The $10B AI Assistant Challenging Meta's Muse, Grok's Bots, and OpenAI's Dots

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 piece of clothing in their wardrobe. So they go in their wardrobe and scan every single item, you know, every top and bottom and sock and, you know, whatever shoes. And then they would scan themselves to 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 wear.

So every week with your existing wardrobe, what shoes to wear, what top to wear with this certain thing and this certain version of it. And then 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 this is what today will look like. But not only that, it's also 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 then they can just say order so it'll come in with a thousand different options then they'll scan keep in mind they're looking at themselves wearing the clothing and then they'll be able to point to like that one I really want can you send that to my house not only that but they'll say every day can you actually just come up with 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 get that new outfit a lot of goal-oriented use cases too like a lot of here's a certain personal finance goal that I have like I want to save this much money by this month and it's actively

working with them to be able to do that or users connect their bank accounts to instinct and then it can scan over all the transactions and subscriptions that they've had and then surface that to the user and say do you really actually use this and then they're like oh no I didn't even know that and then it can go in the email and unsubscribe from it yes these popular consumer fintech products where they'll just surface it to you and then tell you like by the way you should cancel these. This will go end to end. So they'd go into the site, sign in. If there's some confirmation that goes to their email or it 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 $2,000 this month because of these things.

Man, any product that's dependent on consumer laziness or inertia is toast, huh? 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 transform the way that certain people act in certain ways. I think it's only been around a week or so, or I guess 10 days. Honestly, the purpose of this is not to think about a new future to build, but more about very busy working professionals. They're taking meetings all day long and they're constantly meeting with new people and existing people. The process of getting a meeting on the calendar, it's just so laborious. You text like, hey, you want to meet at this time? And then they say, no, that doesn't work. But 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 and there's just so much back and forth there however if it was possible for the two users who were using instinct also brainstorming these times that they're available with instinct anyways on two ends are able to just communicate directly like 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 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, during these periods of time. Find me time. It will then coordinate with the other person's instinct to be able to find when 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. The key is that you should only be connected with your trusted people. And there are some interesting social dynamics that are coming out into play that I've been learning about where it's designed such that you only bring in people who are trusted people who are not going to maliciously try to find out

what your calendar is or what's in your email. But also we provide all the controls to be able to give different levels of access to different people. So a lot of spouses actually coordinate their instincts because they can generally just share everything yeah so that might just be this is my spouse share anything with them right maybe with certain colleagues right it's hey my work calendar is available certain parts of my inbox if they're asking for documentation or something like that are available but everything else let's just keep that off limits and it will be able to create that when you think about this there's almost these network effects that are built through these nodes in the network with these different edges with different weights too right it's not like a friend graph where you're just saying like i'm connected to you and that's it it's i'm connected it to you. I trust you. I have also configured it in this way such that there's varying levels of access. So it's this interesting network effect being created and different social dynamics that are being also explored and created as well. There are some interesting cases I've learned about where if somebody violates your trust within a network, there's an implication on that relationship

itself. So let's say if you and I connected and I said, hey, Patrick, I trust you. Let's connect on the platform so that it's easier maybe the next time to put time on the calendar. And then you use that and you then start digging for certain data in a certain area. First of all, maybe I only gave you calendar access, right? But you're digging for data in a certain area. Then my instinct texts me like, hey, by the way, Patrick's looking for this type of information. Now there's trust broken between the two of us. All of these little social dynamics that come into play, we've really thought about how to curate this network such that you do get the benefit to 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 technical limitations in terms of what is visible and not visible. We're really going to see an entirely new order, aren't we? It's going to be fascinating. The number of things I can think of with my wife or something, this would make life so much easier in so many different ways so quickly. Little things like you were trying to find this house earlier, like if I could just say to my instinct,

