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- [00:01]
Patrick Collison
Brett Taylor is the ultimate Silicon Valley veteran. He was one of the creators of Google Maps, invented the like button, was co CEO of Salesforce. He pushed through Elon's acquisition of Twitter when he was on the Twitter board. He's now the chairman of the OpenAI board and his day job is founder and CEO of Sierra, which is bringing AI to customer service. He's one of the smartest people I know on the topic of how AI is changing established companies. Cheers.
- [00:22]
Brett Taylor
Cheers.
- [00:26]
Patrick Collison
So, most important question, have you installed OpenClaw on your work laptop?
- [00:30]
Brett Taylor
I have not.
- [00:32]
Patrick Collison
Have you played with openclaw?
- [00:34]
Brett Taylor
I have played with openclaw. I haven't bought a Mac Mini. You can put these things in virtual sandboxes for less money. It's really interesting. I mean it's very compelling. It's probably the first, I wouldn't have predicted the first kind of broad. I don't know if consumer is exactly accurate, but maybe a hobbyist use of AI would have been this kind of semi rogue open source project that goes through three name changes in three days. And I love it. I love everything about the chaos of it. Just because people in our circles have been talking about AI agents for consumer use and all these fancy computer using agents and instead you're chatting over WhatsApp with a thing on a Mac Mini that is mildly unhinged and insecure. It's just fascinating. The whole thing is fascinating.
- [01:24]
Patrick Collison
But isn't that okay? The thing that seems to me is funny is if you look at the landscape still in 2026, if you open a new Gemini Chat or if you open a new ChatGPT chat, it's basically a blank slate. There is no memory. And then, I mean KLAW people Talk about the WhatsApp and Telegram integrations and things like that, but it feels to me a big part of the value is not only can it do stuff proactively, but it has memory. But the way it has memory is this super janky. It's like movie memento. It writes things to a markdown file and it's just writing the things to rem. And the compaction is kind of buggy. Like you didn't always write down the exact right things to remember and stuff like that. But isn't it funny that you can get super polished mainstream consumer apps that have no memory at all or this wildly insecure three name changes project that kind of almost remembers things by scribbling notes in the margin. And that is the state of consumer AI.
- [02:22]
Brett Taylor
I have a probably not very thoughtful, but kind of Technical theory on this. So coding agents have gone through a transformation over the past four months. Like the difference between if we were here in October versus now, our conversation about the future of software engineering would be materially different. And how often can you say that about a technology and people? Always in my circles. Anyway, you look at a coding agent and you extrapolate to other domains. You're like, could all digital tasks be like this? And the answer is obviously yes, over some period of time. But it's really interesting because I think sometimes I think the hard part of engineering is in the details and code. Repos have very specific qualities. One is all the context is in one place in files that are largely textual, not binary. And for most broad information tasks, that's not true. You're making like when you were writing your annual letter. My guess is the sources of information are in so many different systems, data warehouses. And so it's not like impossible for an agent to use those things. But the idea that you can like straight line from coding agents to writing the stripe annual letter, I don't totally buy. And then similarly, when the agents actually perform your work on a code base, there's feedback, there's compiler errors, there's often unit tests, there's integration tests, there's the history of every change, every made in a really formal format, along with code reviews. And so you can actually, it's almost designed for a robot and you can self reflect. Maybe we as engineers are sort of like have always modeled ourselves after robots and now we can actually fully realize that vision. So what's interesting about it is like the idea that it wrote a markdown file for memory I think is maybe more significant than a hack. I actually think to some degree.
- [04:15]
Patrick Collison
Turning your life into code, kind of.
- [04:16]
Brett Taylor
Yeah, it's like you almost want to put all everything in a file system that sort of looks like source code. Not because that's the only way these agents can work, but actually it's quite an efficient way to get a mix of context and random access memory, if you think about like a vector database, it's more random access. You have to know what to look for. But actually that's not how real memory works. There's a mix of it. So you're loading a markdown file and as you said, compaction, all these things matter, but the messiness of it actually probably produces a more useful agent than a lot of the fancier things. And I use memory in ChatGPT and I love it. But I actually think this idea that there's a Directory of just everything you've ever done is actually maybe more useful to an AI than people think. And actually if you follow over the past couple months just this emergence of harness engineering where you're building the harness around an agent to do work. I wonder if in the short term it might just be one of those idiosyncrasies of history. Like mimicking a code base is actually the best way to make a general purpose agent work. And maybe over time we'll get fancier than that, but it's actually like a relatively efficient harness for an agent. So anyway, maybe that's why it's.
- [05:31]
Patrick Collison
Yeah. And it's very terminal centric and yeah, it's kind of backwards compatible.
- [05:35]
Brett Taylor
You can use grep. You don't need to make some vector database, you know.
- [05:39]
Patrick Collison
And the AIs really know how to use all the UNIX tools and so you get a lot of lift from that.
- [05:45]
Brett Taylor
That's exactly right. I mean, you know, software engineers were notorious for making tools for ourselves first. So then we, we just almost like bend every other domain in digital towards that domain. But the reason I brought up things like unit tests, integration tests, OpenAI did this blog post. I can't remember the engineer did the post but on hardness engineering. And one of the more interesting parts of it was documentation. So rather than just having a single Agents markdown file, they had a directory of essentially the entire product, the architecture. And they're sort of filling this out over time. And Agents markdown became sort of pointers to it. My hypothesis, having used Codex a lot, I wonder of the output of a session where you make a change to Stripes products should be a documentation artifact in addition to code where the documentation artifact is actually what the product manager version of John. And the code was the engineer version of John where there's a lot in the code that is more transient. You might be fine to delete that. What was the intention? What was the prd? What was the customer problem is actually the more durable asset. And I wrote this on X and one of the funniest comments it would be like. It would be the greatest irony if software engineering agents made all of us just write documentation the whole time just because notoriously every good engineer hates writing documentation. Now that's our job. But I don't know, it resonated with me.
- [07:12]
Patrick Collison
How much are you AI code? Like you're a very prolific engineer in the old fashioned handspun way of writing code. And so how has that changed? Pour over.
- [07:26]
Brett Taylor
That's a really funny way to use that. I am trying to get to a world where I'm not writing code. It's hard emotionally, if that makes any sense. I have a hard time not caring. I don't care about the assembly language produced by the compiler.
- [07:46]
Patrick Collison
Why should you care about the code?
- [07:47]
Brett Taylor
Why should I care about the code? I care about correctness, I care about robustness. And I think I know intellectually I don't need to look at how the compiler unrolled this loop to verify its elegance and correctness. Yet somehow I feel that way about code. And I'm not saying the code doesn't matter, but I've been trying to force myself to not care because I feel like I won't be like a self actualized software engineer in the future if I'm too precious about that artifact which used to be so central to me right now, writing markdown files, like, maybe that's fine, it feels somewhat like a local maximum. And maybe we'll just be like, oh, of course markdown is how we work with machines. If you think about what a compiler does, there's this interesting mix of formality and informality and if you've used Python versus Rust, sort of different ends of the spectrum now that you're not writing the code, I really wonder what that programming system should feel like and look like. And I don't mind chatting with Codex, that's fine. But I also think as you imagine, all the tests that you care about, all the IT showing you demos and mockups, and I wonder sort of what the future integrated development environment, for lack of a better term, will be in that world. So what I'm trying to do is force myself to not be emotionally attached to the code, which is very hard for me because that was my entire life before. I was proud of the elegance of the code that I wrote. But if I still care about the craftsmanship, what do I want? And I haven't quite visualized it yet,
- [09:22]
Patrick Collison
it feels to me like a very interesting time in agentic engineering because you were talking about this domain of harness engineering and people having skills and MCP and everything like that. It's always interesting when not only is the leading product in a category changing where it's just figuring out what the categories are that, you know, we need things for MCP or, you know, skills or stuff like that. And it's all very fast moving and that just feels to me like a very interesting time where clearly a new way of engineering is shaking out and 2026 is clearly not the final word.
- [09:58]
Brett Taylor
Absolutely. And in fact, I'm growing more skeptical of MCP as like a meaningful part of the future. Not it's fine as a protocol, but it's interesting. Going back to your joke around openclaw, just writing a big markdown file, I think it works better than a bunch of MCP servers. But going back to the point of every AI agent knows how to use grep and knows how to use all these things, I feel like this view of a multi agent world was you have all these agents that do tasks that are fraud detection and another one over here for personalization and then you make a superagent. It does all these things and it looks really good on a whiteboard. Like most elegant looking but completely nonsensical architectures. And then you realize if you just imagine you anthropomorphize the stripe experience and you're like the checkout concierge, what information do you need to have no a priority to actually make that a humane experience? And what ends up happening to these multi agent systems is you stuff all the context in the subagents and the one on top has no ability to actually not sound robotic. And then in contrast, you look at something like openclaw, it's just a bunch of markdown files and the memory kind of feels right, even though it's a little bit kludgy. And similarly, if you go back to my arguments about a source control like a repo, it has so much context. So it's not like you just have the myopic view of the file you're editing. It really has some expansiveness. My sense is we're making true agents over time. The way we think about context and how that context is sort of shared so that the agent that's orchestrating it actually understands sort of what's behind all these APIs and why. And the history will maybe look a little bit more like openclaw and less like MCP over time. And I think these agents need a lot more context than what MCP affords. Yes.
- [11:56]
Patrick Collison
One thing we've noticed is there's a bit of a what's old is new again phenomenon where with this agent of commerce stuff that's happening, we actually built the APIs for this like 10 years ago as part of. Do you remember that move of social shopping that was like for a while like buying on Instagram, buying on Twitter. Yeah. And they're just kind of. It didn't quite happen for a few different reasons at the time, but the concepts are very similar that you want some action at a distance, you Want to be able to go kind of manipulate stuff off site. And similarly, I think Patrick has wanted for the longest time in Stripe is the ability to just SSH into your Stripe account. You're like, what do you mean? It's like a very ergonomic way for developers to work is you just be able to log into your Stripe account and you have a command line there and then you can list out all your pay, or you can tail the payments log, or you can.
- [12:46]
Brett Taylor
He wants tail and pipe and grips.
