Will AI Kill White-Collar Jobs? | Matthew Wilson, Jack&Jill CEO

Jimmy's Jobs of the Future

Jimmy interviews Matthew Wilson, founder of Jack and Jill, about the disruptive impact of AI on the recruitment landscape. The discussion ex

Key takeaways

• Matthew Wilson's startup, Jack and Jill, has scaled to 350,000 users within 15 months of operation.
• AI automation is making job applications and outbound recruiting 'infinitely cheap,' leading to a breakdown in traditional CV-based signaling.

Main topics

• AI-driven recruitment noise
• Jack and Jill AI agents

Notable quotes

The processes become infinitely cheap. And then over time, these channels kind of stop working.

Conclusion

The episode provides a forward-looking perspective on how AI agents ca

Transcript preview

Speaker 1 (0:00) Welcome to Jimmy's Jobs of the Future. Today I'm joined by Matthew Wilson, the founder of Jack and Jill. Anyone that has tried to apply for a job recently or tried to recruit knows how complicated the market is getting due to AI. It's extending the processes on all sides. It's a real challenge and Matthew and Jack and Jill are looking to try and solve this. On to today's episode. Matthew, welcome to Jimmy's Jobs of the Future. I really enjoyed one of the descriptions that you have on your LinkedIn profile about how both the recruiter and the employee's spam cannons are pointed at each other. And it's just getting worse and worse. Not a day goes by where the mainstream press doesn't cover somebody who's applied for 200 roles and not got everywhere. And it's not just at the junior. There's always been a factor of that at junior levels over the last decade, I think. but it's also now happening to people kind of midlife as well. And it's a real challenge. What do you think about the kind of traditional status markers and how they'll change? Because Schlombing talks about CVs dead anyway, but I agree even more now that it seems like that era is coming to a close. But how do you see those changing? Yeah, I think you've got... Speaker 2 (1:22) You know, when there's a new technology with AI, the most obvious thing to do with it is to say... What do people do today? And how do we use this technology to do that, you know, faster and cheaper? And that's happening on both sides of the table with recruitment at the moment. You can now have an individual, you know, at the click of a button, go apply to, you know, infinite number of companies for me. And the CVs look great because they've taken the job description and they've like, they've tailored it for that. And that's... That's causing a huge problem for employers. And then on the flip side, you've got employers that are doing this in two different ways themselves. They've got this, you know, you talk to certain people and they get, you know, 1,000, 10,000 applicants for a role. Well, it's just infeasible to look through that number of applications, particularly when on the surface they all look great because a lot of them have been using AI to write these applications. So then you need to kind of go into this war of going, okay, how do we slim this down and how do we cut through this noise? On the other side, you've now got this ability to research. You've got your job and instead of, okay, maybe this is so noisy for all of these applications I'm getting, why don't we go and outreach to people and find people that we think could be great and go and persuade them that they should work with us. And that's now becoming fully automated as well. So you can now take a job description. and put that into a tool, get a list of the top thousand people in the world, and then at the click of a button have personalized outreach that goes out to all of those people. So then what happens? The people that are in demand from a lot of companies are just getting hammered with all of this outbound from companies. So this is the natural conclusion of what happens when you have a technology that automates some processes is that the processes become infinitely cheap. And then over time, these channels kind of stop working. Explain to us what Jack and Jill does. Yeah. So Jack and Jill is a 15-month-old company that's working on two AI agents. Jack, who helps people find their dream job by understanding who they are, what they've done, what they want, and then supporting them through finding the best jobs on the planet for them, scouring the entire market for them, and supporting them, whether that's through mock interviews, through salary benchmarking, or whatever else he can do to support. Jill, on the other side, is working with companies to help them hire amazing people. Today, we have about 350,000 people working with Jack, primarily in the tech markets in London, San Francisco, and New York. And we have thousands of companies working with Jill. I think, you know, we think about... How do we get the jobs that we get? How do we end up in the careers that we're in? You think about it from the perspective of a professional and how they navigate through their career, from figuring out what career they want to do to landing that next job. I think it's