Welcome to the latest Silicon Valley Vibes, a podcast from SVLG. I'm your AI announcer, VJ, bringing you the latest on the people, platforms, and places of the one-of-a-kind ecosystem of Silicon Valley. On this episode of SVV, we welcome G2 Patel, Cisco's president and chief product officer. He talks with us about where he sees the infrastructure growth for AI, and he also gives a positive take on where the future of jobs will go in the new era of expanded artificial intelligence. Bringing you into that conversation is our SVV host Peter Laro Munoz, SVLG General Counsel and SVP of tech policy. Peter, let's get into it.
G2, it's great to have you join us today. Welcome to Silicon Valley Vibes.
Thank you for having me, Peter. It's good to be here. I'm a big fan of your show.
Well, thank you. Always nice to hear that we have our listeners out there. And let's start with your background. You serve as the chief product officer for Cisco, one of the largest and most influential companies in the innovation economy. How did you come to your present role and what do your responsibilities include?
How did I come to my present role? I joined here five years ago. I actually was the chief product officer at Box. I've always been a product guy for the past decade and a half. You know, when I joined here, I was running the WebEx business and the security business. Over time, we were a company that was operated very much like a holding company where we had a lot of different businesses and each one of those businesses kind of did their own thing. And over time, it became very apparent that that model doesn't work anymore because you need to have these products kind of be synergistic and harmonious with one another and operate like a platform. And our CEO Chuck, who's been a delight to work with for the past five years, he and I started talking. It made a lot of logical sense to say let's combine these orgs together because what that does is it's going to reduce the marginal cost of ingestion of every new technology we have because it's integrated into the platform and every technology we introduce to the market will not only add value by itself but it's also going to add value to everything that the customer already owns which then creates a compounding effect. And so we decided to pull it all together into one organization about a year ago and it's been a blast. We've had a great time. There's been a lot of reception from the market that's been very positive. The beauty is we're just getting started. You know, the most exciting work is still to come out, but there's been a huge amount of positivity.
Well, what's interesting to me, G2, is that with all of your experiences, I was doing my research, my homework before this episode, there was one word that kept turning up again and again and again in your professional biography, and that was vision. What does vision mean for you and for Cisco?
You know, the way I think about this is you have to have a clear true north that's defined. And once you've defined the true north clearly, then it makes a lot of sense to have an execution plan in place. But you have to be very clear of like if you were to flawlessly execute, what does that end state look like? I've always found that to be very instructive for a couple reasons. One is it brings the best people to the table. Business is a team sport. So if you actually solve hard problems with an ambitious goal and a vision and then bring the best people in, your probability of success just goes up exponentially. You should just start with that because it's, you know, pick hard problems to solve, have a clear true north and bring the best people on and then ideally get out of the way so that they can go out and do the things that they do best. I'm completely shameless on riding on other people's coattails that do great work.
Well, what's the old line? You see far because you stand on the shoulders of giants, right? I think that's a great lesson for iterating and certainly building on the successes of others whether it's in your organization or somebody else's. Let's turn now to the seminal innovation of our time, artificial intelligence. Cisco has been making big investments in this space. What excites you and your company about the technology?
You know, if you think about AI in general, we are now squarely in the second phase of AI. The first phase for the past two and a half, three years, there was of course a phase zero which was like for the past 25 years where there was a bunch of, you know, advancements in neural networks and how deep learning happened and all of that stuff. But when you start to think about the consumerized phases of AI, we're in the second major phase of consumerization of AI. First phase was you had this era of individual productivity where you had these intelligent chatbots where you can ask questions, it'll give you an intelligent answer. And it felt like magic, like when ChatGPT first came out, you know, I still remember where people felt like, oh my goodness, this feels like magic. We are now in the second phase where rather than chatbots just intelligently answering our questions, we have agents that'll be conducting tasks and jobs almost fully autonomously on behalf of humans. And what that'll do is it'll actually create this kind of very, very dynamic environment where you'll be able to augment capacity to humans at unprecedented scale.
And as a result, our world of 8 billion people will feel like we have the throughput capacity of 80 billion people because for every human there might be 10 agents and every human becomes essentially a manager of agents. You know, every individual contributor is actually now going to be a manager of agents. And so that kind of world will allow us... the simplistic answer to that is, oh my goodness, this is going to improve everyone's productivity. I think that's interesting, but it's not consequential. The more important thing that's going to happen is we will have original insights generated from AI that'll be so profound that we will be able to then dream of solving problems we couldn't even imagine solving before. And when that starts to happen at scale, medicine will change, material science will change, and the way in which you go about engaging and communicating with people will change, and every business and every workflow in every industry will actually get reimagined.
And that I think is a pretty amazing thing to witness where we're right at the beginning and the next decade might actually end up becoming one of the most fun decades that any of us have ever lived through, you know. And so I'm an eternal optimist without being naive about the fact that there's going to be some pretty meaningful downside risks if this thing goes sideways. But our job is to mitigate those risks, not let those risks stifle progress.
And I'm going to get to that a little bit later on in our conversation about what some of those challenges might look like. But for now, I just want to continue to kind of pull on this thread about the opportunity that is going to be coming with AI. And recently, you gave an interview in Fast Company, disclaimer, that's a favorite read of mine. And you spoke about the disconnect some people feel between the excitement they have for AI and the level of preparation they have to use the technology.
