# How Sierra Is Pulling Ahead in the AI Race | Co-founder Bret Taylor

Markdown copy of https://realalpha.app/v/6v9q6k8aF6E/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

Bret Taylor argues that AI will reshape work through competition and reinvestment, not simply eliminate jobs.

- Show: Grit
- Hosts: [Joubin Mirzadegan](https://realalpha.app/people/joubin-mirzadegan/)
- Guest: [Bret Taylor](https://realalpha.app/builders/bret-taylor/) is co-founder of Sierra.
- Published: Mar 9, 2026
- Length: 1 h 13 m

## The best minutes

- [11:55](https://realalpha.app/v/6v9q6k8aF6E/?t=715) [Leaders have to test internal stories against customers](https://realalpha.app/s/leaders-have-to-test-internal-stories-against-customers/) (5 min)
- [22:35](https://realalpha.app/v/6v9q6k8aF6E/?t=1355) [Applied AI will rely on a portfolio of specialized models](https://realalpha.app/s/applied-ai-will-rely-on-a-portfolio-of-specialized-models/) (4 min)
- [32:44](https://realalpha.app/v/6v9q6k8aF6E/?t=1964) [AI's impact depends on task complexity and real-world bottlenecks](https://realalpha.app/s/ais-impact-depends-on-task-complexity-and-real-world/) (6 min)

## Also worth watching

- [52:40](https://realalpha.app/v/6v9q6k8aF6E/?t=3160) [Paid proofs of concept filter out AI tourism](https://realalpha.app/s/paid-proofs-of-concept-filter-out-ai-tourism/) (6 min)
- [48:13](https://realalpha.app/v/6v9q6k8aF6E/?t=2893) [Sierra chose financing partners over the highest valuation](https://realalpha.app/s/sierra-chose-financing-partners-over-the-highest-valuation/) (3 min)
- [38:52](https://realalpha.app/v/6v9q6k8aF6E/?t=2332) [AI gains will fuel competition as well as efficiency](https://realalpha.app/s/ai-gains-will-fuel-competition-as-well-as-efficiency/) (6 min)
- [4:05](https://realalpha.app/v/6v9q6k8aF6E/?t=245) [Sierra pairs enterprise experience with AI-native graduates](https://realalpha.app/s/sierra-pairs-enterprise-experience-with-ai-native-graduates/) (3 min)
- [17:27](https://realalpha.app/v/6v9q6k8aF6E/?t=1047) [AI is expanding contact-center demand while capital delays consolidation](https://realalpha.app/s/ai-is-expanding-contact-center-demand-while-capital-delays/) (5 min)

Skip the roughly 12-minute discussion of founder routines, fulfillment, co-founder resilience and company optimism.

## Summary

Bret Taylor co-created Google Maps at Google, served as CTO of Facebook and later co-CEO of Salesforce. He is now building AI agents for customer experience at Sierra, which he co-founded.

Taylor says Sierra is growing quickly by selling customer-service agents to large enterprises and pairing experienced enterprise operators with AI-native early-career hires. He argues that abundant capital has prolonged competition among AI companies, while demand for models is real and consolidation will likely follow. He expects AI to transform work but rejects the idea that people will stop working, saying the pace of change will vary by profession. He says Sierra’s approach combines close deployment partnerships, global presence and rapid product development with a culture of optimism and blame-free learning.

### Minute by minute

- [2:34](https://realalpha.app/v/6v9q6k8aF6E/?t=154) **Sierra is growing rapidly.** Taylor says Sierra reached $100 million in ARR in seven quarters and then had a $50 million quarter, exceeding his expectations. He says enterprises need AI agents for customer interactions, though buyers still have to choose among competing solutions.
- [4:05](https://realalpha.app/v/6v9q6k8aF6E/?t=245) **Enterprise sales need credibility.** Taylor says Sierra targeted Fortune 100 companies from the start, so it hired experienced people who understand legacy systems, regulation and enterprise operations. It pairs them with new graduates in its APX rotational program, who train as agent product managers or engineers. He says over a quarter of Sierra’s customers have more than $10 billion in revenue.
- [11:55](https://realalpha.app/v/6v9q6k8aF6E/?t=715) **Failure hides behind stories.** Taylor says people tend to claim credit for successful products and shift blame when projects fail. He recalls finding Microsoft employees optimistic about Windows Phone long after the market had settled around Android and iOS. He argues leaders need to hear directly from customers and question internal explanations of poor results.
- [16:32](https://realalpha.app/v/6v9q6k8aF6E/?t=992) **Capital keeps competition crowded.** Taylor says about $400 billion a year went to contact centers and BPOs before large language models, and lower costs could expand demand. He estimates Sierra is three or four times larger than the next player, but abundant venture capital has kept competitors in the market and their valuations make acquisitions difficult. He expects some correction and consolidation.
- [22:35](https://realalpha.app/v/6v9q6k8aF6E/?t=1355) **AI will use varied models.** Taylor says venture funding inflates company valuations and makes it easier to start competitors, but real business revenue is driving token demand. He expects falling model costs and a range of models with different trade-offs in price, latency and quality. He compares choosing models for applications to choosing among database types.
- [27:16](https://realalpha.app/v/6v9q6k8aF6E/?t=1636) **AI’s impact will vary by task.** Taylor says a market correction could follow macroeconomic changes or weak public-market receptions for AI companies, but he sees competition as useful for testing ideas. He says model improvements feel incremental for tasks that already work well, but can transform demanding work such as software engineering. He estimates that even if model development paused, existing intelligence could still unlock trillions of dollars in economic value.
- [29:55](https://realalpha.app/v/6v9q6k8aF6E/?t=1795) **People will keep finding work.** Taylor rejects the idea that automation means people will stop working, arguing that people have historically created new roles after jobs disappear. He says software and finance can absorb digital intelligence readily, while fields such as drug discovery still face wet-lab and clinical-trial constraints. He expects AI labs to move faster than many parts of society.
- [38:52](https://realalpha.app/v/6v9q6k8aF6E/?t=2332) **AI changes how firms compete.** Taylor says coding agents reached their current quality only in the past few months, so it is too early to know what company structures will work best. He argues that when competitors get access to the same AI tools, companies will use them to win market share rather than simply pass savings to shareholders. He expects competition to produce new activity and jobs.
- [44:30](https://realalpha.app/v/6v9q6k8aF6E/?t=2670) **Capital supports enterprise scale.** Taylor says Sierra wants to become the default agent partner for large enterprises, which requires customer-facing offices, product investment and scale. Mirzadegan cites a $10 billion valuation; Taylor says Sierra passed on higher valuations in each of its three rounds. He says the company models how much capital it needs to reach its next milestone and wants to avoid being undercapitalized.
- [52:40](https://realalpha.app/v/6v9q6k8aF6E/?t=3160) **Paid pilots screen for intent.** Taylor calls low-commitment AI projects AI tourism and says Sierra’s proof-of-concept work is generally paid to focus on customers serious about deployment. Sierra may help with technical integration or organizational change; one medical-device company was consolidating 40 call centers into one with AI. Taylor says Sierra aims to be accountable for deployment outcomes, not just provide software.
- [58:12](https://realalpha.app/v/6v9q6k8aF6E/?t=3492) **Taylor prioritizes customers and product.** Taylor says he works a lot because he enjoys the work, but tries to focus his time on Sierra’s product and technology and on customers. He says conversations with clients teach him about their industries and that successful solutions come from combining their expertise with Sierra’s AI. He credits co-founder Clay Bevor and the team with giving him room to focus.
- [1:01:28](https://realalpha.app/v/6v9q6k8aF6E/?t=3688) **Founding feels fulfilling, not simply fun.** Mirzadegan says building a company feels fulfilling rather than like ordinary fun, and Taylor agrees that entrepreneurship brings both meaningful moments and painful setbacks. Taylor says founders feel losses acutely and that shared wins and disappointments make the work easier to bear.
- [1:04:13](https://realalpha.app/v/6v9q6k8aF6E/?t=3853) **Shared ownership turns setbacks into learning.** Taylor says his partnership with Clay helps each founder recover when the other hits a low point. He describes Sierra’s weekly, blame-free lessons-learned reviews, which look for systems that could prevent a lost deal, candidate or production issue from recurring. He says the process pairs optimism with a clear view of what went wrong.

## Transcript

Grit, hosted by Joubin Mirzadegan, with Bret Taylor.

