AI Agents in Recruiting: Driving Profitability and Efficiency with David Paffenholz

Benjamin Mena [00:00:00]:
You are going to rock the year and we're going to help you do that. Here at the Elite Recruiter Podcast, we have the Rock the Year event, the Recruiting Growth Summit, kicking off on March 10. It is going to be awesome. We're going to be focusing on mindset, we're going to be focusing on sourcing, we're going to be focusing on AI. We're going to be focusing on operations and high performance and BD and sales. Every single thing that you need as a recruiter to make sure that you can rock 2025 and make it the year of abundance. Make it the year that that works for you. Make it the year that you crush every single one of your dreams.

Benjamin Mena [00:00:33]:
Let's go get it. Coming up on this episode of the Elite Recruiter Podcast, do you think chatbots will ever have a huge impact on agency recruiting by chance?

David Paffenholz [00:00:49]:
That's an interesting question, I think.

Benjamin Mena [00:00:51]:
Do you think we're going to see a point in time where a team of like five to 10 recruiters can be pumping out $20 million in revenue per year because of the use of AI? Yes.

David Paffenholz [00:01:01]:
And I think we're actually already seeing some of those numbers with some of our customers.

Benjamin Mena [00:01:05]:
Welcome to the Elite Recruiter Podcast with your host Benjamin Mena, 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. I'm excited about this episode of the Elite Recruiter Podcast because I was actually just reading on Axios this morning that 60% of companies out there this year in 2025 are expecting to use AI agents within their company. AI agents to get the job done and many times that's what a human used to do. So like in the combination of having like OpenAI as operator, their deep research, so many things are coming to the table and it's all really coming together in 2025 like we have never seen before. So I am super excited to have a returning guest share about what is happening when it comes to AI agents within the recruiting space. How can you, you, the recruiter, stay ahead of the game and how can you use AI agents to absolutely crush it? So, David from Juicebox, the makers of People GPT, I'm so excited to have you back.

David Paffenholz [00:02:16]:
Welcome. Thanks so much for having me on again. Excited to be here.

Benjamin Mena [00:02:19]:
Real quick, before we get started, want to give you a 30 seconds introduction just in case somebody didn't get a chance to listen to our last episode together for sure.

David Paffenholz [00:02:27]:
So I'm David, co founder of juicebox we're an AI recruiting platform. Some people may know us as PeopleGPT. We help our customers find, assess and engage talent. We built this product out of a pain point that my co founder, Sean and I faced while working on a previous company. Since then, we've scaled to work with over a thousand customers, which has been a fun journey.

Benjamin Mena [00:02:45]:
And if you want to check it out, you can actually play with it for free. The link is in the show notes to definitely check it out, explore it. I actually use it as a recruiting tool and a sourcing tool, which is one of the reasons why I wanted to bring David back on. Just because one, I enjoy the product, it works great. And on top of that, the AI game is absolutely changing. So like I said, if you want to go back, listen to how we started the company, why he started all that stuff, go back to that original podcast. So let's just jump right in. So for those that are listening, you know, we hear AI, this AI is everywhere.

Benjamin Mena [00:03:14]:
AI is overhyped. But when it comes to AI agents, what actually is, in a general term, what is an AI agent?

David Paffenholz [00:03:22]:
I think there's going to be a lot of different understandings and interpretations of it. The way I think about it is what I think is fairly straightforward, really. There's two attributes to an agent. The first one is that it has an understanding of reflecting on its own actions. And so an agent is able to take a step through a process and a workflow. So, for example, in recruiting, that might be creating a search or sourcing for talent, but then it's also then able to reflect on that. And so just like a human would, if something works well, it's able to kind of continue doing that. And if something doesn't work well, it understands that too, and then adjusts its process.

David Paffenholz [00:03:56]:
The second thing an agent does is it can take feedback as it goes. And so for any kind of real agentic workflow, you can think of it as something that you can give direction or feedback to. Going hand in hand with that reflection piece, we can tell that it's not doing something well and then it'll go back and fix it. And so when I think about what is truly an agent or what is really an agentic workflow, those are two things that should be there.

