00:02:18 · Parag Agrawal
[00:02:18] S2: Yeah. Parallel is a three, almost three year old company now. I was the lunatic walking around three years ago telling people agents will use the web 1000x more than humans ever have. And there were no agents. Agents didn't work. Most people didn't believe me at the time. Fortunately, some did, including index. And at the time, it felt like the science fiction hypothesis that there will be a lot of agents at work and in our personal lives and that they'll be doing like web searches for some reason. I believed it because I had obsessed with it for a lot long time. But today, if you look at like what's happened in the last three years, like I was wrong. But on the other side, 1000x is too low. I think at the time I thought 1000x was like the crazy number to make up. Okay. To talk about. Right. And at the time I was like, my deck literally contained a section, which is like, are we too early? Turns out we were not too early. Turns out today, if you force me thousand X's, too low a number. If you just look at just some high level math, right? A person, an average person does like order of 10 or less Google searches a day. I was checking how many I do. Several thousand now. My agents, the ones I track. Wow. Several thousand per day. All the agents that I use today. So I am now sitting at roughly a thousand X, a little bit less than thousand personally. Most of the world is not. Most of the world will in due time. Might take us a few years, but thousand is a low number.
00:04:04 · Molly O'Shea, Parag Agrawal
[00:04:04] S1: But is that efficient? Do you think that'll crawl back at a certain point because they'll just get smarter and know where to go? [00:04:13] S2: Yes, but it is efficient because the other part of the story is that you gotta... You can't build old school search and do 1000x of this. You think about like, okay, all the infrastructure that a Google might have built to serve whatever order of 10,000,000,000 searches a day. Like the best gift I have is 10,000,000,000 a day is what Google will do. They have a lot of infrastructure to pull that off. I don't think we get to build 1000x that infrastructure to do 1000x the searches. Right. So part of what we do is build extremely efficient and optimized search, which again benefits from models getting better for us to be able to distill intelligence ranking into smaller and smaller models for us to be able to use GPUs as the underpinning of search indexes. Historically, search was done on CPUs memory and CPU bound. Now you get to architect and re architect search for a price performance band that the world never needed, until today. [00:05:28] S1: Of one of the things we were talking about before, I recently interviewed G from Vercel, and this is, you know, maybe this is in parallel, but AI agents for coding have reached 60% of traffic on their indices, what they see. You had a hot take.
00:05:28 · Molly O'Shea, Parag Agrawal
[00:05:28] S1: Of one of the things we were talking about before, I recently interviewed G from Vercel, and this is, you know, maybe this is in parallel, but AI agents for coding have reached 60% of traffic on their indices, what they see. You had a hot take. [00:05:47] S2: Generally, on the web, the statistic being shared these days in the last few months is that agent traffic is exceeding human traffic on the web. That's roughly the characterization. Now there are two things to remember. An agent for roughly doing the same work that a human does will likely do a lot more searches because it can and a human is time constraint. An agent isn't really. It's more and right now they're not even that dollar constrained because people are willing to spend on frontier. A human read on the web or a human search on the web to create equal length value. It takes way more agent traffic. A lot of agent traffic is also people crawling for pre training and people like when you look at like for a website owner and looking at automated activity versus human activity, automated activity is ripping. But my best estimation right now of where we are is agents are using the web 10 to 20% of humans. Which is to say if my 1000x number is right, we have from here at least 5000x or 10000x growth left. Just another way of saying, we are very early with agents. I think in the Bay Area and Silicon Valley, we're all living in a little bit of bubble. Yeah. I think most people's agents aren't doing the number of searches my agents are doing, but they will.
00:07:21 · Molly O'Shea, Parag Agrawal
[00:07:21] S1: So Muse just came out with Jolly and I really like Jolly the character for Muse. We see dots coming out for open AI, we've been seeing a lot of these agents pop up for individuals, for consumers. That growth is faster than any growth ever seen. Like Yeah. Even Chatuchipedia. I think maybe, possibly. We'll see. But how do you expect that to grow? And I guess, where does the retention stay? [00:07:57] S2: Two things. One, I have to make a note. We should call out instinct two. [00:08:02] S1: Yes. Almost forgot.
00:08:03 · Parag Agrawal
[00:08:03] S2: I am. Listen, I'm on the rebel alliance here. Okay. There are all these big people. Yeah. And then there are us, startup founders, are running at solving really hard problems, and pushing the frontier of what's possible, and innovating. So we should talk about instinct. Yeah, they are growing to amazing product. So yes, the category is amazing. It's interesting. I think it's growing really fast. I don't have any insider information around retention. I am, as you can imagine, it's a professional hazard that I use every one of these agents. Yeah. And I try to deeply understand what they can and cannot do and what problems we can solve for them. We'll get into this category and how it changes our product strategy later. But I think my expectation is that these agents retention will be good. And it will be good because for the first time, the product onboarding feels natural. Like not someone designing like a bunch of UX click targets and flows to get you to understand the product. The product is natural. All of these products are somewhat natural. And the question is, can they deliver on the promise created by the UX? So the UX is you can text this thing and it can do anything. That's the UX. It's not complicated. Yeah. Retention is entirely a function of can it actually deliver on this very simple high level promise often enough to become a part of your life. Now it's going to happen. Like a lot of other products struggle with the onboarding UX barrier to entry, but this new generation of products, just that's just not a thing. And so I have a feeling that retention will get solved here.
00:10:14 · Molly O'Shea, Parag Agrawal
[00:10:14] S1: Is that where you think Open Claw maybe hit a wall? Because that was really the first. [00:10:22] S2: No, I think Open Claw was right in all of the ways. Yeah, I think once someone got it, it's just not for the masses, right? It's just like most people don't have the ability to set it up and then to keep up with change. I think the other factor we discount. It's not just a one time cough to set something up. Things are changing so fast that you have to adapt your instantiation of it alongside that change and you have to adapt your use of it alongside new capabilities. So part of it might have been that the setup time because of the flexibility and you controlling it was far too much. Part of it is also that it was perhaps a little too early. Right? Because in the beginning, there was like one model which was really good, like the Opus model. And then as soon as you move to other models, it wasn't as great in the very beginning when people started using OpenCLORE late last year. And so you had to adopt alongside it. But today, as evidenced by Instinct and Muse, You kind of don't have to know or think about it, and the product will change underneath. But as the customer of it, you don't need to know what changed in the last month. You're oblivious to the capability improving underneath. [00:11:55] S1: I can't discount that this was really just invented. So, how did you... You mentioned this at the start of the interview, but like, you have been obsessed with this for a while. So, what does that mean and how?