- [12:49]
Patrick Collison
And of course now we're building that because it's like much more relevant in the agentic world. But I find somehow, yeah, all the agentic stuff is also bringing back. I don't know if you have this experience as well. It's bringing back a lot of ideas that you might have had before.
- [13:02]
Brett Taylor
Well, it is because to some degree, the elegance of Unix, which has sort of been the basis of why everyone wants ssh. And like the curl command that was sort of famously on the Stripe homepage for people who got it. It was remarkable because you could have all these tools that did something well, that was small and useful, and you could chain them to make something great. I actually, I wonder in the future. We've talked a lot about this. You know, if you look at the Canonical software as a service application like Stripe's console, and obviously you have your. What consumers see, but like the configuration that a Stripe customer will log into, you would have a web app and that's like the forms and fields and buttons and graphs.
- [13:42]
Patrick Collison
Yep.
- [13:43]
Brett Taylor
And then you have the API and it was typically like a rest API or GraphQL API and you could do stuff with it. And this is how computers talk. This is how humans used it. I wonder if the web application of the future will actually be. Certainly you want a web app for the rare human who wants to sign in, but will you have an agent harness? And what I mean by that is something more than the APIs. But just like if you think about the harness that you provide in a code base, the skills, the documentation, the roles, imagine the person who's the greatest Stripe expert, who knows how to extract the most value from their Stripe account. That's the harness, not the API. That's the button you click and will that be an endpoint on stripe.com and so that your agent knows how to just get the most value from Stripe. And I imagine you don't care if your merchants log in. What you want them to do is drive value for themselves, drive GMV drive payments. And so I just like what I'm really excited about that because an API is great, APIs are awesome, but a harness is basically like here's the instruction manual for all the UNIX commands that power Stripe. That's very interesting. Yes.
- [14:58]
Patrick Collison
And I think if you look at the shape of a lot of APIs that services have, and I think Stripe's API coverage is probably more complete than most. But ultimately it is a way to manipulate some of the highest value business object in the thing. Whereas actually what you want is one, all of the data to be browsable in some kind of identically accessible or textual way. And then all of the actions to be, you know, able to be taken by agents. And it turns out there's a lot of switches in the dashboard that you know, there's no API for. And we are all as an industry
- [15:34]
Brett Taylor
collectively discovered and it might be easier, like imagine being a product manager in the future. You just need to add the switch to the dashboard. You're like, yeah, it looks like a Russian submarine of switches, but who cares, right? Like agents can handle it. And you know, as long as the harness describes when to use that switch, you know, it's easier than UI design in some ways. And that's fascinating to me.
- [15:55]
Patrick Collison
But one funny point Dario made is it's not clear. Well there's a race between people getting their stuff accessible via agents and just desktop computer use getting better. And so it's actually not clear. Will the approach be Stripe builds way more APIs and that's how your agents manipulate the Stripe account or you just give your agent access to Chrome and a login.
- [16:23]
Brett Taylor
Well so actually I'll give a funny story here. So Cira, my company, sorry, we'll get to Sierra. No, no, it's fine. But there's a real funny story here. So Sierra powers a lot of healthcare companies. So like on the healthcare payer side,
- [16:36]
Patrick Collison
health insurance, their API quality.
- [16:38]
Brett Taylor
Well so first of all actually pretty sophisticated engineers in these companies. I really enjoy working them. So you end up with Cigna, Blue Cross, Blue Shield on the health care payers insurance. Then you have health care providers like Sutter Health we work with. Then you have revenue cycle management. So like R1 and revenue cycle management basically help providers get paid by the insurance companies. And then you have a lot of other people in the middle pharmacies, PBMs and they all call each other. So like healthcare provider has to call a payer because a procedure happened and they have to get paid. So we have payers with AI agents that pick up the phone oh sure. And we have providers that have AI agents that pick up the phone and make phone calls. We have revenue cycle management companies that work to make outbound calls to do it. We've already had.
- [17:25]
Patrick Collison
Do they switch to the agent language?
- [17:26]
Brett Taylor
They don't. We've done English over the publicly switched telephone networks. So you have tcp, IP and English over pstn and it goes, I mean it sort of reinforces, I guess Dario's point, which is you can engineer all these fancy protocols, but the Rails that are already there already exist. English is spoken by all AI agents and the publicly switched telephone network has been around for 100 years and it all works, which is fascinating. So you have all these fancy MCP things and we're doing like English over pstn. So on one hand I think I actually agree with the principle that one of the powerful parts about AI is with its ability to do text, do audio and do. I'll say I'm not sure how you qualify computer use, but you can call it form of image recognition and manipulation. Certainly that's useful because you get to the point where you don't need to fully finish the last mile to get value. The thing I'd say though, going back to talk about all the actions and just they're not all in the product, all the APIs don't exist. These visual interfaces were designed for us. So think of, I mean Stripe is sort of, I think famously was one of the few enterprise software companies with good design for a long time. And I like the Stripe dashboard's really elegant. Right. And most enterprise software, you can't say that about their dashboards. I don't think the ideal like Agent Harness will be that elegant because it's optimized for something else. Yes, it's optimized for the context that you need to perform complex multi step procedures on behalf of, of a person. And my guess is it's just very different. And I think seeing the way you write a harness for a software coding agent is just so different than the way you do I design. So I'm certain that it's great that you can click around a green screen or whatever, or click around a green screen because it's an oxymoron. But type around a green screen or click around a legacy on premises enterprise software system. I think these harnesses will be really good. And I wonder if is there a world two years from now where Stripe's ability to work with the agent that manages commerce for a direct consumer e commerce company, that would be one of the ways you're evaluated. And in fact, if you're, for lack of a better word, harness is not compatible with the way their agents work. That's actually you're not compatible with them. And I'm not sure that's right. So I think it's great that these things are backwards compatible. It's great that our agents have spoken over the telephone already in English.
- [20:02]
Patrick Collison
That's really funny.
- [20:03]
Brett Taylor
But I don't think it's the long term future because there's so much value that you can provide. And put it another way, the agents using a sophisticated application harness can just do a lot more and do a lot more with higher fidelity.
- [20:15]
Patrick Collison
Yes. Well, we should get to Sierra because you see a lot of real world AI adoption and so maybe start by grinding us. What is Sierra? You know, the business has scaled very quickly. So one of the latest metrics that you can share because they keep changing from month to month as you guys grow.
- [20:31]
Brett Taylor
So Sierra, we help companies make AI agents for their customer experience. So if you have a big phone line, these agents can replace your IVR system and just pick up the phone. If you have a digital chat system, an AI agent can pick it up. You don't need to wait on hold. These agents can not only answer questions, but take action on your behalf. We work with healthcare companies like Cigna. We just did a great case study with Sofi and I'm really proud that we raised their net promoter score by 33 points just because it's just so delightful. It's really fun to see all these different brands across a wide range of industries get so much value from their agent. We're the leader in the space. Like just you talked about the Metrics. We reached $100 million in ARR in seven quarters, 150 in eight quarters. We're I think around 165 now, one month into our, you know, next quarter. So growing really rapidly and really proud of the momentum that we have.
- [21:28]
Patrick Collison
That's super cool. What is the typical adoption? Are people using it for, you know, email, chat support? Because that's the easiest modality. Do they adopt it for everything including phone and stuff like that?
- [21:40]
Brett Taylor
It's changed a lot over the past two years, but I'll say the median customer and they'll describe some like interesting outliers which I hope are sort of glimpses of the future. So most will start with one channel and a few use cases. So you know, at a lot of healthcare companies, phone remains the dominant channel. So say hey, for a few types of phone calls. Let's have the AI agent take them and see how it does. Do people like it? Are people comfortable with it? Does it lower our cost? Does it raise whatever metrics? Usually it's customer satisfaction and does it work more effectively. So for example, like for a car insurance company, it'll be like first notice of loss, you know, I got an offender bender, you know, and that would be the typical way you start. For a lot of more digitally native companies, they'll start with chat and it and kind of similar, but almost all of our clients will do both. So SiriusXM, if you call them on the phone, their AI agent, Harmony, which I love that name for, SiriusXM, will pick up the phone and if you go to their homepage and you see the chat, that's also the same agent. So the neat part is, I think it's pretty neat because you have like, literally you have all of your, I'll say customer experience team or you know, whatever you might call it at your company. They can spend all their time on one thing.
- [22:52]
Patrick Collison
Yes.
- [22:52]
Brett Taylor
And it actually works over WhatsApp. It can work online. Yes. It can work in your website work remote app. It can pick up the phone. That's a pretty big change. A lot of our clients, when we start working with them, they'll have like a digital team and a call center team and all these different teams. And we've kind of gotten to the point because we've digitized the last remaining analog channel, which is the telephone. Those are all unified when I start by sort of a glimpse of the future. We have a few like really ambitious customers like Rocket Mortgage, Great Detroit Company, they own Redfin. They bought a mortgage services company called Mr. Cooper. If you go to Redfin, you can search for a home using an AI agent. If you go to Rocket.com, you can originate a mortgage with an AI agent and you can service that mortgage so
- [23:33]
Patrick Collison
it becomes a product usage rather than
- [23:35]
Brett Taylor
just customer service and really end to end sales service. And I think that's really exciting. I mean our whole view is that if we're in 1994 and you were doing cheeky pint about this Internet phenomenon,
- [23:47]
Patrick Collison
that would have been a fun. I was a bit young, but yeah,
- [23:49]
Brett Taylor
yeah, I would have my Nirvana shirt on. You know, we would be talking about like, look, this is like your digital front door or maybe wouldn't have the pressure to say that. But I'm the information superhighway on the information superhighway. And I think the same is true of Most companies, AI agent, singular, there are lots of agents, but the one with your brand at the top that your customers interact with is special. And that's the one we're trying to power for companies.
- [24:18]
Patrick Collison
So using this like what customer is built on Sierra, your aspiration is that it just becomes sometimes the primary way people deal with the company.
