Is AI Killing Software? — With Bret Taylor

25:38Like each of these new waves of technology is adopted seemingly five or tens times faster than the previous generation because they're all compounding. And that's what's so exciting about right now. We were talking about before this show, just I've never felt a pace of change more rapid than the moment right now. For you, I mean, the timing has been really impeccable. Do you have like, I mean, when something's shifting, like when the shift, let's say, just from search to social happen, And a lot of people might have seen something happening, but there was still, I think, in the general public, a feeling of like, I don't know about social media.

26:13I don't want to put my whole life on the Internet. But you're like, I want to be the CTO of Facebook. What do you think gave you that sort of gives you that sense of timing and the decision to move and go all in on this nascent thing? Because you've been right about it a lot of times. I think some of it is just luck. There's no doubt. I mean, I think it's arrogant to say otherwise. I'll just actually, it's funny. I was reflecting on this. Well, my first job was at Google, which has to be one of the best first jobs of all time. Nice job. Why? The dot-com bubble had burst. So the job fair was like a bunch of tumbleweed and like Microsoft and Google.

26:47And I was like, I'd prefer Google. And I knew Marissa Meyer had gone to work there. So just, you know, I would say dumb luck, but it wasn't exactly, I always wonder if I had started my career in 1999, would I have been at pets.com? I hope not, but I don't know. I did have the, I just graduated at the right time. I just want to say we've done two shows at this space and that's the second pets.com reference we've had. I feel bad for them. They're the cool sock puppet. Good for them. I would say if there's one thing that is, you know, I'm curious. I really am curious about new technologies. I think it is hard to embrace change in your own business or change in technology if you immediately are reflexively negative about anything that you see.

27:29I encourage people who are skeptical about a technology to find someone whose opinion that you trust who has a different opinion than you have lunch or have dinner with them and say convince me that I'm wrong and I've done this with a few different technologies that I was skeptical about and I'd find you know a fellow entrepreneur that was really bullish on it and I'd say I just want to I want to understand what you see and I say that just because I not every hyped technology is you know worth the hype but there's usually if smart people are interested in it, there's usually something really important that they see.

28:05And I think if you have that curiosity, you'll be more likely to be able to apply what's good about it to your business or to your life. And I definitely have that. I joke, I've never met a pessimistic entrepreneur and I'm definitely not one either. So it's interesting because we've just talked about these big shifts in technology, search to social, desktop to mobile, and now all of it to AI. There's some people that say AI is the last invention, that there won't be another shift after this. Do you believe that? Not at all. Really? I like to do the thought exercise. So the United States was founded in 1776.

28:44At the time, I don't know what percentage of our economy was agrarian, but I'm guessing it was like 95 % of the country were farmers. And I always imagined taking, I don't know who the most tech savvy founding father was, but Benjamin Franklin maybe I don't know and try if he were teleported right here in between us first of all that would be a little cool but secondly like how long would it take him just to understand where all the food comes from probably a really long time because we've been automating essentially agriculture food distribution for so long we just take it for granted right now I think you know we often see new technologies and see what it displaces that we currently do.

29:22But we create an economy and a culture around our technology, not the other way around. And so in those past, you know, 300 years or something, we've made power relatively abundant, we've made food abundant, we've made transportation relatively abundant. And, you know, just think about the fact that both of us flew here on airplanes, you know, 24 hours ago, and we're podcasting over the internet. It's mind blowing, right? We don't think of it as mind blowing, but it's mind-blowing. I think we just lack the imagination. I think that's delightful. I'm excited that in my lifetime, hopefully 25 years from now, there will be things that today I wouldn't understand and jobs I don't understand, technologies that were hopefully discovered by AI.

30:05And I think a lot of people look at AI because it can do things that we can't and it somehow thinks it takes away from our humanity. And I just disagree, just like the car didn't take away from the horse. It's just different. And I think I'm just optimistic about it. I don't mean there won't be meaningful disruptions. Technology is hard. And we just talked about, I self-identify as a software engineer. And even over the past four months, that job has changed dramatically. The skills that made me what I am are less valuable now than they were, you know, four years ago. But I'm excited for that because I'm excited for the progress it means for humanity.

