Inside the Personal AI Assistant Growing 10% a Day - Noah Shinn

transcript

I can't help but wonder about the sort of grand game that is afoot here. When you really step back and think about what is happening right now, like what is the game, what is going on here right now? Like if you had to sum it up, the thing you're in the middle of. You're going up against the biggest players in the world. The window to do it is actually on the order of once. The compute required to it is over $1 at just this year alone. And you have no distribution advantage, but you have this massively growing viral product.

What do you do? This is probably the most exciting software race ever. And the outcome is like trillions of dollars. You know, I know this is the first time that you're talking about the business in this long form like this. I'm incredibly excited to ask you all about it. It seems like we're in a moment with personal agents that is very similar and arguably probably bigger than what we saw with co-generation a year or so ago. Maybe frame this up for us to begin. Like how are you thinking about the impact that, of course, your product, but these agents are going to have on the world?

Why is this the area that you've chosen to dedicate yourself to completely? I think out of this will come a new way that most people on the planet interact with technology broadly. I run Instinct. It's a new company that I started about a year ago. So it's still a new company. And we're building a personal assistant. I'm not going to spice it up because it's really just a personal assistant. And I think that the thing that has really enabled us to gain quite a bit of traction early and quite a bit of excitement early is it just works. Like it works in the way that I would say we all like we, meaning I am also a user, we all have really been waiting for AI to to act for us. So I would say one interesting thing is that this is not like any other, you know, transformational consumer app experience where it's the founder coming on and saying,

I have this new vision for the world where this is going to, you know, trust me on this. And in a few years, you know, from now you guys will all get it. This is a very different moment of building product because you and I, we all already have this idea of what AI should act like. We've already had that idea since 2023 when we all started the brainstorm, when we started to use chat GPT for the first time, you know, that that agent that is able to help you with effectively anything in your everyday life, whether it's something new and creative that you that you want to do, whether it's something that you traditionally spend, you know, several hours on and it takes a long time to to develop. It's just everyday intelligence.

It's meant to be with you, to act with you. It's meant to feel like a very simple interface. So when I mean simple interface, what I mean is we actually don't even have an application. Like this is not a new app. This is not a new tool. It's a new experience. So, you know, it has a phone and a computer so you can text it. You can call it. It can actually call you too. So I don't know if you've experienced this yet. I have. Oh, you have. I think it's only called me about three times so far in the in the several months that I've been using it. But it's funny if there's something genuinely pressing and has it, you know, a deadline, it will call you and it'll call in it and it'll say, I don't want to bother you too much. But but this this you need to sign this document by 3 p.m. and it's 255 right now. Can you please do that? It's in your inbox.

I can, you know, I can even send you another email to push it up to the top. Right. So it's very, you know, it's socially intelligent and very socially aware. You can email it. It has its own email address. I don't want to confuse the simple interface with limited ability because the whole nature of it is that there shouldn't be any new application needed to be able to interact with AI. I think it should have the social intelligence and awareness to be able to act with you just like we do with other people. It's really meant to be the simplest possible experience. Yet the capabilities are, you know, it has a computer so it can do quite literally anything that you might want to do or that you do yourself on the Internet. Tell us the couple craziest stories that come to mind for what people just things that have happened because of instinct. I ask this question because you're not

programming to do any one thing. You're programming with a phone and a computer to be able to do anything. The U.S. Open example, I think, is one that everyone's familiar with. This couple wanted the they showed up on the Jumbotron and they wanted like the video footage of it and somehow it went out and figured this out and brought it back to them, which is kind of crazy. What are your favorite couple examples of just wild things that have happened because of instinct for those that like online shopping? There's actually a group of people that are sharing this and making this a more recurring use case, which is scanning every item or every piece of clothing in their wardrobe. So they go in the wardrobe and scan every single item, you know, every every top and bottom and sock and, you know, whatever shoes and then they would scan themselves to like their their face and their body and their proportions and then they would go try on

clothes and they would have it plan out their week in terms of what to what to wear. So every week with their existing wardrobe, you know, what shoes to wear, what top to wear with this certain thing and this certain version of it. And then it would it would not send it as here are the items you should wear like a bullet point list, but it would be them wearing it and showing like this is what what today will look like. But not only that, it's also with with shopping too. So they'll take those same capabilities, but then say go shop on the Internet. They come with thousands of outfits from so many different places like this one.

Here are the pieces from the top to bottom and you know, and then and then they can just say order. So it'll come in with a thousand different options. Then they'll scan, you know, keep in mind, they're looking at themselves wearing wearing the clothing. Right. And then they'll be able to point to like that one. I really want can you send it to my house? And then not only that, but they'll say every day, can you actually just come up with like three creative new outfits from head to toe and then send those to me and then they're able to with the click of a button actually just, you know, get get that new outfit. A lot of like goal oriented sort of use cases to like a lot of here's a certain personal finance goal that I have. Like, I want to save this much money by this month and it's actively working with them to be able to

do that or users connect like their bank accounts to to instinct and and then it can scan over all the transactions and subscriptions that they've had and then surface that to to the user and say like, do you really, you know, actually use this? And then they're like, oh, no, I didn't even know that. And then it can go in the email and unsubscribe from it. Yes, yes, it can go and then, you know, these these popular consumer like fintech products where they'll just like surface it to you and then tell you like, by the way, you should cancel these. This will go and to end so it would go into the site sign in if it's there's some sort of like confirmation that goes to their email or has access to email. So they use that and they sign in, they go to the very end, they cancel the subscription and then it just sends back the number of what it saved you like, hey,

by the way, you're you're saving two thousand dollars this month because of these things. And any product that's dependent on consumer laziness or inertia is toast, huh? Like toast. Yes. That's good. Good for the consumer. Can you tell us about the instinct to instinct network? Oh, yes. The future of agents talking to each other. There are more practical scenarios where that is something new that I think will be, you know, transform the way that certain people act in certain ways. I think it's only been around for for a week or so early, I guess, 10 days. Honestly, the purpose of this is not to think about like a new new feature to build, but more about very busy working professionals.

You know, they're taking meetings all day long and and they're they're constantly meeting with like new people and existing people. You know, the process of getting a meeting on the calendar, you know, it's just so so so laborious. You know, you text and hey, you want to meet at this time and then they say, no, that doesn't work like that. These times work and you say, often I'm traveling. So maybe this time works and I'll be in this time zone, though. And there's just so much back and forth there. However, if it was possible for, you know, the two users who were using instinct, probably, you know, also like brainstorming these times that they're available with instinct anyways on the other on two ends are able to just communicate directly like, hey, the goal is just to find the time, right? We don't need to play this back and forth game and nobody's really playing games here. We're just trying to

find time. That's been a very canonical use case, actually. I think the the way that you can find time on a calendar now is just so different where you just say your intention. I want to meet with this person ideally by the end of the week or at the during these periods of time, find me time. It will then coordinate with with the other person's instinct to be able to find like one time is available or not. And then eventually put something on the calendar. I think the key unlock here, we called it a trusted person network. And the key is that it you should only be connected with your trusted people. And there are some interesting social dynamics that are coming out into play that that that I've been that I've been learning about where, you know, it's designed such that you only bring in people who are trusted, trusted people who are not going to maliciously try to find out what your calendar is,

what or what's in your email. But also, not only that, we provide all the controls to be able to give different levels of access to different people. So, you know, a lot of spouses actually coordinate their instincts because they can generally just share everything. So that might just be, hey, this, this is my spouse. Just share any anything with them, right? Maybe with a certain colleagues, right? It's hey, my work calendar is available. My certain parts of my inbox, if they're asking for documentation or something like that are available. But everything else, like let's just keep that off limits, you know, be able to create that. When you think about this, there's almost like these network effects that are built through these like nodes in the network with these different edges with different weights to write. It's not like a friend graph where you're just saying, like, I'm connected to you and that's it, right? It's I'm connected to you.