Benjamin Mena [00:04:21]:
And I know, like, the agentic word is being thrown around, like, more than ever before. What does agentic actually mean?

David Paffenholz [00:04:26]:
Yep. Yeah. And I think the kind of real thing that it often gets confused with is like an automation. Automations are great. Automations are things that you know, we can set up once and then they continue happening. And so, for example, an email sequence is an automation, but an email sequence is not an agent or not an agentic workflow because we can't give it feedback, it can't understand what it's doing well and improve on its own. And so as soon as it starts doing those things, it would go into the category of agent or agentic workflow.

Benjamin Mena [00:04:52]:
So when you're looking at the recruiting world, which is the space that you're in, like what are the different places where you can potentially see actual AI agents involved in the recruiting process? And, and the reason why I want to ask this is because I actually asked OpenAI's ChatGPT, their deep research and operator, how much of the recruiting process can it handle? And it responded back saying like, I could probably handle 40 to 60% of your job right now playing with it, it's acting like a drunk toddler and got lost 17 times. Looking at like how the recruiting process is and let's just say like, you know, the agency recruiter, what can be done for AI agents for every part potentially in their workflow?

David Paffenholz [00:05:33]:
I think in terms of the number of tasks, the 40 to 60% estimate from OpenAI sounds directionally correct to me at least. I think in terms of more specific tasks, everything that has a clear process around it is something that is usually more suitable to an agentic workflow. And everything that is less well defined is going to be trickier. And then at the same time, everything that has some type of human component to it, where it's a call, a relationship, I think is going to be very tricky to start replacing with agents or agentic workflows. And so to kind of apply that specifically to recruiting and agency recruiting, I think both kind of customer and hiring manager interactions are going to continue to be kind of extremely personal or focused on that human to human interaction. And then similarly on the candidate side, building those candidate relationships and guiding them through a process, I think the steps in between that are more on the organizational side or that are more on the say top of funnel sourcing side, managing outreach and more, those are the places where I think agents are going to have the biggest impact.

Benjamin Mena [00:06:33]:
And do you think, and I know like AI agents are new, they're going to be a lot of flirting around it. I personally think, and this is, you know, me and my little bubble, I think we got about a two year window where it's not quite mainstream yet. And I think like a lot of recruiters can really take Advantage of it. Where can recruiters maximize their profitability, maximize their impact, and probably the placements by utilizing AI agents.

David Paffenholz [00:07:03]:
Yep. So I'm a little bit biased because it's where we've been focused on, but I think the biggest immediate impact is on the sourcing side. And so really being able to go even more in depth, find profiles that maybe other agencies are not uncovering, and finding profiles that would also be really hard to uncover in manual workflows. And then also just scaling up and automating that outreach component. And so being able to orchestrate that full workflow with an agent and having to really understand and learn your preferences is where I think there's a chance for kind of an immediate outsized impact. And so I think that's what we're working on. What I see happening in the short term, the everything beyond that, I'm still a little bit unsure, to be honest. And so I think everything that goes in the direction of, like, there's agents that are being tested for screening candidates and things like that, and those could be interesting areas, but to me, it's a little bit less clear if that will be the future of any of those areas.

Benjamin Mena [00:07:54]:
I know there's like a ton of companies getting started on the screening part of the process. Almost as if, like, that's the cheapest place to start versus the building out the data and the sourcing. Yes. Yeah.

David Paffenholz [00:08:05]:
And it's also the, I guess it has the least external dependencies. You know, it doesn't need to, as you said, like, you don't have to acquire the data, you don't have to clean the data, keep it up to date, et cetera, where it's maybe like a pure, more normal software use. Case of like, doing that interview, we'll.

Benjamin Mena [00:08:19]:
Say like two to three years out with the development of AI and with you being on the forefront, how smart do you start to see these agents become in two to three years?