- [24:27]
Brett Taylor
I think a company's AI agent will be the vast majority of their digital interactions. And I think digital has come to include the telephone. And that's sort of a big shift because we think of that differently and that's a huge change just because the bigger shift. So customer service, which is one big part of what we do, but not the only thing we do, is traditionally been thought of as a cost center because it's really expensive. So I'm sure you have people answering the phone for your clients and depending on where they're located and how well trained they have to be, like how simple is the case? It can cost 10, $20, it can be much less. If it's a more simple case and you have some customers who pay you millions of dollars and you'll answer the phone anytime they call and you might have one that has started monetizing yet and you might want to call them, but there's a limit to like literally how much you can afford to talk to that person and still have a profitable business. I always joke it's probably easier for you and me to call Sundar than to get Google customer service on the phone.
- [25:29]
Patrick Collison
It's very hard to get Google customer
- [25:30]
Brett Taylor
service on the phone. But it's not because they don't like you. It's just if you think about the average revenue per user of Google, they literally, I mean, they just can't afford to do it.
- [25:40]
Patrick Collison
Yes.
- [25:40]
Brett Taylor
So now if you take that 10 or $20 phone call and you make it 10 or 20 cents and over time, 1 to 2 cents. All of a sudden not only can you afford to provide a great customer experience to more people, even less profitable customers, or in lower margin businesses, which I think is very exciting. So it's like not just doing what you did before, but new you can
- [26:01]
Patrick Collison
provide better customer service.
- [26:02]
Brett Taylor
You really can. And then just think about running like a subscription business where you care as much about customer acquisition, you care a lot about churn, because that's how your lifetime value equation works. And you think about, okay, if I had a budget of how much I spend on service and now I can do 100 conversations more than I could before, can I actually reduce my churn rate Can I improve lifetime value? And then the interesting thing is then you realize that, wow, all of my competitors have access to the same technology.
- [26:30]
Patrick Collison
Yes, yes.
- [26:30]
Brett Taylor
And then you're saying, okay, what are my competitors going to do to actually take my customers away from me? And then that's where you start to get things like, you know, the ATM machine didn't actually reduce bank branches because some bank had the great idea of, I'm gonna put different people in this branch, it'll generate revenue. And all of a sudden it wasn't job displacement, but something completely different. So I think the exciting part in our world is you're taking something that's just so, so, so expensive that people like literally hid their phone numbers so people couldn't call them. And you're making it inexpensive and delightful. And everyone. The thing I'm excited about is the second and third order effects are going to be really interesting and very hard to predict. And that's pretty exciting.
- [27:11]
Patrick Collison
I want to come back to this idea of the agent as the ui, because I found it really interesting. We talked about this a bit in our annual letter in the context of agent E Commerce, where again, I think people are trying to pitch too much of the end state of fully autonomous, the robots just choosing a few. And the point we always make is let's just start with not having to fill out the web form. Like, no one likes filling out forms on the Internet.
- [27:31]
Brett Taylor
Speak for yourself.
- [27:33]
Patrick Collison
I wonder, just will using websites have been actually a bit of a. Like the fax machine, you know, we used to hum emails over the telephone lines as a way of transmitting information. Or like, I wasn't working for this, but like, there was an era of like voicemail memos for you ever in the working world for that?
- [27:53]
Brett Taylor
Some still do this where they, you
- [27:55]
Patrick Collison
know, but like, companies will like blast a voicemail memo to like employees at the company and like, that's a way of distributing information. And all these things are like very moment in time. And maybe navigating websites and filling out forms was like a bit of a moment in time. Is that how you see things playing out?
- [28:10]
Brett Taylor
I don't know. I mean, it's interesting because if you look at the past few iterations of technology, you had the PC revolution, then you had the Internet and the browser, then the smartphone came out and the tablet. And I was more optimistic about tablets than sort of the way the world turned out. I see more tablets on airplanes, but I'm guessing if I walked around Stripe, I would see very few tablets out. And similarly, there's more smartphones than people, but there's still about 2 billion PCs in the world. And I think it peaked some number of years ago, but it hasn't gone down as far as I know and I haven't tracked this. That's interesting, right? We sort of added to our digital world but I think perhaps a more interesting metric is for like you and me, what percentage of emails were sent through each device. And certainly from 2010 to 2020 most of the world might have transitioned from like percentage of email on desktop to smartphone significantly. And so it's almost like market share of digital interactions which I think is a really interesting way to think about it. And certainly as you think of like Stripe's business, like where does commerce originate? And you saw that move to mobile. But it doesn't mean that people. It's actually a very big. You wouldn't want to eliminate the PC commerce business. Like that would actually be catastrophically bad. And so then you look at AI agents and I believe most businesses, it will be their primary digital interface and it's because it works over WhatsApp and it works over the phone. If smart speakers make a comeback, they'll work over smart speakers, which they may now.
- [29:47]
Patrick Collison
Smart speakers were just too early.
- [29:48]
Brett Taylor
Yeah, well, it's like apps for the weather just turns out to be like not the biggest market in the world. But now.
- [29:53]
Patrick Collison
Set a timer. Set a timer.
- [29:55]
Brett Taylor
I mean it's amazing they made that much money off a timer setting speaker. And so it is very future proofed because it's fundamentally conversational. But maybe it's like going from punch cards, mice and keyboards, touchscreens, now voice and chat and probably 3D immersive at some point. Does it just sort of add and make the other ones less important? Is probably the way I think about it. I do wonder if we'll see the end of the smartphone at some point. It doesn't seem anywhere close to right now, but it is interesting. I mean I think most people don't love how much we're sort of addicted to staring at this glowing screen. On the other hand, you can't talk to TikTok. You know, it's fundamentally visual. But I wonder if there's a world where you could actually be really productive without such an invasive device on your body. Yes. And if that's the case, can it offer an opportunity to sort of like unwedge some of the addictive properties of these technologies and get a lot of the benefits from it, you know, because like, at least for me, like I think all of us are so connected. You sort of end up like, I'm gonna check my email. And then like, you're like, where. Where have I been for the past hour? You know, like. And the fact that we actually have technology that affords that kind of innovation now I think is quite interesting. So I don't know what the future is, but I'm very excited for it. I know that sounds really cheesy, but I sort of like, we've now changed the ingredients available and we have a lot more recipes we can cook, and I think that's very exciting.
- [31:23]
Patrick Collison
Yeah, I agree with you. I'm excited for not having to look at a screen for as many things for a variety of reasons. When a customer installs Sierra, I know there's a significant customer satisfaction component as well as cost, but I'm curious, what kind of cost difference does it make? And maybe relatedly, when a customer is fully deployed, what kind of mix do they see between queries fully resolved agentically, things that end up having a human who is presumably somewhat AI assisted. But just what does a normal equilibrium look like there?
- [31:58]
Brett Taylor
Yeah, it turns out most of our clients have pretty different priorities, so some are very focused on cost savings. And you can automate very, very high percentages of your cases. A lot of. There's a company called Ramp, that's a really impressive tech firm there.
- [32:15]
Patrick Collison
We had Eric just here.
- [32:16]
Brett Taylor
Oh, that's great. Well, they're automating 90% of their cases. They're really sophisticated, though, because they're like, you know, they're basically getting in front of cases before they escalate. But I think it's kind of an example of just a really fantastic company, you know, implement really well, and you can see anywhere between, you know, 70, 90%, which is really incredible. The interesting thing, though, is there's counterintuitive effects to it. The cases that do make its way to your customer service team can end up more complex, sort of by definition, what's called average handle time will actually go up. And we heard from one of our clients that actually their satisfaction of their call center agents went way up too, because it turns out it's way more fulfilling.
- [33:00]
Patrick Collison
Totally.
- [33:01]
Brett Taylor
To solve a hard problem.
- [33:02]
Patrick Collison
Have you tried plugging it out and
- [33:03]
Brett Taylor
plugging it back in again? Exactly. The other gen one, we had one retailer whose volume, total volume went up almost as much as they saved from the AI agenda.
- [33:16]
Patrick Collison
Gentleman's paradox.
- [33:17]
Brett Taylor
It was a form of that. So, you know, if you've used a chatbot from three years ago, they were really annoying. Like no one. Like three years ago if you said like, do you like chatbots? There was like zero. People would say yes.
- [33:29]
Patrick Collison
It's so funny that there was a Silicon Valley wave of hype around chatbots. It was even earlier than that. It was like 2018. It was like pre LLMs, pre transformers.
- [33:36]
Brett Taylor
Yeah, they were just like multiple choice machines or something. It was just the worst products of all time. And so replacing it with something that was like a delightful a people are like, I'm going to talk to this thing a lot more. So they ended up keeping their cost didn't really go down, but their volume of customer conversations went up, you know, 2 or 3x. And the CEO was incredibly happy about it. They were like, I've just. We're now actually listening to our clients. So it sounds funny, but it's a little bit of a choice how much you want to drive cost savings with AI versus other metrics. Most of our clients are interested in the top line metrics. And so if you could save $10 or save $1 and improve your net promoter score and competitive positioning by a meaningful amount, everyone in the world would choose the latter. So that's the interesting going on right now because again going back to it was 1994 and we're hockey and websites on this podcast, I think if you were to go to a major bank and say if you launch a website, you're going to have a competitive advantage against every other bank with the benefit of hindsight that would have been over promising. The correct thing to say was if you don't want a website, you don't
- [34:52]
Patrick Collison
have to have a website.
- [34:53]
Brett Taylor
And so this technology is broadly available. And so as a consequence you can't just sort of like launch in all parts of AI, not just arbits. You can't just launch AI, absorb the cost savings, pass it on to shareholders. Unless you have a monopoly.
- [35:08]
Patrick Collison
Yes, yes, but in most businesses it's a consumer surplus.
- [35:12]
Brett Taylor
Exactly. So you either going to lower prices. But I think that's why it's an overused analogy. But the atm, bank branch thing is really interesting because if every single company in an industry has access to technology, I would say it's an imperative, not a competitive advantage. The more interesting I would say board discussion is when everyone adopts the obvious things. Customer experience, customer service, software engineering, legal, just pick the ones where there's solutions off the shelf solutions available. Now what will the industry look like? And my guess is you could ask chatgpt think. And my guess is there's some really Interesting second order effects. And when you have competitive markets, you're going to end up investing, lowering prices, whatever it may be. And that's the thing. I don't think it's talked about enough. And I actually think that we just. It happens with every technology change. You project it through the lens of what you're doing today and you don't take into effect. It's like a multiplayer game that we're all in right now.
