Recruiting is generating more activity than ever and less connection. Candidates are using AI to produce polished applications at scale, employers are using AI to screen and reach out at scale, and the result is a level of noise that is eroding trust on both sides. More automation applied to the same processes will only make this worse. Solving it means rethinking how matching works, with depth of understanding on both sides and transparency and fairness designed in from the start. So what does that look like in practice?
My guest this week is Matt Wilson, Co-founder and CEO of Jack and Jill, whose AI agents work on both sides of the hiring market. In our conversation, Matt shares why supercharging existing processes deepens the noise problem, how transparency and independent auditing build trust in AI matching, and where human judgment remains essential.
In the interview, we discuss:
- Why job hunting is still an inefficient, luck-based process
- How AI is supercharging broken processes and creating noise on both sides of hiring
- Building trust in agentic driven processes
- Bias, fairness, and transparency
- Challenging deep-seated beliefs about how recruiting gets done
- Where human judgment remains essential in the hiring process
- How Jack and Jill manage their own hiring process
- What does agent-to-agent recruiting mean for the future of hiring?
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Key takeaways
- Matt Wilson argues that most AI at the top of the recruiting funnel supercharges existing processes, producing more applications and more outbound that both sides increasingly tune out.
- Jack and Jill’s agents represent close to half a million professionals and work with around 5,000 companies, building matches through in-depth conversations rather than keyword searches.
- An experiment described in Jack and Jill’s white paper found that both humans and out-of-the-box LLMs consistently exhibit bias when ranking applications, while a well-designed, audited AI system can be measured and improved in ways human-based processes cannot.
- The broad adoption of agents on both sides of hiring will lead to lower volumes of conversations but much higher quality ones.
- Human judgment remains essential to hiring decisions; the purpose of agents is to maximize the time both sides spend in the right conversations, not to remove people from the process.
Transcript
Advert 0:00
Support for this podcast comes from Jack and Jill. Jack and Jill are two AI agents changing how people find jobs and companies find great people. Jack gets to know what professionals want from their careers. Jill gets to know exactly who a company needs to hire. Together, they make warm introductions at the scale of the internet, matching people on far more than keywords and skipping the application altogether. Find your next great hire or your next great job at jackandjill.ai. That’s jackandjill.ai.
Matt Alder 0:38
AI has made it easier than ever to apply for a job and easier than ever to contact a candidate. And the result is a level of noise that both sides are starting to tune out of. So where does the signal come from when everyone is using AI? Keep listening to find out.
Matt Alder 1:14
Hi there, welcome to episode 827 of Recruiting Future with me, Matt Alder. Recruiting is generating more activity than ever, and less connection. Candidates are using AI to produce polished applications at scale, employers are using AI to screen and reach out at scale, and the result is a level of noise that’s eroding trust on both sides. More automation applied to the same processes will only make this worse. Solving it means rethinking how matching works, with a depth of understanding on both sides and transparency and fairness designed in from the start. So what does this look like in practice? My guest this week is Matt Wilson, co-founder and CEO of Jack and Jill, whose AI agents work on both sides of the hiring market. In our conversation, Matt shares why supercharging existing processes deepens the noise problem, how transparency and independent auditing build trust in AI matching, and where human judgement remains essential.
Matt Alder 2:22
Hi, Matt, and welcome to the podcast.
Matt Wilson 2:25
Hi, Matt. Good to be here.
Matt Alder 2:26
An absolute pleasure to have you on the show. Please, could you just start off by introducing yourself and telling us a bit about what you’re doing?
Matt Wilson 2:33
I’m Matt Wilson. I’m one of the co-founders and the CEO of a company called Jack and Jill. And Jack and Jill, we do two things. We built two agents, Jack and Jill. Jack works for professionals and helping them land their dream job. And Jill works for companies, helping them hire amazing people. A little bit more colour on that. Jack works on behalf of professionals. He gets to know you, your background, what you have done. And what your dream job would look like through looking at your background, looking at a CV or resume, your LinkedIn profile, but then importantly, jumping into about a 20-minute phone call with you, much like you would do if you’re getting a coffee with an exec recruiter to tell them about who you were, and what you want so that they can then go out and recognise you. Present you out in the market. Once Jack’s got that really rich picture of who you are, he gets to work for you, looking over every public job listing that is posted every day. So I think it’s about 14 million jobs a day that he’s screening through on your behalf, looking for things that are really interesting, not using keyword searching, but really looking with all of this rich contextual information that he’s got on you. So just continually monitoring to see if anything really interesting comes up and then sending that to you over WhatsApp, over email as you instruct him to. From there, he can support with applications. You can do mock interviews and practice with Jack on voice calls, get feedback, and then all the way through to actually getting an offer, getting comp benchmarking specifically tailored around your profile through to even practising going in and negotiating the salary with the employer. So it’s really end-to-end support that’s free for professionals out there in the world. And we’ve got close to half a million people across San Francisco, New York, London, and beyond that are working with Jack, and Jack is representing them like a Hollywood agent would be representing an A-lister.
