Matthew Wilson (Jack & Jill) & Peter Specht (Creandum): AI Recruiting Agents, a $20M Seed & the New GTM Playbook

0:00Welcome back everyone to the European VC podcast. Today, we're joined by Matthew Wilson. He is the co-founder of Jack and Jill and their partner Peter Speck at Creandum. Together, they've just closed a 20 million seed round to take their AI recruiting agents global. This is a conversation about how conviction is built in Europe from founding insights to investor belief. We'll unpack both playbooks, how to spot and shape a breakout company at the frontier of genetic AI, and how to build one with speed, precision, and craft. We've had quite a few episodes covering this lately, so I'm looking forward to see how this playbook is different from other things.

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2:56Tear down this wall. It's more than just an alliance. This is a union of values. Let's start acting. This show is not investment advice and the hosts of this episode may be invested in the funds and companies featured. Maybe Matthew, I should allow you to be the one to first tell us in a little more detail than what I just did. What is Jack and Jill all about? Jack and Jill, we're building two products. We're building an agent to help people find their dream job and optimize their careers. And he's called Jack. And we're building an agent to help companies hire brilliant people. And she's called Jill.

3:37The way that these products work is that they speak to their respective customer, really get to understand what somebody wants out of their career or what the company is looking for out of a hire. And then they get to work at trying to make that a reality. So they both do that in all sorts of ways. Jack scours the internet for every job that he can find and sends them through to people, helps people think and kind of coaches them through thinking about what they want out of their career, helps people prep for interviews. And we're building up kind of all sorts of functionality. Similarly on Jill's side, doing whatever she can to help companies find brilliant people.

4:08And then together, these two products are kind of greater than the sum of their parts. As Jack builds up a big network of candidates, Jill builds up a big network of companies that she's working with, they're able to facilitate kind of the most high signal direct introductions and together kind of form the world's most networked, but also most high signal recruitment agency. Very interesting. This is so exciting. And I think this is one of the tools that everyone, the products everyone can understand so that it's going to be a fascinating conversation. Peter, I want to shift to you and ask you because Quiantum, if I'm not wrong, also invested in Bordy Boardman.

4:46And this feels like not in any way similar, but it has similar nuances in terms of it being agantic and coupling people in work, trying to figure out a better way to connect us all. It shows our conviction in the modality of voice, I think. But it is, I think, two completely different use cases and how people use voice in different spaces where Bordy is much more going into any connections that touch your life. and you jack and jill very much focuses on the recruiting part and as matt just mentioned you know the the interplay of you looking for uh the best choices for your career and what's next or someone accompanying your career and companies really trying to recruit the best people and so it's very much here about the focus and sort of like the vertical that a massive problem that we were very excited about it's super interesting and i we should definitely dive into that modality of voice as well and reflected it on a broader scale.

5:44But first, Matthew, let's ask you to dive a bit deeper. Let's talk about the founding moment. When did you realize that this is what you should be doing? Yeah. So just the context on me, this is actually my third startup. And my previous company is a company called Omnipresent, and we were building infrastructure to help companies work with talent anywhere in the world and helping tens of thousands of people find opportunities they wouldn't have otherwise been able to access without what we built. And on the flip side, thousands of companies helping them build incredible teams with great talent that we couldn't have found otherwise.

6:15And I absolutely loved the mission of that company and the difference that we made to people's lives and to companies. And I handed over the reins of that company in 2023. And I took 18 months figuring out what the next thing was. It was really, really difficult to actually figure out, you know, you know how hard it is having been through a journey as a founder. And I think there was a couple of things. One, I wanted to do something that I loved that was on a mission that I really cared passionately about and felt was going to be needed in the world and was going to move the world towards being a better place.

6:46And two, I wanted to build something that I had conviction that was going to build something globally leading and build a really ambitious category defining business. So those are two pretty hard criteria to kind of come across in an idea. And it took me 18 months of really thinking about the way the world was going to move, meeting interesting people. I think the third criteria there is working with somebody brilliant who your values aligned with, skill sets aligned with, and finding the right co-founder. So 18 months of kind of going through the wilderness. Earlier this year, it was kind of mid-February when Saris and I got talking about the thesis for Jack and Jill.

7:24It was about a month of us through mid-February to mid-March of us saying, do we believe that things are different this time? And there's been so many companies that have tried to build talent marketplaces before, and not very many have been successful. Lots have kind of gotten off to a hot start and then stalled out. So we spent about a month kind of really understanding what was different about AI. And I think, you know, voice is a large component there. The ability to match really accurately being a large component. The ability for these agentic products to actually work on behalf of candidates and of companies in a broader setting than just being able to make matches directly.