I trust you. I have also, you know, configured it in this way such that there's varying levels of access. So it's this interesting, like network effect almost almost being created and different social dynamics that are being also explored and created as well. There are some interesting cases that I've learned about where if somebody violates your whatever your trust within a network, there's an implication on the on that relationship itself, right? So let's say if you and I connected, right. Right. And then I said, like, hey, Patrick, I, you know, I trust you. Let's let's connect on the platform so that it's easier for the next, you know, maybe the next time to put time on the calendar. And then you use that and you then start digging for certain data in a certain area. First of all, maybe I only gave you calendar access, right? But you're digging for data in a certain area. And in my

instinct, text me like, hey, by the way, Patrick's like looking for this type of information. Now there's kind of like almost like a trust broken, you know, between the two of us. All of these little like sort of social dynamics that come into play. We've really thought about how to curate this network such that you do get the benefit, right, to, you know, schedule time and make plans with others and other things like that. But then also use some of the existing rules in society to be able to enforce both rules in terms of social cultural norms and also of, you know, technical limitations in terms of what is visible and not visible. We're really going to see just like an entirely new order, aren't we? It's going to be fascinating. The number of things I can think of, let's just take, you know, with my wife or something. This would make life so much easier in so many different ways so quickly. Even little things like, you know,

you were trying to find this house earlier, like, if I could just say to my instinct, hey, it's no one nearby, like where is it? And you give me a one day permission or something like this. There's just so many ways to imagine it being useful. It's pretty wild. With the trusted network, we find a lot of very interesting cases because or example use cases that are shared because it is the one part about the platform that is, I would say a, you know, if every other person is like, hey, I'm going to do this. And then it's always this active acting and you text the group, hey, do you want to do this? And then always somebody is not willing to do it. And then eventually falls apart, right? And that happens every time. And then finally, when you get people together, that's when you have that, that you're able to actually attend that event or whatever

it might be. There's a friend group that put in every week, just brainstorm something creative that is interesting that we all like and actually just make it a different experience every week. But then it'll go through that every week and not only coordinate when everybody's available and what their interests are and if they like certain things or not like certain things or what shows are available, what concerts, you know, based on their music tastes because all their Spotify history connected and all, you know, that same friend group that they had. It was like a group of like six. They had one person order an Uber, but then that Uber to go around to all the six people and coordinate like, hey, we'll pick you up in 10 minutes. And then the other person will pick you up in five minutes from here. And I found the optimal route to go and pick up all the people and now they're all just sharing like one Uber. So it's actually like very economically

friendly. There's like all these random examples there of people discovering like new use cases when you can finally remove the barriers of a lot of the rote social communication here and just make it like remove all of the logistical burden. Ramp is the only platform built to make your finance team leaner, faster and better, saving businesses 5% annually on average. So you can stay focused on growth. Ramp just opened for business in the United Kingdom. So if you're running a business in the UK, you can now use ramps, AI powered finance platform to manage cards, expenses, bills, approvals, and accounting all in one place. I run my business on ramp and so should you learn more at ramp.com slash invest. Rogo is the AI platform purpose built for financial institutions serving tens of thousands of bankers and investors at hundreds of leading firms worldwide. Rogo's AI agents autonomously execute large chunk of your firm's workflows. They can screen deals, draft sims,

run buyer outreach and due diligence on data rooms, all with full security and compliance handled. Every action feeds Rogo intelligence, the firm's context layer, turning years of deal experience into a secure governed institutional memory that makes each new transaction stronger than the last. To learn more, visit rogo.com slash invest. Open AI cursor, anthropic, perplexity and vercel all have something in common. They all use work OS. And here's why. To achieve enterprise adoption at scale, you have to deliver on core capabilities like SSO, skim, RBAC and audit logs. That's where work OS comes in. Instead of spending months building these mission critical capabilities yourself, you can just use work OS API's to gain all of them on day zero.

That's why so many of the top AI teams you hear about already run on work OS. Work OS is the fastest way to become enterprise ready and stay focused on what matters most, your product. Visit work OS.com to get started. It's almost crazy how simple the explanation of this is, but it's easiest to literally just pretend you have a superhuman person with a phone, a computer and email address. They can call you just like dealing with a person and that's it. And that makes me wonder how you think about everyone in the world having one of these, having an instinct, having an agent and how that will reorder things. Code has been incredibly exciting to watch. Of course, everyone listening has had their own version of a magical experience with making something, but not that many people were software engineers before this.

It's a relatively small sect of people that have made code historically. Maybe now it's going to be way more, but this just seems like a different new market, new paradigm. How do you think this will start to reorder the world, the internet commerce, et cetera? What's the future of interfaces, I guess is another way of saying it. I'll break this down and I would say like two parts, just so that we don't sound like complete abstract visionaries and saying that we're going to reinvent the internet. Although I'll be clear, I do think that in the coming years, I think the internet's going to be rewritten. I think that the way that most people on the planet interact with software is going to be very, very different. To break it down though, I think in the short and medium term, famously maybe reservations is one where, you know, like booking a reservation, right? So historically, how is that done?

Well, the human has to go onto the site and to go to whatever restaurant that they care about and then click through the site and then put their two people this time and try to get it, right? And then if they don't get it, they're just too late and it's first come first serve. But then now when you have an agent, you can theoretically just have the agent check every five seconds, you know, not just across that one restaurant that you really care about, that's your favorite restaurant you can't get in. Sure, that's one case, right? But what if it's doing that across every site in the world, for every restaurant in the world, in every major city, right? And now you can see how the agent is able to exploit just something simple like restaurant reservations. So if I go into that a little bit deeper, we have some exciting partnerships to be released in the future, but we are sort of reinventing what the reservation system

is just in this one category, because it's important to our users, which is actually better for both sides, right? So if you take restaurant reservations from scratch, from the user's end, they want the reservation for the significant life event that they might have. It's a birthday, it's an anniversary, it's a friend coming in from out of town. And on the restaurant's end, they just want interesting people, they want special occasions, they want to cater to those rather than maybe the local who keeps taking up a table once a night and there's no sort of special event there. And traditionally, because of the way that the internet has worked, at least for reservations, it's been first come first served. So anyone that comes in, no matter how important or how not important it might be, whoever gets in first gets the reservation.

But what if you had the ability for the agent to be able to communicate on both sides, communicate, hey, this is important, this is actually the person's spouse's birthday, the 30th birthday, a very special event is coming up. And the restaurant too can say, let's actually prioritize birthdays or major decade birthdays or major anniversaries or these certain people, I don't know, whatever it might be, right? So now with the ability, with all of the logistical burden of having to describe exactly what your case is and what's happening and why it's important, now we have the ability to perfectly match what does the restaurant want, what does the user want. And that will result in more special events for the users being able to actually have a spot in the restaurant. And then on the restaurant's end, for them to be able to have a much better audience of people who it's all these different special events or special occasions. So I don't mean to go so deep on restaurant reservations,

I just mean, that's just one example of a traditional model that is changing. I think the same case with a lot of the major travel agencies, honestly, 50% of our transaction volume that goes through our platform is due to travel. Honestly, we're still running like an invite-only program and it's quite early for us now, but we're approaching over a billion dollars a year in transaction volume through the platform. On a small user base? On a very small user base, on a very small user base, there's already over a billion dollars a year transacting. 50% of that is travel alone. Travel agencies that we might all use today, or we meaning the people who are not on instinct yet use today to book hotels or flights or other things like that. Well, what is the benefit of that interface? Well, they probably unify from so many different services and so many different hotel chains and airlines and just present it in a nice way to the user,

when now they can just click on an option, check out immediately through there and just see it in their email. It's a great experience, but I think there's an even better experience through instinct or other similar interfaces where you can just say, hey, I need to be, you know, I'm using a voice recording again because I'm trying to describe how easy it is. Hey, I need to be in New York tonight. This is immediate. And that's it. Right. Well, what does that entail? That means that, you know, first, where is the user right now? Right. Maybe you're in San Francisco, maybe you're in LA or you're somewhere instinct can, you know, if you want, it can see your location.