Matt Wilson 4:34
On the flip side, we’ve got Jill, who’s doing a very similar thing for companies, really going deep, understanding what a company is looking for. Again, much like a great executive recruitment partner would be doing, peeling back the layers of what’s actually important in a role for a company. And then utilising this large network of professionals is able to make these incredibly high signal-to-noise introductions between the professionals that are working with Jack and the companies that are working with Jill. We’re working with about 5,000 companies, again across the UK, Europe and the US. The company itself, we’re just under 18 months old and we’re just a relatively young company and we are split as a team between the UK and the US as a company.
Matt Alder 5:19
So tell us a little bit more about why you founded the company and why you got it to work this way because there’s all kinds of different flavours of AI in recruiting but there aren’t many people kind of working along these lines so why this why now?
Matt Wilson 5:38
It comes back to thinking about the process of getting a job from the perspective of a professional. I think the way that people go about finding their next job is this like insanely inefficient, unoptimised, kind of luck-based process, right? So what are the ways that people typically will land a new role or even kind of figure out what career to go into in the first place, you know. Maybe they’ll apply for jobs through companies’ websites or through job boards or through LinkedIn. I think the ability to search over the vast number of jobs that are out there is just incredibly poor. It’s a huge job just to go through and browse all of the openings out there. You miss a whole bunch of stuff and you then spend a whole bunch of time putting together an application. Most of the time, those aren’t even being read and you’re not even hearing back from those. So this is a pretty kind of soul-crushing process, super time-consuming. And unless you are in an intense full-time job search, your ability to actually do that and monitor the market and apply for things is really small. So you’re only seeing this tiny corner of what’s possible. Another way might be if you’re lucky enough to have a network, maybe you get introduced to somebody in your network. Again, that’s great, but you’re only seeing this tiny, tiny corner of what’s possible out there. And you know the third way, maybe you go and work with an agency, a recruitment firm, and again they’re only representing a very small number of clients so you’re again only exposing yourself to this like tiny corner of the universe of what’s possible. And I think that for, you know, one of the most consequential decisions that you make in your life, one of the most important things you do in your life, there’s got to be a better way. And you know, for the first time in history, we now have a technology that enables us to get this really deep picture, this really like deep nuanced picture that was only really possible with a human before, but to combine that with the scale of the internet and the scale of technology. So we think we can take the best bits about working with a job board, the kind of infinite scale, the infinite number of opportunities that you can get, but then combining that with the depth of understanding of an amazing executive recruiter. That’s working for you to help you optimise your next move in your career by looking at the entire totality of what’s possible in the world. And that was really the driving mission behind the company is to say, okay, how do we make that possible? And I think as we spent more time thinking about that, it became really clear to us that you needed to work on both sides. Both on the employer side and on the professional side in order to get the depth of understanding and the connectivity that was needed. When you look at what most people are using AI for in the top of funnel from a recruitment perspective, whether it’s on the candidate side or on the company side, it is about taking the existing processes and supercharging them. Okay, you’re a candidate, let’s help you apply for a thousand jobs and that was what you were doing before was applying for one, let’s make you do a thousand. And then on the company side you’re just getting, you know, so many more applicants for those roles, a bunch of them like very low intent, a bunch of them look very good on the surface because they’ve taken the job description and then they’ve kind of inverted this into the application, but then actually you need to scratch on the surface, there’s nothing there. So you’ve got this problem kind of materialising on the company side as candidates are, you know, rationally using AI to go and apply for lots of jobs. On the company side, you’ve got companies now using AI to identify candidates and outreach to candidates. And I think we’re still in the early innings of that, but I think over the next year, you’re going to see very large volumes of outbound being received by the most in-demand professionals, orders of magnitude more than what we see today. And that’s then causing people to tune out from these channels. So we think in order to do this matching really well, you can’t just rely on somebody’s CV, on their LinkedIn profile, on a company’s job description. You actually need to go scratch under the surface on both sides, build up this really rich picture of what both sides have got to offer as well as what they’re looking for. And then you can, through that, make this incredibly high signal-to-noise set of connections between both sides.