30:40All right, let's talk about Sierra. So you're seven quarters in, which is wild because you're already doing 100 million in annual recurring revenue. You have 50 % of your customers have more than a billion in revenue and 20 % of your customers have more than 10 billion in revenue. So you are selling in AI customer engagement. You're selling into very big companies and you're getting very big deals. some of your customers like SiriusXM will actually have your platform take action. So this is not chatbot. I think this is important to say. This is not chatbot. It's agentic. It's agents. When my satellite radio isn't working, the AI will reset it for me, and I'll be able to listen again, where that typically would have taken a person.

31:30And by the way, that AI agent is sending a signal up to a satellite in space, which is communicating with your car. How cool is that? No person involved. AI agents talking to satellites. And that's just a normal thing that we do now in 2026. It's pretty awesome. And so my question, because that's a big deal, right? That requires Sirius to say, all right, Brett, go ahead and let your AI technology, which is probabilistic, right? Go ahead and send a signal to our satellites and we're going to trust everything is good. And that to me is the big question that I have about Sierra, which is there's been so much discussion about this AI rollout and what's gone right and wrong and what's taken the AI projects from pilot into production.

32:10And you've got it in production with these big companies that are trusting you with big actions. How have you gotten them to trust you with this stuff? I think it all starts with the customer and the consumer. You were implying some of the risks of AI, which I'll talk about. But if you survey your listeners and survey their sentiment about waiting on hold, it would surprise me if you could find one person who had a positive experience with that. I think we spend, like, years of our life waiting on hold. And the reason for it is somewhat like a mix of sort of business and technical. Until recently, the phone line was analogs.

32:50There was no way to build a digital experience there. So if someone did call you on the phone, you had to staff a call center to answer it. And if you want to not wait on hold, you had to overstaff that call center with people be sitting around most of the time doing nothing, which just costs a lot of money. And if you think of a consumer brand, and let's say your average revenue per customer every month is$10, that might be less than the cost of a single phone call. So you actually can't afford, for most businesses, literally can't afford to have a phone conversation with your customers. But now you can because you can actually have an AI agent pick up the phone.

33:26You don't need to wait on hold. It could be multilingual. It can have perfect access to your systems. It can help you find, if you know the retailer next in the UK, it can help find your order. If you order food in London and deliver it, it can help you whether you're a driver or a consumer of that. Cigna Health Insurance, we went live with them in less than two months with CIRA. And it can help you understand your benefits, process claims. All of these things are just really useful. And I think because consumers don't want to wait and they would like an answer now, and because you can do things with this technology, because we've essentially digitized the last analog channel, which is the telephone, it's unlocking new business models as well.

34:12One of my favorite examples of this is Rocket Mortgage, which for those of you not from the States is, I think, the largest consumer mortgage originator in the States. If you go to redfin.com, you can use an AI agent built on zero to find a home. You can go to then rocket.com and finance that home and get a mortgage. And then with their new Mr. Porter acquisition, service that loan, all with AI agents. It's amazing. Right, right. And this is the pain, right, that you're solving. But I want to hear a little bit more about the discussions that you have with them, The fact that, and the persuasion where you've said, trust our technology.

34:46They've looked at the technology. Is the technology good enough now? Because there was some doubts that it could handle such complex things. So talk a little bit about that. How have you gotten them to trust Sierra with these actions? Because we all agree that the pain is real. Yeah, well, so I'll start with actually an important thing to ground ourselves, no pun intended, in, which is humans make a lot of mistakes too. So if you have an associate talking to your customers, the odds that every associate is going to do everything perfectly is essentially zero. And I think we just have a higher expectation of computers, which is understandable.