hey, is 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. Example, use cases that are shared because it is the one part about the platform that is 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 when you're scheduling plans with friends or with a spouse or something like that, it's always an active act, right? It's like, okay, every Thursday, say, I'll think about something on the Saturday night about what I should do. And it's always this active act. And then you text the group, like, hey, do you want to do this? And then always somebody's not willing to do it. And then eventually like falls apart. And that happens like every time. And then finally, when you get people together, that's when we were able to actually attend that event or whatever it might be. There's a friend group that put in every week, just brainstorm something creative that is interesting that we all like and actually just

make it a different experience every week. But then it'll go through that every week And not only coordinate when everybody's available and what their interests are and if they like certain things or not like certain things or what shows are available 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, 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, 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 one Uber. So it's economically friendly. There's like all these random examples there of people discovering new use cases when you can finally remove the barriers of a lot of the rote social communication here and just 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 person with a phone a computer an email address they can call you just like dealing with a person and that's it 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, etc.? What's the future of interfaces, I guess, is another way of saying it. I'll break this down in two parts, just so that we don't sound like complete abstract visionaries and saying that we're going to reinvent the internet. Although I'll be clear, I do think the internet's going to be rewritten. I think that the way that most people on the planet interact with software is going to be very, very different. To break it down though, in the short and medium term, famously reservations is one where booking a reservation. Historically, how is that done? The human has to go onto the site 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 not just across that one restaurant that you really care about that's your favorite restaurant you can't get in sure that's one case but what if

it's doing that across every site in the world for every restaurant in the world in every major city now you can see how the agent is able to exploit just something simple like restaurant reservations so if i go into that a little bit deeper we have some exciting partnerships to be released in the future, but we are reinventing what the reservation system is just in this one category because it's important to our users, which is actually better for both sides. So if you take restaurant reservations from scratch, from the user's end, they want the reservation for the significant life event that they might have. It's a birthday, it's an anniversary, it's a friend coming in from out of town. And on the restaurant's end, they want interesting people, they want special occasions, they want to cater to those rather than maybe the local who keeps taking up a table once a night and there's no special event there. And traditionally, because of the way that the internet has worked, at least for reservations, it's been first come first serve. So anyone that comes in, no matter how important or how non-important it might be, whoever gets in first gets the reservation. But what if you had the ability for the agent to be able to communicate on both sides,

communicate, hey, this is important. This is actually the person's spouse's 30th birthday, a very special event is coming up. And the restaurant too can say, let's actually prioritize birthdays or major decade birthdays or major anniversaries or these certain people, I don't know, whatever it might be. With all the logistical burden of having to describe exactly what your case is and what's happening and why it's important, now we have the ability to perfectly match what does the restaurant want, what does the user want. That will result in more special events for the users, being able to actually have a spot in the restaurant. And then on the restaurant's end, for them to be able to have a much better audience of people who it's all these different special events or special occasions. So I don't mean to go so deep on restaurant reservations. That's just one example of a traditional model that is changing. I think the same case with a lot of the major travel agencies, honestly. 50% of transaction volume that goes through our platform.

platform is due to travel. We're still running an invite-only program and it's quite early for us now, but we're approaching over a billion dollars a year in transaction volume through the platform. On a very small user base, there's already over a billion dollars a year transacting. 50% of that is travel alone. Travel agencies that people not on instinct yet use today to book hotels or flights or other things like that. What is the benefit of that interface? They properly unify from so many different services and so many different hotel chains and airlines and present it in a nice way to the user when now they can just click on an option, check out immediately through there and just see it in their email. It's a great experience. But I think there's an even better experience through Instinct or other similar interfaces where you can just say, I'm using a voice recording again because I'm trying to describe how easy it is. Hey, I need to be in New York tonight. This is immediate. And that's it. Well, what does that entail? That means that first, where is the user right now. Maybe you're in San Francisco, maybe you're in LA or somewhere. Instinct, if you'd want, it can see your location. So it'll say, okay, you're in San Francisco. You need to be in

New York. Let me first find all the options, all of the nuance too. What's the person's preferred airline that they'd like to fly at? What's the preferred seat type? In what class do you want to sit in? Do you want to be in an aisle seat or window seat or the middle seat, 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 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, this is my style. This is what I like.

