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- [00:00]
A
OpenAI board chair and Sierra CEO Brett Taylor joins us to talk about how AI is changing software, whether the technology can push past its limits, and to share some lessons from the world's top tech leaders. That's coming up right after this. This episode is brought to you by Qualcomm. Qualcomm is bringing intelligent computing everywhere. At every technological inflection point. Qualcomm has been a trusted partner helping the world tackle its most important challenges. Qualcomm's leading edge AI, high performance, low power computing and unrivaled connectivity solutions have the power to build new ecosystems, transform industries and improve the way we all experience the world. Can AI's most valuable use be in the industrial setting? I've been thinking about this question more and more after visiting IFS Industrial X Unleashed event in New York City and getting a chance to speak with IFS CEO Mark Muffett team. To give a clear example, Muffet told me that IFS is sending Boston Dynamics spot robots out for inspection, bringing that data back to the IFS nerve center, which then, with the assistance of large language models, can assign the right technician to examine areas that need attending. It's a fascinating frontier of the technology and I'm thankful to my partners at IFS for opening my eyes to it. To learn more, go to ifs.com that's ifs.com welcome to Big Technology Podcast, a show for cool headed and nuanced conversation of the tech world and beyond. We have a great show for you today. We're going to talk about how AI is changing software with Brett Taylor, the CEO of Sierra. For those of you who don't know Sierra, it was founded in 2023. It is an AI customer engagement platform. It's doing 100 million in annual recurring revenue. 50% of its customers have revenue of more than 1 billion and 20% of its customers have revenue of More than 10 billion.
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B
So.
- [01:52]
A
So it's right at the center of everything happening in AI. And Brett is the perfect guest to discuss with us about how AI is changing software and where it's all gonna lead, what the future of the graphical user interface is, what the future of user interaction is. And of course we're here at Qualcomm Space at Davos to break it all down. Brett, great to see you. Welcome to the show.
- [02:12]
B
Thanks for having me.
- [02:14]
A
Okay, so I wanna speak with you first about the way that AI is changing software, about Vibe coding and whether we should buy into the hype. Let me just talk to you about two stories that came across my feed over the past day. Dave Clark, the former worldwide consumer CEO at Amazon, just wrote on LinkedIn, between last night and today, I built a custom CRM that actually fits how we sell. We tried configuring an off the shelf CRM for our sales cycle. There are too many fields we don't need, we're missing the ones that we do need. It forces a pipeline flow that doesn't match reality and and we spend more time fighting the tool than using it. So I built what we needed. It took a night and a morning. I had another connection on LinkedIn. Tell me. Over the past two months I rebuilt my company's business, the non engineering parts of it, the processes, using Claude code, and I've never felt more empowered. I'm trying to figure out whether all these stories of people building their own custom software actually will actually will lead to the change that many of them are promising, or whether there's actual meat behind this. Is Dave Clark's CRM going to fall apart in a week and it was just a nice post for LinkedIn engagement, or is something real actually happening here?
- [03:35]
B
I'm quite optimistic about this trend. I actually think the term Vibe coding will be like information superhighway, where it's a term we don't use in the future because the idea that your software is something that you can change yourself will be something we expect rather than a novel concept. I have two things that sound contradictory, but I don't think they are. So first is most of the cost of software is in maintaining it, not building it. And that's why most people would prefer to buy a solution off the shelf. Because you want to amortize the cost of maintaining software among thousands of clients and not have everyone bear it. Just think your ERP system and a new accounting standard comes out. If every company in the world has to go Vibe code that new accounting standard, someone's going to get it wrong.
- [04:20]
A
Hold on, I've heard this before, but won't the AI just be like, okay, I'm picking that out of the Internet, that's the new standard Now I put it in.
- [04:27]
B
It may, but I think the bigger point I was going to make is right now I think we're just imagining vibe coding our existing solutions. If you think of something like a CRM, it's a bunch of forms and fields in a web browser. I'm not sure that's even the future of software. The future of software is agents. So rather than having a web browser with forms and fields that we click on we will delegate tasks to agents that will operate against a database somewhat autonomously. So I think the interesting thing is, I think everyone's looking at all the software used and say, how fast could I vibe code that I wonder if it's the wrong question, because I actually think the more disruptive thing happening to software is the software used today. When will not be the software we use tomorrow. The form factor will be different, the business models will be different, the consumption patterns will be different. If you're generating leads and opportunities for your sales team, an agent will do that. If you're essentially auditing your financials and your ERP system, an AI agent will do that. Who's making those agents is the question. And will you buy those agents off the shelf or build them yourself? And I think that's still an open question. Whether you can vibe code a CRUD app in a web browser, I think is maybe an interesting question on Twitter, but I don't think it's the most interesting question in software.