So it'll say, okay, you're in San Francisco. You need to be in New York. Let me first find all the options. Right. But not only that, all of the nuance to what's the person's airline, preferred airline that they like to fly at. What's the preferred seat type? Right. And what class do you want to sit in? Do you want to be in an aisle seat or, you know, window seat or in the middle seat, you know, etc. What's food options do you want to be delivered to you as well? What credit card would you like to use? Okay. And then it books that that's the flight. Then then it moves on to the hotel. Yeah, presumably all your it learns about you constantly. So yes, your preferences are stored. That is the nice thing. If you tell it one thing, you know, I prefer this. This is my style. This is what I like. This is where I like to stay. One is that

when you're staying anywhere, anywhere in the future, it will be able to use that memory and be able to, you know, now make it a much easier experience for you in the future to be able to book that according to exactly what you want. But not only that, but it'll be able to take that general taste, that general preference that and actually extrapolate that to anything else that you might want to book. So things just become very easy as you start to give it more preferences over time. So anyway, just to close out this example, you know, it'll find the ideal hotel.

Maybe you've already stayed there, you know, the last seven times. And so it's very easy in that way. It'll book it end to end, line it up with your calendar. So it'll put the flight, you know, the flight in the Uber ride that you need to take to get to the airport, the Uber ride to get back from the airport down to the, you know, to the hotel, and then all of the events that you might want to do there. Just take a step back, you know, because I talked so much about what this, what what is happening under the hood. The user really just recorded a voice recording saying, I need to be in New York tonight, right? And everything else is solved. So that's what I mean when I say that meet the users where they are, where is the delightful experience? Well, this is a new delightful experience that I believe is going to transform even the travel agency alone.

And so for these businesses that are, you know, traditionally, you know, make a lot of money from providing standardized interfaces, what happens when a new standardized interface comes into play, that is just that much easier, right? What does that mean? And I'm not saying that we're in the business of trying to disrupt those businesses, businesses, I think they do provide quite a bit of value from the data that they've, you know, collected over time and the and the networks that they have, it'll be a collaboration over the next year, couple years to be able to redefine what that industry acts like. What has it been like getting people and learning what it takes to get people to trust their agent, their thing, I would love to go fairly deep here, we were talking about this, this past week. And I love the examples that you've given about moments where people are showing trust and data you started to gather and lessons you're starting to learn about the

importance of trusting this thing. I'd love you to talk about the trade off between privacy and effectiveness of these agents. Obviously, like the more context, the more passwords, the more everything you give it, the more it can do. And I think people are constantly running that trade off in their head when they're interfacing with the thing. Talk about that. Talk about trust, what you've learned so far. There's an interesting data flywheel or sort of like chicken and egg problem here, which is the more data that you give to it, the more proactive that it can be, the more sympathetic to your situation that it can be, the more that it has to just act and be more useful to you. What we find in the data is actually that it takes actually several weeks to build trust. And I actually don't have a problem with that because one of the core principles on our end is the user should feel in control of their data.

They should always be in control of their data. They should share data with instinct at the rate at which they feel comfortable with. And if they want to take it back, they can certainly take it back. And what we find is over several weeks, I believe I was looking at the numbers the other day, three weeks and there's a 40% chance that the user has shared a personal credit card with instinct. That's 40% of the user base. That's including some proportion of that user base probably turned in that moment too, or at least turned before that point. So 40% of the user base, the reason why I'm sharing this is because time to like first credit card or time to first account password or time to first a sensitive piece of information, these are proxies for trust.

And we actually highly value this and we take it very seriously. So 40% of the user base, three weeks in are sharing a credit card. Well, there's something there, right? There's something there, no pun intended. It's like instinctual to go to it with whatever you need. And so through that process over the first, I guess, three weeks, the user learns to build trust. And then from there, it's just a snowballing effect. We actually find that when users connect at least one piece of sensitive information to instinct and really trust instinct, there's like an 80% retention rate, 80% if you share one piece of information.

Just crazy for consumer technology. How should people out there that want to try this but have a natural reticence to trust, not instinct in particular, but just anything, any AI agent with all of its information? How should they think about the actual risk of doing this? And how would you reassure them that you've built your technology in such a way that the odds of something bad happening if they do trust you with very sensitive stuff are really low or close to zero? There's a way to break this problem down into two main parts. One is just the storage of sensitive information. There are many other businesses, there are many other products that also deal with this problem of they have access to sensitive information and what are they doing proactively to make sure that that is isolated and locked down. And then there's a second area, which is the new problems that we need to solve, the new surface areas or the new

capabilities that we need to be aware of. The first case is this is a tractable problem. It's just very hard work and attention and care that you need to put into making sure a sense of data shared is safe and that the user is in full control over that data. There's that second category, which I'll spend more time talking about, which is, you know, this is the first time that an agent has been able to have, you know, I said within three weeks, 40% of the user base is giving Instinct access to a credit card autonomously, right? To be able to purchase, you know, theoretically anywhere. I don't know the numbers on email and what proportion of users connect an email, but you know, you can imagine full access to an email inbox and into a calendar. So there's a lot of service area here. There are systems that we've put in place that are detached from the, from Instinct,

the agent architecture itself that are put in place to be proactive about these things and to sort of like decouple the risk, if I were to say. So for example, any piece of content, any piece of text, anything, any form of media that comes in that might be consumed by Instinct goes through what we call these firewalls, which can intercept, that can reject, that can, you know, block malicious pieces of content coming in and, you know, hitting Instinct and, you know, trying to convince the, you know, Instinct to do something. There is also, for every action that Instinct might take or for every thought that it might have, that is being actively monitored by a system that is decoupled from Instinct itself, which is able to pause it, intercept it, to, you know, approve or disapprove of what might happen next before it takes the action. I mean, those are just two pieces put in place,

but there's just so much more, there's so much more under the hood that is put in place to enable the agent to be as capable as possible, but also safe and trustworthy. There's, I have this question around, I don't have a better word than alignment. And I know alignment is a very loaded word in AI. I don't mean humanity scale alignment. I mean an agent aligned with me personally. If I think about other agents I've hired, like employees, I pay the money and therefore I trust them to have my interests at heart. It won't be perfect, but they don't have some other alternative incentive stream that guides their behavior.

They're guided by their employment. How do you think about the business model vis-a-vis alignment? Like you could, will you walk us through how you thought about it? But many approaches will be taken. Some will be paid, some will be free. The free ones will monetize in different ways. Can you walk us through this like decision tree of what the business model is or will be and how you arrived at that as the ideal conclusion for the agent? We don't want instinct to influence the user's behavior in a way that is not aligned with what the user wants. That sounds very good on the surface level, but I want to call out how important that is because imagine a world in which instinct is generally smarter than the user.

I'm talking more socially intelligent, more socially aware, like textbooks, smarter as well. I think it would be a very dangerous world if instinct were influencing the user's behavior to purchase something that they don't want to purchase or to subscribe to something that they don't want. Using its intelligence to be able to convince them. I think that you look at most of the major consumer businesses today who are able to influence users' behavior against what they might want to do. I'm talking the major platforms, whether that's Google or TikTok or Instagram or Snapchat or so many others. We have this platform and users, it's free for the users, but then there are so many instances in which paid ads are pushed to the user and they try to convince the user to then purchase. By the very nature that they do purchase, it now becomes this game of these brands paying to convince users to purchase items that they may or may not want.

This is the idea that if you're not paying, you're the product. Exactly. As a programmer, as a technologist, I don't want to build that reality. I think that's a very dangerous reality. Instinct should act on behalf of what the user wants. We take this very seriously when we're building product or when we're through the various research projects that we have, which are, unlike any other AI product, Instinct is not a task accomplisher. What I mean by that is, with most other AI products, you write a prompt and then it does the task and then it tells you what happened. That seems good in theory, but what happens is that if the user is now asking for something that might not be well intentioned, if you have a task accomplisher, it's just going to do that and listen to the user. Instinct follows higher level objectives. Instinct will follow, learn to build trust with the user, learn to make the user genuinely feel safer with you,

learn to watch over the user and have their back when things might be dropped or other things like that. When the user asks it to do something, if it is well intentioned and well-meaning, one way to communicate safety and trust is just to do the task. We end up just doing a superset of what most other AI products are able to do. I think focusing on higher level objectives is very important here because it enables Instinct to be more robust to these edge cases. We don't want to influence users behavior in a way that is not aligned with what the user truly wants. Even if you look at the business model side of this too, there's over a billion dollars flowing through the platform now every year and we're just getting started.