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[0:00](https://realalpha.app/v/6v9q6k8aF6E/?t=0) If we paused innovation and just absorbed the intelligence of all the existing models, my guess is there's still trillions of dollars of economic value we haven't realized yet, which is interesting unto itself. I'm an optimist in all of this. I just don't believe that humans will stop doing things. Success has a thousand fathers, failure is an orphan. Anytime there's a successful product at a company, everyone who's remotely adjacent to it takes credit for it. And then similarly, when a project fails, everyone deflects blame. So when I say failure is an orphan, I always think about it because every time someone tells me a story rationalizing why something happened, I'm immediately skeptical.

[0:39](https://realalpha.app/v/6v9q6k8aF6E/?t=39) And I'm almost almost seeking out the other side of that argument. But this is the hardest part of building a business is like fighting storytelling. Welcome to Grit. I'm Juven, partner at Kleiner Perkins, a show where we go beyond the highlight reel and explore the personal and professional challenges of building history-making companies. Today on the show, we have part two of Brett Taylor. I'm not sure he needs much introduction for folks that are in Silicon Valley. My personal opinion is he's one of the greatest CEOs of our generation leading what I think is one of the most interesting tech companies. Enjoy the episode.

[1:25](https://realalpha.app/v/6v9q6k8aF6E/?t=85) Good to see you. Great to see you too. Last time I saw you was- In Dallas. Twice. Yeah. How was that? Great. Was it like, you know, I've seen a lot of pretty big time CEOs come into that room. Yeah. And I've seen a lot of pretty big time CEOs. Like it's, you know, 25, it's a room of 25 CIOs each time. Yeah. The biggest CIOs in the world. And it doesn't matter how much you've prepared. It doesn't matter how many times you've done this. Was it daunting? i love it no there's these are my people and so i got a lot of energy from it and uh gotten good feedback on too like we've got a lot of clients from that so it was really um i actually it's interesting just partly because they are like i met a lot of those people i've helped a lot of them and so like i go in less like i'm trying to pitch something and more like let's have a conversation and i find it really energizing yeah you did a great job i appreciate it yeah you did great job uh did you get good feedback from our episode one i did how about you good yeah you do more of these than i do so i have no idea so you do a fair you do a fair bit yeah try to do more yeah oh it's good to see you um congratulations on the like my man i don't even know where to

[2:39](https://realalpha.app/v/6v9q6k8aF6E/?t=159) start congratulating you um maybe i'll start with congratulations on the growth is that a fair place to start congratulations seems fair uh seven quarters what was the stat that i read seven quarters 150 million of error 100 million and then like a 50 million dollar quarter what happened we did 100 million seven quarters 150 and eight um so we were really proud of that 100 million dollars in annual recurring revenue in seven quarters just because i think uh we and wiz there's been a you know very maybe one or two companies that have done it and so it was certainly and rarefied air and i think just the reason we decided to be more public about it is i think there's a lot of you know a lot of venture funding available a lot of competition in this space but we're definitely growing faster and we felt like you know it was worth uh worth letting the market know that just because uh we do think and then to follow it with a 50 million dollar a quarter exceeded my expectations to say the least so really the business is growing really rapidly I think we're executing well but I also think it's just a really unique environment right now where the product that we sell which is AI agents to replace your IVR system or AI agents to engage

[3:51](https://realalpha.app/v/6v9q6k8aF6E/?t=231) with their customers is so valuable that they're just you know every client we talk to needs it and the question is why us versus some other solution. which we're, I think, pretty effective at explaining, but it's amazing. I mean, it's what a fun privilege to run a company like this. Tell me if this is true or false, but one of my observations actually just looking at the Sierra employee base is seemingly from the beginning, you hired both aggressively and senior. Again, I don't know. I'm just reading back to you what I have observed from looking at the leadership team. You had executives that I would say we're pretty senior kind of from the jump and you've staffed the team accordingly basically since the beginning and you know like my first of all do you think that's true before i continue i'll start with the reason why and then end with basically agreeing with you uh-huh we started the company with the thesis that a lot of the impact we can have on the economy and the world is through some of the largest companies in the world.

[4:58](https://realalpha.app/v/6v9q6k8aF6E/?t=298) So we said, hey, the Fortune 100 is, you know, the cohort of, that's our ideal customer profile. And to serve, you know, a company like Cigna Healthcare or, you know, DirecTV, you have to be able to actually go into those companies and know what you're talking about, understand, you know, what a mainframe is, and understand that not every company uses like next generation software as a service, but there's legacy systems. You have to understand regulations. And so part of that is when we built the company, we built it around really being able to serve these businesses. And so as a consequence, we wanted in parts of our business, we want to make sure we had people with some experience just because it's hard to go into, you know, we serve a pretty high percentage of the Fortune 20 at this point.

[5:48](https://realalpha.app/v/6v9q6k8aF6E/?t=348) And to do so,

[5:49](https://realalpha.app/v/6v9q6k8aF6E/?t=349) **Bret Taylor:** you have to be able to have credibility in that room. We couple it though with a lot of very young people too. So we have this program called the APX program, which is modeled after where I got hired

[6:00](https://realalpha.app/v/6v9q6k8aF6E/?t=360) at Google, where we hire new graduates out of engineering degrees and teach them how to be agent product managers or agent engineers. And it's like a rotational program, just like the APM program at Google. So I would say we kind of get both ends of that, where we have people who to understand the business of enterprise software and understand how to work with the most complex businesses in the world and the most talented young people we can find who are AI native, I guess you could say. And we think that's our kind of sweet spot in the market. But yes, we have tired more experienced people. We are planning for success to some degree.

[6:38](https://realalpha.app/v/6v9q6k8aF6E/?t=398) And actually, I think it's born out in the numbers, not just the ARR numbers, but over a quarter of our customers have over 10 billion in revenue, which for a company that's been in the market for two years is very unusual you tend to usually start with smaller customers and move out from there and we've started kind of at the top end of the market which was very intentional yeah the you just had to be right right because if you have you know like uh call it big company executives um i don't mean that disparagingly but executives that come from big companies that are used to managing big teams with big whatever purviews and you're in obscurity for several months and they don't get to hire teams there's trouble right like it's harder it's harder well it's interesting because you know you said big company executives said not to be disparaging but it sort of is that phrase is right like you don't no one says that i guess it's disparaging in the con in the context of like a baby starter well that's the thing actually but even if just the phrase itself is i would argue probably rarely used except for disparagingly.

[7:39](https://realalpha.app/v/6v9q6k8aF6E/?t=459) And I would say that is more of a mindset than if you go into a larger firm, you'll find people who are extremely high agency and have grit and have intensity, and you'll find people who are good at managing politics and all of that. So the sweet spot for us was to find and people who had experience who weren't big company people totally because and and that's a nuanced thing and i think it's something we really try to hire for you know we one of our values is competitive intensity which is sort of an unusual company value but it's one of our company values like and a part of it is like we want people who relentlessly focus on outcomes more than anything else which is distinctly probably not what you meant by big company people right it sounds more like startup like grit uh and i would argue there are those gems everywhere and especially right now if you just look at the software market which is you know uh it's a really tough spot in the public markets i think a lot of people are saying who are the sort of like new guard of companies that will come to be uh the people who define these markets and we're trying to you know be one of those companies so that those you know folks who have experience who have grit want to work at our

[8:56](https://realalpha.app/v/6v9q6k8aF6E/?t=536) company. And that's kind of the culture we're trying to create. Yeah. The thing that I'm like really poking at and mostly like I think it's a counterexample of success here, which is why I'm so interested in it. And by the way, like the irony is like you are the I'm not really sure what bucket you fall into, but you've certainly been a big company executive and now you're running a startup. But like, let's just say across the top eight KP portfolio companies and let's put the top five executive positions in those companies. So 40 roles. I think in our top companies 39 out of the 40 report to the founder for the first time in their career. And that is somewhat against conventional wisdom because conventional wisdom says like, these are the people that have been there and done that and seen the scale. And I guess my observation, at least in our portfolio, is that that's not necessarily the case. And I started asking myself, why is that? And I think the core answer is because it's very hard to find the people that have all of the things that you just described, the competitive intensity, while also being in a big company.