Yes. We did a study, I think Peter, it was now probably like three, four, five months ago. We would ask CEOs how excited do you feel about AI and like an overwhelming majority, 97% or something like that, said extremely excited. We think it's going to change our company. It's going to be company defining. We are all in on AI. Virtually every company said that.
Then you ask the same people, well, how prepared do you feel with AI? And only 1.7% of them felt prepared. And so you obviously as a next level would ask the question, why do you not feel prepared? And there were a handful of things that came up as reasons why they were not feeling prepared. One was the infrastructure scarcity and the constraints in infrastructure and the complexity associated with the infrastructure didn't make them feel comfortable that they were going to be able to get the full value out of AI because they don't feel like they have the right infrastructure in place nor the knowhow. Number two, there was a trust deficit. You know, safety and security weren't things that they felt comfortable about. They felt like this thing could go sideways and actually affect my safety and security. And number three was a skills gap. They felt like, oh, I don't feel like I have the right skills in my organization to be able to go out and fully prosecute this opportunity that I need to prosecute to the fullest. And the fourth one was like the data that was needed, right? Like for example, how do I prepare my data in the right way so I can get the most use of AI? Those are the top three or four things that came out in that study and it said to us, goodness, we got to make sure that we get cracking here and really help customers not have these constraints become impediments for progress. And that's what we've been busy doing at Cisco. And so what we do is we provide infrastructure that is what we think of as critical infrastructure to power the AI era. We provide safety and security capability so that you can secure AI itself, every model, every agent, every application. And then we provide a data platform, specifically in our case with machine data. And then number four is we provide training at scale around the world to make sure that these skills are learned by people everywhere and not just the people that are the intellectual few elites, but every person should actually get to be dextrous with AI because I feel like there's only going to be two kinds of companies in the world. There'll be companies that are AI forward and dextrous with AI and then there are going to be companies that really struggle for relevance. And I think it'll be the same for people and so we just have to make sure that we raise the bar and increase the dexterity levels for people with AI.
So G2, one of the narratives that everyone is hearing now in the news and in the media at large is that AI is going to take all of our jobs. Whether it's entry level, whether it's white collar with experience, doesn't matter. AI is going to take all the jobs. Do you share in that vision of the future?
I don't. I don't. Let me tell you why. I actually refuse to believe that humans are going to be obsolete anytime soon. And the reason for that is actually an obvious one which is we have been extremely resilient, extremely creative creatures that have always found ways to add value as the society gets reconfigured. And I think you're going to see that same thing happen over and over again. And so the way I see it is it's not AI that takes your job you should worry about. It's someone that uses AI better than you that you should worry about because they might take your job. Worry about the things you can control. Worry about what do I need to do to get to be the most dextrous in the use of AI. So that becomes my differentiator.
And I think it's a very kind of silly comparison to make to say it's AI versus the human. I think AI is in service of the human and the human partners with AI so that we can actually do better. Every job will get reconfigured but that doesn't mean that humans won't have value to add in society. Humans will continue to have value to add in society. Having said that, you know, there was a great line Peter I heard recently which is if you think you don't like change, wait until you come across irrelevance. You'll hate it even more. Don't resist change. Embrace it. Take the innovation that's going on and make it part of your fabric that you continue to keep learning with it. Here's the one thing that I found about every human. I haven't found a human yet that has not enjoyed it. Every human loves learning. And what we don't like is the failure attempting to learn and not being able to learn. What we should do is make sure that we're using these tools to actually get up to speed faster. One of the things Peter I did when I first took this job, look, Cisco has such a broad portfolio that's very hard to get to be good at everything all at once. And so I didn't know a lot of the portfolio when I first came in. I didn't know a lot of those markets. I had no idea what those markets were all about. But what I did was every single day I would listen to my teams and I would take down notes on things that I didn't understand. And every night for three hours I would actually go do research. And the next day I would just be that much more dangerous because I knew more than I knew the day before. And I actually then started developing an instinct.
And that is what humans are so good at is we can take so much context. You know, we keep talking about AI's context window being 128,000 characters. Our context window is so broad. Think about a two-year-old and how much they see, learn, watch, observe. And every single day, if you have a kid, you'll realize how much they've grown and how much they learn. Compounded over time is something that we should not take lightly. And we have instinct and we have judgment that we can actually do things that AI can't do. And then there are things that AI can do better than us. And we should not be shy to give that to AI so that we can actually start focusing our time on doing things we can do better than AI could do.
Yeah, this very much has that feeling of the early days of the internet where, you know, some folks might have been scared. They might not have understood exactly how to navigate the web. And pretty soon it became a language that was universal. Everybody could use it. Your grandmother could use it. Your five-year-old could use it as well.
What's interesting in AI is for the very first time machines are learning the language of humans rather than humans having to learn the language of machines because you can now speak to it in your native tongue and it'll respond back to you. And that unlocks a huge amount of possibility for what could happen because it democratizes the use where you don't need to have these skilled people that are using it. Everyone can use it when everyone can benefit from something. You know, that just has a compounding effect on humanity and the progress we can make.
And making sure that people are able to take advantage of this technology. You spoke a moment ago about training workers and users to leverage the tools around AI. There's certainly that need for people today, but do you have thoughts about how we train a future workforce, maybe those who are, you know, still in school? How do we get them ready so that they're able to step up and use these tools professionally when they enter the work world?