8:00we spent about a month kind of really building conviction that that was going to be the case and then mid-march we got started so yeah just actually eight months ago today was the day that we founded the company so it's been it's been a busy eight months on our side. Can you ask you Matthew it feels like recruiting has been broken for a long time especially if you hire in a space that's somewhat sexy you're flooded with applications and and now when AI then came in 18 months ago-ish, you then started to have stellar applications written by people that have no background in what you're doing. And it's felt like you really needed something to come in and solve this.

8:38Is this also part of the first principle, thinking that AI is completely, or recruiting is completely changed now because of AI? And for that reason, you also have to change on the tools you use. Yeah, I think that's spot on. I think like most AI recruitment products, whether they're built for candidates, whether they're built for companies, are kind of exacerbating the problems that you've had with recruitment rather than actually solving the root cause problem. That's where we were really, when we got started, I think, keen to rethink from first principles around what does the labor market look like in a world with agentic AI and not trying to just kind of take an existing process and AI-ify it and make it faster and better and cheaper.

9:19And that leads to this kind of explosion of noise on both sides that really think about how you can build a really high signal, kind of high value recruitment marketplace with Agenda KIs at its core. There's actually kind of groups of candidates and groups of companies that have different types of problems as well. I mean, you talked about kind of being flooded with high volumes of high quality looking applications and trying to find the signal from the noise. That's true for certain types of roles and certain types of companies. You end up with an excess of applications and there's a kind of selection problem.

9:49There's also roles in companies that have a really hard time finding quality applicants. So you might put a job out, you might get applicants, but actually there's nobody that's a really strong fit in there. So you have these two different problems on the company side, a selection problem with some roles and a sourcing problem with other roles. On the candidate side, it's similar. You've got some people that are having a really brutal time finding work. And there, it's about sourcing opportunities, about helping them through that process and helping them find something that's a fit. And when it's a challenging labor market out there for a lot of people, on the flip side, you've got some talent that's like in incredibly high demand.

10:23And for them, it's not so much about finding a good job. It's about finding the perfect role and optimizing that decision. And all of those are affected by AI and we're kind of building solutions for all of those different modalities and those different cases that people in companies find themselves in. Peter, maybe you can talk a bit about how you built conviction around this. What was it that made you think, okay, this is the opportunity? If you zoom out at this early stage, the two most important things that we look for is founders and markets and combining that with a why now. And I think spotting these things at the right point in time is the essence of what you do as a VC.

11:00And for context, I mean, at random, one in six companies that we have backed at Cedra Series A have become a billion dollar plus company. So it's all about how can you find those right moments in companies to get behind. And when we saw Jack and Jill, it was very, very quickly actually clear to us. This is this one that, that we feel extremely strong about. And the first reason, if I sell founder market on the founders, Matt and Saras are an exceptional team, smart, obsessed with great company building experience coming from, you know, omnipresent and cooler. I think it's also interesting in which space you built before Matt and also Saras.

11:38The one is EOR, the other one is AISDR, which are spaces there that are extremely fast-paced, that require to move fast, that are selling to similar target groups. So it was a fantastic sort of like, you know, founder execution fit that we saw for this play as well. And then if you look at the market, it's, as Matt described before, it's one of the largest markets out there. It's recruiting is one of the biggest problems, not only for companies as well for people and their personal career choices. And, you know, it has a huge impact on their life. And I think what was different for Jack and Jill is there's tons of solutions you see out there that are tackling recruiting from different angles.

12:21But Jack and Jill is just not another automation play or another recruiter on steroids. They're doing both. I mean, like they're introducing stuff like Jack and Jill, they're introducing a new modality for AI in the space that now actually works with voice. But much more than that, they're two-sided marketplace with network effects. And I think that is different from so many of the, you know, pure agentic AI places you currently see that have, you know, less defensibility or this true value and sort of like the network that is built up in Jack and Jill. So I'm super curious because I noted down the words two-sided marketplace with network effects as well.

13:01And I was exactly curious to dive into that further because marketplaces are a bit different now that network effects are a bit different, I imagine, in the AI era. So I'd be super curious to dive into that a bit. But before we do that, I think to make it super clear to everyone, you described so well Jack and Jill and how they work on each side of the marketplace, so to say. but maybe from the user experience side, could you describe it, Matthew? Just like, I'm a recruiter, how to experience Jack? Or I'm looking for a job, how to experience and interact with you? Yeah, so let's take Jack. I think that's something everybody can emphasize with.

13:41If we want Jack to help you find the best job out there for you and help you make that a reality, the first thing that Jack needs to do is he needs to understand who you are, what you're looking for. And these things are actually really complicated. How somebody thinks about their career is it's not a set of five or six criteria of job title, compensation, location, industry. It's really complicated. And I think the premise that we started with was if we were looking for a job and we wanted to have somebody on our network help us out with it, I wouldn't send them an email. I'd go and get a cup of coffee or a beer with them.

