The Role of AI in Modern Recruiting: A Deep Dive with Prem Kumar

Intro [00:00:01]:
Welcome to the Elite Recruiter podcast with your host, Benjamin Menna, where we focus on what it takes to win in the recruiting game. We cover it all from sales, marketing, mindset, money, leadership, and placements.

Benjamin Mena [00:00:18]:
I'm excited about this episode of the Elite Recruiter podcast. Most of all, is AI a bunch of bullshit? Like, is it a faddeen? Or is this something that's going to just absolutely change the game? But here's the thing that we're looking at with AI. There is a lot of bullshit out there. There's a lot of stuff that just isn't doing what it needs to be doing. It isn't a tool that the recruiters need. So I am super excited to have Prem Kumar with me from humanity IO to really just talk about, like, how do you make it past the bullshit? How do you figure out a product that actually works for you? How do you actually get the AI to get you ahead financially and in your career? So excited to have you on the podcast. Welcome.

Prem Kumar [00:00:54]:
Thanks for having me. I'm excited to talk about all that.

Benjamin Mena [00:00:57]:
So first of all, like, real quick, what is humanly IO?

Prem Kumar [00:01:01]:
Yeah, absolutely. So we help high volume hiring teams, screen schedule, and now source candidates through a recent acquisition we made recently of teamable. We do that in a variety of ways. Using AI, real AI is one of the ways, but really, our goal is to allow our mid market customers to upload a job or sync it from an ATS and have qualified candidates show up on their calendar the next day, the next week.

Benjamin Mena [00:01:26]:
Okay. So actually utilizing the AI to actually get something done. Well, first of all, before we start talking into, like, how to look past the bullshit, how to figure out what you need, how did you even end up in this wonderful world? Recruiting.

Prem Kumar [00:01:39]:
Yeah. And I think that even kind of shapes how I think about things like AI or other technologies. It really started from the candidate experience standpoint. So I was graduating from the University of Washington up here in Seattle and applying to lots and lots of jobs, most of the time never hearing anything back, submitting resume after resume, spending a lot of time on that, and just, it felt very one sided. And then when we did have interviews, we'd have companies come on campus and interview students in our field. And my colleague and I, her and I would share notes, and we were getting completely different interviews. They were grilling her on certain things, like her technical skills. They weren't grilling me on.

Prem Kumar [00:02:18]:
We had the exact same degree. We had the exact same internship. It seemed like the process was a bit broken, maybe biased and very one sided. And as I started my career at Microsoft and got into HR tech and some parts of recruiting tech, I saw that this problem wasn't because recruiters were bad people. They just didn't have the tools and technology to engage with candidates at scale. And that's the initial problem we looked at solving. How do we help you engage with scale? And now we've kind of evolved from there. That's awesome.

Benjamin Mena [00:02:49]:
And like I said, congrats on the teamable. I've been talking with those guys for a while. So, okay, how do you figure out the AI that you need personally, for your recruiting career, for your recruiting business?

Prem Kumar [00:03:00]:
My general thoughts on this is I certainly think there's a lot of strong use cases for AI. I don't think AI is replacing recruiters, but recruiters that use it may replace those who don't. But there is a lot of noise. Right? As with any solution. So, you know, an approach I've often taken. So with these hiring teams, these TA teams, they're good at interviewing, they're good at hiring people. So can we take what makes them good at that and use that to help evaluate technology? So I'd encourage you to write a job description for your AI. Think about the experience and training you want your AI to have.

Prem Kumar [00:03:33]:
Think about the background you want your AI to have. Is your AI a culture ad? If it's going to be talking for one common use case for AI that many of us have engaged with our chatbots, which will engage with candidates and screen them, schedule them in human least case, if you're having your first touch point with all the candidates that are attracted to your employer brand, which you spent a lot of time and money to build, if the first touch point is with AI, that AI better be adding to your culture. So I would often write a job description and interview, ask those questions to vendors about the skill sets of AI. Do you have references for the AI? How much does it cost? Background, experience, and training? So that's something that's helped me evaluate AI technology. Kind of ask the same questions I'd ask if I was interviewing a human.

Benjamin Mena [00:04:20]:
I think you got an interesting point there about creating a job description for what you need for this artificial intelligence tool. Because so often that I hate to say this, we see this AI tool and it's like a shiny object. That's going to solve my problem. When you're building that JD, and digging deeper into actually what you need, you mentioned it real quick, cost all sorts of things, like take it a step further. Where should the analysis be between like a 10,000, 10,0000, $200,000 check?