Matt Alder 9:45
I think what’s really interesting about this, particularly your focus on the candidate side, is there are some very deep-seated beliefs about how people get jobs. You know, they need a resume, they apply for a job, they have an interview, all that kind of stuff. Now, this kind of turns it on its head a little bit. It sort of changes the dynamics of kind of inbound and outbound recruitment. From a candidate perspective, how do we kind of educate people that this is happening? Have you come across that resistance either from employers or from candidates because recruiting has always worked like this? What’s the sort of dynamics of how this is working?
Matt Wilson 10:21
I mean, we’ve seen like, I mean, we launched just over a year ago and we’ve had, you know, close to half a million people sign up and enlist Jack’s help in helping them get their dream job. And I think the reaction has been incredibly positive. You know, when we launched, one of the big risks and why we wanted to launch so quickly after we started was to say, will people trust an AI? Will they want to talk to an AI on the phone? Like, can we make a really magical experience for that rather than it feeling like this really clunky experience? Is the technology good enough? And yeah, we’ve seen a kind of resounding yes from the professionals that we work with. And, you know, the growth from word of mouth that we see on the candidate, on the professional side is so strong because I think, you know, we talk to people about it for the first time. I feel like I’ve got somebody, you know, maybe an AI, not a human, but I’ve got somebody in my corner that’s listening to me, that’s working for me. You know, so far there’s, you know, unless you are, you know, Premier League football or an A-list, an A-list actor, nobody has somebody, you know, on their side in this process. Whenever you work with a recruiter, they’re being paid by the company. Their incentives aren’t aligned with you as a professional. We kind of turned that on its head and said, how do we build an agent that is fully representing you as a professional? And that’s been super refreshing to a whole bunch of people. I think on the company side, we’ve seen some of that. Working with Jill is like working with a friend that knows half a million people and has had a coffee chat with half a million people about what they want out of their career. That’s a really valuable friend to know if you’re looking to hire. And, you know, the amount of kind of contextual information and the depth of that network and the ability to make these direct connections to those people is super, super strong. So, you know, we’re still very early. There’s still a lot to build out, but the reaction so far has been incredibly positive. So, you know, we’re even more excited now than we were when we started last year.
Matt Alder 12:19
I think it’s really interesting as well, because one of the things that I’ve seen a lot is with AI hiring systems of all flavours, the candidates, when they’re in the system, are having a great experience. It’s, you know, much better than the way things used to be. They’re having a better chance to represent themselves, all those kind of things. But there is a huge amount of distrust out there, you know, not just about AI in recruitment, but about AI in general. Where do you think the kind of responsibility lies for really educating people and building up that trust? What is it that vendors should be doing? But also, what is it that employers should be doing to, you know, really kind of build trust in these processes and illustrate to people that actually, you know, this is a potentially better and fairer way of finding a job?
Matt Wilson 13:03
Yeah. I mean, I think there are a lot of vendors out there on all sides of the equation, you know, inside and outside of the recruitment space that aren’t actually doing a great thing for the world, right? I think building a tool that enables people to apply for 10,000 jobs, I don’t think is really doing A, that person a service, and B, certainly not the broader system a service. I think the same is true the other way around. If you’re using AI to spam to 1,000 candidates with an AI-generated message that you’ve got a job that you want them to apply for, that’s like contributing to a noisy system. So I think, first and foremost, it’s around really thinking about how does whatever technology you’re using, how does it contribute towards a better, more efficient system overall that is working better for all parties within that? And that’s really where we started thinking about how to build an optimistic version of how AI would impact the labour market rather than just going and thinking about how we can optimise one party’s response. One party’s part in ours. I think beyond that, there’s things that we need to make sure that we’re doing from a bias and fairness perspective. I’m very optimistic that systems designed in the right way, audited in the right way, you can measure and improve these systems in a way that is very difficult to do with a human-based system. That’s something we spend a lot of time thinking about designing into our systems. We build out our matching system to make sure that we’re stripping protected characteristics from any data that gets passed into a matching system, that we’ve got a third-party auditor that’s coming in and monitoring what we’re doing. I don’t think there’s a lot of vendors that are doing that, a lot of home-baked solutions that companies are building that are not doing that. That’s a regulatory risk increasingly, but also a trust issue as well. Much like humans, LLMs out of the box will display biases in that selection if you’re using them for building shortlists or for doing screening. So it’s really important that you educate and then approach that in a responsible way rather than just using something off the shelf.
