Why Most Companies Are Optimizing Hiring the Wrong Way w/ - Kristen Habacht: CEO of Elly

Speaker A: All right now, Kristen, this is great. I am super, super, super excited and blessed. I start off every podcast with the same little rant. Um, I'm always just very honored, very appreciative, very surprised that there's all different types of people that find a way to want to talk to me about all different types of tools, technologies, services, brands, leadership, just whole wide world of HR and recruitment. And I'm always very appreciative. So uh, I'll say that again here to you and I think the way that I'd love to start this is please give us a little bit of a high level perspective on who you are. A, uh, little bit about the brand, a little bit about your background and anything that you think we should uh, know about you before we get going.

Speaker B: Sure. Yeah. Awesome. Well, thanks for having me. Um, so, yes, I'm Kristen Hayback. I am the CEO of uh, Ellie AI. Um, Ellie was kind of born of trying to help recruiters use um, AI in a way that helps them be better at their job, not replaced them from, from doing their job. And we've spent a lot of time with recruiters, um, working and building that out. Before Ellie, I was the Chief Revenue Officer at Typeform. I was the head of um, ah, enterprise Development reps at Atlassian. I was the VP of Sales at Trello. So I've been a hiring manager, never a recruiter, but a hiring manager for the vast majority of my career on the go to market side. And um, I really realized, you know, as I think everyone who's built out a team does, that like the people part is just as important as the thing you're selling part. Um, and trying to figure out a way to help people hire their best teams became something that I just care a lot about because I've seen the difference it can make when, when you have an amazing team behind you versus when you've kind of struggled to fill that.

Speaker A: I love that, I love that. And I already have one random question that just popped in my mind. Um, your background just actually triggered this. So in a good, in a good way, not in a bad way. Um, I've always had a perspective that hiring, recruiting and hiring, sales, marketing and product roles are some of the most difficult to get right. But when you get them right, obviously you can have a great run. And I've always wanted to see a, uh, tool kind of like uniquely, you know, find themselves comfortable just in that pocket because I always felt like they were unique elements to those roles that were hard to get right. Have you ever had that perspective, not being in that, those positions and shoes.

Speaker B: Yeah, it's interesting, right, because I think, I think it sort of depends on what your background is. Um, I do think sales, marketing, um, those are really, really hard roles because there's not necessarily an easy way to test for the skills like you could with an engineer, for example. Um, you know, it's kind of like the difference between a math test and an English test. Like one, it's, it's kind of binary. If the answer is right or wrong, one is a little bit more subjective. And so I think, I think because those sides of the house are a little bit more subjective, it is really hard to hire for them. But I will say I've, I've met founders who maybe are not necessarily technical who are out there trying to hire their first like AI engineer or you know, full stack engineer. And because they don't necessarily know what good looks like, it's really hard for them to hire those roles. So I would just say like, yes, I also think it's a little bit of like what do you know and what do you have experience in? And that can be really hard too. But um, but yeah, I think that's why people lean so heavily on, especially for, for go to market stuff. Um, you know, the, the good word of some other person like oh, so and so said this person was great, so we should look at them just because it's, it's really hard to test if they're really able to do the job or not.

Speaker A: No, that's a good call. Let me ask you one more random question on that. Um, and I, so a little backstory. So I've, and I think I told you this behind the scenes. I've probably built out I think 17 or 18 different types of brand services tools trying to solve a couple different things in this general space. One thing I've always tried to solve is timing. Um, I think when you have someone that's technically skilled and have the background, I've always felt, and I've seen it, not even just felt it, where it's just the wrong timing of that person. And I think we've started to become a little bit more intelligent as we've, you know, developed brands to kind of say, you know, what there is, you know, there is a different type of a person that fits better at a series. Ah, A versus an enterprise. Right. Um, and then also I think there's a better nuance around timing when it comes to just, I call it kind of like behavioral timing or just, just then make that simple ver, you know, verbiage of it. Like just the gut feeling of where they are in their lives. Do like, can they push through another growth phase? Yeah, right. Um, they always have been in series A, they've. Or series B, they've always done it, but now they have three kids and they're kind of like, you know what? Right. So what are your thoughts on all that?