David Paffenholz [00:08:30]:
Yeah. So I think the ironic thing is that they are always a little bit less smarter than we'd like them to be. And so they'll always still get the things. Things wrong, and there'll still be moments of frustration. And, you know, I think what you mentioned in terms of testing it out, where you used OpenAI operator, I think that's like a good example of that. And obviously OpenAI's operator is at the forefront of what's possible when using an interface like a human would a computer interface. At the same time, it's still not perfect, and there's still a lot of mistakes it makes and where user would instantly look at the screen and say, this is where I know where to click. I know what to do.

David Paffenholz [00:09:01]:
I know how this action works. The AI agents are still a little bit behind that. And so even as the use cases get more complex and we're able to do more and more, we'll always demand more from those agents. And so even in two to three years, I think the general feeling will be similar to what it is today of, you know, it's already helpful in my workflow. A lot of people have adopted it, but I wish I could do X, Y and Z. And I feel frustrated that I still have to do some things myself.

Benjamin Mena [00:09:27]:
And do you think this is going to sound kind of stupid? I remember with the increase of all the technology that we have, it almost feels like we're supposed to take my workflow down. But over the years, my workload has increased. With this tech tool and this tech tool, do you think the AI agents have the capability of actually bringing everything together so that way I can actually focus on the relationships and the conversations?

David Paffenholz [00:09:50]:
It's a good question, I hope. Yes, but it's not clear to me that it will. The main reason for that being that the AI agents are similar to us as human operators of different tools as well. Either they need other tools that do those things. So, like, either they need a tool that does email sequencing, or the agent itself needs to be able to do email sequencing. And so unless either of those things is the case, it'll still require all those different tools and all those different systems. Now, I think where there's a really big opportunity is to have an agent be helping manage multiple workflows. And so, for example, if we have an agent that understands both how you source and how you reach out to candidates, that's at least a minimum of two different tools.

David Paffenholz [00:10:30]:
Probably more than that, if you consider things like contact data or analytics in between, that can be consolidated into kind of one single tech tool. I think the other thing that I think often goes kind of unsaid as we transition to using more and more technology is we're actually able to do a lot more. And so even though we have a lot of different tools now, we're also able to place many more candidates than we used to be able to. We're able to manage more relationships than we used to. We're able to manage on more open roles at once than we used to. And I think that trend will continue to increase as well. And so with an agent, maybe it's Another doubling of that capacity.

Benjamin Mena [00:11:03]:
One of the things I'm seeing in the SaaS space and you know, in the SaaS, but recruiting space is the growth of highly valuable, highly profitable companies with small teams. You know, I'm seeing like 10 million per year ARR. With like a team of 25 or 5 million ARR. With a team of 10. And like, in the recruiting space, you see the production numbers and like, almost everybody has like the numbers down. When you're looking at growing and scaling your firm, you know, it's like you want the desk size to be like, typically like 4:30 or 5:50 or whatever it is per recruiter. Do you think we're going to see a point in time where a team of like, we'll say five to 10 recruiters can be pumping out $20 million in revenue per year because of the use of AI? Yes.

David Paffenholz [00:11:49]:
And I think we're actually already seeing some of those numbers with some of our customers, not those exact numbers that you described, but directionally where the revenue driven is significantly higher than one would estimate based on the headcount of the firm, even compared to, say, previous years before using specific technologies or really scaling out the. The way that they operate. So, short answer. Yes, I think that will be a big driver, and I think that number will increase faster than we think. And so, especially for companies that are adopting technologies that actually help them and actually make them much more efficient while their competitors may not be, it can be a really outsized advantage.

Benjamin Mena [00:12:22]:
And I know you can't name who those companies are, but is there any other things that those companies are doing that other firms that you see aren't doing to start seeing a huge exponential revenue growth?

David Paffenholz [00:12:32]:
I'd say one common trait I've seen among them is a eagerness of experimenting with different workflows, but then being able to quickly adopt things that work and quickly get rid of things that don't work. And I think the more traditional approaches has been like, you know, long implementation cycles dedicating to a specific system or software for like, long periods of times and kind of being stuck in that. I think what we've seen with the firms that are growing the fastest is that there's a lot more things going on at any given point in time, a lot more testing, both in terms of different technologies, different workflows, and then just doubling down on the things that work and quickly getting rid of the things that don't.

