Removing the Resume Gate for Better Hires with Jen Ayala, Clay

What if your hiring process was designed to screen people in instead of screen them out?

Jen Ayala, Head of Recruiting at Clay, joins Shannon to discuss why traditional hiring often filters out great talent too early. She shares how Clay replaced resume reviews with project-based evaluations for high volume hiring, giving career transitioners and new graduates a better opportunity to demonstrate their strengths while helping the team hire faster.

Jen also explains how AI supports recruiters without replacing human judgment, why hiring for potential creates stronger teams, and how designing a fair process can improve both candidate experience and hiring outcomes.

Key takeaways:

1. Screen people in, not out: Replace early resume filtering with practical assessments that help candidates demonstrate their strengths.
2. Keep humans involved: Use AI to organize information and speed up evaluations while leaving hiring decisions to recruiters.
3. Hire for potential: Focus on learning ability and unique strengths instead of matching every requirement on a job description.
4. Build together: Partner with hiring managers, recruiters, and cross functional teams to continuously improve hiring processes.

Timestamps: 

(00:00) Introduction
(00:55) Meet Jen Ayala
(02:12) Why traditional hiring screens out great talent
(04:18) Giving candidates projects before resume reviews
(08:35) Eliminating resume screening for high volume hiring
(12:05) Building an AI assisted project evaluation system
(19:12) How recruiters became stronger decision makers
(20:40) Candidate reactions to project based hiring
(24:10) Results from Clay's hiring pilot
(27:46) Where to connect with Jen

Transcript

Jen Ayala (00:00):

I think most traditional recruiting processes and hiring processes are designed to screen people out and filter out instead of screening somebody in and giving them a chance and building a platform for them to shine and show us what they're capable of.

Shannon Ogborn (00:13):

Welcome to Offer Accepted, the podcast that elevates your recruiting game. I'm your host, Shannon Ogborn. Join us for conversations with talent leaders, executives and more to uncover the secrets to building and leading successful talent acquisition teams. Gain valuable insights and actionable advice from analyzing cutting edge metrics to confidently claiming your seat at the table. Let's get started.

(00:39):

Hello and welcome to another episode of Offer Accepted. I'm Shannon Ogborn, your host, and this episode is brought to you by Ashby, the all-in-one recruiting platform empowering ambitious teams from Seed to IPO and beyond. I could not be more excited to be here live in New York with Jen. She has funnily, unlike a lot of us, I still consider myself a little bit as ... Yeah, in the recruiting space. She always wanted to do recruiting. She did not fall into the career. 10 plus years of experience in recruiting, six years leading recruiting and people teams.

(01:09):

She has spent her career building companies intersecting SaaS and AI. She has scaled the AI team at Bloomberg, doubled Bubble's headcount in a year and now at Clay leading the recruiting function and more than doubled their team this year from 300 to 700 plus in 2026. That's

Jen Ayala (01:28):

The plan.That's the plan.

Shannon Ogborn (01:29):

That's the plan.That's a plan. It's an impressive plan and I know you're going to do it. The thing that I love most about Jen is she really leads with her heart and wants to scale a team while keeping the wonderful and unique culture intact, really keeping recruiting as human as possible, which we're going to be talking about today. She cares very deeply about hiring people with diverse experiences into new to them roles, which we're going to take a little bit to. And DB believes in recruiting mindset being person human centered as much as it can be while still prioritizing building a wildly successful company. So Jen, thank you so much for joining us.

Jen Ayala (02:04):

Thanks for having me. I'm so excited.

Shannon Ogborn (02:06):

Well, again, our topic tonight is really around humanizing hiring and especially in the time that we're in now. Would love for you to speak to first when companies are thinking about humanizing hiring, why does this matter so much and why should companies really be considering this when they're building their plans?