14:18And I would sit down and I would say, okay, here's a bit about my background. But actually, here are the things I'm looking for. Here's how I think about this. Here's the things I care about. Here's my take on this space. Here's the types of things I love doing. Here's the types of things I don't love doing. Here's the types of people I like to work with. Here's the types of culture I like to work in. And how do you replicate the extraction of that depth of context? The way that we think is most natural is the way that we do it as humans, which is over a conversation. So the experience starts with sharing a little bit about yourself, your LinkedIn, maybe a CV if you've got one to hand.

14:51but then jumping into a two-way conversation, a voice conversation with Jack, our AI. And that is a kind of magical experience. I think it's a real wow moment for so many people that aren't used to having these types of conversations about their career. And through that conversation, Jack's digging in, probing, understanding exactly who somebody is and what they want out of their career. And once Jack's built up that kind of contextual understanding, he then gets to work helping make that a reality. So he looks at every public job listing in the world that gets posted and shares them with you if they're relevant as they come available.

15:23He can help you, coach you for various opportunities. Oh, I'm applying for this. Can you give me some feedback on my CV before I send off my application? Here's the draft of my application. Can you give me some feedback on this? You can do mock interviews with Jack. Okay, I'm interviewing for this role. Let's role play this. And then you also get direct introductions to companies that are a perfect fit where Jill has gone and done that deep discovery on the other side as well. So I think that the structure of both products is deeply understand the context and the nuance and the depth of how somebody thinks about themselves in their career and then kind of build whatever agentic products we can to help make that a reality.

16:00And then interface with them where they naturally are already. So email, WhatsApp, there is a web interface, but you never need to go into the web interface to actually use the product. You can do it entirely over email and building that kind of ergonomic way. similarly on the company side i really understand what a company's look you know what types of people succeed at a company what they're looking for yes you've got your job description there's so much more to it than that so again replicating the conversation you might have with an agency recruiter briefing them on on who you're looking for and then from there how you jill can can can share candidate profiles from the candidate pool of 60 000 candidates that have spoken to to jack and can help out with uh with a bunch of other things around the recruitment process which we're working on as well.

16:43If we then talk about it as a marketplace, the natural problem that you often have in a hiring situation is that on the person that wants to get hired side, there's sometimes a posturing element and you have that interest. And on the other hand, as the recruiter, you're trying to uncover the truth. I imagine that you as the AI that then interfaces and kind of does the matching as well, you could have that agency problem between who am I actually working for you. Yeah, that's a great point. And it's exactly, if you think about the name of the company and how we've built the product, it's built with two agents.

17:19It's built in that way because Jack works 100 % for the candidate and represents the candidate's interests 100%. Will works 100 % for the company and represents the company 100%. And there's information that you would share with Jack who's working for you that you wouldn't necessarily share with the company. That's the kind of core insight that we had as we built out the product is, if you look at like Cuban recruitment agencies, they have this huge conflict of interest. It's one person that sat in the middle of the relationship. They've got their own incentive structure that they're primarily optimizing for.

17:51They'll get paid once a hire is made. So they end up kind of selling and overselling at times opportunities to candidates and candidates to companies and trying to kind of bridge this incentive conflict between the three different parties involved. whereas with our model, Jack is not actually optimizing for Jack and Jill. He's optimizing for the candidates. We take a fee on hire, but actually we kind of trust that by building these two agents to represent their own customer entirely, that will build the best product for both sides in the long run and that will lead to the kind of growth of our business over the long run by getting that perfect incentive alignment.

18:32So yeah, that's kind of a core insight behind how we built the product with this two-agent model. I think the interesting part here is actually that if you think of AI doing this and how you've done it and splitting it up into two AI people in Jack and Jill, it is actually, I think, the better product than a human recruiter over time. And AI is ideally suited to keep memory of all those data points it learns about people and really remind them all the time at all points in time. And the same goes for companies, which, you know, humans, we will always forget one or two things. But really, if you think this through at scale, it's actually not only like efficiency or more automation or less costs or whatever.

19:14It's actually the better product that will more likely match more people to the right firms. I want to ask about the coaching side, because you mentioned it as an aside. but I imagine that it's something that's really good to ensure the stickiness of the product and people getting into the funnel early as well. I'd be curious to understand that side. Something that's so important to us in our careers and what job we do, the amount of careers kind of services that people use is like woefully small and the quality of the products out there are not great. With AI, we've got this ability, it can kind of dramatically reduce the cost structure, I think massively improve the quality of the products that are out there for helping people think about what they want out of their career, think about making that a reality.