- [36:11]
Patrick Collison
Yes.
- [36:12]
Brett Taylor
And that's fascinating to me. And so the change is disruptive, but I think it's going to be like, I'm very excited for the next few years as like the world absorbs the technology, we start getting to some of those second and maybe even third order effects.
- [36:26]
Patrick Collison
What is the most impressive AI adoption or kind of AI native behavior you've seen from a client?
- [36:33]
Brett Taylor
Oh, that's a really good question. I'll probably say Rocket, where we have a really great relationship. I think Varun is their CEO, Sean Malhotra is their cto. Two people who really are, I would say, not only just curious about AI, but very interested in transforming the home ownership experience with AI. And I don't know, like when you like got your first mortgage, but it's like super. It's very intimidating.
- [37:02]
Patrick Collison
And it's not a modern process.
- [37:04]
Brett Taylor
It's not a modern process. They literally call it mortgage folders for a reason, like it used to be a folder. And for me it's an example of a company like trying to transform an industry. And the reason I brought it up in the context of our last question is it's not just saying how can we take AI to do this? But it's like if you were to think about the homeowner experience from searching for a home on Redfin all the way through servicing it and you had AI available, what would the ideal experience be like? And it's just really interesting to see Rocket with their acquisition strategy to kind of like integrate that experience. And that's why I'm excited about. I think there's an opportunity for CEOs and like, industries like that to have a bold vision of like what the future could be. And you know, going back to my point, imperative, not competitive advantage. It is a competitive advantage right now. So if you imagine I haven't tracked the market share of all the big US telcos, but if you look at T Mobile, Verizon AT&T and you tracked it over the past 10 years, you end up with surges in market share growth. The iPhone came out, you ended up with 5G. And you end up with these things where. But my impression of the industry is you end up with these sort of moments that drive market share and then it ends up at an equilibrium. I think that. So it's interesting about it is like the iPhone moment for telecommunications companies like Softbank in Japan. This is the moment where perhaps if you have a competitive equilibrium, you can absorb this technology, use it, and you'll have this window where you can actually
- [38:38]
Patrick Collison
shuffle the data technology that shakes the competitive equilibrium.
- [38:42]
Brett Taylor
Yes, exactly right.
- [38:43]
Patrick Collison
Is that.
- [38:44]
Brett Taylor
Yeah.
- [38:45]
Patrick Collison
So you talked about how coding is such a domain that is suitable to AI because all of the context you're working with exists in the repo, it is in text. It's kind of neatly organized to be executed and read by humans. And so there's kind of a good bounce there. The problems that customer service agents are not of that character. And so how do you actually smush everything into a format where your AI agent can answer it?
- [39:25]
Brett Taylor
Yeah, we spend a lot of time thinking about that to some degree. One of our engineers called almost like we're creating like a domain specific language for specifying customer experience. You know, like, what is the mechanism of specifying it? We use this metaphor we call journeys, which is what is a customer journey, end to end. And what does the agent need to be successful in that journey? What tools does it need to access? What information does it need to access? And if you think about the capabilities of an agent, like skills and a coding agent, you'll add different capabilities over time as the customer is talking to you. The key thing that's been a breakthrough that is probably not surprising to the technologists listening to this, but has been a huge difference between those crappy chatbots of four years ago is the reasoning capabilities. I think we had one client who had acquired three companies and they had three identity systems, three CRM systems, three of everything. And so they had this big IT project where they were going to unify all the systems. But I was like, why don't you just have the AI agent go in all three of them and just think. And they're like, well, what if there's duplicate data? What if the data conflicts? They're like, you know, that's going to fusion. And I was like, well, what is your person? What does a person do? Like, well, they kind of think about it. And I was like, no, let's just do that. Yeah. And that's the interesting thing about these AI agents is they actually the basic, humane, basic reasoning, not superhuman ASI turns out to be the huge breakthrough in customer experience. The other interesting thing is the innate knowledge of the LLM. You don't want an AI agent to hallucinate, obviously. But I met Sonos is one of our clients. And do you have a Sonos speaker at your house? You probably have at some point.
- [41:15]
Patrick Collison
I have had.
- [41:16]
Brett Taylor
If a Sonos speaker ever breaks, it's never the speaker, it's always WI fi. That's what I've learned. And it's always true of me too. Right. There's always some WI fi issue. You know, if you wanted to make an adjunct to help you with your Sonos speaker, like, you obviously can give it all the manuals for all the speakers, all the technical specific. You can give it the device telemetry, all the stuff you need. Do you really need to give it the history of WI fi? Well now it turns out like large language models have encountered every possible WI fi problem. So like, why does the Sonos AI work so effectively? Well, it knows a lot about WI fi in addition to all the Sonos things. And if you look for any given AI agent, all of the like, it turns out being trained on all of human knowledge is actually useful as a starting point for a lot of tasks. And I think that's been the big breakthrough. So how do you give it all of its knowledge? Well, first we've built, I think the best platform in the market to do so, where you can really narrow the guardrails for regulated conversations, widen them for less regulated conversations. But the fact it starts with like knowledge of obscure WI fi idiosyncrasies turns out to be the greatest breakthrough of all time.
- [42:18]
Patrick Collison
Have you had the opposite problem where the customer whose problem domains mostly don't exist in the public interest? You know, it's like we provide the drill bits used in, you know, deep sea oil drilling and it just turns out there's nothing, you know, on Reddit about that.
- [42:32]
Brett Taylor
Yeah. So 100%. And you know, we work with this like medical device company and it's, it's a deep cut of human knowledge, you know, and you can train it all on that. In fact, we, we do a lot. One of the things you want to be really careful about, if you have a really well known brand and we work with, I want to say a third of our clients have over 10 billion in revenue. Over half have over a billion revenue. So most of our clients are actually quite well known. So one of the challenges when you're offering either sales or service or customer experience to a really well known brand is it's harder to ground it. It's actually easier when the Internet has never heard of you and you want to make a well grounded agent. It's actually pretty easy because there's no temptation from the LLMs to go off script. So actually they know what they don't know. Ironically, the harder challenge is when it's a very well known brand. It's like, no, I got this. No, you don't. You got to go look it up. That's actually a harder problem.
- [43:26]
Patrick Collison
And so how do you force the LLMs mechanically, how do you force them to not answer off the top of their head, but actually look it up?
- [43:36]
Brett Taylor
So we use, we call it a constellation of models. So our platform, we call it Agent Studio, you essentially configure the goals and guardrails of a process and goals and guardrails, not the sequence of steps because you want agency, but you want guardrails around it. And within that, we'll use reasoning, but we use supervisor models to actually inspect that reasoning. And so if you were an AI agent in Sierra and you decide to go off script like, I got this, like I don't, you know, what would end up happening is a supervisor agent would observe your reasoning, say, you know, I think John should have actually looked up the policy here and send it back with notes and say, actually you're not allowed to make that decision. You know, here's the reasons why, you know, go, go redo that decision. It's a really effective technique, the way I think about it, which is a little simplistic, but I think basically right. If you imagine a reasoning System is right 90% of the time, but has some either guardrail malfunction or hallucination, 10% of the time, it's obviously better than that. And then you have a Supervisor that's right 90% of the time. If you chain them together, you get 99% effectiveness. And so that methodology of layering, reasoning and intelligence has been really effective. And in general, it sort of makes sense. You're basically layering compute, you're layering reasoning on top of it. What's neat about it though is we can sort of abstract that complexity from our clients. So, you know, they're sort of expressing the goals in guardrails. And we have all these evals and tests and all these other things. We can find ways to make it more and more and more robust over time. But it doesn't require you to prompt engineer, write in all caps or whatever the hacks that people use to get these things to be conformant and you
- [45:24]
Patrick Collison
started in 20, 22, 23.
- [45:27]
Brett Taylor
We, we launched the company and on February 13th, two years ago. So I guess we're like, oh, 24. Yeah. So we, our two year birthday was like a couple weeks ago.
- [45:39]
Patrick Collison
Because what I was thinking as you were saying that is did you sort of co evolve chain of thought and RL and some of these things that are now in the models, but did you have to build your own kind of janky version of them before they were in the models?
- [45:52]
Brett Taylor
So yes, but I'll also talk about just the weird part about building a product right now and a company right now because so much of what we write we plan to throw out later.
- [46:00]
Patrick Collison
Yes.
- [46:00]
Brett Taylor
And it's just a very weird way to build a company. So Google's chain of thought paper, which preceded O1 and doing reinforcement learning chains of thought was out roughly when we started the company. It was an earlier paper and effectively provided sort of a substantive basis of why asking a model to explain its reasoning step by step produce more robustness. So we use chain of thought all the time and it was like a methodology we used. And then OpenAI very innovatively came up with the idea of we could do reinforcement learning on those chains of thought, which is where O came from. And then most labs are doing that now. So we'd throw out things all the time. You do it and you're like, okay, the model just does this for us. Now we work with a lot of financial services firms. We work with one bank that has a large Hong Kong business and they speak Cantonese and like, okay, well we need really good Cantonese voice support. And it turns out that that's really hard. And there's not an obvious model that does that. So we spend all this time evaluating all these models. What certainty would you ascribe to every voice model supporting Cantonese while in three years, 100%, 99% pretty close. So we did all this work and in fact we I think have the best Cantonese support on the market. Great for us. And it's a huge selling point and it's a technology that will certainly be commodity commoditized in three years. So a lot of what we think about, I think is going from essentially technology innovation. Now I think a large part of why we work with the largest companies in the world is because our technology works. Yeah. In three years those same clients will work with us because we have the best product. And I think if you look at the early marketing for like early software as a service companies, they'll explain why having multiple tenants in the same database is safe. And that was a huge part of their marketing. Nowadays, if you came and you marketed your product that way, people are like, what are you talking about? Like, I don't care what database Stripe is. You know, I think we're just at this period where the technology is so immature. It's a very technology forward conversation just because it's like people are figuring it out. Just like when Netscape's business was like monetized through a Web server back 100 years ago. And it will evolve from being a technology forward conversation to a product forward conversation. So the interesting part about building an applied AI company is you can't have the luxury of waiting for all the models to catch up with your aspirations.
- [48:34]
Patrick Collison
But you know they will.