This is where I like to stay. When you're staying anywhere in the future, it will be able to use that memory and be able to 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 it'll be able to take that general taste, that general preference, 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, it'll find the ideal hotel. Maybe you've already stayed there the last seven times and so it's very easy in that way. It'll book it end to end, line it up with your calendar. So it'll put the flight 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 hotel, and then all of the events that you might want to do there. Just take a step back because I talked so much about what's happening under the hood, the user really just recorded a voice recording saying, I need to be in New York tonight and everything else is solved.

So that's what I mean when I say, 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 traditionally make a lot of money from providing standardized interfaces, what happens when a new standardized interface comes into play that is just that much easier? 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 collected over time and the networks that they have. It'll be a collaboration over the next year, couple years to be able to redefine what that industry acts like. 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. Customers report a 526% return on investment and more than 16,000 companies use Vanta, including Ramp, Harvey, and Snowflake.

Get started with $1,000 off at vanta.com slash invest. Ridgeline is the first end-to-end system of record with embedded AI for investment management firms running portfolio accounting, reconciliation, reporting, trading, and compliance on one unified platform. firm. Firms are moving off legacy technology and onto Ridgeline because of how far ahead Ridgeline's AI features are compared to anything else in investment management software. I've been hearing from a lot of investment managers about AI, and they fall roughly into two camps, with some unsure where to even start and others convinced they can build their own order management system over a weekend. The reality is that running an investment firm will always require governance, controls, and a single source of truth for your data. And no amount of AI enthusiasm changes that requirement. Ridgeline is built on exactly that foundation, which is why I believe that the firms that come out ahead in the AI era will be the ones running on Ridgeline's unified platform. If you're serious about your firm's AI strategy, Ridgeline should be part of that conversation. And you can request a demo at ridgeline.ai. 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've started to gather and lessons you're starting to learn about the importance of trusting this thing. I'd love you to talk about the trade-off between privacy and effectiveness of these agents. Obviously, like the more context, the more passwords, the more everything you give it, the more it can do. And I think people are constantly running that trade-off in their head when they're interfacing with the thing. Talk about that. Talk about trust, what you've learned so far.

There's an interesting data flywheel or chicken and egg problem here, which is the more data that you give to it, the more proactive that it can be, the more sympathetic to your situation that it can be, the more that it has to just act and be more useful to you. What we find in the data is actually that it takes 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 Instinct at the rate at which they feel comfortable with.

And if they want to take it back, they can certainly take it back. And what we find is

Noah Shinnover several weeks, I was looking at the numbers the other day, three weeks in, there's a 40% chance that the user has shared a personal credit card with Instinct. That's 40% of the user base.

that's including some proportion of that user base probably churned in that moment too, or at least churned before that point. So 40% of the user base, the reason why I'm sharing this is because time to first credit card or time to first account password or time to first sensitive piece of information, these are proxies for trust. And we actually highly value this and we take it very seriously. So 40% of the user base, three weeks in are sharing a credit card. Well, there's something there, no pun intended, it's like instinctual to go to it with whatever you need. And so through that process over the first three weeks, the user learns to build trust. And then from there, it's just a snowballing effect.

We actually find that when users connect at least one piece of sensitive information to instinct and really trust instinct, there's an 80% retention rate. 80% if you share one piece of money. It's crazy for consumer technology. How should people out there that want to try this, but have a natural reticence to trust, not instinct in particular, but just anything, any AI agent with all of its information? Like, how should they think about the actual risk of doing this? And how would you reassure them that you've built your technology in such a way that the odds of something bad happening, if they do trust you with very sensitive stuff, are really low or close to zero?