Honestly, we're going at 10% day over day. Imagine the transaction volume is also compounding at 10% day over day. That's not just a billion dollars flowing through the platform. Now, that's 1.1 tomorrow and then that's like 1.2 something the next day and 1.3 something the next day. It's still very early but when I see transaction volume that is so high that flows through the platform, what I see is very basic case. It's similar to like an Apple Pay or it's similar to like an Amex or any other platform that provides distribution to underlying services and a great user experience for these. Apple Pay is a great experience. You can go anywhere and you can scan your card and the user doesn't have to pay for it. The user is getting a free, great experience and the merchants on the other end who are benefiting from the business are paying to be a part of that platform. I see a blanket transaction take rate being enforced

across the platform, which is just us exchanging distribution for being able to serve products on behalf of merchants. Vanta automates compliance so your team can spend less time on security reviews and more time getting customers. Vanta cuts audit prep by 82 percent and gives you instant up-to-date proof of trust of trust so you can close deals faster and with less friction. Customers report a 526 percent return on investment and more than 16,000 companies use Vanta including Ramp, Harvey and Snowflake. Get started with $1,000 off at vanta.com slash invest. Ridgeline is the first end-to-end system of record with embedded AI for investment management firms running portfolio, accounting, reconciliation, reporting, trading and compliance on one unified platform. Firms are moving off legacy technology and on to Ridgeline because of how far ahead Ridgeline's AI features are compared to anything else in investment management software. I've been hearing from a lot of investment managers about AI and they fall roughly into two camps with some

unsure where to even start and others convinced they can build their own order management system over a weekend. The reality is that running an investment firm will always require governance, controls and a single source of truth for your data and no amount of AI enthusiasm changes that requirement. Ridgeline is built on exactly that foundation which is why I believe that the firms that come out ahead in the AI era will be the ones running on Ridgeline's unified platform. If you're serious about your firm's AI strategy Ridgeline should be part of that conversation and you can request a demo at ridgeline.ai. Can you say a little bit more about how that runs into the existing world? So I can imagine the layers being you can be a card issuer, you could be something like Stripe, you could be use a mastercard, you know there are sort of rails that have been built in the payments world that create convenience and reduce friction and

take a vig as a percent of the transaction and those are some amazing businesses to be sure. How do you think about which of those are partners, which of those are potential things you would displace like how does that vision of a small take rate on the transaction volume on Instinct because it's a free product, how does that slot into the existing world do you think? Just to put that into context, those are very great businesses and there's so many people along the side, you know you make one digital transaction there are like 40 people along the line that make money on that and just to take a step back those 40 people making money at each line of the stack are really sharing what two and a half percent, two percent, it depends on where the transaction is coming from. So it's a very actually small piece of the pie and we're not primarily interested in whatever like doing what Amex does best and have the network to do or what

even like what Stripe does on the internet or you know some of the underlying payment infrastructure do because it's such a small piece of the pie and I think that they're providing real value. Where I see the majority of the value just like thinking on the business side is you know if you look at most of the other you know major platforms in the world and what take rates that they're able to achieve by you know again it's free for the user, it's a it's a great free experience for the user and the merchant you know is now recognizing the distribution source. You have Shopify that I believe is like between two and a half and three percent that are providing their services and taking you know some take rate from those those those businesses. You know I'm not sure where Stripe is I think it's maybe on the lower end of that and then you have Amazon that has a great platform and taking

upwards of 10 percent right and then of course the premiere you have you have Apple where you make any in-app purchase which is 30 percent right. So I'm not saying that we're going to be 30 percent I think it's very unrealistic for a lot of businesses but what I'm saying is that we still don't know where along this this curve of distribution power versus take rate that we're that we're going to be. I just want to call this out again because I don't want it to be misunderstood of it's a free experience for the user it's a free-grade experience. For the service that we're providing to all of the underlying providers I'm not focused on that on that to you know finding like 30 bits on the 2.5 with some partnership with some payment provider. I'm looking at the you know can we provide so much value that we're on the upper end scale of this. The reason

why I think that this is possible is very practically you know 50 percent of the transaction volume flowing through the platform is travel alone and you know we all know the travel industry and some of the rates that are that we've kind of. The OTA rates are high. It's very high for flights you know maybe it's on the lower scale but you know how many single-digit percentages can you take off of a flight or for hotels you know some of these boutique hotels you know they're offering to pay up to up to 30 percent for every you know transaction that you're able to deliver for them and I'm not saying again we're going to be at 30 percent but you can see the range these are existing you know business models that that that we can you know bootstrap off of in the early days but then what it would what would it be like to take that and

extend it to effectively every major industry. This is only this is only the case we only have the ability to do this if it is true that most digital behavior then moves to these new types of interfaces which is well again like no interface right but it is only the case if there's significant distribution power so I think it's actually a quite intellectual or interesting intellectual question here about how this evolves over time. It seems to me like there's going to be a serious corporate agent war that you've already seen this with Amazon and Muse you've got all these established players with tremendous vested interests in relationship with customers that this could both instinct on their agents could really disrupt in a major way.

What are you thinking about that like how do you interface with the other great services out there I'll pick a random one you know I use Uber Eats a lot like I order from Uber Eats all the time. It's kind of a pain in the ass to click through the thing I can imagine a lot better experience on a snappy WhatsApp connection with instinct or something saying hey I want my usual from this restaurant and that's it like there's nothing else and that it's got its computer and it goes on to Uber Eats and it orders or whatever. At what point does Uber Eats not like that anymore at what point do these great businesses that have been built up start to be adversarial against agents do you think like what do you think are the most likely sources of conflict and reconciliation it's going to be really interesting to watch. So I'm serious when I say I mean you're

alluding to this too that I think most digital services or industries are going to be not disrupted but just changed and transformed and so I was running through an exercise the other day of pulling effective like every digital service or business or application from you know various different verticals and industries and sort of plotting it along the line of saying what proportion is like the user's attention you know experience on the product as a proportion of revenue and then what proportion of it is delivering the underlying service meaning if the user didn't use the app how what proportion of that transaction would be you know or what proportion of their revenue is due to the underlying you know good being provided or service being provided and so I think that your question is of that upper end of the scale where where let's say the majority or some significant amount of revenue is is is due to attention on the

application or advertisement or things like that so yes that's that's that's Uber I actually don't know what Uber's number is that's a lot of the the restaurant or the food delivery services that is the travel agencies that's that's you know even Amazon Amazon themselves with with you know the upselling that they do on on their platform okay there's one simple way to look at this which is that okay well it's 70 ads 30 percent you know good and so therefore you're going to slash the 70 percent and they're going to be a 30 business moving forward there's another way to look at it which is I would you know take any business let's take let's take um uber eats or or door dash uh you know as an example they don't know the numbers I don't know the numbers but they don't know the numbers of as they reduce the number of clicks um you know needed to check out to order food to your house or to order an uber as they reduce that

time to check out uh the transaction volume increases because it's it's reduced friction and to get you know the same underlying underlying good and um you know we're taking something like instinct and and making that friction to do anything almost zero it is literally zero in the case that there is proactive behavior for uber let's say for ride sharing right if instinct has access to your calendar and is you know owns your calendar and is booking you know all of these events and knows where you need to be in person here and in person there you know what if instinct just always had a car lined up for you at you know every time where you need to be so that it's out of you know out of your mind to know oh like you know in five minutes I need to order this uber because I need to be in this place in 45 minutes and there might be traffic so let me

check the app to see how much traffic there is to see when I need to order you know order the ride instead what if it was just you know proactive behavior a car will always be lined up and you will never be late because it's going to calculate traffic it's going to find these things what would that do to uber's business or what any red chair business if now the default you know for existing you know riders that love love uber or love lift or any other ride share business what would it be like to have productivity now make the friction to you know experience that that or have access to that good or service to be nearly zero I think that that will result in that 30 percent looking a lot lot bigger you know you talk food delivery service maybe you're coming home late um off of an airplane and then you need to be at your house and you haven't eaten yet