Speaker B: Yeah, I mean that, that's absolutely right. That's why I think it's so hard to just look at people's resumes and say like, oh, this person's going to be a fit or this person's not going to be a fit. And because I, I've had people who I have personally worked with and I've brought to other companies when I've changed companies that I wouldn't bring to Ellie, for example, because I just know that like, we maybe lack the structure that they would need to be successful or we would lack the brand awareness or we lack whatever it might be and that they're amazing, you know, salespeople when they have, um, a little bit of brand and some maybe, you know, um, marketing materials and some other stuff. But that doesn't necessarily translate to certain super early stage and vice versa. Right. So, like, I've seen it with real world examples of like, somebody can be an A player at this kind of place at this kind of moment and be a, you know, a D player, the same exact person, um, at a different moment in time or at a different place. So that's why again, like, it's really hard to kind of like just look at a candidate, look at a LinkedIn profile and be like, oh, that's my, that's my guy. Like, I gotta get that guy over here. Because it's just, it's not that straightforward.

Speaker A: Yeah. And, and the thing, I'll end on this and let's maybe go backwards into to how, you know, Ellie and the brand was even thought through and created. Um, I've seen a couple different folks try to solve this in not necessarily a technology format, but more try to solve it with just how they go about maybe let's call it the beginning stages of the recruiting process or even testing. So I've seen like Jason Freed from Basecamp talked, uh, a lot about how at the beginning stages of Base camp, you would actually give people like, I think a two, two month run of kind of, hey, we're going to bring you in. Yeah, it feels great right now, but I'm going to be transparent and you should be Kind of transparent with yourself, your finances, your family. I, I've always loved that because it, it's probably a little scary for, you know, the, the individual contributor or the manager or lead or whatever role they are. It's probably a little scary for the, for the applicant. But it's also a very transparent, I think, way of saying, you know what, I'm, I'm aware that this might not be the right time here, but I'm willing to take a little bit of a gamble if you are. Um, um, I don't know, what are your thoughts on that?

Speaker B: Yeah, I think, I mean it's, it's a thing I do as well. Um, um, I think especially if you're hiring early stage, um, I think you kind of have to be, you have to be transparent with people about that. You have to say, like, yeah, we're, we're both taking a little bit of a risk on each other. Um, I, um, think it's different, you know, obviously the more established of a company you are, um, and there's this different expectation set of the stability of the role and the stability of the company. But that's why when people say, you know, to me, oh, I've always wanted to work at a startup, it's like, I really dig in to what that means because some people can consider, um, OpenAI right now a startup and Ellie is startup, right? And it's like, let me tell you, there's a very big difference between where Ellie is at and OpenAI is at, for example. And so I think it's, it's a shorthand for a lot of people for tech or for like maybe a non public tech company. Though even when I was at Atlassian, we had been public who were like, I've always wanted to work at a startup and it's like, are we a startup? So we used to debate this like, uh, are we, it's just like, when are you not a startup anymore? And so I think that even candidates don't fully always understand that not, not every startup, not every Series A, not every Series B, whatever it might be, um, is the same or has this the same amount of stuff figured out or the amount of risk that you're taking on. Um, so yeah, I always try to be super transparent and I will also often say, like, listen, like, you know, you're going to give it your best, I'm going to give it my best. I'll give you feedback along the way. There is a chance this is just, it's just not going to work. Not because of anything you did. Like, we just, we don't know what we're doing just yet either. And I think that has to be super important as an expectation when someone comes in.

Speaker A: Yep, I think, I think you're right about that. And so I guess the, the nice bow we'll put on this is whether it's your tool that I'm sure has some elements in that, uh, and then whether it's other tools or just more of a framework. Right. Like if there's any, there's any recruiters, folks that are more in the hiring manager onboarding stage. Right. I think that ramp up time, I think those first 60 days are so vital. Like, I just, I've, I've always thought about the second, the first and the last interview, the, the beginning of like what they feel when they even see like more of the employer branding, filling out the, filling out the application stage and then that first 30 to 60 day window. I've always felt that there's just so many complications there that we should keep trying to figure out as uh, technology builders and thinkers in those categories, you know.

Speaker B: Yeah, I mean, I think the candidate experience, um, is one that I think in tough times, you know, it's like the housing market, right? It's like when there's lots of houses on the market, when there's lots of, um, jobs on the market, you know, it's a very different experience than when there's less. And I think right now what you have is a mix of there being a lot of people, a lot of talented people who are looking for, for jobs right now. And so I think you see a lot less investment in tooling and thought, I think generally around that, um, candidate experience, what you're seeing is a lot of people trying to figure out how to optimize for the volume of the candidates that they're getting. Almost trying to like filter and get less people in through a lot of this stuff is becoming like the message that you're getting. And so I think like that piece is kind of fall by the wayside because there's a glut of folks out on the market. I think that's going to shift. Um, and I think there's going to be some rules specifically that you know, like an AI engineer where people are just, there's not many of them and people are desperate to get them. Um, and so I think there'll be a swing to like, all right, how do we, how do we make this, you know, less friction or how to be more transparent or whatever it might Be. But I think you're in a moment of slight imbalance right now that's kind of causing that.