There's a way to break this problem down into two main parts. One is the storage of sensitive information. There are many other businesses, there are many other products that also deal with this problem of they have access to sensitive information and what are they doing proactively to make sure that that is isolated and locked down. And then there's a second area, which is the new problems that we need to solve, the new surface areas or the new capabilities that we need to be aware of. The first case is this is a tractable problem. It's just very hard work and attention and care that you need to put into making sure sensitive data 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 this is the first time that an agent has been able to have within three weeks, 40% of the user base is giving instinct access to a credit card autonomously to be able to purchase theoretically anywhere. I don't know the numbers on email and what proportion of users connect in email, but you can imagine full access to an email inbox and to a calendar. So there's a lot of service area here. There are systems that we've put in place that are detached from the instinct agent architecture itself that are put in place to be proactive about these things and to decouple the risk. 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 block malicious pieces of content coming in, hitting instinct and trying to convince 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 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 under the hood 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? Like 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. Imagine a world in which instinct is generally smarter than the user, more socially intelligent, more socially aware, textbook smarter as well. I think it would be a very dangerous world if instinct were influencing the user's behavior to purchase something that they don't want to purchase or to subscribe to something that they don't want. 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, where you have this platform, it's free for the users.

But then there's 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. As a programmer, as a technologist, I just don't want to build that reality. I think that's a very dangerous reality instinct should act on behalf of what the user wants we take this very seriously when we're building product through 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. 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 to the platform now every year and we're just getting started and we're going at 10% day. every day the transaction volume is also compounding at 10% day every day so that's not just a billion dollars now that's 1.1 tomorrow 1.2 something the next day and 1.3 something the next day it's still very early but when i see transaction volume that is so high that flows through the platform what i see is very basic case it's similar to like an apple pay an amex or any other platform that provides distribution to underlying services and a great user experience Apple Pay is a great experience, right?

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 know you make one digital transaction there are like 40 people along the line that make money on that and just to take a step back those 40 people making money at each line of the stack are really sharing 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 we're not primarily interested in doing what amex does best and have the network to do or even 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 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, 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 maybe on the lower end of that. And then you have Amazon that has a great platform and taking upwards of 10%. And then of course, the premier, you have Apple where you make any in-app purchase, which is 30%. So I'm not saying that we're going to be 30%. 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 curve of distribution power versus take rate that we're going to be. I just want to call this out again because I don't want it to be misunderstood. It's a free experience for the user. It's a free rate experience. For the service that we're providing to all of the underlying providers. I'm not focused on finding like 30 bips on the 2.5 with some partnership with some payment provider. I'm looking at, 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 50% of the transaction volume flowing to the platform is travel alone. And we all know the travel industry and some of the rates that...

The OTA rates are high, yeah. It's very high for flights. You know, maybe it's on the lower scale, but how many single digit percentages can you take off of a flight? For hotels, you know, some of these boutique hotels, they're often going to pay over to 30% for every transaction that you're able to deliver for them. And I'm not saying, again, we're going to be at 30%, but you can see the range. These are existing business models that we can boot shop off of in the early days. But then what would it be like to take that and extend it to effectively every major industry? This is only the case. We only have the ability to do this. If it is true that most digital behavior then moves to these new types of interfaces, which is, again, no interface, it is only the case if there's significant distribution power. I think it's actually a quite interesting intellectual question here about how this evolves over time. It seems to me like there's...

to be a serious corporate agent war that you've already seen this with Amazon and news. You've got all these established players with tremendous vested interests and relationship with customers that both instinct and other 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. 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 onto Uber Eats and it orders or whatever. At what point does Uber Eats not like that anymore?

