Inside the Personal AI Assistant Growing 10% a Day | Instinct Founder

Key Takeaway

Start treating AI as a delegated operator, not a chatbot: choose one recurring task with clear preferences and low downside—such as reviewing subscriptions, preparing a trip, or coordinating a meeting—and write down the objective, constraints, and approval limits. Give the agent only the access needed, review its first few actions, then expand permissions as it earns trust. The lesson is not to automate everything at once; it is to compound confidence through small, reversible delegations.

Episode Overview

Patrick O'Shaughnessy interviews Noah, founder of Instinct, about building a proactive personal AI assistant that works through familiar channels such as text, phone, email, and voice. They explore how agentic AI may reduce digital friction across scheduling, travel, commerce, and personal goals—while making trust, user control, security, and alignment central product challenges.

Full Transcript

Transcript of Inside the Personal AI Assistant Growing 10% a Day | Instinct Founder from Invest Like The Best. Auto-generated from episode audio; may contain minor errors.

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The window to do it is actually on the order of months. The compute required to it is over $$, just this year alone. And you have no distribution advantage, but you have this massively growing viral product. This is probably the most exciting software race ever. And the outcome is like trillions of dollars. Noah, 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. 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. It's a new company that I've 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 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, you know, I have this new vision for the world where this is going to, you know, trust me on this.

And in a few years 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 to brainstorm, when we started to use ChatGPT for the first time, you know, that agent that is able to help you with effectively anything in your everyday life, whether it's something new and creative 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 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 several months that I've been using it. It's funny if there's something genuinely pressing and has it, you know, a deadline, it will call you and it'll call and it'll say, I don't want to bother you too much, 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 asked 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 their wardrobe and scan every single item, you know, every every top and bottom and sock and, you know, whatever shoes and and then they would scan themselves to like 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 you know, 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 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 up 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 they'll be able to point to like that one.

I really want to send that to my house. And then not only that, but they'll say every day, can you 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 serve to do that or users connect like their bank accounts to to instinct and and then I 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, actively use this?

And then they're like, oh, no, I didn't even know that. And then they can go in the email and unsubscribe from it. Yes. Yes. It can go. And then, you know, there's 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 end to end. So they go into the site, sign in if it's there's some sort of like confirmation that goes to their email or that has access to the 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 saving two thousand dollars this month because of these things. 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 a week or so, 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, OK, you want to meet at this time and then they say, no, that doesn't work like that.

These times work. And you say, oh, but I'm traveling. So maybe this time works and I'll be in this time zone, though. There's just so much back and forth there. However, if it was possible for, you know, the two users who were using and 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 that 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 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, you know, find out what your your calendar is 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 anything with them, right? Maybe with with 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, you know, keep that off limits and it'll be able to create 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.

Right. It's not like a friend graph where you're just saying, I'm connected to you and that's it. Right. It's it's I'm connected. I'm connected to you. I trust you. And 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's some interesting cases I've learned about where if somebody violates your whatever, your trust within the network, there's an implication on the on that relationship itself.

Right. So so let's say if you and I connected. Right. And I said, hey, Patrick, you know, I trust you. platform so that it's easier for the next, you know, maybe the next time to put time on my 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 then 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, there's no one nearby, like where is he? 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 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 area of the platform, the user generally has a good feeling of what it should act like. Here is just something new and creative. For example, I heard the other day of, you know, when you're scheduling plans with friends or with like a spouse or something like that, it's always an active act, right?

It's like, OK, every Thursday, maybe I'll like think about something on like the Saturday night about what I should do. And so it's always this active act and then you like text the group chat like, hey, do you want to do this? And then it's always somebody is like not not willing to do it. And then eventually it falls apart. Right. And that happens like every time. And then finally, when you get people together, that's when you have that, that, you know, you're able to actually, you know, attend that event or whatever it might be.

