The Future of Recruiting: Data, Agents & Real Efficiency with Metaview’s CEO Siadhal Magos

So welcome to the podcast.

Thanks, man. Proud to be here.

Sat down a year or so ago. Yeah. And I was just saying to you, like, really interested to speak to someone that is really in the trenches right now of building an AI company. Yeah. Particularly for my world, the recruitment ecosystem, which is also your world.

Yeah.

I've been a huge advocate of your business, MetaVie. I think it's a really cool product. Recently, got shown and championed your sourcing agent, which I also think is really cool. Yeah. I mean, this is a whole nother world, words now that we hear a lot more around agent. So I definitely want to talk about that, but what's been going on in your world over the last year? I know that you raised a bunch of money, but just give us some of the highlights over the last year since your last sit down in your world.

Yeah. I can't believe it was a year ago. In some ways it feels like much more recent, in some ways so long ago because so much I think has changed. So yeah, for those that I guess don't know, Metaview, AI platform focused on recruiting, really gained a lot of, I would say, love and market share with when we initially launched with an AI note-taker built specifically for recruiting. And there's a bunch of really smart stuff you can do when you really focus in on what do recruiters, recruiting leaders, people who are involved in recruiting, even hiring managers, clients, etc. What are the things they care about off the back of their meetings and conversations? When you really dial in on that, you can do really magical things. And so probably when we spoke this time last year, we were still writing. I mean, there's still a bunch we do to make the Notetaker a world-class product, but we, that was the core. That was the product. We were a notetaker for recruiting. Always the thesis of the company has been in recruiting, the most important data is in those conversations. And so by being the home for those conversations, you can start to actually help people with a lot of other parts of their workflow as well. So whether that's them doing sort of market research about compensation expectations for a certain job role in a certain market, or whether that's finding new candidates to add to the pipeline and then reaching out to them, all of those things, if you're going to use AI to do those tasks, to do that work, the AI is going to need to know what's happening in the surrounding conversations in order to be maximally informed. And so To answer your question in maybe more shorter and more elegant, what's changed over the last year for us has been really leaning into what are the agents and applications you can build on top of the conversational data to make recruiters significantly more efficient. That's what we focus on.

And then let me know if I'll get this wrong when, because I was looking at the website again this week. So you've got AI reporting, AI job ads, job posts.

Yeah.

Job posts.

Yeah.

Obviously got the sourcing agent. Is there one more that I'm missing?

There's just a core note taker.

Oh yeah, yeah, yeah. Because you're completely right. It's like you can then, from the examples that I've seen, you can then just type into it what are like, what is the consistent salary that people are asking for with this job title, or yeah, and then it can go away and find that, that those— yeah, yeah, yeah. Data.

Yeah. Which is one of the things we talked about last time. I know we're going to talk about it more, is around, uh, I think people in recruiting need to start to think and start to you know, really take deliberate ownership of the data that they have that isn't out there in the wild. So the example that you just gave there of what are compensation expectations for a candidate of XYZ, uh, Metaview doesn't answer that based on some sort of proprietary data source that we have. It answers it based on the proprietary data source that you have. So if you've spoke to, you know, 500 engineering candidates over the last year and every single one of them you've asked them about compensation expectations and the fact that you can, your ability to sort of manually recall, you know, just using your own intelligence recall, well, how does that average out? And how's that changed over time? That's really hard. People can't, that's not something humans are good at. But for an AI, that's really easy. If you want to say, hey, of the last 500 conversations I've had with engineering candidates in London, how have their compensation expectations changed over time? That's very easy. And, but it's also proprietary data that you have. It's not something that every, all of your competitors have. And it makes it, you know, If should I take that one additional conversation with this candidate? Well, yeah, you probably should because you're actually starting to build up more and more of your own data that you can use to influence clients, to influence and close candidates, whatever it might be.

Let's just talk about this because I do think this is something that we spoke about last time and I think it's, it's like never been more truer with just like how this landscape will no doubt just continue to evolve, the amount of money being pumped into it.