Speaker A: I agree. Okay, give us. So give us some of the origin story. Give us some, uh, give us some of the good details in the ideation phase of this.

Speaker B: Yeah. So, um, Ellie started, you know, originally from the sense of, like, what roles are kind of where there's repetitive work that even the people doing it don't necessarily want to do it. And what are those things and how can we help? And so the first thing that kind of came to mind was recruiting because it's. It's very similar to sales. It's a lot of the, uh, it's a lot of the exact same. Like, you have a conversation, you have to take really good notes. You have to update your system with your really good notes. You need to have, like, those really good notes go to different people, whatever. Um, and so the first version of. Of Ellie was. Was just a note taker. And I think we've gotten very numb to note takers now. I think if anyone's listening, has the same experience I do, sometimes I'll join a call. And there's literally more note takers than there are attendees in that meeting. So, like, we've gotten to the point where we're very used to note takers. When Ellie started, it wasn't the case. They were. They were really like, nobody kind of had them. Um, and it originally started to just, like, optimize a process that nobody liked, which is that recruiters didn't like to take the notes. They had to do it. They wanted to be engaged instead. They wanted to be able to make eye contact with the candidate. They want to be able to ask thoughtful questions instead be jotting down everything all the time. So that's the origin of it. Now, like I said, a lot of note takers have come out since then. And so then recruiters were asking us for. For more. Right. Oh, we have so many candidates who are applying, and a lot of them are not real. They're fake candidates, or they're people who have exaggerated their background or whatever. Maybe they're using AI to kind of like, pump out a million resumes that match. How can you help us filter through that? So then we rolled out our. Our interviewing tool, um, and then we rolled out our AI sourcing tool so that you could find better candidates off the bat. Um, and eventually it just kind of became like, hey, wouldn't it be cool if this was all in one place and I didn't have to Also use another ATS or whatever it might be. So that's sort of the evolution of where Ellie has, has come from. The final step of it is really, um, a lot of these teams are also underpowered and they want to have additional help, but they don't trust AI to make the judgment. So we've, um, we actually can partner our software with real human services where an actual, real person, um, can either help you find candidates or you know, verify the candidates are who they say they are or do scheduling, whatever it might be. Um, and so we kind of combine that with the software and have this algorithm that's trained on what you need help with, but it has a real person who's done the implementation and the legwork through your actual process, um, so that hopefully you feel more comfortable with the data that it's producing.

Speaker A: That's super fascinating. And what really, what were you finding during like the note taking phase that, that allowed you to kind of centralize on some of that, you know, AI source or AI like, like where, where did that come, come about?

Speaker B: Yeah, it really, it really came from conversations with customers. And I think we were, we're so lucky. I've, I've built in so many spaces and I've, I've built a lot in engineering teams specifically. And like engineers don't want to talk to salespeople, they don't want to talk to marketers, they don't want, they don't talk to anybody. Um, well, it's been so, so lovely is that recruiters are very generous with their time and they're very willing to give feedback. Um, and so what we really found was just people were willing to talk to us about what was hard in their job and what parts they felt like had to be run by humans and what parts they felt like they could outsource to AI, um, and what parts they were maybe not so sure about and that were kind of in that in between. And so we started first with really the things that people are like this 100% could be done by AI and so things like sourcing, which right now is like a very rote process. It's a lot of list building, it's a lot of outbound. It's a lot of things that like an AISDR basically is doing on the sales side. So no different. Um, and nobody felt protective of that. Everybody was like, please help us with the top of funnel. So it was just a lot of those conversations. And I think the thing that we kind of consistently heard was, um, going back to that branding idea was that really the most important thing was that the candidate had a great experience. And so trying to minimize anything that would be less than that. And so the notes, in a way help that. Right? Because even though there's an AI note taker on the call, um, it means that, uh, answers are being captured accurately, um, that, you know, recruiters can stay engaged in the conversation. Um, um, so we tried to make sure anything we rolled out kept that at the core of it, which is that, you know, the human connection and the employee, the candidate experience was going to be the most important thing.

Speaker A: That's super, super, super fascinating. I do agree. Right. I think I bid on all sides of it. Right. I've been on the sales side, the product side, the recruiting side. You know, I would agree that recruiters are very generous at times with their time. Um, they're always very curious around how to make things more efficient. Do you. Do you find now where the product is now? Where do you find yourself? Um, I always ask this question because now we're in a marketplace where there's many tools, right? There's many tools that reflect each other, that are identical to each other, that are adjacent to each other, that are direct competitors, all different things. And now as I think about my audience, where I am in my career, I'm. I'm finding myself becoming more attracted to, like, niches and like, nice little tight buckets that services products, brands, experiences, activations can kind of live depending on, uh, the mood of a, of a human being that might lean into a product or a service or the problem that you're solving. Um, so how do you think about that for what you do? Because there's many different brands and products in this category or the categories that you cover. What. And not just kind of like the, the early stage and all of that, but like, what's more of a niche or pocke that you find yourself very good at right now.