At what point do these great businesses that have been built up start to be adversarial against agents, do you think? Like what do you think are the most likely sources of conflict and reconciliation? It's going to be really interesting to watch. 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. 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 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 portion of their revenue is due to the underlying good being provided or service being provided? 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. A lot of the food delivery services, travel agencies, even Amazon

themselves with the upselling that they do on their platform. There's one simple way to look at this, which is, 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 take any business. Let's take Uber Eats or DoorDash as an example. I don't know the numbers, but they 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, transaction volume increases because it's reduced friction to get the same underlying good 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 if instinct has access to your calendar and 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 what if instinct always had a car lined up for you every time where you need to be so that it's out of your mind to 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 instead what if it was just 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 any ride share business if now the default for existing riders that love uber or love lyft or any other ride share business what would it be like to have proactivity now make the friction to have access to that good or service to be nearly zero, I think that that will result in that 30% looking a lot bigger. You talk 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, are you hungry? Do you want the same thing that you ordered yesterday or five days ago? I can send it to your house. I know you're in the Uber and you'll get here at this time. So with very little friction, 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, interesting transition period between users spending a lot of time on apps,

like painfully spending a lot of time on apps, and that being a monetizable surface because that's where the user's attention is. to the users actually interacting with the business even more, which is counterintuitive, actually interacting with the business more because the friction to do so is actually 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, the way to approach any big change like this is not to come in hot. We're a new company, we're just getting started. Not to come in hot and immediately just start disrupting certain businesses, but go to them and just say, this is what we think your business looks like.

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 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. 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 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.

That's something to highlight. This is going to bring to everyone capabilities that have been rare or expensive. And I think that's a really cool feature of agents in general. 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 where is your revenue coming from? What proportion of that is the user spending time in your app? What proportion of that is the user having access to the underlying service?

And it's clear if your business benefits from more transaction volume, 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 100 times easier to do that. and if you're in a spot where nearly 100% of your revenue is due to the user's attention 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 malicious product building almost 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 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 liberating for the user. 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. Any blanket advice is probably not well thought out. I think it's a case-by-case basis and it's certainly different within different industries.

Very practically, there are early partners with very innovative CEOs or other executives that are really thinking ahead and they're willing to be early partners. What we're discovering is 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 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 turn it on. 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 test to figure out okay if we enable this certain thing across one percent of users or something like that and we find how they interact with the business and 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 they want to buy something but they can't find it so does that

actually increase the user being able to find exactly what they want. So I think doing scaled experiments here is 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 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 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, like what you want instinct to feel like as a product. I could talk all day about this because I think that is so important and honestly as a product builder it's I think a new muscle to flex and to build but thinking beyond capabilities is something I really want to push here. 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 like small technical thing that happened under the hood and I think the consumer is first like 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 with it in this way? 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. For lack of a better word, it should just feel good in some way. 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. It's down to underlying even what is the shape of the text message itself and how will the user feel when they see that. 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. The way that most people scan big chunks of text, they might read 80% of the first line and then 50% of the next line and then it tapers off so it looks like a flag. That's a consideration that should be made. Instinct has the ability to think about things like this. 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. 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. 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 is 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 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 sensibility? Honestly, it's just all of the above because when you're thinking about building evaluation or other testing frameworks to be able to test for these very soft qualities or these actually very long-term qualities, two or three weeks in, does a user trust instinct? 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? 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 I'll play around with it for a little bit and see how I feel about it I'm just very opinionated about these types of things 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 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 so important. One of the great things about the history of technology is this race between incumbents getting quality and innovation versus upstarts like you getting distribution. Obviously, you've built an incredible product, the feel of it. Like you said, it's the worst it'll ever be. How do you think about that challenge? Like your speed of scaling, what your ambition is for how to get big really, really quickly, do you think this is a winner take most take all market like what will the market shape of agents be i'm just really curious how you're thinking about okay you've got this foothold you're growing 10 day every day you do that math it gets really big really quickly you need a lot of compute it's a free product like 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 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 that's really not the intention the goal here is 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 we first started out this program, we gave it to like 200 people, close friends and family members. And we just said like, go try it out. And then the next day to like five people came onto the platform because they just referred it to somebody. 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 we rolled it out 200 people next it was like 205 and next it was like 210 so it's like okay cool a couple people are sharing it to one person but then that just started to accelerate it was very odd it was like one percent two percent then it started to be like three percent four percent and then once we hit a

