Furrier with theCUBE. We are here on Sand Hill Road at Mayfields, venture capital headquarters for the People First Network. I'm here with Pradeep Sindhu, who's the co-founder of Juniper Networks, and now the co-founder and CEO of Fungible Granks for joining me on this special conversation for the People First program. Thank you, John. So I want to talk to you about entrepreneurship. You're doing a new startup. You've been so successful as an entrepreneur over the years. You keep building great companies, Juniper Networks. Everyone kind of knows the success there, great success. We've interviewed you before on that. But now you've got a new startup. I do. You're building a company. I thought it starts for free young people. Come on, we're nine years into our startup. We're still a startup. Well, I'm not quite over the head yet. So, one of the reasons I jumped back into the startup world was I saw an opportunity to solve a very important industry problem and to do it rapidly. And so I took the step. We're super excited that you shared your vision with us and folks can check that video out on theCUBE in deep dive on the future of that startup. So it's exciting, check it out. Entrepreneurship has changed. And one of the things that we're talking about here is how things have changed just since the last time you've done a round. I mean, you're now a couple years in, you've been stealth for a while building out this amazing chip, the data processing unit, the DPU. What's different about building companies now? I mean, are you a unicorn? Are you at a billion dollar valuation yet? I mean, that's the new bar. It's different. What are some of the differences now in building a company? You know, one thing, John, that I saw as a clear difference between when I started Juniper and started Fungible is that the amount of bureaucracy and paperwork that one has to go through is tremendously larger. And this was disappointing because one of the things that the US does very well is to keep it light and keep it fast so that it's easy for people to create new companies. That was one difference. The other difference that I saw was actually reluctance on the part of venture to take big bets because people had gotten used to the idea of a quick turnaround with maybe a social media company or something. Now, you know, my tendency to work on problems is I tend to work on fundamental problems that take time to do, but the outcome is potentially large. So I'm attracted to that kind of problem. And so the number of VCs that were willing to look at those kinds of problems were far fewer this time around than last time. So you got some nos then? Of course I got nos. Even from people that... Founder of Juniper Networks, you've done amazing things. Like, you created billions of dollars of value. You shouldn't be gold-plated. Well, so what you did 20 years ago only goes so far. I think what people were reluctant, remember, I started Fungible in 2015. At that time, silicon was still a dirty word. I think now there are several people who said no were regretting because they see that it's kind of the second coming of silicon. And it's for reasons that we've talked about in the other discussion, that Moore's law is coming to a close and that the largesse that it was distributing over the last 30, 40 years is going away. So what we have to do is we have to innovate on silicon. As we discussed, the world has only seen a few architectures for computing engines on silicon. One of the things that makes me very happy is that now people are going to apply their creativity to painting on this canvas. So silicon's got some new lifeblood. What's your angle with your silicon strategy? So our silicon strategy is really to focus on one aspect of computations in the data center and this aspect we call data-centric computing. Data-centric computing is really computing where there's a lot more movement of data and lot less arithmetic on data. And today, given scale-out architectures, data has to move and be stored and retrieved and so on as much as it has to be computed on. So existing engines are not very good at doing these data-centric computations. So we are building a programmable DPU to actually do those computations much, much better than any engine can today. And that's great. And just a reminder, we've got a deep dive on that topic. So check out the video on that. So I've got to ask you the question, why are people resistant to the silicon trend? Was it trendy? Was it the lack of information? You're almost seeing people almost less informed on computer architecture these days as people blitz scale for SASBOT businesses. Cloud certainly is great for that, but there's now this renaissance. Why was it, what was the problem? I think the problem is very easy to identify. Building silicon is expensive. It takes very specialized set of skills. It takes a lot of money and it takes time. Well, anything that takes a long time is risky and venture, while it likes risk, it tries to minimize it. So it's completely understandable to me that people don't want to take, they don't want to put money in ventures that might take two, three years. Actually, going back to the juniper era, there are venture folks, I won't name them, but who said, well, if you can do this thing in six months, we're in, but otherwise no. How long did it take? Two and a half years. And then the rest is history. So there's a lot of naysayers. It's just categorical, kind of like courses for horses for courses, as they say, that expression. All right, so now with your experience, okay, you got some nose. How did that make you feel? You're like, damn, I gotta get out and do the rounds? You just kind of moved on? I just moved on because the fact that I did juniper should not give me any special treatment. It should be the quality of the idea that I've come up with. And so