Speaker B: Yeah, it's a good question. I think, um, I think as AI tooling makes it easier for people to build companies, um, you do find that these niches kind of are becoming more important because the only thing you sort of have that can only. That can be uniquely yours is a little bit of, like, the culture of the company you're building and the choices that you're making. Because, like, anybody can go, and anybody can go make what we make, right? Like, generally. Right. Like there's. And I think that's true of just about everything. Like, I could use AI to make my. To make Jira for me. Right now, like, you know, the things that were proprietary, I think, are less proprietary anymore. So all you have is kind of like, yeah, little niches. You. You maybe you have the best network of salespeople. To that earlier point of, like, we really know salespeople, and that's what we're going to find for us. I think the thing that we're really leaning into, whether this ends up being right or wrong, I don't know, is that, uh, a lot of these brands are talking about replacing people. That is their thing. They're like, you do not need recruiters anymore, or you'll need less recruiters or whatever it is. I think our piece is this hybrid of like, no, you'll always need people to talk about your company and to identify the best people for your company. That's not ever going to go away. Um, but the tools that you were using before, like, you know, let's say you were using an ATS before, it was always filtering people out. You didn't have to wait for AI for that. It was using keywords or something else. What we need to do is make these tools much better so that recruiters can spend more time doing, you know, selling the absolute best AI engineer candidate, because that one's going to be really hard. And that's more of, like a sales job now than it is, like a filtering job. Or maybe they're at networking events so that when they are ready to open up the next role, they already know the top five people, things that they couldn't have been doing before because they were stuck in this purgatory of kind of digging through stuff. And so our. I think our niche that we're trying to build out is really this, like, human centric energy around AI, which is maybe at odds with each other. And that's why we have this service offering where we're basically saying, like, you know what, you're right. Don't just trust that the AI is configured the best way possible. We're going to give you an actual, real recruiter, kind of like what Clay has done. If you're familiar with Clay on the skill side, where Clay has basically said, like, we're going to give you this, this engineer, this, you know, go to market engineer who's going to set up and make you successful. We're basically doing the same thing, which is we're like, hey, the AI, you're right, is only going to be as good as you set it up. And you're not the expert in setting the AI up. We have an expert who's done this, who is a recruiter. And they're going to do this by helping you find a person. Because the best way to train the tool is to put it through an actual search. Um, and that way, at the end of the day, you have a person, but you also have this algorithm built. I don't know anybody else doing that right now. I think that's unique to us. And so I think that's the niche where we're, we're trying to play and.

Speaker A: Hold on, hold on, hold on, hold on. Okay, hold on. Okay. You and I have Talked, I believe, two times. Very insightful, deep, like 40 minute conversations. What you just said, how did I miss that part? So you're telling me. Okay, hold on now. This is. Okay, this is the first time, uh, audience here, I'm usually very good at this, but I think I missed something. So you're telling me that at that stage of someone deciding to utilize your tool, you all will then go and find the potential ideal applicant that the organization is looking for just to be able to train the I AI better contextual for that company?

Speaker B: Yep, that's right.

Speaker A: Okay. I don't curse on this. Actually, I'm not gonna curse. I was gonna say, you know, so one thing weird, uh, random story that just popped in my head. Uh, Will Smith made a promise to his mom that he would never curse on, uh, his rap song. So that's why he's never cursed. I made a promise to my mom after being a filthy mouth on the football field, uh, that if I ever did something publicly, I would never embarrass her. So I was about to drop a big F bomb. But, um, I am very impressed with that is what I'll say. Uh, that. Wow, that, that is interesting. Okay, so here's how I would think about that if I were an organization. Let me just play this out. So, uh, this is super fascinating. Okay, so if I'm looking for an ae, let's just go down this sales pocket. Um, and I have clear frameworks of the AES that have historically worked well, that currently work well due to our timing. I just have a bunch of data. I just think I, I have a perspective. Um, but I don't know how to either a, bring all that data into like a very tight pocket. I'm just busy. Or I can explain that to you and you can go find that person. Or maybe I can even bring you that ae. You can interview the ae?

Speaker B: Yep.

Speaker A: Right. So then you're just creating that, that knowledge corpus, if you will, and Then you're okay, I'm getting it now.

