00:10:42 · S1, Brendan Foody
[00:10:42] S1: As a founder and CEO, how have you thought about scaling yourself? [00:10:47] S0: Yeah. I think that the most important thing is how many people you have in your team that you really trust, where it's like they can quarterback an initiative and take something that you give to them or work on with them all the way to the finish line. And so I think that's most important almost like these... Each individual that you have immense trust in and trying to have as many of those people throughout the org because you can't expect that people on day one or even day 30 are gonna get there. It takes building context, having the right... Exactly. The right, training, the right culture, all the right experiences, to to get there. Yeah. One characteristic I really like about certain people on my team is having strong opinions loosely held where they have immense conviction in whatever idea they're telling to me. But when they're presented with, you know, an idea that is counter to that or or or data or evidence against it, they change their mind very quickly. And I found that that's a very good habit and value. So indexing on on that and people that make decisions and, you know, sometimes it's their call, sometimes it's mine, but always trying to have a very thoughtful way of arriving at that answer. So. [00:12:12] S1: Scaling your culture is one of the hardest things to get right. And one of the easiest things to get wrong. It seems even when it feels right. I'm curious to know what have been some of those cultural, uniquely you things that you want Merkor to keep.
00:12:12 · S1, Brendan Foody
[00:12:12] S1: Scaling your culture is one of the hardest things to get right. And one of the easiest things to get wrong. It seems even when it feels right. I'm curious to know what have been some of those cultural, uniquely you things that you want Merkor to keep. [00:12:25] S0: Yeah. So there's three values that jump out the most that we always preach to everyone. The first one is having a can do attitude, and that when we set really high goals, the decision making forms around those goals to optimize for much larger outcomes. So people that have this sense of optimism and ambition around how they approach problems is very important. The second is having really high standards, going back to hiring, and keeping a really high bar for who we wanna work with, what we expect of them is incredibly important. And I think one of the most, largest differentiators between the legendary companies and those that don't get there. And then the third is intensity, and that we work really hard. And if you look at the early cultures of all of the greatest businesses, they work like no one else. And so I think that's important to maintain as much as possible. [00:13:22] S1: Let's talk about your products a little bit. Can you walk us through the power behind Merkor? [00:13:28] S0: Absolutely. So it goes back... The right mental model is really automating all of these manual processes and [00:13:36] S1: And repetitive processes.
00:13:36 · S1, Brendan Foody
[00:13:36] S1: And repetitive processes. [00:13:37] S0: Exactly. Repetitive processes. And the way I think about our product over a long time horizon is that there's three big things that we need to get right. We know that there's a lot that will change, but for the duration of the business, our customers will always want more candidates available on our platform. They'll always want better matching with those candidates, and they'll always wanna be able to hire more quickly. [00:13:58] S1: How does matching work? [00:14:00] S0: Matching is [00:14:01] S1: That's a tough one. [00:14:02] S0: A very... The most challenging problem because there's sort of two sides to it, both of which are very high dimensional. The first side is is the candidate interested in the job. Right? And so there's all the characteristics of the role, the people they'd be working with, the compensation of that role, the other opportunities they have present. And so we have models that predict the probability that said candidate is interested in the job. The other side of it is from the company perspective of what is the probability that said candidate will perform well on the job once they're hired. And so you need to collect all of the performance data as your eval set to make better predictions around what are the types of interview responses and the characteristics on people's resume and all of that that predict that they're going to do well on a particular job. And it's the blend of those two problems that really go into matching effectively.
00:14:02 · Brendan Foody, S1
[00:14:02] S0: A very... The most challenging problem because there's sort of two sides to it, both of which are very high dimensional. The first side is is the candidate interested in the job. Right? And so there's all the characteristics of the role, the people they'd be working with, the compensation of that role, the other opportunities they have present. And so we have models that predict the probability that said candidate is interested in the job. The other side of it is from the company perspective of what is the probability that said candidate will perform well on the job once they're hired. And so you need to collect all of the performance data as your eval set to make better predictions around what are the types of interview responses and the characteristics on people's resume and all of that that predict that they're going to do well on a particular job. And it's the blend of those two problems that really go into matching effectively. [00:14:57] S1: I love that. Something I've always struggled with is the bias that creeps into the human decision making that is part of the recruiting process. Walk me through how you think about that within your technology.
00:14:57 · S1, Brendan Foody
[00:14:57] S1: I love that. Something I've always struggled with is the bias that creeps into the human decision making that is part of the recruiting process. Walk me through how you think about that within your technology. [00:15:08] S0: For sure. I I mean, I find it so fascinating because so much of the way people hire is very vibes based. Mhmm. Right? Of, like, does this person seem like I get along well with them? And it's not data driven around who's gonna perform well on the job and what are all of the features that actually prove that that person is more likely to succeed. And so I think the first answer is grounding everything in performance data. Obviously, you need to be thoughtful around how you're evaluating performance and thoughtful about that. But so much as you can do that, it's the most effective way to make decisions and optimize for the right thing that you should be hiring for. And I think the second thing is that in automated systems, you can get very thoughtful about the features that you consider. One example of that is that when humans are interviewing, we consider all of the vibes. When our AI interviewer is talking to people and evaluating interviews, it can just look at the transcript, the substance of what people say. Right? Leaving out all of the, like, multimodal aspects of whether that person sounds like us or looks like us and all of that. [00:16:17] S1: That's fascinating. What about nuance? I mean, does that matter?
00:16:17 · S1, Brendan Foody
[00:16:17] S1: That's fascinating. What about nuance? I mean, does that matter? [00:16:21] S0: It does. I mean, a big part of who we hire is like the vibes matter in some ways. Right? Like matter. Yeah. I... And so there's a little bit of a balance there. I I think that our our mission as a platform is very much to avoid that bias and to have as much transparency as possible, around who we think is going to be as successful as possible in the particular role. But at the same time, a lot of the time humans will make the final final call. And there are some things that they should consider that they shouldn't. And there's others that, you know, it's the way it is and the people that that they get along well with. [00:17:03] S1: I think that's really meaningful. You know, you're, you're diversifying the top of the funnel so that when you get to your final few candidates, can apply that level of judgment, taste, perspective that is really valuable, I think when you're making that final decision. [00:17:18] S0: For sure. [00:17:19] S1: So what can you share about your fundraising history?