There's like a friend group that put in every week just brainstorm something creative that 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 is available and what their interests are and if they like certain things or not like certain things or what shows are available or what concerts, you know, based on their music taste because all of their Spotify history connected and all, you know, that same friend group that they had.

And 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.

It's almost crazy how simple the explanation of this is that it's easiest to literally just pretend you have a superhuman personality. person with a phone, a computer, an 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, you know, complete, um, you know, abstract visionaries and saying that we're going to reinvent the internet, although I'll be clear.

I, I do think that in the coming years, I think the internet's going to be, going to be rewritten. I think that the way that, that, that most people on the planet interact with, with software is going to be very, very different. To break it down though, I think in the, in the short and medium term, famously, maybe reservations is one where, um, you know, like booking a reservation, right? So historically, how has that done? Well, the human, you know, has to go onto the site and, and to, to go to whatever restaurant that they care about and then click through the site and then put their, you know, 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, that one restaurant that you really care about. That's your favorite restaurant. You can't get in. Sure. That's, 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, how the agent is able to, to exploit just something simple, like, 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, um, we are sort of reinventing what the reservation system is just in this one category, because it's important to, to our users, um, which, um, is actually better for both sides, right? So if you take restaurant reservations from, 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, you know, a friend coming in from out of town and on the restaurant's end, they just want, they want interesting people, they want special occasions, you know, they want to cater to those rather than the, you know, maybe the local who keeps, you know, keeps taking up the table once a night and, and, um, and there's no sort of special event there.

And traditionally, because of the way that the internet has worked, at least for reservations, uh, it's been first come first serve. So anyone that comes in, no matter how important or how non-important it might be, you know, 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, the person's, you know, the person's spouse's birthday, the 30th birthday, a very special event is coming up and the restaurant too can, can say, let's actually prioritize birthdays or, or, you know, 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, 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 reservation, on the restaurant's end for them to be able to have a much better, uh, you know, audience of people who, you know, it's all these different special events or special occasions.

So I don't mean to go so deep on, on restaurant record reservations. I just mean, that's just one example of a traditional model that is changing. I think the same case with, with, um, a lot of the major travel agencies, honestly, 50% of our, of, of transaction volume that goes through our platform is, um, due due to travel, honestly, we're still running like an invite only program and it's, 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, there's, there's already over a billion dollars a year transacting.

50% of that is travel alone, travel agencies that, that we might all use today or, um, we meaning the people who, who are not on instinct, um, yet use today to book, you know, hotels or flights or other things like that. Well, what is the benefit of, of that interface, right? It's, it's. Well, they unify, they properly unify from so many different services and so many different hotel chains and, and, and airlines and just present it in a, 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 through instinct or other similar interfaces where you can just say, Hey, I need to be, you know, I I'm using a voice recording again, because I'm trying to describe how easy it is. Um, Hey, I need to be in, in New York tonight. This is immediate. And that's it, right? Well, what does that entail? That, that means that, you know, first, where is the user right now? Right. Um, maybe you're in San Francisco, maybe you're in LA or you're somewhere instinct can, you know, if you'd want it, 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. Um, but not only that, all of the nuance too, what's the person's airline preferred airline that they'd like to fly at? Uh, what's the preferred seat type, right? In what class do you want to sit in? Do you want to be in an aisle seat or, you know, window seat or the middle seat, you know, et cetera, what 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 your preferences are stored. That is the nice thing. If you tell it one thing, um, you know, I prefer this, this is my style. This is what I like. Um, 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 set, 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 anyways, 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 their calendar.

So it'll put the flight, you know, the flight and 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 talk 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, 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, 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.

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, the networks that they have. It'll be a collaboration over the next year, a couple of years to be able to redefine what that industry acts. Vanta automates compliance. So your team can spend less time on security reviews and more time getting customers. Vanta cuts audit prep by 82% and gives you instant up-to-date proof of trust without all the manual work. So you can close deals faster and with less friction.