- [05:37]
A
All right, let's just unpack this a bit. So a CRM or customer relationship management technology, if you have one of those software tools that goes from the graphic user user graphical user interface to a chatbot, what does the interaction look like? And isn't it valuable to have. I mean, not to stand up for dashboards, but isn't it valuable to have those dashboards where you can basically see what's going on, as opposed to have to type into a chatbot what's going on? I don't fully see how chat and agents can replace the software stack that exists today.
- [06:16]
B
The word agent comes from agency, and it just means AI has some ability to autonomously reason and make decisions. And so it doesn't mean the concept of a dashboard will go away, but perhaps everyone at your organization will have a different dashboard. Your head of sales, your head of sales operations, the CEO, probably all have very different things they're interested in. So. So every morning, that agent might reach out to you and give you just the information you need. It's a new form of dashboard. Right. But it's custom for every individual. And the form factor of the software underneath is actually very different. Because if you think about what it means to craft a dashboard, it's a lot of, like, database joins and things like that. If you think about giving an AI access to all the information it needs to give you personal insights, it's very, very, very different. And I think that's why, whether it's the birth of the web browser or the smartphone or now large language models and AI. It's a disruptive moment in technology because the incumbent software players, their advantages, all of a sudden start to look a little bit like disadvantages. And it doesn't mean they won't all pivot, by the way, but it opens the door for, I'll say, AI native companies who are building software sort of native to that form factor. So I do think it will change. I think the importance of dashboards will go down. A point of a dashboard is so a human can stare at it and derive some insight. I think that probably AI can serve a very meaningful role in deriving insights from your data. And if staring at a bunch of colorful lines on a screen is the best we have, I'm not sure that's true. It doesn't mean all dashboards are going away, but you have to imagine that these AI agents are becoming progressively more intelligent than you. And if you're not relying on it to help find insights in that data that you were previously staring at in a dashboard, your competitors probably are. So I think a lot is going to change. And I think the interesting thing in Silicon Valley, as you said, I've been in this industry for a couple decades, is it's a race. The incumbents need to transform themselves. The disruptors or insurgents or whatever term you want to use, are trying to compete to create AI native applications in each of these areas. Will the insurgents and upstarts becoming the incumbents before the incumbents transform themselves? And I don't think it's a foregone conclusion for any one of the incumbents, but I think it's a really fun time to be in this industry.
- [08:35]
A
All right, so as the words were coming out of my mouth, I was saying, I can't believe I'm standing up for dashboards. And just note to self when I'm doing podcasts, I'm not going to stand up for dashboards anymore. Terrible decision. I hear you on that front. But let's talk a little bit then about the disruptive power to today's incumbents. Right, so you talked a little bit about how businesses might disrupt other businesses. I think there's a belief now that it's individuals with these tools are going to be able to build their own instances, and that will be the threat to incumbent software platforms. So reading between the lines of what you just said, I don't think you really believe that it is going to be an individual building their own custom technology. You still think that companies need to be able to do this?
