00:00:00 · Molly O'Shea, Molly O'Shea, Parag Agrawal
[00:00:00] S0: Parallel Web Systems closing a $100,000,000 series b funding round last month, valuing that AI startup at $2,000,000,000. [00:00:07] S1: You were at Twitter for eleven years. You were CTO, then you became CEO. [00:00:10] S2: I was also an engineer before that. We're building a collection of APIs that agents use to search and access the web. Parallel is a almost three year old company now. I was the lunatic walking around three years ago telling people agents will use the web a thousand x more than humans ever have. Most people didn't believe me at the time. I was wrong. Why? Thousand x of tool. My deck literally contained a section which is like, are we too early? Turns out we were not too early. We're building a parallel web for agents. We can transform the web even if you don't publish your website to be agent friendly. We'll do that for you. [00:00:45] S1: In such a competitive career in every stage, how do you not break from the pressure? What pressure? You don't feel pressure? No. Prague, welcome to Sorcery. Thank you for having me. Well, we're in Index's office in San Francisco. It is gorgeous here. They're one of your investors. I'm not sure if you've ever gotten asked this question before, but what have you gotten done this week?
00:00:45 · Molly O'Shea, Parag Agrawal
[00:00:45] S1: In such a competitive career in every stage, how do you not break from the pressure? What pressure? You don't feel pressure? No. Prague, welcome to Sorcery. Thank you for having me. Well, we're in Index's office in San Francisco. It is gorgeous here. They're one of your investors. I'm not sure if you've ever gotten asked this question before, but what have you gotten done this week? [00:01:17] S2: I'll tell you what I got done today. Okay. We just shipped a really exciting integration with Browserbase. We now power search in browser based. And if you think about every AI agent that people use, what are they doing? They are looking at your internal information. They're looking at web information. They're searching a bunch, a bunch more than us. Then they're going into a browser, logging in and doing something, buying something, writing something. So that's what we got in today. [00:01:48] S1: Congratulations. We were talking a lot before this and we were having a really great discussion. Every interview I've had recently is some sort of explosive growth of agents and it's going to be really fun to unpack all of that because from your point you were talking about read versus write, what you're doing versus browser based. So I guess to start, let's talk about that. Parallel, what is Parallel? How is it different? How has it evolved? And how are you learning as things are just changing so fast?
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.