Bret Taylor on AI and the Future of Software | Ep. 42

Clearly in three years we could talk about what are the best practices to set up a software team that's optimized for this technology and we'll know what those best practices are and right now

we're just figuring them out in real time and like my hypothesis is the companies that figure it out first will move the fastest. It's fascinating to me.

>> Brett, thanks so much for doing this with me. I'm super excited for it.

with me. I'm super excited for it.

>> Thanks for having me. So you're one of the best people to ask this following question which is what is your view on the SAS apocalypse if we can call it that >> SAS magdon.

>> SAS magdon. But basically it's like you know in public markets all of these companies are trading way down. you

know, you go on X and everybody's talking about how like, you know, software can now be written in 2 seconds and so there's no moes anymore in software. And so it's leading a lot of

software. And so it's leading a lot of people to ask like where does durability come from. And so I just wanted to sort

come from. And so I just wanted to sort of start with this topic because, you know, you've built your own companies, you've been the co-CEO at Salesforce, you're now building like one of the, you

know, fastest growing AI startups there is. You're on the board of open AI. How

is. You're on the board of open AI. How

do you see software like in this moment in February 26?

>> So first I think the market isn't necessarily reflecting an indictment of individual companies. I think it's more

individual companies. I think it's more of a broad view of like the the bigger questions you were saying i.e. every

software stock is down but I don't think that means every software company is equally disadvantaged. It's just

equally disadvantaged. It's just basically anxiety about the future. I

think it's a few things. Um we can talk about sort of defensibility broadly. I

think it's a really interesting question. I think if you look at the

question. I think if you look at the history of enterprise software a lot of the value has gone to the big systems of record. So ERP systems CRM systems like

record. So ERP systems CRM systems like the core databases that Oracle you know sort of famously powered in the early days of of software all and then you ended up with all the software as a

service companies SAP for day sales force service. Now,

force service. Now, >> if you look at what a system of record is, it's essentially a database with a bunch of workflows around it. And to

date, those workflows are manipulated by people clicking on buttons in a web browser, filling out forms. If you had to like synthesize preai, like why were those businesses so good? Was it the source of truth thing and that there had

to be some immutable thing and so the database row? Is that what it was? Was

database row? Is that what it was? Was

it the ecosystem of the integrations?

Like what what do you attribute the success of systems of record to? So I

think the reason why a system of record has always been the most valuable is it is the anchor tenant of your technology deployments. You know if you wanted to

deployments. You know if you wanted to you know create a workflow for quote to cache or something like that you had to integrate with your ERP system and your CRM system. So, as a consequence, you

CRM system. So, as a consequence, you know, the companies that sort of owned those databases could either develop that functionality as an add-on like a new SKU or if it was a third party

company, they would often be a part of the the ecosystem like Salesforce's App Exchange or whatever the marketplace equivalent is for SAP. And so you ended up with a lot of value in those systems

which meant switching costs were just really high because it was sort of this uh that system plus all the partners that integrated with it sort of created gravity and and high switching costs and then similarly you just end up acrewing

a lot of value either by collecting rent from your ecosystem or developing premium add-ons on top. And so it sort of became the sun and the solar system you know for each of the different lines

of business that these systems of record were sold into. And then you'd end up where you'd get a a scale. So you'd get um sales capacity scale, you know, so the larger you grow, the more sales

people you have, you can reach more and more people. Then there's the proverb,

more people. Then there's the proverb, no one gets fired for buying IBM, which uh, you know, obviously a somewhat dated, you know, expression, but it sort of was like, hey, if you're going to put in a new ERP systems, no one's going to

blame you for choosing SAP because everyone chose SAP, right?

>> If you choose something new and it doesn't work perfectly, big trouble.

>> Then you're you're the C. So all those things sort of acrue. But then the question is now that all of a sudden that a lot of those start getting chipped away with AI agents. You know,

first could you just vibe code it in a weekend? So does it change build versus

weekend? So does it change build versus buy? So that's one risk. Does it change

buy? So that's one risk. Does it change when you come up on that renewal? Are

you going to make a different decision?

Secondly, I actually think the more fundamental thing is what is the role of that system of record if AI agents are doing most of the work. So rather than people clicking around on an ERP system to onboard a vendor if you just delegate

to an AI agent to do it.

>> Yeah.

>> All of that is sort of invisible to you and all of a sudden it goes from being an application to sort of a database.

>> Right.

>> Similarly, if you imagine a CRM system and rather than having people staring at it all day to manage their leads, contacts and opportunities, if you just say, "Hey, generate me some leads."

>> In other words, like does a does a system of record have a place in the world if nobody logs into it?

>> And it does. But the real question is like how valuable is it? How important

is it? You know, when you go back to my metaphor on a solar system here, how how important is that gravity versus the gravity of the agents, you know, running around it? And it's just really

around it? And it's just really interesting because if you imagine you're running a sales team, you know, how much do you value the database of leads versus the agent that generates the leads >> and along like ancient history 3 years

ago, those were the same thing. But now

you're like, gosh, I actually probably care more about the lead the lead generation and how it's stored and tracked is actually maybe a more tactical part of it. So there's all sorts and that's true of every system of

record. This isn't you know I just know

record. This isn't you know I just know CRM systems you know pretty well and if you look at ITSM which is like the play source now plays or ERP systems which is

workday SAP Oracle etc >> that all these questions start coming up and so what's interesting though is I think every single one of those companies could transform and benefit from AI. I really do believe that you

from AI. I really do believe that you know you saw what Microsoft did in the cloud transformation and they went from being dependent on Windows revenue to going to active directory and Azure and all those other things but it was really

awkward you know I think folks like you and me back in the day used to probably dismiss Microsoft I mean I certainly did I I did know I didn't foresee them becoming as powerful as and strong as they are today but it was good

leadership good technology but I don't think the market knows like who is Sevil Systems and who is Microsoft in this like landscape of software companies probably no one knows was civil systems

was that was the company that Salesforce beat to become the cloud CRM. So can you actually develop this ecosystem of agents around your platform and you know will it become more valuable than the

platform you had and then on top of it the existential risk of you know is the value of software just going to zero? I

don't necessarily believe that, but you look at all of that and if you're just an investor in public markets, you're like, I'm going to sit on the sidelines on this one. I'm going to let the market play out a little bit. And I think that's sort of what's going on.

>> Yeah. I mean, you can never know for sure who's going to turn into the next Microsoft, but you can kind of try to think about like who has the structural ability to expand like who's got the right with customers to make the

expansions and then which products will be easier. So like you know in the

be easier. So like you know in the database question is it easier for today's databases to build agents on top or is it easier for a modern agent to go say well I'm going to go build a database at some point because I can I

could do that and I've got the customer relationship and how do you think about like what creates the rights to expand.

>> I think all the incumbents sort of have a right to win in a lot of ways. You

know in the same way we talked about you know why a system of record is powerful.