Prem Kumar [00:04:50]:
Yep. Yeah. So I'll pick one example, and actually another thing I'll share too is as a buyer, when you're purchasing a piece of AI technology, you're not just deciding if that technology solves your problem, but you're also committing, without knowing, to a bunch of tech stack decisions that vendor has made. In a climate where AI is very new, if they're using certain LLMs, how they're measuring bias there, are they having some sort of guardrails on top of AI before? So you're really committing to a lot, not just what they say it's going to solve. So getting those questions answered could help you understand. Again, when you're hiring a human, you don't just find out, does this human do XYZ? You want to know a lot more information about them. So one example to dive deeper, if we're thinking about experience and training common in hiring people, you want to not want to know about their experience. So I think that the data the AI is trained on, I would ask vendors those questions, is this a thin layer on top of an existing LLM? What is homegrown? How is my data being used? Obviously, if you hire a human, you don't want them sharing your data everywhere else, so you probably don't want AI doing that either.

Prem Kumar [00:06:04]:
But the data piece is, if data is the lifeblood of AI, it kind of. What if I look at AI as making things happen faster and more efficiently? It can also make bad things happen faster and more efficiently. And a lot of that has to do with how the models are trained. That's one thing. And then the last thing I'll say too, is with the one way to actually short circuit learning. That is, ask if the vendor has been audited by a third party, and can you see the reports, see the results? So that'll help on the experience and training side. But yeah, the data piece is really important. And then the other piece is like, are you even ready? When you're hiring a human, the worst thing you can do is hire someone for a role that you don't really need, and expectations are misaligned and everything you know doesn't work out.

Prem Kumar [00:06:46]:
So I would kind of figure out where is this going to sit within your human stack? Are you going to promote the AI if it does well, is it going to take on other tasks? So I'd, from a recruiting standpoint, kind of think of the end journey for me. I'd start with the candidate journey and then see kind of what, where within your existing flow these things can fit in versus just getting it and hoping everything solves itself.

Benjamin Mena [00:07:10]:
Well, you mentioned a few things. First of all, like the auditing, third party auditing, is that a normal thing when it comes to, like AI tools?

Prem Kumar [00:07:17]:
So that, or should be? Yeah, it's 100% should be. So I wouldn't, I wouldn't personally, and it depends what the tool is, but if I'm actually buying something to help with my recruiting process and it's going to talk to candidates or it's going to do things even internally, yeah, I would certainly expect it to be. The issue is there up until recently that a lot of the regulations and rules and laws and auditing bodies have also been new and not necessarily doing so. It's not quite at the level of ISO certification, SoC two certification, but I definitely think it should be part of any person's criteria in terms of valuing vendors. And there are now auditing bodies like Fairnow is one that we use other ones as well, that are independent auditors and can produce reports that buyers can see.

Benjamin Mena [00:08:04]:
And you mentioned one more thing about the data. AI is built on learning all the data. But how do you really ask that question when you're working with a potential vendor? Is my data going to be used to train everybody's stuff?

Prem Kumar [00:08:16]:
Yeah, for sure. That is one question that I think is totally fair. How is my data going to be used? Is it going to be used to help me or is it also going to be used to help others? I think knowing a little bit about the technology stack, if it is, there's nothing wrong with LMS and what's publicly available, what OpenAI is doing and others, great stuff. But I think knowing how that fits into the stack, because if you're asking something trained on the Internet to talk to your candidate, the Internet is, first off, it's not like 70% English and the web pages are. So you might have issues in other ways. We all know the problems of that. But I, I think what we're seeing is people starting to realize that you can get in trouble here. There's not just inefficiencies created, but things that are really bad for the candidate and for the company.

Prem Kumar [00:09:03]:
One example is if there's a candidate in Colorado that asks a question about pay, you want your AI to be set up in a way where it understands Colorado's pay transparency laws and how it answers the question back. And if you ask a vendor, and I would ask for their kind of tech stacks. So where do the LMs fit in? How can you guarantee that this chatbot isn't just good at talking to people, but it's actually good at recruiting and understands all the complexities of what it takes to have a recruiting conversation?

Benjamin Mena [00:09:32]:
Wow. I didn't even think about the chatbot having to have a conversation understanding the transparency laws in the different places. But that makes perfect sense if that's going to be the front end. Are a lot of the different AI recruiting tools, are they built on top of the existing LMS or is it in house?

