0:00
I can't help but wonder about the sort of grand game that is a foot here.
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0:02
When you really step back and think about like what is happening right now, like what is the game?
0:07
What is going on here right now?
0:10
Like if you had to sum it up, the thing you're in the middle of.
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>> You're going up against the biggest players in the world.
0:15
The window to do it is actually on the order of months.
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The compute required to it is is overs this year alone.
0:22
And you have no distribution advantage, but you have this massively growing viral product. What do you do?
0:30
>> This is probably the most exciting software race ever >> and the outcome is like trillions of dollars.
0:49
No, I know this is the first time that you're talking about the business in this long form like this.
0:52
I'm incredibly excited to ask you all about it.
0:54
It seems like we're in a moment with personal agents that is very similar and arguably probably bigger than what we saw with code generation a year or so ago.
1:04
Maybe frame this up for us to begin like how are you thinking about the impact that of course your product but these agents are going to have on the world.
1:12
Why is this the area that you've chosen to dedicate yourself to completely?
1:18
>> I think out of this will come a new way that that most people on the planet interact with technology broadly. I run Instinct.
1:25
Um, it's a new company that I've started uh about about a year ago.
1:30
So, it's it's still a new new company.
1:33
And we're building a personal assistant.
1:35
I'm not going to spice it up because it's really just a personal assistant.
1:39
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.
1:45
Like it works in the way that I would say we all like we meaning I'm also a user.
1:52
we all have really been waiting for AI to to act for us.
1:58
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 um 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 you know from now you guys will all get it.
2:17
This is a very different moment of of building product because you and I we all already have this idea of what AI should act like.
2:26
We've already had that idea since 2023 when we all started to brainstorm when we started to use chat GBT for the first time.
2:32
You know that that agent that is able to help you with uh effectively anything in your everyday life whether it's something new and creative that that you want to do whether it's something that you traditionally spend you know several hours on and and it takes a long time to to develop.
2:46
It's just everyday intelligence.
2:47
It's meant to to be with you um to act with you.
2:49
It's meant to feel like a very uh simple interface.
2:52
So when I mean simple interface, what I mean is um we actually don't even have an application.
2:58
Like this is not a new app. This is not a new tool. It's a new experience.
3:02
So you know it has a phone and a computer. So you can text it. You can call it.
3:05
It can actually call you too.
3:07
So uh I don't know if you've experienced this yet. >> I have. >> Oh, you have?
3:11
I think it's only called me about three times so far in the in the several months that that I've been using it. It's funny.
3:16
If there's something genuinely pressing and has a, you know, a deadline, it will call you and it'll call in and it'll say, "I don't want to to bother you too much, but but this this you need to sign this document by by 3 p. m.
3:28
and and it's 2:55 right now. Can you please do that? It's in your inbox.
3:32
I can, you know, I can even send you another email to push it up to the top, right?"
3:35
So, it's very, you know, it's socially intelligent and and very socially aware. You can email it.
3:39
It has its own email address.
3:40
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.
3:52
I think it should have the social intelligence and awareness to be able to act with you just like we do with other people.
3:58
It's really meant to be the the 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.
4:10
Tell us the couple craziest stories that come to mind for what people just things that have happened because of instinct.
4:16
I asked this question because you're not programming to do any one thing.
4:19
You're programming with a phone and the computer to be able to do anything.
4:21
The US Open example, I think, is one everyone's familiar with.
4:26
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 uh and brought it back to them, which is kind of crazy.
4:36
What are your favorite couple examples of just wild things that have happened because of Instinct?
4:39
for those that like online shopping.
4:41
There's actually a group of of people that are sharing this and and and making this a more recurring use case, which is um scanning every item or every piece of clothing in their wardrobe.
4:52
So, they'll go in their wardrobe and scan every single item, you know, every every top and bottom and sock and you know, whatever.
4:57
um shoes and and then they would scan themselves too, like their their face and their body and their proportions and 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.
5:10
So every week with their existing wardrobe um you know what shoes to wear, what what um uh you know what top to wear with this certain thing and and this certain version of it and then it would it would not send it as here are the items you should wear like a bullet point list but it would be them wearing it and showing like this is what what today will look like.
5:32
But not only that, it's also with with shopping too.
5:33
So they'll take those same capabilities but then say go shop on the internet.
5:37
They come up with thousands of outfits in so many different places like this one.
5:40
Uh here are the pieces from the top to bottom and and you know and then and then they can just say order.
5:46
So it'll come in with a thousand different options and then they'll scan.
5:49
You know, keep in mind they're looking at themselves wearing wearing the clothing, right?
5:52
And then they'll they'll be able to point to like that one I really want.
5:55
Can you send that to my house?
5:57
And then not only that, but they'll say every day can you actually just come up with like three creative uh new outfits from head to toe and then send those to me.
6:04
And then they're able to to with a click of a button actually just uh you know get get that new outfit.
6:09
that new outfit. a lot of like goal oriented sort of 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 then it's actively working with them to be able to s to to do that or um users connect like their bank accounts to to
6:25
instinct and and then it can uh scan over all the transactions and subscriptions that they've had and then surface that to to the the user and say like do you really you know actually use this and then they're like oh no I didn't even know that >> and then it can go in the email and unsubscribe from it. Yes. Yes. It can go Yes. Yes. It can go end to end.
6:40
You you know these these popular uh consumer um like fintech products where 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.
6:49
So it go into the site sign in if it's there's some um sort of like confirmation that goes to their email or it has access to the email.
6:56
So they use that and they sign in.
6:57
They go to the very end they cancel the subscription and then it just sends back the number of what it saved you.
7:03
Like hey by the way you're you're saving $2,000 this month because of these things.
7:06
Man, any product that's dependent on consumer laziness or inertia is toast, huh? Like toast. >> Yes. >> That's good. Good for the consumer.
7:16
>> Can you tell us about the instinctto instinct network? >> Oh, yes.
7:20
>> In the future of agents talking to each other, >> there are um more practical scenarios where that is something new that I think will be uh you know transform the way that that certain people act in certain ways.
7:30
I think it's only been around for for a week or so or I guess 10 days.
7:34
Honestly, the purpose of this is not to think about like a new new feature to build, but more about very busy working professionals.
7:39
You know, they're taking meetings all day long and and they're they're constantly meeting with like new people and and existing people.
7:44
You know, the process of getting a meeting on the calendar, you know, it's just so so um so laborious.
7:49
You know, you text like, "Hey, you want to meet at this time?"
7:53
And then they say, "No, that doesn't work."
7:54
Like, "But these times work."
7:56
And you say, "Oh, but I'm traveling, so maybe this time works and I'll be in this time zone, though."
7:59
And there's just so much back and forth there.
8:02
However, if it was possible for, you know, the two users who were using Instinct probably, you know, also like brainstorming these times that they're available with Instinct anyways on the other on two ends are able to just communicate directly like, hey, the goal is just to find the time, right?
8:14
We don't need to play this back and forth game and nobody's really playing games here.
8:18
We're just trying to find time.
8:19
That's been a a very canonical use case actually.
8:22
I think the the um way that you can find time on a calendar now is just so different where you just say your intention.
8:28
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.
8:33
It will then coordinate with with the other person's instinct to be able to find like when time is available and not and then eventually put something on the calendar.
8:40
I think the key unlock here we called it a trusted person network.
8:43
And the key uh is that it it you should only be connected with your trusted people.
8:48
connected with your trusted people. And there are some interesting social dynamics that are coming out into play um that that um that I've been that I've been learning about where you know it's designed such that you only bring in
8:59
people who are trusted trusted people who are not going to maliciously try to you know find out what your your calendar is what or what's in your email but also not only that um we provide all the controls to be able to give different levels of access to different people. So, you know, a lot of um
9:14
So, you know, a lot of um spouses actually coordinate their instincts because they can generally just share everything.
9:21
>> So, that might just be, hey, this this is my spouse.
9:23
Um uh just share any any anything with them, right?
9:25
Maybe with a with certain colleagues, right?
9:27
It's hey, my work calendar is available.
9:29
Um 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.