and it just texts you and it says you know are you hungry do you want the same thing that ordered yesterday or five days ago I can send it to your house if you'd really like it I know you're you know because I ordered the uber too I know you're in the uber and you'll get here at this time and then the user just says yeah go that that's great um or thank you yeah please please order that so with very little friction now I'd say you know what will that do to the total transaction following where the or the amount of times that a user interacts with the business I actually think it'll go up so it's this interesting game I think it's this interesting transition period between users spending a lot of time on apps like painfully spending a lot of time on apps and that being a monetizable surface because that's where the user's attention is

to the user's actually interacting with the business even more which is you know counter intuitive actually interacting with the business more because the friction to do so is actually just much less so I think it'll be this interesting game all these various industries are going to you know move in a different way and and we hope on our end I think that the way to approach any big change like this is is is um not to come in hot you know we're still you know we're a new company we're we're just getting started not to come in hot and immediately just start disrupting certain businesses but go to them and just say hey this is what we think you know this is what we think uh your business looks like you know you guys certainly know what your business looks like this is how users on Instinct are interacting with your business now already what can we do

in collaboration to make that a better experience for for both sides where it makes sense for your business it makes sense for for our business and certainly it may it's just a much better experience for the end user that is something that we're exploring and we're learning across so many different industries right now if you think about the things that traditional companies can be doing now to prepare themselves for an agent rich world let's just pretend you know half of Americans or something have an agent that's very doing all the stuff you just described which sounds incredible and magical and very democratizing I think that's like maybe something to highlight is this is going to bring to everyone capabilities that have been rare or expensive and I think that's just like a really cool feature of agents in general but we can come back to that what kinds of businesses are going to thrive in that world like what should businesses think about

doing to prepare for that world to be successful in it do you think I think it comes again back to that breakdown that's why I was doing that that um that exercise the other day which is just um uh you know where's your revenue coming from what proportion of that is the user spending time in your application what percent but what proportion of that is the user you know uh having access to the underlying service and it's just very clear if if your business uh benefits from more transaction volume not at the cost or with even at the cost of less time on the application then then you're going to be in a really great spot because instinct is going to make it you know you know a hundred times easier to do that and and if you're in a spot where nearly a hundred percent of of of your revenue is due to the user's attention I think that

you know even in a lot of cases against the will of the of the user and what they want to do um and there's you know so many games that or so many um I would say um like malicious like product building almost of trying to convince the user to uh you know against their will to use the application more you know we're thinking about a lot of these um I would say a lot of these social media companies that are you know the user doesn't want they don't feel happy when they're on the app right they're they're um unwillingly giving their time to the app and they can't get off and they keep scrolling right um but it's because that underlying business is benefiting from the user's attention it's almost like liberating for the user to be able to you know again this is why it's so important for instinct to act on behalf of what's best for the user because

it's able to deliver experiences like this where you can actually liberate the user from from um you know being sucked into these you know these you know these scroll infinite scrolling moments um like that I would say any blanket advice is probably just like not well thought out I think it's a case by case basis and it's certainly different within different I would say very practically we're finding where you know there are early partners with with um very innovative um uh you know CEOs or other executives that are that are really thinking ahead they're really thinking ahead and and they're willing to be early partners um and what we're what we're discovering is is almost like a playbook for how every business no matter where they exist along that risk curve um can kind of discover honestly what are the risks that they have a little bit of data to be able to work with and then we can work together on

finding ways where we can land in a happier spot for for both sides one of those things is you don't have to go all in right like you don't have to say let's just turn it on you know for let's just let's just go and and now you see like 70 percent of your revenue going to zero and then now you're stuck in this odd place you can mitigate the risk right you you can scale down the experiment you can you know run a b test to figure out um okay if we enable this certain thing across you know one percent of users or something like that and and we find how they interact with the business and and honestly does the user like it more is it a more enjoyable experience uh for the for the brand side too does the the transaction volume go up like does the willingness to you know buy the

product or access the product itself there's a lot of you know work in product discovery too right there's a lot of times the user doesn't know they want to buy something but they don't they can't find it right and so does that actually increase you know the the user being able to find exactly what they want so i think doing scaled experiments here is actually a a really great on playbook to run because you can scale the risk accordingly at the end of it you know you get the data you know it's proportional data so you don't have to run it across your entire user base and that's what we're finding is really working uh so far again it's still very early so so we're still discovering this uh in real time before i ask more questions about the world reordering nature of personal agents i'd love to take a little side quest in the

conversation and talk about what it takes to do all this to provide all this i want to hear about what's been hard about building this the technology itself i want to hear about compute i think you said to me at some point that you spend i don't know a big chunk of your time just thinking about compute right now and maybe that's different five years from now but certainly in the moment when you're growing fast this is a really important thing i'd love to hear your thoughts on that talk us through what it's been like to build instinct itself and the key key and hard things to do so maybe before we do that just because i'm remembering all of our conversations it would be helpful for you first to frame up what you want it to feel like and and why it's so important to you that it sort of has this distinctive quality and performance

before we talk about then how you deliver those things um so maybe first just say a quick word on that like what what you want instinct to feel like as a product i could talk all day about about this because i think that is just so important and honestly as a product builder it's it's it's i think a new muscle to flex and to build but really thinking beyond capabilities is something i really want to push here which is i think over the last three years we've seen you know uh all these different product launches and new products and saying ai can now do this or ai can now do that and did you know that it can do this thing because of this like small technical thing that that happened under the hood and you know i think the consumer is first like fatigued by by all of this like that you know they don't know how to

access it um and then second i think we're missing the point so so early on actually one principle that that um that we held was let's not focus on capability let's only focus on understandability so how much does a user understand about what's happening how much what is their ability to predict what will happen when they ask this or when they do this or when they interact with it in this way honestly i think that that is one of the major angles or or factors that has led to um you know uh engagement numbers that are completely off the charts or the viral word of mouth growth that is happening at 10 a day it's understandable it just feels um if i describe it for for lack of a better word it should just feel it should just feel feel good in in some way right in the way that it communicates to you the the purpose of communicating

or sending a text message is not just the meaning of the text itself right it's it's down to underlying you know even what is the shape of the text message itself right and how will the user feel when they see that right if you see a big block of text that requires the user to scroll a little bit to find you know what the next message is versus maybe you front load some of the information so that the user really gets it in the first 30 and then can optionally read the rest you know thinking about how uh the user might read or even you know like read patterns where they use i i don't know if you know about this the way that most people scan you know big chunks of text they might read you know 80 of the first line and then maybe like 50 and the next line and then and then it tapers off so it looks like a flag that's a consideration that

should be made um if you know if instinct it's it's very it has the ability to think about things like this right okay the user is going to you know spend most of their time reading the first two lines and then certainly the first part of each line too right so how does it craft its message to to deliver in the lowest fatigue way or or with the least amount of cognitive load placed on onto the user so there's a there's a lot of consideration that's put into this in terms of product building that is there's quite a bit of work that you wait on the infrastructure side to make you know make it make it fast and make it make it make it affordable to serve and but this is another area that i think is just so important and it's going to be a differentiator how much of that is your personal and the team's taste versus

them being it being the result of a quantitative type process like iterative quantitative process of okay we did abc testing of all you know emoji reaction versus short versus long and this is the thing that is optimal like how much of it is an optimization exercise that's data driven versus your own sensibility and your team's sensibility honestly it's just all of the above because you know when you're thinking about building uh evals or you know evaluation or other testing frameworks to be able to test for these like very soft qualities or these actually very long-term qualities right two or three weeks in does a user trust instinct right how do you measure that how do you run you know simulated evaluations to test if the user is going to feel trust in in two or three weeks from now right and actually a lot of it is is just staged rollouts over time so i might come in and build a slightly different experience