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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. 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, the more contacts, 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. Right. 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 always feel in control of their data.

They should always be in control of their data. They should share data with with instinct at the rate at which they feel comfortable with. Right. 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 percent chance that the user has shared a personal credit card with instinct. That's 40 percent of the user base. That's including, you know, some proportion of that user base probably turned in that moment to write or at least trend before that point.

So 40 percent 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 for trust. And we actually highly value this and we take it very seriously. So 40 percent of the user base three weeks and are sharing a credit card. Well, there's something there. Right. There's something there. No pun intended. It's like it's the it's like instinctual to go to it and, you know, 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 when users connect at least one piece of sensitive information to instinct and really trust instinct, there's like an 80 percent retention rate. 80 percent. If you share one piece of crazy for consumer technology. Yeah. How should people out there that want to try this but have a natural reticence to trust, not not instinct in particular, but just anything, any A.I.

agent with all of its information, like how 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 like a way to break this problem down into into like 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, you know, they have access to sensitive information and what are they doing proactively to to make sure that that is, you know, isolated and and locked down.

And then there's a second area, which is the new problems that we need to solve, right? 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 to making sure, you know, a sense of data shared is, you know, 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 three weeks, 40 percent 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 on email and what portion of users connect an email, but, you know, you can imagine full access to to an email inbox and to a calendar. So there's a lot of surface area here. There are systems that we've put in place that are detached from the from instinct, the agent architecture, 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, 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 that is put in place to enable the agent to be as capable as possible, but also safe and trustworthy.

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 interest 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?

You could walk us through how you've 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 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, right? 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, right? And using its intelligence to be able to convince that. So 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 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. And 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, exactly. As a programmer, as a technologist, I don't want to build that reality.

I think that's a very dangerous reality. And so instinct should act on behalf of what the user wants. We take this very seriously when we're building products, when we're doing the various research projects that we have. Unlike any other AI product, instinct is not a task accomplisher. So 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. So 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. And 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. So we end up just doing a superset of what most other AI products are able to do.

But I think focusing on higher level objectives is very important here because it enables instinct to be more robust to these edge cases. So 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 growing at 10% day over day, so you imagine the transaction volume is also compounding at 10% day over day.

So 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 a very basic case. It's similar to an Apple Pay or it's similar to an Amex or any other platform that provides distribution to underlying services and a great user experience for the user. 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. So 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. Can you say a little bit more about how that runs into the existing world?

So I can imagine the layers being you could be a card issuer, you could be something like Stripe, you could be Visa MasterCard. 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? 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 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 even like what Stripe does on the internet or 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 if you look at most of the other major platforms in the world and what take rates that they're able to achieve. Again, it's free for the user. It's a great free experience for the user and the merchant 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 some take rate from those businesses.

I'm not sure where Stripe is. I think it's 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 premier, you have you have Apple where you make any 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, great 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. Yeah, it's very high for flights. You know, maybe it's on the lower scale. But but, you know, how many single digit percentages can you 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 transaction that that 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 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 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, 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 and 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 into 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? 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 effectively every digital service or business or application from various different verticals and industries and sort of plotting it along the line of saying, what proportion is the user's attention 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, what proportion of that transaction would be, or what proportion of their revenue is due to the underlying good being provided or service being provided? And so I think that your question is of that upper end of the scale where let's say the majority or some significant amount of revenue is due to attention on the application or advertisement or things like that. So yes, that's Uber. I actually don't know what Uber's number is.

That's a lot of the restaurant or the food delivery services. That is the travel agencies. That's even Amazon themselves with the upselling that they do on their platform. Okay. There's one simple way to look at this, which is that, okay, well, it's 70% ads, 30% good. And so therefore you're going to slash the 70% and they're going to be a 30% business moving forward. There's another way to look at it, which is I would take any business. Let's take Uber Eats or DoorDash as an example.