9:40
When you think about this, there's almost like these network effects that that are built through these like nodes in the network with these different edges with different weights too, right?
9:48
It's not like a friend graph where you're just saying like I'm connected to you and that's it, right?
9:52
>> It's it's I'm connect I'm connected to you, I trust you.
9:54
I have also um you know configured it in this way such that there's varying levels of access.
9:58
So it's this interesting um like network effect almost almost being created and different social dynamics that are being um also explored and created as well.
10:07
There are some interesting cases I've learned about where if if somebody violates your um whatever your trust within the network, there's an implication on the on that relationship itself, right?
10:17
So, so let's say if you and I connected, right?
10:18
Um and then I said like, "Hey, Patrick, I you know, I trust you.
10:22
Let's let's connect on the platform so that it's easier for the next, you know, maybe the next time to put time on the calendar."
10:27
And then you use that and you you then start digging for certain data in a certain area.
10:32
First of all, maybe I only gave you calendar access, right?
10:34
But you're digging for data in a certain area.
10:35
Then my instinct text me like, "Hey, by the way, Patrick's like looking for this type of information."
10:40
Now there's kind of like almost like a trust broken um you know, between the two of us.
10:43
All of these little like sort of um social dynamics that come into play.
10:47
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.
10:57
Um, but then also use some of the existing rules in society to to be able to enforce both rules in terms of of of social uh cultural norms and and also of you know technical limitations in terms of what is visible and not visible.
11:11
>> We're really going to see just like an entirely new order, aren't we?
11:13
It's going to be fascinating.
11:15
The number of things I can think of, let's just take, you know, with my wife or something.
11:21
This would make life so much easier in so many different ways so quickly.
11:23
Even little things like, you know, you were trying to find this house earlier, like if I could just say to my instinct, hey, is no one nearby? Like, where where is he?
11:32
And you give me a one day permission or something like this.
11:34
There's just so many ways to imagine it being useful. It's pretty wild.
11:37
With the trusted network, we find a lot of very interesting cases because or or example use cases that are shared because it is the one part about the platform that is um 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.
11:55
For example, I I heard the other day of you know when when you're scheduling plans with friends or with like a spouse or something like that, it's always an active act, right?
12:01
It's like, okay, um, every Thursday maybe I'll like think about something on like the Saturday night about what I should do.
12:09
And and so it's always this act of act and then you like text the group chat like, hey, do you want to do this?
12:13
And then always somebody's like not not willing to do it and then eventually like falls apart, right?
12:16
And that happens like every time.
12:17
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.
12:24
There's like a friend group that put in um every week just brainstorm something creative that that is interesting that we all like and actually just make it a different experience every week.
12:33
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 tastes cuz all their Spotify history connected and all, you know, that same friend group that they had um it was like a a group of like six.
12:51
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, we'll pick you up in five minutes from here."
13:02
And I found the optimal route to go and pick up all the people and now they're all just sharing like one Uber.
13:06
So, it's actually like very economically friendly.
13:08
There's like all these random examples there of people discovering like new use cases when you can finally remove the barriers of of a lot of the the the wrote um social communication here and just make it um like remove all of the logistical burden.
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15:04
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.
15:17
They can call you just like dealing with a person and that's it.
15:19
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.
15:30
Code has been incredibly exciting to watch.
15:32
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.
15:40
It's a relatively small sect of people that have made code historically.
15:44
Maybe now it's going to be way more, but this just seems like a different new market, new paradigm.
15:48
How do you think this will start to reorder the world, the internet, commerce, etc.
15:56
What's the future of interfaces, I guess, is another way of saying it.
15:59
>> I'll break this down in in 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.
16:07
I I I I do think that in the coming years, I think the internet's going to be going to be rewritten.
16:13
I think that the way that that that most people on on the planet interact with with software is is going to be very very different.
16:19
To break it down though, I think in the in the short and medium term, famously maybe reservations uh is one where um you know like booking a reservation, right?
16:30
So historically, how is that done?
16:31
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?
16:41
And then if they don't get it, they're just too late and it's first come first serve.
16:46
But then now when you have an agent, you can theoretically just have the agent check every 5 seconds.
16:50
You know, not just across that that one restaurant that you really care about that's your favorite restaurant you can't get in.
16:56
Sure, that's that's one case, right?
16:56
But what if it's doing that across every site in the world for every restaurant in the world in every major city, right?
17:03
And now you can see how how the agent is able to to exploit just something simple like like restaurant reservations.
17:08
So if I go into that a little bit deeper, we have some exciting partnerships to be released in 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?
17:26
So if you take restaurant reservations from from scratch, from the users end, they want the reservation for the significant life event that they might have.
17:34
It's a birthday, it's an anniversary, it's a you know, a friend coming in from out of town.
17:37
And on the restaurant end, they just want they want interesting people.
17:41
They want special occasions.
17:42
You know, they want to cater to those rather than the, you know, maybe the local who keep, you know, keeps taking up a table once a night and and um and there's no sort of special event there.
17:51
And traditionally, because of the way that the internet has worked, at least for reservations, uh it's been first come first serve.
17:57
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.
18:03
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
18:19
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 you know 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
18:35
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 reserv 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.
18:55
So I don't mean to go so deep on on restaurant reservations.
18:57
I just mean that's just one example of a traditional model that is changing.
19:02
I think the same case with with um a lot of the major travel agencies.
19:07
Honestly, 50% of our of of transaction volume that goes through that goes through our platform is um due due to travel.
19:16
Honestly, we're still running like an invite only program and 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.
19:26
on a very small user base.
19:28
On a very small user base, there's there's already over a billion dollars a year transacting.
19:31
50% of that is travel alone.
19:33
Travel agencies that that we might all use today or um we meaning the the people who who are not on Instinct um yet use today to book, you know, hotels or or flights or other things like that.
19:45
Well, what is the benefit of of that interface, right?
19:48
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.
20:03
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.
20:14
Um, hey, I need to be in in New York tonight.
20:17
This is immediate and that's it, right?
20:19
Well, what does that entail?
20:21
That that means that, you know, first, where is the user right now, right?
20:24
Um, maybe you're in San Francisco, maybe you're in LA, you're you're somewhere.
20:26
Instinct can, you know, if you would want it, it can see your location.
20:30
So, it'll say, "Okay, you're in San Francisco.
20:31
You need to be in New York.
20:33
Let me first find all the options, right?"
20:35
Um, but not only that, all of the nuance, too.
20:37
What's the person's airline, preferred airline that they like to fly at?
20:40
Uh, what's the preferred seat type, right?
20:41
And what class do you want to sit in?
20:43
Do you want to be in an aisle seat or, you know, window seat or the middle seat, you know, etc.
20:48
What food options do you want to be delivered to you as well?
20:50
What credit card would you like to use? Okay. And then it books that. That's the flight.
20:55
Then then it moves on to the hotel. >> Yeah.
20:57
Presumably all your it learns about you constantly.
20:58
So your preferences are stored.
21:01
>> That is the nice thing.
21:01
If you tell it one thing, um, you know, I prefer this, this is my style. This is what I like.
21:07
Um, this is where I like to stay.
21:07
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.
21:20
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.
21:27
So things just become very easy as you start to give it more preferences over time.
21:32
So anyways, just to close out this example, you know, it'll find the ideal hotel.
21:36
Maybe you've already stayed there, you know, the last seven times.
21:39
And so it's very easy in that way.
21:39
It'll book it end to end.
21:41
Line it up with your calendar.
21:43
So it'll put the flight, you know, the flight in the 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.
21:53
Just take a step back, you know, cuz I talked so much about what this what what is happening under the hood.
21:58
The user really just recorded a voice recording saying, "I need to be in New York tonight, right?
22:03
And everything else is solved."
22:05
So, so that's what I mean when I say that meet the users where they are.
22:08
Where is the delightful experience?
22:10
Well, this is a new delightful experience that I believe is going to transform even the travel agency alone.
22:14
And so for these businesses that are, you know, traditionally um, 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?
22:26
And I'm not saying that we're in the business of trying to disrupt those business businesses.
