Episode Transcript
[00:00:04] Speaker A: When it comes to the learning side of it, one thing that I knew from our initial experiments, that you can have the best simulation, you can have the base learning content, you can have the best assessments. But without personalization, without personalized tutoring and instruction, skills development still doesn't happen.
[00:00:23] Speaker B: Welcome to a new episode of the what Works podcast series. That was Tigran Sloyan, founder and CEO of CodeSignal. In this conversation, we dive deep into one of the most important shifts in hiring and workforce development. Moving beyond resumes to a truly skills based approach. We talk about why measuring skills, not just mapping them, is critical to building a talent strategy that actually works, and how organizations can implement skills based hiring while also transforming into internal mobility and learning.
Let's get to it.
[00:00:57] Speaker C: Hi Tigren. Welcome to the what Works podcast.
[00:01:01] Speaker A: Hi Kathy. Thank you for having me. I'm excited about this.
[00:01:04] Speaker C: So looking forward to our conversation. I know we'll dive into your company and all of that, but first, tell us a little bit about Tigran. Tell us about yourself.
[00:01:13] Speaker A: Yes. I'm based in San Francisco and I run a company called Codesignal where we are on a mission to discover and develop the skills that will shape the future.
[00:01:25] Speaker C: Wow, that's a big mission. And Codesignal. So tell us more about Codesignal. How did you come about founding the company? How long has it been? Tell us more about how you came to that mission.
[00:01:38] Speaker A: Absolutely. I was working at Google. This is a little over 10 years ago. And I was doing a lot of interviewing where Google was trying to hire a lot of engineers and many other roles as well. And it was very hard to do because we, we had so many open roles and very few people were making through the interview process. And I started realizing a few things that were kind of shocking to me at the time. First, I realized that the only people that were actually getting to the interview stage were people who had good looking resumes. And that was very interesting because I knew a lot of people who were very, very good at the skill we were looking for, but they just didn't happen to have the resumes that would stand out in the process. And I would encourage them to apply and then they would tell me they got rejected. I'll be like, wait, you couldn't do this interview? They're like, no, no, no. We like just got a rejection at the resume review stage. And that seemed so backwards to me that I was like, okay, maybe people know something that I don't, so I'll just let it slide for the time being. But then I also realized that a lot of people who actually could be good and could be highly skilled skilled never actually get the chance to build those skills and become proficient and live up to their potential. It's a very punishing funnel. By the time you are in college, most of the people who could have really survived that funnel have already been cut from the funnel. But then it keeps on going. Then you graduate, and unless you actually have a fancy resume, it becomes harder and harder to find the next career and find your next job and keep on building that skill. And at the end of it all, the realization that talent is the most precious resource humanity has was the big aha moment for me because skilled and talented humans build everything. So to me, this mission and idea of solving the talent problem, right, and making it possible for us to have not one Einstein every 100 years, but 100 Einsteins every year. And driving humanity forward as a species became the mission. So I quit Google, started a company originally with this give me a year, I'll fix everything attitude that entrepreneurs need to have.
But we've come pretty far. We've come pretty far since then.
[00:03:59] Speaker C: Wow. So you saw this problem at Google when you're working at Google as an engineer, right, where you're an engineer at Google?
[00:04:06] Speaker A: Yep.
[00:04:06] Speaker C: You saw this problem and we said, we gotta fix this problem because talent is the most precious resource. How cool is that? So how did you go about it? So you founded Code Signal, then focusing first on the recruiting side. So how did you do this?
[00:04:20] Speaker A: I wanted to give people a way to learn in a way that speaks to them, that is personalized to their experience. I wanted to fix skills based hiring in one go and I wanted to kind of help create a healthier funnel from learning to finding your first job to developing on the job. Now at the end of year one, we've been quite successful, right? We've raised a Series A, we've raised a Series B. But then we've started to realize that it's too big of a problem and we have to focus on like step one of that process. And to me, step one was about measurable skills. It was about can we build the best skill assessment company as a first step, because if you can't measure skills, you actually can't teach anything. Right. It's very hard to teach somebody something if you don't know what they already know. Sure, you can teach a beginner because you know they know zero, but as soon as they go beyond that zero, you're like, are you here, here or there? Right. Like how do I match content to you? That will still keep you motivated but challenged at the same time. On the flip side of it, if you can't measure skills, you can't hire people based on skills. So you're back in that resume driven world, which is very, very backwards, especially in an age where technology is advancing so rapidly and changing skills that matter almost at a monthly basis these days, especially with the rise of AI. So skill assessments and skills based hiring became the first kind of step of the mission. Right. I knew that if we could do that, it will unlock many things, including doing the educational mission. And for the first five years of the company, that's what we did. And it worked. Right. That brought us to our CSC funding that led us to hundreds of top tier companies actually living behind the resume based approach and giving everyone who applied to the company a shot to demonstrate their skills and actually get hired. And we have so many of those stories, we call them talent stories, of people who could have never even hoped to get an interview, who actually got a job to change their lives and had a massive impact on the companies they worked at.