what I tried to do, my response was to make the idea more compelling, sharpen it further and try to convince people that, hey, there was value here. I think that I've not been often wrong about predicting things maybe two, three years out. So on the basis of that, people were willing to give me that credibility. And so there were enough people who were interested in investing. What did you learn in the process? What was the one thing that you sharpened pretty quickly? Was it the story? Was it the architecture message? What was the main thing that you had to sharpen really fast? The thing I had to sharpen really fast was while the technology we were developing is disruptive, customers really, really care. They don't want to be disrupted. They actually want the insertion to be smooth. And so this is the piece that we had to sharpen. Anytime you have a new technology, you have to think about, well, how can I make it easy for people to use? This is very, very... So the impact of the architecture, Sophie, if it was deployed in the use case and then look at the impact of the whole effect. You cannot require people to change their applications. That's a no-no. Nobody's going to rewrite their software. You also probably don't want to ask people to change their network architecture. You don't want to ask people to change their deployment model. So there are certain things that need to be held constant. So that was a very quick learning. So one of the things that we've been talking about with other entrepreneurs is, okay, the durability of the company, you're going down, playing the long game. But also innovation and attracting people. And so you've built companies before RC Juniper and you've worked with a great team of people in your network. How did you attract people for this? Obviously, they probably were attracted on the merit of the idea, but how do you pick people? What's the algorithm? What's the method that you use to choose team members or partners? Because that's obviously super important. If you've got a gestation period where you're building out, you gotta have high quality DNA. How do you make that choice? What's the thought process? So John, the only algorithm that I know works is to look for people that are either known to you directly or known to somebody that you trust. Because in an interview, it's a hit or miss. At least I'm not so good at interviewing that I can have a 70, 80% success rate. Because people can fake it in an interview, but you cannot fake it once you've worked with somebody. So that's one very important test. The other one was, it was very important for me to have people who work collaborative. It is possible to find lots of people who are very smart, but they're not collaborative. And in an endeavor like the one we're doing, collaboration is very important. And of course, the base skill set is very important. So, almost half of our team is software. Because we are- It's a programmable chip. It's a programmable chip. We're writing our own operating system, very life-weight. So you need that combination of hardware and software skills, which is getting more and more scarce, regrettably. I had a chat with Andy Pechnestine at VMworld and he and I had a great conversation similar to this. He said, you know, hardware is hard, software is easier. And that was his point. But he also was saying that with merchant silicon, it's the software that's key. It is absolutely the key. Software, you know, software is always important. But software doesn't run on air. We should also remember that. And there are certain problems. For example, switching packets inside a data center, where the problem is reasonably well solved by merchant silicon. But there are other problems for which there is no merchant silicon solution, like the DPU that we were talking about. Eventually there might be, but today there isn't. So I think Apple is a great example for me of a company that understands the value of software hardware integration. Everybody thinks of Apple as a software-only company. They have thousands of silicon engineers, thousands. If you look at your Apple Watch, there are probably some 20 chips inside it. You look at the iPhone, it won't do the magic that it does without the silicon team that they have. They don't talk about it a lot on purpose because- Because they don't want a China chip in there. Well, they don't want a China chip, but not only that, they don't want to advertise. It's part of their core value. And so, as long as people keep believing that everything can be done in software, it's good for Apple. So this is the trend, Larry Ellison brought this up years ago when he was talking about Oracle. He tried to make the play that Oracle would be the iPhone of the data center. Which people poo-pooed and they're still struggling with that idea, but he was pointing out the benefit of the iPhone, how they're integrating into the hardware and managing what Steve Jobs always wanted, which was security number one- Absolutely. And seamlessness of use. And the reason the iPhone actually works as well as it does is because the hardware and the software are co-designed. And the reason it delivers the value that it does to the company is because of those two. So you see this as a big trend. You see that hardware and software work together. You see cloud-native heterogeneous- Computing. serverless environments abstracted away with software and other components, fabric and specialized processors. Yes. And just application developers just programming at will. Correct. And edge data centers. So computing, I would say that maybe in a decade we will see roughly half of the computing and storage being done closer to the edge and the remaining half being done in these massively scalable data centers. I want to get geeky with you for a second. I want to ask you a question. I want to get your