The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:25:56 · Harry Stebbings, Adarsh Hiremath
[00:25:56] S1: Over 30. That... That's great. Amazing. Well done. When you look at candidate completion rates, how much of that is India versus rest of world today? I know you specialize in finding amazing talent in India specifically. [00:26:09] S0: So the reason we started with India is because our parents immigrated from from India, Suri and I, so they went to these amazing schools. So we, like, started these recruiting campaigns from those schools specifically. And actually, like, one of the things that got us really, really excited about labor markets in general and the inefficiencies associated with it was just because, like, one of the best engineers I've ever worked with on our team. We found through a Facebook ad, and I manually interviewed him. Actually, he didn't pass the interview, but the reason that we ended up hiring him is he sent me a really, really long message about what exactly he got wrong in the interview and how to correct it. And I just felt like we gotta work with him. It was sort of that that prompted us to start in India. But if you fast forward to today, actually, the number one place that, you know, workers on the Merkor platform who, you know, have jobs through through us are from is actually The United States. [00:27:02] S1: Percent wise, is that 60% US style? [00:27:05] S0: It's high up there. [00:27:06] S1: Yeah. And client wise, all US too? [00:27:09] S0: Mostly US.
00:27:09 · Adarsh Hiremath, Harry Stebbings
[00:27:09] S0: Mostly US. [00:27:10] S1: Yeah. A lot of young exceptional people are being told to say that they shouldn't maybe study CS anymore because actually CS is becoming so automated. 41% of code is now written by AI. In five years' time, that'll be extortionately higher. Do Do you agree with that advice? And how do you think about whether or not young people should learn programming today? [00:27:31] S0: My take is that programming is actually more important today. It's just gonna happen at a different level of abstraction. One could argue that the leap from assembly to Python was actually maybe even a bigger leap than the leap from Python to natural language. My answer there is that the way we define programming will look very, very different. It may be a person who, you know, has like average skills by today's standards in in computer science, who's orchestrating thousands of superhuman coding agents to achieve more than we thought was even possible. But that skill set, which, you know, we can define as programming at a different level of abstraction, programming in English is gonna be super important. [00:28:11] S1: Can I ask how has the way that you program changed over the last two years?
00:28:11 · Harry Stebbings, Adarsh Hiremath
[00:28:11] S1: Can I ask how has the way that you program changed over the last two years? [00:28:15] S0: I I definitely use a lot of the the AI tools. They've gotten really, really good. A great example is Cursor. A lot of members of our team use use Cursor and love it. It makes doing things that would take a lot of time just so simple and elegant. Right? A great example is testing. With a couple of prompts, you can just generate a more thorough test suite than than, you know, anyone could have imagined for your application, for example. And that just wasn't possible before. Maybe it's like bringing the same consistency from, like, one part of the code base and refactoring it for another part of the code base. You can basically snap your fingers in cursor and it'll get done. And I think, like, the implication for software is that software is gonna get commoditized very, very quickly as these coding agents get really, really good. [00:28:58] S1: What does the world look like where software is commoditized? What does that mean? [00:29:02] S0: It means that people will be able to build applications much faster than was historically possible. It also means that the businesses that succeed in a world where software costs approach zero will be built on network effects. The companies that could even give away their entire code base and then still be alive. The marketplaces and companies like Meta, you know, and Airbnb that have built these really, really strong network effects will be the ones that thrive.
00:29:02 · Adarsh Hiremath, Harry Stebbings
[00:29:02] S0: It means that people will be able to build applications much faster than was historically possible. It also means that the businesses that succeed in a world where software costs approach zero will be built on network effects. The companies that could even give away their entire code base and then still be alive. The marketplaces and companies like Meta, you know, and Airbnb that have built these really, really strong network effects will be the ones that thrive. [00:29:30] S1: Do you agree with people who say like, oh, SaaS is dead because companies will just build their own software? Or do you think differently? [00:29:37] S0: I think what we consider SaaS will change. The next era of SaaS will be replacing entire services, whether it's the end to end process of a recruiting agency like Merkor or another, you know, different service or that that is incredibly manual and incredibly repeatable. [00:29:55] S1: You said about network effects there. If I were to push you to the strongest network effect that you have within today, what do you think it is?
00:29:55 · Harry Stebbings, Adarsh Hiremath
[00:29:55] S1: You said about network effects there. If I were to push you to the strongest network effect that you have within today, what do you think it is? [00:30:04] S0: It's a it's a great question. And I would break it down as... In two categories. So one is the network effect of a marketplace that you might see in a labor marketplace like Uber, where every additional company that hire through Merkor strengthens the marketplace, and every additional candidate on Merkor strengthens the marketplace as well because there's like a higher pool of really, really exceptional people to choose from. And the second network effect or or like data flywheel is around this job prediction piece. We're able to see who is performing well on jobs and the specific reasons why they're performing well on jobs, and use that end to end data on people's outcomes to to make it really, really easy to surface the person that might be the best for for a given role, even if they themselves don't know it. [00:30:50] S1: How do you think about building stickiness and switching cost and making sure that 50,000,000 is really fucking sustainable? [00:30:58] S0: It all starts with quality. A lot of the greatest products or companies of our generation have been usage based. Stripe is a is a great example of this. The reason that that revenue is really, really sticky is because you're able to create these, like, six star experiences for customers and candidates. And and I think that's one thing that has resulted in our very, very quick revenue ramp. Right?
00:30:58 · Adarsh Hiremath, Harry Stebbings
[00:30:58] S0: It all starts with quality. A lot of the greatest products or companies of our generation have been usage based. Stripe is a is a great example of this. The reason that that revenue is really, really sticky is because you're able to create these, like, six star experiences for customers and candidates. And and I think that's one thing that has resulted in our very, very quick revenue ramp. Right? [00:31:21] S1: When you think about the product today, what would you most like to change that Brandon and Surya would most not let you change? [00:31:28] S0: Maybe running our entire internal hiring process for Merkur in a completely automated way. Meaning, Brendan Suri and I don't even talk to someone when they come into the office. We walk in the conference room to meet them the first time, and we're just like, wow. This person is awesome. We couldn't have found this person even if we spent all day every day trying to find this person. We're getting there, And that's just super, super exciting for us. [00:31:54] S1: How do you think about the future of remote and remote versus in person? I don't think you can do nine nine six and do it effectively unless you're in person. I think that motivation, that intensity, you feel in the same room.