Invest Like the Best with Patrick O'Shaughnessy
00:42:44 · Noah Shinn, Patrick O'Shaughnessy
So there's a lot of consideration that's put into this in terms of product building. There's quite a bit of work that you wait on the infrastructure side to make it fast and make it affordable to serve. But this is another area that I think is just so important and is going to be a differentiator. [00:42:59] S1: How much of that is your personal and the team's taste versus it being the result of a quantitative type process, like iterative quantitative process of, okay, we did a b c testing of emoji reaction versus short versus long, and this is the thing that is optimal. How much of it is an optimization exercise that's data driven versus your own sensibility and your team's sensibility?
00:43:21 · Noah Shinn
[00:43:21] S2: Honestly, just all of the above because when you're thinking about building evaluation or other testing frameworks to be able to test for these very soft qualities or these actually very long term qualities, Two or three weeks in, does the user trust instinct? How do you measure that? How do you run simulated evaluations to test if the user is going to feel trust in two or three weeks from now? And, actually, a lot of it is just staged rollouts over time. So I might come in and build a slightly different experience, and then I'll release it to myself, and then I'll play around with it for a little bit and and see how I feel about it. I'm just very opinionated about these types of things. Then if I feel comfortable with it, I'll send it out to the team. I'll say, hey. You guys should try this. We'll see how they feel about it, And then they'll send it out to our smaller early access group, then they'll play around with it and see how it feels. And then if we're confident there, if there's any tweaks that we need to make, we'll do that. And then we'll eventually roll it out to the general public. So I think this is very important because I think that Instiq is quite capable and is one of the most capable products out there, but I'm not saying that over the next couple months or years that others are going to come and deliver the seemingly same experience. But I think that this deep focus and priority on how the user feels and how to make it the most enjoyable experience beyond the words that it's saying, just the way that it feels is so important.
00:44:32 · Patrick O'Shaughnessy
[00:44:32] S1: One of the great things about the history of technology is this race between incumbents getting quality and innovation versus upstarts like you getting distribution. Obviously, you've built an incredible product, the feel of it. Like you said, it's the worst it'll ever be. How do you think about that challenge? Like, your speed of scaling, what your ambition is for how to get big really, really quickly. Do you think this is a winner take most, take all market? Like, what will the market shape of agents be? I'm just really curious how you're thinking about, okay. You've got this foothold. You're growing 10% day over day. You do that math. It gets really big really quickly. You need a lot of compute. It's a free product. Like, you're a very chill guy. It just seems like a stressful situation to be in facing down how big this could get as quickly as it could get. Talk us through that many headed monster of a problem.
00:45:16 · Noah Shinn
[00:45:16] S2: Well, I think you just described everything all in once in about twenty seconds there. And I think maybe if we think about the growth story so far, just to describe where we're coming from, we are famously or infamously serving an invite only product, which is honestly not meant to be an exclusive thing. Although some users are treating it like that, that's really not the intention. The goal here is I'm ambitious. I want to scale this thing as fast as possible, but I also want to do it in a responsible way that enables us to not wake up one morning and have 10 times the number of users, and then 80% of them actually can't talk to me because there's not enough compute. The interesting thing, both the benefit and also the detriment is we first started out this program. We gave it to, like, 200 people. It was close friends and family members, and and we just said, like, go try it out. And then the next day, two, like, five people came onto the platform because they just referred it to somebody. Just to describe a little bit more, it's an invite only platform, and every user will have five invites to be able to get. So we rolled it out. 200 people. Next, it was, two zero five, and then next, it was, like, two ten. So it's like, okay. Cool. A couple people are sharing it to one person. But then that just started to accelerate. It was very odd. It was, like, 1%, 2%, then it started to be, like, 3%, 4%. And then once we hit a couple thousand users, some people just started to share it online too, just, like, natively share some cool use case that they had with it. And then that accelerated the growth. It actually started to turn into, like, 6%, 7%, 8%, 9%. And now I believe we're, like, 10 or 11% day over day. And just to call that out, it's not that we're doing some sort of creative marketing event. We spent $0 on marketing so far. It's not that we're doing something every single day to just be able to support 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 something very significant there. When I talk about strength of word-of-mouth, it's honestly a little bit surprising. It's one of the strongest cases of word-of-mouth growth.
00:47:12 · Noah Shinn
I find all these stories of people saying, don't ask me, and they'll actually be ashamed. They'll, like, email me and say, hey. Can I please get an invite? I think I have a friend that has it, but I don't know if I make it into his five friends. Right? And then there are also people who are bragging, like, I got three invites left. I'm just, like, holding on to So there's so much happening of people that want access to the product, but there's these odd social games happening of people using their invites. I was seeing the other day, there were some invites that were selling on eBay. It's, like, $300. People were buying these invites on eBay, and it's just to control the growth. So then the thing that most people are asking right now is you have much bigger players that are able to distribute to a billion or 2,000,000,000 people on the planet immediately. And maybe they might not be compounding naturally as fast, but they have such a great top funnel distribution. And then you have us compounding at a very fast clip every day, but then we don't own a major service that has two or 3,000,000,000 people and able to distribute immediately that day. So it's this interesting question, like, where does the curve line up and where is the inflection point? And there's another problem that comes with this too. It's an interesting scaling problem. This is what is, I think, the core of the problem that I spent, like, 40% of my time worrying about, which is it's not like the traditional other consumer products that grew very fast where to double the number of users on, let's say, Instagram or Facebook or something, it would be this many number of other requests going through the platform. And, yes, there's a scaling story there, and it's certainly hard infrastructure work. We also have that, to be fair. But what do you do when the underlying compute also needs to dub... You know, 10% there every day. We've been doing this for several weeks now. What does it mean when the amount of compute that you need access to is now doubling effectively every week? Do we buy compute two x of what we have right now? Well, we're gonna consume that in a week. So then do you buy five x? Well, we're gonna consume that in less than three weeks. Do you buy 10 x? So now it's like 10 x leverage if you can even stomach what it's like to buy 10 x ahead.
00:49:06 · Noah Shinn, Patrick O'Shaughnessy
But then you're gonna consume that in a couple weeks from now. So that is the hard problem is thinking about how far ahead do you buy. It's going at a faster rate than Claude Code or Codex or some of those other applications where they also had to reason about other similar exponential type of problems. The other subtlety here is that it's not like a certain business where when you double the number of users, you can buy two x more resources in order to power it. It's that the resource has a lead time of several months. So you can't just go out tomorrow and start by a compute because you get taxed, like, three or four x what it is. If you're wrong, you're wrong by three or four x. Let's say it slows down. Let's say we don't actually do 10% for a very long sustainable period. Let's just say it's, like, five to 8%. But five to 8% compounding day over day for three, four months, which is the lead time to bring compute online, and that's even aggressive itself. That's a 100,000,000 users. Then do you buy compute for a 100,000,000 users? So those are the types of questions I'm wrestling with. If you're wrong, you're very wrong. You get charged three or four x. [00:50:03] S1: What is that if you zoom in on the individual user and the cost to serve them on a per day basis? I don't know what the right metric is. How much me using my instinct costs in inference per day or something like this? What is that scale?