take on something I've been thinking about and haven't really talked publicly about. I kind of said it on theCUBE a few times in a couple of interviews, but I want to get your thoughts. There's been a big discussion about hybrid cloud, private cloud, multi-cloud, all that stuff going on. And I was talking with Andy Jassy, the CEO of Amazon and Diane Green at Google. And I'm like, okay, I can buy all these definitions. I don't believe any of them, but you know what the hell does that mean? But I know, I said to Diane Green, I said, well, if everyone's going cloud operations, if cloud operations and edge is the new paradigm, isn't the data center just a big fat edge? And she looked at me and said, interesting. So is the data center ultimately just a device on this network? If the operating model is horizontally scalable, isn't it just a big fat edge? So you can, so here's the thing, right? If we talk about, you know, what is cloud? It's essentially a particular architecture, which is scale out architecture to build a data center. And then having this data center be connected by a very fast network to consumers anytime, anywhere. So let's take that as a definition of cloud. Well, if that's the definition of cloud, now you're talking about what kinds of data centers will be present over time. And I think what we observed was, it's really important for many applications to come and with the advent of 5G, with the advent of things like augmented reality, with the advent of self-driving cars, that a lot of computing needs to be done close to the edge because it cannot be done, because a lot of physics reasons cannot be done far away. So once you have this idea that you also have small scale out data centers close to the edge, all these arguments about whether it's a hybrid cloud or this cloud or that cloud, they kind of vanish because- So you agree then, it's kind of like an edge. It is. Because it's an operational philosophy. If you're running it that way, then it's just what it is. It's a scale out entity. Correct. Could be a small sensor network or it could be a data center. Correct. So the key is actually the operational model and the idea of using scale out design principles, which is don't try to build 50,000 different types of widgets, which are then hard to manage. Try to build a small set of things, think of toys that you can connect together in different ways. Make it easy to manage. Manage it using software, which is then centralized. That's a great point. You jumped the gun on me on this one. I was going to ask you that next question. As an entrepreneur who's looking at this new architecture that you just mentioned, what advice would you give them? How should they attack this market? Because the old way was, you get a PowerPoint, you show a presentation to the VCs, they give you some money, you provision some hardware, you go on next generation, you get a prototype. It was up and running. You got some users, built it, then you get some cash. You scale it. Now with this new architecture, what's the strategy of the eager entrepreneur who wants to create a valuable opportunity with this new architecture? What would you advise them? So, I think it really depends on what is the underlying technology that you have for your startup. There's going to be lots and lots of opportunity. Well, don't fight the trend, which is that the headwind would be don't compete against the scale out, ride that wave. People who are competing against scale out by building large scale monolithic machines, I think they're going to have difficulty. There's fundamental difficulties there. So, don't fight that trend. There's plenty of opportunities for software. Plenty of opportunities for software. But it's not the vertical software stack that you have to go through five or six different levels before you get to doing the real work. It's more a horizontal stack. It's a more agile stack. So, if it's a software company, you can actually build prototypes very quickly today, maybe on AWS, maybe on Google Cloud, maybe on Microsoft. So maybe the marketing campaign for your company or maybe the trend that's emerging is data-first companies. We heard cloud mobile-first, cloud-first, data-first. Correct. We think that the world of infrastructure is going from compute-centric to data-centric. This is absolutely the case. So, data-first companies, yes. All right, so final question for you. As someone who's had a lot of experience in building public company, multi-billions of dollars of value, embarking on a big idea that we like, I love the idea. A lot of people struggle with the entrepreneurial equation of how to leverage their board, how to leverage their investors and advisors and service providers. What would you share the folks watching that are out there that have struggled? Some think, oh, the VCs, they don't add value. Some do, some don't. There's always mixed reactions of different types out there. And some do, some don't. But in general, it's about leveraging the resources and the people involved. How should entrepreneurs leverage their advisors, their board, their investors? I think it's very important for an entrepreneur to look for complementarity. It's very easy to want to find people that think like you do. If you just find people that think like you do, you're not, they're not going to find weaknesses in your arguments. It's more difficult, but if you look to entrepreneurs to provide complementarity, you look to advisors to provide that complementarity, look to customers to give you feedback, that's how you build value. Pardeep, thanks so much for sharing the insight. A lot of opportunities. Thanks for sharing here on the People Network. I'm John Furrier here at Mayfield on Sand Hill Road for theCUBE's coverage of the People First Network series, about of Mayfield's 50th anniversary. Thanks for watching.