Jen Ayala (02:25):

I think most traditional recruiting processes and hiring processes are designed to screen people out and filter out instead of screening somebody in and giving them a chance and building a platform for them to shine and show us what they're capable of. I think another thing that maybe keeps me up at night about traditional process is that we're, I think if we're looking for somebody to check a lot of boxes and go through a process and get a three out of four, three out of four, four out of four, then maybe there's a chance that we're also reverting to the mean instead of looking for somebody who's going to shine and spike in some particular way. And I think when I'm thinking about helping build a company like Clay, I don't want to revert to the mean. I don't want to screen people out. I want to screen people in and give them a chance to show us how wonderful they are and build process and opportunity for them to feel comfortable to say like, "Actually, I can't do this part of the role or I haven't done it before, but I'm really good at this other thing that is going to inflect clay in some particular way."

Shannon Ogborn (03:22):

And it's true regardless of whether you're talking about a high level knowledge worker role or a high volume role that is potentially more junior. And I know we're going to get to some of that today, but I know we've talked about how, especially when facing high volume, people's first instinct is to go straight for AI or go straight to the thing that's going to help them process the fastest.

Jen Ayala (03:50):

Yes. And I think that is an interesting way to use AI. I think AI for us, at least the way I'm seeing it unfold in front of us, you can use AI to say, "Oh, we can process lots of candidates and we can go really fast." But I think where we're seeing value at Clay is we can basically build an opportunity to get to know more people deeply and give them a chance to shine versus say like, "Hey, go do this AI project with an AI recruiter." We're saying, "Let's give you a really human experience and we will use AI to basically allow us to evaluate more people at the same time."

Shannon Ogborn (04:28):

And resumes have real limitations just speaking to the more traditional side, especially for new grads and career transitioners, it doesn't really tell you a lot about what someone can actually do. I know that you took some roles that were in more of those categories and you changed some of the process around them. Can you talk about high level first what Clay was doing with that?

Jen Ayala (04:53):

The challenge in front of us was we have a lot of hiring to do, right? We were basically going from 250 to what we thought was going to be maybe like five or 600 in a very short amount of time. And like all of you, we had a ton of volume and noise at the top of the funnel for roles that maybe didn't require a ton of years of experience. And honestly, we were sort of at a standstill. The process was so long. We had so many applications to review. We review each one, like human reviews each one and then we had to do recruiter screens and then we would have the manager talk to the candidate and then after what, like three weeks, then we get to like the meat and potatoes of the interview process where we start to understand what they are capable of.

(05:35):

So I remember talking about just generally the challenge of hiring at Clay. We had so much volume ahead of us and I was talking to Varun, our co-founder about this and he was like, "Wait, why don't we just give everybody the projects that we have that are hiding in the middle of all of these interview processes He's like, why don't we just let people show us what they can do? " And I loved that idea. I think his version of this would be, let's just do it for every single role and open source projects across the full slate of roles that are open. And I think maybe one day we will do that. I love the idea of being very transparent about what we're asking people to do, but I feel like this is a cheat code of saying, why don't we pilot it with one role first before we change everything about our recruiting process?

Shannon Ogborn (06:18):

Yeah.

Jen Ayala (06:19):

So we- It's a really

Shannon Ogborn (06:20):

Good way to talk someone off the ledge there.

Jen Ayala (06:23):

Yeah. I was like, yes, and we'll pilot it. And so we chose the product support specialist role, which was a high, we had thousands of applicants and it was a place where we sort of felt like we were sort of fitting our bills and not making the hires that we needed to make. And on top of this, we found out we needed to hire maybe double or triple the number of product support specialists that we thought we had to and we had weeks to make this change.

Shannon Ogborn (06:49):

Well, and I think some of this is really embedded in the philosophy Clay has of person first not role first. Can you speak a little bit to that? Because I think it's important context going into the sort of how of you implementing this.