Yeah.

But particularly, I don't know if like you see this from your seat, but I've interviewed a lot of founders over the last 18, 24 months. A lot of companies have really struggled post that real boom period.

Mm-hmm.

And one of the things that really tripped people up was their LinkedIn licenses and going from saying, yeah, let's go on this big enterprise package. Yeah. We've got 50 recruiters in the business. We're absolutely flying. The demand's through the roof. And maybe didn't quite see some of the signals that then, then they've now got a business of like 15 people, but they're paying for 50 licenses.

Yeah.

And from the conversations that I've had, LinkedIn don't care. Yeah. For the most part. That aside, the reason why I'm bringing this up is I think this sort of dependency on what you're talking about there, just relying on data that everyone has access to.

Yeah.

And being a recruitment business that's just a thin layer on top of LinkedIn. Yeah. I do think like you're really in trouble if that's what you are, if we're being really brutally honest. And the reason I'm bringing this up is when I think about your product, like the sourcing agent, I know that way it's going to continue to go. Correct me if I'm wrong here, but that's going to really, a tool like that is going to really enable me to get the most out of the data that I already have versus always thinking about new search. I need to get new data. I need to do my LinkedIn recruiter. But actually, I'm sure you've seen this. One of the biggest problems a lot of agencies have is just they're sitting on so much fucking data that is gathering dust, isn't actually updated.

Yeah.

But if, imagine if we had all of that data tagged with all the conversations that people have had.

Yeah.

And that's where we can go.

Yeah.

Do you, does that show up in your world in terms of like LinkedIn? Like that can be one of the company's like biggest costs, LinkedIn.

Yeah.

And then also companies feeling like they're so dependent on it.

If it shows up a bunch, I might, I might have to, I think that like to answer your question fully from, with, from my perspective, we need to zoom out like one level even further than that. But just to answer on LinkedIn, uh, listen, LinkedIn is where like the vast majority of profiles of candidates you might want to hire lives. And so they, they, they build tools on top of that. And, uh, it totally makes sense that if you're, when you're building a recruiting business or if you're in-house talent team, you need your people to have access to that. That those profiles, otherwise it's going to be really hard. And so, I don't know, business practices notwithstanding, obviously they've built something very valuable that I use a bunch when I'm hiring for my company and, you know, they run their business the way they run it. I don't look at Metaview as like a, um, as in there's no sort of almost like competition there. It's, but what I also agree, if that's all you are, if all your recruiting team is, are some people that happen to have a LinkedIn recruiter license, then obviously you're in a pretty in a bad spot because actually very soon you'll probably have AI agents that have LinkedIn recruiter licenses, you know. So the whole, this brings me on to my, I think the more foundational point, which is you mentioned earlier with agentic AI or agents is coming up more and more. That's probably one of the things that's changed in the last year is people are talking about AI agents all the time. I think what might be useful for folks is to have a little bit more like a framework for thinking about what an agent is. For us, an agent is, there's sort of two sort of key attributes to it. One, it's an AI that doesn't follow specific sort of task-level commands, but is instead given an objective, a sort of an objective function, and then figures out for itself how to achieve that. And then that brings us on to the second point of an agent that's interesting, which is in order to do that, they need to have tools. And so just as when, if you're a, you know, a founder of a recruiting firm, you hire people into your team and you give them tools. And one of those tools might be LinkedIn Recruiter license, and one of those tools might be an email client, you know, all of these tools that your human agent has access to, AI agents now have access to those same tools. So the biggest thing, if I could sort of summarize the biggest shift from last year to now, or the biggest feel the artificial intelligence moment for everyone, you need to understand that AI now has access to tools as well, or put another way, AI can use your computer. And so whatever you think, whenever you look around your organization, when you look at yourself and think, what am I spending time on? If it's very heavily fingers on keyboard doing work, you know, clicking around my browser, etc., AI can do that work now as well. And so that's obviously going to bring around massive change and massive disruption, massive opportunity, obviously, for folks who, you know, are running firms, for example, and, you know, almost just need people to fill the seats to find more candidates. You can ask AI agents to do that now as well.