Benjamin Mena [00:13:07]:
And is for those teams, is it like the founder that's there, like testing all the workflows? Or do they have typically somebody on the team that's like, hey, you're in charge of testing all this stuff and let's see if it works?

David Paffenholz [00:13:16]:
Depending on the size of the firm, there's a few firms that I'm thinking of that are like all in the 10 to 30 recruiter range. And they're like, the founders are pretty involved. So oftentimes they have like one person on the team who kind of naturally tends towards like owning the tech stack or spending the most time with it. And oftentimes that person takes the leading roles.

Benjamin Mena [00:13:32]:
And for, you know, a firm owner that's looking at actually implementing this. And actually this is a question I had like a week ago. The guy has a team of 56 recruiters and they're very flat. It's 100% revenue driven. He was actually talking to me about like, how do I actually go start implementing like all this stuff? Like, do I need to hire a person or do I find like somebody on the team and just kind of like protect their commission a little bit? Like, how do you actually help empower that person that's going to lead the tech stacks or the, you know, the tech changes?

David Paffenholz [00:14:03]:
Yep. So I think there's a significant risk to bringing in someone like hiring someone specifically for that role, especially someone who doesn't know the exact workflow of the team and what has worked and what has not worked for them in the past. I think there is an easier workflow of seeing what tools are already working for your best performers. Oftentimes there are different workflows that best performers use compared to other members of the team and then rolling that out to wider shares of the team. The one nuance with those is like things that have to be implemented on an org wide level. So say switching an ATS or a crn, that's something that has to come top down. But frankly, those are also usually not the things that drive like a 3x improvement or anything that's like orders of magnitude. And so, you know, the more individual recruiters are empowered to test things on their own and be that through, you know, being more, more flexible with purchasing different softwares or testing out different softwares and letting them drive it, I think can be a really good way to power that adoption.

Benjamin Mena [00:14:54]:
I'm so excited we're going to be kicking off a AI and clay boot camp at the end of this month. I've actually partnered with Stephen from the Art of Sales Academy. You guys saw him talk at the last summit. But we are putting together a four week Bootcamp. Because if you guys want a good laugh, some of these AI tools are complicated and I'm going to be sitting in the class learning along with you. But these AI tools, once you master them, they can have such a huge impact in your business. But the problem is learning the tools. So we're partnered up to put together a bootcamp starting at the end of this month to help you master these tools so that way you can multiply what you have done for your recruiting business.

Benjamin Mena [00:15:32]:
And on top of that, I'm also going to add in a free VIP ticket for the Rock the Year summit. So that way you don't miss any of that. Also so excited. Join me for the boot camp so that way we together can learn how to master these AI tools so that way it can work for you when it comes to, like, testing software if you want a good life. Like way back when I was an internal recruiter, I actually paid for all the new software myself. And because, like, every time I asked, like, I got told no. So I actually went and paid for stuff myself, like a job board or whatever. And then I presented the case.

Benjamin Mena [00:16:09]:
Do you see recruiters actually doing that, like within, like, you know, with people GPT, like, hey, I'm going to go pay for this myself and then build the case out for bringing it to management? Yes.

David Paffenholz [00:16:21]:
I've actually been surprised at how frequently we've seen that. We recently did like a poll where we basically can tell whether a credit card is a corporate card or not. And so we have like some type of indication whether someone is probably paying for it with their personal card. We never know, you know, what's on the back end with reimbursements, et cetera. But it's a surprisingly large share of people, especially at large companies where procurement processes are slow and there's just no easy way to roll out a new tool. And frankly also for good reason, because it's complex to roll out a new technology to a large team. But that's where we've seen a lot of people individually use tools, use them to get ahead, even use them as part of their interview processes. And we have like a program where basically we give free access for people who are interviewing for new roles or like kind of doing case studies, et cetera, trying to land a role as a recruiter.

David Paffenholz [00:17:02]:
Those are often some of the most fun ones because can see how they succeed in, in that process, join their new role, and then oftentimes they'll actually take the technology with them and roll it out to their team.

