00:26:14 · Parag Agrawal, Molly O'Shea
[00:26:14] S2: I actually, I am more of an optimist on this. I think they will actually get proactive. So, they will know us. They will know our explicit and implicit needs and they will try to proactively do work. That's the phase. The next phase, I think you're trying to, you're starting to see glimmers of proactivity in instinct and muse and dot. Glimmers. I think they're still more reactive than proactive. They're always on, but they're not really proactive. I think the next era they will be hyper proactive, which I'm really excited about. [00:26:57] S1: I guess, to peel back because this is a brand new economy and layer of the internet and what could, I don't know, the internet might not exist anymore. Maybe we'll just use agents. This is what people are saying. What are those components of the underlying infrastructure? You're one of them. What are like, what makes up that base?
00:27:18 · Parag Agrawal
[00:27:18] S2: There are two ways to talk about this. I think before going into the internet, let's first talk about the underlying infra components for building an agent. You need a model, which is inference. You need perhaps a sandbox. I think you need web search like we provide. You need an action space, which includes a browser and a few other API hooks. And you need access to a bunch of connectors to access your personal data or your company's data. You build these together and you can build an agent. And then the rest of it is all of the same stuff we've always had, which is observability, feedback loops, security. And then you have a cloud for agents. Right? Now you go into the web piece of the infra layer. You now need to do web search, but also you need to figure out to your point around the internet shutting down. I do think the primary consumer of the internet is going to be an agent, which means the internet will get re architected. The first thing that's happening is agents are reading the web, which is what we do. What we haven't figured out is, what's the new business model? Like previously, if you put your content out there on the web, you were either building a subscription business, which is like you put some content out there, a bunch of users come, some fraction of them subscribe for a monthly subscription to a newspaper. Other internet businesses were monetized by saying, I'm going to put ads and I will get paid based on human visitors seeing ads. Other business models were like either affiliate business models or you drive a transaction of some sort. All of these business models are fundamentally relied on us random walking the web as humans, opening pages and taking the next action after the next action on it. Some of which are monetizable actions for these participants. If agents are doing this, the buying action still remains. Every other action breaks. So you can't monetize attention anymore. So ads business model per seat subscription business model, these things are not durable. So what replaces it? That's part of what gets me super, super excited about building parallel with like, I think solving just technology problems, I think is far less interesting than solving a technology and a business model problem.
00:30:05 · Parag Agrawal, Molly O'Shea
So we have a highly opinionated point of view on how we keep the web open on how we incentive align content owners with the AI app or AI agent so that the content owner isn't sitting there saying, I'm going to block all the agents because I don't know how to, how that becomes business for me. Right. So we need to solve this problem for people, which is like, okay, give me an incentive to make my content available to AI agents. What is that? We built a system which runs a model, not surprising to compute how much to pay each content owner every time an agent reads their content. And we've been now doing a bunch of partnership with content owners. And the bet we are making is that we'll be able to keep the web open as a result of our version of, we can call it AdSense, which is easy auto differential pricing actually provides content owner value for high quality content. [00:31:10] S1: That's a really good point. I was interviewing USV Union Square Ventures not too long ago, and Fred Wilson was talking about how Google, the traditional business there is being cannibalized by AI, LLMs, agents. It just is. And so Gemini is like the Hail Mary to pull it in. And they're emphasizing that and they're taking advantage of that. I'm curious to go deeper into this monetization standpoint. In another interview I did at Browserbase with John Collison of Stripe, he posed the question, do we need bot detection anymore? There's obviously good bots, there's bad bots, but if everything, all the traffic becomes essentially bots, these agents, like what is the point?
00:31:59 · Parag Agrawal
[00:31:59] S2: Yeah, no, I think today there's a lot of people doing a lot of bot detection. The word bot detection, I think is a few different things. It is crawlers. It is actual agents working on behalf of a human or a business. It is malicious bots, which are trying to do harm. So I think we have to use that word now a little bit more carefully than we have in the past because historically people have mostly had negative connotations with that word in that, like it's not serving anyone. Yeah. Today there's a category which is actually highly useful for you or for me. I would like my agents to inherit privileges I have. So I think we should be careful. I do think there is like a bot detection market is doing well right now and doing well right now because we haven't figured out how to do incentive alignment. And there's a a separate kind of incentive alignment needed. Let's call it on the action side. So earlier I spoke about the incentive alignment needed on the content side, which is like, why do I let you read my content? The other side is what happens if I let your agent buy on my store And you're starting to see divergent strategies there. I'm of the belief that we need to figure out how to solve problems so that all agents, not just the ones built by a large lab can both access all content and take all actions that their owner is allowed to. Right? But we're not there right now.
00:33:46 · Molly O'Shea, Parag Agrawal
[00:33:46] S1: One of the biggest topics behind growth is cyber security and active threats. How do you I know you said you're an optimist, but realistically, like, how do you see the biggest concerns around this? [00:34:02] S2: No, I think cybersecurity risks are real. I think agents help both defenders and attackers. Problem always is that the people who rush ahead to adopt agents for defending themselves, I think will be fine because attackers like to find the weakest link and there will always be a weakest link. So broadly, that's what I think. Now, the security risk for something highly sensitive, like the model weights of a frontier model are a whole different conversation. Yeah. But by and large, my intuition is that we will use coding agents aggressively to secure. But along the way, there's going to be a cyber event every few weeks of consequence, which will drive action and urgency in getting ahead on defence. We're going to spend a bunch of influence on both attack and defence. [00:35:21] S1: Do you see any of this analogous to your time at Twitter on consumer internet? Obviously, that's a huge, one of the largest social media platforms, and so, that creates a lot of vulnerabilities.
00:35:21 · Molly O'Shea, Parag Agrawal
[00:35:21] S1: Do you see any of this analogous to your time at Twitter on consumer internet? Obviously, that's a huge, one of the largest social media platforms, and so, that creates a lot of vulnerabilities. [00:35:35] S2: No, all of the... There are obviously parallels, right? Not to just keep calling out my company's name again and again. There was a real incentive to attack, whether it were crypto spams. Those were popular for a period, right? Or whether it was some state sponsored influence campaign, which we used to disclose a lot publicly. Those things always happened. It required real energy focus to control. It is, the thing most people don't understand is, it is almost impossible to take it to zero. You have to contain it because it is a knife fight and the tactics change. Anytime you control some vectors, another new vector will emerge and then you will control that. The other thing people don't understand is most of the bad stuff is stuff that doesn't show up on the surface. So if you saw an account and thought this is a bot, it's harmless because you could see that's bot. So the real problem is going to be in the margins when we lose our ability to differentiate. Yeah. Either as people or as the technical people building these systems, when you can't differentiate a human from a bot or an agent, that's when you're like, okay, now I don't know what I'm up against. And I think that is very similar today that we used to deal with back then. [00:37:21] S1: Do you think bots should address themselves?