I don't know the numbers, but they don't know the numbers of as they reduce the number of clicks needed to check out to order food to your house or to order an Uber, as they reduce that time to check out, the transaction volume increases because it's reduced friction to get the same underlying good. And we're taking something like instinct 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 ride share business, if now the default, you know, for existing, you know, riders that love, love Uber or love Lyft 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% looking a lot, lot bigger. You know, you talk a food delivery service, maybe you're coming home late off of an airplane and 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 it 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's great. Or thank you. Yeah, please, please order that. So with very little friction now, it's a, you know, what will that do to the total transaction volume 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. And 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 users actually interacting with the business even more, which is 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 move in a different way. And we hope on our end, I think that the way to approach any big change like this is not to come in hot, you know, we're still, you know, we're a new company, we're just getting started, not to come in hot and immediately just start disrupting, you know, certain businesses, but go to them and just say, hey, this is what we think, you know, this is what we think 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 both sides where it makes sense for your business, it makes sense for our business, and certainly 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 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? 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 exercise the other day, which is just, you know, where's your revenue coming from?

What proportion of that is the user spending time in your application? What proportion of that is the user, you know, having access to the underlying service? And it's just very clear if your business benefits from more transaction volume, not at the cost or with even at the cost of less time on the application, then you're going to be in a really great spot because Instinct is going to make it, you know, a hundred times easier to do that. And if you're in a spot where nearly a hundred percent of your revenue is due to the user's attention, I think that, you know, in a lot of cases against the will of the user and what they want to do.

And there's so many games that, or so many, I would say, malicious product building almost, of trying to convince the user against their will to use the application more. We're thinking about a lot of these social media companies that the user doesn't want, they don't feel happy when they're on the app. They're unwillingly giving their time to the app and they can't get off and they keep scrolling. 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, 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 being sucked into these infinite scrolling moments like that.

I would say any blanket advice is probably just not well thought out. I think it's a case-by-case basis and it's certainly different within different industries. I would say, very practically, we're finding there are early partners with very innovative CEOs or other executives that are really thinking ahead. They're really thinking ahead and they're willing to be early partners. And what we're discovering is almost like a playbook for how every business, no matter where they exist along that risk curve, can kind of discover, honestly, what are the risks so 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 both sides.

One of those things is you don't have to go all in. You don't have to say, let's just go and now you see 70% of your revenue going to zero and then now you're stuck in this odd place. You can mitigate the risk. You can scale down the experiment. You can run A-B tests to figure out, okay, if we enable this certain thing across 1% of users or something like that and we find how they interact with the business, and honestly, does the user like it more?

Is it a more enjoyable experience for the brand side too? Does the transaction volume go up? Does the willingness to buy the product or access the product itself? There's a lot of work in product discovery too. There's a lot of times the user doesn't know they want to buy something, but they can't find it. And so does that actually increase the user being able to find exactly what they want? So I think doing scaled experiments here is actually a really great playbook to run because you can scale the risk accordingly.

At the end of it, you get the data. 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 so far. Again, it's still very early, so we're still discovering this 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 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 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.

So maybe first just say a quick word on that, what you want Instinct to feel like as a product. I could talk all day about this because I think that is just so important. And honestly, as a product builder, 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 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 small technical thing that happened under the hood? And I think the consumer is first fatigued by all of this. They don't know how to access it. And then second, I think we're missing the point. So early on, actually, one principle 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? What is their ability to predict what will happen when they ask this or when they do this or when they interact it with it in this way?

Honestly, I think that that is one of the major angles or factors that has led to 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, if I were to describe it, for lack of a better word, it should just feel good in some way, right? In the way that it communicates to you, the purpose of communicating or sending a text message is not just the meaning of the text itself, right?

It's down to underlying, 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 blob of text that requires the user to scroll a little bit to find 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. Thinking about how the user might read or even read patterns where the user...