- [09:21]
B
It may be true. It's interesting. I think it's very hard to predict the second order effects of the marginal cost of software development going down so dramatically. But it's interesting. For our first customer conference at Sierra, I was doing research and I was looking up in the Wayback Machine old wire articles and I found one from I think it was 1997. And the article was about banks failing to launch websites with login forms and spending tens of millions of dollars with consulting companies and how hard it was to go from read only to enabling someone to log in to check their balance. It's trivial now. You could vibe code that probably during the course of this podcast. Yet most people, when they're starting a commerce storefront, don't start from scratch. They go to Shopify. Why is that? Well, making a website was incredibly difficult in 1994. Something like a Shopify just adds more and more capabilities. Maybe it helps you with fulfillment. Maybe it integrates all the other systems you use for delivery CRM. Maybe it helps you acquire ads to drive traffic to each of your listings. I think as AI becomes easier to make, you just make software that's more and more high leverage and more and more valuable. And at the end of the day, most companies aren't software companies. Dave Clark is one of the great technologists of the world and grew up at Amazon and understands software deeply. If you're a CPG company, do you have that kind of skill at your organization? Maybe you do, maybe you don't. But I think at the end of the day most companies don't want to be software companies. They want to buy solutions to their problems and if there's an opportunity to do that, I think it's actually smart. I don't think you should be in the business of maintaining software if that's not the core of what you do. And I think that's true of most businesses. Just to give you an example in tech, when I started my first company, we built our own servers and put them in a colocation facility. Now we have no data centers, we just use the cloud like every other startup in the world. It's an entire department that isn't at our company and it means we can be more self actualized in what we do. I think the same should be true of most companies. So I'm hopeful that actually in the future the form factor of acquiring software will be acquiring agents. There will be, I believe, a different business model which is outcomes based pricing rather than just paying for the privilege of using that software. And I think there will still be software companies in the future. I may be wrong. I just think right now we lack the imagination to imagine what this software does. And we're just projecting all this technology through the lens of what we currently use, which is not what we will be using in the future.
- [11:52]
A
So the market, if you look at the index funds, the market has dropped software like 10% this year, software bundles. Is that the market misunderstanding what's happening? Because basically it's been in reaction to cloud code and cloud cowork. So is it the market misunderstanding what's happening? Or is the market seeing the seed of something which is that there is something big changing in software and if people can do this in their backyards or in their basements as easily as it's taken, you know, companies years to build, then there's going to be a shift somewhere.
- [12:26]
B
I think the stock market wonders. It's sort of funny to talk about the stock market as a person, but.
- [12:32]
A
The market, we're talking about chatbots as people. So let's.
- [12:35]
B
That's great. Well, let's anthropomorphize both. I think the stock market doesn't know which of those incumbents will make the transition. And I think that's what the market is unsure about. And you know, I think it's interesting if you look at the multiples on AI stocks and we can debate what that is versus software stocks, it's the haves and have nots. Right. And I think it's largely the market's wondering which of these companies will make the transition. If you look back at the transition to the cloud, you know, Microsoft went through fits and starts, but it eventually came out quite strong. But it wasn't obvious for a period that they were companies like Siebel Systems, which most of your listeners may not even remember, but that was the number one CRM before Salesforce existed, did not make the transition. And I think if you look at all the incumbent platforms out there, my strong intuition is people are saying, yeah, there's a, there's a play there. These are strong companies, you know, will they actually pivot? I think the interesting, maybe counterintuitive point that I would make is I think business model transitions are harder than technology transitions. I think it was harder for most on premises software companies to move to ratable subscription revenue than it was to necessarily make something that ran in a web browser. It's a very different business model. Revenue recognition, even sales cycle from selling Windows 95 and then Windows 98 to just have an always on system. I would argue that actually I think agents will go the way of outcomes based pricing. Where for example, at Cira we charge per resolved case for our customer service agents. I think if you made an agent to audit your financials, you should pay per audit. That's a very different form factor as well. I think companies going through these transitions have to disrupt their technology stack to disrupt their business model. It may even mean that the revenue dips for a period as they come back out. And any public company CEO will tell you that's easier said than done. And so I think that will actually be one of the more interesting stories in 10 years when we look back and say who made the transition and who didn't.
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A
All right, let's end this talking about one of your former employers. You were the co CEO of Salesforce. We started talking about CRM. So let's end this segment talking about CRM. Obviously Salesforce is a place where salespeople log, there's a call information and then their leaders can see how they're doing and judge the pipeline and you know, make predictions on the quarter. Does Salesforce become a chatbot or what is the future of a company like that?
- [15:05]
B
Well, Salesforce is first of all Mark's a great leader. So you're going to pick like companies who can make the transition, founder led, great leaders. So never count him out at all. It's also a multi product company. The largest product in Salesforce's portfolio, at least when I was there was Salesforce Service Cloud, they bought Slack, Tableau, Mulesoft. And so I think if you think about Salesforce as just managing leads and opportunities, it's probably too narrow. And so you know, Salesforce has all this, these assets and the question is what is the quote unquote agentic manifestation of the value proposition they provide. And you know, I'm not close enough to them anymore to really say black and white, but they have a lot of great assets, great leadership to do it. Right.