[9:58](https://realalpha.app/v/6v9q6k8aF6E/?t=598) I think in some ways, like that is the ideal profile. You just have to sift through. You just have to really make sure you know. It is the hardest thing for a founder. And this is, you know, there's some downsides to, you know, I'm kind of an old guard at this point in Silicon Valley. You know, this is the third company I've started. And as you said, I've started two companies prior to this, and I've worked at Google and Facebook and Salesforce. So I've seen big, I've seen small. One of the benefits of that experience, and there are some downsides too, one of the benefits is I actually can identify people, I think, more effectively. I mean, the hard part for a first-time founder is if, let's say you're a software engineer making an enterprise software company and you have to hire your first head of sales, you probably never, I assume you've never run a sales team. It's not an area that you like studied or an expert in. And so you end up relying on other people's advice on what, you know, there's sort of the fit that you have, the personality match. And you rely a lot on your board members, investors, other things. Oh, this person's a great head of sales. And there's just so many examples of organs rejected by the body. And, you know, failure is an orphan, right? So

[11:07](https://realalpha.app/v/6v9q6k8aF6E/?t=667) everyone blames everybody else. In starting Sierra, there's a lot that are really new about it you know the ai market is completely novel so you think about you know writing software in the age of software coding agents and it's completely novel and then there's parts of the business where like i know what i want you know i know what i want and clay knows what clay my co-founder and i like we decided this is who we want and we decided let's shoot for the stars like let's get the the person we want in this role to help scale the business and i would say probably half of our executive team it's their first time in a role like that and half are quite seasoned and it's a really nice nice mix um but the nice part of experience is i can sift through because i've seen hundreds of sales leaders and i kind of know who i want and and you know them and i yeah exactly yeah exactly yeah that makes sense sorry um you use the phrase failure as an can you explain that? So, especially at larger firms, but I think broadly, you know, success has a thousand fathers, failure is an orphan. And basically what that means is anytime there's a successful product at a company, Claude Code at Anthropic or Google Maps at Google, everyone who's

[12:22](https://realalpha.app/v/6v9q6k8aF6E/?t=742) remotely adjacent to it takes credit for it. You know, I've had people who describe themselves as creators of google map that i've never met before like not sure you're involved but i might have been overstated a bit and and then similarly when a project fails everyone deflects blame you know it's like well the product manager blames the engineering team the you know we couldn't really get the marketing we needed the classic thing in enterprise sales is if your sales are bad the sales team blames the product, the product people blame the sales team. And it is actually the ultimate challenge with recruiting. But as an entrepreneur, it's actually the hardest challenge in building a company. I had a really impactful moment when I was working on Quip, where I went up to Microsoft's campus and saw a lot of people on campus using Windows phones. And I had, you know, down here, there was like, I'd never seen one in the wild, you know, like, you know, they exist, but you know, they weren't, it was just not a popular product. And I went and I talked to someone just on campus. Like I was waiting, I was in a waiting area kind of thing. And they had so much optimism that windows phone was going to beat Android or, you know, beat iOS. And this was like

[13:42](https://realalpha.app/v/6v9q6k8aF6E/?t=822) well past the battle being done. You know, like if you had talked to anyone in our circle, they'd be like, no, it's a two-horse race, Android and iOS. But somehow in the echo chamber of Redmond, Washington, there was still a chance. And you ask like, why is that? Because Microsoft tires really, really smart people. And I think it's arrogant to say otherwise. They hired like some of the best of the best. Somehow all these smart people could convince themselves of something that was self-evidently not true from the outside looking in. Well, if you think about a larger company, Clay gave me this metaphor, but it's like a sphere that grows. And the surface area of the sphere is your engagement with your clients. And the middle of the sphere is your company. And the volume grows faster than the surface area. So what ends up happening is the people in the middle of that sphere, all they can see is the sphere. They can't see the surface. And you end up with internal narratives driving decision making. And I think storytelling kills companies. You end up of these stories of why your product isn't selling. And that story becomes the truth.

[14:48](https://realalpha.app/v/6v9q6k8aF6E/?t=888) When in fact, if that story is probably someone covering their ass, you know, that story is the sales team blaming the product or the product team blaming the sales team. And if you actually think about being in the environment we're in now, which is, I would argue, one of the most competitive environments I've ever been in, the most important thing is understanding the truth about your product market fit about understanding your competitive landscape and so when i say

[15:14](https://realalpha.app/v/6v9q6k8aF6E/?t=914) **Bret Taylor:** failure is an orphan i always think about it because every time someone tells me a story that essentially is a rationale or like rationalizing why something happened i'm immediately skeptical

[15:25](https://realalpha.app/v/6v9q6k8aF6E/?t=925) or i immediately think about all the incentives of all the people involved and sort of synthesize that story through that lens and i'm always almost seeking out the other right other side of that argument and i think it's why like as a entrepreneur you just need to be on the surface of that that sphere at all times you need to be listening to your customers not you know a middle manager telling you why something happened and it is the hardest part and then when you're doing recruiting and someone says you know explaining something on the resume i can promise you every initiative that was successful.

[16:00](https://realalpha.app/v/6v9q6k8aF6E/?t=960) was solely because of them and everything was a failure was because of someone else like it it's like a tale as old as time and and and then you're like your job is to like as a it's like a detective novel like what actually happened and uh that's where references and all that happened but this is the hardest part of building a business is like fighting storytelling it's like a it's like a vc when you know a company is going well like they were you know they were intimately involved from the beginning and they knew it when nobody else knew and then when it's not going well like it's not even the founder wouldn't listen to me yeah 100 you mentioned like this is one of the most competitive uh times that you've seen and like i'm curious like okay yes in the space that you're in like a support ai native support okay you're right there are like i don't know at least seven companies and growing some of which are like good companies like you're not fighting legacy old stodgy solutions and by the way you're also probably fighting some version of like open ai going into an account or anthropic going into an account like it's competitive in that respect okay like i buy that but do you think it's maybe somewhat less competitive in the sense that the

[17:20](https://realalpha.app/v/6v9q6k8aF6E/?t=1040) pie is so much bigger that maybe that's why there's so many sharks in the water here. Like, I'm curious how you think about like, yes, there's more companies in the space, but it seems to me that this space is, you know, like next to coding, uh, one of the biggest spaces or markets that I've ever seen. So I don't know, like square that for me. I think you're right. I would say there's two reasons why I think there's a lot of competition. One is the market is gigantic. Um, and you know,

[17:48](https://realalpha.app/v/6v9q6k8aF6E/?t=1068) **Bret Taylor:** prior to large language models and generative AI, about $400 billion a year were spent on contact centers and BPOs and that sort of category. And I think that with AI, you end up

[18:06](https://realalpha.app/v/6v9q6k8aF6E/?t=1086) generating more demand when the unit economics go down. So put another way, if you do 100 million phone calls a year with your call center, when the cost of phone calls go down, you'll probably you a lot more phone calls, you know, as a consequence of it. So I think the market is gigantic and which is why there's a lot of people going after it. I also think there's, I'll use it, that'll mean it's too unfair, but there's sort of an excessive amount of venture available as well. And so as a consequence, you don't really get, right now, we're not really getting the culling effect of the winners and losers. We estimate we're, you know, three or four times larger than and the next biggest player in our space, but none of them have been consolidated yet.

[18:49](https://realalpha.app/v/6v9q6k8aF6E/?t=1129) I think, and it's, that'll happen. I believe it will. Not because they're, as I said, they're not a bad company. They just mean there's like, you know, it's like the economics of software. You know, there's basically, you tend to get a large number of companies all going after a space. Then you tend to get incumbents purchasing the second, third, fourth place players. And it works out well for everybody. It's kind of the economics of Silicon Valley. right now, because of the wide availability of capital, the valuations for the second, third, fourth, fifth, sixth, seventh, eighth, ninth place players are all so high that they're not really affordable for the incumbents to absorb. So you just end up with lots of players in the space. I imagine we'll just see some consolidation over the next few years, just because that's sort of the ebbs and flows of these technology cycles. And you'll end up where you know the folks in the lead have the privilege of sort of becoming the next incumbents if you will you know and remaining independent but because valuations are so inflated right now it's just not economical and especially with valuations depressed with a lot of the incumbent software stocks because of the sort of gray cloud of

[19:59](https://realalpha.app/v/6v9q6k8aF6E/?t=1199) it. hanging over all of them. So it'll just be interesting. I think we'll need probably a modest correction for a lot of the natural kind of consolidation to happen. But I think it will. I think it's sort of a matter of timing and more than anything else. But I do think the markets are different and it's not just service. One of the things I firmly believe is that there is not enough applied AI companies working on AI agents for business processes that are are extremely valuable, as opposed to working for tooling around AI itself. You know, I think software engineering and customer service are certainly two of them. I think the legal tech market, the legal AI agent market is maturing. You know, we're really close to Harvey, one of the entrants, but there's a couple other decent players. They have competition now as well.