I don't know if you know about this. No, what's that? The way that most people scan big chunks of text, they might read 80% of the first line and then maybe 50% of the next line and then it tapers off so it looks like a flag. That's a consideration that should be made. It has the ability to think about things like this, right? Okay, the user is going to 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 deliver in the lowest fatigue way or with the least amount of cognitive load placed onto the user? So 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 we do on the infrastructure side to make it fast and make it affordable to serve. 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 it being the result of a quantitative type process, like iterative quantitative process of, okay, we did ABC testing of all emoji reaction versus short versus long and this is the thing that is optimal.

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 when you're thinking about building evals or evaluation or other testing frameworks to be able to test for these very soft qualities or these actually very long-term qualities, right? Two or three weeks in, does the user trust instinct, right? How do you measure that? How do you run simulated evaluations to test if the user is going to feel trust in two or three weeks from now, right?

And actually a lot of it 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 then I'll play around with it for a little bit and see how I feel about it. And I'm just very opinionated about these types of things. And 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 they'll send it out to our smaller early access group and then they'll play around with it and 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 quite capable and is one of the most capable products out there. But I'm not saying that over the next couple months or years that others are going to come and deliver the same, seemingly same experience. But I think that this deep focus and priority on how the user feels and how to make it the most enjoyable experience beyond the words that it's saying, just the way that it feels 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, 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? What will the market shape 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. You're a very chill guy. It just seems like a stressful situation 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 the growth story so far, just to describe where we're coming from, we are, I guess, famously or infamously serving an invite-only product, which is honestly not meant to be an exclusive thing.

Although some users are treating it like that, but that's really not the intention. The goal here is to be able to, I'm ambitious, I want to scale this thing as fast as possible. But I also want to do it in a responsible way that enables us to not wake up one morning and have 10 times the number of users, and then 80% of them actually can't talk to it because there's not enough compute. The interesting thing, both the benefit and also the detriment is, well, we first started out this program, we gave it to 200 people, you know, close friends and family members, and we just said, go try it out.

And then the next day, five people came onto the platform because they just referred it to somebody. Oh, just to describe a little bit more, it's an invite-only platform, and every user will have five invites to be able to get. So just five invites. And so we rolled it out, 200 people, next day it was like 205, and the next day it was like 210. So it's like, okay, cool. A couple people are sharing it to one person, right? But then that just started to accelerate.

It was very odd. It was like, okay, it was like not 1%, 2%, then it started to be like 3%, 4%. And then once we hit a couple thousand users, some people just started to share it online too, just natively share some cool use case that they had with it. And then that accelerated the growth. It actually started to turn into like 6%, 7%, 8%, 9%. And now I believe we're like 10% or 11% every day. And just to call that out, it's not that we're doing some sort of creative marketing event.

We spent $0 on marketing so far. It's not that we're doing something every single day to be able to support this growth. Every day, about 10% of the audience, or 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's something very significant there. When I talk about strength of word of mouth, it's honestly a little bit surprising. It's one of the strongest cases of word of mouth growth.

I find all these stories of people saying, they'll ask me and they'll actually be ashamed. They'll email me and say like, hey, can I please get an invite? I think I have a friend that has it, but I don't know if I make it into his five friends. And then there are also people who are bragging like, I got three invites left and I'm just holding on to it right now. So there's so much happening of people that want access to the product, but there's these odd social games happening of people using their invites.

I was seeing the other day, there were some invites that were selling on eBay too. I don't know if you saw this. It's like 300 bucks, people were buying these invites on eBay. It's just to control the growth. So then the big question comes, the thing that most people are asking right now is, you have much bigger players that are able to distribute to a billion or two billion people on the planet immediately. And maybe they might not be compounding naturally as fast, but they have such a great top funnel distribution.

And then you have us compounding at a very, very fast clip every day. But we don't own a major service that has two or three billion people and able to distribute immediately that day. So it's an interesting question. Where does the curve line up and where's the inflection point? And 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 spent 40% of my time worrying about. It's not like the traditional other consumer products that grew very fast, where it's to double the number of users on, let's say, Instagram or Facebook or something, it would be this many number of other requests going through the platform.

