Sebastian Scott Podcast Transcript

Sebastian Scott Podcast Transcript

Sebastian Scott joins host Brian Thomas on The Digital Executive Podcast.

Brian Thomas: Welcome to Coruzant Technologies, Home of The Digital Executive Podcast.  

Do you work in emerging tech, working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.coruzant.com/brand. 

 Welcome to The Digital Executive. Today’s guest is Sebastian Scott. Sebastian Scott is the co-founder and CEO of Clera, an AI powered talent platform rethinking how professionals connect with career opportunities. 

He leads the company strategy, fundraising, and go-to-market efforts. Having grown Clera to more than 75,000 represented professionals and over 500 startup clients in under a year. He personally onboarded the company’s first 100 plus startup clients and developed a success fee model. He also led Clera’s 3 million pre-seed round backed by 1984 ventures, deal ventures, and angels from companies, including OpenAI, LinkedIn, and more. 

Well, good afternoon, Sebastian. Welcome to the show.  

Sebastian Scott: Thanks, Brian. Finding me.  

Brian Thomas: Absolutely my friend. I appreciate you making the time and hailing outta San Francisco today. I’m in Kansas City. We’re just traversing two time zones, but I always appreciate the efforts you all make to jump on a podcast with me. And Sebastian, let’s jump into your first question. You founded your first company at age 17 and have built multiple ventures across AI and talent platforms. What experiences shaped your journey to becoming CEO and co-founder of Clera?  

Sebastian Scott: That’s a great question, Brian. Thank you so much. I think it was actually a lucky coincidence that I had the privilege to start a company at 17. So, me and my friends were still in high school. We were noticing challenges within our friends and in age groups of connecting to other people. And at the time we were. Pre university also trying to figure out what’s next and so we basically connected tutors to pupils to help them throughout their career and we’re able to, to scale the platform to quite a few users, actually ended up scaling it to 10,000 users. 

And it was actually a pretty intense time. But at the same time, when you’re. Early when you’re young, you just start building because you don’t really have anything else to overthink over. So, I think it’s been a, been a great time. That shaped me a lot into having a bias for action and, and just going with your gut feeling and, and helping and. 

Fundamentally, what we noticed is that even at the young ages, a lot of these pupils and students were challenged in what they wanna become in their career. So, I kind of always wanted to, I had this itch to start something in the, in the career space and, and help them even after their, their school. 

Never had the chance to do so. But that was definitely one key pillar. And then. What sort of made a tip in, in the end, roughly one, one and a half years ago, is someone from my family was actually laid off from, from his job, and that stuck me quite, quite a bit. I, I really tried helping and, and noticed the power that recruiters have in the market because there was a recruiter helping this family member of mine. 

Really understand what their passion is, what their background is, what they’re really good at, and tried understanding which job, which opportunity could be a great fit. And I was by stand a bystander in, in, in this moment. And I, I saw, wow, can we somehow provide the same quality, the same type of support to more people? 

Because I personally, I’ve never had the privilege in, in working with a recruiter. At the same time, I was working a lot on, on tech, on AI, and I saw there’s a huge opportunity in, mimicking what a human recruiter does and scaling that to a large amount of people. And that’s what we’re doing with carer. 

We are providing an AI talent agent, an AI form of a human headhunter to really help thousands, millions of talented people find and explore the next opportunity.  

Brian Thomas: That’s awesome. I really appreciate that. You’re passionate about things, obviously you’re curious, you know, you, you went through a couple stories here, but you know, starting out with the backstory, there was a gap right, in the, in the market, so to speak when you were in school finding tutors to match with students and grew that to a significant number. 

I think that’s pretty cool. But you always had a vision to help young grads also find opportunities, and then it really hit you. When you share that story about that family member that was laid off and the work that and the knowledge that goes behind the scenes as far as recruiting and, and you wanted to explore more and help people. 

And I think that’s just an awesome story. So, thank you. And Sebastian, Clera has grown rapidly representing over 60,000 professionals and 500 startups in under a year. What key strategies enable that kind of early traction and scale?  

Sebastian Scott: Yeah, that’s a great question actually. By, by now we’ve, we’ve grown even further. 

So, we just crossed the 75,000 professionals mark this week which we’re very excited about as a team. I think there, there’s multiple pillars that, that we are focusing on. I think for one, we. We’ve seen there, there’s a lot of different approaches in the market and generally recruiting has always had a very company first approach where recruiters work for a company, they understand what type of role this company is looking for, and then we’ll approach candidates all over the country to see if there’s a great fit. 