[20:52](https://realalpha.app/v/6v9q6k8aF6E/?t=1252) And just like you said, they're credible companies, right? They're good companies. And so competition's good. I'd love to see that in finance. I'd love to see that in other parts of, I'll say, the back office. It'll be interesting to see what happens in marketing. Martech is sort of famously saturated with a billion different vendors, but I think there's a lot that can be sort of truly automated there from purchasing ads to content marketing where you see some investments as well. And my view is that that will be, I think that's what most companies would prefer to buy, i.e. buy solutions to their problems or, you know, buy improvements to core business metrics.

[21:32](https://realalpha.app/v/6v9q6k8aF6E/?t=1292) But just because the market is so new right now, there's just not a really mature applied AI market in a lot of categories. And so it's going to have to go through a wave like we're going through in coding agents and customer service agents, which is you need a lot of companies trying it. You need to have the free market do its job of culling, and then you'll see some consolidation on the other side. It's interesting, your point on like the venture dollars that are creating somewhat artificial growth and expectations in these markets and then creating more competition. Like, if you think about that, like if you put your kind of chair of the board of OpenAI hat on, your argument is like, as the cost per unit of token basically goes down, demand will go up.

[22:18](https://realalpha.app/v/6v9q6k8aF6E/?t=1338) I guess, couldn't you make the same argument that all of those venture dollars are also now artificially deflating the cost per unit of the tokens, like these actual underlying models? Or do you think that we are in an inevitable race to the bottom and it's just going to continue to get cheaper and cheaper independent of the venture funding for the underlying models? it's a good question i i don't think the venture economy is what's driving token demand i think it's actual like the revenue numbers are real in these companies so i think the venture this is my take and i'm not a sophisticated economist i'm just like a business person in this world but to me it's inflating valuations and it's like making it just really easy to start company it's like too easy to start companies like you're starting a company in a crowded market with no particular uniqueness you know in a in a market with less venture capital you wouldn't get financing for that now we're just in a different world we're like so that's sort of that's where i think the venture is playing in more in the quantity of competition as you said there's really smart people building these companies i don't mean it in a disparaging way at all it just uh you know

[23:27](https://realalpha.app/v/6v9q6k8aF6E/?t=1407) it's not it's there's not enough room in the market for all these players to to thrive as an independent company. But I think demand, like the revenue is real. And I think that's what's driving token demand. I mean, just look at software engineering. Like if you just look at all the other markets, you know, Quip and Sierra, Harvey, they go away and you just have software engineering that could probably saturate demand. That and chat GPT. And you've got enough demand for all these tokens. And I think the Moore's law characteristics of, you know, these models will drive token costs down. because there's every incentive to do so and also scientific breakthroughs that facilitate it, just like the transistor in the early days of Moore's Law.

[24:09](https://realalpha.app/v/6v9q6k8aF6E/?t=1449) The interesting thing is the way I see the models playing out is a little bit more of a heterogeneous set of models for applied AI applications. I think if you look at the pursuit of AGI, you end up using a lot of tokens because you do both that training but also inference time with these reasoning models, you're using a ton of tokens, but producing remarkable amounts of intelligence. In the more applied AI world, you're seeing this with codecs and modern versions of Claude, where they're actually thinking for long periods of time, consuming a lot of tokens, but writing extremely high quality software.

[24:49](https://realalpha.app/v/6v9q6k8aF6E/?t=1489) So, you know, it's not like the actual, you know, iterative, like each iteration of using codecs, like the cost hasn't gone down, it's probably gone up, but you're actually building software you couldn't do before. So it's quite valuable. And then the other end of the market, you might be using, let's say you're making an LLM augmented thing to detect credit card fraud. Well, you can't, you don't want to use a reasoning model for that. It's too expensive and high frequency for that. So you might, that you probably want, you care about latency and other things. If you're doing voice AI, you care a ton about latency.

[25:20](https://realalpha.app/v/6v9q6k8aF6E/?t=1520) **Bret Taylor:** And so my sense is we're going to end up with a, we use the term internally at Sierra, a constellation of models where you have different price performance, which is both latency and throughput.

[25:31](https://realalpha.app/v/6v9q6k8aF6E/?t=1531) And different applications are sensitive to both quality. And you're going to trade off all those different levers for your application. And if there's an analog in the pre-LM world, there's probably databases. You know, like, I don't think there's a database you use for everything, right? If you want a trillion data points and you want to do analytics on it, you'll use one column or data store type thing. If you want a transactional database for credit card transactions, you'll use something different. And if you want to, you know, eventually consistent cash, you'll use a different thing. And engineers over the past three decades of building cloud applications have pretty much a shared set of rules of thumb to figure out which data storage technology you use for different applications.

[26:16](https://realalpha.app/v/6v9q6k8aF6E/?t=1576) uh i think that's the way models will play out over time and i think i i think we'll sort of grow up in you know five years and there'll be a lot of different um things that we call large language models today but sort of in that heritage of model um probably with new advancements just like the reasoning models and there'll be a lot used in concert for to power an agent and i think that'll be a really healthy um healthy progress in the ecosystem earlier you mentioned um hey like a market correction might be good here let's like play fake economists for a second like we don't know i'm curious if you think that will come from i don't know like models slowing down progress in air quotes um if that will come from all of a sudden public sass comps are down 50 and so people start getting jittery like i'm curious if you're like as you read the tea leaves obviously you have to think about some of this because you have to capitalize the business as a byproduct of what you see coming down the pike like how do you yeah like how are you like indexing the risks here i think it probably will happen um i think as you said the juxtaposition of multiples of software stocks being lower than they have been and the premium on ai uh investments which are largely private

[27:35](https://realalpha.app/v/6v9q6k8aF6E/?t=1655) creates this you know awkwardness which is like what happens when these companies go public do the valuation settle down and so you know you could end up where a world where you know as some of uh some i'll quote unquote ai companies and that definition is an interesting one just because i not sure exactly what it is like clearly open ai is one right there's everyone else is striving to be one just you mean it doesn't count if you put It could be that you end up where a few of these nominally AI companies enter public markets and don't get the reception. And that trickles down to private markets, late stage, and then early stage. Maybe the more likely one is macro, though. When interest rates went up because of inflation after the pandemic, that corrected a lot of the software market.

[28:28](https://realalpha.app/v/6v9q6k8aF6E/?t=1708) And so, you know, it does feel like these macro forces are greater than any sort of insular tech specific thing and, you know, will generally make, you know, just change the way people invest. I'm not sure what which will cause it, but it does feel like I don't think it's unhealthy, by the way. I mean, just just say, like, I'm a capitalist. So, like, I think it's really healthy that there's lots of companies going after these problems because it enables the market to kind of like do more exploration of ideas. um so it's but my sense is it just can't go on forever just because you can't have 20 companies going after the same space with uh it's just like there's just too much sort of saturation uh in the market but i think there will be a some form of correction there and then some form of consolidation and i think it'll be fine i think we'll i think we'll survive it and it'll be fine and actually the economic of impact of ai will be viewed uh probably with as much optimism as anyone has right now.

[29:30](https://realalpha.app/v/6v9q6k8aF6E/?t=1770) It's truly changing. We can feel it deeply in software engineering and in customer service. It's completely transformed those industries. And for those of us in the middle of it, you can just see the capabilities of the models because you feel it. You know, you feel like the difference between using Codex today compared to three months ago, and you see what it can do differently. And it's easier if you're in the middle of one of those industries to extrapolate to all the others. But I just I do think it will have a huge, huge impact. I'm sure you read that article. I guess it was yesterday that came out. It was like, do you remember the name of the article? I don't, but I did read it. Okay. Yeah. It was like, how would I characterize it? I would say like sounding the alarm bell of the change that is to come through the lens of coding as the like models are improving. Basically, like the author was arguing that people, no matter how bullish you may be, you're still underestimating how quickly this rate of change is. And as most like primarily evidenced by what's happening in coding today with how good the models are getting where, you know, like two years ago, you could barely write, I think like, you know, it could barely write a line of code. And now it's like writing

[30:45](https://realalpha.app/v/6v9q6k8aF6E/?t=1845) like thousands of lines of code autonomously well yeah like really well like full code bases and then checking that code and it's really good yeah you know uh and um and you know i think the point of the article was like hey for people outside of the valley that don't really aren't living and breathing it like we are like you have no idea basically and i kind of viewed it as like um There was definitely a dystopian lens to it. Would you agree with that? Like it was somewhat dystopian. It was hard to tell. It sort of ended optimistic, but it was. Yeah, I sort of said, I agree. It had a kind of anxious dystopian lens to it.