Speaker B: Yeah. The most common one for us.

Speaker A: Yeah, talk to me.

Speaker B: That we're finding is that, uh, it's the. From a niche perspective, it's a lot of founders, often first time founders who maybe don't necessarily have that network for every role. Right. So like we're working with a company right now. Um, the guy's great, the founder is great. Um, but they're looking to hire an iOS engineer. And he's like, I don't have anybody in my network. I don't even have a network that has a network that has an iOS OS engineer. And so, um, this is a rule that maybe he would have gone to an agency for before and paid 20% or whatever on it. Um, but instead we've kind of said like, okay, we'll go find your AI engineer for you. So we'll source them, we'll interview them, we'll calibrate with you, we'll run the whole process. Um, and by doing that, we'll also set up the tool. And then you're not paying 20% to an agency, you pay 20% to an agency. You've paid them like what, you know, a huge chunk of change that affects your Runway. And all you got was one person out of it. You didn't actually get like a system or a sense of learning or anything. And so when we do this, the idea is that you'll get the person. And then in a couple months, hopefully when things are going well and you need to hire that second iOS engineer, everything's already built for you to be able to do that. And it works for other roles too. Obviously the algorithm is there, it can plug in for, for any other role that you're hiring. But the idea is, it's like we're going to teach a man to fish. We're not just going to give the guy a fish and be like, good luck. Like, hope this sustains you for a long period of time.

Speaker A: I fully, fully, fully agree for that. Agree with that. That is so fascinating. And I think where my mind is now going, I could, I can imagine how that creates. Is that, is that during the sales experience, when you're talking to a recruiter or head of people or a founder, have you found that competitive advantage or that nuance has a response that people feel great about? Are they, are they skeptical of. Is there some, like, how are they feeling about this part? Because this sounds like to me a no brainer. Because everyone's talking about just AI and the fears there you're now bringing both to the picture.

Speaker B: Yeah, yeah. I mean the response has been really, really positive. I think what you are finding is that um, there's always kind of only been, you know, whatever. Call it three options, um, when you're hiring, especially early stage. One is to pay an agency, which is expensive. Two is to just do it yourself. And I mean I, I am a founder. Um, there's so many other things pulling your attention and, and hiring is super important but it's also very labor intensive. And then maybe you're also doing a fundraise, maybe you're also trying to get your revenue where it needs to be to be able to do your next fundraiser and there's just so many things going on. Or the third option is to hire an in house talent acquisition person. And unless you have a very clear line of sight of like consistent hiring that you're going to need to do, that's just not a viable option for a lot of people. And it certainly isn't going to be. Most companies, you know, third or fourth hire that they make is going to be an in house TA person. And so you've kind of only had these three options. Do it yourself, pay an agency, hire an employee to do it full time. Um, and AI has kind of come up with this like, well, you can do it yourself but AI will really do it. But at the end of the day, like bad data in, bad data out. If the founder doesn't know how to run recruiting, you still have the exact same problem you had. And so what we're trying to offer is this kind of fourth option where it's like, it's human enabled. It's, we will train you honestly a little bit in how to build almost like a fractional head of talent, like how to actually do this thing. If you want to keep using us for the services and we'll hire a bunch of people for you, we can do that. But really our thing is that uh, we give you the tool and you can go do it then afterwards yourself if you want to or you can use an in house person eventually, whatever. But you've not dropped hundreds of grand on an agency that like, you know, there's a guarantee for some period of time about that employee but you know, not, not forever. Right. So really it's like that, that person churns. You're just straight about all of them.

Speaker A: You know what's interesting that that was literally going through my head when you were breaking this down. Uh, well, another thing too. Good, good on you for Making that call. I've. So I. Okay, let me give you a couple quick stories. M. When I had. So shout out to Michael, shout out to Mic. Uh, uh, so Mindstand AI was a company that we had back in 2018. Microsoft, uh, gave us a bunch of cash and hope and dreams of trying to find a way to go into Slack channels, Microsoft Team channels and look for like microaggressions and all these cool things.

Speaker B: Right?