I think you could say the same logic for all the agents running on top. The

dynamic that plays out though, not just with AI, is when a new technology comes out like the web browser or the smartphone. Rarely is the expertise on

smartphone. Rarely is the expertise on how to do exceptional things with that technology at the incumbents. So, first

if you there's this thing in enterprise software, there's a phrase called best of breed and best of platform. Best of

platform means, hey, we're a Microsoft shop. We just buy Microsoft stuff. And

shop. We just buy Microsoft stuff. And

it sounds silly, but actually there's a lot of logic to it. Like a you get sort of good procurement leverage. B,

everything works together.

>> You don't have to deal with a ton of people.

>> There's probably some benefits, all sorts of things.

>> What ends up happening when new technologies come out as you the pendulum swing from best of platform best to back debris because when the new plat when the web browser came out, >> it's much easier to get a 10x experience

>> 100%. And also just think of the like

>> 100%. And also just think of the like pre and post web browser enterprise software like you're running like client server Windows software and like it's a completely different skill set to make a web application as you and I know.

>> Totally. And so at the time like there's this window of time where best of breed competitors are are light years ahead of the incumbents and it's a race. So

basically can the best of breed upstarts y >> turn into get scale before the incumbents figure out the technology and that's what we're going on right now. So

like I would argue very few of the incumbents have any credible like decent AI technology but they will. It's like

inevitable they will.

>> You know what I don't understand? Why is

that? Like what's the real reason for it? is like I see these companies that

it? is like I see these companies that have let's call infinite resources roughly speaking. They ought to be able

roughly speaking. They ought to be able to hire who they want. They ought to know what the products could look like.

They ought to be able to try them. They

ought to be like why is it so hard for like let's say legacy companies to like catch up quickly, you know, versus like an AI startup with 50 engineers seems to, you know, outperform, you know, the

teams that are 10 or whatever times bigger at a big company. Is it cultural?

Is it systems? Is it

>> I like the phrase strategy tack. Uh I I don't remember who to uh attribute that to. We could pull up chatbt and ask. I

to. We could pull up chatbt and ask. I

think the idea is like in these moments of big platform shifts, what were your strengths can become weaknesses. So

let's just take seable systems and the birth of the web browser. They have a you know on premises CRM um system. when

you say okay like let's compete with this cloudnative CRM system in Salesforce you start to say well I don't want to just start from scratch like we've got all these assets so how do we

do it in a way that takes advantage of all of our assets and so all of a sudden you're like okay let's not just build a great product let's transition from this product to that product and what if

someone wants on premises too and you know that's our strength we should play to that strength and you start like basically making all these decisions that like you know sound really clever because you're playing your your

strengths and in practice if the technology wave is bigger than the category which I think the web was as an example you end up sort of basically um chipping away at sort of doing a pure

play value proposition it can also happen with business models though so you know in that time you'd have perpetual license software and moving to software as a service >> that's a huge change for a business to make

>> uh for your customers it goes from being um capex to opex For you as a company, it changes radible revenue. I mean,

Adobe Shanton who did this at Adobe.

Very few companies could make that transition.

>> Yeah.

>> And you have to sell it differently. You

have to compensate salespeople differently. Revenue recognition is

differently. Revenue recognition is different. So you have the product

different. So you have the product strategy tax. You have the business

strategy tax. You have the business model strategy tax. You have even like incentives of sales people. There's a

strategy tax because you know you don't want to just have your business collapse overnight. So you can't just it's so

overnight. So you can't just it's so easy for clever Silicon Valley like just pivot. I'm like, "Yeah, if you're a

pivot. I'm like, "Yeah, if you're a public company, you have to, you know, go in front of your investors every single quarter and be like,"Hey guys, I know our revenue just went off a cliff, but trust me, it's going to turn around next quarter." Like, there you don't

next quarter." Like, there you don't survive that. So, you just compound all

survive that. So, you just compound all those things and all of a sudden you're like, "Why does a 50 person company succeed?" Well, they have none of those

succeed?" Well, they have none of those all of the advantages that you had all of a sudden become anchors that are holding you back from actually doing the

right thing. And that's why, you know, I

right thing. And that's why, you know, I always like to remind our company Sierra that, you know, the wave that we're riding of large language models and this

next generation of AI is greater than any company riding it. And so, like, don't fight AI. It's going to happen with or without us. And if you go back to the internet, if we were talking in

1995 or something and we'd probably like search as a category, e-commerce is a category, oh digital payments, that's definitely going to happen. I don't know which I Google hadn't been founded yet.

I guess Amazon probably had around then, PayPal probably not founded yet. The

categories are obvious. The categories

are like whether or not any of those founders existed, all of they would be winners.

>> And it's the same now.

>> And it's the same now. like everyone

knows what's going to happen and it's like you're competing for the privilege of winning and so in a world where the technology is that remarkably powerful

the strengths of the incumbents start to wither in the face of the technical change and that's why it's you tend to get new new great companies like the companies that are enduring tend to be created in platform shifts more than any

other time. I should be curious on this

other time. I should be curious on this topic of sort of, you know, there's these obvious things and within AI, I would say, you know, no, not to discredit your insight, but support I would count as an obvious thing, like in

a good way, like it looks like it works.

And you did it, you know, early enough that you were able to get, you know, to a place, you know, at the right time, but other people did too. And so in some ways I'm like you have been playing both

in a very blue ocean you know wide field like you know the incumbents are sort of like categorically different and so like it seems like inevitable that we're going to have agents doing support and

so there's that and then on the other side you know a lot of other companies see the same thing a lot of other people have been building it. So before getting into the specifics, I'm just curious

like experientially day-to-day does does your sort of operation of the company feel competitive or like wide open?

>> It feels competitive and it feels like a really big market. Um so it doesn't feel particularly demand constrained, which is a really great feeling as a fellow entrepreneur. It's like you don't get to

entrepreneur. It's like you don't get to >> So you feel like there's lots of demand and there's like a contest with each sort of situation.

>> Yeah, that's right. the way it feels, it feels like there's sort of too much capital available. Uh, put another way,

capital available. Uh, put another way, there's obviously going to be competition in in meaningful markets. It

feels like there's sort of too many competitors that don't necessarily have strong differentiation. I think it's

strong differentiation. I think it's probably healthy though. I think that, you know, uh, there will be a culling, you know, just as the market progresses, but it does feel, you know, quite competitive. I'll just sort of give you

competitive. I'll just sort of give you maybe like a quick glimpse of the past couple years. So, we've had a remarkable

couple years. So, we've had a remarkable growth rate at Sierra. We closed 100 million in seven quarters, 150 millions in eight quarters, which has exceeded my expectations. But this past year has

expectations. But this past year has felt like an inflection point. So the

first year of our company's history, we would often go in and be explaining to clients what an agent was. The term was was novel. Um, and it was part of our

was novel. Um, and it was part of our marketing, explaining what an agent was.