[31:22](https://realalpha.app/v/6v9q6k8aF6E/?t=1882) I agree. Yeah, like the world's going to change and we're not ready for it. And, you know, it's interesting. Like I think every, what's crazy is like every three to six months, I feel like we, the pendulum swings from like the models aren't improving to nobody's going to have a job anymore like like it just keeps going back and forth between those two things like it's overrated and nobody cares about ai anymore to like we're all going to sit on the beach and have my ties one day yeah um and um that's like a pretty like I think if you don't come I think if you come from our world, it's still like a pretty heavy feeling. I can't imagine basically the rest of the world, how they feel just reading these things from the outside in. And Sam at OpenAI also talks about this in, and like Dario, like these guys are also talking about this, like this, like almost change management of society that is coming.

[32:28](https://realalpha.app/v/6v9q6k8aF6E/?t=1948) and um you know in some ways like there i think everybody's right in that like we are like things are going to be like drastically different but in other ways i'm like you know the pendulum has definitely swung into like we're all going to be on the beach in my ties i'm curious like i like where do you follow yeah like i'm not in camp my tie but i also not in the other camp either i i find i don't i question the premise of the two extremes i'll give you my perspective so first part of the reason i think you have the juxtaposition of the models aren't changing and oh my god everything has changed is how much intelligence you need for the task so if you're using chat gpt to plan your vacation and you use gpt40 and use gpt53 my guess is the experience won't be that different because planning a vacation on chat gpt doesn't require a huge amount of intelligence to do it was already had reached sort of sufficient quality you know a year or two years ago that actually like everything is sort of feels like incremental on top of it in contrast if you're using the model to write a rust module that is going to do something low-level systems software with like high sensitivity around both correctness and latency

[33:44](https://realalpha.app/v/6v9q6k8aF6E/?t=2024) the models were like woefully and like they just could not do it two years ago and all of a sudden over the past three months they could i think what's ending up happening is if you end up i don't think it's really possible to do but if you're just like take every task you do in your life and and sort of order them by how much intelligence is required to do them we're sort of moving down that line and if you're testing something that we'd already like the horizon had already passed you're like nothing's changed and that's actually people's lived experience with chat gpt a lot of it is these sort of simple and they're useful right but we already we already solve that. So now it's a commodity. And then if you're trying to do drug discovery or software engineering, you're seeing it change on a daily basis. That's why I think there's a juxtaposition.

[34:28](https://realalpha.app/v/6v9q6k8aF6E/?t=2068) And put it out of the way, one interesting sort of thought exercise is we've reached sufficient

[34:35](https://realalpha.app/v/6v9q6k8aF6E/?t=2075) **Bret Taylor:** intelligence for a lot of tasks. Put it out of the way, if we paused innovation and just absorbed the intelligence of all the existing models, my guess is there's still trillions of dollars of economic value we haven't realized yet, which is interesting unto itself. Uh, I think it's

[34:50](https://realalpha.app/v/6v9q6k8aF6E/?t=2090) really interesting. Then you go to like the, what's going to happen. I think a couple of things are true. I'm an optimist in all of this. The reason why I don't, I'm not in camp Mai Tai is I just don't believe that humans will stop doing things. I think we've, uh, through automation, like eliminated a lot of jobs from the jobs of a bank teller to a lot of agricultural jobs, which have, you know, I think it's like what, 5% of our jobs are in agriculture today compared to like 95%, you know, a few hundred years ago. And so just because we automate jobs, I think we often lack the imagination to imagine what comes on the other side of it. And I firmly believe that, you know, I just think that we are, I believe this technology is fundamentally a tool, even though it's a really impressive and super intelligent tool, but it's fundamentally a tool and we will create an economy and identity around it.

[35:46](https://realalpha.app/v/6v9q6k8aF6E/?t=2146) And I don't believe that because it took something we're doing now, it's taking away our identity and we want to go sit on a beach. I just don't believe that as a human being. The other thing, though, to temper the excitement is suffering. engineering is both getting the most attention right now because the research labs know to create self-improvement for AGI, a automated AI researcher is a prerequisite. So as a consequence, all the smartest research labs are specifically working on this. So it can write its own, write the next series of models. That's right. And if you saw the OpenAI post on 5.3, there was a lot of openness about sort of using the model to help build the model, which I thought was really interesting and what's happening in all the labs right now. So first, just because software engineering is getting great, the idea that that's completely general is not, it may be true, but it's not obviously true. There's a lot, how much this generalizes the G and AGI is the hard part. And it certainly generalizes, but how broadly is an interesting question. The second thing is like which parts of the economy can basically absorb intelligence completely fluidly.

[36:58](https://realalpha.app/v/6v9q6k8aF6E/?t=2218) Software engineering is definitely one of them. It's a purely digital profession, right? You write code, you compile code, you produce, you know, binaries. And so the entire process is digital and you can test it digitally, contrast that to, you know, a drug discovery. It might work until you need a wet lab and then you need a wet lab and all of a sudden you need robots. Okay. Then unless you did robots in the wet lab, then you want to bring it to market. Well, you need a clinical trial. And that clinical trial, even if you have great ideas on how to do it better, it's still a process that is regulated by the government. Like there's no amount of like intelligence you can just like pour onto that process and make it run faster. And so the interesting thing I see is like clearly finance and software engineering are professions where you can take intelligence and sort of absorb it into the profession quite efficiently. You know, because a lot of the job is essentially operating in the world of information.

[37:52](https://realalpha.app/v/6v9q6k8aF6E/?t=2272) And then you say, okay, like, what are all the other parts of the economy? And not only are we absurdly focused on coding agents just because of its importance to the AGI labs, but also it's not obvious to me that every other profession is as easy to take an information-oriented digital agent and transform the profession. So I think it's going to have a really big impact, but I think the takeoff in the AI labs might be faster than the takeoff in society to some degree, just because different professions will be sort of differently impacted by it. And it's useful. I actually have started doing this, which is like I'll walk around and just think about like, OK, if we had like super intelligence by any measure, you know, what would happen to that flower shop right there?

[38:46](https://realalpha.app/v/6v9q6k8aF6E/?t=2326) You know, like what would change about it? And it's really interesting to simulate that because I do think it sort of shows both the short term opportunities and like the complexity of, you know, how this technology gets rolled out around the globe. Super interesting. And then, you know, a lot of what the labs are saying right now is, you know, we're not going to be hiring engineers in the future. Like, uh, there's this big take from the heads of the labs that they're going to reduce their own head count. You know, uh, Sierra seems to be growing. Like, uh, there seems to be a lot of people that you're hiring. Uh, like, um, you know, it seems like you're still hiring a bunch of software engineers and salespeople. Like it seems to me from the outside in that you're building a high growth company and staffing it with the resources that I would have seen for any company growing of this size? Square that. I think it's a correct critique. Yeah, I always laugh. Like if you look at Anthropic and OpenAI, they don't look that different than a high growth company that preceded it, I would argue. Sam and Dario might disagree, but they're not fundamentally different. It's hard to know, though, because on the other hand, OpenAI's revenue scale is truly

[39:59](https://realalpha.app/v/6v9q6k8aF6E/?t=2399) unprecedented. And there's no way to A-B test what you would have needed, you know, preceding it. So maybe that's an unfair comparison. I think one of the things just to state it is these coding agents have only gotten this level of quality literally over the past few months. So these companies have been built over the past years, not months. And so one of the, I think the, perhaps an interesting question to ask is with the current technology, what shape would you want your company to be maybe, uh, as a proportion of your revenue or users or whatever the right, you know, uh, proportionality might be.

[40:38](https://realalpha.app/v/6v9q6k8aF6E/?t=2438) And I think one could argue that if you project out the skillset, you may want a different shape in the future. So one reason may be that actually we just hadn't gotten to the point where the kind a new shape of the company were really possible. But for the smart leaders of these labs, they're projecting forward. And it might be right. Going back to my, you know, bank teller example, though, you know, when the banks automated distributing cash with an ATM, they decided to keep their branches and keep employees in those branches, but have them do higher value things. And so we live in a well hopefully in a free market that's very competitive and so uh clearly the people who are software engineers won't be doing they're already not doing the same things as they were a year ago like they're operating you know clod and codex not typing and just nine months ago they were in cursor and like nine months before that they were in vs code so like every you know it's it's incredible how rapidly it changes but will you want the same number of people, I don't know, the way I'd answer that question is, does having more people enable you to gain more market share than your competitors? And if the answer is yes, I think the answer will

[41:52](https://realalpha.app/v/6v9q6k8aF6E/?t=2512) be yes, because you don't just like recoup efficiencies in your business and pass them

[41:57](https://realalpha.app/v/6v9q6k8aF6E/?t=2517) **Bret Taylor:** on to shareholders, because every one of your competitors has access to the exact same technology.