- [15:47]
A
But that distance is valuable because you can give us like some perspective on what you think a company like that will look like.
- [15:53]
B
Well, I mean it's the same of all whether it's ServiceNow, SAP, Salesforce, Adobe, you have to say there's a framework from Clayton Christensen who wrote this book competing against luck called Jobs to be Done. What job does your customer hire the software to do? And it's not to edit a field in a database, it's to generate leads, it's to manage pipeline, it's whatever it is. And if you imagine that job through the lens of an AI agent, What is the purest form of that technology? I'm not sure I know the answers to all those questions because it hasn't been my job to think about it anymore. And I've been working on Sierra, but that's the question is, can you make that transition as a value proposition and then say, what is the business model for that new value proposition? And as I said, it's a race because for each of everything I said, I guarantee there's five startups trying to compete for that right now as well. And it's a question of the classic innovator's dilemma.
- [16:47]
A
So taking a step back, we've been talking about enterprise, by the way. Very interesting what's happening to enterprise. So I think it's worth spending the time talking about it. But let's take a step back and talk about consumer for a moment. If the Internet was to just start up today from scratch and knowing that we have conversational AI and large language models, what does it look like? Do we have a Facebook and an Amazon and a Google, or is it everything just mediated by a chatbot? What does the Internet look like if it just starts from zero today?
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B
It's hard for me to imagine starting from zero today because so much of what we have in ChatGPT was a byproduct of the Internet existing.
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A
But for the sake of this thought exercise, we're just burning it down and.
- [17:29]
B
Starting burning it down and starting from scratch. So first I'll say, I think when I was in college, when I started college, the front door to the Internet were portals, so Yahoo and Excite and the like. And it was sort of a quaint time. You could list every website that was worth reading in a directory like the Yellow Pages very quickly. I think Google launched in 1998 and then sort of became took over on Stanford campus. And then by the early 2000s, most people were googling things and portals didn't go away, but were no longer the front door for most people's experiences. I think ChatGPT is already the front door for the Internet for many people. And I would say if you look at like ChatGPT, Gemini and the like, I think your personal AI agent will be your front door to the Internet. And I say that to answer your question because I think it really changes the way you use the Internet. Rather than getting 10 blue links and clicking on them, you might delegate some of that responsibility to your agent. Maybe. When I planned my family vacation to Copenhagen last year, ChatGPT did almost all the research for me. And so it really changes your relationship because it changed your relationship with all the content that ChatGPT looked at. I didn't end up booking Airbnb, but I probably would have if was it, if it had let me. So I think we're moving from a world of just clicking on links to companies having agents. This is what Cira does. We help companies like Cigna and SiriusXM DirecTV make AI. Agents can talk to their customers and consumers over the next three or four years will have their own agents. And that's a very huge change because I think it's quite personal. But what will you delegate to your agent? You know, some things you'll probably care a lot about, some things you may say, hey, just go book that hotel for me on my business trip. If you're going on a family vacation, you might spend a little more time looking at the listings. But in those moments where you're delegating basically decision making to your agent, it really changes a lot of the mechanics and economics of the Internet. SEO, SEM, all these things that have been awesome, optimized towards persuasion of humans. All of a sudden we're in this brand new world. So I think the Internet's going to change a lot. I think it's largely going to be very consumer friendly just because we can accomplish more with less thanks to the prevalence of agents. But it will change pricing strategies, marketing strategies, discovery in ways that I can leave someone sort of in the middle of it. I can't quite predict right now, but you can sort of see the change coming even if you don't see the end of it.
- [20:09]
A
So much of the web and so much of the Internet is premised on us visiting things, publications, if you have to visit them, that's the way the economics work. Site like Amazon, right, that you want, they want you to visit because they get the data and then they can tailor the experience to you. If you're not visiting sites anymore, then does the math fall apart? How does it work?