And yes, there's a scaling story there and it's certainly hard infrastructure work. We also have that, to be fair. But what do you do when the underlying compute also needs to double? 10% day every day. We've been doing this for several weeks now. What does it mean when the amount of compute that you need access to is now doubling effectively every week? Do we buy compute 2x of what we have right now? Well, we're going to consume that in a week. So then do you buy 5x?

Well, we're going to consume that in less than three weeks. Do you buy 10x? So now it's like your 10x leverage, right? If you can even stomach what it's like to buy 10x ahead. But then you're going to consume that in a couple of weeks from now, right? So that is the hard problem. It's thinking about how far ahead do you buy. It's growing at a faster rate than Cloud Code or Codex or some of those other applications where they also had 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 users, you can buy 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 buy compute because honestly, you get taxed 3x or 4x what it is. If you're wrong, you're wrong by 3x or 4x. Let's say it slows down, right? Let's say we don't actually do 10% for a very long and sustainable period.

Let's just say it's like 5% to 8%, right? But 5% to 8% compounding day over day for three, four months, which is the lead time to bring compute online. And that's even aggressive itself. That's 100 million users, right? So then do you buy compute for 100 million users? So those are the types of questions I'm wrestling with, which is just like, if you're wrong, you're very wrong. You get charged 3x or 4x. What about if you zoom 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've figured out how to serve the product which is um when we when we run no matter how you evaluate whether it's a b 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 5 which is now I guess we're dating ourselves um opus 5 is uh um you know like frontier level uh intelligence we're able to serve it's the same engagement rate the same um you know a b test performance 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 free for a lifetime for now but 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 proactivity that is happening throughout the day that doesn't actually need to finish in hundreds of milliseconds it needs to finish in 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 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 it 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 CodeGen's obviously been an enormous amount but ground us in some sense of scale of like you know whether it's per user or something or some way of understanding just like how much 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 it comes back to user and then asks for something else and then the user sends something again 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 is not showing up like you know I'll be able to you know help help the user through this moment so proactivity 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 with the earlier break you know breakout products in the AI space that are just scratching the surface of proactivity or of background work here now we have something that is almost natively proactive it is it is a smaller subset that is actually interactive right so I I think that the amount of compute that is going to be needed is going to be honestly orders of magnitude more than what we thought that we needed it's just with more proactivity comes more 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 6 a.m because it knows that you wake up at you know 7 a.m and then it goes and scans everything make sure that that you know everything's ready for the day for you and and 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 4 p.m there's something that's coming up there's value that could be provided maybe 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 something valuable to the user so it might then just wake up at 4 p.m 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 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 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 i'm 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 a simple and and very easily accessible and um you know of the of the soft qualities that we were we were talking about earlier of you know really thinking from the user standpoint about what's what's important what's not important and how to make this task easier and easier to read and other things like that uh 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 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 things 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 are are actually using ai in 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 uh i'm just i'm just focused on building the best product experience what have been the blunders 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 talk 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 um 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 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's an early version of the product that that had 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 build 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 of their data the user can share as much as they'd 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 access to 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 or i'm just curious for you to riff on the future of security and and safety and guarding against 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 um building uh security and safety and and a mindset towards that uh 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 in 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 tracked the last 20-30 years seeing some of that now um but also i i think just um uh 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 hallucination 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 certain 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 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 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 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 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 is one key um uh 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 uh in the 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 uh 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 interaction 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 and 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 uh discretion to know when you're addressing 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 you might be going on a hike or on a bike ride or on a walk on on a on a run or something like that and you're just like catching up like hey this like contract needs 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 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 interface has 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 and 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 and ship it out to people and then and then you find like some feedback like hey i wish it looked like this and then you take it and you make the improvement and you ship out a new version.