Jen Ayala (07:04):

Yeah. I mean, if you go on LinkedIn and look at people who work at Clay, you'll find so many interesting stories of people doing a role that is new to them for the first time in their career, people who are doing roles that maybe don't exist in a lot of other companies. I have so many examples. We hired somebody who applied to an EA role to be our executive brand person who she's now helping all of our leaders show up on LinkedIn the way they're showing up. That was a bet we took. We met her, we got to know her, got to know what her strengths were and what she actually wanted to do and we hired to do that. And I think we just deeply care about hiring people again who don't just revert to a mean and meet the expectations of the job description, but they are going to show us something new and again, like inflect our business in some direction.

(07:57):

I think around the last time I talked to Verne about this, I think we have like maybe 50% of people who are in non-technical roles at Clay doing their job for the first time. On my own, on the recruiting team, we have examples of this. We just hired a software engineer to join the coordinating team. We have another coordinator who was an assistant principal who joined our team and it's so cool to see what they are doing to the perspective they're bringing to our team.

Shannon Ogborn (08:22):

It is so interesting to have those different perspectives and you start to piece together something where you're thinking more well rounded, you're thinking in a way that other companies aren't thinking. I think one of the best ways that people can get ahead at a company is hiring and the only way you're going to get ahead is if you're doing something different. And so like breaking through this traditional mold of the resume reviews, particularly for the role that you were just talking about, tell me a little bit about how it was done because you're not reviewing the resumes before someone submits a project. You're removing that gatekeeping entirely, which I think may be scary to some

Jen Ayala (09:04):

People. Yes, it was frightening. There are people in this room with me when we were like, "Okay, let's give this a try." So we said, "Okay, let's remove the resume. What value are we getting from looking at people's resumes?" And it's taking so much time. We could be using that time to review projects or to get to know our candidates more deeply instead and then scheduling a recruiter phone screen that can take days or a week. That's a huge time suck for us.

Shannon Ogborn (09:31):

Well, unbeknownst to some hiring managers, not everyone is available immediately.

Jen Ayala (09:38):

The hiring reader just at Clay know that. I

Shannon Ogborn (09:40):

Know, right? They're like, "Why isn't this person available right now today and the one time slot that

Jen Ayala (09:45):

I have? " Yeah, just simply call them.

Shannon Ogborn (09:46):

Yeah.

Jen Ayala (09:46):

Yeah. Just make it work. Too real. So we said, okay, instead of asking people to ... Of course we say, give us your resume, but we also say, "Here's our project. We used to gate keep this behind a resume review and a recruiter phone screen and the hiring manager screen. Just like show us what you can do. " And so we have a three part project that they complete. It's building something in clay in our product. It's having a conversation with an agent to simulate basically a support conversation where you're helping a user with a challenge they're having in the product and then an email, basically putting together an email to answer somebody's question about Clay.

(10:27):

Of course, we used our own product to build out how we evaluate this. I think the really cool part about how we put this together technically is that this is where a lot of people are using AI to score a project, to score a resume, to score how well this person matches. So instead of saying, "How did this person do on the project, give us a score." We separated each project out into its own score and then have basically an explanation of that score for each segment of the project that makes it a lot easier for us to dig in on where somebody's spiking or maybe didn't do as well in the project and it just made review a lot faster for us. So we're not in a position where we're like saying, "OAI just makes decisions on applications at all. " There's a human in the loop reading through the AI evaluation and then pretty much every time looking at the actual project that the person put together.

Shannon Ogborn (11:19):

Yeah. I mean, under the old process there were thousands of applicants. I mean, Clay is a very desirable company to work for, which is always a blessing, but then there's the flip side of that where you just get massive amounts of applications. How many people do you think fill this out?

Jen Ayala (11:40):

I think we've had like 5,000 applications for this role this year and we started this new pilot in February and we were now caught up in our hiring, which is a great feeling for this role.

Shannon Ogborn (11:53):

That's amazing. For this

Jen Ayala (11:53):

Role.

Shannon Ogborn (11:54):

Yeah. Well, the pilot, that's the point of the pilot. Yeah.