- [48:35]
Brett Taylor
But you know they will.
- [48:36]
Patrick Collison
Yes.
- [48:36]
Brett Taylor
So you have to have the best technology and have to be comfortable with throwing it out. Yes. And so it's a real momentum and pace of innovation game. Rather than thinking of this as like precious intellectual property, if that makes any sense.
- [48:49]
Patrick Collison
It absolutely does. But isn't this organizationally hard where if I'm the head of Cantonese Language as Sierra, my incentive and not disingenuously so I'll notice all the corner cases, like the models aren't that good at Cantonese? Yeah. And obviously we saw this in prior tech waves, right, where the cloud adoption laggards were companies that had their own on prem stuff and they had a million reasons, half real, half fake, as to why cloud did not suit their business purposes. But how do you avoid getting stuck in this mode of thinking where like, oh, well, their chain of thought doesn't do what we need is like the classic thing you'd hear from someone within the organization.
- [49:36]
Brett Taylor
It's a huge shift. I mean, going back to the first thing we were talking about, it's hard for me to not care about the elegance of the source code, which I think is an impediment to my fully realizing, like being a software engineer in this new world. I think teams that start to treat the code that they wrote as precious, that has been obviated by a general purpose AI model will fundamentally fall behind.
- [50:05]
Patrick Collison
Public markets deem the software industry 20, 30% less valuable than they did maybe three months ago.
- [50:15]
Brett Taylor
A day ago.
- [50:16]
Patrick Collison
Yeah, exactly. Very recently. And the two sides of the debate are, one, the valuations were based on what the businesses will do in 2030 or 2035, like far in the future. And just there's much more uncertainty there. And so this is deserved. And the counterargument is that it's still not the case that agentic software production is really going to build you a workday.
- [50:41]
Brett Taylor
Indeed.
- [50:41]
Patrick Collison
Anthropic just installed workday very famously. Where do you net out on Is this a rational response or not?
- [50:50]
Brett Taylor
I think it's rational, but I think it's a bit overblown at the same time. So I think it's rational just in the sense that there's probably been. There hasn't been more uncertainty in this market ever. And so unless you have a strong thesis about an individual company, my guess is like will these companies be less valuable 10 years from now than now? I think the answer is probably yes. Will that be true for every individual company? I don't think that's true. And so if you're just thinking about a portfolio of investments, I think it's sort of an indictment of the sector more than it is an indictment of an individual company. I don't know if the value of these platforms was who could vibe code it in a weekend ever? Not that we knew what vibe coding was. My point is everyone who's ever built a software as a service application has had a hacker news comment of I could have coded this in a weekend like every single one. Famously Dropbox, I'm sure you have as well. Every single product I've ever made, I just have. It's like a right in fact, if no one said that on your product, like, I'm sorry, it's not relevant. Yeah, interesting. And obviously most of those comments were incorrect. But if you think about, you know, all the work you've done in compliance or the relationships you have with large financial services institutions, the work you do on fraud, the, the things under the surface that aren't, you know, the forms and fields in the web browser are actually incredibly valuable. If you think about a large software company, they'll have thousands of quota carrying account executives that represent sales capacity, which is basically a channel and distribution turns out to be a very important part of software. There's social proof. There's the old saying no one gets fired for buying IBM, which few people say. Right now though, IBM is actually doing really well under Arvin. You want to be maybe the first health care insurance company to adopt something. There's another health care insurer who says I want to be the fifth, I want other people to prove it. There's all these network effects around these businesses and scale and moats and sort of Silicon Valley speak around them. I think the big risk is where is value in the software industry? And years from now, one risk is that More people will build than they do now versus buy because the marginal cost of writing software goes down. I think that'll be true for some software, particularly developer platforms and things like that that are already being consumed in purchases by other engineers, little libraries or,
- [53:25]
Patrick Collison
you know, things that already were part of a build versus buy calculus. It shifts the balance of power.
- [53:29]
Brett Taylor
Absolutely, yeah. The other part of it is systems of record. So I think these systems of record have always been sort of the gravitational center of their relative solar systems and it roughly breaks down by department. So ERP systems are associated with the finance department and SAP and Oracle and Workday have ERP systems and you have Adobe in the marketing department and you had Salesforce in the sales department and you had ServiceNow in the IT department and everything sort of rotated around them. And why? Well, first their database was sort of truly the system of records. So every application that wanted to interact with the data in that had to you essentially collect taxes from your ecosystem and then similarly allowed each of those systems of record company to essentially have revenue expansion opportunities to go to adjacent areas where they're all sold to the same buyer and all of that. The thing that's really interesting is AI agents are actually performing valuable labor is the database and the system of record. Does that continue to be the gravitational center of each of those workflows? So I'll just take marketing as an example. The database of your customers that you use to drive sending out an email blast on Black Friday has some value. But if you had an AI agent that drove like, way higher, like more leads for your sales team from that marketing blast, you probably that's worth more to you than the system of record itself. Similarly, if you imagine I'll just take a CRM system and you think about the AI agent that's carving your territories if no one ever logs in to actually do it manually, all of those things have a lot of value and a lot more value than you know, relatively speaking than they did because they're actually performing the action. And so the real question to me is like, does it upend this? I would say something that's been true for 30 years, which is all the value is in these systems of record. And the way I think about it is agents are to some degree a system of record of a process of generating a lead or auditing your financials or reviewing a contract or whatever, whatever it might be. And I don't think we've ever had a piece of software like that. And will those encoded, well, optimized processes start to have more value than the databases? I don't know that's the case. For example, if your ERP system is your company's ledger, that'll have a lot of value. But I wonder for all these others. And my theory is the closer you get to literally the database is the value that is a ledger, the more durable it is, the closer you get to be in a system of engagement, the less durable it is.
- [56:24]
Patrick Collison
That's a very interesting framing. Yeah. And it kind of gets back to the point you were making about the company that was looking to standardize and not have three different ERPs and stuff like that. And you're like, why just try not doing that? And I think maybe the consumer example of this is I think people have probably had the experience of you paste data into an LLM to do something with it and you know, like the formatting is all messed up and like, you know, the tabs and spaces don't come through and everything like that. So it's all doesn't matter. You know, LLM doesn't care. You know, you can just like pay through whatever and it'll work with it. And so this idea that as you say, if like the system of record is important because it's your general ledger and it matters to the auditors, that's one thing. But if it was a system of record in this kind of all your data in one place way, and because it was easier to build incremental software atop it, maybe that advantage is going away because the agents are fine plucking data from 10 different places.
- [57:23]
Brett Taylor
That's roughly my view. But the bull case, I'll just mix up bear and bull. I need to spend more time on Wall Street. The bull case though is I think all these companies sort of have a right to win. They're all big, they still have sales capacity, they have all these advantages, but it's a race. How fast will smaller companies build differentiated scaled businesses before the incumbents go into this new world? But for a wide variety of well documented reasons, like disrupting their own business model, it's harder. But I think your ask is, is it irrational? I don't think it's irrational. I think there's just more uncertainty now than there's ever been. And I think that's markets are telling you there's a lot of uncertainty. And that's why you see sort of people recede from the whole category, basically.
- [58:13]
Patrick Collison
I feel like there's also a totally separate thing playing out here where for a long time certain companies were criticized for not Taking profitability that seriously. And at some level there's just a return to normal valuation levels on like a fully loaded stock based comp baked in and everything basis. That's kind of independent of the AI thesis, but maybe just some return to again on a fully loaded GAAP basis. More normal evaluations.
- [58:45]
Brett Taylor
Well, essentially if you look at a traditional software as a service company, the way most people model it is you have annual recurring revenue which is basically an annuity and it should throw off that much cash every year. Then you have attrition which is subtracting from the annuity and then you have net new arrival which is adding to the annuity. Your salespeople sell software to add to the ARR. You typically have account management team or customer success team to keep churn down. And you grow that annuity and you grow your headcount often just a little bit ahead of that annuity because you need to grow a new business. And if that annuity is not an
- [59:25]
Patrick Collison
annuity, then that math really changes.
- [59:28]
Brett Taylor
It really changes. And so because the whole idea of software as a service is you can just slow down hiring and you become very profitable because the annuity starts starting off cash. That's been the thesis of every private equity firm who acquires slow growth software as a service companies. If you don't assume that that revenue is going to be there two years or three years from now, your discounted cash flow analysis looks pretty different. And I don't think it's actually quite so dire in the timeframes that people think. But again, if you're asking like markets are, there's all those great quotes about Wayne and I don't know, voting way machines. I get it, there's probably more safer sectors to invest in, but I don't think it's an indictment of individual companies. That's my point. I actually think when we first met, I doubt either of us had an extremely positive view of the future of Microsoft. At the time it was like it felt like a previous generation company. Now you look at Azure, their OpenAI relationship, all these things like what an impressive turnaround. So I think any one of these companies could do it. I think it's just. But it's more of an indictment of the market. Yes, Yes.
- [60:40]
Patrick Collison
I have a lot more questions. Would you like to do Guinness?
- [60:43]
Brett Taylor
Sure.
- [60:46]
Patrick Collison
Brett has been through a few platform shifts and one thing he's been pretty consistent about is being mindful of the external forces that are shaping the ecosystem you're in. He talks a lot about building with the broader Wave of AI agents in mind. Stripe Sessions is our way of helping builders see that wave up close. What's changing in the Internet economy? What's actually working in production and what the next era of software looks like when agents are running real commerce workflows. It's not the usual conference fluff, it's insights into what the fastest moving companies are actually up to. So if you want to experience the next chapter of the Internet economy firsthand, join us at Stripe Sessions this April. Use the code cheekypint for 50% off a conference pass@sessions.swepe.com you talked about business models. Are you guys usage based or. Yeah. How are you innovating on the business model front or are you.
- [61:36]
Brett Taylor
We are trying to. So we do outcomes based pricing. So for a customer service context that means if the AI agent resolves the case, no human intervention, there's a pre negotiated sort of rate for that. And if we do have to escalate to a person, it's free for sales, it would be a sales commission. And wherever possible there's a way to align our interests with our clients. We choose it. And I'm a huge believer in this. I think the analogy of going from impression based ads to CPC ads is apt. I don't think any ad platform thinks like man, think of all the impressions we're giving away for free because when you charge for something closer to a business value, it's actually more valuable, it's more efficient. It's a lot more efficient. And I think the idea if an agent's outcome is measurable, it's a really compelling way to both for clients obviously because it's aligned with their business. But it's also quite disruptive because most I'll say legacy software companies are not necessarily equipped to do it for a variety of reasons I'm happy to go into. But it's just a very disruptive model.