- [20:33]
B
I think business models will change with technology. You know, I think the advertising supported Internet was a byproduct of the distribution of the Internet, where a lot of companies said, hey, rather than having a payment as a gate to content, providing it for free and providing ads is a better business model. Not all publications made that trade. In fact, somewhat interesting enough. Many of the healthiest publications didn't, which is interesting. I think certainly AI agents and consumer agents will drive similar changes to business models. I'm not sure what they are yet to be Honest with you, I still think fundamentally it's a market where people, it's like demand generation, demand fulfillment. It's essentially finding people who might in the future be interested in your product and making sure they're aware of you. This is largely happening on TikTok and Instagram and Facebook today. Demand fulfillment, which is largely happening on Google and Amazon today. With the prevalence of agents. What is the new world of demand generation? How do you make your products known to you, but also maybe to your agent, which is a funny thing to say. And then when you are actually transacting what is sort of the paid equivalent of that. And I think both of those are nascent. I don't think we know what they are, but I think the, the economy, or like I'll say the digital economy will be fine. It's going to change things. It's just going to make things that used to be really profitable less so. But I think just like the, whether it was the advent of the Internet or the news feed, this is not even the fourth time over the past decade that there has been changes to that economy. And I think entrepreneurs and innovators will figure it out and I think it'll be great. I just don't know exactly what it will look like. Yeah, yeah.
- [22:18]
A
I'm struck hearing your answers that A, you think a lot will change and B, it's still so uncertain what will actually change.
- [22:24]
B
We are inning two of this nine inning game. Yeah. In my opinion.
- [22:29]
A
So actually you've been playing well. You've been playing, let's say it's a doubleheader. You were definitely on the field for the first nine innings of, of the last, the last game. Because you know, if you look through Internet history, you've just been at the center of so many of these really important moments. You know, it's amazing. I keep seeing the name Brett Taylor whenever there's a big news story. So it's great to be able to speak with you. Just for our audience and I'm sure many of them know this. You were the Twitter board board chair during the sale to Elon Musk. You became the OpenAI board chair upon Sam Altman's return after he was fired. Over that weekend, you were the co CEO of Salesforce with Marc Benioff like we spoke about. You were the Facebook CTO as the company moved to mobile and you built Google Maps. So let's just introduce you to our audience on this one. How did you end up in the middle of so much tech history?
- [23:22]
B
Glutton for Punishment? No, I'm just kidding. One of my favorite quotes is attributed to Alan Kay, and I haven't actually verified it from him. Alan Kay was a researcher at Xerox parc and he said the best way to predict the future is to invent it. And I love it just because I think it captures the mix of optimism and I'd say this sort of imperative, I feel, when there's a really compelling new technology, to get my hands on it and help shape it, as opposed to observe it passively from the sidelines. And it's interesting you talk about those different trends because I started my career at Google, went through both social and mobile at Facebook, and then learned enterprise software at Salesforce. At Cira, we help companies build AI agents for their customer experience. So think not having to wait on hold when you call up Sirius XM or even helping people refinance their home with a rocket mortgage agent, part of our value proposition actually reflects that history. We say if it were like 1994, we'd be telling everyone why they needed a website. And if it were 2015, I guess I'd say, here's why. You should have a mobile application. And now it's 2026. And we say you need an AI agent. And your AI agent is going to be your digital front door. And most of your customer interactions will happen via your AI agent, not by from your mobile app or your website, even if they exist in those platforms. And so it's really interesting just because my own personal history is sort of tied up with what I'm doing now. But it's so interesting because if you look at, I love the history of computers, and I think Microsoft's mission at one point was to put a PC on every desktop. I think we only reached about 2 billion PCs, so certainly maybe reached that mission in the Western world, but certainly not in the developed world. Then the Internet was developed and connected those PCs, and then thanks to Steve Jobs, and then obviously Android's evolution of that technology, we have more smartphones than people now. And they're all connected to the Internet, but they're all building on top of one another. The smartphone would not have been the smartphone without the Internet, and the Internet wouldn't have existed without the PC. And now you have AI and it's building on top of all of those. And so what's so interesting about this, at least the way you articulated my career, is it feels like this sense of acceleration, like each of these new waves of technology is adopted seemingly five or ten 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 the show just. I've never felt a pace of change more rapid than the moment right now for you.
- [25:57]
A
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 happened, 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. I don't want to put my whole, you know, 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.
- [26:29]
B
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.
- [26:40]
A
Nice job.
- [26:41]
B
Why? The dot com bubble had burst. So the job fair was like a bunch of tumbleweed and Microsoft and Google. And I was like, I'd prefer Google. And I knew Marissa Meyer who had gone to work there. So just say dumb luck. But it wasn't exactly. I always wonder, if I had started my career in 1999, would I have been@pets.com I hope not, But I don't know. I did have the. I just graduated at the right time.