Number two, people be talking about, hey, AI is maybe non-deterministic. They

wouldn't necessarily use that word, but that would be what they would be describing. you know, how can we trust

describing. you know, how can we trust this technology directly engaging with our customers, our consumers? What are

the risks? Now, the conversation is clearly we need this yesterday. I

mentioned this to you earlier, but over a quarter of our companies have 10 billion or more in revenues. We're

talking big companies. We serve most of the Fortune 20 as an example. And so,

these are big companies. They're coming

in saying, "We've evaluated. We know

what we want. Uh we've heard of you.

We've done all this evaluation. Here's

an RFP." you know like let's go and as a consequence because the market has matured and you know by the illustration of the existence of things like RFPs you end up in more competitive conversations

and then it's a question of like why Sierra you know why Sarah and you know I'm happy to talk more about that I mean obviously love to as I say all the reasons are the greatest but you end up in this world where you're not explaining what the word agent any is

anymore you're saying here's why we're the right partner for you which is a very different conversation >> well what I mean so like you know they're like yeah I'm bought in on an agent so like why is it Sierra like What have you found is like the most important thing that makes you win?

>> So, one thing we really did uniquely at SE the reason why over quarter of our customers have over 10 billion revenue is we've tried to serve more complex more regulated industries. You know, we

want we serve most of the US healthcare insurance market as an example and we serve US banks, Spanish banks, UK banks like and these are companies that you know as you if you know the industry

they're regulated by everybody.

>> It's easy to make a demo in AI. It's why

like you can go on X and just see a thousand demos and like demos are cheap but making an agent sort of industrial grade is hard and we've really uniquely been able to make agents that can actually have complex conversations. The

other thing that we do really uniquely is in addition to I think having a really easy to use product is we help companies move faster. Um uh we went live with Sigma in in two months.

>> That's crazy.

>> Which is remarkable. Yeah.

>> I mean how big is Sigma? It's a Fortune 20 um healthcare company and I was on stage with Suchin who's who runs their AI practice there at the health conference and he was talking about this and part of that is like how can you

show up at a like we're really great at AI Sigma is really great at healthcare how do you bring those two together to move extremely fast and so for a lot of our clients like the reason they bring

us on is like can you help us move quick move quickly and that requires knowledge of AI and knowledge of business and I think we sort of show up with a a greater sense of maturity there >> you mentioned like um you know that the

pricing scheme was one of the difficult things you know in the past era >> you know we don't have to like belabor it but obviously you know going from you know just buying a license to a cloud

subscription and now usage based is like the future like what are you feeling as important in you know as you have created and probably continue to iterate on pricing like what are the important

levers for agent companies >> we do something specific at Sierra that I'm sort of an evangelist for which is outcomes based pricing. So it turns out our industry the outcome is usually well defined. So in a service context is

defined. So in a service context is could the AI agent solve the problem? Uh

in a sales context we do a lot of sales agents as well. Could it make the sale?

You probably your company's paid your sales people commissions, right? Like

that's if you can measure the outcome, you want to incentivize the outcome. The

interesting about agencies are autonomous um or can be autonomous. And

so if the outcome is measurable and trackable, what an interesting opportunity to actually charge for that.

And if you look at the history of software, like let's take advertising, we went from impressionbased ads to cost perclick ads to and now for mobile ads, you can do pay per install. At least

that's my understanding.

>> And then you had, you know, enterprise software. You went from on premises

software. You went from on premises licenses to subscriptionbased software.

And you know, could outcomebased software be the next? And what's so neat about that is for a company, what an interesting and accountable business model. And I think there's some

model. And I think there's some challenges to it because, you know, you obviously put some revenue at risk, but I don't think most advertising tech people would say CPC ads put revenue at

risk. It's like the opposite, right?

risk. It's like the opposite, right?

Because the closer you get to the outcome, the more valuable it is for the company. So, they're actually willing to

company. So, they're actually willing to to invest in it. And so my view is to the degree agents have a measurable outcome, outcome based pricing feels like the secular business model for

agents and I think it's quite both disruptive and I think a huge step forward.

>> Why is it better than tokenbased? So

like you know if those are like you know I guess sort of like the two reasonable options now why is an outcome better than tokenbased even over the long term?

>> Let's say you had an AI agent to generate leads for your sales team. What

do you care about? You care about the number and quality of the leads, right?

And so, you really don't care how many tokens the model uses. In fact, it's not obvious to me that like there's a

correlation between used tokens and leads generated. Uh, and in fact, in in

leads generated. Uh, and in fact, in in the same way, there's no correlation in a SAS product between their cost to serve and the quality of the product.

You you can have a really good engineer write it or a really bad engineer write it, though. you really cross the quality

it, though. you really cross the quality of the product. The reason why I don't think tokenbased makes sense is it's charging for an input that is uncorrelated with the output that your

clients actually care about. And I think this is actually uh you know I'm a huge believer in applied AI, but I actually define applied AI as can you describe your value proposition without without

mentioning models. Because if you think

mentioning models. Because if you think about, hey, we can answer the phone and solve 80% of phone calls without human intervention with a seat score of 4.8

out of five. That's you don't mention models. I mean, models are an input to

models. I mean, models are an input to that, but not output. If you have to mention token utilization, it's probably a tool. It's probably not an applied AI.

a tool. It's probably not an applied AI.

It's not an application of AI. It's just

sort of like a tool around AI. And I

actually think that uh the closer you get to a business outcome like it's actually you should charge for the business outcome which is uncorrelated with tokens. And I also think it's

with tokens. And I also think it's almost a measure of are you actually an applied AI company if you can if you don't have to talk about tokens.

>> Do you think that there will be markets either where things get so competitive that people have to price based off of like cost rather than value? like could

that happen or maybe the other format for it would be if you can't describe the outcome cleanly like for example code coding which we probably think is super important obviously it's like a

little harder to say what the outcome is there versus like usage or something like that so like what are the conditions where like tokens do make sense >> yeah so I mean there's this old Apple site where they had sort of like Apple

folklore kind of thing and I think there was this one boss at Apple that made people fill out a form saying how many lines of code did you write? And this

engineer infamously wrote a negative number because he had just like refactored a bunch of stuff. It's my

it's like the good analog historical analog for why tokens don't matter because it was he was it was his way of saying you know the man like your lines of code has nothing to do with my value and he was doing it to sort of

like you know piss off a middle manager to make that point. But it's interesting is like in the world of software engineering, people truly understand like the customers of those right now are software engineers who intimately

understand these models. So there's a little bit of a the customer uh product market fit. So it's a it's a nuance

market fit. So it's a it's a nuance point, but I'll say like where I see it might happen. So right now if you're

might happen. So right now if you're evaluating a software engineering agent, a coding agent, um you're probably comparing it to the cost of a software engineer. um if you fast forward five

engineer. um if you fast forward five years, you probably will be comparing it to the cost of other coding agents. So I

think the second order effect as AI becomes prevalent is you uh you know you're you're just you're you're the reference point for its value will change. The thing I would say is that's

change. The thing I would say is that's true where you're thinking about a cost center, but if you're thinking about topline revenue growth, that doesn't necessarily apply. And if you go to my

necessarily apply. And if you go to my example of an AI agent generating leads for your sales team, depending on what you're selling, a lead is a lead is a lead. Um, and you probably will value

lead. Um, and you probably will value quantity and quality of leads. And

there's a math equation.