I'm glad you explained that because I was going to ask you to like, how did you, I think you did a really good job there of just like explaining it to people because I think with these types of conversations, you can always hear these words, but sometimes you haven't actually spent the time to define what an agent actually means. Yeah.

But just before you move on, just, I think the reason that's almost, that's relevant is because I do wonder if there's this moment in time where of course you scale up a team, you give them all these tools, But in many ways, yeah, some of that, the tooling is going to change in that these tools are also going to become appropriate for AI agents to use as well. And we, so we think a lot about what are the tools that we build for our AI agents so it can do things, do amazing recruiting work, but also how do we train it to be able to use the same tools that humans already use so that, you know, you can, rather than scaling your team and then realizing, oh damn, we're left with all of these outstanding licenses, maybe actually you've kept your team a bit leaner. You've brought on 3 to 10 AI agents for things that you can obviously scale up and down much more fluidly. And they have access to sort of this different set of tools.

Just on the agent piece, as you're talking about it, so correct me if I'm wrong here. So I don't know where you are on the journey with it, but am I right in thinking that your sourcing agent will be able to, I don't know if it can do this now, but when you like, you could do it like a prompt, like I'm certain I need to find someone with this skill set. 'cause I did it for my business. Obviously it can go and search on like LinkedIn, but would that also then be able to search my ATS?

Yeah, so great question. Over time, MetaView's AI agents will have access to as many tools as you can imagine. So if you, if you, if you're, if the members of your team have access to an ATS over time, MetaView's AI agents should have access to that too. And you can line up any number of tools. So when we first, one of the, some of the, it was a funny, it was like a funny coincidence when we first launched the sourcing agent. Actually, a handful of the first customers we spoke to were at AI research labs. And so they do a lot of this. One of the places they go for their sourcing is they go to Google Scholar, which is a place where you host lots of, there's, they host lots of research papers and they want to see who are the people who are cited in these research papers because that probably means they're really smart and they know that they know AI. And so they wanted Google Scholar to be one of those tools, one of the tools that the AI has access to. So anyway, to answer your question very directly, yes, at the moment, our AI sourcing agent has a few databases and tools that uses, it uses publicly available data. So, you know, things that are on the internet, basically, it uses your ATS or CRM. But over time, we'll add more and more different tools, just as when you onboard an employee, you might think, well, first of all, I'm going to give you access to a computer with a browser on it and a LinkedIn account. Oh, you're now I'm going to give you access to our database. Hey, I'm actually going to, you know, you should actually unlock you on this tool as well. You'll treat AI agents the same way.

Right. Yeah. Yeah. Yeah. Because I think then that'll be where it would be really powerful because then I'm assuming it can then also go to all of the data that we have around the conversations in MetaView. Yeah.

Yeah. Yeah. So Meta is, it's a bit of like a meta situation in a way where MetaView, the note-taker, is also a data source for MetaView, the AI sourcing agent, which is funny enough how the whole thing started actually, because we had two sort of really interesting situations. One, people would go back into their historical conversations to source candidates. So if you're a customer who's been with Metavy for 2 years, and you know, you've spoken to someone 18 months ago, and you sort of have in the back of your mind, I'm sure there's someone who I spoke, maybe, maybe it's 6 months ago, I'm sure I spoke to someone who would actually be really good for this. And you can sort of like fuzzily explain some of the things you recall about that conversation. You can't put in particular search terms like their name was this and they worked at this company, but they would use MetaView already to, for like, hey, who was the person who I spoke to who like was XYZ? And it might come up with 3 or 4 options and you realize, oh yeah, that's the person. So we've, people have already been using the note-taker product for sourcing. And so that's why we expanded it to, well, let's include that outside people, to people outside, people you've had conversations with. Um, so that was, that was the sort of a big, big inspiration for it. And then the second thing that made it such an obvious priority for us was a lot of people when we first launched MetaView, people would use the note-taker mainly in candidate conversations. But of course, so much of a recruiter's business is meeting with clients, getting to understand their requirements and all these things. And so we built a new summarization model specifically for intake, for client intake. So, you know, so you can store really accurate data on what did this client say they're looking for. And of course, what do you do after you do a client intake? You take that summary of what they're looking for and you use that almost as your your baseline material for sourcing. So people were already using MetaView to almost set their sourcing strategy, but now we've just given them the tool to actually do the sort, like have our AI do the sourcing for them off the back of that call.