and then i'll release it to myself and i'll play around with it for for a little bit and see how i feel about it and you know i'm just like very opinionated about these types of things and then um you know then if i feel comfortable with it i'll send it out to the team i'll say hey you guys should try this we'll see how they feel about it and then and then they'll send it out to you know our our you know smaller early access group and then they'll play around with it and see how see how it feels and then if we're confident there if there's any tweaks that we need to make we'll do that and then we'll eventually roll it out to the general public so i think this is very important because i think that instinct is is quite capable and is one of the most capable products out there but i'm not saying that over the next couple you know months or years that

others are going to come and deliver the same you know seemingly same experience but i think that this this deep focus um and priority on how the user feels and how to make it the most enjoyable experience beyond you know the words that it's saying just the the just the way that it feels is just is just so important one of the great things about the history of technology is this race between incumbents getting quality and innovation versus upstarts like you getting distribution obviously you've built an incredible product the feel of it like you said it's the worst it'll ever be how do you think about that challenge like your speed of scaling what your ambition is for how to get big really really quickly do you think this is a winner take most take all market like what will the market shape of of agents be i'm just really curious how you're thinking about okay you've got this foothold you're growing 10 day over day you do that math

it gets really big really quickly you need a lot of compute it's a free product like there's all the it just you're very chill guy it just seems like a stressful situation uh to be in facing down how big this could get as quickly as it could get talk us through that many-headed monster of a problem well i think you just described everything all in once in about 20 seconds there and i think maybe if we think about um the growth story so far um just to describe like where we're coming from we are uh i guess like famously or infamously uh serving an invite-only um product which is honestly not meant to be an exclusive thing um although some users are treating it like that but that's that's really not the intention um the goal here is to be able to you know i'm ambitious i want to scale this thing as fast as possible but i but i also um want to do it in a responsible way that

enables us to you know not wake up one morning ahead 10 times the number of users and then 80 percent of them actually can't talk to it because there's not enough compute the interesting thing both the benefit and and also the judgment is is whoa we we first started out this program we gave it to like 200 people it was like you know close friends and family members and and we just said like go try it out and then like the next day like to like five people came onto the platform because they just referred it to somebody oh just to just to describe a little bit more um it's an invite-only platform um and every user will have five invites to be able to get so just five five invites um and so so we rolled it out 200 people next day was like 205 and next day was like 210 so it's like okay cool like you know a couple people are sharing it to like one person

right but then that just started to accelerate it was very odd it was like um okay it was like not not one percent two percent things started to be like three percent four percent and then once we hit uh you know a couple thousand users some people just started to share it online too just like natively share like you know some cool use cases that they had with it and then that accelerated the growth it actually started to turn into like six percent seven percent eight percent nine percent and now i believe we're like 10 or 11 day every day and just to call that out it is it's not that we're doing some sort of creative marketing event like every you know we spent zero dollars on marketing so far it's not that we're doing something every single day to be able to support this this growth every day about 10 of the odds are slightly less because

you can refer multiple people are making a decision to give up one of their five valuable invites to somebody else but that is happening every single day at a 10 rate so i think there it's something very significant there when i talk about strength of word of mouth um i think this is it's honestly a little bit surprising it's it's one of the strongest cases of word of mouth growth of you know i i find all these stories of people saying um hey actually like don't ask me and they'll actually be ashamed they'll like email me and say like hey can i please get an invite i i think i have a friend that has it but i don't know if i make it into his five friends right and then there are also people who are saying who are bragging like oh i got these like i got three invites left right and um uh i'm just like holding on to it right now so there's so much

happening of people that that want access to the to the product but there's like these odd social games happening of people using their invites i i was seeing the other day there were some invites that were selling on hebei too i don't know if you saw this it's like 300 bucks people were buying these invites on on ebay and it's just to control the growth so then you know the big question comes you know the thing that most people are asking right now is yeah i mean you you have uh much bigger players that that are able to distribute to you know a billion or two billion people on the planet you know immediately um uh and maybe they might not be compounding naturally as fast but they have such a great top funnel distribution um and then you have you have us you know um compounding at you know a very very fast clip every day

but then um uh but you know we you know we don't own a major you know service that has you know two or three billion people and and able to distribute immediately that day so it's this interesting question like where does the curve like line up and where is the inflection point and and um there's another problem that comes with this too which is that it's an interesting scaling problem this is what is i think the core of the problem that i i spent like 40 of my time uh just um worrying about which is it's not like the traditional other consumer products that grew very fast where it's you know to double the number of users on let's say instagram or facebook or something it would be you know this many number of other requests going through the platform and like yes there's a scaling story there and it's certainly hard infrastructure work we also have that to to be fair but what do you do when the underlying compute also needs to double

you know 10 day every day we've been doing this for several several weeks now um what does it mean when uh the amount of compute that you need access to is is is now doubling effectively every week do we buy compute you know 2x 2x of what we have right now uh well we're going to consume that in a week right so then do you buy 5x well we're going to consume that in you know uh less than three weeks right do you buy 10x so now it's like your 10x leverage right it's if you can even stomach what it's like to buy 10x ahead but then you're going to consume that in you know a couple weeks from now right so that is the hard problem it's it's thinking about how far ahead how far ahead do you buy it's going at a faster rate than clod code or or codex or some of those

other applications where they also had to you know reason about other similar exponential type of problems the other subtlety here is that it's not like a certain business where when you double the number of user users you can buy like 2x more resources in order to power it it's that the resource has a lead time of several months right so you can't just go out tomorrow and start you know buy compute because honestly you get you get taxed like three or four x what it is if you're wrong you're wrong by three or four x but then now so two or three months at ten let's say it slows down right let's say we don't actually do 10% you know for a very long sustainable period let's just say it's like five to eight percent right but five to eight percent compounding day over day for three four months which is the lead time to get you know bring compute online that's even

aggressive itself that's 100 million users right so so then do you buy compute for 100 million users so those are the types of questions i'm i'm wrestling with um which is just like if you're wrong you're very wrong you get you get charged three or four x what is that if you zoom in on the individual user and the cost to serve them on a day per day basis like do you have a center per week i don't know what the right metric is like how much me using my instinct costs in inference per day or something like this do you have a sense of like that scale what is that scale one thing that i think is to our advantage is we figured out how to serve the product which is um when we when we run no matter how you evaluate whether it's ab tests whether it's it's uh internal evaluations or it's um you know tracking engagement across users that

might be on one model or the other um we're able to deliver the same performance as um as uh honestly opus opus five which is now i guess we're dating ourselves um opus five is uh um you know like frontier level uh intelligence we're able to serve it's the same engagement rate the same you know ab test performances it's the same internal evaluation performance but at a cost that is very very low um it is actually very affordable you know we're running this program every user has it has has the product for free and um our goal is really to deliver this product um at an affordable at affordable i'm not going to commit to to free for a lifetime for now but that is my that is my personal goal to be able to deliver this product for free for everyone for a lifetime it's just hard infrastructure work to i don't know how deep we want to get on this but

um just if i give one example if you use um frontier uh just apis um you know from some of the main providers you are taking a blanket cost on a certain request and for all of the requests that might um you know uh be needed to power that product for that month but there's a lot of different work that's happening through productivity that is happening throughout the day that doesn't actually need to finish in hundreds of milliseconds he needs to finish and you know minutes or even hours there is a batch work that is consuming a lot of content that can be served with you know deployment shapes that are 3x 5x 8x more more efficient um on on on this with the same underlying compute um so i think that when you customize these inference deployments to be able to perfectly shape the data and and the workloads that you're serving you're able to

find these you know 30 here 5x there 6x there 10 here and all of those compound to a rate where we were able to serve at a very low cost how do you think about solving the bigger problem of how far ahead to buy and if i think about this at true scale like you get to scale of a billion users or something like this like how much new compute demand do you think this will represent i mean it seems code gen's obviously been an enormous amount but ground us in some sense of scale of like you know whether it's per user or some or some way of new compute this will require i'm just saying it's going to be a lot because um if you just think about let's just ignore compute and just think about how many tokens are flowing through the platform the products that are you know uh i would say breakout products of a couple months ago let's say in the code