20:00I think we've been talking about this product as a marketplace. I think that's one lens to look through the product on is that you've got this two-sided marketplace with two agents that are facilitating the introductions. I think the other way to look at it is to compound AI products. And that's really how we think about, first and foremost, think about Jack and Jill is saying, if you had a hundred people working for you to help you out in your career what would you get them to do for you and how do we then build jack to be able to do that so you'd probably have somebody giving you coaching you'd have somebody going in and helping you prep for interviews you'd have somebody else going and reading through all of the all of the job boards you'd have somebody else reviewing your applications as you're sending them off you'd have somebody else looking through your network and thinking about who you could get introduced to that's how we think about building out jack and and you know actually the network is only one of those hundred people that's uh that's actually out there going out looking at who Joel's speaking to.

20:49So yeah, coaching and helping people think about what they want out of their career and then helping them make that a reality through whatever needs we can do is a big part of what we're building out with Jack. Peter, I'd love to ask you, if you describe your thesis around it as a marketplace with network effects, can you elaborate on that? The more people are on each side of the platform, the better the value for both sides are. And I think it's the network effects in a very classical sense, right? Every customer on both, every user or customer increases the value of the platform. That is the simple math behind it here.

21:27Yeah, I think, you know, to just make it really real, if you imagine you had a friend and you're looking for a job in startups in London, And that friend had actually, in the last two weeks, had spoken to 400 different hiring managers across startups in London to really understand what they were looking for. You'd go and talk to that friend if you were thinking about making a move and think about who they could introduce you to. Imagine if they spoke to 4 ,000 or 40 ,000, and they'd also spoken to all the people in New York and Paris and Berlin and San Francisco that could also potentially hire you.

21:57the more people that that friend has spoken to the more you'd want to engage with them and keep keep tabs on what they were what they were seeing in the market because they might have something super interesting for you and vice versa if you're a company and you've got the most networked person that you know that deeply understands what 60 000 people want out of their career if you're hiring you're probably they're probably the first person you go and tap on the shoulder and say hey i'm thinking about hiring somebody for this role do you know anybody great and you can imagine as that scales up to 600 000 to 6 million people how valuable that friend would be and if that friend could have like this incredible, perfect recollection of all of those conversations and some of those relationships over the years.

22:33You can imagine how kind of that, how valuable that friend would be. Matthew, I wanted to, because you've built Omnipresent as well and have tried to build a company, so to say, before the era of AI. And now you saw that there's a big opportunity and you decided to go at it again. But now you're building a company in a completely different context that everyone who's building now are saying, I've never tried anything like it. And many of the things that we did before, we would do completely different now. I wanted to ask you about the AI playbook, but I think we should go about it from the angle of a 20 million euro seed bet or a 20 million dollar seed bet, because that is, of course, a very significant investment round.

23:13And thus, you're now about to truly scale up the company and build your way into the market. And I'd love to ask both of you, what does a growth journey like this at the seed stage look like today when you're raising 20 million? What are the next steps, the things that are different from maybe a 5 million or 10 million seed round five years ago? And Peter, maybe you can reflect on a more abstract side first, like how is today different and why are the seed rounds so much larger? And why does it make sense to make such large seed rounds today? If you zoom out, it's always about two things you look for.

23:50It's about, do you think this company has outlier potential and operates in a huge market and is on a great track to execute on that? Then you look at where does the company stand? And it's true that the market has evolved where rounds have become, round sizes have increased. That said, I think Jack and Jill is one of the, still also an outlier on the round size and sort of like the round they've raised of one of the larger ones, etc. However, they've also executed in the first, you know, six, seven months since inception of the company, like rarely other companies do. And so it's a reflection of the speed of execution of the team that is behind there.

24:33You know, the fantastic and strong early momentum that the company has. I mean, getting in on 50 ,000 candidates on the platform, if you actually talk to users, like very strong initial user feedback. So there's meat behind it on what has been built so far and how strong one can grow from here on. When investors look at things, you look at where do we think this company will be in 12 months or 24 months. This is also something you factor in and to sort of like around. And here we think this can grow extremely fast. And the fact that Matt and Sarah are our founders that also have done it before, know how to do it, know what the next steps are and know how to put that money to work is something that is important when you do a large round like that.

25:23And so it's a space where you should build the best product fast and deliver sort of like value very fast to users on the platform. and how our thinking was like we we want to enable jack and chill with with the amount of money sort of like that gives them the best shot at it and and gives them no limitation on executing on that plan as fast as possible i think as as peter said like we're here to build a global cash-related business we're going to do that as quickly as possible the pace has changed between how companies build today and how companies built in two two years ago three years ago the speed at which you can grow the speed at which you can build 10x better products and i think the speed at which you need to grow if you're going to build a leader in a competitive base.