Jen Ayala (11:58):

Yeah, exactly.

Shannon Ogborn (11:59):

In terms of how it was done, of course this isn't something that recruiting can just take on a loan and expect it to work. Who did you work with internally to help make this happen?

Jen Ayala (12:11):

This is my favorite thing that so many people came together. I've been talking to my team about this. I feel silly coming up here and telling you about this project because I did not build this play table for AI evaluation of projects. I didn't come up with a project, like the team did it. We got buy-in from our head of support, George. He was down to, instead of reviewing lots and lots of projects, instead we asked him, "Can you review? Of course, we'll do some batch reviews, but then we're going to take something off your plate if you invest upfront." We have a program at Clay called the Wheel Rotational Program where we hire typically new grads, but also career transition folks to learn basically about just the go- to-market side of Clay and become hopefully the next generation of technical operators. And part of this program, people get to take on projects outside of their day-to-day, which is basically working on the support team and working on our version of an SDR team.

(13:06):

So one of the wheel participants, Adidi, she basically rotated onto our team to help us figure out how to build a clay table that could do all the eval work against the projects. And I think she deeply understood the project because she went through the actual recruiting process herself, which was very lovely to have her perspective. And then we actually had one of our tech recruiters was helping out with support because we had this big hiring push. So Max Geller helped us with basically project managing the whole thing and then Julia Moore, our former assistant principal/recruiting coordinator actually made sure that this was running smoothly for all of our candidates.

Shannon Ogborn (13:46):

That's a lot of people.

Jen Ayala (13:47):

Oh yeah. And Danielle, our talent scientist also, I think she was sort of like the creative mind behind visualizing the actual clay table and how we would execute so many people.

Shannon Ogborn (13:59):

So many people, but that's great because that shows that there's buy-in, that there's a lot of people involved. I think if you're just trying to build these things in a silo or you're building for your hiring managers, not with them, it really doesn't resonate as much as like, "No, I don't like this. Oh, it's too hard." It's like, well, it's going to be harder for longer unless we do the work.

Jen Ayala (14:18):

Yeah. Yeah. It was so easy once we came up with the idea and it was so clear that we should give it a try. But I think that speaks to our culture of let's try things and iterate. We have one of our operating principles is make it work then make it great. And I certainly think we're in the make it work section of this project, but yeah, it's just so nice to work in a place where we don't have to go through a bunch of bureaucracy or ask permission. We're just trying stuff. It's so much fun.

Shannon Ogborn (14:44):

You had spoken a little bit to building the evaluation system. So the really human part of this just going back a little bit is that candidates who may not previously get a chance based on their resume are able to have an opportunity to do this assignment.

Jen Ayala (15:04):

Yes. We're not saying you can't ... Who am I to say, "Oh, based on your experience that based on other companies' decisions to whether or not to hire you, I will decide whether you can go in our process." That just feels really bizarre to me, especially for an entry level role or like a career transition role. What do you even have to look

Shannon Ogborn (15:23):

At? Yeah.

Jen Ayala (15:25):

I don't know, what am I evaluating? It's hard to say. Something that comes up that I think about a lot is, golly, what if other people have, what if just nobody's taken a bet on you yet and you're wonderful and you're super high slope and just nobody has seen that in you because maybe nobody has picked up the phone to talk to you yet. And I love the idea of saying, "Yes, we invite you in. Come in and show us what you can do instead of making you wait."

Shannon Ogborn (15:50):

Well, I think if everyone's realistic in the room, we've all had someone take a bet or a chance on us. I know I have and it's made such a big difference in my career and it's amazing to be at a company that wants to be that for somebody.

Jen Ayala (16:07):

Yes,

Shannon Ogborn (16:08):

Absolutely.

Jen Ayala (16:08):

I think about the people that we've hired, like former web designers. We have an investment banker who's joining one of these roles.That's so ... I don't know. It's so

Shannon Ogborn (16:18):

Cool.