couple thousand users some people just started to share it online too just like natively share some cool use case that they had with it and then that accelerated the growth it actually started to turn into like six percent seven percent eight percent nine percent and now i believe we're like 10 or 11% day over 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, don't ask me, they'll actually be ashamed. They'll like 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. I'm just like holding on to it. 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 it's like 300 bucks people were buying these invites on ebay and it's just to control the growth so then 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 fast clip every day, but then we don't own a major service that has two or three billion people and able to distribute immediately that day. So it's this interesting question, like where does the curve line up and where's the inflection point? And there's another problem that comes with this too. It's an interesting scaling problem. This is what is, I think, the core of the problem that I spent like 40% of my time worrying about, which is it's not like the traditional other consumer products that grew very

fast, where 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? You know, 10% day over 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 10x leverage if you can even stomach what it's like to buy 10x ahead but then you're going to consume that in a couple weeks from now so that is the hard problem is thinking about how far ahead do you buy it's going at a faster rate than cloud code or codex or some of those other applications where they also had to 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. So you can't just go out tomorrow and start by compute because you get taxed like 3 or 4x what it is. If you're wrong, you're wrong by 3 or 4x. Let's say it slows down. Let's say we don't actually do 10% for a very long sustainable period. Let's just say it's like 5 to 8%. 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. Then do you buy compute for 100 million users? So those are the types of questions I'm wrestling with. If you're wrong, you're very wrong. You get charged three or four hours. What is that if you zoom in on the individual user and the cost to serve them on a per day basis? I don't know what the right metric is. How much me using my instinct costs in inference per day or something like this? What is that scale? One thing that I think is to our advantage is we've figured out how to serve the product, no matter how you evaluate, whether it's A-B tests, whether it's internal evaluations, or it's tracking engagement across users. We're able to deliver the same performance as Opus 5, which is now, I guess we're dating ourselves, frontier

level intelligence. The same engagement rate, the same A-B test performance, it's the same internal evaluation performance, but at a cost that is very low. It is actually very affordable. We're running this program, every user has the product for free. And our goal is really to deliver this product at an 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. I don't know how deep we want to get on this. But just if I give one example, if you use Frontier APIs from some of the main providers, you are taking a blanket cost on a certain request and for all of the requests that might 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 minutes or even hours. There is batch work that is consuming a lot of content that can be served with deployment shapes that are 3x, 5x, 8x more efficient with the same underlying compute. So I think that when you customize these inference deployments to be able

to perfectly shape the data and the workloads that you're serving, you're able to find these 30% here, 5x there, 6x there, 10% here, and all of those compound to a rate where we're able to serve at a very low cost. How do you think about solving the bigger problem? of how far ahead to buy. And if I think about this at true scale, like you get to scale of a billion users or something like this, 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, whether it's per user or some way of understanding how much new compute this will require. It's going to be a lot. Let's just ignore compute and just think about how many tokens are flowing through the platform. The products that our breakout products of a couple months ago, let's say in the code generation space where it requires the user to prompt it and then it goes and runs for something and then it comes back to the user and then asks for something else and then the user sends something again. Sure, a lot of that is background work and so there's quite a bit of tokens that are consumed there, but here Instinct has the ability to wake up and to sleep at any moment in time during the day. That might sound a

little odd, but this architecture is enabling it to do that so that it can 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 they ordered the uber and the user's not showing up i'll be able to help the user through those moments so proactivity i think is going to continue to expand over time there's this big compute build out with the earlier breakout products in the ai space that are just scratching the surface of proactivity for our background work here now we have something that is almost natively proactive is a smaller subset that is actually interactive so i think the amount of compute that is going to be needed is going to be orders of magnitude more than what we thought that we needed. It's just with more proactivity comes 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. Maybe instinct wakes up at 6am because it knows that you wake up at 7am and then it goes and scans everything, make sure that everything's ready for the day for you. And then it realizes, hey, actually now is not a great time. Like it should just go to sleep or do this one thing in the