[42:02](https://realalpha.app/v/6v9q6k8aF6E/?t=2522) And so what's going to happen is the second order of fact is, if you assume every company in a market has access to this technology, which is truly democratizing. What does every company do with that new higher leverage operating model? And that's what's exciting about it. And this is why I find a lot of people's projections about jobs to be simplistic, because let's just take the mobile phone market in the United States. So you have Verizon, T-Mobile, AT&T, all fighting for the same, how many mobile subscribers are in the US? I don't know, 300 million? I don't know what it is. It's a fixed pie.

[42:42](https://realalpha.app/v/6v9q6k8aF6E/?t=2562) So like, you know, just assume all of them have access to the same AI technology to improve their business. Well, then the question is like, okay, they're not going to pass that on as cost savings. I mean, they can, but if one of them lowers prices, the other one will have to lower prices. If one of them finds a new interesting channel for customer acquisition, the other person will. And so I think the key in all of this processes in a competitive market with a technology like this, everyone's going to absorb the impacts of the technology and then compete. It's a little bit like, to some degree, if we went back to 1995 and I were trying to sell you the prospect of making a website, and I said, if you make this website, you'll be able to do X and Y and Z. And if I ended that way, then none of your competitors will do that. It would be a lie. In fact, for the benefit of hindsight, the correct sales pit for a website is you should build a website x y and z because if you don't all of your competitors will and here's what's going to happen to your business which will be not have access to these new digital channels and search and you know all the other like demand generation all these things and all

[43:49](https://realalpha.app/v/6v9q6k8aF6E/?t=2629) of a sudden it becomes an imperative so that's kind of how i view ai is it's sort of a strategic opportunity but it's actually more of an imperative if every software company in the world can produce software to marginal cost, it's like much lower than you can, you're at a disadvantage. And I think because everyone is going to do it, it's going to play out in the second order effect is where all the job creation will be, but also the interesting competition. And it's fascinating. And I think it's very hard to imagine just because, you know, if people knew people would be doing it already, it's like you kind of need this to wash over the market and then, you know, have these companies compete. And I think it will surprise us what comes of that competition. When you think about capitalizing the business, I'm really curious, is the last valuation public? Is that out?

[44:41](https://realalpha.app/v/6v9q6k8aF6E/?t=2681) The 10 billion? 10 billion. Okay. And so we know your ARR roughly. We know about when you did the deal. So it was like a hundred ish million at 10 billion. Okay. Those revenue multiples do not resemble the public market comps it's high it's expensive um like uh why like what like uh you can probably raise even higher but let's just assume that's a pretty high clip for you to raise at how do you um um why even capitalize the business so much right now um why raise at a higher mark Is it like, I'm just curious, like how you think about the strategy of what capital and valuations means as an edge to your business?

[45:27](https://realalpha.app/v/6v9q6k8aF6E/?t=2727) There's a lot to the why, because you're probably saying why I did it and why maybe our investors chose to do it. Actually, less the latter. Yeah, why we did it. Yeah, why you did it. We aspire at CIRA to be the platform of choice for every company in the world, in particular, the largest companies of the world. when they're thinking about using an AI agent for their customer experience. So whether it's healthcare companies like Blue Shield of California and Cigna or revenue cycle management companies like R1 or telecommunications companies like DirecTV, SiriusXM or the banks that we work with or the fintechs that we work with or the insurance companies we work with, we wanna be the default.

[46:09](https://realalpha.app/v/6v9q6k8aF6E/?t=2769) We wanna be the company that you can partner with that will enable you to go live, get success, and we want to be your first phone call. And I think that requires a lot. You know, one is, you know, I think part of the reason we've grown so much is we have by far the best sort of customer base. And so, you know, when people are saying, they look around and say, I'd like to use a partner that companies I respect use, we're in that. It also requires scale. So we opened an office in London, we opened an office in Singapore, we opened an office in Tokyo. you know you need to be present in these markets to work with the clients who are present in those markets and so i just don't think you know being so lean the uh you know focusing so much on that is really the right way to to win in this market we want to we use the term face in the place like we won't be next to where our customers are we work with you know one of the large spanish banks we need to be present in madrid to to partner with them uh you know we work with one of the you know, Southeast Asians telcos. And, you know, you don't want to have to wake up in the middle of the night to have that phone call, you need to be present there. And then similarly, you know,

[47:16](https://realalpha.app/v/6v9q6k8aF6E/?t=2836) I want to make sure we're scaling our product as well. I think I always admire sort of what the rippling guys talk about this, but like your pace of innovation is, it's actually almost important than your product, right? Because in a world where AI is changing so rapidly, your roadmap matters a lot, right? Because you could have the state of the art today and 12 months from now have something that looks pretty archaic and you know our goal is to have like the fastest pace of innovation as well so we want to capitalize investment so we have the fastest pace of innovation we can grow our customer base the fastest and be present in all these markets and we just need to grow up pretty quickly to do that and it's in part because if you are one of the largest banks in the world you want to know your partner is going to exist in 10 years you know you want to know that you're not the first, you know, structurally important bank to go live on this platform. You know, second or third is probably five and not first. So that's, and that just requires capital and growth and maturation. And that's what we're investing in. That makes sense. And then on the valuation piece, like, do you have a philosophy on like, just take the

[48:17](https://realalpha.app/v/6v9q6k8aF6E/?t=2897) highest valuation so you can have the least amount of dilution? Like, I'm curious, like, you know the let's take the market correction example like let's imagine that it happens this year and it happens meaningfully the counter argument to raising whatever a hundred at 10 billion is i'm just making up numbers but just for the story's sake um you you just have a proverbial gun to your head of a really big target that you have to hit at a valuation that was quite frothy at that given moment. So like, I'm more just like philosophically curious about how you

[48:55](https://realalpha.app/v/6v9q6k8aF6E/?t=2935) **Bret Taylor:** think about it. We definitely don't choose the highest valuation. In fact, in all three of our rounds, we had higher valuations available that we didn't take. So factually, we definitely don't

[49:05](https://realalpha.app/v/6v9q6k8aF6E/?t=2945) do that. We have a dilution that we care about, but within that range, we're choosing a partner and that's how we think about it. But it is a generous valuation. The way I think about it is actually quite simple, um, which is how much capital do we need to grow, uh, into the next milestone, which, you know, might end in, in entering the public markets, but between that, it would be to have a revenue scale and growth rate to justify, to capitalize the business in the next round in a way that all of the existing cap tables happy, uh, with that outcome. And so the way I think about it is, you know, if you take the $10 billion valuation scale, what does it mean to sort of fill in that valuation what revenue scale and growth rate how much capital do we need to achieve that that's all it is and i think the uh so we're very much focused on like our business plan which is like how are we going to invest in uh you know the products and uh you know our go to market teams to grow uh grow our revenue and it's a sort of a spreadsheet to be honest with That's how we think about it. And the unknowns, uh, but we just put a lot of, you know, air bands around it are, you know, the demand environment and competition. Um, though, you know, when you're

[50:22](https://realalpha.app/v/6v9q6k8aF6E/?t=3022) a company like ours, you just assume you're going to, you know, remain the best product on the market, uh, which is not something you're entitled to, but like, that's why you exist. Um, and then similar things like there's a lot of unknowns around we've talked about, like, well, how many software engineers will we need to reach? I don't know. I have no idea. Um, but with usually what these things is you try to plan somewhat conservatively because the last thing you want to do is under capitalize your business and then be in an environment where you have to raise money on terms that aren't favorable which has you know happened a lot but you don't want that to happen to you so we tend to sort of you know you put a bunch of padding in on different assumptions and run some contingency plans and all those other things and just make sure that you have enough capital to get to where you want to go to and by the way the reason why you know 100 it does sound but most companies aren't going 50 quarter over quarter either you know so that's the that's the dynamic and so i'm not sure it's right or wrong but i just mean like i i would no judgment past i'm more just curious one of uh i i incubated a company here with mamoon um who's

[51:22](https://realalpha.app/v/6v9q6k8aF6E/?t=3082) on the board with me and um we came out of stealth and um there was a lot of investor demand and you know we like our things are working let's put it that way and i really wanted to bet on call it flipping over one more card or two because there was giant multi-million dollar deals that I was pretty confident were going to get done. I could calibrate accordingly. I don't think you'd mind me sharing this. Ilya here at KP, he had heard that there was a lot of demand. He was like, You know, there's an old Kleiner law. I guess there's Kleiner laws and he was like, one of the Kleiner laws is, um, uh, when the appetizers are passed, take an appetizer. And that stuck with me, you know, like, uh, that stuck with me. So maybe there's just something to it. Like when the thing is macro matters a lot, like there were a lot of companies and whenever interest rates started growing up that maybe could have been healthier than they were, but just didn't have capital available as well. Um, so I, that's the thing that is always like you know whether i mean i my first company the bank banking crisis happened in the middle and so you know it turned out fine but it just it changes markets and so like you know right now there's just a lot of volatility in the world and so yeah when the