Speaker A: Um, and I kept thinking throughout that phase of my life, now this is, we're now in 2026, we're talking a long time ago. I was thinking at that time, do people even know the power of what we're giving them? Like, will they even know? Okay, when the microaggression comes across, like what, what do they do with that now? Do they even know how to approach the conversation of the leaders that keep providing those microaggressions as creating this uncomfortable experience? Do they even. Like I was always thinking AI plus Human, right? AI plus more like of a niched M, you know, understanding of that issue. So with that product I kept trying to push Microsoft, some of the advisors they sent to us, um, to say, no, we need to, we need to have a consultant that sits with this product. We can actually get more money for the, for the potential contract because we're not only giving them this tool, but we're enabling the tool, we're enabling the data and all of that. Everyone was telling me I was crazy. Now they've told me I was crazy quite literally up until recently as, ah, six months ago. Not these exact same people, but like generally people in the space. And you are one of the first companies and I'm starting to see this a little bit more now, but you're one of the first people that have like naturally kind of gone there. I want to ask you a question and I'll finish my rant. Did you, did you get any pushback when you decided to go there? Was there anyone in your corner that said, no, I don't think that's the right path. You don't have to say their names.

Speaker B: But yeah, no, I will say I think the biggest thing, um, right, super candidly is at the end of the day we're a venture backed company and venture backed has historically not liked services, revenue. Um, and so I think the question was, hey, if we go and do this, does that complicate anything? Because I think we really believe that this is going to be the way a lot of AI tools actually are going to end up going, not just Us and I think that we were very fortunate because um, this happened right around the same time. I think it was um, Sequoia maybe had put out um, some, some an article and some um, studies around basically the future of software is services. And this idea of like a lot of. Because, because uh, the thing we were talking about earlier because this like there is no real moat around software anymore. That the real moat is come from having these services as part of software and the implementation. And like I said, it's similar to what Clay is doing, it's similar to what Monaco, which is like an AI native CRM is doing. And so I think because this moment in time kind of came, that they understood that and they were fully supportive of it. I think if we had honestly even tried to do it six months earlier, I don't know if it would have been as easily because I've been in companies before that tried to do services and they really generally are kind of looked down upon traditionally by investors. So I think that was the only group that if there was a risk it would have been from them. Um, but we were fortunate enough not to have that kind of dynamic.

Speaker A: I have a very blunt statement to not your investors, but investors generally around this. Um, I think I know you like scale. I know the multiples and the financials on that from like the math spreadsheet perspective. I get it right, I've been in those rooms, I get that math. But I think we also need to start finding the investors and the angels, the VCs that really understand, in my opinion, like brand. Because what I just heard you say from a AI as well as having the human in the mix is you'll create more long term brand because you're not just to your point teaching them how to fish, but you're actually kind of fishing with them to a certain degree to really build out that full capability long term, which will actually either keep your product there longer term or even if they decide to remove your product, they will always remember you as the one that enabled that learning, which in my mind there's a way long tail on that that I could put my investor hat on to, to think about that long tail. So I don't know, like, I just think we need to see more investors, think a little bit more brand, long tail rather than just kind of like math in the beginning. Do you agree with that?

Speaker B: No, I totally agree. I totally agree. I think that's right. I think that um, I think there are certainly a number of investors who have always understood that and I Will say like for example, let's pre. AI if anyone's familiar with Type Form. I think Typeform is a really great example of that which is like at the end of the day this is a form. It's the thing that literally a million companies give away for free. Um and Typeform was able to build a really successful big business because of brand and the concept of this being the form, the most beautiful form or the form that understood your business the most, you know, and that it would give your customers the best experience and people who give their customers the best experience have the best businesses. And I think that um, there have always been a set of investors who really understood that and I think that those are the folks that are going to do really well um, in this change because the SaaS apocalypse stuff, you know of like hey, software is just not going to grow the same way software used to grow. I think a lot of people who understand that the brand it can be bigger than that will be the ones who invest in the right founders who do the right things. Hopefully long term.

Speaker A: No, this is right. Okay, so that's. Let's keep leaning in. The last thing I'll say on this from a different angle is what it's now making me think about. Like, like if you were to bring me in from like a go to market perspective, my brain is now going to where are the industries that over index on being the most comp. Like. Like where are the industries that have the most complicated roles to fill and it's not because of how many of the roles they have to fill. It's the, the nuances that a human being. Like there's a bunch of messy middle there.

Speaker B: Yeah.

Speaker A: Um. Because my brain would go to your tool helps that recruiter now have a bit more m. Like mind share to be able to like really figure out some of the more complicated nuances of that role. Um and then you actually have the human being element to now come in to even help do more of that strategic coaching with that thinking partner. Um, and there has to be a number of industries that uniquely have certain roles that have always historically given those industries and those brands trouble.

Speaker B: Yeah. And it's.

Speaker A: And it's not just trouble from. Okay. They're you know we have to hire a bunch of them or like it's difficult to scale and it's not even like just the fact of like maybe they're hard to find but maybe they're hard to. To. To our earlier conversation. Maybe they are hard to onboard because of the right fit. Maybe there's just a lot of nuances of the timing of these types of roles which would then tell me they, that the recruiters probably need to do more of the human part. Right. And build and build their skill sets there. So I don't know, you see, I'm thinking in real time right now.