>> And that probably will be remain independent of token costs is my guess.

>> And so I think a large part of AI is productivity and and reducing, you know, costs and there's a big part of it. But

the other side of it is outcomes. And so

could you imagine a world in four or five years where you know there's one coding agent that can actually produce something of greater value for your company will you value that or you just

look at the token cause I think probably you'll start looking for value is my guess will they all be the same I don't know you know it's like they well I was just reflecting on over the past year

there have been all these articles about has like AI progress slowed down and then in our world of software engineering it's been the opposite like every new model comes out and you're like, "Oh my gosh, it can write

increasingly complex software." My

theory of that is it depends on what you're testing. So if you're using chat

you're testing. So if you're using chat GPT for trip planning, you probably haven't seen a material change over the past year and a half because you reach sort of sufficient intelligence for trip

planning a long time ago. If you're

using an AI to make write rest code, >> codeex is like mindblowing right now. So

I think the one of the interesting things when I think about like second third order effects and like the progress of AI is you know where you will you pass the horizon where like every model is sufficient in that task

and then there'll be some things where like the frontier continues to move and it's hard to imagine but it's just like we're in a crazy time.

>> Where are we at with support agents right now? Like is are there still edge

right now? Like is are there still edge cases last mile things like that AI can't do still? Yeah, we are though I imagine a lot of the technical problems

uh as opposed to product problems will become easier but there there's a lot of them still. Um so you know we at Sierra

them still. Um so you know we at Sierra support most spoken languages in the world and you know if you want to support um Cantonese and Tagalague most

of the good voice models you know don't come from like the traditional western model companies. Um, similarly, one of

model companies. Um, similarly, one of our clients has Safe Light Autoglass.

So, it's like roadside assistance. And

it turns out that like car horns, background noise, kids talk in the background, you know, are actually all fairly hard uh problems to solve. And

even in some of the advanced voice mode stuff, if you are in a noisy environment, it it constantly thinks it's being interrupted and things like that. So, you end up having to build

that. So, you end up having to build proprietary voice activity detection, multiple speaker detection, all these other things. We develop all this

other things. We develop all this technology because we need to be the best now. And I think we are the best

best now. And I think we are the best now. And you're like, okay, that's

now. And you're like, okay, that's probably going to be a commodity two years from now, one year from now. I

mean, who knows? But you have to do it because you need to be the best at every stage of your company's existence. And I

think then you're the way we think about the world is we have a product which is called agent studio or agent OS. And

we're going to make the in three years you'll judge us by our product. And

right now we're probably they don't our clients don't really put this way judged by the technology. But if you go back to 1996, I remember when Netscape had a web server and Apache was new and like no

one cares how you serve web pages now.

Like it's a commodity, but at the time that was what you sold and now you have increasingly higher order website building like Shopify. So I just think the AI agent market is going to take that progression. We're going from a

that progression. We're going from a tech ccentric sales cycle to a productcentric sales cycle.

>> It's interesting that you're obviously having to be the best at something that you know is going to get commoditized.

Yeah. Yeah, which is probably not something I don't know if you ever had to experience something like that. I

mean, for that to be true, you just have to be in the middle of an insane rate of change, but that means you have teams who are putting like, you know, a lot of their life force for 2 years into something that everybody knows is just

for 2 years, but it still matters nonetheless.

>> It's crazy. I mean, if you look at traditional, I'll just say enterprise software, consumer is a little different, but you think about you're building up this asset, your intellectual property. There's a fancy

intellectual property. There's a fancy name for it. It's like look at this platform that we're building and like we took so many years to build it and it's got all these features >> and now you're like I'm building this

and I'm 100% certain we'll throw it away in the next 4 months but I have to build it because if I don't I can't serve the bank that has a big you know business in Hong Kong or whatever it might be where

they we need Cantonese support.

>> So that is the reality right now. So I

actually think I've been thinking a lot about this actually just because I think it was Toby Luki who sort of said something provocative around you know when generating the code is is easy it's

almost like the the system and the prompts that are actually the durable asset. Uh you know put another way could

asset. Uh you know put another way could you sort of terraform your software from scratch you know it's the prompts that led to it. I do think that is sort of the software of the future in a lot of ways where how do you encode the

infinite number of little product decisions that you made um because so much of that is encoded in in code today. Uh I mean if you think about like

today. Uh I mean if you think about like a product requirements document versus the code what percentage of the uh emergent product that comes out of his encode almost like 90% like a lot of the little details

>> are in there. I think a little bit it's like software companies of the future and the products that they make are just going to take a really different shape uh in the future and I I'm so excited to be a part of it. I I mean I think it's

really fascinating. I think there's

really fascinating. I think there's something really interesting about AI impacting the software engineering industry almost first and most because

>> like we're disrupting the craft of making what we're building in real time and it's fascinating. It's like a fascinating time.

>> I think there's a prevailing idea in tech that AI is moving so fast that like young founders have this massive advantage and I mean this with no offense. You're not old but you're also

offense. You're not old but you're also you're not tell me I'm old. No, you're

not the youngest founder and you have one of the most successful AI startups there is >> and it does seem like you've brought a lot of your previous experiences >> to what you're doing, but I can tell

from talking to you that you also are just rethinking everything. And so I'm curious your own experience for yourself and for other founders you look around at like do you think by and large young founders have the advantage? What does

it take for more experienced founders to have the advantage? You know, I'm always a big believer there was I don't know if it's a real quote, but I some VC said, you know, like uh why was this, you

know, founder able to, you know, conquer this market where so many others had failed? And they said, well, he was too

failed? And they said, well, he was too naive to know it couldn't be done. And

there's a certain element of that that I I love because you end up with this kind of naive that is actually sort of a form of principled first principles thinking that a lot of young founders have. you

know, you just don't know why this messy bad product, you know, dominates the market. You think there's a better,

market. You think there's a better, faster, cheaper way to do it. And

because you you don't have any of the hard one lessons that can end up uh, you know, oversimplified analogies keeping you from actually taking that leap, you can end up with, you know,