- [62:43]
Patrick Collison
Yeah, there's kind of a few lens you can have on it. One is that you get more alignment like usage based is more aligned than other ways of charging. And as you say it's more efficient because you're incentivized to drive the right outcomes. People also make the analogies to it's almost more correct for the labor substitution dynamics that you get or just because you have real inference costs, you kind of have to do a usage based model. I mean do those factor in at all where this is just. It would not be possible almost to a fixed price contract Because I would
- [63:16]
Brett Taylor
actually argue outcomes based is pretty different than usage based. Just because think of it this way, if you have an AI agent that is making sales for stripe to small businesses and I told you I will sell 1/10 the number of new stripe GMV, however, you'd value that. But I'll use 1/100th of the tokens. You probably wouldn't care like you care about the value to your top line of your business. I would argue there's not a strong correlation between token usage or utilization and value. There may be, but there's not always. There was that infamous, I think it was called folklore, but it's this website where that Apple engineer used to put just all this Apple folklore. And this is Forkload.org Forkload Door. Yeah. Thank you. I love it. It's like if you're an engineer, it's a fun site to go to. But there was a story about some new bozo manager asking for lines of code every day and one of the engineers wrote a negative number as a way of saying like fu to the man because he refactored a code base or whatever. I think that is the essence of why tokens are not correlated with value. They may be, but the idea that they definitely are I don't think stands to reason. And so I think usage based is like charging for storage or something. Outcomes based is what business outcome is this agent designed to produce and did it produce it effectively. And that is really aligning because it creates like this whole vertical alignment. So as a company reducing your token utilization for the same outcomes as your problem, not your customers. And that's a great incentive to just drive more efficiencies over time. It means that to grow your relationship with the client, you actually have to make your product better and not just theoretically better to steak dinner, like better better.
- [65:09]
Patrick Collison
How do you have usage based or sorry, outcome based when you move beyond customer service where there's a clear was this resolved or not? To product usage where people are shopping and yeah, they didn't buy a house there, but they mostly don't buy a house on most website visits. But it was a successful visit.
- [65:30]
Brett Taylor
So it's the right question and there's not a great way to do it for every type of agent right now. And so you know, you can all sort of like fall back to usage based, which is fine. But in that over time it's like, wouldn't it be interesting? I think AI agents should have memory. I think AI agents should drive relationships, not conversations. And it would be really interesting to say could we make an AI agent that actually drives home ownership over Time. I think that's actually. It's hard, but it's not have a territory kind of. I think so. I mean even because it's hard today and we're a pragmatic company, I think it's sort of the right thing to ask though, because that's fundamentally the value the software is designed to produce. And so I think actually it's a really sort of values aligning thing. It also though changes the dynamics of a software company's relationship to its partners, to its clients. Because if you go back ancient history four years ago, there was a really stark separation between software and implementation and usage. It was the client's accountability to use the product well. It was either your IT team or a systems integrator's responsibility to implement the software. And the job of the software company is just to make it and throw it over the wall. Obviously it's not exactly that, but that was kind of the market we were in and everyone had good intentions. But what's the same success as a thousand fathers failure as an orphan? When the software didn't go well, everyone was blaming everyone else. The client was like, I'm using it just fine. It was implemented poorly. The person to implement it was like, no, the platform's broken. The platform people would say and it was like everyone's pointing at everyone else. What's nice about outcomes based whether or not but the client sets it up, you become more accountable to help them be successful because until they do, they can't use it. If there is some long sort of last mile of implementation creates a strong incentive for the software company to have skin in the game to just help you navigate that last mile. I think so many of the problems in the software industry are due to that lack of accountability. If you talk to any company who's ever implemented an ERP system, it's like a multi year process.
- [67:51]
Patrick Collison
It's invading Russia.
- [67:52]
Brett Taylor
Yeah. And you don't even remember why you're doing it midway through. You've gone through two CFOs and three CIOs by the time it's done and we're okay with that. That's just the way software works. And so my view is just like, I think AdWords sort of changed the advertising industry on the Internet, just drove it. And I think you can even pay for a mobile app install now, directly and truly pay for outcomes. I think it's a really positive step forward. So it's not going to be possible for everything. You have to have pragmatism. But I think it's the right way to actually have a partnership. You should share in the outcomes.
- [68:27]
Patrick Collison
You want to wire the company to be thinking in this outcome based way. And like in your main customer service stuff, you can do that in other ways. You might not be able to yet, but you want people to be spring loaded to be thinking about it.
- [68:36]
Brett Taylor
That's right. And if the whole company is incentivized towards outcomes, we're like a way better partner to work with because of it.
- [68:44]
Patrick Collison
I mean we find this with Stripe where again, we have outcome based pricing.
- [68:47]
Brett Taylor
You've always had outcome based pricing.
- [68:48]
Patrick Collison
Exactly. Yeah, yeah. It's transactional. But we find like there's a lot of uplift we can get on just getting people more revenue and finding ways to, you know, we're sometimes hammering customers where it's like you should be accepting, you know, local payment methods for internationalization or like you're crazy not to be turning on this feature. But we really feel it because like we have the same incentive as the customer. It's like this will be revenue maximizing for both of us. An asked very AGI brained question. I just kind of.
- [69:14]
Brett Taylor
I'm glad we're in a second. Guinness.
- [69:15]
Patrick Collison
Exactly. Yeah. Now we get to it, which is you described building stuff that you know you're going to throw away because the model capabilities will get there. And you're like, occasionally they are developing capabilities that you developed yourself. Isn't Sierra itself kind of shortage? Yeah, sorry, I said I couldn't resist.
- [69:34]
Brett Taylor
No, it's the right question. You know, the short answer is I don't know. I mean the fog of war in the software industry is pretty thick right now. I really believe in the applied AI market though. I think most companies don't want to buy models or buy software. They want to buy solutions to their problem. And if you just go back to the cloud industry, why doesn't Amazon and Microsoft do everything for everyone? There's not really like a sort of by somewhat similar logic, like why should any software as a service company exist when you have bigger scale all this technology, in theory they could just develop all the software and actually many of them have tried. There's actually competitors to Salesforce and almost all the above. I think there's so much nuance in how these companies align themselves with different departments at these companies solve their very unique problems in very specific ways. That is a mix of product, not technology, but product go to market. It's an ecosystem around it. And I think a lot of that still exists because I'm not sure coding the software was necessarily the hard part. And then similarly, I actually think, especially in enterprise software, how you engage with your clients really matters. And I think it turns out that GPT5 and Claude, whatever version it's on right now, or Opus, excuse me, is sold to a different buyer than like the CFO or the chief customer officer or the chief digital officer. And that seems small, but it's actually big. And so I think you tend to see software companies orient around individual buyers within companies. You tend to see consolidation around departments and around buyers. It's possible that you can go beyond those lines, but it hasn't happened traditionally. And I think the reason for it is most business users want actual solutions to their problems and they want a company that serves their unique problems in a very specific and bespoke way. So I actually am extremely bullish on applied AI. I actually think we could accelerate. I'll make one statement which is I think if we paused model development, we'd still have trillions of dollars of economic value.
- [71:54]
Patrick Collison
I totally agree.
- [71:55]
Brett Taylor
That have yet to be realized. And I think if we had a mature applied AI market where the CFO could go buy that agent to onboard new supply chain vendors that just worked, we could actually accelerate that trillions of dollars of economic value. So I think not only am I somewhat skeptical that there will only be like two companies in the world, I actually think one of the main things impeding adoption of AI is the lack of existence of all those other companies. And so many of the startups, particularly here in San Francisco, are basically doing relatively rote kind of tools around the AI rather than actually building agents for business processes that are boring but important and valuable. So I'm really bullish on it.
- [72:38]
Patrick Collison
Yeah, yeah. And I guess you help companies ensure that they can always have access to the latest models, which sounds like a minor thing but like the leading model is always changing and so that's not a trivial.
- [72:50]
Brett Taylor
I agree. And I don't know, like, I'm not sure how much a long term value is. I think it is, you know, I think your customer up to this point
- [72:57]
Patrick Collison
the like the race is led by a matter of months, right?
- [73:01]
Brett Taylor
Well, every single month there's a new frontier model and your customer experience doesn't change that frequently. So you're absolutely right. But I also think there's just a big product like our clients use it to optimize their sales and that is a product, not a technology. And it's very particular to the workflows of people building customer experience teams building Sales teams, and that's like really what we're focused on. And I think those departments deserve purpose built software and I think there'll be enduring value there. But it's interesting, it's the right question to ask. I don't think we've ever lived in a world where production of software was easy and, you know, software engineering was the most scarce access asset in a company and now it's the most plentiful. And I don't think we've ever lived in that world.
- [73:44]
Patrick Collison
Yes, yes. Well, that kind of gets to one of the biggest conundrums in Silicon Valley right now is what will the shape of AI productivity be? And I think there's this strong sense that the AI has gotten really good and it should change the composition of companies and it should change the hiring plans somewhat. And you've seen this in some corners. Block announced their 45%, 50% AI layoff yesterday. And you have some companies not growing as quickly. At the same time, in coding,
- [74:30]
Brett Taylor
you
- [74:31]
Patrick Collison
see a lot of AI benefits. You can kind of argue that either way, right? You can say engineers have gotten much more productive, therefore we should hire fewer engineers. Or you could say engineers have gotten much more productive. The ROI on a single engineer is way higher. Like we now have super engineers that we can hire, therefore we should hire way more of them because there isn't like a fixed amount of stuff for Stripe or any other company to do. And then the AI productivity story in other roles is just a bit less clear because as we've discussed, AI is kind of uniquely well suited to coding. And so what do you make of just how does the AI productivity show up? I feel like every company in Silicon Valley is trying to figure this out right now.