Matt Alder 15:25
What questions should employers be asking around fairness in AI and regulation to make sure that they’re not putting themselves at risk?
Matt Wilson 15:35
I mean, from a regulatory perspective, it differs based off of geography. So it wouldn’t be right for me to kind of talk about that too broadly. I think, you know, there’s lots of resources available online to go and educate yourself about that. But, you know, I think from when you’re looking at a vendor, I think it’s about seeing, you know, what information do they have available? We actually have a blog with a checklist that you can go through to say, okay, what types of things should you be looking at from a bias and fairness perspective? So we’ve got a white paper that we wrote on kind of the state of bias in AI and recruitment, which is available on our website as well. So that’s something that I think is really important that you should be looking through. But ultimately, it comes down to, is this something that the vendors take seriously? Are they being audited by a third party? And then, yeah, there’s a whole bunch of other material that I think would be worth kind of going through and reading.
Matt Alder 16:29
I think it’s really interesting as well, because you sort of touched on this a little bit earlier, that in all of the, quite rightly, all of the focus on is AI biased, what about regulation, we kind of seem to be losing a little bit of focus on the fact of how biased humans are. And actually, humans aren’t necessarily the best alternative to some of these. Where do you see humans fitting in this reimagining of the recruitment process?
Matt Wilson 16:57
Yeah. Maybe kind of two angles on this. I think just to comment on the kind of bias piece, you know, this is something that we talk about in that white paper that’s on our website. But we ran an experiment, there’s lots of third-party papers that have been written about this, comparing humans doing a ranking of applications, a ranking of profiles, like LLMs out of the box doing a ranking of applications, and then a well-designed, well-architected, audited AI system. And it was really clear that hierarchy that came in. Both the out-of-the-box LLMs and the humans, like incredibly, like consistently exhibited bias in those systems. And it’s very, very noticeable when you look at the data. And then, you know, there’s still lots that can be done to continue to improve the systems. But just the ability to measure, the ability to audit, the ability to control what information is being passed into whatever matching stages there are. It’s something that is very, very difficult to do when you do have humans in that initial process. So I’m very optimistic that we can build a fairer system than, you know, not just than what’s possible with an AI out of the box, but also than what’s possible with humans that are kind of riddled with this bias under the surface. I think that said, you know, our belief is not that humans should be, you know, either on the candidate side or on the company side, should not be involved in the recruitment process. Like the AI is like nowhere near sophisticated enough to be able to replace the human judgement when it comes to going through an interview process, meeting your future manager and evaluating if that’s a company that you want to work at, meeting your future team member and evaluating if that’s somebody who’s going to be a great part of your team. And I think AI is changing some of the ways that assessment and things work, but actually that process of figuring out together, is this a really strong fit? Is this where we’re going to make this big bet on this person being a great member of our team? I’m going to make a big bet on this person being a great manager for me, this company being the place I want to be at for the next few years. That is an intensely kind of human process and a human decision. Our view is that we want to maximise the amount of time that people are spending in the correct versions of those conversations. So how do we, on behalf of both the companies and the candidates, connect up small numbers of incredibly high signal connections where there’s a huge likelihood that is going to be a conversation that’s worth having. And then spend all your time doing that rather than spend your time browsing through job boards or scrolling through LinkedIn to find candidates to reach out to. And that to me is where I think we kind of maximise the amount of time that professionals and hiring teams are spending with each other, but only in the right conversations because you end up with a lot of those conversations where there’s just a clean mismatch or it’s not been a great fit from the start and I think those are, you know, what’s the time that we should be eliminating at the top of the funnel.
Matt Alder 20:08
Tell us a little bit about your own experience of recruitment because you know you’re a young company but you’re scaling up fast. This week you’ve just announced a kind of a big round of investment. How do you recruit for your business? What’s your perspective on the whole recruitment process from that side of this?