35:23But what these AI agents are doing aren't necessarily doing something that was previously perfect. And I think a lot of companies understand that. And for anyone who has a large sales team or customer service team, you know exactly what I'm talking about because you've gotten the phone calls from a client where it didn't go well. So first, I would actually argue counterintuitively, AI agents are actually more reliable than most of the systems that they replace. That doesn't mean they're perfect, by the way. They're just more perfect than the very fallible human operation systems that preceded them.

35:57And the second thing is essentially what we do at CIRA is try to essentially put more robustness and determinism around these inherently non-deterministic systems. One of the best ways we do that is through a technology called simulation. So all of our clients have a database of usually hundreds or sometimes even thousands of simulated conversations that they run before every release of their agent that simulates everything from an angry customer to an unusual case to background noise. Is it AIs talking to AIs? That's right. And it can simulate languages, accents, background noise. And it means that essentially before your agent goes live, your customers aren't finding all the flaws, your simulations are.

36:38For those engineers listening, you can think of it as almost a regression test suite for your agent. We also use AI monitors. So how can you use AI to monitor the AI to look for things like hallucinations? Was it saying something that wasn't in the data presented to it? Or even subtle things like was the AI being frustrating to your customer? Was it being repetitive? and it enables you to, you know, the joke that we say in the office is the solution to every problem in AI is more AI. And there's probably a limit to that, but we really believe it. And what's really fun about that is, you know, with AI monitors, you can monitor all conversations.

37:13So you can go well beyond the scale of your operations teams. And even where you do want people looking at the conversations, you can put the needles at the top of the haystack. So your operations teams are just looking at the conversations that have potential issues. And so really creating a virtuous cycle of testing, monitoring, and human review to create what we hope is a virtuous cycle. So every day that your agent is live, it's more robust than the day before. It doesn't mean it's perfect. But it's really, you know, it's interesting. I'll just go back to the way software's evolved over my career.

37:47In roughly, I think it was like the early 2000s, there's that outlook worm that took over everyone's desktop. And it was before there were CISOs in most companies. Since then, we've developed the role of the CISO. We've formalized the software development lifecycle, which is essentially a methodology to make software robust. We've essentially, in AI agent development, have this idea of an agent development lifecycle. The same idea, which is don't expect perfection, but with this methodology and the product and the platform we've built, you can make a robust agent and you can make it reliable and you can make it something that becomes more trustworthy over time.

38:22um is is what you're saying then that with these ai agents uh it's not like self-driving cars right so self-driving for instance was it was i don't want to say trivial but the company's got it to 95 pretty fast and getting from 95 to 100 has been very difficult and we still don't have it rolled out even though it seems like there's been progress that's been made but if you make one mistake there you know it's it's catastrophic whereas do you think that there's much more of a willingness to allow some errors with ai agents and the type of solution that you provide because your your baseline is these fallible human workers and if you're if you make a couple fewer mistakes with ai you're still doing a better job i'm not sure there's a black white answer to that i mean certainly the reason why sierra has become one of the fastest growing enterprise software companies of all time is because the technology is ready for many companies and many applications.

39:22But it doesn't mean it's ready for all. The challenge with self-driving cars is that the consequences of being wrong can be human injury. So it's rightfully sort of held to a very, very high standard. I might argue held to a higher standard than human drivers, which we might be safer if regulators allowed it to roll out sooner, but it's a whole separate discussion. What's interesting about the technology that we make at CIRA is you don't have to use it for all applications. But if you think about recovering your password or finding your order or even finding a health care provider in the network of your health insurance company, AI agents can do that now.

40:01And that's why we're being pulled by the largest health care financial services, telecommunications, and consumer companies in the world. It doesn't mean it's ready for everything yet, but that's why we exist. If we were sitting here three or four years from now, I'll tell you the more and more mission-critical applications that we'll be ready for. And just going back to where we started our conversation of vibe coding, it's probably very safe for you to vibe code your blog right now. Should you vibe code the login system for a bank right now? I probably wouldn't recommend it. Not if you want to stay in business.