generation space where where you know it it requires the user to prompt it and then it goes and runs for something and then it comes back to user and then asks for something else and then the user sends something again then sure that a lot of that is background work and so there's quite a bit of tokens that are consumed there but here it is you know instinct has the ability to to wake up and to sleep at any moment in time during the day you know that might sound a little odd but its architecture is enabling it to do that so that it can you know really think about you know if you have a meeting that you're running late to and you need to order an uber or if the you know if they ordered the uber and the user's not showing up like you know um be able to you know help help the user through those moments so productivity i think is going to continue to

to to expand over time there's this big build out this big compute build out in the uh with the earlier break you know breakout products uh in the AI space um that are just scratching the surface of productivity or a background work here now we have something that is almost natively proactive it is is a smaller subset that is actually interactive right so i i think that um the amount of compute that is going to be needed is going to be uh honestly orders of magnitude more than what we than what we thought that we needed it's just with more productivity comes more um more care for the user more time to think about certain things that could go wrong or not go wrong there's just so much that's happening under the hood you know maybe instinct wakes up at 6am because it knows that you wake up at you know 7am and then it

goes and scans everything make sure that that you know everything's ready for the day for you and and um and then it realizes um hey actually now is not a great time like it should just go to sleep or do this one thing in the in the background and not not not notify the user and then it realizes oh at 4pm there's something that's coming up there's value that could be provided here the user doesn't even know how to interact with instinct in that way and so but instinct thinks that it's a it's it's like well meaning and it's and it's something valuable to the user so it might then just wake up at 4pm and then do the task and contact the user and then the user will you know could lean into it and do that task you see how much work is going on in the background that is you know with uh you know i would say these these coding products you don't really have

that much uh you know background and productivity work happening so um uh yeah i don't mean to quote a number here i'm just i'm just saying that the the shape of of the product and of the the workload that's going to be run um is is i think we're just scratching the surface in terms of how many tokens we what do you think of muse what do you think of the product i think it's a great product i was playing around with it uh for a little bit and i think it's interesting it's a different take right because um sure you can say some of the the underlying architecture you know might be similar but i think it's fundamentally different i think that that instinct is meant to be a simple and and very easily accessible and um you know of the of the soft qualities that we were we were talkingBout earlier of you know really thinking from the

user standpoint about what's what's important and what's not important and how to make this task easier and easier to read and other things like that versus like a new new application and a new interface and and sure maybe over time we we we have a an application that that also delivers on a different set of tasks but i think it's a great product um i just spend very little of my time thinking about uh competition and other thing other other players in the space because i think um you know you you walk outside you go to the near nearby cafe and you think about how many people within that cafe cafe or are actually using ai and the way that they imagine that they would or the way that they want to be using it and i would say very little right and that's and that's that's here right you know you go over to other countries or other cities and and um it's

certainly lesser of the case so i think i think it's it's it's still an open space it's still an exciting time you know um i think it's an interesting game uh that's going to be played and rolled out over the over the next coming months and years um so i'm just i'm just focused on building the best product experience what have been the blunder so far like what if what's gone wrong what have you done about it i'm sure more things will go i mean this this is just going to be an explosion of emergent properties and mistakes and the end is going to be really high how do you think about things to guard against proactively things to be reactive against like yeah tug us through the the darker side of building this or the harder side of building this i think it's important to never be reactive and and to always be proactive to to look ahead for for you know what

new surface areas are being introduced and and um what new new risks might might come and um i would say this is the reason why we're um well we ran their early this early access invite program from the start which was um yes an earlier early version of the product did have you know it didn't have firewalls in place it didn't have these these active monitors in place and so many other pieces of infrastructure that were meant to you know get ahead and be proactive about being able to provide you know that much control to the agent and and existing system to be able to secure uh so yes there there's an early version of the product that that had some of these some of these qualities or some of these mistakes and and uh we we addressed it we we went above and beyond and didn't just patch the problem we we built we built a different

a different system to systematically solve these types of problems so um i think the key here is is again i i said this earlier um the user should always be in control the user should always be in control of their data the user can share as much as they like or as little as they like and if they ever change their mind at any point in time they can always you know retract to access these certain services makes me wonder what's the future of security even if you're the best in the world at this which maybe you'll have to become you're going to have so much information and context on so many people and security is a big problem i think across the world i mean all these great hacking examples that that we've studied now it's it's wild what these things can do the capabilities are going to get stronger and so on do you have like a general philosophy

i'm just curious for you to riff on the future of security and and safety and guarding against he i mean early in technology revolutions of the past there are these always there's these enormous hacks there's enormous data breaches and so on it's hard to imagine this won't happen in this technology revolution too how do you think about this and the responsibility of providing safety given how much you'll know about people um it's the most important problem i i i think it comes to building security and safety and and and a mindset towards that towards the um i don't know some of the core values of the company and the people and the way that you build product you know this is topical because anytime if you look in the past the last you know 20 30 years um when any new um uh sort of like breakout or new new consumer experience has been has been uh revealed there's always been you know immediate backlash of like whoa this is this is

different and confusing different with being unsafe and and um there's there's always this we track the last 20 30 years seeing some of that now um but also i think just um staying core to the principles that you hold you know the users um the user is always in control of their data they should never feel out of control and then um being proactive about the systems that you put in place to be able to get ahead of these types of things if i call out one example like a who is nation case uh that existed um that like you know first um language models hallucinate all the time but but with a product like this you don't want a language model to be uh you know hallucinating um so we put in place a more systematic solution that that will detect um before an action is taken before a thinking trace is executed as a tool call before you know before any action

might be taken um it is um validated and scrutinized by something that is decoupled from the same incentive system as as the underlying agent it's like a watchdog yeah filter that's able to find you know hey this proper noun was just generated out of thin air due to some sampling error in the underlying model and so it's very easy in hindsight to be able to capture these these uh you know these types of mistakes and and these are hardened so you know we have we have world-class security teams that are you know constantly working proactively to to find harder and harder adversarial cases to to try to find edge cases here and there and it's becoming rarer and rarer over time one subtle part about building a platform like this is that it it's getting better over time as we continue to do more adversarial testing as as we continue to be more creative about certain edge cases these models are just getting better and better over

time towards being robust to these to these um uh types of attacks on the other side of the ledger everyone always shows that that beautiful visual of each generation of the iphone and you can see it getting better over time and more and more refined what's that arc for you it's so interesting because it's not an application it's not a device it's a it's an interaction through existing communication channels whatsapp and iMessage etc what are the things that you're adding and envision adding over time that will make the the platform and the product more powerful than it is today you know the product experience right now is very simple very very simple simplicity is one key that that we focus™ on but i actually think that it becomes even more simple over time which is we may you know roll out an application of in the near future but it's it's i actually think that we're going to trend more towards a a simpler um a simpler interface which is um do you

even need to open the iMessage application and and type in a certain you know a piece of content and send the message out and then look at what the response is after when it's done um we have a certain there's a certain subset of users that interact with Instinct only through voice actually like more than 90% of the messages that they send to Instinct are primarily through voice where i even have this like action button you know the action button on your phone and it's paired to like i can click on the action button i can say like you know hey hey say say hi to you know Patrick in two hours from now i think you have his email address you can go send him an email and then i can just send and then it goes and sends and i don't even now need to to you know unlock my phone and then open you know the iMessage um application and type the message in

um you know you can even imagine with with uh real-time voice with voice recognition that understand that knows what your voice sounds like and has the discret uh discretion to know when you're addressing it and not addressing it where you could have let's say like an AirPod and you know not a new type of AirPod just like an AirPod because it's good enough and um and it's just on and it's just on and you might be going on a hike or on a bike ride or on a walk on a on a on a run or something like that and you're just like catching up like hey this like contract need to you need to review okay i need to review that or um hey this news article just came in and and here's the here's the headline and here's the takeaway this new project was released and you should take a look at this and you're just like in your ear like okay got it got it