- [27:03]
A
I just want to say we've done two shows at this space, and that's the second pets.com reference we've.
- [27:07]
B
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. I 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. I've done this with a few different technologies that I was skeptical about, and I'd find a fellow entrepreneur that was really bullish on it. And I'd say, I want to understand what you see. And I say that just because not every hyped technology is worth the hype. But usually if smart people are interested in it, there's usually something really important that they see. And 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.
- [28:18]
A
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?
- [28:35]
B
Not at all, really. I like to do the thought exercise. So the United States was founded in 1776. At 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 imagine taking. I don't know who the most tech savvy founding father was, but Benjamin Franklin maybe, I don't know. And if he were teleported right here in between us, first of all, that would be a little cool. But secondly, 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 we often see new technologies and see what it displaces that we currently do. But we create an economy and a culture around our technology, not the other way around. And so in those past 300 years or something, we've made power relatively abundant, we've made food abundant, we've made transportation relatively abundant. And just think about the fact that both of us flew here on airplanes 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. And 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 four years ago. But I'm excited for that because I'm excited for the progress it means for humanity.
- [30:41]
A
All 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 Sirius xm will actually have your, your platform take action. Right, so this is not chatbot. I think this is important to say. This is not chatbot. It's agentic. It's agents. It's. 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.
- [31:31]
B
And by the way, that AI agent's sending a signal up to a satellite in space, which is communicating with your car. Who 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.
- [31:45]
A
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, 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. And 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?
- [32:18]
B
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 were to 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 years of our life waiting on hold, and the Reason for it is somewhat like a mix of business and technical. Until recently, the phone line was analog, so there 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, would people be sitting around most of the time doing nothing, which just cost 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. You 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 Deliveroo, it can help you whether you're driver or 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. One 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.
- [34:34]
A
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. They'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 about that. How have you gotten them to trust Sierra with these actions? Because we. We all agree that the pain is real.
- [35:01]
B
Yeah. Well, so I'll start with actually an important thing to Ground ourselves, no pun intended, 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. But 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. It doesn't mean they're perfect, by the way. They're just more perfect than the very fallible human operation systems that preceded them. And 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 simulations. 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.
- [36:26]
A
Is it AI's talking to AI?
- [36:28]
B
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 for 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. 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 with AI monitors, you can monitor all conversations. So 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 has evolved over my career. In 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 life cycle, which is essentially a methodology to make software robust. We've essentially, in AI agent development, have this idea of an agent development life cycle, 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.
- [38:24]
A
Is what you're saying then that with these AI agents, 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 companies 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, if you make a couple fewer mistakes with AI, you're still doing a better job.
- [39:10]
B
I'm not sure there's a black white answer to that. I mean, certainly the reason why Cira 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, but 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 for sure it is. 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 healthcare provider in the network, of your health insurance company. AI agents can do that now. And that's why we're being pulled by the largest healthcare, 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 will be ready for it. And just take 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.
- [40:34]
A
Not if you want to stay in business.
- [40:35]
B
Yeah, exactly. Could you ask, is Vibe coding ready for production? What production application? And I think that's. 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? How 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.
- [41:28]
A
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.
- [41:35]
C
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- [42:08]
A
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- [43:39]
B
Consultants is a broad category. You know, you have strategic management consultants, you have systems integrators, you have, you know, outsourcing firms, you know, that essentially can like build software on your behalf. I 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. But 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. I 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.
- [45:39]
A
Okay, so you're the chair of OpenAI. I want to talk a little bit about OpenAI and also the broader foundational technology underneath. First 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?
- [46:09]
B
So if you look at OpenAI's business model, kind of three pillars, the first first is ChatGPT, monetized through subscriptions today. And this is where Fiji announced the ADS principles, where the plans are to introduce some monetization component to that. Then 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 am 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 OpenAI 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. I also, having been at a number of companies, both Google and Facebook, that effectively developed 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, it was strictly better on the other side of it because the ads complemented what you searched for and it actually provided actually 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 ChatGPT 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, and I'm excited for the opportunity.
- [47:47]
A
But the argument that if there were real great economic value on the other side of the rainbow, that their ads would be unnecessary.