Yeah. Makes complete sense. So there's a couple of things that I'm just curious to get your take on because of the business that you're building, the city that you're in. So I've, like, I spend most of my days, weeks speaking to Obviously my world is like recruitment agencies, founders, recruiters. And I don't know if this shows up in your world or conversations or on your sales team's conversations, but I do feel like there's this real tension at the moment I find between on one hand you've got a business owner who's being told every single time they go online that they need to be efficient. We've got AI that can do all these different tools and like just efficiency, efficiency, efficiency. And then you've got this other side where they're really mindful of like how they're showing up in people's inboxes, how they're starting conversations with people. They experience it, they're experiencing themselves where like they're just inundated with like just AI, just shite in their inbox all the time. Yeah. And they don't, they don't want to be all the way over here where it's all efficient and then they can't be relevant and they can't show up the way they want to. But then this person might feel like they're behind and they're going to get left behind. And then, so a lot of my conversations conversations, I'll be honest, like this year, and it'll really vary, but I've had a lot of conversations where people have gone down that AI rabbit hole and it's like, let's be efficient as hell, no time on sourcing, that's— yeah, like, don't use all that, agents for this, AI for that. And then they've ended up— and this is normally for context— on typically, I'd say, the part where recruitment agencies have a lot of pain, which is business development and sales. Yeah. So they're trying to like get that sorted and they go down that path and then they find themselves in the same position or maybe worse position where they're not getting the results that they want. Yeah. And then they find themselves going back to doing the legwork of like just making sure when they show up in the inbox, it's relevant.

Yeah.

They know a human's written it.

Yeah.

Is this showing, is this coming up in your world? Like I'm finding it super interesting. I'm just super curious on like how you're, 'cause you are a business that's providing a solution and a product.

Yeah.

How do you think about, is that showing up in your world a bit?