Tony made Door Dash and didn't care about, you know, say Web Vans, Monzo or whatever. I can't remember all the the

whatever. I can't remember all the the the bubble companies, but I do think especially in enterprise software, uh the experience that that some of our

team members bring, including the old man, me and Clay, bring to it really does matter. You know, part of the

does matter. You know, part of the reason we're able to serve, you know, so much of the Fortune 100 is we can go into a bank or a healthcare payer, healthcare provider, a revenue cycle

management firm or a big telecommunications company and understand their business under we're working with one large medical device companies consolidating 40 of their call

centers into one and we can have a discussion about like the change management of doing that and that's not really a tech problem but it does require you understanding business and I

think if there's like we always joke at Sierra it's like the the ven diagram like there's a circle of people understand like next generation of AI and people understand business and we're like the company right in the middle of

that maybe the only one and that matters because I don't know there's that sort of infamous MIT study saying all these AI projects fail it's like none of ours do and that's our value proposition like

we can actually help you go live and I think the experience has benefited us then >> yeah I'm curious like if you can point to what has created the lead you have so far. And obviously I know you're just

far. And obviously I know you're just getting started, but at the moment you do, you know, you've you've you've pulled away in a big way. And um I'm sure there's a lot of just like daily blocking and tackling, but I'm curious

if there are any like foundational decisions that you've made or strategic approaches that you know over the last couple years you look back at and you're like that was pretty essential to make this happen.

>> I think there's two almost independent um areas of investment. not not they're not independent but they're like uh very different. One is the product and one is

different. One is the product and one is our sort of our go to market and partnership model and they're both really intentionally built. On the

product side, we've tried to balance ease of use and extensibility because when you serve really large companies with very comp that been around for 200 years, you know, you need to work with

mainframes, you need to work with a thousand different systems. You've done 10 acquisitions. There's all the like

10 acquisitions. There's all the like enterprises are messy. And so that's why you tend to have, you know, most uh I'll say enterprise software that's designed for larger companies tends to be quite

extensible. often that extensibility

extensible. often that extensibility comes at a cost which is is it easy to get up and running and so as a product designer like one of the things I've just spent a lot of time thinking about

is like we're trying to have our cake and eat it too like can you go live in 2 months and still be maximally extensible and I'm really proud of the product that we've built and some of that is born from experience of what does extensibility mean and I think we have

an opinionated view of what it means and have been able to accommodate like some fairly exotic deployment requests and still do it fast. That's really unique.

The second thing is our go to market and partnership model because we knew when we started the company we wanted to work with the largest companies in the world.

Not only but we want to be able to work with the largest companies in the world and have focused on that and as a consequence we just have a really unique partnership model. Um there's sort of a

partnership model. Um there's sort of a fashionable thing to talk about forward deployed engineering in Silicon Valley.

We don't call it that and it's a very unique model because it's not all about technology like most of our clients build and maintain their agents themselves. is pretty easy to do, but we

themselves. is pretty easy to do, but we show up and we help you be successful.

And so it's like we'll just show up like we're not going to let you fail. Like

and I think that is a very different because we have this outcomes model, outcomesbased pricing model. We don't

get paid unless it works. And so

>> how much of that is technical versus like change management?

>> It's a mix of both. Uh you know, I don't know if it's 50/50, but >> do you do it as two people or it's one person who does both?

>> We have a mix of roles. Uh we've sort of evolved that. Uh we try to hire really

evolved that. Uh we try to hire really technical people in all roles though because part of our our secret is we want we want to be like be your trusted partner in AI. So you want the person

who is working with you every day to be the most knowledgeable AI person you know.

>> It's like a like a forward deployed change management engineer.

>> Yeah. Yeah. Exactly.

>> It's crazy what we're doing.

>> And so and what's really neat about it is if you're like a really talented technical person who wants to go transform an industry you can do it at SR. you can go in and like we're working with most of the healthcare insurance

companies like you want to change health care costs and you know like what a cool vantage point to do. So we've been able to attract some really remarkable people too.

>> You said that it's not just support agents now.

>> Yeah.

>> So like what else are you finding shoots in?

>> I'll give you one of my favorite relationships with the Rocket. So based

in Detroit, remarkable story. Uh you

know their founders done more for Detroit than I think any one person's done for any city. Just like remarkable company. But they own Redfin, which is a

company. But they own Redfin, which is a home search site, Rocket Mortgage, which uh is like the number one consumer mortgage originator in the country. And

then they uh bought a mortgage servicing firm recently as well. And you can go to redfin.com and use an AI agent to search for a house. You can go to rocket.com

and finance that house with an AI agent.

And then you can with the acquisition they did this mortgage service firm, you can then when you're servicing your mortgage, you'll talk on the phone with an AI agent as well. So like everything from finding a house to originating the

mortgage to servicing that mortgage I think is pretty cool and like >> they have an amazing CTO named Sean Mo like pretty visionary uh and I love their co Vune too but it's like everything from finding a house all the

way through servicing. It's kind of what we believe a lot of businesses will do is like look at their entire customer life cycle from uh you know I'll say purchase consideration which is a fancy

way of saying like browsing I think homes are probably one of the more considered purchases that you could do through executing the purchase through having issues with it all the way through you know retention and for a lot

of for example a lot of our telecommunications customers their AI agent is actually doing negotiations so like you've probably negotiated your cable bill at some

Yeah, probably. And so agents are doing

Yeah, probably. And so agents are doing billions of dollars of negotiations for everything from, you know, satellite radio subscriptions to cable television

subscriptions. It's pretty cool. I mean,

subscriptions. It's pretty cool. I mean,

it's like really uh, you know, over a billion dollars of mortgage, >> just like all transactional communications eventually.

>> The way I think about it is website is a technology, but your.com, the one with your brand at the top, is your website.

We're sort of doing that for agents.

It's sort of like agents will do a lot of things. The one with your brand at

of things. The one with your brand at the top that your customers go to, whether it's buying or servicing, we would like to help you make that. And I

think it's it's an interesting as agents go, um, it's pro often interact with other agents, right? If you think about a a home and auto insurance company, you

know, you may have a claim adjudication agent, you know, that's quite complicated. So our agent that's having

complicated. So our agent that's having the phone conversation when you're on the fender bender will interact with that >> but it is almost the intersection of all of the that technology because it's sort

of your your front door and our whole hypothesis is every company need a website in 1997 every company needs an agent in 2027 and like we want to be that that company.

>> What's the nuance about like agent builders though because I know you have like a view that like just being like a generic agent builder is not the right thing. Yeah, I mean I've been surprised

thing. Yeah, I mean I've been surprised how many enterp like large income enterprise software companies like their first foray into AI was you can an agent

building tool. It just feels inevitably

building tool. It just feels inevitably to be a commodity in my mind because uh you maybe making a website was hard in 1995 but today there's like a million ways to make a website. Most of them are

open source and you have like cool companies like Burcell which I love but it's not like there's a huge market for this stuff. Um and and in practice I

this stuff. Um and and in practice I think the same will happen with agent building. Um I think OpenAI will have a

building. Um I think OpenAI will have a great tool. Probably all the foundation

great tool. Probably all the foundation model companies will there will be open source packages like Langchain and Langraph.