- [47:54]
B
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. And so 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 GPT 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, send us the commission. I don't think there was a commission on it. The mission hasn't changed. And I think this is just a way of growing the OpenAI business so we can continue to finance what I think is the greatest research lab in the world.
- [48:34]
A
Okay, let's talk about that research. So OpenAI is 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. Clearly they haven't hit a wall, but you could argue that they are 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?
- [49:29]
B
First of all, I think all criticism's important to listen to if you're in science and you want to make progress. My take, first of all, I think there's one of the nuanced aspects of the progress we've seen, particularly this past year, is 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 GPT 5.2 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, well, but if you're Using Codex 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. So 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 superintelligence or artificial general intelligence. But 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. I 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 structured, 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? I'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 create something close to AGI.
- [52:39]
A
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 Marc Benioff.
- [53:00]
B
Marc was amazing at creating an ecosystem and a community around a company. I was really inspired by my first Dreamforce 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.
- [53:19]
A
All right, Mark Zuckerberg.
- [53:21]
B
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. He's always looking at the horizon, beyond the horizon, which I deeply admire.
- [53:52]
A
Speaking 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?
- [54:11]
B
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. So I think that's all it is. I don't think it's an indictment on human relationships.
- [54:26]
A
Oh, okay. I will take the other side of that. No, really, I think we are. Many of us are. 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.
- [54:43]
B
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. And I think with any of these new technologies, there's a Risk of addictiveness and 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 menial 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. But I'm really optimistic for the benefits.
- [55:41]
A
Sam Altman, you've spent some time with him as the board chair of OpenAI. How does he operate? What have you learned from him?
- [55:49]
B
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 didn't have the good fortune of really knowing Steve Jobs, but 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.
- [56:10]
A
And what is his grand plan for OpenAI? What is the long term potential there.
- [56:15]
B
To build AGI and ensure that it benefits humanity? And it's always been the mission of, 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.
- [56:52]
A
One interesting dynamic of that business and Sam's challenge is it does seem that everybody just catches up real quick.
- [57:01]
B
It's absolutely right. What I see going on right now maybe ending where we started. When I graduated from university. I was in Stanford when the dot com bubble happened and then it broke 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 sort of the number one.
- [57:35]
A
I was a big user.
- [57:36]
B
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. I mean, competition drives innovation, it lowers cost. 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 there's new competition. But that's what's great about the free market technology economy is on 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.
- [58:35]
A
But a lot of those early pioneers fell off 100%.
- [58:37]
B
That's just the way it works. I think there'll be a period of consolidation. Well, that was always my joke. Your perspective on the dot com bubble is very different. If you went all in on buy.com versus Amazon.com and so you're going to have some companies go out of business, I think more likely be consolidated. I think there's probably, I don't say too much capital, but it's been applied blindly to categories bublish. Oh, 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 isn't 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 that's the world I grew up in. And I think it's exciting, though mildly stressful at times.
- [59:27]
A
Yeah. What about Marissa Meyer?
- [59:29]
B
Marissa was my first boss. I probably learned the importance of people and hiring. I came in through a program she made at Google called the Associate Product Manager program, where she hired new grads out of 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, I think was one of her greatest contributions to that company. And I always remind myself, 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.
- [60:11]
A
Sheryl Sandberg.
- [60:14]
B
Sheryl, this is going to sound funny. Sheryl always gave me the harshest, best feedback. He 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 at it. I think she's a mentor to half of Silicon Valley for a reason.
- [60:55]
A
Do we put Larry and Sergey together? I feel like people just say Larry, Sergey.
- [60:59]
B
We 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 and was remarkable. Just incredibly long term technical view.
- [61:37]
A
I have this written down. I'm just going to ask it. What's your opinion of Elon Musk after your interactions with him?
- [61:44]
B
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 had some complicated interactions, but sort of the undisputed leader in that respect.
- [62:02]
A
Did he make a good choice buying X?
- [62:04]
B
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.
- [62:11]
A
Okay. I have learned not to ask people in your position to predict like the next five years, but can you tell us what's going to happen over the next year?
- [62:21]
B
I think we will see a set of things like that math conjecture that's proven where society outside of the realm of like 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. I'm really looking forward to that.
- [63:02]
A
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.
- [63:09]
B
Thanks for having me.
- [63:10]
A
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.