Speaker B: Yeah, yeah. I think it goes back to the conversation earlier, which is like, I think it gives, if you don't have a recruiter and you're the founder, for example, it gives you more time to really like sell the vision of what you're doing and you know, even though it's risky, why it's the right risk for this person to take and you know, all that kind of stuff or you know, if you're that go to market founder who's never hired engineer, if you're an engineering hire who's never hired a go to market person, you know, it gives you that time but also it gives you an expert partner to help you figure out how to do it. But I think at ah, the end of the day, right, let's, let's take like an AI engineer. There are some roles right now that everybody is trying to hire. And so the hardest part of that job is not necessarily getting that person interested. It's going to be that first connection where you really are selling the opportunity to the person. And so we believe that like the person still needs to be right there in that moment to sell and to pitch and to excite and all that kind of stuff. Um, and that's a lot when you're asking that founder or that TA person to also be hiring three other roles and they're all super important and they also are doing all their own pipeline. And so that's where we feel like we can, we can help you with a real person, but also with the tooling to make it faster long term.

Speaker A: So let me ask you a little bit of a different question. Within the tool itself can so will you bring, you bring in someone to kind of help find the person that you think would be a great fit for this to kind of like build out the AI model a bit more to make it very contextual or you download some data or maybe you have someone internally that's already a perfect reflection of what you're looking for. However you get it, is there a way for, is there a way to keep having that learn on? Like is there a way to keep having the data plug in where a recruiter or ahead of people now even with the current people can just keep storing capabilities and Knowledge about who's going to be a great fit here at what times. Is there a way for it to keep growing?

Speaker B: Yeah, I mean uh, the ideal situation is that you then use it for your next hire and your next hire and it continues to, to learn based off of that. So whether you use it with your existing ATS or whether you replace your ATS and use it, it kind of can do it either way. But then the idea is like, okay, well you know, Ellie helped us, Ellie had a person who helped us with this thing. But now we're just going to use the Ellie tool to hire the second account executive. And so there are some scoring pieces that are already built and all that kind of stuff. But then you'll run through the process with that next person, um, and you know, it'll learn from that. And then when you go to hire a third account executive, it's better than it was even after we trained it on the first one. So yeah, the whole goal, and that's where I think AI is uniquely suited to do this. Well, versus like a flat ats, uh, above before which is that it can learn, um, and it can take into account the changes you're making versus just being like a filing cabinet for the data.

Speaker A: This is fascinating. Yeah, you're right. You're writing. There's even so much then that could go into, I mean from like a people analytics perspective, I can even see how you know, you're taking on a founding team. Like what's your typical organization size that, that, that you're finding consistently that you're able to um, help support, convert business with and be able to help them place the right talent. Like what, what is, yeah, a typical size.

Speaker B: Yeah, the real sweet spot is um, kind of any size company before they've brought on an in house ta person. So that tends to happen around 50 employees. Sometimes it happens later. Like we're working with a company right now that has over 100 and doesn't have an in house TA team. Um, but you know, it's, it's usually around there. We do um, help larger companies. We tend not to do the services piece with them because they've already, to your point, they've already got a ton of this data. So it's more of us just ingesting that data and helping them out with that. Um, but like the real sweet spot I think to help the most is kind of that before you have an in house TA person, maybe you have a fractional person, but, but usually it's, it's the founder or the head of that team is doing a lot of the hiring.

Speaker A: As you go up market though, couldn't you bring this to, couldn't you bring this to a larger organization that maybe has had a rough two, three years of placing certain key roles, roles and, or a lot of change management or maybe they've acquired a few brands. I could see this being a tool that's used like for like a refresh.

Speaker B: Yeah, yeah, absolutely. Yeah, we definitely can and we help larger companies, um, that, in that. So I would say yeah, for sure, we definitely can. Um, but it's more just like you tend as, as you get bigger, there tends to be more bureaucracy in that process. Uh, and so just like from a, from a right now moment, the smaller, the smaller companies are just able to move faster and be more agile around things like this.

Speaker A: Yeah. The last thing I'll say, we can move on to something else here. You know, for any, for anyone listening that is in that sweet spot, you know. Definitely. Clearly. I mean the call to action is very simple here. Um, I don't, I don't even see how you don't even at least consider to have a conversation. Um, I think for the larger companies I'll just, I'll just speak to you directly. My brain is really going to, I mean there's a couple leaders that I know right now in my mind that are going through a hard time the last two, three years of finding the right people or they've had a lot of shuffling and moving around and again that timing where the company is, all the change management that has created a lot of different, frankly skill sets and capabilities that are needed. I could very much see this being a uh, tool and a process where you're thinking to yourself, okay, we hire 600 people a year, which is a big number for these two different roles. These roles are completely different now. And based off where we are, we kind of need to do a little bit of a refresh and be able to use this tool to not only scale some of the administrative capabilities, but kind of build out that new knowledge and that new, that new, that new capability. Because all the data that we have really doesn't give us any indication of where we need to go in the future with these roles.