>> Mh.

>> The idea that you you have the right to win there. I don't know if anyone has

win there. I don't know if anyone has the right to win there just because it's just a technology. It's a horizontal technology and I just believe in open source and it's just going to become a

commodity. So my belief where there's

commodity. So my belief where there's value is really going to be in agents that do things and you'll uh hire those agents and purchase those agents for

what they do. So I believe in companies like Sierra. I believe in companies like

like Sierra. I believe in companies like Harvey. I really admire what they do and

Harvey. I really admire what they do and you know they have an agent that will do an antitrust review. Uh you know I think there will be a finance agent that audits your financials. There will be

one that helps you onboard a you know supply chain vendor. there'll be one that uh you know if you just think about onboarding a new vendor it's like there's a procurement process there's a legal process there's a contract review

process whether or not it's completely autonomous or human in the loop all of that could be augmented with an AI and I'm like that's a product yeah >> agent building is not a product agent building is a technology

>> yep speaking of the platforms um aside from being the founder of CI you're also on the board of openai you're the chairman there I wanted to ask you specifically about codeex like over the last you know couple weeks it's been

unbelievable believable. It's like, you

unbelievable believable. It's like, you know, a curtain just came down. Did you

expect this? Like, did you think that what has happened here was going to happen or like when did you start to have an inkling that like code was going to go vertical like this? I'll say yes, I expected it just because you know

being on the board of open we talk a lot about it and all the labs uh uh enthropic and openi in particular talk a lot about using coding agents to help

build AI and and certainly like building an AI researcher is an important part of building an AGI lab. The weird part about for me as someone who is a

software engineer um I didn't feel it until I used it. So you like you can talk about it all the time and then like the first time you oneshot something and

it turns out like really good and not like slop but like really good. It's an

emotional experience I think. I mean for me it was it was just sort of like holy like this is real.

>> Yeah.

>> As you said it's really over the past 3 months that has felt really materially different to me and I've been thinking about it a lot. Um, I was thinking about

the past 20 years of software engineering. Um, I remember the first

engineering. Um, I remember the first time I uh worked on an engineering time that had real CI/CD where you'd check in code and it would just automatically end

up into production. And I remember how I'll just like if you've ever worked an engineering team that did that versus one that did manual releases, it's completely different because to have

something that can safely go from commit to production, there's so many things that have to happen to make that work.

You end up relying a lot on testing. So

both unit testing, integration testing, and canary testing because the last thing you want is someone clicking a button and taking down the service. And

it's almost impossible for a team that is doing manual releases to convert into CI like true continuous delivery because there's so many implied processes that

are incompatible with that. It's like

easy to start that way and and very hard to work. So I've been asking myself

to work. So I've been asking myself clearly in three years we're going to like if we were talking we could talk about what are the best practices to set up a software team that's optimized for

this technology and we'll know what those best practices are. And right now we're just figuring them out in real time. And like my hypothesis is the

time. And like my hypothesis is the companies that figure it out first will move the fastest.

>> Yeah.

>> And and the other part of that the companies that don't will move much more slowly. It's fascinating to me. Uh, and

slowly. It's fascinating to me. Uh, and

Andre Carpathi, he had a really interesting post about this too. Like I

think a lot of folks who are sort of like in deep here have been thinking about it and it's fun to see the industry you love sort of flipped on its head and >> yeah in real time. Well, it's

interesting because like I think people like you know software engineers on one end and then like say somebody who's like you know in you know some part of the country where AI has not yet kind of

like gotten it 10 fully extended like there's like a wide gap in people's current sort of comprehension of like what AI is going to do. And so I think you know it's like it's a little bit unknown like you know there's a lot of blog posts going around right now that

are breathlessly saying like it's all over. I think you know I'm probably more

over. I think you know I'm probably more in the camp of like maybe software is like I don't know sol people you know use the word software is solved. I don't

know if it's that, but I'm curious if you have a view on like if codeex and cloud code and sort of like the the latest in coding. Is that going to change the way companies are built? You

know, like one easy strongman question there would be like, you know, people have been claiming that there's going to be my brother, you know, these 10 10 person billion dollar companies, you know, is that are we at the precipice of

that? Does that make sense? Are there

that? Does that make sense? Are there

other changes? Like what's going to happen now? There probably will be a 10

happen now? There probably will be a 10 person billion dollar company, but I don't necessarily think it'll be the norm. Uh, and the reason for that is

norm. Uh, and the reason for that is competition. If you imagine like the

competition. If you imagine like the mobile phone market in the United States, there's three main competitors, Verizon, AT&T, T-Mobile, and they're all competing for a fixed pie of mobile

subscribers. And it's why it's extremely

subscribers. And it's why it's extremely competitive. There's promotions, there's

competitive. There's promotions, there's ads.

>> They can't make more of us.

>> They can't make more of us. They can

build up their network. they can do other pricing, packaging, uh, and and it's a really complex business to run.

All of them have access to AI, every single one. So, the idea that you could

single one. So, the idea that you could deploy AI and, you know, not have to do things you were doing currently because of AI is probably true. But if any one of them figures out a way to use a

person to gain market share against the other one, they're going to do it. And

then as a response, their competitors will do it, too. And that's how, you know, we spoke about this earlier, but it's the reason why when automated teller machines were introduced to banks, the teller job went away, but

there's no fewer bank branches and no fewer people in those bank branches. And

it's because, I don't know if it was JPMC or someone figured out, hey, if we put financial advisors in there and other things, we can actually make more revenue per branch. My personal take is

in a competitive market, and that's the key, by the way, you need competition.

So people can't just pass the cost savings on to shareholders or dividends.

The second order effect of the efficiencies of AI will be investment to compete lower prices or customer acquisition or whatever it might be.

>> So we want fewer engineers per company will just they'll be way more productive and so you just end up with way better software >> or you might have fewer engineers and more of something else or you might have more engineers. You know, I don't I'm

more engineers. You know, I don't I'm not sure, but it's it's the idea that like it will be what it is today, but just more efficient, I think, is like a lack of imagination in my opinion. The

interesting thing though is the other part of this software engineering does feel special and I think people extrapolating too much from software engineering or it's a bit simplistic.

>> You're like the same thing might not happen to every other function.