[52:44](https://realalpha.app/v/6v9q6k8aF6E/?t=3164) appetizers are served eat that's right yeah that's right um uh you uh you guys do paid pocs is that right? Like you, like maybe the question behind the question is that every CIO, every large company, maybe it's not the same voracious demand as a year and a half, two years ago, where their boards are telling their CEOs that they have to go use AI, but they are looking for wins. And then that like trickles all the way down. Right. And then what do they do? They like go online or they start asking their peers. And then they usually do like a bottoms up market first like what are the good markets okay like what are the projects that we should start in then they'll usually start in coding they probably already doing something with microsoft then they'll make their way to you know whatever windsurf and then they'll go straight to clod or codex or whatever right then they'll probably look at legal you know and then they'll probably look hopefully give us a call that's right they'll probably look at uh support right so like there's like a few buckets yeah and you're in one of those buckets okay and the the the good news is like you're in one of those buckets. And so you're like, you have more demand than supply

[53:55](https://realalpha.app/v/6v9q6k8aF6E/?t=3235) in some ways. The bad news is, I don't know, but like, I'm just parroting this back to you. There's probably a lot of tire kicking. Like there's probably like, it's not that your software can't scale. It's like you have a forward deployed engineering model where I suspect the reason you do it is because the underlying technology is nascent. The LLMs are nascent. Sierra is early and you want to it's prerogative on your it's your prerogative to basically give these large enterprises a bear hug a brett taylor sized bear hug to make sure that like they are successful and so you want to invest a bunch of resources in making sure that they're successful and in order to do that like you need great people that can partner with them and so like uh maybe not to put words in your mouth but i'm curious like do you then have to raise the bar of like when you are supply, not demand constrained, who you choose to work with and how those engagements go? Because that's a very caviar, but interesting problem right now. Yeah, I think you're right. So just talking about the kicking times, we have a name for it. We call it AI tourism. And so there are companies often, as you said, due to board and CEO pressure where you're trying to

[55:11](https://realalpha.app/v/6v9q6k8aF6E/?t=3311) show AI momentum, but without necessarily like a business mandate. And that's where you have, there was that MIT study that got sent around like everywhere about failed AI projects. I think a lot of that is AI tourism, where people sort of start ostensibly POCs, but they're essentially, they're like POCs marching into the void. Like they never were, there was no path to production for any of them, but they were, you know, showing motion or trying to learn about the technology. And so we, with our proof of concept, uh, more often than not, you know, we're, we're essentially always paid. Um, and the reason for that is we want companies that are serious about doing this. We don't want, you know, the companies that are doing AI tourism.

[55:57](https://realalpha.app/v/6v9q6k8aF6E/?t=3357) Um, and, uh, but it's. modest it's a little bit more just like hey like you're you're for real you know you actually want to to deploy this project at the end going to your point on the bear hug um you know more often than not our product can fix itself and it's pretty easy to use so the ford deployed part of it is uh is different than just being uh having a seat at the table with our clients um sometimes it's change management. We work with one large scale medical device company that had 40 call centers and they're consolidating it into one with AI. Some of it's technical, right? There's 40 different stacks and that's where sort of a, maybe a forward deployed motion helps, but they also need help with that transformation as well. And so, you know, part of the benefit we provide at Sierra is we can, whether you're small or big, by the way, it's not really a size thing, but the hard part of AI is like, how do you successfully deploy it? And some of it's human, some of it's technical. And what we want to do is actually be accountable for that, that outcome. It's why we have outcomes-based pricing. It's why we have, we call it agent development, that sort of forward deployed team, but it's not, you know, we can, we have a lot of clients who's like, Hey, I want to

[57:10](https://realalpha.app/v/6v9q6k8aF6E/?t=3430) do this all myself. And that's great. And we'll just say, here's the product, go to town. We have some who really need a lot of help, but our best are sort of, you know, co-innovation, you know, We're there helping you consult, if you will, on sort of like the right way to do it. And I think it's the way a lot of companies want to work in AI because they want to know best practices. They want to know, hey, I noticed you went live with this healthcare insurance company in two months, and that's really impressive. That's almost unbelievable. How did that? Tell me how to do that. That's actually kind of the thing that we can do at Sierra that's really unique, is we can kind of come in and say, we have experience with the largest banks. We have experience with largest healthcare companies. We have experience with the world's largest telcos. And if you want to move faster, we can help you do that. And that's not always technology. It's often a lot of other things. And so that's really been our sweet spot. So, and it does though, it is a higher touch model, if you will, and it's not all engineering, but what we want to be as a partner, not a vendor. That's how we want to show up with our clients. Yeah, that makes sense.

[58:16](https://realalpha.app/v/6v9q6k8aF6E/?t=3496) Can I ask, like, personally, like, one of the things that I was thinking about this morning in anticipation of this conversation, I'm like, you know, given your pedigree, both like with what you're doing in OpenAI and everything else that we know, and obviously what you're doing today at Sierra, you're probably getting hit up on like, it's got to be like five to 10 cool things a day. you know like i don't know how else to say it like there's and some of them are customer things which i suspect you prioritize then some of them are like should i go talk to jubin today you know on grit and whatever do that right and then some of i said yes yeah you did you twice now thank you uh uh uh some of them are you know probably like the other founder dinners and stuff right some of them are like go give a talk somewhere like the list goes on some of them are like fly you to i don't you know some awesome place and go skiing with investors whatever it is right like it starts to add up like uh uh have you had to develop the no motion like uh it's uh again it's kind of a caviar problem it's the same problem as like too much demand at sierra right but like there's a lot of demand on your time and you have a wife and and kids at home like like uh tell me about the time

[59:30](https://realalpha.app/v/6v9q6k8aF6E/?t=3570) management piece? I'm very curious about that. Uh, first I work a lot. Um, I, I love to work. Um, so I mean, I guess all the time. I mean, I, uh, I think you, you know, this as a founder, you know, you, you, if you're in bed and your eyes are closed, you're still, still thinking about work. I mean, at least I am. Um, but I enjoy it. It doesn't mean it's always, uh easy but i i just love uh love what i do and i love sir and i love open ai So I just really enjoy it. And I do put in a lot of effort into it and a lot of time into it. And I don't know, it's fun. But also, my wife, she knew since she was married, and we love talking about it. It's great. So I do put in a lot of time. I do prioritize my time. I try to spend basically time on our product and technology and time with our clients.

[1:00:25](https://realalpha.app/v/6v9q6k8aF6E/?t=3625) And I try to do as little other things as possible. And the idea being that I think I love spending time with our customers, our partners. AI learn a lot. You know, I always joke if I'm talking to a banking CEO or a banking CIO, they've forgotten more about banking than I will ever know. I know a bit about AI, but to actually have the combination of Sierra and that client produce something great is like the two of us together. And that requires a relationship and like deeply listening, you know, truly being a partner. And, you know, when I was talking about that sphere and the surface of the sphere versus the center of the sphere, like I try to live on the surface and really spend time with our customers.