Jen Ayala (16:19):

I think I would have screened ... I think there's a world where we would have screened people like that out of like, "What are you doing in this pipeline?" And because they got the chance to show us what they can do, we're like, "Oh yeah, it also shows us that you're interested and

Shannon Ogborn (16:32):

Excited

Jen Ayala (16:32):

To learn more."

Shannon Ogborn (16:34):

On the more technical piece, you were talking about building the evaluation system and sort of the investment that required and of course you're using Clay to do that. Tell me about the process about calibrating the scores and things like that. Because I think when anyone thinks about scoring and AI and they're like, "How would I possibly do this in the most human, ethical way that we could?"

Jen Ayala (16:59):

Yeah. I mean, I think part of it is that we just haven't taken the human out of the loop. It's helping us move faster and frankly, I think in some ways be more objective, right? Something I thought about recently with high volume hiring, whatever process we have, we ask people to go through it and there's some level of fatigue I think with evaluating the same project over and over again. We're hiring

(17:25):

Over a hundred salespeople this year. We're hiring close to a hundred CSMs, right? For me, that feels like a lot. I talked to hiring managers and recruiters about this. A lot of our projects, we're asking people to be creative and so we're seeing a lot of creative projects over and over again, right? People come up with an idea that is creative and new and interesting, but of course many people have gone through the process and had the same ideas even though they're like, I think they're still very valuable. So I think we get fatigue of like, "Oh, I've seen this before, I've seen this before." The AI evaluation actually helps us remember like, "No, this is good." Compared to the training data that we have where we said this was a good idea, this was a great email, this was an innovative play table. I think that helps us stick to our rubric instead of saying like, "Oh, I'm so tired of reading about the same case study or

Shannon Ogborn (18:17):

Whatever

Jen Ayala (18:18):

It is. "

Shannon Ogborn (18:18):

Yeah, for sure. The AI doesn't get tired of

Jen Ayala (18:21):

That.

Shannon Ogborn (18:21):

Not that we're aware of anyway at all, maybe it does. Maybe it will eventually. That makes total sense. And from my understanding, you guys also took some of the human grading from previous instances and applied it.

Jen Ayala (18:36):

Yes, exactly. Yes. We asked our hiring managers to invest time in grading, basically grading each segment instead. The old way was you look at all the three different projects and the hiring managers look at all the projects and then wrote a scorecard and gave an overall score. So we had to ask them to segment out their scores of, what do I think of this piece and why? And then that fed our grading tool basically. So it was up investment and we have to keep doing that. We have to keep iterating a bit to make sure that just that we're continuing to improve the precision. What we've noticed I think is that our tool is very good at recognizing an excellent answer and an excellent project and good at recognizing something that was phoned in, but bad at the middle winged projects. We have to investigate those more each time we get a score in the middle.

Shannon Ogborn (19:32):

And the human still reviews it, as you already said, where does the recruiter come in to this conversation or this process?

Jen Ayala (19:40):

Maybe one impact of this project that I didn't necessarily expect was that the recruiter is now empowered to make decisions about projects when that was really the job of the hiring manager before and that's so cool that we learned so much about what the bar is for this role that we can now say, "Oh yeah, this is a good project. I'm confident that I know what good looks like now because I have all this training data." So the recruiter typically is the one saying, is pushing the person into the meat and potatoes part of the process now instead of asking the hiring manager to get to get involved. We still, of course there's education where we get the hiring managers involved too.

Shannon Ogborn (20:18):

How have candidates responded to this as a project? Because I know a lot of people in the talent space have concerns about doing bigger projects or who's going to drop off or who's actually going to fill this out and I think candidate experience as part of the humanizing experience is important. How has that panned out?

Jen Ayala (20:39):

I think about this a lot. I remember when I was 26 and I applied to a job and the first thing was a project and I was like, "I don't have time for this. " I give up.