>> I'll just be really simple about it, which is finance and software engineering um might be limited by intelligence. uh meaning they're largely

intelligence. uh meaning they're largely digital um they are largely like manipulating sort of digital things to and and you could imagine AI automating

that most of the economy isn't digital like exclusively uh so you know if you need to ship something a t-shirt from Vietnam to here yeah you could automate some of that stuff but at the end of the

day like that that cargo ship still needs to be in the water and I always bring this up you know like just imagine you run a pharmaceutical you know you can think about >> you know how to make a therapy you

probably need a wet lab so okay well that's intersects the real world maybe you could do robotics but then you need a clinical trial and then you know so just a lot of the economy is like real and so it definitely will change the way

companies are built but I think when people say everything will be 10 people >> maybe just the stuff that lives in bits >> that's right which is a lot of the economy but not the economy >> yeah I mean I was you know it's easy like to talk about this but you're right

like if you just move around the physical world and you get off of, you know, this podcast and, you know, this computer I'm sitting in front of and all this stuff and you go into the world and there's like, you know, trucks moving

dirt around and people who need a building that has lights in it and all there's like a lot of physical things and I I kind of tend to think that the value of that stuff's all going to go up until maybe robots happen. But in

general, I think, you know, the value of bits goes down, the value of stuff goes up potentially.

>> That's I think you're probably right.

And uh and some you know like robotics will have a big impact as well but I think people are thinking about this a bit simplistically is my my take and I think intelligence is clearly on the

cusp of going up exponentially but it doesn't mean adoption of like that can't be absorbed by the economy >> perfectly exponentially and so I just think people are a little bit

simplistic. Do you think there's any

simplistic. Do you think there's any cognitive things that are immune from intelligence? So like um Dylan Field

intelligence? So like um Dylan Field when he was on this podcast gave an example of like Brat Summer as something where he was just like that would have been such an insanely hard call for an

AI to make and you needed so much context and taste and opinion. You know

where my head was going is okay so coding is you know whatever's happening there is happening there but what about like brand or storytelling like and I'm kind of asking you this both as an

operator and as you know somebody who's very you know deep with open AI like do you think that these other parts of intelligence also you know go the way of AI?

>> I don't know if taste is necessarily related to intelligence. uh you know it might be but um I've got three kids including a 16-year-old and a

15-year-old and when they decide what they're going to wear to school I don't think they will they will consider chat GBT's opinion they care more about what

the person in class next to them is wearing similarly uh if you go to the most like elite competitive college preparatory

school or the worst school in the world there's always going to be the smart kid in class and the dumb kid in class and the strong kid and the fast kid and all these other things and like it's all

relative and it's all very local and it's all very human and so I think the idea that because AI is smart it takes something away from us as humans I don't

necessarily subscribe to uh I don't you know uh you I was you all see these things that go around online where people are sort of lamenting older technology like the bicycle and you know

we've been weaker than machines for my entire life >> and I don't I don't think it like it doesn't make me feel like weak as a person and I think we this for the first time we have computers that are going to

be more intelligent than us. I think

there will you know the emotions I had about codecs writing code that was high quality wasn't experienced because you know I I might have some of my identity

tied up in that task. Yeah. And the next day I woke up and I'm using it as a tool and now I can make better software. I'm

like this is great. probably actually

like a good like self-actualization anyway to go through that and be like, "Oh, I'm not my ability to code."

>> I think this I think people's vocations and their identities are often very intertwined. But I think once you absorb

intertwined. But I think once you absorb the technology, I don't think it's actually your identity. And so I think I actually am quite optimistic that we will be human. We will all be status

seeking animals. We all compete for the

seeking animals. We all compete for the real estate here in San Francisco. And

even though our standard of living will go way up, we will all be jealous of people still, we will all compete. And

as a consequence, I think humanity will be just fine. Uh that's my view on it.

And I think it's just hard to imagine, but it doesn't mean it's it's going to be catastrophically bad. I just think it's actually I think will be largely good for humanity.

>> I have a friend who believes that like as this kind of progress, you know, we're already everybody's already completely addicted to their phones and it's a disaster and whatever. Now you

have all this AI happening. A friend of mine was saying that he basically thinks that it'll actually become a status signal to become increasingly offline.

And I'm like actually that might be an interesting call. Like I do think that

interesting call. Like I do think that like people will kind of hit a tipping point with a lot of this stuff where like all of it will happen like intelligence will get so good and then people will sort of just be like enough of all of this and like hopefully

there's a big screen time reduction you know and it's like you saw like parents were revoling on social media like about social media for their kids and like a bunch of schools and all the parents like nobody take a phone like everybody

agree to it. So, I think that'll be an interesting thing of like does humanity like does is there like an essential humanity that like gets sharpened?

>> I hope so. I actually one of the things you know I I love the iPhone is one of the greatest inventions of this century.

I hope we're not staring at a glowing rectangle and and you know now that AI can talk to you and human computer interfaces like so this is my point. I actually think

hopefully humanity can become more self-actualized you know as a consequence of this and that is the purpose of technology. Um so you know just like the industrial revolution had

leites and uh globalization led to job loss in the rust belt of the United States but certain goods got less expensive in other parts of like these there's not going to be no issues. I

think it would be insincere to imply just really accelerate humanity in a really positive way. And I think that

for me and I think for like if you're thinking about how does this impact me is like have a more um flexible view of your own identity like the what how you do it every day doesn't define you. I

always like the metaphor because it was so obvious before and after. Imagining

being an accountant before Microsoft Excel and after Microsoft Excel. Yeah.

>> So much of the act of being an accountant was like adding up numbers and things, you know, and now it's like building a model. And it's not like what you did like the value you provided didn't change, but actually the act of doing it is completely different. Like

the skill set is completely different.

And so I think we're just like a lot of us are just going to go through that in a very compressed period of time and it's okay. It's just a little anxiety

it's okay. It's just a little anxiety >> written. Yeah, it makes sense. My last

>> written. Yeah, it makes sense. My last

question about AI. There was a shot from Anthropic at OpenAI around the Super Bowl commercial about the ads which was they were good ads. They were funny. Um

but then it I think sparked like a debate around sort of like the whole topic of like what is the role of these foundation labs and um how should they

sort of like bring AI to the masses or not? What's the appropriate business

not? What's the appropriate business model? What are the trade-offs of all of

model? What are the trade-offs of all of this? you've obviously like you know you

this? you've obviously like you know you have experience with social networks and a lot of different pricing you know models you know open AI well you know you know how to consume AI so I'm just

curious how you think about this and like what is the right thing when you consider like a lot of these dimensions >> I'm very optimistic about ads done in

sort of a tasteful way um you know I started my career at Google I think I arrived like the day AdWords came out so and it was just interesting because when I started there you'll laugh at But like

everyone in my family when they found I was working there was like how do they even make money? I laughed just because I was I think I listened to the Acquired podcast. It's literally the most

podcast. It's literally the most profitable business ever created.

>> But as a consequence you know Google is widely available for free for people who want to use it and has created an economy around it for demand fulfillment advertising. I think there's reasonable

advertising. I think there's reasonable criticisms of advertising. you know, if it starts to get in the way of the sanctity of what the AI is recommending you, which was sort of the um, you know,

backhanded implication, but I just think it's not true. And so I actually think if ads are clearly labeled and, you know, not maintain the experience,

>> I think it's really aligned with the the Open Eye mission because our mission is to ensure artificial general intelligence benefits humanity.

