00:04:48 · Siadhal Magos
[00:04:48] S1: It's gotta be both. I I... And I... We've always been... Much as we're... You know, we started in Europe. I'm based in London. We've always been... We've been global from the outset. I would say many of our even early customers were based in The US, so it's been international expansion from a boots on ground perspective, but we've always had about 50, 60% of our revenue from The US, and that's... Gets... Continues to be the case. We opened up a San Francisco office last year. We're opening up a New York office now. Basically, we opened up a a couple of weeks ago. So there is, like, definitely boots on ground and meet customers where they are with this, you know, transformational technology. But, yeah, the the the the the real key is I sort of feel in many ways to build a world class AI first company. A lot of it is actually about the always on figuring it out. Because as I mentioned, the models are actually changing all the time, and even user expectations around how they are willing to or want to interact with AI is changing all the time. And you sort of need to be in the game and have your fingers on the dials as as maximally as possible in order to actually figure out what's next. And so those are the two focuses for us. We're scaling what clearly... You know, we have a we have a product or a platform whose time is now, and at the same time, there are new capabilities that are emerging that we need to make sure we figure out before anyone else. And the way we solve for that is by, obviously, building a world class team in order to to figure those things out, and that's the the... That's essentially what we're doing with the cash. I mean, there's also a bunch that we can do to spread the word about Metaview, which is really good fun as well. We're... I think our marketing team is absolutely nailing it at the moment and getting the word out in really sort of evocative and fun ways. So that's a that's a that's a bit of fun use of the cash as well.
00:06:36 · Sebastian Johnson
[00:06:36] S0: Yeah. Definitely. This week, you you... The public launch of fillmore, you're sort of, like, opening up to to to everybody. That was everywhere. Right? And it was like very distinct. I probably saw like a dozen posts about it on LinkedIn and they were all... You could tell that they were all talking about the same thing just by glancing for half a second, which I think is like an amazing strength of brand. Yeah. But it was like... It was almost like a new activation, but it very instantly became recognizable and dominated. Tell me about that launch. Right? So so what have you launched, and and what's the impact been?
00:07:06 · Siadhal Magos
[00:07:06] S1: Yeah. So I'll I'll share I'll share some of the sort of technical aspects of what we launched launch first, and then we can talk about, like, the... Like, what does this mean for the market? So you can think about Metaview's core product as an AI native workspace. So you go you go to the workspace to do the work of recruiting alongside an AI, and it's still a big part of our future. We do believe people will continue to want to go somewhere to do, like, lean in work, and they want to be augmented by AI while they're doing it, and that's what Metaview's sort of... The core Metaview product is. The thing we launched earlier this week, fillmore, is almost a different form factor. Same thesis, but different form factor, and the form factor is more... It's like it's a coworker. So you don't actually go to it to do work. It either comes to you where you are, which is usually in Slack, or you sort of, you know, give it... Throw it a task while you're in Slack, it goes away and does the work itself. And who this is really great for, and the work, just to be clear, is researching where to find candidates, finding those candidates, engaging with them, I. E. Communicating with them to say, are you interested in this role and sort of following up and scheduling and all those things and booking new meetings. So you engage with fillmore because you wanna fill more roles and you want an AI agent to do it for you. And so who this works really well, the the sort of reaction this is is much as the workspace makes a ton of sense for this lean in work, the fact is AI has moved on to the point where you can trust it to do, like, long time horizon, multistep processes by itself. And, of course, if it's a multistep process and it's long time horizon, it's less about having a workspace. Right? You're not gonna... You don't wanna sit there and watch it the whole time. It... You you expect it to happen in the background. Just like when I delegate a task to a member of my team, I don't sort of watch them the whole time and, you know, tweak here and there what they're doing. I sort of let them get on with it, and you get, like, high... Much higher leverage results as a result of that because it can do far more work, than you could ever keep up with. And so that's what fill... Fillmore is.
00:09:00 · Siadhal Magos, Sebastian Johnson
It's a, like, highly autonomous sourcing agent whose sort of sole objective is to get you meetings with candidates that are fit for your role, and it has it's it's right for customers who give... Are are happy to give it a high level of autonomy in making that happen. Of course, it still understands guidelines. Still understands your brand. It still understands your tone of voice. It understands all those things, but it it can get super creative in the ways that it finds candidates and gets them in your calendar. And we've been sort of amazed even even as the builders of the agent because you leave so much of the reasoning to the agent itself. We've been amazed with some of the creativity that it's shown in in getting people booked in. [00:09:37] S0: How similar do you see the role of AI in how it's impacted engineering to the impact that it could have in recruitment? You know, everyone talks about, like, a 10 a... 10 x engineer. That's, like, the thing that everybody wants and how AI can make the very best even better. Yeah. Do you see the world of 10 x recruiters?
00:09:56 · Siadhal Magos
[00:09:56] S1: Certainly. It hasn't happened yet. I think fillmore is by far the closest. I I... If I'm gonna, like, put a number in it, I think you're... We're probably in the four to five x range with fillmore as opposed the 10. I know I know people don't necessarily mean these things literally, but it's funny how it ends up being actually quite accurate. If you look at the PRs by our engineering team, like PRs per engineer, it has, I think, at the moment, I think we're... It's either eight or 12 x what it used to be. So, you know, let's call it 10 x on average. But it's hard to say use... Because that job has been transformed. Right? That is now an agent orchestration job. Now the funny thing is... And the people that, you know, join Metaview as, you know, as members of the team, what they sort of get excited about is, obviously, people sort of put the the the job of engineering on a pedestal a bit because it's just, you know, it seems such a high leverage, like, highly... It's just like, it's a high status role, let's say, certainly in the tech world. The funny thing is it's actually harder to achieve that in in... Within the recruiting workflow. And it... That's for, like, a very simple reason that the level of trust you need to have for, truly... For a recruiting agent to do work on your behalf is much higher than the level of trust you need for a coding agent to do work on your behalf. Because if I get a coding coding agent to work on, you know, 12 features while I'm sleeping overnight, I can come in, realize that they're all bad, and bin them all. And, like, okay. I've wasted a bit of money on tokens, but no one's, you know, no one's been hurt. You know? Whereas if I'm ever going to trust a recruiting agent to do work on my behalf, it cannot do work unless it comes into contact with reality. Right? The work of a recruiter involves communicating with other human beings, And you can't just say, oops. That was a terrible way to communicate. Let me do it again. You've burned that candidate. Right? And so the level of trust is that much higher. And so I think that's why you have this slightly slower... That's why we haven't had it yet, but I think we're really getting there. Because now, a, the AI is smart enough to understand all of that nuance and context.
00:11:48 · Siadhal Magos, Sebastian Johnson
B, it can actually, again, do things over a long time horizon, like maintain a relationship or help you maintain a relationship with a candidate for multiple weeks or even months while you're trying to hire them. And just fundamentally, the the models are smart enough... Sorry. The models are smart enough such that they don't make some of the mistakes they've made in the past. [00:12:07] S0: You know, when you when you look at your product road map or designing or rolling out products, how much does that, like, sort of, like, high stakes nature of recruitment impact how willing you are to push things live or test things or... I don't know. And, like, how on it just to be watching all these interactions and checking because you're right. It's really high stakes. These are real relationships, real people that if you get it wrong or the agent get it wrong, that could be a relationship burn either for your, you know, yourselves or your clients. What impact does that have on the products you roll out and and when you roll them out?