40:35Yeah, exactly. So it doesn't, and could you ask, is vibe coding ready for production? What production application? And I think we're at that stage of innovation right now where the technology is immature. No one's claiming it's perfect. But the idea that you should wait until it's perfect to do anything, I think, is a death sentence for companies who have that mentality. I think the better question is, what processes at my company are ready for the current set of technologies? Recognizing, by the way, that it's not a question of if it will make a mistake, but when it does, how do you detect it?

41:08How do you mitigate it? All the controls that you have in place. And I would make the argument that actually for most processes in most companies, the technology is ready today. Put another way, if we paused innovation at the foundation model layer, we would still have, I think, trillions of dollars of value in the economy with current technology. Okay. I have so many more questions to ask. We have 20 minutes left, so let's take a break, and we're going to come back right after this. Fiscally responsible, financial geniuses, monetary magicians. These are things people say about drivers who switch their car insurance to Progressive and save hundreds.

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42:35And we're here with Brett Taylor. He's the CEO of Sierra, chair of OpenAI. Interesting thing you said before the break, Brett, that Cigna, I think, rolled out in what, a couple of months with you guys. There is a whole industry of consultants that integrate systems and are basically connecting business processes, and they take a year, and they usually do it like 50 % effective. What's going to happen to consultants in this world? Consultants is a broad category. You have strategic management consultants, you have systems integrators, you have outsourcing firms that essentially can build software on your behalf.

43:20I think all of them will have different impacts on this technology. The first principles view I have is software engineering agents are bringing down the cost of developing software. It's not going to go to zero, but it's going from extremely expensive to relatively inexpensive. And that's a huge change. And so where you had a dynamic where a company was outsourcing software development to save costs, the cost of the AI agent might be less than the cost of the outsourced, I'll say resource even, so it's somewhat a dehumanizing term, but often the term used in the industry. And that will disrupt that part of the industry.

43:59But behind every technology project is a business transformation. If you're digitizing part of your business, the software is a means to the end, not the end to itself. And I think most consultants would say the change management that they participate in, the actual advice on how to do that and how to be competitive has always been the more valuable part of what they do. So I think a lot of these consulting firms will probably need to transition away from the billable hours of the hands on the keyboard and more towards change management, strategic consulting. And I think that will have some innate value.

44:36I think having an outside-in perspective is inherently valuable, I think, for a management team. So I don't think it's going to go away. But what is it that you're buying for them and how they provide it, I think, probably will change a lot. And by the way, as we also started, the software industry is also changing a lot. And so there's a lot of unknowns right now. But I think it's going to skew towards higher and higher leverage types of consulting, just given the commoditization of producing software, which is obviously happening with AI. Okay, so you're the chair of OpenAI. I want to talk a little bit about OpenAI and also like the broader foundational technology underneath.

45:15First of all, they just decided that they're going to start showing ads. I think the funniest tweet that I saw in response to this was like, AGI is nowhere close because if OpenAI thinks that they have to show you ads as opposed to like, you know, redevelop the way the world works, then it's going to be a while. What's your response to that? So if you look at OpenAI's business model, kind of three pillars. The first is ChatGPT, monetized through subscriptions today. And this is where Fiji announced sort of the ads principles where the plans are to introduce some monetization component to that.

45:53Then you have the API, which companies are using to essentially build applications on top of these models. And then you have agents, which probably the most meaningful of that is Codex, which is a software engineering agent. I'm excited about developing all of those business models because, as has been covered by many people, the cost of training these models and the cost of inference is incredibly high. And so to really make open AI sustainable towards our mission to ensure that artificial general intelligence benefits humanity, we need a sustainable business. And that really means monetizing the incredibly intelligent asset that we're producing, which is these models.

46:33I also, having been at a number of companies, both Google and Facebook, that effectively develop ads platforms, I think it's quite complementary to these free offerings. I was at Google when we launched AdWords. And the before and after of the monetization for the internet was strictly better on the other side of it. Because the ads complemented what you search for. And it actually provided a lot of value to consumers. So I think there's always an art form because you just can't reduce trust. You need the chat GBTGV agent acting on your behalf. And I'm confident the team can do it in a way that complements that experience rather than competes with it.