[00:06:37] Speaker C: Wow. Now that's fantastic. And I know this is a huge problem that many companies, many tech companies are trying to address too. The skills assessment and skill based hiring, obviously, and many practitioners too that are listening to us. So how do you help the HR practitioners that want to go more towards skill based hiring, maybe at some point skill based learning, those kind of things. Tell us more about how do you do this.
[00:07:03] Speaker A: Absolutely. So it starts from stimulating the skill. Because if you're trying to assess a skill or even teach a skill, the best way to do it, the actual, only real way to do it is through having somebody perform the skit. If you say I can play basketball and I can shoot a basketball, all I have to do is give you the ball, Right. If I give you the ball and have you do it, it actually becomes very easy to tell if you can or cannot. Now that means though, when in professional setting, you need to create some kind of a simulation. So if you're talking about engineering skills, you need to say, what do engineers do on the job? Will they write code to create products? But you need to create a coding simulation. What do salespeople do on the job? They talk to customers trying to sell a product. So if you're going to create a simulation like that, you need to essentially have a way for me to talk to somebody and to demonstrate my ability to sell them a product. Without generative AI, we could have Never done it. We simulate every professional skill you can think of. We have coding simulations, we have writing simulations, we have code conversational simulations where you're literally talking to an AI in a voice conversation where the AI is role playing anything you want.
[00:08:19] Speaker C: So now you're not just focusing on technical skills, you're focusing on all skills that you could imagine, right?
[00:08:26] Speaker A: Absolutely. And we were at the root of the Gen AI revolution. When all the top tier models started coming out, we were one of the first ones to get exposure to it. And for me it was a massive eye opener because a, it was about simulations because like, oh wow, we can now start to think about simulating all these different things that we couldn't do before. But also, also when it comes to the learning side of it, one thing that I knew from our initial experiments, that you can have the best simulation, you can have the best learning content, you can have the best assessments. But without personalization, without personalized tutoring and instruction, skills development still doesn't happen. So to me, one of the biggest aha moments when I saw what Genai could do was personalized tutoring. 1984, Benjamin Bloom ran this very famous experiment and this is the same Bloom everybody knows Bloom's Taxonomy. The same Bloom run an experiment where he took a classroom, split it into two groups and half of the group got randomly split, right, like a proper economist would do. Half of the group got one on one personalized tutoring, the other half didn't. The other half went through standard one too many instruction and what they saw was two standard deviations above educational outcomes for the group that had one on one tutoring. And this has become known as Bloom's two sigma problem. So essentially it's been replicated many times and shown that if you can get one on one tutoring, if you allow for that, then you get dramatically better educational outcomes. But it's not called the, you know, the two sigma effect, it's called the two sigma problem because Bloom, his PhDs were like that. Great. We found something that has impact, but it's never, it can't be scaled. How are you going to get a tutor for billions and billions of people? But AI actually allows for that. We can now build a AI tutor that can personalize your learning journey and solve Bloom's two sigma problem 40 years later.
[00:10:34] Speaker C: Wow. So not only did you expand the skills areas dramatically, but then also you expanded into the learning area much more so than you were ever before. Because before you were not sure how you could create all this personalized learning. Obviously and you couldn't. Right. So so fast forward to today. So today you bring kind of skills assessment, skill based hiring and then skills development across all the skills. Do you have any client industries that you're working more with? I mean, I assume you probably started out with a lot of tech companies, right? Because of where you focused first. But tell us a little bit about your market and which companies you help today.
[00:11:14] Speaker A: Absolutely. You actually nailed it. We did because we started on the tech side. Our clients initially were very tech focused. So from the Netflixes of the world to Ubers to Zooms to pretty much any top tier tech company that you can think of. But then over time what started happening is both because technology has been very rapidly getting into every aspect of business, but also because we started expanding into delivering our skills platform to non technical roles and non technical skills as well. Now we partner with most of the larger financial organizations From Visa to MasterCard to Capital One to many, you know, retail, healthcare and so on and so forth.
[00:12:02] Speaker C: Sure. So a couple of questions because I know we talked so much about the skill based organization and how you do this. Do you need for this to work well? Does everybody in the whole organization have to take your assessments and go through your development or how do you companies usually roll this out?
[00:12:22] Speaker A: Yeah. So it actually goes more bottom up than top down. Typically when you think about becoming skills based organization, you think very top down. You think we're going to bring in a taxonomy and then we're going to start to map everybody's skills. But in reality that doesn't really lead to the outcomes you want in order to get quantifiable, measurable skills. Start from the hiring side. Right. Essentially start to implement skill based hiring practices. And those have become very commonplace. Actually most organizations are really giving up a massive competitive edge because you can really find incredible people that just don't have that resume. But when you start doing skills based hiring, almost everybody you get in the door already has a skills profile. What we've seen be very successful is learning with Cosmo. Right. Who is our AI tutor and guide. One team at a time. Because when you do that, over time it starts to spread and you start to realize not just the skills skills that certain individuals have, but then over time it spreads and starts to build this very rich skills taxonomy that contains not just what skills people have, but at what level of mastery they're at and what they're trying to learn next.