Obviously, the most important part of that mission is safety. But after you get back the hypocratic oath, first do no harm, the job of a doctor to cure you. So then after you say, "Okay, it's

you. So then after you say, "Okay, it's safe." How do we widely distribute it?

safe." How do we widely distribute it?

And I think we have an obligation being a missiondriven, >> you know, I'm I'm the chair of the foundation and on the PBC board. Like

>> our mission matters and being able to offer it for free widely is a huge part of that and we need to be able to to afford that.

>> Yeah. I think it's not only I just I find it inauthentic like I'm like this is an incredible opportunity to provide this at scale to society and I think the idea that it will somehow t the

experience is strong >> you know like I grew up in like suburb of St. Lewis and you know so it's like a

of St. Lewis and you know so it's like a whole different world than like you know what we're in now and it's like when I think about like you know people you know that I grew up with or you know from just other parts of the country 20

bucks a month is a lot and I think you know it's easy to forget in our ecosystem that like not everybody wants or can spend $20 a month on stuff but they really want these services like you know if the whole world had to pay for Google like that'd be a worse world like

it's really good that everybody has access >> and I just think it's important we do it well and >> yeah we will people want good ads Like I like good ads. Like I would actually if people bring me the right product, I'm like that's really nice.

>> This is the other part of it is like you want businesses to be able to grow from scratch. There's such a purpose of it.

scratch. There's such a purpose of it.

It just needs to be done in the right way. So I I find the discussion not not

way. So I I find the discussion not not particularly authentic.

>> Yeah. Yeah. The last thing I wanted to ask you about was um how you've chosen to sort of like finance the company. And

I guess I'm curious about three parts which are how you got started and you know working with Peter Fenton and then like what you've done since then to date and what's been important for you and then I'm curious just like as you think

about the future like what's important to you as you think about other partners or capitalizing and you know I'm asking just cuz this is a podcast has a lot of VC in it so I got to have a little flourish.

>> Yeah totally. Um we have uh three members of our board which are sort of represent kind of like our kind of three rounds of investment. So Peter Fenton from Benchmark, Ravi Gupta who just left

Sequoa though he's still a venture partner there and Neil Meta from Green Oaks.

>> Um just a fantastic group of people >> and chose them all both for the firm and the person. Um but notably like Peter

the person. Um but notably like Peter I've worked with both my previous companies. So, uh, you know, our first

companies. So, uh, you know, our first round of financing, I didn't talk to anyone else. And, uh, introduced him to

anyone else. And, uh, introduced him to Clay, my co-founder, who hadn't spent time with him and, uh, we talked once, he sent me a term sheet, I signed it, no

edits, and it was like a very much a, uh, trust relationship. And, um, it is interesting like one of the things I really have appreciated about so there's some downsides to Silicon Valley and our

our, you know, how insular the community is. One of the great parts though is

is. One of the great parts though is just like the relationships you can forge over years. And for me it meant Peter and I could sort of start on third base just because we had worked together a lot before and so you just don't end

up with a lot of the there's no no funny business in the fundraising process, no funny business in the boardroom. It was

just like let's get to work and uh it's fun. It was fun to you know sort of get

fun. It was fun to you know sort of get the band back together there. But the

fun part for me is I had never worked with Ravi nor Neil before and like Clay and I just it's like it's just it's just a great board. like it's like people we

seek out advice from as opposed to people we report to you know every quarter. So it's amazing.

quarter. So it's amazing.

>> How do you think about cuz you're both like known like you know when when open we won't go back through the story but like you know when OpenAI had its like oh my god moment like Sam was like you know right you got to like you're like the board member and then you've also

got a board that you're so you're you're in both roles at once. How do you like make the most out of a board? like you

know obviously you've got these particular relationships but like what do you expect that relationship to look like?

>> First I really like written documents for boards over presentations both as a board member and as uh like a a founder of a company because you end up letting

people synthesize information ahead of the board meeting. So you end up with more substantive discussions in the boardroom. I've done this for the last

boardroom. I've done this for the last two companies I've started and it's just been great to send out a, you know, a board document. Sometimes people will

board document. Sometimes people will comment of the meeting, but I actually think the main thing is it's been read and it's been read ahead of time and then you end up with a meeting about the actual meat and potatoes of the topics.

You're not like staring at a bunch of sales numbers for the first time. You're

not running through slides.

>> You're not running through slides. And I

find it to be incredibly I I think most companies should be run um this way. The

other thing that is really interesting is like don't write it with AI. It's so

funny to have to say that now, but I find that >> the process of the writing, >> the process of the writing is a process of clarifying your thoughts. And so for Clay and me, this is a process by which we synthesize what's been happening. And

you know it, you talk about it, but to actually write it and write it eloquently and concisely is incredibly important because it's essentially a way of, you know, it's like what's that famous line? If I had more time, I would

famous line? If I had more time, I would have written a shorter letter like spend the time because that's actually how you can show respect to your stakeholders that you're thinking about the strategic issues going on in your business. And

the last thing I say is um board members aren't sort of single issue voters, but they everyone has their strengths and you know at at OpenAI we've recruited a pretty diverse set of skill. Ziko

Coulter is a professor at CMU who's a uh specializes in among other things jailbreaking. So just like one of the

jailbreaking. So just like one of the experts on some of the more subtle safety aspects uh Nicole Seligman was you know a great attorney and you know she's an expert in a lot of like legal

issues and what's really nice is when you grow out of board you know beyond sort of your initial investors too is find people that your management team will want to go to for advice. Obviously

the audit committee chair and your CFO have a really unique relationship um but you really want folks like who's your head of sales going to go talk to? Do

you have someone who's like kind of been there, done that? Because you want them to have that kind of like I always think of it as like who are the adviserss? You

want to surround your management team well. And I think a functional board

well. And I think a functional board really has those relationships. And then

when you're in a board discussion, you have all these board members who have had lots of engagement with the company, but in a really valuable kind of targeted way. So I like to think of the

targeted way. So I like to think of the board as a collection of people. Don't

look at the individuals. It's a it's a the whole should be greater than the sum of his parts. anything this year you're particularly excited about that you can share?

>> I think the real exciting part is going to be adoption in regulated industries.

Uh I think we we're moving beyond like the early adopters to everyone. And so I think if we have if we talk a year from now >> you're doing the hard stuff.

>> It's going to be like the really hard stuff. Um and

stuff. Um and >> I have if you want like a hot take you I think my intuition is regulators will start asking for agents. Um, the idea that you have a human set of controls

over a regulated process will uh start to feel like a risk rather than the risk being AI. And that's my I don't know

being AI. And that's my I don't know it'll happen this year, but I think that will happen.

>> All right. Well, I'll call you in a year and we'll do take two of this and see.

Sounds great. All right. Thanks so much for doing this, Brett. This is great.

>> Thanks for having me.