47:12and I'm excited for the opportunity. But the argument that if there were real great economic value on the other side of the rainbow, that ads would be unnecessary? I don't buy that just because it's unclear. Just because OpenAI is making this technology doesn't mean we're monetizing all the benefits to the economy either. I was just reading, I don't know if this is true, but I just was reading on acts that a mathematician proved one of the unproven conjectures using GBT 5.2. I hope it's true. I haven't personally verified it. That's amazing. That is progress for humanity, but it's not like, you know, send us the commission.

47:49I don't think there was a commission on it. And so the mission hasn't changed. And I think this is just a way of, you know, growing the OpenAI business so we can continue to finance what I think is the greatest research lab in the world. Okay. And let's talk about that research. So OpenAI spending a lot of money. We won't get into the ROI discussion. I feel like that's been, we've had that on this show a lot, But I want to talk a little bit about what the argument would be for this technology starting to slow down. A year ago, there was a discussion about whether the models were going to hit a wall.

48:22Clearly, they haven't hit a wall. But you could argue that they're getting better through tricks. For instance, a model can learn something by going to the Internet and searching for it. But that doesn't get baked into the core of the model. So it's using these tricks, or some people call it scaffolding, orchestration to get most of these improvements. And it's not like the underlying technology is getting that much faster. That's the argument. And so then maybe eventually the tricks will run out. What do you think about that? First of all, I think all criticism is important to listen to if you're in science and you want to make progress.

49:03my take first of all i think there's a one of the nuanced aspects of the progress we've seen particularly this past year is um the models have gotten a lot more intelligent they may have been sufficiently intelligent like a year ago for most consumer applications like my trip planning to copenhagen i'm not sure how much the reasoning capabilities of gpt52 would have benefited that trip planning we were at peak travel agent i'm being a little facetious here but if you're using Yeah, but if you're using codecs to write software for you, the difference between GPT-5 and GPT-5.2 was huge. And you can see this online, just all the developers using it, because reasoning capabilities for authoring complex software is incredibly valuable.

49:49So I think one of the dynamics that's sort of playing out, particularly for people using ChatGPT and Gemini for, I'll say, casual, everyday use, which most of us are at this point, is a lot of the model improvements are not necessarily visible for those class of applications, but incredibly visible if you're using it to, say, develop software or to prove an unproven math conjecture. So that's an interesting dynamic, which is, and I think it's going to probably over the next few years amplify, which is for a given task, the models from last year are sufficient. and the new models will be necessary to achieve some semblance of super intelligence or artificial general intelligence.

50:30But we're actually at sufficient intelligence for a lot of different applications. And I think that's why it's really important when we're judging progress and cost and all these things that we'll actually probably have to start looking at it through the lens of applications. If you're doing pharmaceutical therapy discovery, you probably care a lot about the reasoning capabilities. If you're planning a trip, a little less so. To your point on accessing tools, I actually think this is strictly a positive. I think that one of the big breakthroughs with AI agents will be long-running tasks. And I think that using writing code, searching the internet, I think is great.

51:10I think it enables, whatever your training process is, the internet changes on a second-by-second basis. And having an AI agent that can respond to that is very important. But more importantly, it can access a private database, it can access a structure, it can access a system that's looking at a particular strand of DNA, whatever you might want to do. So Tullios is incredibly important. Probably the one thing that I think in AI circles, and I'm not an AI researcher though, is to achieve true AGI, will we need reinforcement learning from the observations that this model makes, which most of the mainstream models don't do?

51:49I'm not sure about that, and there's a really healthy debate about that. But I don't characterize this tool use as like a hack. I think it's actually a structural input to long-running agents, which will probably be what we need to to create something close to AGI. Okay. So we've talked a little bit about your personal history. I just want to end here with a bit of a lightning round where we can talk about some of the leaders in the tech world that you've worked with. They're going to be big names that a lot of our audience will know. Just give us one thing that you've learned from each. And I want to start with Mark Benioff.