[00:13:37] Speaker C: Got it, Got it. No, that totally makes sense. And so I'm sure AI literacy or AI skills in general are hot on your clients roadmap for sure. Right, Because I know everybody is trying to build that. How, how can we think about codesignal and the overall HR tech stack?
[00:13:55] Speaker A: Absolutely, that's a great question because you're right, it's a very complex ecosystem right now and we knew this going in. That's why we've built everything to be highly compatible and integrated. So from being able to integrate with the different LMSs to create a very interconnected learning experience like the LMSs, ATSs and HRI systems in general. But also the skills taxonomy and ontology that we've built is actually a universal map that can map to any existing skills repository. Which means that when we come in, if you already have an existing mapping in place, we can map ours to yours. Which means that as soon as that mapping that bridge is done than all the learning and assessment content that exists can essentially be layered on top of your existing system, allowing you not have to go through the entire remapping and reevaluation process.
[00:14:58] Speaker C: So you basically feed seamlessly into all these systems and you're not trying to obviously go there, right? You're not trying to be an ATS or an LMS or an HCM at all.
[00:15:08] Speaker A: In no way. We are a skills platform, an AI native skills platform, which means for us that we do everything that relates to building and assessing skills.
[00:15:20] Speaker C: Got it, Got it. Now that totally makes sense. So where are you taking the company next? What's next for you? I mean you've had such great success and I think expanded so much just in the last few years, both from a skills perspective, but then also from a functional perspective now focusing also on skill building, not just at recruiting. Where are you going next?
[00:15:42] Speaker A: It's about building on top of what we've done so far to continue achieving the mission. Because if you look on the hiring side, there's still many, many organizations, especially outside of the sort of the core tech, finance, e commerce space that still primarily rely on resumes, especially for non technical skills. I mean our skill based hiring for sales and go to market roles has been around for over a year. But you still, when we look at the feedback go to market people, candidates are surprised by that experience, very pleasantly surprised. And we see that a lot in the feedback that say wow, this is the first time I've gone through a skills based assessment. This is amazing. All hiring should be done this way. But if you look at what percentage of the industry follows that best practice, it's still probably less than 10% especially outside of technical skills. So helping that space grow and embrace skills based hiring so that resumes can finally die is one of the big portions. Then you go into learning and on the learning side, we still have a lot of work to do to really help individuals build skills in a way that's comfortable for them.
[00:17:00] Speaker C: Wow, amazing. So go broader and deeper, obviously in this depth of the resume, in the skill based hiring, expand into the skill based learning like content wise and then the mobile app like Duolingo. I mean that's fantastic. So kudos to you.
[00:17:18] Speaker A: Thank you. Somehow we have like different bars and expectations for enterprise learning and for consumer learning, but it doesn't have to be that way. Right. I actually fully believe that you can build a fun, enjoyable and almost addictive learning experience that is about career relevant skills, that is about enterprise relevant skills. And there are certain core facts you need to understand about it. From the atomic learning idea, to the habit building, to the joy of getting the celebrations when you do something. There is a lot of research and learning science that goes into it, but it's been a fun journey to build it and we've already done it for the web based version. And everybody loves learning with Cosmo and shares their streaks. I mean, we already have users that have over a year long streak learning on the web with Cosmo and I can't wait to bring that to a mobile experience.
[00:18:18] Speaker C: If you haven't seen our listeners, if you haven't seen Cosmo, you've got to check him out because he's just amazing. So I love Cosmo. When I saw him, I'm like, wow, this is very cool. So is this like, is he like a dog? Right? So like this really fun, cute little dog that's helping you learn.
[00:18:36] Speaker A: He's a corgi. Who doesn't love a corgi, was the idea when we were thinking about it. But at the same time, from the name code signal to the name Cosmo and the Corgi, everything starts with a cl. So it was one of the things. But also he's a space Corgi. We've thought long and hard about a theme that we wanted to bring into that, that to make that learning experience more fun. And after a lot of research, we realized that space is the most unifying things we have as humans. That transcends cultures and nations and languages or reminds us that we're just humans from Earth.
[00:19:11] Speaker C: That's so fun. Yeah, I love those ideas too. So. Well, Tigran, this was so fun and I'd love to talk longer, but I think we need to wrap it up. So thank you so much for joining us on the podcast. I learned a lot about Code swiggle, about yourself, about how organizations can become more skill based and use skills assessment and skill building. So thank you. Thank you so much.
[00:19:34] Speaker A: Thank you for having me. This was fun.
[00:19:39] Speaker C: Thanks for listening in to this insightful conversation with Tigran Sloane about the power of skill based hiring and learning. I so enjoyed learning about Codesignal and how Generative AI helped the company to broaden their reach, enabling them to do skill simulation not just for technical positions, but now for all roles including management, customer service, sales and much more. It also allows them to create personalized assessments of development as companies rethink how they identify and develop talent. Solutions like Codesignal are really helping create more equitable opportunities for candidates and they also ensure that the companies find and develop the capabilities they they need. If you enjoyed this discussion, be sure to subscribe for more conversations. Until next time, continue to push the envelope and what works.