22:30
I I think they do provide quite a bit of value from the data that they've uh uh you know collected over time and the and the the networks that they have.
22:37
It'll be a collaboration over the next uh year, couple years to be able to redefine what that industry acts like.
22:43
>> What has it been like getting people and learning what it takes to get people to trust their agent, their thing?
22:46
I would love to go fairly deep here.
22:49
We were talking about this um 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.
23:02
I'd love you to talk about the trade-off between privacy and effectiveness of these agents.
23:06
Obviously like the more context, the more passwords, the more everything you give it, the more it can do.
23:11
And I think people are constantly running that trade-off in their head when they're interfacing with the thing. Talk about that.
23:19
talk about trust, what you've learned so far.
23:21
>> There's an interesting um 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 um you know uh sympathetic to to your situation that it can be, the the more that it has to just act and and be more useful to you, right?
23:38
What we find in the data is actually that it takes actually several weeks to build trust.
23:42
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.
23:50
They should always be in control of their data.
23:52
They should share uh data with with instinct at the rate at which they feel comfortable with, right?
23:58
And if they want to take it back, they can certainly take it back.
23:59
And what we find is over several weeks um I believe I was looking at the numbers the other day um 3 weeks in, there's a 40% chance that the user has shared a personal credit card with Instinct.
24:11
That's 40% of the user base.
24:11
That's including you know some proportion of that user base probably turned in that moment too right or at least turned before that point.
24:18
So 40% of the user base the the reason why I'm sharing this is because um 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.
24:32
So 40% of the user base 3 weeks in are sharing a credit card.
24:36
Well, there there's something there, right? There's something there. No pun intended.
24:39
It's like it's the it's like instinctual to to go to it and and and you know, with whatever you need.
24:44
And so through that process over the first I I guess 3 weeks, um the user learns to build trust.
24:50
And then from there, it's just a snowballing effect.
24:52
We actually find that when when users connect at least one piece of sensitive information to to Instinct and and really trust Instinct, there's like an 80% retention rate.
25:01
80% if you share one piece of information.
25:05
>> Crazy for a consumer technology. Yeah.
25:07
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 AI 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 are really low or close to zero.
25:34
there's like a way to break this problem down into into like two main parts.
25:37
One is just um the storage of sensitive information.
25:40
There are many other businesses, there are many other products that that also deal with this problem of you know they have accesses sensitive information and what are they doing proactively to to make sure that that is you know isolated and and locked down and 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 that we need to be aware of.
25:58
The first case is this is a tractable problem.
26:01
It's just very hard work and and attention and care that you need to put into to making sure you know uh a sensitive data uh shared is is you know is is safe and and that the user is in uh full control over that data.
26:11
uh full control over that data. There's that second category um which I'll I'll I'll spend more time um 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 3 weeks 40% of the user base um is giving instinct
26:27
access to a credit card autonomously right to to be able to purchase um you know theoretically anywhere I don't know the numbers on on email and what proportion of users uh uh connecting email but you know you can imagine full access to to an email inbox and and to a calendar so there's a lot of service
26:42
area here there are systems that we've put in place that are detached from the from instinct the the agent architecture architecture itself that um 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 um any piece of content any piece of text
27:00
anything any form of media that comes in that might be consumed by instinct goes through what we call these firewalls which can um intercept that can reject that can you um block malicious pieces of content coming in and you know um hitting instinct and you know trying to convince you know instinct to do uh do something. There is also for every
27:20
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 um uh you know approve or disapprove of what might happen next before it takes the action.
27:38
I mean, those are just two two pieces put in place, but there's just so much more.
27:42
There's 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.
27:51
>> There's I have this question around um I don't have a better word than alignment and I know alignment is a very loaded word in AI.
27:56
I don't mean humanity scale alignment.
28:00
I mean an agent aligned with me personally.
28:02
If I think about other agents I've hired, like employees, I pay them money and therefore I trust them to have my interest at heart.
28:09
It won't be perfect, but they don't have some other alternative incentive stream that guides their behavior.
28:15
They're guided by their employment.
28:17
How do you think about the business model visav alignment?
28:19
Like you could well you walk us through how how you've thought about it, but many approaches will be taken, some will be paid, some will be free.
28:27
The free ones will monetize in different ways.
28:29
Can you walk us through this like decision tree of what the business model is or will be and and how you arrived at that as the ideal conclusion for the agent?
28:39
>> We don't want instinct to influence the user's behavior in a way that is not aligned with what the user wants.
28:43
That sounds very good on the surface level, but I I want to um call out how important that is because imagine a world in which instinct is generally smarter than the user.
28:55
I'm talking uh more socially intelligent, more socially aware um uh like textbooks uh smarter as well, right?
29:04
I think it would be a very dangerous world if if instinct were influencing the users um you know behavior to purchase something that they don't want to purchase or to subscribe to something that they don't want, right?
29:16
And using its you know its intelligence to be able to convince the Yeah.
29:20
So I I think that um you know you look at most of the major consumer businesses today whose you know are able to influence users behavior against what they might want to do.
29:29
they might want to do. you know, I'm I'm talking the the major platforms whether that's that's um uh Google or or Tik Tok or or Instagram or um or Snapchat or or so many others where you have this platform and and users you know it it's free for the users but then there's so
29:45
many instances in which you know paid ads are are pushed to the user and they try to convince the user to then purchase and you know by the very nature that they do purchase it now becomes this game of these brands paying to to you know convince you know users to to purchase items that they may or may not want. >> This is the idea that if you're not
30:00
>> This is the idea that if you're not paying, you're the product. >> Exactly. Exactly.
30:02
As a programmer, as a technologist, I just I don't want to build that that reality.
30:07
I I think that that is a very I think that's a very dangerous dangerous reality.
30:11
And so um we uh instinct should um should act on behalf of what the user wants.
30:18
We take this very seriously when when we're building product when we're when we're um uh through the various research projects that we have um which are um instinct is not unlike any other AI product instinct is not a task accomplisher.
30:32
So what I mean by that is you know with most other AI products you write a prompt and then it accomp you know it does the task and then it tells you what happened right that seems good in in theory but what happens is that if the user is now asking for something you know that is might not be well-intentioned well the if you have a task accomplisher it's just going to take the you know it's just going to do that and listen to the user.
30:53
Instinct follows um higher level um uh uh objectives.
30:58
So instinct will follow you know uh learn to build trust with the user.
31:03
Learn to make the user you know genuinely feel safer with you.
31:05
Learn to watch over the user and have their back when when you know things might might be dropped or or other things like that.
31:14
And when the user asks it to do something if it is well-intentioned and well meaning one way to communicate you know safety and and and and trust is to just to do the task.
31:21
And so so we end up just doing a supererset of of of what most other AI products are able to do.
31:28
But I think focusing on higher level objectives is is is very important here because it enables instinct to be more robust to these edge cases.
31:33
So we don't want to influence users behavior in a way that is not aligned with what the user truly wants.
31:38
Even if you look at the business model side of this too, there's over a billion dollars uh flowing through the platform now every year and and you know we're just we're just getting started and and uh honestly we're growing at 10% day over day.
31:48
So you know you imagine the transaction volume is also compounding at 10% day over day, right?
31:54
So, so that's not just a billion dollars flowing to the platform now. That's that's uh 1.
31:57
1 tomorrow and then that's like 1.
32:00
2 something the next day and 1.
32:02
3 something the next day, right?
32:04
the next day, right? It's still very early but when I see transaction volume that is so high that that flows through the platform what I see is very basic case you know it's similar to like an Apple pay or it's similar to like an MX or um you know any other platform that provides you know distribution to underlying services and a great user
32:22
experience for the Apple Pay is a great experience right you can go anywhere and you can you know scan your card and the user doesn't have to pay for it right the the the user is getting a free great experience and um and the merchants on the other end who are benefiting from the business are um paying to be a part of that platform. So I see a blanket
32:37
So I see a blanket transaction um take rate being being uh enforced across the platform which is just us exchanging you know distribution for for um uh being able to you know um serve products for on behalf of merchants.
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34:19
Can you say a little bit more about how that runs into the existing world?