Benjamin Mena [00:17:11]:
That's actually super smart. And it was just, you know, curious. I was like, I know I did it, but I was also like this weird person in the internal space where I was just like, hey, you know what, Let me test this. Let me build this out and let me present it to management. I'm like, if you're going to pay for it, cool. If not, I'm going to get my job done.

David Paffenholz [00:17:26]:
That's exactly right.

Benjamin Mena [00:17:27]:
Back to AI, like when you're. And let's talk about, like, you know, not just recruiting. Let's talk about, like, you know, the companies out there. Like when we hear the number saying that like 60% of companies are going to be using AI agents, like, do you think that's going to impact our end users, the people that we're placing?

David Paffenholz [00:17:45]:
I guess like an impact is in, like, will they hire less people or.

Benjamin Mena [00:17:48]:
Will they hire less people?

David Paffenholz [00:17:49]:
I see. My prediction is, no, I don't think they will hire less people. At the same time, I'm definitely not the most qualified person to answer that question. I can tell you my reasoning, though. I think as technology evolves, people get better at doing things and we're able to do more. So one, we're running, like, as an example in the recruiting use case, we're running better searches than we did 20 years ago. And we're also running more of them. And also for roles that wouldn't have had a dedicated search 20 years ago, they now can get a search because, you know, our kind of economy has evolved in a way that that makes sense.

David Paffenholz [00:18:21]:
And so that we're able to, you know, we have the technology to do things more efficiently, we can run more searches and more of that happens. And so basically more of the, of the recruiting service gets consumed. I think the same happens across industries and the same will happen with AI agents. And so as AI agents are able to make us more effective at things, it's almost like us having assistants for different parts of our job that take the most time of our job, we're able to do more of that and we're able to do it better. And I think that is going to be the case within recruiting agencies. That's also going to be the case within most other business lines. And so depending on the business that the customer is in, I think they'll have a similar experience. There will probably be specific roles that shift more drastically.

David Paffenholz [00:19:01]:
And so perhaps we've seen some of that in, say, customer support, where a lot of tickets are being handled by AI agents in a way that is very different to what it was even two or three years ago. And so there might be larger disruptions to what we see in terms of employment.

Benjamin Mena [00:19:15]:
I completely forgot about customer service. I feel like the bots are so smart now answering my questions. It's kind of wild how that's changed.

David Paffenholz [00:19:22]:
Yeah. And like, I think the I, I've gotten to the point where on certain software that we use, I actually, I like when it's the AI agent responding to me because I get a quick response, it's definitely a fast response and most of the time it's right. And then I know I can still reach out to a human afterwards, which I don't know about you, but I felt like even, even just a year ago I would get really frustrated when it was like, oh, AI is looking for a response or something and I'd know like, oh, I'm not going to get the answer.

Benjamin Mena [00:19:45]:
I'm looking for the platform that I use. And David's going to be part of the AI summit that will be this summer. You know, the second round of it. I had an issue with the platform and I hopped into the AI bot like literally six months ago. I had to wait for a human response and literally the question that I had, it was actually so like wild and so weird. I didn't think they were going to have the answer. They're like, oh yeah, it gave me everything. I was like, oh, I don't even have to like wait for them because they're in the uk so I don't have to wait till tomorrow to get the answer.

David Paffenholz [00:20:11]:
Yeah, and those are like the, the delightful AI agent experiences that hopefully we'll have more and more of.

Benjamin Mena [00:20:17]:
I really never talk about chatbots when it comes to recruiting because, you know, outside of talent acquisition, I don't see that much of a use case. Do you think chatbots will ever have a huge impact on agency recruiting by chance?

David Paffenholz [00:20:31]:
That's an interesting question. I think for high volume roles that go more in the staffing direction, yes. I think for most agency recruiting I'd be more surprised. The way I like think back of it is like just from the candidate experience perspective, what is something that a candidate is likely willing to do or something that they want to do. And I think I could see a use case for chatbots of say, learning a bit more about a role or being able to ask them about things like compensation, et cetera. Though the use cases that I could see being strong there in my mind at least are a lot more limiting. As I'm curious, have you seen cases where like a chatbot was really well implemented on the recruiting agency side, not.