We felt for the first time that we can actually turn this around and really have a candidate first approach. And so our value proposition to. People in startups, in in tech is, is quite simple. It’s, we will be your talent agent. We will understand your background and we’ll always work for you. And this has really helped us grow our platform because a lot of our users are then referring us to friends and, and, and, and really. 

Supporting our, our mission there. Then secondly, I think what was important, ultimately we are building a marketplace. So, we both serve candidates, but also companies was that of course we needed to solve the, the chicken and egg challenge. So, we started off acquiring some important customers and important startups that are fast growing, that are impressive and that have big brands. And so by showing to candidates all over that we are working with these great institutions, these great companies, we were able to already provide quite, quite some value there. And then I think ultimately the big disruption that we are seeing is that fundamentally, if you are a really good recruiter. 

Your work is amazing and everyone will refer you, but at some point you’re just limited in time, right? You can only work seven, do seven days a week. And so scaling beyond that doesn’t work. And that’s where our new products is. A, an AI agent is basically able to scale because for the first time, our learnings all go into the system and that can now serve. 

75,000, maybe 150,000 in a couple of months, and so this is for the first time that we think we can scale a really high touch white glove service. And then ultimately a lot about community, a lot about referrals actually less on ads. This is something we want to explore more, but I think fundamentally what was important to us is understanding can we actually grow a community without paying for ads? Because this is the key feedback loop that we are looking for, to understand if the product that we’re working on and providing is actually living up to its expectations.  

Brian Thomas: That’s amazing. And just to highlight a few things. I think what you’re doing is, is just great. But the milestone you, you did correct me is 75,000. You crossed that threshold this week. Professionals, which is awesome. But I like your candidate first approach. You’re building relationships. Obviously you’re representing these folks looking for jobs. You’re, you’re their talent agency, but you’re also helping employers startups, making those perfect matches. 

Lastly I love that you’re leveraging the power of AI so that you can go beyond just a, a limitation of, of humans, right? You know, there’s a lot of work that goes into recruiting, and as you said, there’s only seven days in a week and AI can really advance and move that volume and connect people much more rapidly. 

So thank you.And Sebastian, you focused on solving the challenge of matching the right people to the right opportunities. What fundamentally, what’s fundamentally broken in today’s hiring and talent marketplace?  

Sebastian Scott: Great question, and I think I could probably rumble on, on this for, for ages, but I think fundamentally the core problem that we are seeing is noise. 

So seeing a lot of volume over value, fundamentally meaning. Both sides of the market, be it hiring managers, companies, but also candidates are increasingly using and leveraging AI to automate processes and also automate mass applications on both sides. So, and the challenge is that when, when both sides do this, it just leads to hundreds and thousands of applications that individual candidates make. 

When they’re looking for a job, meaning that when a hiring manager receives an application, it’s really hard for them to understand how genuinely interested this candidate actually is. And the same goes for the other side, right? Hiring managers using AI to, to scan resumes. And so there’s fundamentally a, a moment basically of AI technology creating more volume, more noise, and it’s really hard to understand who’s actually a fit. 

Then secondly, what I have always found quite interesting is that there’s a lot of job boards and job platforms that have fundamentally misaligned incentives, so most of them are actually paid by click. And not per placement. So, they’re not incentivized to actually find you a job, but rather to get you to click on an ad. 

And so, a lot of these job platforms actually are not even aware how many hires they make on a year because they can track this data. And so for us, quite importantly, we always wanted to focus on how can we. Optimize and how can we work on maximizing the chances that everyone in our pool will actually land a job. 

And so that’s how we work and that’s also how we are incentivized. So, companies only pay us and reward us if we actually find them higher. And then. The, the third root cause or, or challenge that I’m seeing right now. And I think that’s causing a lot of also emotional damage for a lot of candidates that are frustrated. 

And yeah, just challenged in this situation is there’s a lot of ghosting taking place because when hiring managers receive 5,000 applications for a job, it’s really hard for them to be transparent on where candidates are in the process. And this is really discouraging for a lot and causing. In my opinion to large friction in the job market. 

So, a lot of my friends are kind of. Not really that satisfied in their current job, but the thought of looking for a new opportunity of exploring something else feels very emotionally draining. And I think this should never be the case. People should be more incentivized to change their current job if they’re actually unhappy. 

And that’s one of the key pillars that we’re working towards with Clera in removing the fiction and making it easier for people to find a job that they’re actually. Yeah, really passionate to work in.  