Matt Wilson 20:25
I mean of course we, of course we use our own, kind of first and best customer of working with Jill. So we work with Jill on sourcing for all of our roles. And we’ve had a large, large, large percentage of our team have come through utilising our own product. I think outside of that kind of sourcing element, the things that we think about in terms of building out our team, we are a young company, we’re a very ambitious company, and we are moving very quickly and we’ve got a lot of complexity in our business. We’ve got a kind of bleeding-edge agentic product for consumers with half a million people using them. We’ve got a bleeding-edge B2B product for companies, thousands of companies using that. We’ve got to then build the consumer marketing motion. We’ve got to build the B2B marketing and sales and service delivery motion. So as a young company, we’ve got a lot to do. And we’re also across just less than 18 months old. We’re in three markets in San Francisco, New York, and London. So we’ve got a large surface and a lot to do very quickly. And that plus we’re big believers in utilising AI to lever ourselves up from a productivity perspective. So we have as many internal AI agents, I think more than we have human employees working in the business. So, you know, those two things place for us a really large premium on having incredibly capable and incredibly entrepreneurial first-principles thinkers in the business. So we have a small team. We’re just over 20 people today. And we treat every single person to our team incredibly, incredibly thoughtfully, incredibly carefully. And we have a very high bar for the people that come into the business. So with that, I think we’re kind of market leading on our compensation in London. We pay for the engineers that come and join the team. We pay over half a million dollars in total compensation to the engineers that join our team in London. Which for an early-stage startup is definitely kind of jaw-dropping. And that is because we think the leverage and the ROI of one incredible person, you know, working and kind of with a whole team of agents is actually, you know, what you’d get out of an entire team of people previously. And just given how much there is to build from scratch and how close to cutting edge we want to be and how thoughtful we want people in our team to be, we’re like very, very thoughtful about the people we bring in. In terms of the recruitment process itself, we try to blend two things. We try to blend a really short cycle time. I think when you’re looking for these specifically these types of people that we look for, being able to run a very quick process so you can get out with an offer to great people before other people are able to complete their process, I think is like a huge competitive advantage. And so we look to be able to run our entire process within just a couple of days, but then also spending lots of time really getting a sense for the person. And then we also have a pretty intense environment that we work with internally. We want to make sure that people get a really good picture of what it’s like to work with us. So to do that, we run a really short process. We do one or two calls and then immediately we bring people in for a paid full day working with the team where we will give people real problems to work on and we’ll work hand in hand with them through the day on real business problems, for a full day and evening, and then have dinner with the team and get a really… For them, they’re getting a really clear picture. Is this an environment that I want to be working in and hopefully seeing the calibre and the quality of the team and the culture and for the right person really opting into that and for the wrong person opting out of that, which is great. And then for us, instead of drawing out over weeks of conversations, we’re able to run this very tight process to get a lot of rich data on that day. If I’m like, okay, this is kind of like day one, like what is it like working with this person and are we able to see them really kind of hit the ground running on that day?
Matt Alder 24:35
Let’s talk about the future around this because I completely agree that the agent-to-agent approach is absolutely the way things are going. I think we can see the trends in recruiting, the trends in candidate experience, and also what’s happening outside of our industry. How does it pan out? How do you see the sort of next two or three years of evolution around this? Because it’s a sort of a shift that a lot of people haven’t really thought of yet or got their heads around yet. But at the same time, things are obviously moving very quickly. And, you know, it seems to be very much what the candidates want. So what does the next couple of years look like?