this crazy setup. I think back to when I was a student graduating and all of these job titles that I had no idea what they meant. And you make these decisions with such limited information, oftentimes based off of, you know, who, you know, if you've got the privilege and connections, who you happen to know, or just based off of kind of a series of accidents. If you ask people, how do you end up in, you know, as a lawyer, how did you end up as a management consultant? How did you end up as a designer? How did you end up as a recruiter? You know, people have these just kind of like random walks into what they do. And then that sets. you know, what they do for most of the day for the rest of their lives. And, you know, and then if you look at the, actually, you know, you're in a career and you're looking to make a move, you know, for whatever reason. How do you land that next job? Again, it's this kind of random mix. You can go and look on LinkedIn or on some job boards and apply for jobs, and you get served with some random slew of whatever pops up at the top of there, and you send off some applications, and which applications get read and respond to you. You kind of end up going down that path, or you maybe have people in your network that you can refer into, again, if you've got people that you know. Speaker 2 (5:45) But, you know, or you are, you go and talk to a couple of recruiters and, you know, maybe they're representing three or four firms at that point in time and you end up with one of them. And you've just covered like 0.1 % of the available opportunities that there are in the world. And in this way of like, in this kind of careless way of just like, oh, whichever one of those things kind of pops through and maybe I'll seriously consider 10 things. But there was like 10,000 things that you could have done. Did you consider that you could have moved to New York and could have done this job in New York? Speaker 1 (6:16) Did Speaker 2 (6:16) you consider that you could have changed your career completely? Like maybe there's a great job for you in an adjacent field that would actually tick all the boxes of what you're looking for that you just don't even, it's not even on your radar. And yeah, and then that process for a lot of people of going through and actually going through the application process, the interview process is incredibly painful and soul-sucking, demanding process. And it's a really awful process for a lot of people. And people just don't have help throughout all of this process. So we think about how do we... You know, we now, for the first time, the technology exists to understand somebody with software at a really deep level and not just say you're a set of filters on a job board or you're what you can fit on a page in a CV or you're a set of keyword filters. and say, okay, we've got the technology to build an agent that works for you, that you explain who you are, what you've done, what you want, with a ton of nuance. And we do that with a voice call with an AI. And then with this rich picture of who you are, the kind of picture your friend might get if you went and sat with them for a coffee. Speaker 2 (7:28) That AI can go and work for you and it can survey all of the job listings that are out there in the world and only send through the ones that it thinks are like a 10 out of 10. It can help coach you for an interview. It can help... This is our agents called Jack. Jack can help you think about, you know, look at all the job listings and think about what you should be paid in that next job. So you can go in armed with a good set of data. If you are at the start of your career, you're considering a change, you can do a career coaching call. And, you know, all of this is now available to everybody and we offer that service for free. And so that's what we do with Jack. On the flip side, you know, the exact same thing happens when we're hiring people and the exact same set of... compromises of only considering a small corner of the universe, of having tools that don't have the ability to handle the nuance that we think about when we're thinking about our careers or hiring. So we've built an agent called Jill, who is speaking to companies, understanding exactly what they're looking for, like a great executive recruiter would be, but for every role, and with then access to the network of people that are... working with Jack. So these two agents can then build this, you know, kind of infinitely scaled network with incredibly deep nuance of what companies are looking for, what people are looking for. So you can make incredibly, incredibly precise matches at scale. And that's not something that's been possible before. Instead of taking how things are done today and thinking about how we can do them faster, why don't we think from first principles around how this should work? What would be the best possible way that we could construct this? And imagine you could have your own AI that worked for you, that you could tell exactly what you wanted. And that AI, if you're looking for a job, and that AI, it was actually connected up into an