Brian Thomas: That’s awesome. You’re really solving the problem here. And, and you’re right. I, I think AI, there’s a lot of benefit to AI, but today, as you said, the core problem is all the noise. 

People, it’s this volume over value. Everybody’s using it. So it’s just, again, creating that noise. I also like that you talked about this and, and a lot of people don’t know this, but you know, the incentives are backwards, in my opinion. Right? You talked about them getting paid on clicks or matches, but really not paid on hiring the candidate or placing the candidate. 

And that’s where you are certainly differentiating yourself. I know you’re not the only one on the market, but. But again, that you’re highlighting the, the value and the benefit of this type of model. And of course ghosting is a big problem. We all know that. And it’s is creating a lot of friction in the market emotional challenges for candidates as well. 

So thank you. And Sebastian, last question of the day. As we look ahead, how do you see AI transforming hiring talent, discovery, and career mobility over the next decade, and what role will platforms like Clera play in that evolution?  

Sebastian Scott: Yeah, great question. I think my answer would probably be, be twofold. One, on the general improvements that AI. Have and, and can have on the process of getting hired and hiring fundamentally. And then the second is, is more broadly or macroeconomically speaking, what impact AI will have on, on jobs themselves and on the job market, starting with the first? So I think fundamentally what we’re seeing right now is there’s an increased usage of agents. 

So, for the first time, AI has been an enabler of doing end-to-end tasks, automated. So. When it comes to hiring, we are seeing a lot of advantages of basically removing a lot of these mundane tasks, especially for, for hiring managers, but also for job applicants, where maybe historically you would’ve needed to look through the newspaper or go to LinkedIn or a job board every day to see if there’s something new. 

But now you can have your personalized agent that will scan the market every morning. And we’ll inform you if there’s something interesting. And that’s also what we are leaning into with Clera, right? So we work as your personal career assistant and career partner where whenever we see there’s a new opportunity, we will reach out and we will, we’ll share that with you. 

And then secondly. Matching. I think just like in, in dating, we see actually a lot of, a lot of similarities when it comes to the technology behind it. So far jobs and candidates, it, it’s, it’s been very difficult to match, make. Matchmaking has basically taken place on a, on a keyword level or on a, on a very. 

Limited technical way. And for the first time with large language models, you can go much deeper in understanding what do people want and what do these roles require. And you are much more a precise in being able to match those sides. So, I think that’s probably one of the most exciting parts for me personally, that for example, we recently were able to connect a software engineer with a company. 

The software engineer fundamentally wouldn’t have had the. Best credentials for this company as they would’ve only hired from Ivy League universities. But actually, what our system found is that this software engineer had built a very, very similar project by himself, and the company was looking for exactly this skillset. 

And so that’s something that no existing job board could. Provided for, and given his skillset, we were able to connect them and within two weeks he actually got an offer and is now working for, for them. And that’s just so sort of the, the tip of the iceberg on what we’re starting at. The second dimension on, on, on the job market in in general. 

I mean, I personally do expect quite a lot of layoffs happening this year. I think there’s still an ambiguity in the market whether these layoffs are actually truly triggered by AI or if, corporates are using AI more as a scapegoat. So that’s something we, we will still have to monitor more closely. 

But there is definitely gonna be huge disruptions in the job market as more and more processes are automated. And what our take is that fundamentally there will be an ever growing mobility in the job market. So, people will have to redefine their careers more often and more quickly. Thus will require more of a matching technology. 

And so that’s something that we want to lean into even further and what’s, what’s driving us quite a bit.  

Brian Thomas: Thank you. And I think that’s important. You, you know, you highlighted the, the, the layoffs that are happening and, and gonna happen this year. The matching that matching technology obviously is gonna be key to really dial this in and, and narrow those matches. 

Make ’em a lot better, obviously. But we know that AI in the future is only gonna get better. You talked about that. Today agents are doing that end-to-end work through a lot of these tasks, but it’s only gonna get better. And I really like your. Kind of stepping through the similarities with the, the dating industry, right? 

You’re going deep into the candidate’s experience, education, projects, et cetera, again, for better outcomes. And in the end, we want to have a win-win situation. So, I really appreciate that and Sebastian, it was such a pleasure having you on today and I look forward to speaking with you real soon.  

Sebastian Scott: Equally. Thanks for the thoughtful questions. Brian was a pleasure.  

Brian Thomas: Bye for now. 

Sebastian Scott Podcast Transcript. Listen to the audio on the guest’s Podcast Page.