- [75:12]
Brett Taylor
Well, first I think I'll go back to my why I believe in applied AI. I think the atomic unit of productivity in AI is a process, not a person. I don't think AI. I don't know if you have an assistant, but if you do, he or she might help you prepare for a podcast, might help you prepare for a meeting. He or she might also get you a cup of coffee. AI will be really good at the first two, but quite poor at the last one. So no matter of AGI, short of robotics will get you a cup of coffee. So I think it's wrong to think about AI as like sort of replacing people in addition to being inhumane. It's just sort of nonsensical because AI often sort of operates in the world of digital technologies. And I think if you go to like an example of even a mundane process in your business, like onboarding a new supplier. Think about all the departments and people involved in that. There's a legal department to do a contract, there's some finance department procurement to negotiate the relationship. You probably have it that's involved to sort of onboard them into your core systems. And then there's usually a business that's sort of sponsoring it. Fairly mundane, happens all the time. Let's just say you tracked what is the median amount of time it takes to onboard a new supplier and it was 17 days. Just for argument's sake, I bet you could say as a CEO of a company, I want to use AI to optimize that process and make it 17 hours or one day. And you could go through and if you had a product manager on that and optimize every part of it, I bet you could achieve that. But the hard part isn't like a person's job. It's actually all the systems and people in between it. And so I think part of the reason why I think it's been slow to get the productivity enhancement is we sort of ship our org charts as companies. Naturally, that's the natural state. There's not usually a person responsible for that process. There's the legal team responsible for the contract, there's a procurement team. So I think actually we will end up reimagining our companies with the benefit of AI. Will we actually think of our companies as a collection of processes, have people responsible then with KPIs who can apply AI? And I think I bring it up just because that's my theory of the world. I might be wrong, I might be right, but I'm not sure. Companies are set up to essentially absorb the benefits of AI efficiently right now, and we need to do that to really do so. But the bigger point, I think is that there's the paradox of, well, you want more software engineers, but on top of that, most of the world isn't just digital technology. And so I think a lot of the people in sort of the AGI community have only ever worked at like a research lab or software company. You look around, you're like, wow, AI is going to do all of this. And as they walk by the flower shop and get their coffee at the coffee shop and you think about like the local flower shop, like if you took all the AI in the world and gave it to that, you gave it super intelligence, like, how much would it impact the flower shop's operations? Like maybe a little. I mean, I'm sure it would help, don't get me wrong, but someone's still clipping the ends of the stems of the flowers, arranging the bouquets and thanking you on your way out the door and congratulating you for your daughter's wedding or whatever it is. And so I think if you think about what parts of the economy can absorb intelligence really efficiently, it's certainly software. And we're seeing that already. Finance seems particularly meaningful here because so much of finance today is just digital information. You know, we sort of, everything's in digital systems now. Not even just crypto. I mean, just everything's in digital ledgers everywhere. It still doesn't touch a wet lab. It's still, you know, can't do a clinical trial. You know, you still need to get, you know, crate from this country to that country, you know, on a ship. So as a consequence, I think, I'm not sure we'll see the productivity enhancement we see in software in every sector as quickly. And then on top of that, I think companies need to stop just giving like copilot to every employee and be like we're AI now and start to think about from first principles, what are the parts of your business that have a lot of digital workflows? Where can AI have a real big impact? And how do you actually set up your company to actually have someone accountable to drive that? And that feels like a real big change management opportunity that most companies haven't done well.
- [79:38]
Patrick Collison
Yeah, just to push on that. So software engineering, I think we clearly are seeing a lot of AI productivity gains and software engineers have always loved tools and the latest tools and are just kind of headlong diving into it. Then you have stuff like you're seeing the flower shop where just stuff that requires really good robotics that we're far away from, that will take a while. What I'm talking about is like there's like a.
- [80:02]
Brett Taylor
And by the way, I might prefer a flower shop with the florist. Totally.
- [80:08]
Patrick Collison
Yeah.
- [80:09]
Brett Taylor
Yeah. Just to say it, I'm not sure it solves, I'm not sure it solves a problem I have in my flower shop. Absolutely. I might be wrong, I might be unique in that. But that's, but I think a lot
- [80:17]
Patrick Collison
of the company, a lot of the economy is actually white collar knowledge work, not coding. Think of finance departments, legal departments, things like that, where you should be able to see a lot of AI uplifting and a lot of AI productivity improvements. And it just feels like at current course and speed, we're not on track to get those productivity improvements.
- [80:43]
Brett Taylor
Well, I'm not sure I'm right, but I would argue thinking about it by department rather than by processes, where it's off.
- [80:50]
Patrick Collison
We can talk about the processes as well.
- [80:52]
Brett Taylor
Hear me out though on this, because if you said I want to make the legal department more productive so I want to make it easier to do red lines and you optimize that. But why is the contract there? What is it for? You might, if you're for example, onboarding a supply chain vendor and you have hundreds of them, you might actually say actually making an abstract technology for your legal department to redline contracts more efficient is actually a harder, more general problem than for your supply chain vendors because you might actually have very rigid rules around your supply chain. Let's say you're a CPG company and you might actually have very specific saying like, look, if you want to work with us, here's our core legal terms, here's the axes of independence. And if you want to make an AI agent to automate that contract, that's actually a much more narrow problem domain that doesn't require general purpose redlining technology. In fact, if you sort of reduce it, you could say, well, There are like 10% of our suppliers where we let them negotiate their contract, but only for this spend, let's have them go through our legal department. The rest, let's do it all with AI. And my point on it is if you look at it through the lens of like an end to end business process, you can turn science into engineering. And I think solving legal through AI, that's a science problem. And this is my point though, which is I think people are going through department by department. Similarly, there's not like a person accountable for that end to end process. And the more you can narrow the domain that you're solving with AI, the more you can build a harness or a scaffolding with existing technology to actually fully automate it. And my hypothesis is most companies just aren't set up that way. That's just not how we're organized. And as a consequence we're all optimizing our silo. We're all just installing copilot. And copilot's great by the way. Didn't mean to insult it, but it's not actually like, yeah, yeah, and to
- [82:51]
Patrick Collison
be clear, like that's the kind of thing we're doing where. And obviously good companies did this before AI, continuous process improvement. And it feels like that is the best thing to do. And I think what you're saying is there's no such thing as an AI lawyer. Instead there's improving your commercial contracting. That is a thing that you can
- [83:10]
Brett Taylor
tend to and even more narrowly pick one domain of commercial contracting and solve that. And I actually think those are truly solvable. And I think the companies that really think about their business that way, I think they can see the value. And again, I'll go back to the immaturity of the applied AI market is probably one of the bigger barriers right now. And my hope is that as the applied AI market matures over the next few years, we'll see kind of a step change in productivity.
- [83:40]
Patrick Collison
Yeah, there is a canonical way to build a Silicon Valley company. You have engineering and product and design. You have this number of ratios of engineers to product managers and engineering managers and then you have your go to market organization and you have these pipeline coverage ratios and you have, you know, the product marketers and all this kind of stuff. But I find it interesting how similar so many Silicon Valley companies are to each other because they've all learned from each other. Right. There's like a shared recipe and a shared playbook as to how to build a company and it gets tweaked. But ultimately I think it's pretty good IP like certainly companies are much better off with it than without. How is that canonical template for building a company different post AI than before?
- [84:25]
Brett Taylor
Yeah, it's a really interesting question. One is, I've always believed in the primacy of tech leads over engineering managers. Both Google and Facebook, where I spent some of my early career, both did this well, where in a product review you weren't just talking to a manager, you were talking to the tech lead and PM who are product manager who are building the product. Whereas if you went to companies that produced worse software, I'd notice you sort of move up the chain of the command like the military.
- [85:00]
Patrick Collison
Yes.
- [85:01]
Brett Taylor
I think that we will end up with individual tech leads who because of the existence of AI agents will become even more important. Where if you are a. I'll say product engineer, I'm trying to find the right word for it. We might invent one who has taste but didn't necessarily know css, who has infrastructure ability, meaning that you understand the basics of distributed systems and debugging and you understand your customer very deeply. With the presence of Codex you can produce amazing results. Those people are truly worth a thousand x other people. Because it's relatively easy to find someone who's a great infrastructure engineer. Not easy easy, but like relatively finding someone with good taste that's relatively Easy. Find someone who also understands your customers extremely well, like the nuances of the problem they're solving. Those people who can combine that will, I think, end up being able to actually produce products like Capital P, valuable products with relative autonomy. And I wonder if it will change our view on generalists broadly. I've always identified myself as a generalist just because I've been both a software engineer in a suit basically, and I've gone to kind of back and forth in that world. And as companies grow, you tend towards more specialization. Just because the person who's sort of the Jack or Jill of all trades ends up sort of not fitting in, there's not really a place for them because, okay, well, you're not really the deepest engineer, you're not really the best designer, you're not really a product manager. If you've been at the company for a while, we'll give you an honorary something to do. And you have to lead through influence and da da, da da, could that person actually endure as one of the most valuable people in these companies? And I think, I don't know whether it's naive optimism or true, but I actually think those people who often exist in early stage startups are often the people who get sidelined, but actually in a way that actually really harms the company. And I'm hopeful that in a world of AI agents, those generalists who, again I think the most important part is understanding the customer need with agency, no pun intended, and empowerment can end up more powerful in the Silicon Valley company.
- [87:36]
Patrick Collison
I've noticed the exact same thing at Stripe, the exact same thing, which is high agency, really caring about customers, just really caring, generally high work ethic people who maybe weren't the best engineers previously or now. Those people are massively ascendant, as far as I can tell, because they suddenly got the exoskeleton and they always had the ideas as to what we should be doing and this is the better way to serve the customers and everything like that. But now they have the way to make all their schemes real. I've really noticed that at Stripe.
- [88:16]
Brett Taylor
Well, it's interesting, you talked about work ethic. It's addictive right now because you can do so much with the technology. Everyone I know who's really used it works harder because it's like, wow, I could do so much. You think you're about to go to bed and you're like, should I get an AI agent to do something? Am I wasting the next 8 hours of my life that might be a novelty that Wears off. But I think it's really exciting. So I'm hopeful on the product engineering, design side, you end up with these hyper high agency people who really deeply care. I really like the way you said it, actually. It's Right. It's not just customer problems. It's like care, period. Just care can end up more empowered. And I'm curious what that means for organizational structures. You know, it's.