34:23
So, I can imagine the layers being uh you could be a card issuer.
34:25
Um you could be something like Stripe, you could be Visa Mastercard.
34:30
You know, there 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.
34:39
And those are some amazing businesses uh to be sure.
34:42
How do you think about whi which of those are partners?
34:44
Which of those are potential things you would displace like how does that vision of a small take rate on the transaction volume on instinct because it's a free product.
34:53
How does that slot into the existing world do you think?
34:57
>> Just to put that into context, those there's a very great businesses and there's and there's so many people along the you know you make one digital transaction there like 40 people along the line that that make money on that.
35:06
And just to take a step back, um those 40 people making money at each line of the stack are really sharing what 2 and a half% 2% it depends on where the transactions coming from.
35:15
So it's a very actually small piece of the pie.
35:17
And um we're not primarily interested in whatever like doing what MX does best and and have the network to do or what uh even even like what what Stripe does uh on the internet or or you know some of the underlying uh payment infrastructure do because it's it's such a small piece of the pie and I think that they're providing real value.
35:34
Where I see the majority of the value just like thinking on the business side is you know if you look at most of the other um you know major platforms in the world and what take rates that they're able to achieve by you know again it's free for the user.
35:47
It's a it's a great free experience for the user and the merchant, you know, is now recognizing the distribution source.
35:52
You have Shopify that I believe is like between two two and a half and 3% um that are providing their services and and taking, you know, some take rate from those those those businesses.
36:01
Um you know uh I'm not sure where Stripe is.
36:04
I think it's it's it's u maybe on the lower end of that.
36:08
Um and then you have Amazon that has a great platform and taking upwards of 10%. Right?
36:11
And then of course the premiere you have you have Apple where you make any inapp purchase which is 30%. Right?
36:16
So I'm not saying that we're going to be 30%.
36:18
I think it's very unrealistic for a lot of businesses.
36:21
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.
36:29
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.
36:34
It it's a free great experience for the service that we're providing to all of the underlying providers.
36:41
I'm not focused on that on that two you know finding like 30 bips on the 2.
36:43
5 with some partnership with some payment provider.
36:48
I'm looking at the you know can we provide so much value that we're on the upper end scale of this.
36:52
The reason why I think that this is possible is very practically you know 50% of the um transaction volume flowing through the platform is is travel alone.
37:00
And you know we all know the the travel industry and and and some of the rates that are that we've kind of >> yeah the OTAA rates are high.
37:07
Yeah >> it's very high for flights.
37:08
you know, maybe it's on the lower scale, but but you you know, how many singledigit percentages can you can you take off of a flight?
37:15
Or for hotels, you know, some of these boutique hotels, you know, they're they're offering to pay up to upwards of 30% for every, you know, transaction that that that you're able to deliver for them.
37:23
And I'm not saying again we're going to be at 30%, but you can see the range.
37:27
These are existing, you know, business models that that that we can, you know, bootstrap off of in the early days.
37:33
But then what it would what would it be like to take that and and extend it to effectively every major industry?
37:39
This is only um this is only the case.
37:41
We only have the the um ability to do this.
37:44
If it is true that most digital behavior then moves to these new types of interfaces, which is well again like no interface, right?
37:52
But um it is only the case if there's significant distribution power.
37:56
So I think it's actually a quite intellectual um or interesting intellectual um uh question here about how this evolves over time.
38:04
It >> 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.
38:13
You've got all these established players with tremendous ve vested interests and relationship with customers that this could both instinct and other agents could really disrupt in a major way.
38:25
What are you thinking about that?
38:26
Like how do you interface with the other great services out there? I'll pick a random one.
38:30
You know, I use Uber Eats a lot.
38:32
Like I order from Uber Eats all the time.
38:33
It's kind of a pain in the ass to click through the thing.
38:35
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.
38:43
like that there's nothing else and that it's got its computer and it goes on to Uber Eatats and it orders or whatever.
38:48
At what point does Uber Eats not like that anymore?
38:50
At what point do these great businesses that have been built up start to be adversarial against agents, do you think?
38:57
Like what what do you think are the most likely sources of conflict and reconciliation?
39:00
It's going to be really interesting to watch.
39:02
So, so I I'm serious when I say I mean you're you're alluding to this too that that I think most digital services or industries are going to be not disrupted but just changed and transformed.
39:12
but just changed and transformed. Um and so I was running through an exercise the other day of pulling um effectively like every digital service or business or application from you know various different verticals and and industries and sort of plotting it along the line of saying what proportion is like the
39:29
user's attention you know experience on the product as um you know proportion of revenue and then what what proportion of it is delivering the underlying service meaning if the user didn't use the app how what proportion of that transaction would be you know or or what portion of their revenue is is due to the underlying um you know good being provided or or service being provided. Um and so I think that your question is
39:49
Um and so I think that your question is of that upper end of the scale where where let's say the majority or some significant amount of of of revenue is is is due to uh attention on the application or advertisement or things like that.
40:01
So yes, that's that's the that's that's Uber.
40:03
I actually don't know what what Uber's number is.
40:04
That's um a lot of the the restaurant um or the food delivery services that is the um travel agencies that's that's um you know even Amazon Amazon themselves with with you know the upselling that they do on on their platform.
40:18
Okay, there's one simple way to look at this which is that okay well it's 70% ads 30% you know good and so therefore you're going to slash the 70% and they're going to be a 30% business moving forward.
40:28
There's another way to look at it which is I would you know take any business.
40:32
Let's take let's take um Uber Eats or or Door Dash uh you know as an example.
40:37
They don't know the numbers.
40:38
I don't I don't know the numbers but they don't know the numbers of as they reduce the number of clicks um you know needed to check out to order food to your house or or to order an Uber as they reduce that time to check out uh um the uh transaction volume uh increases because it's it's reduced friction to get you know the same underlying underlying good.
40:57
And um you know we're taking something like instinct and and making that friction to do anything almost zero.
41:04
It is literally zero in the case that there is proactive uh behavior for Uber.
41:09
Let's say for ride sharing, right?
41:11
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.
41:20
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 5 minutes I need to order this Uber because I need to be in this place in 45 minutes and there might be traffic.
41:33
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.
41:39
Instead, what if it was just, you know, proactive behavior?
41:41
A car will always be lined up and you will never be late because it's going to calculate traffic.
41:46
It's going to find these things.
41:46
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 lift or or any other ride share business, what would it be like to have productivity now make the friction to to, you know, experience that that or have access to that good or service to be nearly zero?
42:06
I think that that will result in that 30% looking a lot a lot bigger.
42:11
You know, you talk uh food delivery service.
42:13
Maybe you're coming home late um off of an airplane and and you need to be at your house and and you haven't eaten yet and it just text you and it says, you know, are you hungry?
42:21
Do you want the same thing that ordered yesterday or 5 days ago?
42:23
I can send it to your house if you'd really like it.
42:25
I know you're you know because it ordered the Uber, too.
42:28
I know you're in the Uber and you'll get here at this time.
42:29
And then the user just says, "Yeah, go that. That's great." Um or or thank you. Yeah, please order that.
42:35
So with very little friction now it's a you know what will that do to the total um transaction volume where the or the um amount of times that a user interacts with the business I actually think it'll go up.
42:47
So it's this interesting game.
42:47
So it's this interesting game. I think it's this interesting transition period between users spending a lot of time on apps like painfully spending a lot of time on apps and that being a monetizable surface because that's where the user's attention is to the user actually interacting with the business even more which is you know
43:05
counterintuitive actually interacting with the business more because the friction to do so is actually just much less so I think it'll be this interesting game all these various industries are going to you know move in a different way and and we hope on our end I I think that the way to approach any big change like this is is is um not to come in hot. You know, we're we're
43:22
You know, we're we're still, you know, we're a new company.
43:25
We're we're just getting started.
43:25
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 uh uh your business looks like.
43:36
You know, you guys certainly know what your business looks like.
43:38
This is how users on instinct are interacting with your business now already.
43:42
What can we do in collaboration to make that a better experience for for both sides where it makes sense for your business, it makes sense for for our business and and certainly it m it's just a much better experience for the end user.