Prem Kumar [00:09:47]:
Llmdez it's a really interesting thing. So what's happening right now? First off, I haven't seen any technology since cloud computing that so many people want to use and so few people trust. So there was tidio did a study saying that 83% of people want to use AI, but like 27% of people actually trust it. Auditing and things like that can help with the trust. But the reason I mention that is knowing how the tech is built. There's a lot of folks that have built things in house, many startup companies and even larger companies before this recent wave of LMS and large language models. So what's happening is there's a lot of in house stuff, and when the LMS came out, the infrastructure for building a lot of generative AI things like a chatbot is now in place. If you're buying from a company that built things not incorporating this big step change, they might be built in a way that is not necessarily very conducive to the results you're wanting to build.

Prem Kumar [00:10:47]:
But it doesn't mean that just because I'm also not saying that building on top of the LLM is always going to get you the right results. I think it's important though to know where an OpenAI might fit into your vendors tech stack and then know that they're doing the things to actually make sure that whatever the infrastructure is, it works for you based on your needs and concerns. I don't know if that totally answers your question.

Benjamin Mena [00:11:10]:
I think it did, but goes back into the very start of our conversation that there's a lot of B's out there. Do you think the B's tools and the B's stuff is going to sell a lot more with the growth of AI, or is it going to be a clearing suit of what's actually getting the job done versus what's saying that's getting the job done?

Prem Kumar [00:11:32]:
It's a good question. So it certainly depends on the, the type of tech, but I have full confidence in the TA leaders of America in other areas. These are smart folks. I know when I talk to our buyers, they're asking a lot of the great questions. So I do feel that when we buy AI software, we're basically voting for how much safety we want, how much ethics we want, and I am seeing people asking the right questions. So if you're selling B two B Saasden AI solutions, I do think that the crap stuff will be weeded out. A lot of stuff that's more on the consumer end that might make it through for a while. But then you also do have the auditing the laws.

Prem Kumar [00:12:13]:
I do think audits will be just as common as asking for a soc two report. So I personally feel that a lot of the vaporware type stuff will get weeded out.

Benjamin Mena [00:12:25]:
They sometimes see it feel like there's a new AI tool coming at me like every 5 seconds. So just always like, what's good, what's not good, what are people actually buying and how are they utilizing those cases when they buy it?

Prem Kumar [00:12:37]:
Yeah, good question. And I've always been so my background's in product and I've always been kind of trained to start with the problem. I'm not the solution. Right. And oftentimes with AI, like people are just leading with the solution. We heard about AI, we want AI. We don't yet know exactly how it's going to help. So I don't think that's really the right approach.

Prem Kumar [00:12:59]:
I think there's a lot of great tools out there. Not a direct answer to that, but I, which I'm happy to also provide, but I think that it really kind of starts with like getting your own house in order first, like really knowing where your gaps are. Is it on the front end? Is it in matching candidates? Is it in answering candidates questions? Is it maybe a backend analytics thing, but really knowing what the problem is, because a lot of these vendors will tell you they could do everything. So once you know what the problem is, then you can decide specifically where you need help. The ones that I'm seeing that are working very well. So I'm seeing more and more matching type scenarios or sourcing, but based on candidates you already have relationships with. So if you have an ATS database of millions of candidates that you spent time and money to attract to your employer brand, but you're only talking to them when they apply, how do you light that up and get people ready to go that are qualified, interested and available when you have a new role? Using AI to deepen and make better investments you've already made, such as your candidate database is one thing that I think is coming up a lot. There's a lot of great sourcing tools out there.

Prem Kumar [00:14:08]:
So I think on the front end. And then there's also, you know, if you're, if you have high applicant volume, chances are you don't have human time to talk to every candidate that applies to your job. I often gives an example. If I told our marketer, you know, bring a million eyeballs or a million demos to our website, through our website. But, sorry, our sales team's really busy. We can only talk to 5% of people that want to buy our product. That's kind of what's happening. And you have these candidates raising their hands and wanting to buy your product, your employer brand, but you don't have time to talk to them.

Prem Kumar [00:14:39]:
So I see AI help in extending how many of those conversations you can have. So those are a couple examples.

Benjamin Mena [00:14:46]:
Are people starting to feel like, okay chatting with these AI tools as a job seeker, or do they not realize they're chatting to AI or talking to AI or something of that nature?