Benjamin Mena [00:21:07]:
On the agency side. I've seen a lot of it in a talent acquisition, you know, especially on like the lower end stuff. I think this company is like, you know, paradox and all those. They're doing a really good job with that. But I haven't seen it quite implemented on the agency side. I was at a conference up in D.C. with a lot of like government contractors and I was one of the speakers. Like it was me, a bunch of like SVPs for these billion dollar organizations and AI scientists from Microsoft and one of the SVPs from the government organization.

Benjamin Mena [00:21:35]:
I was like, actually somebody came into the office and said like, hey, they wanted to meet this recruiter and the TA team actually had to tell them that it was a bot. That's so like, it isn't like seeing it too much, but I know it's getting smarter, but it's just, I just haven't seen like the use case around the agency recruiting like it is on the TA side of the house.

David Paffenholz [00:21:55]:
Yep. And I expect that to like. I think that largely makes sense to me as well because you know, a lot of the cases like Paradox, et cetera usually specialize in those high volume recruiting rules where it's you know, intake of information and then directly to scheduling of a first round interview. And it's a pretty structured process where there's like a defined flow of next steps. Whereas you know, oftentimes with, with agency recruiting we've even looked at this. We did like an analysis of categorizing the average first reply from a candidate. So like, what is like a typical first reply from a candidate to outreach. And you know, it can be things like straightforward ones like scheduling, going right ahead, but there's actually a huge tail of different questions from like asking about compensation, about location, flexibility, remote work.

David Paffenholz [00:22:34]:
There's so many different questions and kind of flows that can come up from there that I think the using a chatbot for that doesn't quite seem right in my mind.

Benjamin Mena [00:22:42]:
Okay, so the last time I interviewed you, you guys just launched, just went public, kicked off. You guys have gained like over a thousand customers and just absolutely growing. What is the most interesting data points that you have seen that have really surprised you when it comes to like the recruiters or the candidates behind the scenes? Like if you're able to like look at that kind of stuff.

David Paffenholz [00:23:04]:
So a few things that like we recently did a big deep dive into email response rates and like what good email sequences, setup look like and there's been a lot of things that surprised me. One, we noticed that the, the majority of responses don't come on the first email. They come on emails 2, 3 and 4 and to a pretty large extent. And so especially with like well set up kind of three, four step email campaigns, true driver of success. There are the later step emails but then also the time for average candidate responses. We saw like significant number of responses over five days after the sequence was first sent out. And so the delay there and going from you know, initial outreach to bringing in interested candidates is quite significant. So those are two stats that like I just looked at like yesterday which is why they were top of mind and very going to go into some kind of guides that are going to insert into the platform as well.

David Paffenholz [00:23:53]:
And then apart from that, I think we've been able to learn about like a huge diversity of different recruiting kind of verticals and specializations. And I'm always surprised at like how niche those specializations can go, especially on the agency. Recruiting side is small agencies say like two or three people. I've seen like hyper specific niches like recruiting designers for game studios only or things where there's like a very defined and limited talent pool but it's clear that the recruiter is focusing on it are true experts in that space. And so that's maybe a little bit more of like a overall thing that I've been impressed by.

Benjamin Mena [00:24:27]:
Awesome. Well, before we jump over to the quickfire questions, is there anything else that you want to share about People GPT.

David Paffenholz [00:24:34]:
We just launched our agent. I think by the time this video or this podcast is released it'll be live and so it has a free version to test out and you can head to Juicebox AI and try for free. It's already been in beta with over 60 customers that have had a lot of success with it and so excited to hear what you think.

Benjamin Mena [00:24:49]:
Awesome. I know we did the quick fire questions last time, so I'm going to mix it up on you on the fly. This is going to be more of like a questions that you've seen based on like the organizations that you've been working with. If you have an organization that's kind of like doesn't want to touch AI, but they're still chatting with you about the future of artificial intelligence when it comes to recruiting. What conversation would you have with them? What would you actually tell them?

