Lenny's Podcast: Product | Career | Growth
00:03:38 · Lenny Rachitsky, G2 Patel
Changes to your Framer site go live to the web in seconds with a single click and without any help from engineering. Whether you want to launch a new site, test a few landing pages, or migrate your full .com, Framer has programs for startups, scale-ups and large enterprises to make going from idea to live site as easy and fast as possible. Learn how to turn your website into a growth engine from a Framer expert, or just get started building for free today at framer.com/lenny. And if you're a Lenny's Product Pass subscriber, you get an entire year of Framer Pro for free. Check it out at framer.com/lenny. Rules and restrictions may apply. Jeetu, thank you so much for being here, and welcome to the podcast. [00:04:22] S0: Lenny, I'm excited. Good to see you.
00:04:22 · G2 Patel, Lenny Rachitsky
[00:04:22] S0: Lenny, I'm excited. Good to see you. [00:04:24] S1: The timing of this conversation is so amazing. You're just coming off running the most insane assembling of AI thought leaders and tech leaders I've ever seen. Let me just read a few of the names that you guys had at the summit that just happened a couple of days ago. You had Jensen, you had Sam Altman, and you had Marc Andreessen, you had Fei-Fei Li, you had the CEO of Intel, AWS, Mike Krieger, Kevin Weil. That's just like a third of the guests you guys had. I don't know how you did this, but it feels like you have this fire hose of information coming at you. You interviewed a lot of these people on stage, and so while it's fresh in your mind, I want to ask you, after doing this summit, after hearing from these folks, what's something that you've changed your mind about, or what's just like an insight that has been lodged in your head ever since doing the summit?
00:05:13 · G2 Patel
[00:05:13] S0: It was an amazing thing to pull off, because we never thought we'd be able to do it, and we were really worried going into it, thinking, "Well, we're trying to do fireside chats for 12 hours, and there's a capacity of human absorption that we're trying to challenge." And so, we tried to put a lot of breaks in there and we started at nine a.m and we ended at nine p.m., and we had a couple hour break in the middle, but everyone stayed and everyone was engaged and we could have gone until 11 and it would've been fine. And it's because the quality of the conversations and the caliber of the guests that were there made a world of a difference. What was the takeaway from it? I'd say a few things. One is the capabilities overhang is real. I think there's more functionality, on one end there's kind of this paradox of progress. On one end we are solving all these amazing problems with science, on the other end you talk to the enterprise, they're like, "We're struggling with adoption." And I feel like there's help that's going to be needed within organizations. And the reason we pulled this thing together, the goal was, what is happening in the industry and how can we help customers make sure that they can make the most of it? Because we are in one of the most foundational movements that we have seen in human history, and it's we got to make sure that we make the most of it. So, that was one is, the capabilities overhang is real. The second area is, I'd say that it's harder when you go beyond some of the more obvious use cases. For example, coding is a very, very good use case that you're starting to get a lot of success in. I mean, we just had our first product that we think we'll be in the next two weeks, 100% written with AI. I don't think that's as easy when you go into every other function of the business. And that was actually very apparent that hey, this is going to require some nuance and understanding of how every business works. And then the third one, which is a really interesting takeaway, and Marc Andreessen talked about this in your podcast a few days ago. In fact, when I talked to him, I actually started with your podcast, because it was so interesting, and then we dug into it a little bit more.
00:07:21 · G2 Patel, Lenny Rachitsky
And then Kevin Scott was also talking about this, but this notion of the fact that birth rates are going down and we have a demographic shift that's happening in the world and there's going to be more people that are in the older age bracket than the younger age bracket, and those older people are going to need folks to take care of them. And historically in society, that's actually always been the case, but we might be at a point where that might not be the case. And when that's not the case, we worry about AI taking our jobs, I think that survival of humanity depends on a successful AI. Because at some point if you have 60% of your population that's in a demographic where you don't have enough people who take care of them, that could cause a lot of human suffering. So, I don't think people talk about this enough, and that's something that we have to take a moment and digest, that this is so important for our collective success moving forward. [00:08:16] S1: Something I was going to say during my chat with Marc and when he talked about that AI is basically coming just in time to save us, because there aren't going to be enough people to do the jobs. In my head I was thinking, "This is like another signal that we are in a simulation that things are working out just right for us." What are the chances? [00:08:34] S0: The older I get, the more I believe that we are actually in a simulation. The first time I heard that concept, I thought it was such an absurd concept. Now I'm like, "This might actually be happening." You never know.
00:08:34 · G2 Patel, Lenny Rachitsky
[00:08:34] S0: The older I get, the more I believe that we are actually in a simulation. The first time I heard that concept, I thought it was such an absurd concept. Now I'm like, "This might actually be happening." You never know. [00:08:47] S1: Following this thread, a lot of companies are trying to adjust to this new world. You are doing an incredible job at actually doing this. We got connected through Kevin Weil, who is former CPO at OpenAI, now head of science at OpenAI. And the way he described it is the work that you have done to turn Cisco the way he described it from an older, slower, more traditional enterprise to a very AI-forward company. How many employees do you guys have? You said 45,000. [00:09:15] S0: We have 90,000 employees, 43,000 watch the stream. [00:09:18] S1: So, the big question for you is, it feels like it's really working, and this is very difficult to do at a company of that scale. A lot of leaders are trying to make it work. What are two or three things that you've done that you think have been most impactful and effective in helping Cisco lean into AI, not be scared of it, and actually embrace the future?
00:09:40 · G2 Patel
[00:09:40] S0: Innovation in my mind is a choice. I always find it interesting when people say, "Well, you're a large company, you can innovate. You're a small company, you can innovate." It's like, "No, it's just a choice. Every day you come into work and you can choose to be thinking about being creative, or you can choose to not be creative." It's like a little binary ... It's a binary choice You can make every hour, every minute of every day. And so, we made that choice that says, Cisco is going to be not just an iconic company. And Chuck Robbins, our CEO says this very eloquently. He's like, "I want Cisco not just to be an iconic company. I want Cisco to also be an iconic and innovative company." And so, we got to make sure that we are actually innovating with the set of constraints that we are dealt with. Every company has their own set of constraints, and we have our own set of constraints, and we have to make sure that given those constraints, we have to actually innovate really well. Now, what are the two or three things that have happened that have really helped us out? One was, being very clear on what is up for debate and what is not up for debate. Because what can end up happening is you can always have a pocket veto in a large company where if you ask enough number of people, people say no. If you're a large company, you ask enough number of people, someone's going to say no, right? And so, when you have conviction about something that's happening, that is going to be a bet that you need to place. What most people think in large companies is large companies don't experiment. That is in fact not true. Large companies experiment a lot. What large companies don't do is when an experiment works, they don't go all in and double down. They try to keep hedging. We didn't hedge on AI. We said we were going to go all in. That was number one. What that meant was we had to get people to understand that their personal success and the success of the company are very aligned in us getting dexterous with the use of AI. That means that if they feel like for some reason AI is going to take their job or AI is going to be negative for them, we had to reassure them that that was not the case.