Prem Kumar [00:14:56]:
Yeah. So I have some strong and in some cases biased opinions on this, which I will gladly share. I think really, candidates want to, they have a set of things they need and they want that to happen. And AI of old was not providing that. So there was a lot of skepticism around talking to chatbot because it would go in circles or hallucinate or. But if it's actually helping you solve for what you're looking to solve, it's not actually really making a candidate isn't really making a choice between human and chatbot. It's making a choice between chatbot and being ignored for a week. If it's actually screening you in the right way, getting you to the next step or communicating to you, if there isn't necessarily next step with humanly, we kind of want an outcome for every candidate, whether that's actually being scheduled for the interview or maybe looking at other jobs.

Prem Kumar [00:15:46]:
So I think if it actually solves the problem you want it to, it can be very powerful to candidates. A lot of companies like ours will measure that. So we have candidates that'll, that rate our bots. I think the average score is about 4.7 out of five. And the ones that like it, which is the majority, are getting to the next outcome or next step and not, not going in circles, if that helps.

Benjamin Mena [00:16:07]:
Man, I feel like, I know, like, the us governments, like, against, like, AI tools and stuff like that. When it comes to hiring. But man, talk about a black hole that could be fixed.

Prem Kumar [00:16:15]:
Sorry.

Benjamin Mena [00:16:17]:
Well, before we jump over to the quick fire questions, is there anything else that you want to share about artificial AI tools, vetting them out, getting past the bullshit, or, you know, just the future of AI when it comes to recruiting?

Prem Kumar [00:16:28]:
Yeah, the only last thing I'll say is I think more bullshit will come before things settle. So just be aware, be vigilant out there and ask for audits. Ask those right questions. So those are the things I would say.

Benjamin Mena [00:16:40]:
Awesome. Well, jumping over to the quick fire questions, and this is going to be kind of like a, you know, based on what you're seeing from recruiters, I'd love to get your insight, but I'm also going to ask it as a founder, too. What advice would you give to recruiters out there that are looking at these AI products to see success in their own career?

Prem Kumar [00:16:57]:
Yeah, so I think what I'm seeing with a lot of great recruiters, a lot of them are customers or people that I meet, is they're extremely savvy on the technology. So I think just being very aware as to what's out there, maybe going a little beyond the comfort zone around understanding how these products work. Again, like you're interviewing a humanity is something that I would certainly encourage. So when I say knowing how these products work, if it's a chatbot, for example, being very comfortable in asking those questions around, what data is it trained on, where the data is going, what use cases will it solve for being keeping an open mind? I think things are changing really rapidly and processes are changing really rapidly. So I think having an opinion on where AI and other technologies. Fitzhen, within your, I kind of look at the kind of human stack or your people workforce now as being real people as well as maybe agents and automated people, but having an opinion on what should be done by humans and what shouldn't, and doing the reading to arrive at that opinion. So it's really just an education thing right now for all of us because this is new. But that would be my main thought there.

Benjamin Mena [00:18:09]:
And kind of like the same question. But like think of it like more towards around like recruiting technology founders. What advice would you give to them to see success with their companies?

Prem Kumar [00:18:18]:
Yeah, the biggest problem I see right now as it relates to recruiting technology founders is people coming from trying to throw product and technology at a very human driven problem. So there are some great founders that have recruiting or HR experience, but there's a lot that don't, which it doesn't. Mean you don't have to, but if you don't, you have to learn it. And I think when you're a recruiting technology founder, many of those oversimplify what it takes to run a ta or get at scale. They think hiring is more simple and easy, and it isn't. So the main advice is make sure you really, really know what your customers and what recruiters are doing on a day to day basis, how they spend their lives, and what those pain points are before you start coding.

Benjamin Mena [00:19:04]:
Awesome. Do you have a favorite? I know you're probably going to say humanly is one of your favorite tools, but do you have a tool that has a huge impact on your own personal day to day success?

Prem Kumar [00:19:14]:
Yeah, so I certainly do a lot with generative AI, including playing around with chat GPT, as all of us have done over the last few years. To me, it's really like getting the first start on documents or emails. One thing I've been using a lot and humanly has this, but there's others. There's a lot of great tools that do this. I'll actually give a shout to somewhat of a competitor, but bright hire, I think they do a really good job of this concept of really getting better day in and day out. I'm obviously using humanly for some of that stuff, but what I mean by getting better day in, day out is after I do an interview, I'll get a report that might say so. One of the things I'm working on is I speak too quickly and I've learned that. I don't know if you've noticed that.