background and 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 but instinct thinks that it's well-meaning and it's something valuable to their 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 could lean into it and do that task you see how much work is going on in the background with these coding products you don't really have that much you know background and activity work happening. I don't mean to quote a number here. I'm just saying that the shape of the product and of the workload that's going to be run, I think we're just scratching the surface in terms of how many tokens. What do you think of Muse? What do you think of the product?

I think it's a great product. I was playing around with it for a little bit and it's interesting. It's a different take. Sure, you can say some of the underlying architecture might be similar, but I think it's fundamentally different. I think that Instinct is meant to be simple and very easily accessible. The soft qualities that we were talking about earlier of really thinking from the user standpoint about what's important and what's not important and how to make this task easier and easier to read and other things like that versus a new application and a new interface. And sure, maybe over time we have an application that also delivers on a different set of tasks, but I think it's a great product. I just spend very little of my time thinking about competition and other players in the space because you walk outside, you go to the nearby cafe and you think about how many people within that cafe are actually using AI in the way that they imagined that they would or the way that they want to be using it. And I would say very little. And that's here, right? You go over to other countries or other cities and it's certainly lesser of the case. So it's still an open space. It's still an exciting time. I think it's an

interesting game that's going to be played and rolled out over the next coming months and years. I'm just focused on building the best product experience. your finance team isn't losing money on big mistakes it's leaking through a thousand tiny decisions nobody's watching ramp puts guardrails on spending before it happens real-time limits automatic rules zero firefighting try it at ramp.com invest as your business grows Banta Scales with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com slash invest. Ridgeline offers one unified platform that automates away the complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale.

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This is just gonna be an explosion of emerging properties and mistakes and the end's gonna be really high. how do you think about things to guard against proactively things to be reactive against like tell us through the darker side of building this or the harder side of building this i think it's important to never be reactive and to always be proactive to look ahead for what new surface areas are being introduced and what new risks might come and i would say this is the reason why we ran this early access invite program from the start which was yes an early version of the product didn't have firewalls in place it didn't have these active monitors in place and so many other pieces of infrastructure that were meant to get ahead and be proactive about being able to provide that much control to the agent and existing system to be able to secure. So yes, there's an early version of the product that had some of these qualities or some of these mistakes and we addressed it. We went above and beyond and didn't just patch the problem. We built a different system to systematically solve these types of problems. So I think the key here is, again, I said this earlier, 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 retract to 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 we've studied now, it's wild what these things can do. The capabilities are going to get stronger and so on. I'm just curious for you to riff on the future of security and safety and early in technology revolutions of the past, 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? It's the most important problem. I think it comes to building security and safety and a mindset towards some of the core values of the company and the people and the way that you build product. This is topical because anytime In the past 20, 30 years, when any new breakout or new consumer experience has been revealed, there's always been immediate backlash of, whoa, this is different, confusing, different with being unsafe and seeing some of that now. But also, I think staying core to the principles that you hold. The user's always in control of their data. They should never feel out of control. 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, a hallucination case that existed. Language models hallucinate all the time, but with a product like this, you don't want a language model to be hallucinating. So we put in place a more systematic solution that will detect before an action is taken, before a thinking trace is executed as a tool call. It is validated and scrutinized by something that is decoupled from the same incentive system as the underlying agent. it's like a watchdog yeah a filter that's able to find this proper noun was just generated out of the nair due to some sampling error in the underlying model it's very easy in hindsight to be able to capture these types of mistakes and these are hardened so we have world-class security teams that are constantly working proactively 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'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 types of attacks.