David Paffenholz [00:25:12]:
That's a tough one. You know, I'd ask them to see if there's anyone. There's always someone on the team who wants to try out new things, who wants to try out AI. Usually the reason that we're on that conversation in the first place is that someone does think it's interesting or has an impact. And so I always like to ask and say, you know, why is that the case? What have they had like success with other things and brought on new things. And usually there's some type of story there where, you know, a new tool ended up being really successful or they're known for bringing on new workflows in their organization. And so if that's something that the organization wants to do more of, that's something we might be able to help them with. In other cases, you know, agency might say, you know, we're happy with the way things are going and we don't have any plans of changing things.

David Paffenholz [00:25:49]:
And that's also totally fine, you know, so in those cases we try to keep a good relationship and then perhaps at some point in the future things change there too.

Benjamin Mena [00:25:57]:
Awesome. Now looking back at like the, the organizations that are really like hitting it out of the park with AI, like you said that they move fast, you said that they cancel things. But have you seen like a difference in the leadership that just stands out from those organizations?

David Paffenholz [00:26:15]:
Yes, I'd say the leadership is much more hands on and they actually know how to run great searches themselves as well. And so oftentimes we see that like I guess there's two types of demos we do. One where it's a demo, where it's a decision maker who actually hasn't like, you know, run a search in a long time. And then other cases it's a decision maker who is actively running searches and actually goes into them and might like go as specific as like really working on a role with a recruiter on their team. And so in those cases I feel like it's easier for them to get a feeling for where can AI have a big boost in the workflow and also makes them a better evaluator of what makes a good tool or not. And so I'd say that's one thing that we've seen be really effective is when the leadership goes really hands on with different tools and trying to get a feeling for what would help them in their workflow as well.

Benjamin Mena [00:26:58]:
Okay, so when we look at tech tools and you can't say like, you know, People GP is your favorite. If you want to check out People GPT, there's a link in the show notes, check it out for free. But for you personally, is there like a tech tool that you cannot live without now.

David Paffenholz [00:27:14]:
So I really love this task scheduling slash task tracking app called Sunsam. What's really cool about it is one, you can keep track of your tasks, but then two, it does some smart planning with that as well. So it'll suggest how much time a task will take. You can actually slot things into your calendar, you can drag emails into your tasks and more. And so I manage my whole life on Sunset.

Benjamin Mena [00:27:36]:
Awesome. I know I asked you this last time, but, like, in case it changed, has there been a book that's had a huge impact on your personal success?

David Paffenholz [00:27:45]:
I have to go and see what I. What I answered last time. I'm not sure. I don't. I don't think there is, like, been one book that has heavily influenced my thinking. I like to read like biographies, though. I think those are more from a perspective of, like, interest and curiosity rather than trying to apply something myself directly, if that makes sense.

Benjamin Mena [00:28:08]:
What's your favorite biography?

David Paffenholz [00:28:10]:
I enjoy reading the most recent Elon Musk biography. He's a very unique character, but I think in the biography his personal side shines through a lot as well. And so, you know, maybe some of the more tricky things that he's gone through too, both early on in his life but also throughout his career. And so I thought that was a, that was a good read and also a bit different than the typical media portrayals or maybe Twitter portrayal of himself.

Benjamin Mena [00:28:32]:
His portrayal of himself.

David Paffenholz [00:28:35]:
What'd be the impression that one gets from it?

Benjamin Mena [00:28:39]:
So I know as a founder, things are hard and I know there's like, listening. There's many recruiting founders that are going through the battles that they go through themselves. But how do you personally get through those hard days or those hard weeks where everything's just coming at you, things aren't working out and how do you get out of that funk?

David Paffenholz [00:29:01]:
I think one, we try to actively celebrate our wins. We used to not do this. We used to just kind of keep going on day by day, and if something good happened, we just keep going. Whereas now we try to actually take out some time and celebrate the wins because in times when there's maybe a really tricky week or something is just not going well, being able to turn around and say, also, hey, good things happened and we can celebrate that as a team is really powerful. And then second, being able to lean on each other as a team, so having that kind of sense that we can be honest with each other even if things are not going well is really nice because I feel like oftentimes the things that cause me the most stress is if I don't feel like I have a direct action plan to solve something, being able to talk it through with someone else and the team is a really good way of solving that.