Benjamin Mena [00:19:58]:
Then I'm laughing at myself. That's my problem.

Prem Kumar [00:20:03]:
But I realized at first it was, okay, whatever. But then I realized, actually, I did some research, and if I'm speaking at over 150 words per minute in interview, candidates where English is the second language have a disadvantage all of a sudden. And then I have bias thinking that they're not keeping up in certain ways or they don't know what this term means, but maybe it's just because I said it fast. So after every interview I do, I'm looking at, you know, am I kind of keeping to the topics, but am I doing so in a measured manner that isn't too quick? So I'm using AI to help in how I communicate. There's another tool called virtual sapiens. I use chrome extension where I can see am I like touching my face a lot or giving body language that isn't what I want to portray. And clearly for anyone watching this podcast, I'm not using those tools enough, but maybe next time I will have perfected all of this, so I use it for showing up better in my day to day meetings.

Benjamin Mena [00:20:58]:
That's actually pretty cool. I know one of the things I've learned because of this podcast is many times I speak too fast because I realize that in the editing process and I'm like, all my words are together.

Prem Kumar [00:21:10]:
That's aside, I'm like, I can't make.

Benjamin Mena [00:21:13]:
An edit, everything's together. But jumping over to a book, have you had a book that's had a huge impact on your own personal career and success?

Prem Kumar [00:21:20]:
Yeah. So the answer is one that is pretty common book in the startup world. But the art thing about hard things by Ben Horowitz, I think that the thing that I really took away from that is he has a quote, I won't get the exact quote right, but just having to do with being a startup founder and there's no way to like learn how to be a great startup founder, no matter how much you read it, is just doing it and you know, it can be a lonely process at times, even with co founders. But yeah, that book was, the writing style really resonated with me and it made it really real about what this thing is going to take as Trudy's going to take.

Benjamin Mena [00:21:57]:
That's awesome. It's a really good book. Looking at your own personal career, it looks like you had a ton of success with Microsoft. Humanly is growing substantially. You guys just acquired teammable, you're investor in other places, you're speaker at the state Department. All sorts of things are just accumulating to a ton of success with you. What do you think has been a huge driver personally for your success?

Prem Kumar [00:22:19]:
Yeah, to me it's really just getting started. I was at Microsoft for ten years and I love the time there, but I think what helped me is it took me a while. I always wanted to join the startup ecosystem. It took me a while. And I feel there's a metaphor called the elephant rope that goes that these elephants in Asia back in the day were tied down at the zoo as babies. And then as they grow older, they can easily just break the rope, but they're mentally conditioned not to. And I had all kinds of ropes, whether it's, hey, I don't want to leave big company because what are the benefits going to be like? Or there's always another rope, right? So I think just getting started and then allowing everything else to the learnings and figuring out later. So I think it's Reid Offman that says that founding a startup is like jumping off a plane and assembling a parachute on the way down.

Prem Kumar [00:23:09]:
So making that jump, breaking that rope and just forcing yourself to do it and then figure stuff out later has been, been helpful in a lot of things and certainly not the excuse for poor planning and strategy and things of that nature. So certainly nothing. But I think personally that has been a big thing that's helped me get to the next step.

Benjamin Mena [00:23:29]:
I mean, I know the tech layoffs, Microsoft doesn't sound as safe as it used to, but Microsoft, if you're in Seattle, is a super safe place. It's the time to work. What finally pushed you to start your startup?

Prem Kumar [00:23:42]:
Well, I mean, quite literally it was, I had my first kid and I was sitting around on paternity leave with the kid in my lap, eating ice cream and passing the time and thinking about life and the impact I wanted to create on the world in the future. And I now try and incorporate, I'm not having more kids just to have those moments, but I try and try and have those moments in other ways. Just give myself the space to sit back reset. And that kind of forced me to sit back reset. And I think part of fatherhood too, is you do start to think more about the impact you're having on your kids and others in the world. So that was kind of then I'm like, okay, I'm going to go do this. And unfortunately, a couple weeks after I left, Microsoft came out with this amazing new paternity leave process. But it was pretty good when I was there, so I won't complain.

Benjamin Mena [00:24:33]:
That's awesome. Well, just being a founder, also, you have a ton of tough days, especially in the get go. How did you deal with those hard days and hard weeks?