52:27Mark was amazing at creating an ecosystem and a community around a company. I was really inspired by my first dream force and just seeing all the people that showed up there and realizing there's a difference between having customers and having a community. And that's definitely something I took away from him. All right, Mark Zuckerberg. Mark Zuckerberg was probably the longest term thinker I ever worked with. We used to go on long walks around Palo Alto talking about strategy and every time I thought I was thinking long term he was thinking about two times longer than me and I've tried to model that now it's like am I thinking long term enough and I think you can see it in just Facebook and Meta's performance over the past decade like he's always looking at the horizon beyond the horizon, which I deeply admire.

53:18Speaking of Zuckerberg's long-term thinking, do you think this big bet that they're making on artificial intelligence, right? I mean, they've poached many of the top engineers from the company that you're the board chair of. Do you think that's his belief that we are going to stop communicating with our human friends online and we'll start communicating with our digital friends instead? I think we're going to be communicating with our friends for a long time. I think this is just, I mean, Mark has a lot of conviction and is willing to put his money where his mouth is. And I think that's a real admirable trait for a CEO.

53:49So I think that's all it is. I don't think it's an indictment on human relationships. Oh, okay. I will take the other side of that. Yeah, really. I think we are, many of us are, I mean, we have this like, isn't it interesting? We have this loneliness crisis and into the void is coming these bots that will tell you how great you are, remember everything about you, look out for your best interests. I actually am worried about sycophantic AI. I think it is. Some of the science, I guess, has been partially debunked, but I like the anxious generation and it resonated with me, just the negative impact of smartphones and social media, particularly on young people.

54:27And I think with any of these new technologies, there's a risk of addictiveness and, you know, particularly the sort of sycophantic nature of some of these agents. But I'm an optimist. I think technology broadly moves society forward and can unburden us from repetitive and medial tasks and enable us to be more self-actualized. So I do think it's important to worry about, but I also think it's wrong to think it's an existential risk. And I think we should worry about it, mitigate those risks, be smart with our kids, and particularly kids in middle school and secondary school, about when they get access to technology.

55:04But I'm really optimistic for the benefits. Sam Altman you've spent some time with him as the board chair of open AI how does he operate what have you learned from him Sam probably has the most ambitious vision of any founder that I've worked with and his superpower is aligning people to that vision I was didn't have the good fortune of really knowing Steve Jobs that they always talked about the reality distortion field and why so many great engineers went and did great things like creating the Macintosh or creating the iPod. And I see a lot of that in Sam. And what is his grand plan for open AI?

55:39What is the long-term potential there? To build AGI and ensure that it benefits humanity. And it's always been the mission of the foundation, and it still is. But that sentence obfuscates a lot of the challenges of doing so. Just look at even the capital requirements to do so, which I don't think anyone knew when it was founded. So I think the hard part Sam's doing now is taking that vision and mapping out a decade-long plan to get there, which is, I think, one of the most remarkable technical achievements in human history. And it's exciting to be a part of it. One interesting dynamic of that business and Sam's challenge is, it does seem that everybody just catches up real quick.

56:26you know i it's absolutely right i mean there's just uh what i see going on right now uh sort of maybe ending where we started when i graduated from university i was in stanford when the dot com bubble happened and then it burst in the middle of my undergraduate education if you look at that period of the internet most people knew that the internet was going to be impactful and most people even knew the key applications like e-commerce and search that would be impactful. And it was this cutthroat competition to decide who would win in those markets. If you remember AltaVista, which is sort of the number one surge.

57:02I was a big user. Yeah. And then you had Yahoo and Excite as the portals. And you had... Lycos. Buy.com, Lycos. You had Buy.com and Amazon. And every country had their own. I think we're just in a similar state right now. You don't need to have a PhD in artificial intelligence to think and say, wow, this is going to have a big impact on the economy and society. So you have all of the capital, all the smart people in the world all focused on the same thing. So this degree of competition is completely, in my opinion, expected. It means it's super stressful for those of us in the middle of it. It's great for the world, though.