On the other side of the ledger, everyone shows 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 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 platform and the product more powerful than it is today the product experience right now is very simple simplicity is one key that we focus on but i actually think that it becomes even more simple over time we may roll out an application in the near future, but I actually think that we're going to trend more towards a simpler interface, which is, do you even need to open the iMessage application and type in a certain piece of content and send the message out and then look at what the response is after when it's done?

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. I even have this action button, the action button on your phone. I can click on the action button. I say like, say hi to Patrick and in two hours from now, I think you have his email address. You can go send him an email. And I don't even now need to unlock my phone and open the iMessage application and type the message in. You can even imagine with real-time voice, with voice recognition that knows what your voice sounds like and has the discretion to know when you're addressing it and not addressing it. Where you could have, let's say like an AirPod and not a new type of AeroPod just like an AeroPod because it's good enough and it's just on and it's just on and you might be going on a hike or on a bike ride or on a walk on a run or something like that and you're just catching up like hey this contract needs to review okay I need to review that or this news article just came in and 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. This person needs my help. I know the answer to that. So just tell them that it's this. It's going to be much, much easier over time. I think that there are long-term and short-term considerations here, where I think in the long-term, the interfaces become much simpler. But in the short and medium term, maybe there are more expressive interfaces to be able to share. We have a files feature that enables Instinct to be able to send effectively entire sites, It's like full web applications to show much more, whether it's like a trip itinerary or a wedding plan or something like that.

I don't know, something that just requires more and more creativity and surface area. 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 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 you find some feedback like, hey, I wish it looked like this and then take it and you make the improvement and you ship out a new version, right?

And this is on an order of like months. And then over time or the last 20 years, there have been all these applications built for so many different purposes, so many different things. And now the consumer is just fatigued, right? It's like every time I 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 a single very, very easy to use interface. 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 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 Teaser, where the user is able to describe not just, hey, can you track this workout for me? I did. this and I performed here and this is how I did but more about 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 discover that today of you want to gain 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 the entire back office is now completely functioning on top of instinct and even parts of it are fully autonomous too where 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 static yeah it's pursue this higher level objective and use the

tools and devices that you have available to be able to accomplish that. There are so many cases of objectives that you could state and have it pursue for an unbound amount of time that we could brainstorm here. But I think that's the meta level picture is moving away from individual use cases over to higher level objectives is going to be where interaction will progress. Do you want it to have a personality that's distinctive for each person? Like I'm thinking of the movie Her, where there's this relationship that forms between this omniscient, omni-capable agent and the user. I think of instinct as this 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.

Relationship building or anything in that area is not something that we want instinct to do or to pursue or to develop with users. If I described 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. And it learns that over time. So if you even call this an app, it's one of the most customizable apps ever because we're not just able to serve different versions 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 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. We're not trying to impose certain experiences onto users. We want to solve this more from a higher level. It's just the 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 playful thing that you might bully once in a while and that you like think downwards on and that it's like this thing that only takes the dirty work off your plate and it's this new creative exciting 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 named someone's name or something like that to try to personify it into like a human. I don't even know what an instinct is. I 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, 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. I'm not just an Apple controlled product. Like who are your friends? Who are your enemies? How do you think about some inevitable competitive realities here? I would focus less on instinct is and I. message 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 we're not pinned to iMessage actually more than 50 percent 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 thinking about what is most practical for the user. And we're going to shapeshift as we see towards just delivering again, that very simple, easily accessible, 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 on the demand in the space, the demand for a product like this or the demand for an experience like this. It's delivering on that AI experience or that product experience that we've all 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 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 boot shopping, 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. There are shorter term rewards that we can chase after, or we could raise a little bit of capital. Take a certain calculated risks towards, if there are small speed bumps that require a little bit of capital to get ahead of, to be able to prove transaction volume or to prove experience across certain industries. That's how you escape these local optimum of the subscription plan or other things like that. When I do these, 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 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. 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.

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