43:54
>> That is something that we're exploring and that we're learning um across so many different industries right now.
43:57
If you think about the things that traditional companies could be doing now to prepare themselves for an agent-rich world, let's just pretend, you know, half of Americans or something have an agent that's very doing all the stuff you just described, which sounds incredible and magical and very democratizing.
44:12
I think that's like maybe something to highlight is this is going to bring to everyone capabilities that have been rare or expensive.
44:18
And I think that's just like a really cool feature of agents in general.
44:23
But we can come back to that.
44:25
What kinds of businesses are going to thrive in that world?
44:27
Like what should businesses think about doing to prepare for that world to be successful in it do you think?
44:35
>> I think it comes again back to that breakdown.
44:37
That's why I was doing that that um that exercise the other day which is just um uh you know where is your revenue coming from?
44:43
What proportion of that is the user spending time in your application?
44:46
What percent what proportion of that is the user you know uh having access to the underlying service?
44:51
service? And it's very just very clear if if if your business uh benefits from more transaction volume not at the cost or with even at the cost of less time on the application then then you're going to be in a really great spot because
45:02
instinct is going to make it you know you know 100 times easier to do that and and if you're in a spot where nearly 100% of of of your revenue is due to the user's attention I think that you know even in a lot of cases against the will of the of the user and what they want to do. Um, and there's, you know, so so
45:17
Um, and there's, you know, so so many games that or or so many um I would say um like malicious like product building almost of trying to convince the user to uh you know against their will to use the application more.
45:29
You know, we're thinking about a lot of these um I would say a lot of these social media companies that are, you know, the user doesn't want they don't feel happy when they're on the app, right?
45:38
They they're um unwillingly giving their time to the app and they can't get off and they keep scrolling, right?
45:43
Um but it's because that underlying business is is benefiting from the user's attention.
45:46
It's almost like liberating for the user to be able to, you know, again, this is why it's so important for Instinct to act on behalf of what's best for the user because it's able to deliver experiences like this where you can actually liberate the user from from um, you know, being sucked into these, you know, these, you know, these scroll infinite scrolling moments um, like that.
46:05
I I would say any blanket advice is probably just like not well thought out.
46:08
I think it's a case by case basis and certainly different within different industries.
46:12
I would say very practically we're finding we're you know there are early partners with with um very innovative um uh you know CEOs or other executives that that are really thinking ahead.
46:22
They're really thinking ahead and and they're willing to be early partners.
46:25
Um, and what we're what we're discovering is is almost like a playbook for how every business, no matter where they exist along that risk curve, um, can kind of discover honestly what are the risks so that they have a little bit of data to be able to work with and then we can work together on on finding ways where we can land in a happier spot for for both sides.
46:41
One of those things is you don't have to go allin, right?
46:45
like you don't have to say let's just turn it on, you know, for let's just let's just go and and now you see like 70% of your your revenue going to zero and then now you're stuck in this odd place.
46:56
You can mitigate the risk, right?
46:59
you you can scale down the experiment.
47:00
experiment. they can you know run AB tests to figure out um okay if we enable this certain thing across you know uh 1% of users or something like that and and we find how they interact with the business and and honestly does the user like it more is it a more enjoyable experience uh for the for the brand side too does the the transaction volume go
47:18
up like does the willingness to you know buy the product or access the product itself there's a lot of you know work in product discovery too right there's a lot of times the user doesn't know they want to buy something but they don't they can't find it right and and So does that actually increase you know the the user being able to find exactly what they want. So I think doing scaled
47:34
So I think doing scaled experiments here is actually um a really great um playbook to run because you can scale the risk accordingly at the end of it.
47:43
You know you get the data you know it's proportional data so you don't have to run it across your entire user base and that's what we're finding is is really working uh so far.
47:49
Again it's still very early so so we're still discovering this uh in real time.
47:53
Before I ask more questions about the world reordering nature of 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.
48:05
I want to hear about what's been hard about building this the technology itself.
48:09
I want to hear about compute.
48:09
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.
48:16
And maybe that's different 5 years from now, but certainly in the moment when you're growing fast, this is a really important thing.
48:20
I'd love to hear your thoughts on that.
48:21
talk us through what it's been like to build instinct itself and the key key and hard things to do.
48:28
So maybe before we do that just to because I'm remembering all of our conversations, it would be helpful for you first to frame up what you want it to feel like and and why it's so important to you that it sort of has this distinctive quality and performance before we talk about then how you deliver those things.
48:45
Um, so maybe first just say a quick word on that like what what you want instinct to feel like as a product.
48:52
product. I could talk all day about about this because I think that is just so important and honestly as a product builder it's it's it's I I think a new muscle to flex and to build but really thinking beyond capabilities is is something I really want to push here which is I think over the last 3 years we've seen you know uh all these
49:10
different product launches and new products and saying AI can now do this or AI can now do that and did you know that it can do this thing because of this like small technical thing that that happened under the hood and you know I think the consumer is first like fatigued by by all this like they you know they don't know how to access it. Um and then second I think we're missing
49:24
Um and then second I think we're missing the point.
49:26
So so early on actually one principle that that um that we held was let's not focus on capability.
49:31
Let's only focus on understandability.
49:33
So how much does a user understand about what's happening?
49:38
How much what is their ability to predict what will happen when they ask this or when they do this or when they interacted with it in this way.
49:45
Honestly, I think that that is one of the major angles or or um factors that has led to um you know uh engagement numbers that are completely off the charts or the viral word of mouth growth that is happening at at at 10% a day. It's understandable.
49:57
It just feels um if I were to describe it for for lack of a better word, it should just feel it should just feel feel good in in some way, right?
50:06
In the way that it communicates to you, the the purpose of communicating or sending a text message is not just the meaning of the text itself, right?
50:12
text itself, right? It's it's down to underlying you know even what is the shape of the text message itself right and how will the user feel when they see that right if you see a big blob of text that requires the user to scroll a little bit to find you know what the next message is versus maybe you frontload some of the information so that the user really gets it in the
50:30
first 30% and then can optionally read the rest you know thinking about how uh the user might read or even you know like read patterns where the user I I don't know if you know about this >> the way that most people scan you know big chunks of text they might read you know 80% of the first line and then maybe like 50% of the next line and then and then it tapers off so it looks like a flag. That's a consideration that
50:48
That's a consideration that should be made.
50:49
Um if you know if instinct it's it's very it has the ability to think about things like this, right?
50:55
Okay, the user is going to you know spend most of their time reading the first two lines and then certainly the first part of each line too, right?
51:02
So how does it craft its message to to deliver in the lowest fatigue way or or with the least amount of cognitive load placed on onto the user?
51:09
So there's a there's a lot of consideration that's put into this in terms of product building that is there's quite a bit of work that we do on the infrastructure side to make you know make the make it fast and make it make it make it affordable to serve and but this is another area that I think is just so important and is going to be a differentiator.
51:26
>> How much of that is your personal and the team's taste versus them be it being the result of a quantitative type process like iterative quantitative process of okay we did ABC testing of all you know emoji reaction versus short versus long and this is the thing that is optimal like how much of it is an optimization exercise that's data driven versus your own sensibility and your team sensibility >> honestly it's just all of the above
51:52
because you know when you're thinking about building uh evals or you know evaluation or other testing frameworks to be able to test for these like very soft qualities or these actually very long-term qualities right two or three
52:03
weeks in does a user trust instinct right how do you measure that how do you run you know simulated evaluations to test if the user is going to feel trust in in in two or 3 weeks from now, right? And actually, a lot of it is is just
52:14
And actually, a lot of it is is just staged rollouts over time.
52:15
So, I might come in and and build a slightly different experience and then I'll release it to myself and I'll play around with it for for a little bit and see how I feel about it.
52:24
And, you know, I'm just like very opinionated about these types of things.
52:28
And then, um, you know, then if I feel comfortable with it, I'll I'll send it out to the team.
52:32
I'll say, "Hey, you guys should try this."
52:33
We'll see how they feel about it.