Speaker B: Right? Yeah, totally. Yeah, absolutely.

Speaker A: You know.

Speaker B: Mhm.

Speaker A: Um, that's interesting. Okay. Any, anything else that um, that is fascinating about this tool that you've enjoyed or anything that's, that's potentially you're brewing on, I would love to get any little tips on new ideas you're Thinking about.

Speaker B: Yeah, I think it's just, it's a really interesting. I mean it can be exciting or it can be scary depending on who you're talking to. Time. Because this stuff is just all moving so, so, so quickly. Um, you know we've, Ellie's been, I joined Ellie, um, a little over. I guess it's been like a year and a half now. And even in that period of time, you know, we've gone from like nobody being comfortable with note takers being on the call to like everybody brings a note taker to the call. So it's just, it's an interesting time to really like it's a lot of noise and it's, it's, it's really important to continue to kind of see what the signal is inside the noise of what people actually want, people actually need because there's no shortage of people yelling that they want stuff. But I don't know if they actually want that thing or they want this other problem solved and they think that thing will do it. And so it's, it's, it's a fun time to be building tooling because everything is um, it's a little west I think right now.

Speaker A: Yeah, I would say, I would say so. I was actually looking back at a couple of notes that I had. I have one, one thing that I would love to do with you real quick, maybe a little rapid fire on this. Um, when you think about time back plus like better candidates.

Speaker B: Mhm.

Speaker A: Being like the real roi and we've kind of talked about this. Where do you, where do you think your market is right now? So the folks that you do a great job of serving, do you think they're more. What side are you think they're on right now and debate. Depending on where you think they're naturally leaning based off of how they're engaging with you, where do you see that potentially as not a negative but something that they, they shouldn't forget about. So if they're leaning into the time back. Yeah, they should be. What advice would you say to them about hey, don't forget about this on the better candidate side?

Speaker B: Yeah, I think, I think there's two, two sides to it. So we work with some really, really large companies um, that they are 100% just trying to get time back and so they're trying to optimize that because they're just getting so many applications. Um and I think that for us it is really important to balance that time back with that human connection and customer experience or candidate experience. And so for things like even an AI interviewer, we don't do the, like, fake human avatar, and we don't try to pretend it's a real person, and we position it more like an extension of your application versus feeling like you're getting filtered in or out by. By an AI. So I think, like, there's that side. Then I think on the smaller side, the. The recruit the founders that are trying to do recruiting and hire their first couple people. Um, they are. It's. It is time back, but it's. It's way more like there's a diamond in the rough out there, and I have to go find this person. And even when they meet really good people, I think there's that sense of, like, they're trying to move fast, but they're so concerned about making a misstep because, you know, on a team of five, one bad person is like, a very large percentage of the. The company. Um, and so I think there is a little bit of, like, a treasure hunter mentality that they're hoping AI will fix, which is like, can AI go out and find this, like, mythical creature that I've crafted for myself? So it's interesting because I think on that side, that's where the human can really help to kind of help understand the market and the kind of candidates that are available. And because otherwise, I think you start thinking like, well, wouldn't it be great if I could find this person who has, you know, five years of AI experience, but they only want, you know, 100 grand, but they'll take a lot of equity. But they also want to sleep under their desk. And, you know, they just. I think they have a sense of this thing that doesn't really exist out there, and they're hoping to find it.

Speaker A: I love that. That is super fascinating. And you are right. There's. There's a lot of different ways that they need to look at this and, and pros, and I wouldn't say cons with pros and. And then future developments that they just have to, you know, keep a close eye on. Um, any. Anything else before we get you out of here? Anything you want to plug? Anything that you'd love to say?

Speaker B: No, I mean, I. I would just say, like, if. If anybody out there needs help hiring, we're. We're. We're here to help. Or if anybody has a spicy take on anything I said, I'm also super happy to. To hear that. But, yeah, I mean, no, I think it's. It's been a lot of fun to chat through it. Hopefully it's been. It's been helpful and interesting for people.

Speaker A: It definitely has. Uh, I truly appreciate it.

Speaker B: Awesome. Thank you so much.

Speaker A: Likewise. Talk soon.

Speaker B: All right.