Matt Wilson 25:11
I think the next couple of years, you’re going to see pretty broad adoption of agents on both sides of the hiring equation. And I think that’s going to be through a mix of different systems. I think if they’re only adopted as standalone agents that are then going and reaching out to companies on the other side, if you’re a professional, or on the recruitment side, and then reaching out or screening internal and screening applications, I think those systems aren’t going to work particularly well. I think actually that they’ll work okay for a while. And then there’s just going to be this kind of cacophony of AI-generated noise going in both directions. And so what we think that’s going to then force people to kind of tune out a bit from this noisy ecosystem and find ways of finding signal in the noise. And for us, that means designing the kind of end state, which is, from our perspective, agents working on both sides, but these agents interacting through a protocol in a network that is designed around finding signal in that noise and is designed around ensuring that both sides are fairly representing their views and that the system is being optimised for signal rather than for noise. So that’s the world in which we think we’re going in. What does that look like concretely as that comes to fruition? And what’s that already looking like for the close to half a million people that we’re working with? It is a brief, right, agent on what I want out of work. I think that’s going to be increasingly something that’s done by all people. This shift in job seeking being this quite intense activity to something that is being run by your agent allows it to be done in the background continually for people regardless of whether they’re in an active or passive state. So I think we’re going to see much more people in passive states monitoring the market and kind of continuously seeing what’s out there. That agent is then looking out for opportunities all the time. And as things come up, it’s connecting you directly in or offering that connection and then connecting you directly in to options you may not have even come across before. Expanding the pool of opportunities that are available to people, expanding the kind of option set and making them, helping people make the optimal choice. And the exact same thing happening on the company side. I think you’re going to shift towards having these agents continually monitoring the market for folks to be a great fit for a given role, for a given company. And then, again, those people you maybe wouldn’t have considered, maybe if you just look at them on a CV or you just look at them on a LinkedIn profile, you don’t get the full picture of who they are. You’re able to consider this much greater totality of what that person is. And then these agents are able to facilitate these connections directly. So I think you’ll see actually lower volumes of conversations happening, but much higher quality volumes of conversations happening with the agents actually taking large amounts of the grunt work out of the process for people.
Matt Alder 28:14
A couple of final questions for you. So, first of all, what surprised you building this company? What has kind of been unexpected or what’s kind of really stood out?
Matt Wilson 28:17
I think the reaction that people have when they work with Jack is often quite an emotional one. You know, when we talk about our careers are so important to us and they’re often things that we don’t really talk about with anybody else. You know, maybe it’s that our friends and our partners and our families just don’t have the kind of domain context to be able to really understand what’s going on in your career at any great depth. Maybe it’s, you know, if you’re in a job search process, it can feel like you’re kind of loading your problems onto whoever you’re talking to. If you’re going to go, you don’t want to go and talk to them for an hour. This emotional reaction that people have when they get on a phone call with an, you know, with an AI and they speak to an AI and they’re saying, you know, we’ve had lots of people say that they cried after the first call they had because it feels like for the first time they’ve been able to express themselves, have somebody really listen and feel heard for the first time. And like, I don’t, I think we thought this would be an impactful, you know, product for people to use. But to actually see this, yeah, it’s such, our careers are so important to us. They’re so emotionally loaded, so tied up in our financial well-being and all of the stress around that. But, you know, giving people a tool, an outlet, somebody, you know, even an AI that is there representing them, listening to them with patience, with understanding, domain knowledge that’s then able to help them is, you know, so there’s such a, like for a lot of people, is this like surprisingly kind of cathartic experience.
Matt Alder 30:02
What would your advice to the TA leaders listening be around AI, what they should be doing, how they should be thinking, what they should be doing right now?
Matt Wilson 30:05
Yeah, I mean, I think there’s a huge amount of noise out there at the moment. And I think there’s lots of vendors claiming that they can do all sorts of magical things. I think the natural reaction to that would be to get quite sceptical, get quite cynical, and kind of tune out from a lot of it. And I think that would be a huge mistake. The technology is unbelievable when it’s leveraged properly, when it’s not oversold by a vendor, when it’s set up in the right way for, you know, thoughtfully for the high-stakes, risk-laden work of recruitment where people’s livelihoods are at stake. And embracing the technology, playing around with tools, playing around with building your own agents or working with AI yourself and then evaluating what problems you want to solve with this technology, what problems do you not want to solve? But being really thoughtful about that. And I think just somebody who is working closely with the technology in recruitment every day, utilising the products after having utilised every other product under the sun across previous businesses that I’ve worked with, the potential here is remarkable for a much better world, I think, for both professionals and for companies and hiring teams. So, you know, I’m very optimistic and I hope that optimism is kind of held by the industry as we kind of go through these early stages of figuring out how this technology is best used, and to kind of look and try to kind of cut through the noise and find the signal in that noise.
Matt Alder 31:49
Matt, thank you very much for talking to me.
Matt Wilson 31:51
Thank you, Matt.
Matt Alder 31:51
My thanks to Matt. You can follow this podcast on Apple Podcasts, on Spotify, or wherever you listen to your podcasts. You can search all the past episodes at recruitingfuture.com. On that site, you can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time, and I hope you’ll join me.