57:39I mean, competition drives innovation. It lowers costs. So I think it's just a great thing. For those of us in the middle, we don't get a lot of sleep because every day you wake up and there's new competition. but that's what's great about the free market technology economy is the other side of this is I think we're going to have some amazing tools that benefit humanity and I'm excited to be a part of it. But a lot of those early pioneers fell off. 100%. That's just the way it works. I think there will be a period of consolidation. Well, that's also my joke. Your perspective on the dot-com bubble is very different if you went all in on buy.com versus Amazon.com.

58:16and so you're going to have some companies go out of business I think more likely sort of be consolidated I think there's probably, I don't say too much capital but it's sort of being applied blindly to categories It's absolutely a bubble but I think it doesn't mean that there's not truly generational companies being created at the same time and I think both are true at the same time and that's why venture capital is up for the week of art and you're going to see some people do very poorly and some people writing their proverbial book about the great bets they made. And, you know, that's the world I grew up in.

58:51And I think it's exciting, though, mildly stressful at times. Yeah. What about Marissa Meyer? Marissa was my first boss. I probably learned the importance of people in hiring. I came in through a program she made at Google called the Associate Product Manager Program, where she hired new grads that have technical degrees and who wanted to become product managers. And she said, rather than getting an MBA, get an MBA at Google. And a lot of the young people she recruited there ended up running big parts of Google, running companies now. But she spent just a lot of her time curating the people at Google.

59:24I think it was one of her greatest contributions to that company. And I always remind myself, you know, it's like eating your vegetables. If you want your company to be great two years from now, focusing on the people you're bringing in now is probably the smartest thing. And I always think about her when I do that. Sheryl Sandberg?

59:42Sheryl, this is going to sound funny. Cheryl always gave me the harshest, best feedback. She was like, whoa, we're not cutting to the chase here, are we? And I realized that so much of my career hadn't been really given feedback. And if someone actually cares about you, their willingness to actually tell you what you need to hear, not what you want to hear, is a gift. And so I think it's very hard to give feedback because you think about the way it will make someone feel rather than thinking about you want them to be better at their career in the future. So I learned that from her, and she's amazing.

1:00:19I think she's a mentor to half of Silicon Valley for a reason. Do we put Larry and Sergey together? I feel like people just say Larry Sergey. We'll put Larry and Sergey together. Larry, for me, always focused on long-term technology direction in a way that was remarkable. When I got to Google, I had no idea why we were building our own data centers, and it turned out to be an incredibly important part of the cost to serve of Google. When we were making everything from Google Maps to App Engine, which became Google Cloud, his focus on setting it up architecturally to have unfair advantages of scale was remarkable.

1:00:59Just an incredibly long-term technical view. I have this for you. I'm just going to ask you. What's your opinion of Elon Musk after your interactions with him? Probably the greatest entrepreneur of our time. I mean, he's a company, he's created everything from SpaceX and look at the impact of Starlink, let alone Tesla and X. So, you know, had some complicated interactions, but sort of the undisputed leader in that respect. Did he make a good choice buying X? I'm not very close to it, so I haven't really followed it as much since the transaction went through, so I don't have a strong opinion on it.

1:01:37Okay. I have learned not to ask people in your position to predict the next five years, but can you tell us what's going to happen over the next year? I think we will see a set of things like that math conjecture that's proven where society outside of the realm of my social circle starts to acknowledge the impact that AI is going to have on science. And I think that will, in a good way, change the positive perception of AI when we realize this can help perhaps over time discover cures to uncured diseases, make breakthroughs in physics, clean energy, battery storage, where we'll get out of the discussion of AI as a chatbot and the discussion of AI as something that's going to move society forward.

1:02:27I'm really looking forward to that. Well, Brett, it's great that you came down here. This is our first conversation. I've been looking forward to it for a long time and I hope it's not our last. So thanks again. Thanks for having me. All right, everybody. Thank you for listening and watching. And thank you to Qualcomm for having us here at your space at Davos. We'll see you next time on Big Technology Podcast. Awesome. Thank you so much. Great stuff. Thanks, everybody.

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