52:35
and then and then they'll send it out to, you know, our our, you know, smaller early access group and then they'll play around with it and see how see how it feels and then if we're confident they're if there's any tweaks that we need to make, we'll do that and then we'll eventually roll it out uh to the general public.
52:47
So, I think this is very important because I think that instinct is is quite capable and is one of the most capable product products out there.
52:54
But I'm not saying that over the next couple, you know, months or years that others are going to come and deliver the same, you know, seemingly same experience.
53:01
But I think that this this deep focus um and priority on how the user feels and how to make it the most enjoyable experience beyond you know the words that it's saying just the the the just the way that it feels is just so is just so important.
53:15
>> 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.
53:23
Obviously you've built an incredible product.
53:26
The feel of it like you said it's the worst it'll ever be.
53:29
How do you think about that challenge?
53:31
Like your speed of scaling, what your ambition is for how to get big really really quickly.
53:35
Do you think this is a winner take most take all market?
53:40
Like what will the market shape of of agents be?
53:41
I'm just really curious how you're thinking about okay, you've got this foothold, you're growing 10% every day.
53:47
You do that math, it gets really big really quickly.
53:49
You need a lot of compute. It's a free product.
53:51
Like there's all the It just You're a very chill guy.
53:54
It just seems like a stressful situation uh to be in facing down how big this could get as quickly as it could get.
54:00
Talk us through that manyheaded monster of a problem.
54:04
>> Well, I think you just described everything all in once in about 20 seconds there.
54:08
And and I think maybe if we think about um the growth story so far um just to describe like where we're coming from, we are uh I guess like famously or infamously uh serving an invite only um uh product which is honestly not meant to be an exclusive thing.
54:27
Um although some users are are are treating it like that but that's that's really not the intention.
54:31
Um the goal here is to be able to you know I'm ambitious.
54:36
So I want to scale this thing as fast as possible, but I but I also want to do it in a responsible way that enables us to, you know, 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.
54:48
The interesting thing both the benefit and and also the detachment is is well we we first started out this program.
54:54
We gave it to like 200 people.
54:55
It was like you know close friends and family members and and we just said like go try it out and then like the next day like say like five people came onto the platform because they just referred it to somebody.
55:05
Oh just to just to describe a little bit more um it's an invite only platform.
55:08
Um and every user um will have five invites to be able to get.
55:14
So just five five invites.
55:16
Um and so so we rolled it out 200 people.
55:20
Next day it was like 205 and then the next day it was like 210. So it's like okay cool.
55:24
Like you know a couple people are sharing it to like one person, right?
55:26
But then that just started to accelerate. It was very odd.
55:30
It was like um okay it was like not not 1% 2% then it started to be like 3% 4%.
55:34
And then once we hit uh you know a couple thousand users some people just started to share it online too just like natively share like you know some cool use case that they had with it.
55:42
And then that accelerated the growth.
55:43
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% day over day and just to call that out it is it's not that we're doing some sort of creative marketing event like every you know we spent $0 on marketing
55:58
so far it's not that we're doing something every single day to be able to support this this growth every day about 10% of the audience or 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
56:15
So I think there's something really very significant there when I talk about strength of word of mouth.
56:21
Um I I think this is it's honestly a little bit surprising.
56:24
It's it's one of the strongest uh cases of word of mouth growth of you know I I find all these stories of of people saying um hey actually like they'll ask me and they'll actually be ashamed.
56:35
They'll like email me and say like hey can I please get an invite?
56:37
I I I think I have a friend that has it but I don't know if I make it into his five friends. Right.
56:44
>> And then there are also people who are saying who are bragging like, "Oh, I got these like I got three invites left, right?"
56:49
And um uh I'm just like holding on to it right now.
56:52
So So there's so much happening of people that that want access to the to the product, but there's like these odd social games happening of people using their invites.
57:00
I I I was seeing the other day there were some invites that were selling on eBay, too.
57:03
I don't know if you saw this. It's like 300 bucks.
57:04
People were b buying these invites on on eBay.
57:06
And it's just to control the growth.
57:08
it's just to control the growth. So then you know the big question comes you know the thing that most people are asking right now is yeah I mean you you have um much bigger players that that are able to distribute to you know a billion or two billion people uh on the planet you know immediately um uh and maybe they
57:27
might not be compounding naturally as as fast but they have such a great topfunnel distribution um and then you have you have us you know um compounding at you know a very very fast clip every day but And um uh but you know we you know we don't own a major you know service that has you know two or three billion people and and able to distribute immediately that day. So it's
57:47
So it's this interesting question like where does the curve like line up and where's the inflection point and and um there's another problem that comes with this too which is that it's an interesting scaling problem.
57:58
scaling problem. This is what is I think the core of the problem that I I spent like 40% of my time uh uh just um worrying about which is it's not like the traditional other consumer products that grew very fast where it's you know to double the number of users on let's say Instagram or Facebook or something
58:14
it would be you know this many number of other requests going through the platform and like yes there's a scaling story there and it's certainly hard infrastructure work we we also have that to to be fair but what do you do when the underlying compute also needs to d you know 10% there every day. We've been
58:27
We've been doing this for for several several weeks now.
58:31
Um what does it mean when uh the amount of compute that you need access to is is is now doubling effectively every week.
58:38
Do we buy compute, you know, 2x 2x of what we have right now?
58:43
Uh well, we're going to consume that in a week, right? So then do you buy 5x?
58:46
Well, we're going to consume that in, you know, uh less than 3 weeks, right? Do you buy 10x?
58:50
So now it's like you're 10x leverage, right?
58:54
It's if you can even stomach what it's like to buy buy 10x ahead, but then you're going to consume that in in you know couple weeks from now, right?
59:00
So that is the hard problem.
59:02
It's it's thinking about how far ahead how far ahead do you buy.
59:05
It's going at a faster rate than claude code or or or codec or some of those other applications where they also had to you know reason about other similar exponential type of problems.
59:15
The other subtlety here is that it's not like a certain business where when you double the number of user users you can buy like 2x more resources in order to power it.
59:22
It's that the resource has a lead time of several months, right?
59:27
So, you can't just go out tomorrow and start, you know, buy compute because honestly, you get you get taxed like 3 or 4x what it is.
59:33
If you're wrong, you you're wrong by three or 4x.
59:39
>> But then now, so two or three months at at 10, let's say it slows down, right?
59:43
Let's say we don't actually do 10%, you know, for for a very long sustainable period.
59:47
Let's just say it's like 5 to 8%, right?
59:49
8%, right? But 5 to 8% compounding day over day for three four months which is the lead time to get you know bring compute online and that's even aggressive itself that's 100 million users right so so then do you buy compute for 100 million users so those are the types of questions I'm I'm wrestling with um which is just like if
1:00:07
you're wrong you're very wrong you get you get charged three or four >> what about if you zoom in on the individual user and the cost to serve them on a day per day basis like do you have a s 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
1:00:22
Do you have a sense of like that scale? What is that scale?
1:00:26
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 AB tests whether it's it's uh internal evaluations or it's um you
1:00:42
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 like frontier level uh uh intelligence we're
1:00:59
able to serve it's the same engagement rate the same um you know AB test performance it's the same internal evaluation performance but at a cost that is very very low um and is actually very affordable you know we're running this program every user has it uh has
1:01:15
has the product for free and um our goal is really to deliver this product um at an affordable at affordable I'm not going to commit to to free for a lifetime for now but that is And that is my personal goal to be able to deliver this product uh for free for everyone for a lifetime. It's just hard
1:01:30
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 uh you know from from some of the main providers you are taking a a blanket cost on a certain request and for all of the requests that might um you know uh uh be needed to power that product for that month.
1:01:49
But there's a lot of different work that's happening through productivity that is happening throughout the day that doesn't actually need to finish in hundreds of milliseconds.
1:01:58
It needs to finish in you know uh minutes or even hours.
1:02:02
There is a batch work that is consuming a lot of content that can be served with you know deployment shapes that are uh 3x 5x 8x more more efficient um on on on this uh with the same underlying compute.
1:02:15
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 survey at a very low cost.
1:02:36
>> How do you think about solving the bigger problem of how far ahead to buy?
1:02:40
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?