AI on the other side of the table that was working with thousands, tens of thousands of companies working across their roles and knew exactly what they were looking for and was then able to, you know, kind of skip all of this inefficient process and just go straight to, you know, here are the five best opportunities out there for you that we've got a direct connection and we can just introduce you directly. You don't need to apply. And you're doing that based off of, you know, maybe you've spoken to this AI about what you want and what you've done for 40 minutes on a couple of phone calls. So it's got this really rich picture of who you are rather than just your LinkedIn profile or just your CV. So that's how we think about. what's happening in the market today, why it's happening, and what our approach is and why that's Speaker 1 (10:02) different. Speaker 1 (10:06) Let's get kind of really meta with some of this stuff. You and I are both a big fan of Charlie Songhurst and the kind of content that he creates. And he talks a lot about how you should spend your early years career. And perhaps because we're recording on A-level resorts day as well, though it won't be out for a few weeks. I'm particularly thinking a lot about those kind of early years and what happens. And I don't know what I would put into an LLM today. Because part of it is you need to go out and get the experience. to know what you do and don't like. What's your advice for young people thinking about that? I think that's Speaker 2 (10:42) right. I mean, I think you need some experience, but... I think you're doing people a little bit of a disservice if you say you just need to go and do something random to find out what you do and don't like. And you can't have some agency in thinking about what those things should be. I think you can have an AI that is able to not just be a blank text box, but be a thought partner in something. Think back to what I was saying earlier about me being a graduating student coming out into the world of work and not even knowing. what the words meant in the job titles. You know, it would have been great if I could have sat down with Jack and said, OK, look, I went to this careers fair. I met this private equity firm. I don't really know what private equity is. What does it mean to be in private equity? What does a career in private equity look like? How do we think that might change over the next 10 years? And Jack would have a pretty good perspective on that. He'd also have a good perspective on what does it mean to be a management consultant? What does it mean to be a software engineer? What does it mean to be all of these different things? And, you know, if I could say, okay, well, what does that career look like over a 10, 15-year period? And what does the first year of that look like? And what might I learn from that? And I think, you know, a thoughtful young person that would be able to have that would be in a much better position to make a much better informed decision. And maybe that decision is... I do this for a year and it's my bet as the thing I think I'm going to want to do. And a year later they go, actually, I've learned something. I want to go in Speaker 1 (12:20) a Speaker 2 (12:20) different direction. And then they can go and have a similar conversation again. But I think that equipping people with some sort of compass, some sort of tools about where they could end up going and what even the world of work looks like if they've not come from a background where they've been exposed to these things or they don't have the people in their family or in their extended network that is. and going to be able to say, hey, I've worked in private equity for 30 years and I'm going to talk you through what it looks like. I think that will give people so much more clarity in terms of what they can look at. Speaker 1 (12:57) And what about your kind of personal experience? You started, your schooling was, you know, just in the Yorkshire Dales, et cetera. Like it's quite removed from London, San Francisco, et cetera. How's that kind of shaped your view? Speaker 2 (13:12) Yeah. I mean, I think, you know, maybe I might just tell my personal story a little bit. I grew up in the Yorkshire Dales. I went to grammar school in the Yorkshire Dales. I then... went to study physics and maths at Oxford, I thought I was going to be an academic. I thought I was going to go and do a PhD and pursue a career as a very romantic theoretical physicist thinking hard with a pen and paper and a pencil all day around how the universe works. And then I... I did an internship for a couple of weeks while I was doing my master's in between a couple of the terms. And I did an internship with a guy that had dropped out of Oxford and he was from Yorkshire. And he had set up in Batley. If anyone knows where Batley is, it's a town in between Bradford and Leeds. And it is about the furthest place in the world from Silicon Valley. And, you know, close to where I'd grown up. And he'd set up a one-person startup while he was at Oxford. Before, when he was 17, he'd set this up. Speaker 2 (14:36)