- [89:07]
Patrick Collison
I think we have a new job role we need to invent. It's like what roles are these people in?
- [89:11]
Brett Taylor
I mean, hyper generalists.
- [89:13]
Patrick Collison
Yeah. Like kind of product managers. But like sometimes maybe without a product, like minister without a portfolio, they're just doing stuff. But now they can do much more.
- [89:20]
Brett Taylor
Yeah. And it's almost like product designer, product manager, engineer. That's why I said product engineer. But that means something different. But it's interesting because we've talked about this. You end up where the grass is always greener with orange structure. So you go, functional organization. Okay. We're going to have engineering, product design. Let's go to business units. They're like, wow, that led to silos and more infections. You sway back again. That's welcome to just one more reorganization. Yeah, exactly. I'm a middle manager now and I think that it is interesting if these people become extremely important. What does it mean to organize around them? And I think it does feel like something that will end up flatter just because of the amount of impact an individual can have. And so that feels really exciting to me. But I don't really. It sort of feels like a blurry picture right now. Enhancement.
- [90:14]
Patrick Collison
I agree. It's very blurry. It's so interesting. You were on the Twitter board during the super interesting takeover battle with Elon Musk. What are your reflections on that experience a few years later?
- [90:32]
Brett Taylor
It was really interesting to sort of be in the public spotlight. I hadn't really experienced that in my career before. I joke like, no one really cares about enterprise software. I worked for Salesforce for six and a half years. Sorry, what's the joke? I worked for Salesforce for six and a half years and I don't think my mom knows what Salesforce does. And so to have something that was not really just like a business issue or a technology issue, but like sort of in the mainstream, I realized I didn't love that very much. You know, like, I prefer enterprise software. Exactly. I'm like a builder. I like to build things and have people use them. I know it sounds sort of funny and reductive. That's what Gives me joy. So the one thing I realized is the conflict of it all. However it turned out, like victory, defeat, whatever it was, it wasn't something that filled my bucket very much.
- [91:31]
Patrick Collison
What do you make of the fact that in all these kind of headcount debates, Elon is now running Twitter with 80, 85% fewer people? I think Nikita Beard tweeted recently that all of Eng product and design Twitter is 50 people. And you know, maybe it's really impressive. Yeah, it's been a little flaky in pockets or just at times. But mostly the service works and they have shipped new features. And I think those two statements are undeniable. But just what's your takeaway from that?
- [92:04]
Brett Taylor
I don't know. I haven't followed as much as sort of the like. I didn't see that tweet as an example. Do you call it tweet still?
- [92:10]
Patrick Collison
Sorry, I'm retro, I'm old fashioned zeet.
- [92:14]
Brett Taylor
So I don't know about that. But I mean, it is interesting right now because obviously a lot of that predated AI. But I mean any person who's been an individual contributor, engineer knows that the size of the team does not produce linearly greater outcomes. Everyone in the world has experienced that. Yeah. So, you know, I think the, you know, the idea of can you actually give individuals with good taste more agency, no pun intended. I think it's always been sort of an enduring thing. What was Jeff Bezos a two pizza box sort of thing.
- [92:49]
Patrick Collison
But then do large tech companies underrate this phenomenon? Like, do they pay lip service to small empowered teams and two pizza teams, but extras that maybe they should be doing it more?
- [93:00]
Brett Taylor
I think companies largely act somewhat rationally. I can't remember who the CEO was, but it might have been the rippling CEO. Just talking about there's this idea of being lean and agile and then there's like, you want to capture market share and grow your product and grow your platform. And at the end of the day, you can be clever but not smart. And you might be so clever to think I'm not going to have anything more than two people on these features. And if you have a competitor who maybe does something a little less elegantly but wins, who cares that you were clever with your two pizza box team or two person team or one AI agent team or whatever it is? When someone said we're going to have a X billion dollar company with one person, I think they might have been right. But it's not.
- [93:50]
Patrick Collison
You could have had a $10 billion company if you'd hired a bit more.
- [93:53]
Brett Taylor
That's right. And I would actually argue the more specific thing is if all of a sudden, for some clever reason, you want to prove you can, the idea that a competitor might have 10 people and beat you is probably more likely than even having a $10 billion company. And so I think at the end of the day, when you're building a business, especially one that's in hyper growth, which successful businesses in tech tend to be, if you are too clever and austere and going back to your point about Silicon Valley cultures all being the same, there are examples of companies that really innovated in culture. You wouldn't think of it this way, but hp sort of like a lot of the kind of traditional open office floor plan came from them. Facebook. Oh, I didn't know that. That's interesting. And then Google offered free food to their employees, which a lot of people did. And then Facebook, a lot of the layouts of offices all look like Facebook for a long time. But then you have other companies like, working to innovate in hr and they spend all this time and energy on it. And in fact, the smart thing to do is just be like, it's not what we do. Let's just do the same old thing as everyone else. Because everything is just push button. I don't need to worry about it. And so I do think it's the right question to ask for every technology company. Yeah.
- [95:15]
Patrick Collison
After being on the Twitter board during the Elon takeover, you were then on the OpenAI board when Sam got fired. Have you considered that you are the problem? You are bringing the drama.
- [95:28]
Brett Taylor
I came in after the drama there. Oh, right.
- [95:30]
Patrick Collison
You joined after. Oh, sorry.
- [95:32]
Brett Taylor
I was brought in as the mediator.
- [95:34]
Patrick Collison
I see. Post the. Okay, yeah, okay.
- [95:36]
Brett Taylor
Your hands are maligning my reputation here. Yeah, I was. I wasn't actually on the other side of it, but I got a phone call. Was it Saturday or Friday after? And basically my understanding was I was the person that both the existing board and Sam agreed upon to kind of help mediate the situation.
- [95:55]
Patrick Collison
What have you Learned in the OpenAI board?
- [95:59]
Brett Taylor
A lot. I mean, certainly the most interesting part is the AI research. I've never been affiliated with a true research lab before, and that's fascinating to me. It is very inspiring. I mean, it's very easy to grow. Not cynical. But you can look at OpenAI, Google Anthropic, and say, whose model scores better on this leaderboard? To actually go in and see this company where every single researcher trying to make Safe AGI and not come out of those board means inspired is impossible. It's amazing. The other thing is it's the first not for profit board I've been affiliated with. And that's really interesting as well. Just because.
- [96:46]
Patrick Collison
Different thing.
- [96:46]
Brett Taylor
Yeah, well, and I mentioned the fiduciary duty is you have a duty to submission. Yeah. And that is really clarifying and interesting as well because when you're making decisions and you realize, you know, you have your sole duty is to ensure that artificial general intelligence benefits humanity. That's really different. It's really interesting. I've never had a fiduciary duty to a mission before, so that's really interesting to me because I take those duties really seriously. And like reflecting in a board meeting and you're making a decision, you think about it very differently through that context. And then the other thing was, because I was brought in after that crisis, there was three people on the board. On the other side of that, when I agreed to temporarily be the chairman is still there.
- [97:32]
Patrick Collison
Funny, that works.
- [97:32]
Brett Taylor
We had to grow the board essentially from scratch. And so that was really interesting too, just to think about. Normally you add one board member at a time. This one was like, do you have a bulk rake?
- [97:44]
Patrick Collison
We're going to build a board, put together a team.
- [97:47]
Brett Taylor
So you really think about, spend time with the other two board members, just really thinking about what does the composition for an OpenAI board look like? How do you represent the not for profit part of it? How do you represent safety? How do you represent the economic impact of AI? Oh, we're doing lots of infrastructure investments. How do we find someone with that specific type of financial expertise that was really rewarding as well. Just sort of building a board not from scratch, but effectively from scratch.
- [98:17]
Patrick Collison
Last question. What are your AI predictions for 2026?
- [98:20]
Brett Taylor
I think we will have some scientific breakthroughs with AI that positively break through into the mainstream press and awareness. We've already had some interesting math proofs, but I joked with one of my friends, like until I can understand what the title means, I'm not sure it's going to make.
- [98:42]
Patrick Collison
I'm not excited about N dimensional manifold space.
- [98:45]
Brett Taylor
Exactly. And it won't quite be like the Apollo landing, but I remember the Kasparov chess match and Certainly things like AlphaGo were really meaningful given the progress in math. I'm hopeful we have at least one moment of discovery that is inspiring because I think a lot of the dialogue around AI right now is economic opportunities, but also what could go wrong. And I actually think one of the main things that can go right is actually discovery and science that actually can improve the human condition. So I'm really excited for it because I think it will contextualize why so many of us are excited about this technology in a way that sort of captures attention. So, as you said, something beyond N dimensional manifold, blah, blah, blah, and I feel not confident in that, but it certainly feels like the ingredients are there for that. I think we'll continue to see mainstream adoption of AI by both consumers and companies. That doesn't really feel like a prediction, but I think this will be really a year of adoption of agents, and we're certainly seeing that in Cira's customer base, but I think we're going to see it more writ large. And then you already see in ChatGPT growth, really unprecedented levels and things like OpenClaw, you can sort of see that kind of translate over to agents and sort of the. More like long running autonomous tasks. So it does feel like by the time we exit this year, can that go from a niche community to something more mainstream? It feels probable to me. And then the other thing is, I think most companies in Silicon Valley won't write code by hand. And that might seem almost. It's sort of funny that it sort of feels obvious right now. You're like, oh, yeah, of course. You're just nodding like, yeah, of course, yeah, why not? But if I had said that like four months ago, that would have been a bold prediction. But I think that's really interesting just because that's such a fundamental state change. And I say in Silicon Valley, because I do think it takes a while for these tools to sort of diffuse through society. Silicon Valley is insular enough that I think it will here, but I'm not sure it will happen through every company in the world yet.
- [101:08]
Patrick Collison
So the year of agents across businesses and just people finally getting their kind of cloth agents and then, yeah, all code written by AI as well.
- [101:16]
Brett Taylor
Yeah, it's good celebrations. Right?
- [101:18]
Patrick Collison
Thank you.
- [101:18]
Brett Taylor
Thanks for having me.