Shannon Ogborn (20:50):

Yeah, that's

Jen Ayala (20:51):

All. That company is really great. And I would think about like, "Oh man, I wonder if I had put in the effort or if they had a different process what my life would be like. " So I think about this a lot. I think we have to keep in mind what the market is like for each particular role that we might roll this out with and what the sentiment is. I think something I recently got an email and inbox of, "Hey, we'll give you a screening tool, like an AI screening tool that does AI video interviews." And that sort of thing I know that many people are allergic to. Part of it is about our branding of it. We are saying we want to screen you in versus go do this thing that we won't talk to you until you do this. It's a lot about our posture and I think iteration two of this could be I have a dream that we have like a choose your own adventure so we can say, "Here's the traditional path that you submit your resume, you do a recruiter phone screen, then we get you into the process or you can do this like hyper speedy cool way and I think that would maybe make me feel better about asking people to do work before

Shannon Ogborn (21:58):

They've

Jen Ayala (21:58):

Even gotten to know us. I also wonder, I would want to think more deeply on this, but I want to think about what if people who we say, oh, maybe we reject somebody in a process and instead of rejecting them, we say, Hey, do you want to do a project and have this chance to like show us what you're capable of? But yeah, I want to be careful about how that feels for the candidate. So far candidates have ... I think 40% of applicants truly finish the entire project and we get to evaluate their project. And from what I'm hearing, people enjoy it because it's a chance to get in the product. Frankly, I think it's a cool project. Maybe I'm pilled, but I love the idea. I was looking through the projects a couple nights ago and yeah, it's so fun to see what recruiting can look or what a project or recruiting can look like now that we have these tools.

(22:57):

It's kind of fun to talk to a robot and then answer this question from a customer and get to know the Clay product a little bit better.

Shannon Ogborn (23:05):

Well, with all of the companies coming out with AI competencies and things like that where it's like, you must have used two different AI tools and like basically can't be ChatGPT or Claude and things like that.

Jen Ayala (23:18):

Is that in the job description? What are we ...

Shannon Ogborn (23:20):

Yeah, there's companies that are like- You just have

Jen Ayala (23:22):

Seven

Shannon Ogborn (23:22):

Years

Jen Ayala (23:22):

Of

Shannon Ogborn (23:22):

Experience with

Jen Ayala (23:23):

Claude kind

Shannon Ogborn (23:24):

Of- Yeah, of course, of course. And you're always going to see that, but then you're talking about especially entry level career transitioners, people returning to work. They're not going to have that, but that you're actually giving them an opportunity to use a tool that they can use elsewhere in their job search. Yes.

Jen Ayala (23:40):

Yeah. Yeah. We've gotten feedback that even people that we've rejected say, "Oh, thanks. This good prep." Now I know what projects are like for this type of role. This is nice to have.

Shannon Ogborn (23:51):

And you know what's good when someone says thanks for letting me do that project?

Jen Ayala (23:55):

I want everyone going through a recruiting process for it to be worth it to them. My dream is that people, everybody walks away with some new insight or learning or opinion even that they didn't have before.

Shannon Ogborn (24:07):

You had mentioned that 40% of applicants complete the project, which obviously is sort of a natural filter to people's interest, but what else have you seen as a result of this pilot?

Jen Ayala (24:21):

Our speed to hire has definitely increased so we can hire faster for this role. We have very high conviction now that if you do a good job on the project for this role, you're very likely to get an offer, frankly. So it's really great. It seems to be working really well for this particular role.

Shannon Ogborn (24:38):

And what about the hiring managers? Are they happy that they're not- They're so happy. Yeah, I'm sure.