[1:01:10](https://realalpha.app/v/6v9q6k8aF6E/?t=3670) And then I try to spend all the rest of my time on product and engineering. And I'm fortunate enough to have both an amazing co-founder in Clay Bevor and also just an amazing team. So I have the luxury of spending time on, you know, product and engineering and spending time with clients and more or less keep my calendar to those things and the occasional podcast. That makes sense. Yeah. You use the word fun to describe like how you feel. People ask me all the time, like, how am I enjoying, you know, like building a company and doing all this stuff? um i like you mentioned rippling earlier like i like parker and mckinnis's metaphor which is like it feels like playing my favorite sport that's how i feel i love the way parker talks about like i know parker like not that well but like every time he talks i'm like yeah he's one of them totally he's one of my we're in the same like he's a sicko for the game yeah complete sicko for the game i love that guy he's great and i like the way that he uses that metaphor because i feel the same way but i would not describe even if i'm playing my same my favorite sport as fun the way that i would describe it is like i feel deeply fulfilled and the the reason i don't

[1:02:21](https://realalpha.app/v/6v9q6k8aF6E/?t=3741) say fun is like a different version of fun for me is like i don't know going and playing golf or hanging out with friends or doing other things and those days are like long gone at this point but i would never i never long for doing that version of fun if that makes sense because i can't imagine doing anything else. It is what I want to be doing. And it is all consuming because it is extremely fulfilling, but because it's also all consuming, I wouldn't necessarily describe it as fun because sometimes at two in the morning when my eyes are closed, I would like to actually be asleep. You know what I mean? You're right. Fun is too simplistic a word for it. I actually agree with every word that you said. And I feel almost exactly like no notes. Like that is also how I feel. But there are moments of fun. I mean, that's the interesting thing about um sport like you know uh yeah I'm a huge Niners fan and you know it was fun when we were winning games when we shouldn't have and it was really painful to lose against the Seahawks in the divisional round but and that wasn't a fun moment that was a tough moment I can't even imagine if you're Christian McCaffrey and you've been like burning the kettle at both ends you get to that

[1:03:27](https://realalpha.app/v/6v9q6k8aF6E/?t=3807) point probably didn't feel fun but he did probably feel fulfilled and I think the NFL honors honored that like i think you deservedly won comeback player of the year and and uh and so kind of similar you know where i think the interesting thing about being an entrepreneur is you you do feel every bump in the road i think you i generally i hate to lose more than i like to win i think that is something that's pretty typical of most entrepreneurs that i know which makes the feel particularly low you know if you lose a deal or you you know something goes wrong your candidates as know, whatever it might be like it, it haunts you. Um, which is why, you know, uh, the, I think it's hard to be not, I think the intensity in that are like two strands of DNA that are really intertwined, but you also have those moments of true fulfillment, but also fun that go along with it. And one of the things I would say, I'm a huge believer in having a co-founder. Um, I, uh, like I, it's not sort of a philosophical thing on solo founders not working. I don't mean that at all.

[1:04:28](https://realalpha.app/v/6v9q6k8aF6E/?t=3868) I think those, generally speaking, I don't agree with rules, like there's rules of thumb or lack first principles thinking in my general view. I think it's just hard to be a founder by yourself. And like Clay and I do everything together. Like internally, we're Clay and Brett. There's not like one of us separately. And like having that partnership makes it more fun because in those moments where you're about to go too low, the other person lifts you up. And when you have those moments of great things happening, you have someone you can share it with. And it's actually why I like, I'm a huge believer in marriage.

[1:05:02](https://realalpha.app/v/6v9q6k8aF6E/?t=3902) I'm a huge believer in co-founders. Like life is hard. It's really great to do it with someone that you care about. And what's nice about a spouse or a co-founder is there's something sort of unconditional about it because you're literally kind of in it together. Like it's either going to work or it's not going to work. And so for me, I would say like clay makes it fun. But you're right. It's more fulfilling than fun. It's like it's complicated. Yeah. One of my other observations that I've had in this same vein that you just kind of made me think about with the co-founders thing. I have two co-founders and both in them, but also in my team, the trait that I have come to value almost more than anything that has surprised me is default optimism.

[1:05:47](https://realalpha.app/v/6v9q6k8aF6E/?t=3947) like uh you can't handle the pessimism like i can't handle it yeah and with them it's like true in spades like they just um they've never met a problem that they don't think they can solve yeah and there is um i think like we all feel this way across like the three of us and i think it permeates through the company like um i think when you are a default optimist it starts to imbue a sense of inevitability into the organization. And I think that's really healthy because like it builds momentum towards an end state that is like promising. And like momentum does to me feel like the oxygen of at least Roadrunner. Maybe you feel the same way at Sierra. Like it just feels really critical to continue to stack wins. And now I've even in employees, I have started to crave that value of, of optimism. The venture version of this, of this world is the expression that, um, pessimists sound smart and optimists make money and applied to startups. Like, uh, it's not about making money, but like there's something to that. And anyway, like maybe one of my most unexpected things that I look for now is that. I think it's, I agree with you. And it's hard because uh it's sort of uncool as a founder to you know show up and be like i'm freaking out you know

[1:07:10](https://realalpha.app/v/6v9q6k8aF6E/?t=4030) because as a founder you're you have to essentially manage a lot of stakeholders like you have to whether it's your employees your customers your investors your the public writ large and their opinion of your your firm there's a it's part of why there's sort of that distasteful kind of like hustle culture and performative stuff on social media is people need to act like everything's great. And it's so obviously bullshit, but people do it anyway. But it's partly because you're trying to convince yourself and try to convince everyone else. The thing I'd say is I agree on the optimism, but I also think you have to be careful not to bleed into inauthentic optimism.

[1:07:47](https://realalpha.app/v/6v9q6k8aF6E/?t=4067) Uh, you know, there's a, we, we have a, um, uh, philosophy, um, at Sierra related to our value of craftsmanship, which is like, basically the idea is like we. as a team. So in engineering, there's this idea of a root cause analysis when a system goes down and the spirit of an RCA, a good RCA is you don't blame people because the whole point of a well-engineered system is it should be impossible for a human operator to accidentally like trip over the wire and have the whole thing go down. So for example, if you push new code and it failed in production, it's not the person who wrote the bad code or even the person who pushes is like, why wasn't there a test?

[1:08:26](https://realalpha.app/v/6v9q6k8aF6E/?t=4106) You know, if it took the whole service down, why didn't we roll it out to a set of canary servers first and measure the metrics? And you say, okay, like, what is the system that could have been in place that would have prevented that thing from happening? We try to do that with all parts of our culture. If we lose a deal, if we lose a candidate, if we, you know, anything goes wrong, we'll do a dispassionate, blame-free, you know our root cause analysis so we call it lessons learned across the company yeah we do in front of the company every week um and the idea being that it's a way of making a failure collective because it makes it not pessimistic but it's like here's how we're going to keep this from happening again um and i think it's important because for us when i brought up the the flip side of optimism is storytelling and you know you want to have people who can solve a problem but you also don't want people the collective delusion that everything's okay when it's not because it might actually impact your decision making so it's interesting because you sort of want people who are like optimistic um but like with a real solid sense of reality and sometimes people are optimistic and they're like hype men you know and like everything's great when it's not

[1:09:45](https://realalpha.app/v/6v9q6k8aF6E/?t=4185) and then then there's the toxic people they're like everything sucks we're gonna lose yeah well like get those people yeah like i don't have the mental i don't have the emotional capacity for that and so our tactic is uh losing collectively and i think it's really important what i mentioned going back to the beginning and success is a uh as a thousand fathers failure is an orphan uh how can we make failure have a thousand fathers and like how can we make it so that when something goes wrong there's a cultural it's like cultural antibodies come out say we're going to make sure that we never make that same mistake again and i that's our mechanism it's like andy grove only the paranoid survive it's like our way of operationalizing paranoia yeah i think it's very well said and i totally agree with it um i think on the optimism thing like it's very easy to be a default optimist when things are going well yeah you know like the other slice of this is like almost i view it as a responsibility to inject tension and pressure into the system when things are good and then be uh supportive and optimistic when things are tough uh and i think when things are tough i really value like yeah no shit like this bug

[1:11:00](https://realalpha.app/v/6v9q6k8aF6E/?t=4260) just took down our system you know what i mean like it's pretty easy to be down on ourselves and i think we all collectively agree that shouldn't have happened that i wish it didn't happen. But I think that in those moments of like real vulnerability, uh, that's, that's the moment where I like crave the optimism. You want the person who's like, let's go fix this. Not, oh my God. Yeah. I appreciate you doing this. Um, like, can we do it more? Like I would love to do this more. I'm right down the street anytime. Yeah. Where are you? Uh, we're right around like, uh, Right over on 2nd and Howard. Oh, good.

[1:11:37](https://realalpha.app/v/6v9q6k8aF6E/?t=4297) All right. Yeah, we could do like biannually or something. That sounds great. I'd be happy to. There's so much change. Six months is like a year. I was going to say, we could do it weekly and we'd run out of things to talk about. Yeah, absolutely. Good to see you. Thank you. Are you hiring? Any roles that you want to shout out? We're hiring in all functions, engineering, products, our agent development team, which is a mix of sort of both engineering and some consulting roles, sales, We're also hiring in the UK, Europe, Singapore, Japan. So if you are talented, please reach out. All right. Thank you.

[1:12:15](https://realalpha.app/v/6v9q6k8aF6E/?t=4335) Thank you. That's it for now. If you like the episode, please leave us a review or go back into the archives where we've done more than 200 episodes with some fantastic folks. This podcast is a Kleiner Perkins production, and I'm Juven. Thanks for listening. We'll be right back.