"Turpentine VC" | Venture Capital and Investing
00:32:59 · Usman Hanif, Brendan Foody
[00:32:59] S1: We've touched upon this a bit when I asked how our company sort of vetting your vetting, like, making sure that you're doing it right. But you mentioned, like, you need data on what makes a good designer. Right? Say you've trained the model, you get an output. How do you just internally validate like, hey, this model is doing well or not doing well. This is actually a good designer. This is actually not a good designer. Is it pretty manual? Like, do you yourself just need to kind of do it by inspection? Or how do you do this systematically? [00:33:29] S2: Yeah, so we do occasionally have, you know, human teams that will use the product and find like, if there is a result that shouldn't be there, why it's getting surfaced, how can we fix that? And then I think the most important one is really the customer data of customers, you know, telling us giving us preference data of who they want to hire for which reasons of whether that's that person is performing well. And as the customer data begins to scale, we're leaning less and less on our own human teams that can help create data. [00:34:01] S1: Yeah. We've talked a whole lot about how, at least from the side of the employers, this is amazing. Let's, see a lot more candidates, you know, sort of offloads the vetting process. You also briefly touched on from the side of the candidates. Could you speak a bit more about how this sort of helps them? I'm sure a lot of folks, especially overseas, are actually really loving something like this that's legitimate, systematic, and works.
00:34:27 · Brendan Foody
[00:34:27] S2: Absolutely. I mean, there are so many people in The US, let alone abroad, that have applied to dozens, if not hundreds of jobs, and just not heard back from the vast majority of them because of extremely irrational resume screens. They don't get feedback on why they're not getting considered for opportunities. And the process is wildly unfair. But when you're able to lower the cost of assessing talent to zero, and do so in a centralized fashion, where they apply to one platform that can facilitate transactions with hundreds of companies, it just makes it a way better experience. So I think the two things client that are three things that candidates love about our platform are first of all, we consider everyone in a fair way, not just based on the credentials on their interviews, or on their resumes. The second thing is that candidates are able to get feedback on their resumes, on their interviews, why they're performing well, and selected for a role. And then the third thing is that they apply to one place that considers their applications for hundreds of companies that are hiring for 1000s of roles. And so it's just a far, far more efficient structure than this, like, very disaggregated labor market that we see today.
00:35:42 · Usman Hanif
[00:35:42] S1: Yeah, that's really powerful. Stepping away a bit from the technology and maybe heading towards the world of, you know, distributing this out to people. Obviously, you're creating a marketplace, comes with a bit of a chicken and an egg problem. You need employers to use you to sort of attract candidates. At the same time, you need those candidates to have the employers consider you. How do you guys go about doing this early days? How are you getting candidates? And how are you getting employers?
00:36:10 · Brendan Foody
[00:36:10] S2: Yeah, it's, it's hard to start a marketplace early on. And this is where a lot of the network effects come from. And so it was a lot of hustling, starting with customer needs and finding role candidates that are a good fit to fill those roles, and and brute forcing it in a lot of ways early on. Now, we've had this really interesting insight, which is that one of the inherent challenges of marketplaces is the chicken and egg problem that you're describing. But if you're able to create intrinsic value on one side of the marketplace that can unlock growth there, then you can facilitate far more transactions, get people in new networks where you don't yet have demand and create a lot more opportunities. So that's why we've been investing in building out these resume feedback and interview feedback tools, giving them away for free to candidates, so that they can come to our platform, they can see feedback on their resumes, practice their interviews, gain a lot of intrinsic value. And then while they're at it, get matched with all the opportunities that we have from employers. And so the focus is on being the one spot that solves all of the problems for a customer where or for an applicant where they come, they can improve their application, and then also get matched with opportunities.
00:37:33 · Usman Hanif, Brendan Foody
[00:37:33] S1: I see. So solving that problem was a little bit more on the candidate side, sort of giving them these tools like resume feedback. And and these tools are you're you're... I'm assuming you're you're using the same AI here. Right? You're you're doing this automatically. And and what are you sort of giving back to them this feedback? Is it telling them, like, a score you're creating online? Or is it actual written feedback about how they're interviewing? [00:37:57] S2: Yeah, it's both. So we give them scores. And then we also give them written feedback. The interview feedback is still in beta. So it's not available to everyone. The resume feedback is available to everyone that interview feedback soon will be available to everyone. And it leans on a lot of our existing knowledge, though, and data in terms of what is effective, though, it's a little bit of a different problem. And that there are certain things that people can and can't control about their application. So it's important to be thoughtful about, you know, telling them to improve in the ways that they can control, and less so and the things that they [00:38:35] S1: Yeah, I guess I'm curious about that. When it comes to resume feedback, is it is it most like stylistic, like, you know, keep on a page, don't make it to or how is that?
00:38:35 · Usman Hanif, Brendan Foody
[00:38:35] S1: Yeah, I guess I'm curious about that. When it comes to resume feedback, is it is it most like stylistic, like, you know, keep on a page, don't make it to or how is that? [00:38:45] S2: Yeah, there's a lot of stylistic feedback. Also reformatting resumes for people can be super helpful. And there's a lot of challenges that people particularly internationally have with formatting resumes and ways that are picked up effectively by parsers and surfacing all of that data effectively. Lot of stylistic things. We're also interested in exploring giving people career suggestions where we can help be their coach and partner throughout their, you know, process of career development and what opportunities are the best fit for them, what things they should do to help be more desirable to employers, like, you know, doing projects to play around with LLMs and and all sorts of stuff like that. [00:39:34] S1: Wow. That's really exciting. And could you maybe speak to some of the work being there? I know, even at large companies are often be sort of internal tools when it comes to career planning and, you know, how to how to progress at the company. What are you guys looking at to do here?