Prem Kumar [00:24:46]:
Yeah. So the truth, truthful answer is at first, very poorly. Right? So at the beginning I almost had this concept that I could just do everything right. And what I mean very poorly, it would be, you know, I burn the candle at both ends, not manage my stress very effectively, eat very well. So that was like the beginning. And then after I, you know, as I've evolved over the last four years, the way that I'm one is getting some planned separation. Um, so I try and do that and it doesn't have to be just via PTO, but having these, you know, maybe like a quarterly break where I'm just not thinking about work and I'm thinking more about the future and then also having that scattered throughout the day. So my EA now has been very helpful in having planned breaks in the day.

Prem Kumar [00:25:36]:
I'm always great at using them, but I do feel when I do and then just take the detachment, it helps me be much more effective afterwards so that that's been helpful. And then another thing is, you know, at this life stage in my career or other careers, you don't have, like, tons of time for social stuff like you once did. But I do think with the key relationships I have in my life, obviously my family and my wife, but also with certain friends I'm close to just forcing myself to make the time to get out there and be social. That has been helpful for me, and I need to do more. That's awesome.

Benjamin Mena [00:26:09]:
Well, looking back on, like, the ups and downs that you had and the successes you've had, a, if you had the chance to go back and get a cup of coffee with yourself, let's say the first month or two that you started humanly, what advice would you give yourself?

Prem Kumar [00:26:23]:
Yeah, kind of go back to, like, just start. Just do it for a lot of things, whether that's starting the company itself or whether it's making the first hire. I think there's too many things holding me back from just moving fast on certain things that I thought I needed to do. So trusting myself to be able to figure things out later, that's one advice. A lot of the things that seem like big hurdles oftentimes end up not being so. So that would be one thing. And then the other piece I would say is just, yeah, really trusting yourself. I think there's going to be a ton of opinions you get, particularly as a recruiting tech founder or founder in general.

Prem Kumar [00:27:00]:
There's lots of advice, and advice for very smart people that do know what they're talking about, but everyone's experience is different. Yours is your own. I wouldn't say don't take all the advice, but I would say, don't allow yourself. Make this really brief. But I was reading my daughter a book about I forget the animal I think was a bear, but he's walking to school, he's dressed in his favorite outfit, but then every animal he passes gives him another element of clothing that's their favorite, and he puts it on. Then he shows up at school looking really ridiculous. And I think I was taking advice from everyone because I hadn't done this new thing before, and it led to showing up to school looking ridiculous. So I would say, know that you can do this and trust yourself to make the right decisions.

Prem Kumar [00:27:46]:
Listen to others, but don't get pulled in a million directions. Just do one thing. Even if it's like 70% right or 60% right and maybe 40% wrong, it's much better to move than to be kind of moving around in different directions.

Benjamin Mena [00:28:00]:
Oh, that's absolutely great because, you know, once you're getting started with something, you want advice, but then everybody else's has an opinion, and then it's always like, down the road it's like, so what's the opinion of the buyers?

Prem Kumar [00:28:11]:
Yeah, well, exactly.

Benjamin Mena [00:28:14]:
Well, awesome. Before I let you go, if anybody wants to follow you, how do they go about doing that?

Prem Kumar [00:28:18]:
Yeah, so you can check me out on LinkedIn, look me up by my first name, last name. Feel free to email me too. Pre mlead IO, if you want to learn more about anything I chatted about or want to talk about something else, always try and be available there.

Benjamin Mena [00:28:31]:
Awesome. Well, before I let you go, is there anything else that you'd love to share with the listeners?

Prem Kumar [00:28:35]:
No, selfishly, check out humanly IO, where we really are trying to land on that promise of allowing our customers to sync their jobs into our tool and then have qualified candidates show up the next day, in the next week. So check us out. I would love feedback too, but yeah, that's the last thing I'll leave with.

Benjamin Mena [00:28:54]:
Awesome. Well, I just want to say thank you so much for coming on. And we're getting constantly bombarded with artificial intelligence tools in the recruiting technology space, but it's like, I love that you just like, here's what you needed to break down to figure out exactly what you need to solve the problems and get past the bullshit. So I'm excited about the future. I'm excited about what's happening with recruiting. I'm excited about how recruiting is changing, and I'm excited about the recruiters that are just going to absolutely just crush it. Yeah, I want 2024 to be your best year yet. Thank you, guys.

Intro [00:29:24]:
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