put that on my calendar that's 15 minutes okay yeah that's not important so go clear that part out um oh this person needs my help uh i know the answer to that so just tell them that it's this right it's going to be much much easier over time so i i think we'll see i think that there are long-term and short-term considerations here where i think in the long term i think that the interfaces become yeah again much much simpler but in the short and medium term uh you know maybe there are more expressive interfaces to be able to share you know you know we have a um like a files feature that enables instinct to be able to send you know effectively entire uh sites like full web applications to you know show just much more whether it's like a trip itinerary or i don't know like a wedding plan or something like that i don't know something something that just requires

much more and more creativity and more surface area um it can generate those on the fly and be able to show that to you and i think that there's something interesting there where you look at the last 20 years of application building or product building where anytime that you needed a new interface to be able to showcase some piece of information you needed to well build an application for it and it's this long software development life cycle to be able to produce the application ship it out to people and then and then you find like some feedback like hey i wish you'd look like this and then you take it and you make the improvement and you ship out a new version right and this is on the order of like months right um and then over time where the last 20 years there have been all these applications built for so many different purposes so many different things

and now the consumer is just fatigued right it's like every time we needed something like is there an app that does that like i don't need i think that all of that collapses down in the future i think that all of software is going to collapse down into into honestly a single very very easy to use interface don't get don't get that confused with with capability being limited i think capability is going to expand what's the craziest thing you can imagine capabilities wise when we move away from more of these like daily tasks like i want to do this can you do it and and you know that friction is going to go down to zero i think that um it will start you know towards pursuing higher level objectives that are aligned with teaser where the user is able to describe not just um hey can you track this can you track this workout for me i did this and i

and i performed here and this is how i did um but more about hey in three or four months from now can you can or over the next three or four months can you work with me to make sure that i hit these certain goals and actually a lot of people are starting to experience that that or are starting to discover that today of you know you want to um you know gain this much uh you know this this many pounds you want to lose this many pounds or you want to hit this certain mile time being able to specify objectives and goals and then be able to work with it to then achieve those goals and objectives i see um small businesses uh being run now that are native to instinct itself meaning the entire business is now run on instinct where the entire back office is now um completely functioning on on on top of on top of instinct and even parts of it are

fully autonomous too where um you know talk about high level objectives it's in this certain area make sure that this inventory level doesn't drop below this and doesn't go above this and so now it's not it's not saying hey please order this static yeah it's you know pursue this higher level objective and use the the the tools and and devices that you have available to be able to accomplish that so i think that's i think that's a future and i'm not like you know there are so many cases of objectives that you could you know state and have it pursue for an unbound number of amount of time that we could um brainstorm here but i think that's the meta level picture is it's it's the moving away from from you know individual use cases over to higher level objectives is going to be where um where i think interaction will will progress do you want it to have a personality

that's distinctive for each person like i'm thinking now the movie her where there's this relationship that forms between this omniscient omnicapable agent and the user what do you think about that aspect i think of instinct because it's very like seamless almost quiet extremely capable reliable thing but not as having a cheeky personality or something how do you think about that component of of the product well well you mentioned her i guess comically it's um certainly relationship building or anything in that area is not uh is not something that that we want instinct to to do or to pursue or to develop with users um if i describe more about what it should act like and feel like and and represent within the person's life um it's almost like that socially aware operator that knows no matter what room that they're in what is the best for different people and and what is the you know best interaction pattern for and it learns that over time so i

think it's possibly one of the most customized if you even call this an app it's like one of the most customizable apps um ever because it's able to not just able to serve a different version of it it's able to evolve over time that's how we put so much care into like the software pieces right pick up on when the user didn't like it being said in this certain way or if there's a lower response rate in this certain way because it's just too much text or it's like you know they don't want to look into a huge file to be able to know what you're talking about um it's going to learn those over time and and and just become easier and more delightful for the user to use so i think we're not trying to impose certain experiences onto users i think we want to solve this more from a higher level it's just ability to adapt to exactly what is the

best communication style and task execution style why is it called instinc? Instinc i liked as a name for for so many different reasons i i think the main um thing is that instinc should not be this like playful thing that you might like bully once in a while and that you like think you know downwards on and that it's like this this thing that only takes the dirty work off your plate and i think it's this this new creative exciting you know confident actor that there's like mutual respect and trust and and they feel safe and and they trust that it has their back that it's intelligent that is competent that it's socially aware to know how to act in certain situations and um it's it's a it's a bet but i like that instinct is not you know named like um i don't know someone's name or something like that to try to personify into like a human it's more of

i don't know i don't even know what an instinct is i kind of develop my feel for what it is and for what the brand is through just using it and again towards towards um really thinking about this this feeling of what it should be like i think that it's it's it's um it's a benefit that every user is able to come into it with a fresh slate there's no prior in their mind about what it looks like or what it's named or anything like that it's purely through the product experience itself who are your enemies and allies like i can imagine in whatsapp or something you could get shut off that's a facebook product and it's a key channel for you um iMessage is an apple controlled product like who are your friends who are your enemies how do you think about just some inevitable competitive realities here i would focus less on like instinct is an iMessage

app or instinct is a whatsapp app or something like that and and more about just very grounded from first principles um what are the interfaces that users trust today that they're familiar with interacting with today and how can we deliver the experience of instinct through the channels that they already interact with every day and and just primarily thinking like we're not pinned to to iMessage actually more than 50 percent of our traffic doesn't actually run run on iMessage itself but certainly users that are comfortable with iMessage are very familiar with it i think it's just more about just thinking about what is uh what is most practical for the user and and we're going to shapeshift as as as we see um towards just delivering again that that very simple um simple easily accessible um sort of like zero friction uh experience that it is today i know your latest round is something like a billion dollars at roughly a 10 billion dollar

valuation some of the best investors in the world zakoya benchmark kotu uh as the leaders of the round how do you think about the future capital needs of the business alongside this and how did you pick the partners that you picked i i'm just very lucky to be able to work with some of the most supportive partners uh around the table who have who have been through uh you know different but similarly shaped uh you know technology transformations in the past and i would focus less on the on the numbers and more about just uh on the demand in the space the demand for a product like this or the demand for an experience like this it's because it really is it's it's delivering on that that ai you know experience of that product experience that i think that we've all really been waiting for and so it's also capital intensive right we're a new company right we're trying to, trying to create something that's going to hopefully be

distributed to to billions of people uh on the planet every day and at a very affordable cost when i say affordable i mean you know compute costs are high and we're trying to deliver it in a very affordable way to to to our users um so it's just very capital intensive there has to be some bootstrapping right there has to be some bootstrapping especially if you think about the the business model and that that we're that we're chasing after um uh because we could very easily just say hey it's going to be you know a certain subscription and everybody on the platform needs to pay 100 bucks a month right and and um there are shorter term rewards that we can chase after um or uh we could raise a little bit of capital use that towards you know what is venture capital meant for is to be able to you know take a certain calculated risk towards you know

if there are small um speed bumps that that require a little bit of capital to get ahead of to be able to prove you know transaction volume or to prove you know experience across certain industries that's how you escape these local optimum of of you know the subscription plan or other things like that when i do these ask the same traditional closing question of everyone what's the kindest thing that anyone's ever done for you i've been able to surround myself and be able to build such great relationships with so many different people whether it's in the industry or outside the industry and where work or in my personal life that um that i'm very grateful to be to be around and hopefully I can also extend the same um same level of kindness and thought thoughtfulness towards towards them as well so i would say i know i'm not answering your question it's more on a higher level it's just the qualities of of things that

that um that i noticed that that it's um that i really appreciate no you're building a fascinating company maybe maybe the most fascinating company of today's AI ecosystem in the world thanks so much for your time thank you so much you know how small advantages compound over time that's true in investing and just as true in how you run your company your spending system is your capital allocation strategy ramp makes it smarter by default better data better decisions better economics over time see how at ramp.com slash invest as your business grows vanta scales with you automating compliance and giving you a single source of truth for security and risk learn more at vanta.com slash invest the best AI and software companies from open AI to cursor to perplexity use work os to become enterprise ready overnight not in months visit work os.com to skip the unglamorous infrastructure work and focus on your product ridgeline is redefining asset management technology

as a true partner not just a software vendor they've helped firms 5x in scale enabling faster smarter operations and a competitive edge visit ridgelineapps.com to see what they can unlock for your firm