Jen Ayala (24:43):

Yeah. I mean, we took so much off their plate. Well, it's so funny. We were just doing this this week of we had a batch of candidates that we wanted a second pair of eyes on and they were so happy to jump in because they aren't exhausted from doing it day after day, right? Now they have a smaller batch and yeah, it's like a quick favor instead of saying, "Hey, you have 20 projects to grade and saying that day in, day up to them." They're not-

Shannon Ogborn (25:08):

It's easy to pick up jaded in that situation where it's like, I know I need to do this because I know we need to hire, but that's a lot of work and then it's like Groundhog's Day, every day reviewing the same thing over and over again. It's like your perception might start to drift over time. Exactly. I know that you had mentioned as a result you feel like the grading is less biased because for those- I wonder. Yeah.

Jen Ayala (25:32):

Yeah, I wonder. Because I do hear frequently like, "Oh, I'm kind of tired of this project." And we've actually changed for ... We have a case study for another interview process and we actually changed it, I think, because we, the hiring managers and recruiters, we just needed a fresh start to not talk about that same company case study anymore.

Shannon Ogborn (25:50):

Yeah, that's fair enough. What does this look like moving forward? Because I know your co-founder's initial vision was-

Jen Ayala (25:58):

Everywhere.

Shannon Ogborn (25:59):

Get it out to everyone.

Jen Ayala (26:00):

Wouldn't that be nice?

Shannon Ogborn (26:01):

It would be so

Jen Ayala (26:02):

Nice. Radical transparency of here's ... I know Ashby does a great job of that, of here's the full process. So I think that is the dream. I think my dream is that we have an opt-in version of this instead of saying this is the only way to get in front of us. We say you can do it the traditional way or you can do it this new, fast, modern way. I think that feels like cozy and I don't know, maybe more candidate friendly. And I like the idea of doing this across other roles too. And I wonder who ... I don't know, we've hired a really diverse group of people since we've implemented this for this one role. So I wonder what would happen if we gave people the chance to show us what they can do.

Shannon Ogborn (26:36):

It sort of is a callback to the billboards that GitHub did. We had an episode with Kiana Johnson about this. Obsessed. And people drive by the billboard and if you want. If you don't won the challenge, then you got fast tracked into the engineering and it was like a lot of people who actually weren't engineers.

Jen Ayala (26:55):

Yeah. Uber did this back in the day. If you got into Uber, then you'd get a coding challenge in your car while you were taking your ride. I want to figure out a way to do that that is fun and yeah, it feels more like Clay. I think that's like it's kind of silly to just have a little more fun.

Shannon Ogborn (27:12):

But when you break out from the traditional recruiting processes in a thoughtful way that's still a solid evaluation of, can this person do this job? They may not have to have done it, but can they do it? I think that's where you start to build a generational company because you're pulling in candidates that other companies are constantly overlooking.

Jen Ayala (27:32):

Yeah, absolutely. I don't know, maybe we'll do a puzzle hunt and the winners get a fast track. We could have so much fun with it and still have something that we feel is credible and we can build conviction on.

Shannon Ogborn (27:44):

Yeah, 100%. Well, we were coming up on our time. Where should people go to learn more about you and your work in Clay?

Jen Ayala (27:51):

We have, of course, LinkedIn. We have this series on YouTube called Clay, How Clay Uses Clay, like Clay for Clay. And I think that's a cool way to learn about our use cases, especially the recruiting use cases. And yeah, I guess that's where to find me. I do post sometimes. I feel like I have to really stew on something before I decide to go out there with it. But I think I'm learning a lot from Varun and the other execs at Clay who put their hot takes out there. Just

Shannon Ogborn (28:16):

Rip it.

Jen Ayala (28:17):

Yeah, exactly. I don't know. We talk a lot about dessert at Clay on LinkedIn. So I think, yeah, come join the conversation, join the dialogue there if you want.

Shannon Ogborn (28:27):

Well, Jen, I cannot thank you enough for being here and being a live guest. Humanizing hiring is getting increasingly more important and people are getting more hyper aware of this just with everything with AI. So I think this was very helpful. Thank you.

Jen Ayala (28:42):

Thank you for having me. Thanks for coming.

Shannon Ogborn (28:48):

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