00:39:44 · Molly O'Shea, Parag Agrawal
[00:39:44] S1: Do you think everyone will need alignment and safety on their team? Is that the next higher class? [00:39:49] S2: Yeah, I think how do you not deal with the problem? Like we, if you think about us, we are the web layer. The web is the dangerous place. Anyone can post anything malicious anywhere. Right? A lot of that content will flow into an agent's context. So you can do injection attacks. To the credit of model builders in the last two years, models have made very real strides on not being very vulnerable. But I think this whole world will rely on defense in many, many layers. So almost every layer has to obsess about this problem. You can't say, models will solve it. We have to really focus on it to solve it at our layer before we get into the models. Then models have to really focus on it. Then the app builders who are building with models and with us have to really focus on it at their layer. So we have to deal with adversaries at every layer and that is actually what gives you true defense. Still the occasional thing will leak out.
00:40:59 · Molly O'Shea
[00:40:59] S1: Merkur's ivity Index, or APEX, tracks it with every major Frontier model release. Built with partners like Harvey and Cognition, see where the Frontier actually stands at merkor.com/apex. Today's episode is sponsored by VCX by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. Learn more at getvcx.com. Some of you may not have heard this yet, but our sponsor Public just launched something called Generated Assets and it brings AI into investing in a way I've honestly never seen before. Here's how it works: You type in an idea like AI powered supply chain companies with positive free cash flow or defense tech companies growing revenue over 25% year over year. Publix AI then dispatches a swarm of agents that scan every single US stock, evaluates them, and instantly builds a custom index around your thesis. What really stands out is how clearly it explains why each stock is included. And before you invest, you can even backtest your idea against the S and P 500, so you're making decisions with real context, not just guessing. And beyond generated assets, Public lets you invest in stocks, bonds, options, crypto all in one place. They'll even give you an 1% match when you transfer your investments over from another platform. If you want to build a portfolio that actually reflects your thesis, visit public.com/sorcery, paid for by Public Investing. Full disclosure's in the description. Founders scale faster on Deal. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit deal.com/sorcery. That's deel.com/sorcery. How did you recruit for your team, especially as this is moving so fast? So you have global offices now.
00:42:47 · Parag Agrawal, Molly O'Shea
[00:42:47] S2: Yes. How [00:42:49] S1: big is the team and how have you recruited? What are the main roles? [00:42:52] S2: The team is about 120 people now. I think we started the year close to 30. This has been a year of explosive growth. Lot of that growth has been because we had no GTM at the beginning of the year. We were pure tech play. Now, the last three months, six months, we've built a pretty sizable GTM team, and that's been done because we are seeing all of these, almost every business that buys inference needs to buy web search. So we're finding really large, like whatever, the top five five hundred hundred companies in the world, starting to really spend on tokens, and starting to really buy us alongside those tokens to make them more effective. So, a lot of our growth is the sales team, which [00:43:50] S1: has How been do they know to buy you it alongside the tokens?
00:43:50 · Molly O'Shea, Parag Agrawal
[00:43:50] S1: has How been do they know to buy you it alongside the tokens? [00:43:54] S2: They run into problems. Of the common things people run into is people start using a model. That model perhaps bundles itself with a web search. Okay. And they start building an application with that. Now, sometimes it's not good enough and the team realizes that it's the web search component which is causing it, despite the model being great, which is causing it not to be capable enough to solve the problem they're solving. Which is perhaps how we started first working with some of the AI legal, AI finance, AI science kind of customers. The second point at which they really need us is they decide to use multiple models. So we're like, okay, we want to switch across multiple proprietary models on a dime, or we want to start adopting, open weight models. And at that point, having the highest quality web search which works with every model actually enables model independence for you to have flexibility to build your application. So that's the second reason people buy us. The third reason is when people have really scaled use cases and now start optimizing for measuring ROI, optimizing for end to end costs. Because our search is so high signal and token efficient, the models do half the number of searches, use up far fewer tokens, end to end are cheaper, faster. That's the third reason people buy us, which is like, I'm spending too much on tokens. It works. It's useful. Can you help us be more efficient? [00:45:37] S1: So it's not just routing. You also help with token optimization?
00:45:37 · Molly O'Shea, Parag Agrawal
[00:45:37] S1: So it's not just routing. You also help with token optimization? [00:45:42] S2: A lot of categories of knowledge work, where a lot of work happens on the web, we help a lot in token efficiency. [00:45:49] S1: Wow. So when we talked to Gia Vercel, we were talking about the shift of GTM. It was SEO, then it was GEO, and now it's AEO. So like I think [00:46:01] S2: GEO and AU are the same? [00:46:02] S1: A little bit, but not really. Okay. Because the agents now More than chat. Yeah. GEO was like chat. Exactly. So it's like Vercel has optimized itself for the agents coming to its website so agents can read the website and know exactly what products they offer, how they can use it. And so because of that, Vercel is like one of the top uses for building out your products and that kind of coding and all that environment. [00:46:27] S2: No, I think it's interesting you bring that up. Three years ago when we put up our first website up, when we were still kind of... They didn't say anything. We were in stealth. We had a machine version. Until the update, if you go to our website, you will see the human version, and then there's a toggle to transition into the machine version. [00:46:47] S1: Really?
00:46:47 · Molly O'Shea, Parag Agrawal
[00:46:47] S1: Really? [00:46:48] S2: We've had it, as far as I know, were the first website to take on this metaphor because we're building a parallel web for agents. Yeah. And so, we have always carried this metaphor, which now the world is coming around to. It's like a cute thing to do because the truth is the presentation layer almost doesn't matter because we can, we can transform the web. Even if you don't publish your website to be agent friendly, we'll do that for you. Like we can, we can understand what the human version is and how to help it become agent friendly. [00:47:24] S1: Oh, wow. [00:47:26] S2: We don't do AE or GEO, but I think your website will become consumable by agents with us. But I do think like we, for example, even think of our onboarding and our documentation and every part of the developer or customer journey with the primary assumption that it's a human with a coding agent or a developer with a coding agent rather than a developer. And so you'll see a bunch of on our website, you'll see like, put this prompt into your agent and then it'll exactly know how to use parallel to solve whatever problem you're trying to solve. Like one claim, like you just need the human needs to just authorise slash add a credit card slash accept terms and the rest of it, the agent can rip. So really rethinking how you design every experience to be agent first is, I think, pretty fundamental. Vercel, like I know, is very agent built. So people who live that world have an advantage.