1:02:48
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 or some way of understanding just like how much new compute this will require.
1:02:59
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.
1:03:08
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
1:03:18
then it comes back to user and then asks for something else and then the user sends something again and 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
1:03:28
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
1:03:39
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 um be able to you know help help the user through those moments. So
1:03:47
So productivity I think is going to continue to to to expand over time.
1:03:53
There's this big buildout this big compute buildout um in the uh with the earlier break you know breakout products uh in the AI space um that are just scratching the surface of productivity or of background work. here.
1:04:04
Now we have something that is almost natively proactive.
1:04:08
It is is a smaller subset that is actually interactive, right?
1:04:11
So I I think that um the amount of compute that is going to be needed is going to be uh um honestly orders of magnitude more than what we than what we thought that we needed.
1:04:24
It's just with more productivity comes more um uh more care for the user, more time to think about certain things that could go wrong or not go wrong.
1:04:33
There's just so much that's happening under the hood.
1:04:34
You know, maybe Instinct wakes up at 6:00 a. m.
1:04:37
because it knows that you wake up at, you know, 7 a. m.
1:04:39
And then it goes and scans everything, make sure that that you know, everything's ready for the day for you.
1:04:45
And and um and then it realizes um hey, actually now is not a great time.
1:04:50
Like it should just go to sleep or do this one thing in the in the background and not not notify the user.
1:04:55
And then it realizes, oh, at 4 p. m.
1:04:57
there's something that's coming up.
1:04:58
There's value that could be provided.
1:04:59
Maybe the user doesn't even know how to interact with Instinct in that way.
1:05:01
And so, but Instinct thinks that it's a it's it's like well-meaning and it and it's something valuable to their user.
1:05:06
So, it might then just wake up at at 4 PM and then do the task and contact the user and then the user will you know could lean into it and and do that task.
1:05:14
You see how much work is going on in the background that is you know with uh you know I would say these these coding products you don't really have that much uh you know background or productivity work happening.
1:05:27
So um uh yeah I don't mean to quote a number here.
1:05:30
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.
1:05:42
>> What do you think of Muse?
1:05:42
What do you think of the product?
1:05:44
>> I think it's a great product.
1:05:44
Uh I was playing around with it uh for a little bit and I think it's it's interesting.
1:05:49
It's a different take, right?
1:05:49
Because um sure you can say some some of the the underlying architecture, you know, might be similar, but I think it's fundamentally different.
1:05:56
fundamentally different. I think that that instinct is meant to be a simple and and very easily accessible and um you know of the of the soft qualities that we were we were talking about earlier of you know really thinking from the user standpoint about what's what's
1:06:11
important and 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 uh I just spend very little
1:06:25
product. Um uh I just spend very little of my time thinking about uh competition and other thing other other players in the space because I think um you know you you you walk outside you go to the near nearby cafe and you think about how many people within that c cafe are are
1:06:41
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 or other cities and and um it it's certainly lesser of case. So, I think I think it's it's it's
1:06:55
So, I think I think it's it's it's still an open space.
1:06:58
It's still an exciting time, you know.
1:07:00
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.
1:07:05
Um so, u I'm just I'm just focused on building the best product experience.
1:07:11
>> What have been the blunders so far?
1:07:11
Like what have what's gone wrong?
1:07:12
What have you done about it?
1:07:14
I'm sure more things will go I mean this this is just going to be an explosion of emerging properties and mistakes and the end's going to be really high.
1:07:21
How do you think about things to guard against proactively, things to be reactive against?
1:07:27
Like, yeah, talk us through the the darker side of building this or the harder side of building this.
1:07:32
>> 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.
1:07:42
And um uh I would say this is the reason why we um well we ran their early this uh early access invite uh 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.
1:07:57
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.
1:08:11
Uh so yes, the the there's an early version of the product that that had some of these some of these qualities or or some of these mistakes and and uh we we addressed it.
1:08:18
We we we went above and beyond and and didn't just patch the problem.
1:08:22
We we build we built a different uh a different system to systematically solve uh these types of problems.
1:08:28
So um I think the key here is is again I I I said this earlier um the user should always be in control.
1:08:36
The user should always be in control of their data.
1:08:37
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 at in
1:08:49
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
1:09:02
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 hu I mean early in technology revolutions of the past there are these
1:09:17
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
1:09:33
I think it comes to um building uh security and safety and 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 and the way that you build product you know this is topical because anytime if you look in the past the last you know 20 30
1:09:50
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
1:10:07
this V track the last 20 30 years seeing some of that now um but also 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
1:10:23
to be able to get ahead of of 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 a language model to be uh you know hallucinating. Um so we put
1:10:37
Um so we put in place uh 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.
1:10:58
filter that's able to find, you know, hey, this proper noun was just generated out of the ner due to some sampling error in the underlying model.
1:11:05
And so it it's very easy in hindsight to be able to to capture these these uh you know, these types of mistakes.
1:11:11
And and these are hardened.
1:11:13
So So, you know, we have we have uh world-class security teams that are, you know, constantly working proactively to to um find harder and harder adversarial cases to to try to find edge cases here and there.
1:11:23
And it's becoming rarer and rarer over time.
1:11:25
One subtle part about building a platform like this is that it um it's getting better over time as we continue to do more adversarial testing as as we continue to be more creative about certain edge cases.
1:11:36
These models are just getting better and better over time towards being robust to these to these um uh types of attacks.
1:11:44
>> 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?
1:11:51
It's so interesting because it's not an application. It's not a device.
1:11:55
It's a It's an interaction through existing communication channels, WhatsApp and and iMessage, etc.
1:12:01
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?
1:12:10
>> You know, the product experience right now is very simple, very very simple.
1:12:14
Simplicity is is one key um uh that 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 um uh in the near in the near future, but it's it's I actually think that we're going to trend more
1:12:29
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 and send the message out uh and then look at what the response is after when it's done. Um we have a
1:12:42
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 of the messages that they send to instinct are primarily through voice where I I even have this like action button you know the action button on on your phone and
1:13:01
it's paired to like I can click on the action button and I can say like you know hey say say hi to you know Patrick in 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
1:13:15
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 discre uh discretion to know when you're addressing it and not addressing it where you could have let's say like an AirPod and you know not a
1:13:37
new type of AirPod just like an AirPod cuz it's good enough and um and it's just on and it's just on and you might be going on 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 your needs your review. Okay, I need to review that." Or um,
1:13:51
Okay, I need to review that."
1:13:51
Or um, "Hey, this news article just came in and and here's the here's the headline and here's the takeaway.
1:13:57
This new project was released and you should take a look at this."
1:14:01
And you're just like in your ear like, "Okay, got it. Got it. Put that on my calendar. That's 15 minutes."
1:14:05
Okay, yeah, that's not important.
1:14:05
So, go clear that part out.
1:14:06
Um, oh, this person needs my help.
1:14:09
Uh, I know the answer to that.
1:14:11
So, just tell them that it's this, right?
1:14:12
it's going to be much much easier over time.
1:14:14
So I I I think we'll see.
1:14:14
I think that there are long-term and short-term considerations here where I think in the long term I think that the interfaces become yeah again much much simpler.
1:14:24
But in the short and medium term uh you know maybe there are more expressive interfaces to be able to share you know you know we have a um like a files feature that enables instinct to be able to send you know effectively entire uh sites like full web applications to you know show just much more whether it's like a trip itinerary or I don't know like a wedding plan or something like that.
1:14:44
I don't know something something that just requires much more and more creativity and and more surface area.
1:14:48
Um it can generate those on the fly and be able to show that to you.
1:14:52
show that to you. And I think that there's something interesting there where you look at the last 20 years of of application building or 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
1:15:07
it's this long software development life cycle to be able to produce the application, ship it out to people and then and then you find like some feedback like hey I wish it looked like this and then then you take it and and you make the improvement and you ship out a new version, right? And this is on
1:15:17
And this is on order of like months, right?
1:15:18
Um 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 right like every time I needed something like is there an app that does that like I don't need I think that all of that collapses down in the future.
1:15:34
I think that all of software is going to collapse down into into um honestly a single very very easy to use interface.