And this is on the order of like months, right? And then over time, over 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. Every time we need something, like, is there an app that does that? I think that all of that collapses down in the future. I think that all of software is going to collapse down into, honestly, a single very, very easy to use interface. And I don't get that confused 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 daily tasks, like, I want to do this, can you do it? And that friction is going to go down to zero. I think that it will start towards pursuing higher level objectives that are aligned with the user, where the user is able to describe not just, hey, can you track this workout for me? Can you do this? And I performed here, and this is how I did.

But more about, hey, in three or four months from now, can you, 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, or are starting to discover that today, of, you know, you want to, you know, gain this much, 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 small businesses 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 completely functioning on top of Instinct. And even parts of it are fully autonomous too, where, 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 saying, hey, please order this thing, it's, you know, pursue this higher level objective and use the tools and devices that you have available to be able to accomplish that.

So I think that's the future. And I'm not like, you know, there are so many cases of objectives that you could state and have it pursue for an unbound number of amount of time that we could brainstorm here. But I think that's the meta level picture is it's the moving away from, you know, individual use cases over to higher level objectives is going to be where I think interaction 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, omni-capable agent and the user.

What do you think about that aspect? I think of instinct as this 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 the product? Well, you mentioned Her, I guess, comically. It's certainly relationship building or anything in that area is not something that we want it to instinct to do or to pursue or to develop with users. If I describe more about what it should act like and feel like and represent within the person's life, 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 what is the 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 ever because it's able to not just, you know, we're not just able to serve a different version of it, it's able to evolve over time. That's why we put so much care into 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.

It's going to learn those over time 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 Instinct? Instinct, I liked as a name for so many different reasons. I think the main thing is that Instinct 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 thing that only takes the dirty work off your plate.

And I think it's this new, creative, exciting, you know, competent actor that there's like mutual respect and trust and they feel safe and they trust that it has their back, that it's intelligent, that it's competent, that it's socially aware to know how to act in certain situations. And it's a bet. But I like that Instinct is not, you know, named like, I don't know, someone's name or something like that to try to personify it 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 really thinking about this feeling of what it should be like. I think that 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. 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 more about just very grounded from first principles. 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 just primarily thinking like we're not pinned to iMessage actually. More than 50% of our traffic doesn't actually 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 most practical for the user and we're going to shape shift as we see towards just delivering again that very simple, easily assessable sort of like zero friction experience that it is today. I know your latest round is something like a billion dollars at roughly a $10 billion valuation.

Some of the best investors in the world. Sequoia, Benchmark, Kotu 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'm just very lucky to be able to work with some of the most supportive partners around the table who have been through different but similarly shaped technology transformations in the past. And I would focus less on the numbers and more about just 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 delivering on that AI experience or 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 create something that's going to hopefully be distributed to billions of people 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 our users. 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 business model that we're chasing after, because we could very easily just say, hey, it's going to be a certain subscription and everybody on the platform needs to pay a hundred bucks a month, right? And there are shorter term rewards that we can chase after. Or we could raise a little bit of capital, use that towards, you know, what is venture capital meant for? It's to be able to, you know, take certain calculated risks towards, you know, if there are small speed bumps 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, you know, the subscription plan or other things like that. When I do this, I 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 I work or in my personal life that I'm very grateful to be around. And hopefully, certainly I can also extend the same level of kindness and thoughtfulness 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 things that I noticed that I really appreciate. Noah, you're building a fascinating company, maybe the most fascinating company of today's AI ecosystem in the world. Thanks so much for your time. Thank you so much. If you enjoyed this episode, visit Colossus.com. You'll find every episode of this podcast complete with hand-edited transcripts. You can also subscribe to Colossus, our quarterly print, digital and private audio publication featuring in-depth profiles of the founders, investors and companies that we admire most.

Learn more at Colossus.com slash subscribe. Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit PSUM.VC. You know how small advantages compound over time. That's true in investing and just as true in how you run your company.

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