Entrepreneurial Thought Leaders (ETL)
00:28:22 · Brendan Foody
[00:28:22] S2: So on the first one, I will say I really don't think about it too much. But if I had to choose two things, it would be, first of all, very surreal. Like, you know, my friends in college just graduated in June of last year. So, like, roughly the same age as most of you, and it's obviously beyond my wildest imaginations. And then second of all, it's very fortunate. Like, so much of what has happened has been a function of having incredible cofounders, an incredible team, having, you know, a degree of fortune associated with how we were positioned in the market, and I'm super grateful for all of those. And then your other question was habits, right? Yes. On habits, maybe if I had to choose one thing, it's that I think people try too hard to be disciplined to do things that they don't necessarily want to do when a lot of the key to success is finding the thing that you can be obsessive about. Like, I remember when I was in college, I I would have a hard time motivating myself to cover your ears, like, in homework on time, attend to class, all that kind of stuff. And it was really... The key was just, like, finding the thing that I couldn't stop thinking about, where whenever I'm, like, with my friends or trying to do something else, like, my mind comes back to Merkur because it's the place where I can have the most impact in the world and make a dent in the universe. And I I think that find... If you find that thing that you can be deeply obsessive about, everything else follows. And and that's also what the Teal fellowship looks for, actually, is they look for traits that someone is extremely obsessive because that's one of the largest predictors of the end outcome of the company.
00:30:10 · S7, Brendan Foody, S3
[00:30:10] S7: Thank you. [00:30:10] S2: Yeah. [00:30:14] S3: Thank you for being here, Brendan. So my question is when you were playing around with all these different projects, what was, like, the initial ideation process? Like, how did you decide which projects to pursue? And my second question is about the Thiel fellowship. Mhmm. How did they kind of support you in building what you built today? [00:30:34] S2: Yeah. So on the first one, I would say we were always very customer oriented with with all of them of how do we have our early design partners that can give us feedback on the product across each of the different initiatives, and that was certainly foundational to being intellectually honest for whether what we were doing was actually useful. And so I'd encourage everyone to always try to spend as much time with your users of any products you're building or the customers of any business because that is by far the most important thing, to get right. In terms of... Sorry. What was your second question? [00:31:14] S3: The fellowship? Yeah.
00:31:14 · S3, Brendan Foody, S8, Emily Ma
[00:31:14] S3: The fellowship? Yeah. [00:31:15] S2: Yeah. It's actually funny because it came later. It... We didn't get the TL fellowship until March 2024, and that was after things were... The company was at, like, 2,000,000 revenue, but we knew that we would be at 50 by the end of the year. And so things were real... Just, like, on the dawn of starting to work. And probably the largest value add was, I think, the credibility stamp to investors and hires is meaningful, but also the community. Like, I met, some of my best friends. My friend, Yash, who's on there, who's the CEO of Applied Compute and was previously our customer at OpenAI. And so those those are the two things, probably the credibility stamp and then the community. [00:32:01] S3: Thank you. Mhmm. [00:32:03] S8: Thank you so much for being here today, Brennan. When you started Merkor, it was around a time when Scale already owned a lot of the narrative around AI data and training. [00:32:12] S1: Yeah. [00:32:12] S8: And I'm curious what gave you and your team the conviction to kind of go for it and assume that the market's not fully taken as opposed to go and work for, say, Alexander Wang. Uh-huh.
00:32:12 · S8, Brendan Foody, Emily Ma
[00:32:12] S8: And I'm curious what gave you and your team the conviction to kind of go for it and assume that the market's not fully taken as opposed to go and work for, say, Alexander Wang. Uh-huh. [00:32:22] S2: Well, it's funny because I skipped over part of the story earlier, which is before I met Sean, our initial intuition was that we should actually partner with scale and have them become a customer of ours. And so we hired over a thousand software engineers for them using our platform and our technology, and then we got flooded with support tickets that these people weren't being paid. And they were like, Merkur is a scam because they referred us to this opportunity that is Scale AI. And what we realized was that there was this gap in the market in part because it was changing really quickly. Like, scale grew up in autonomous vehicle labeling with people in The Philippines, and a lot of the infrastructure was built around that. And if we went directly to the labs, we had opportunity to build things from the ground up around exceptional people creating this new paradigm of agentic data. And so that was really the moment that it it all flipped for us. [00:33:28] S1: Thank you. Hi,
00:33:28 · Emily Ma, S9
[00:33:28] S1: Thank you. Hi, [00:33:30] S9: Brandon. Thank you so much for being here. So since you missed two years of college, I thought I'd ask you something related to the education system. What do you think that education systems around the world can do in order to cope with this wave of agentic AI? And do do we need to change the way we actually evaluate human skill at this base level? Or do you feel like the current system is preparing students to actually take on a world that will look vastly different to the one we inhabit during our schooling?
00:33:59 · Brendan Foody, S9
[00:33:59] S2: I think a lot about this because we do... I mean, we've done over 6,000,000 AI interviews. So I I think a lot about how do we effectively assess people, in all sorts of different scenarios. And I think the most important thing for educators to get right is to lean into assessing people using the technology rather than stopping the technology from happening. Like in the initial waves of AI, we saw all of these things of like GPT zero try to stop the use of the models, which is almost analogous, like stopping people from using calculators or computers. And the better way is how do we encourage everyone to use the technology as much as possible and see what they can do with it? Like, now all of you can build a production skill app using Claude code in a week. And so how do we... That can be, like, a one week project, which is insane and has never been possible before. And so how do we, you know, just set these really ambitious targets and goals for students that that force the adoption of the technology and the exploration of what's possible with it. [00:35:10] S9: And just another question to lead up on that. Was there a moment you had during your founding process that made you realize that the whole Pagentic AI landscape was actually moving in this direction? Because today, if we look at it, we have so many tools like Open Claw. That's just a list of them. So was there one moment that made you actually realize that, Okay, the whole AI agent revolution is actually gonna be the next kind of change in in the whole AI landscape?