1:15:40
Don't get don't get that um confused with with capability being limited.
1:15:44
I think capability is going to expand.
1:15:46
expand. What's the craziest thing you can imagine capabilities wise >> when we move away from more of these like daily tasks like I want to do this can you do it and and you know that friction is going to go down to zero I think that um it will start you know towards towards um pursuing higher level you know objectives that are aligned
1:16:04
with teaser where the user is able to describe not just um hey can you track this can you track this workout for me I did this and I and I performed here and this is how I did um but more about, hey, in in 3 or 4 months from now, can you can or over the next 3 or 4 months, can you work with me to make sure that I hit these certain goals? And actually, a
1:16:22
And actually, a lot of people are are starting to experience that that or are starting to discover that today of you know, you want to um you know, gain this much uh this this many pounds, you want to lose this many pounds, or you want to hit this certain mile time.
1:16:36
Being able to specify objectives and goals and then be able to work with it to then achieve uh those goals and objectives.
1:16:41
those goals and objectives. I see um small businesses uh being run now that are native to Instinct itself meaning the entire business is now run run on Instinct where the entire back office is now um uh completely functioning on on on top of on top of Instinct and even parts of it are are are fully autonomous too where um you know talk about highle
1:17:02
objectives it's in this certain area make sure that this inventory level doesn't drop below this and doesn't go above this and so now it's not it's not saying hey please order this >> static yeah it's, you know, pursue this higher level objective and use the the the tools and and devices that you have available to be able to accomplish that. So, I think that's I think that's a
1:17:19
So, I think that's I think that's a future and I'm not like, you know, there there are so many cases of objectives that you could, you know, state and have it pursue for an unbound number of amount of time that we could um brainstorm here.
1:17:32
But I think that's the meta level picture is it's it's the moving away from from you know individual use cases over to higher level objectives is going to be where um where I think um uh interaction will will progress.
1:17:47
>> Do you want it to have a personality that's distinctive for each person?
1:17:50
Like I'm thinking now of the movie her where there's this relationship that forms between this omnisient omniapable agent and the user.
1:17:59
What do you think about that aspect?
1:18:01
I I think of Instinct as this very like seamless, almost quiet, extremely capable, reliable thing, but not as having a cheeky personality or something.
1:18:11
How do you think about that component of of the product?
1:18:16
>> Well, well, you mentioned her, I guess, comically.
1:18:17
It it's um certainly um relationship building or anything uh in that area is is not uh uh is not something that that we want instinct to to to do or to pursue or to develop with users.
1:18:31
Um uh if I describe more about what it should um uh act like and feel like and and and represent within the person's life, um it's almost like that um socially aware uh operator that knows no matter what room that they're in what is the best for different people and and what is the you know best interaction pattern for and it learns that over time.
1:18:51
So, I think it's possibly one of the most customiz if you even call this an app, it's like one of the most customizable apps um ever because it's able to not just um you know, not just able to serve uh different versions of it, it's able to to evolve over time.
1:19:06
That's why we put so much care into like the software pieces, right?
1:19:07
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.
1:19:20
um it's going to learn those over time and and and just become easier and more delightful for the user to use.
1:19:25
So I think we're not trying to impose certain experiences uh onto users.
1:19:30
I think we want to solve this more from a higher level.
1:19:32
It's just ability to adapt to exactly what is the best communication style and and task execution style.
1:19:39
>> Why is it called instinct?
1:19:40
>> Instinct I liked as a name for for so many different reasons.
1:19:42
many different reasons. I I I think the main um 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 this thing that only takes the dirty work off your
1:19:56
plate and and I think it's this this new creative exciting you know competent actor that there's like mutual respect and trust and and they feel safe and and they trust that it has their back that it's intelligent that it's competent that it's socially aware to know how to act in certain situations and um it's it's a It's a bet. But I I like that
1:20:12
But I I like that instinct is not, you know, named like um I don't know someone's name or something like that to try to personify it into like a human.
1:20:20
It's more of I don't know.
1:20:22
I don't even know what an instinct is.
1:20:22
I kind of develop my feel for what it is and for what the brand is through just using it.
1:20:29
And again towards towards um really thinking about this this feeling of what it should be like.
1:20:33
I think that it's it's um it's a benefit that every user is able to come into it with a fresh slate.
1:20:39
There's no prior in their mind about what it looks like or what it's named or anything like that.
1:20:42
It's purely through the product experience itself.
1:20:46
>> Who are your enemies and allies?
1:20:46
Like I can imagine in WhatsApp or something you could get shut off.
1:20:51
That's a Facebook product and it's a key channel for you.
1:20:55
Um iMessage is an Apple control product.
1:20:57
Like who are your friends? Who are your enemies?
1:20:59
How do you think about some inevitable competitive realities here?
1:21:01
inevitable competitive realities here? I would focus less on like instinct is an iMessage app or instinct is a WhatsApp app or something like that and and more about just very grounded from first principles um what are the interfaces that users trust today that they're familiar with interacting with today and
1:21:19
how can we deliver the the experience of instinct through the channels that they already interact with every day >> and and just primarily thinking like we're we're not pinned to to iMessage actually more than 50% of our traffic doesn't actually run run on on iMessage itself, but certainly users that are comfortable with iMessage are are very familiar with it. I I think it's just
1:21:37
I I think it's just more about just thinking about what is uh what is most practical for the user and and we're going to shape shift as as as we see um towards just delivering again that that very simple um simple easily accessible um sort of like zero friction uh experience that it is today.
1:21:55
>> I know your latest round is something like a billion dollars at at roughly a $10 billion valuation.
1:21:59
some of the best investors in the world, Zoya, Benchmark, Kotu, uh, as the leaders of the round.
1:22:06
How do you think about the future capital needs of the business alongside this?
1:22:09
And how did you pick the partners that you picked?
1:22:11
>> I I'm just very lucky to be able to work with, um, some of the most supportive partners uh, around the table who who have who have been through uh, you know, different but but similarly shaped uh, you know, technology transformations in the past.
1:22:22
And I would focus less on the on the numbers and and more about just uh on the demand in the space, the demand for a product like this or the demand for an experience like this.
1:22:30
It's because it really is it's it's delivering on that that AI, you know, experience or that product experience that I think that we've all really been waiting for.
1:22:38
And so it's also capital intensive, right?
1:22:40
We're a new company, right?
1:22:41
We're trying to create something that's going to hopefully be distributed to to uh billions of people uh uh on the planet every day and at a very affordable cost.
1:22:50
When I say affordable, I mean, you know, compute costs are are high and and we're trying to deliver it in a very affordable way to to to our users.
1:22:57
Um, so it's just very capital intensive.
1:22:59
There has to be some bootstrapping, right?
1:23:00
There has to be some bootstrapping, especially if you think about the the business model and that that we're that we're uh chasing after um uh because we could very easily just say, hey, it's going to be, you know, a certain subscription and everybody on the platform needs to pay 100 bucks a month, right?
1:23:16
and and um there are shorter term rewards that we can chase after.
1:23:21
Um or uh we could raise a little bit of capital, use that towards you know what is venture capital meant for to be able to you know take certain calculated risks towards you know if there are small um speed bumps that that require a little bit of capital to get ahead of to be able to prove you know transaction volume or to prove you know experience across certain industries.
1:23:40
That's how you escape these local optimum of of you know the subscription plan or other things like that.
1:23:46
>> When I do these I ask the same traditional closing question of everyone.
1:23:48
What's the kindest thing that anyone's ever done for you?
1:23:50
I've been able to surround myself and 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 um that I'm very grateful to be to be around and and hopefully certainly I I um I can also extend the same um same level of kindness and thought thoughtfulness towards towards um towards them as well.
1:24:12
So I would say I know I'm not answering your question.
1:24:15
It's it's it's more on a higher level.
1:24:17
It's just the qualities of of things that that um that I notice that that it's um that I really appreciate.
1:24:24
>> No, you're building a fascinating company, maybe maybe the most fascinating company of today's AI ecosystem in the world.
1:24:29
Thanks so much for your time. >> Thank you so much.
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