Benjamin Mena [00:29:41]:
So I think you were probably about 150 episodes ago was the last time you were here. You know, if you got the chance to actually like go back in time and like, with everything that you've learned now, gone to market growth scale, hired people, worked with a ton of recruiting agencies. If you had a chance to go back to yourself right at that time where we had our conversation, you just went public with the company or, you know, with everything. What would you give yourself advice? What would you tell yourself back then?

David Paffenholz [00:30:09]:
Yeah, I think we last spoke right when we had just like a few months after we had done the launch and you know, the launch had like got a lot of attention. We got a ton of signups. Like 3,30,000 people tried it out after like within the first week, which was crazy, way more than we thought. At the same time, the product wasn't working as well as we needed it to. And like a lot of our early users were having quite significant issues. And so looking back, I would tell myself to, you know, take a pause there, focus more on our product improvements right away rather than kind of we continue this two pronged approach of continuing to fix product, but then also continue to onboard new customers. Whereas perhaps looking back, we should have made that a more explicit prioritization of like pure product focus. We did that for the next six to eight months and then it, you know, really had a big impact, especially at the beginning of last year, which is when our growth really started accelerating.

David Paffenholz [00:30:55]:
And I think we could have done that like six to eight months earlier if we had been a bit more reflective early on.

Benjamin Mena [00:31:00]:
Awesome, awesome. Lesson learned right there. Okay, so you're talking to recruiters every single day. You're talking to recruiting lawyers all the time. They're like asking you questions about AI this, AI that, and like you. This doesn't have to be like just about your product. Okay. But like when they're like asking for advice, you know, I'm sure a lot of it's tactical strategy.

Benjamin Mena [00:31:19]:
Is there a question that you wish a recruiter or recruiting leader would actually ask you, but you really don't?

David Paffenholz [00:31:26]:
I think the overall thing that I think is one of the most impactful thing a recruiter can do is try out the different tech that's available for free. So like, you know, Juicebox has a free Trial. But there's also a ton of other platforms that have free options like Metaview. Like you can start taking notes, I think, I don't know, for a certain number of calls, like pretty self serve and there's a bunch of different options out there. And so I think there's a little bit of like, analysis paralysis of like, oh, there's so much tech out there, I don't know what to choose. Whereas just going and trying things and seeing what works and then, yeah, I'd say that's like probably the biggest thing.

Benjamin Mena [00:31:58]:
Awesome. Yeah, I mean, you're kind of right. Like a lot of tech is now free for trials. Well, okay, so before I let you go, two last questions. If somebody wants to follow you, how do they go about doing that?

David Paffenholz [00:32:09]:
Probably on LinkedIn.

Benjamin Mena [00:32:10]:
Best place is LinkedIn.

David Paffenholz [00:32:11]:
Yeah, best place is LinkedIn.

Benjamin Mena [00:32:13]:
Awesome. And I'll have your LinkedIn profile in the show notes. And before I let you go, is there any last thing that you want to share with listeners?

David Paffenholz [00:32:19]:
Thanks so much for having me on. This was fun as always and hope to see you at the AI Recruiting Summit.

Benjamin Mena [00:32:24]:
Awesome. And everyone out there, like, I know this year is going to be the year of change. I'm actually flying out after this time of recording, flying out to Austin next week to give a talk on AI and recruiting. And it's the craziest thing, like looking back on history, like, things have changed, like a certain amount and now we're hitting this exponential curve where things are just going to be changing constantly. AI agents are going to be smarter and smarter. Like I'd say 2025. The tail end of 2025, you're going to be hearing AI agents and recruiting nonstop. It's finding out what works for you, spending time learning about it.

Benjamin Mena [00:32:54]:
So that way you can absolutely crush it, hit your goals and make your dreams come true. Because 2025 can be the absolute year of abundance. So keep crushing it, guys.