Yeah, for sure. And I would say in adjacent markets to ours as well, like there was a really big, you probably may have seen this, like AI SDR boom where you would have, there was actually a handful of companies who grew incredibly quickly. Off the back of selling AI SDRs, i.e., don't hire SDRs yourself, just use our AI and it will email basically everyone that you might possibly be interested in meeting to sell your product. And the story, I've not been inside these companies, so I can't speak to it in detail, but the story that has been is that there was an initial real boom where everyone's like, this is amazing. And so everyone signed up to use this AI SDR. And then you realize you've completely scorched. Yeah, of course, because it sent out like millions and millions of emails. So you've had hundreds of meetings. And then by month 3, you've got nothing because you've just totally scorched the customer base or the TAM. And actually the conversion wasn't that high. So you've sort of like, you screwed it. So anyway, point is, yeah, we've seen that all the time. I think my main pushback, if I was going to be harsh, not pushback, the main way I would encourage people to interpret what you said, which is, hey, on the one hand, you've got this drive for efficiency. On the other side, you've got people who want to show up accurately in inbox is We have to have a more sophisticated understanding of efficiency. Efficiency is not how much effort do I have to put in to send 1,000 emails? Because you are not, your business does not rely on you sending 1,000 emails. Your business relies on you getting high quality candidates in front of customers. So what you, the way you want to think about your efficiency is what's my efficiency towards closing a rec or getting at least that first high quality candidate in front of a client. That's when you put, efficiency through that lens instead, I think you start realizing, well, sure, sending out 2,000 unpersonalized, unengaging, non-compelling emails, it might feel good in the moment, but actually when I wake up tomorrow and I've got no pipeline, is that efficiency? So it shows up in terms of, I mean, I'll be honest, we haven't made that mistake of building something that just enables you to, you know, almost feel a sugar rush of feeling like it's automated and therefore it's good. Yeah. It's like, I, and yeah, like Once you feel like you've automated something before you, if you don't actually know it's successful, that's not real efficiency. I think people need to learn that. That said, I still think the experimentation is good. So I wouldn't want to discourage people from like trying some of these things and seeing how it works. But I think over time, of course, you know, the winners, the winners determine how work gets done. And the winners will realize, well, actually, the efficiency needs to be towards a goal that actually matters. And the good news for anyone in recruiting and any other business function is the goals haven't changed. So the goals that you sort of understand really well, the ones I described, getting a great candidate in front of a client or obviously closing a rec, those have not changed at all. And so you still want to measure your efficiency by that. So we have a bunch of ways that we try and really marry up against, you know, the right definition of efficiency. So we don't do things like, you know, hey, we just send like 10,000 emails in the click of a button to all and sundry. But yeah, it shows up for sure. Actually, sorry, Hishem, can I add one thing? I forgot to get to it. So if I was going to, so that's like maybe an overall way to think about it. Talking specifically, if you're one of these people who really takes pride in the quality of outreach that you do, I still think there's a ton of space for you to think about how to use AI. So AI agents are really good at doing research, right? So you, even within ChatGPT, I mean, we have a recruiting specific way of doing this within MetaView, but even in ChatGPT, if you wanted to sort of ask the AI to do deep research on a certain segment, on a certain sector that you might not be familiar with, getting high-quality, like synthesized information out of AI so that your outreach can then be higher quality without you having to spend 2 hours, 4 hours, 6 hours, you know, understanding a sector. Maybe you're planning to go to the next industry event in order to sort of like, you know, steep yourself in that industry's culture. Maybe you get to do less of that stuff. You can still finesse and have world-class outreach, and you can do that in a personal way, but you can still leverage AI to give you a ton more efficiency up to that point.

And I'm glad that you went there because that sort of is what I wanted to ask you next, because I feel like this might be really helpful for people and almost something that may or may not show up in your sales team's conversations. But I was asking you around like what could be like a good and useful framework for people to use to understand where they can deploy AI? Because I think that, that's because what you just explained there, yeah, was you've obviously thought about your workflows. Where do I spend a lot of time? What could these things type to do? But I feel like you've got a hat, you've got to see that.

Yeah.

Whereas I think sometimes where people might find themselves in that position of like, I tried all these things and then I've just got back to where I was again.

Yeah.

Was it they didn't take that step back and go, actually, This is where I'm spending a lot of my time or where I do spend my time. Is that something that AI could do? And then you go through that process because I don't know if that, that may sometimes show up or it might be a smart way of educating your customer on that journey of like, they might just say like, we've got this problem and I need MetaView for this, but then your team educate them and go, actually, yeah, there's all these other things that we need to think about where this could go in. Does that make sense? I don't know what this, how you thought about this, but I think framework on like, where can we deploy AI?

Yeah.

How we think about that. Is probably helpful for people.

For sure. And I don't want to act like we've got it all figured out. I still think it's like a, it's still a, this is still like a bit of an expedition that we're on, frankly, as a species to figure out how we're going to use AI to get work done more effectively. And obviously, I think there's a number of answers that are good answers, but we're just barely scratching the surface of how we'll use it. So literally today, I had a conversation with a a TA lead at an in-house, like they have an in-house TA team. And we've been talking a lot about our sourcing agent and how really the best way to judge it is essentially around time to fill and time to getting that first high quality candidate into a hiring manager. And just like the raw amount of time that your full lifecycle recruiters are spending on sourcing, reducing while you're also still getting more source candidates in the pipeline. That's what we were really pushing on. But he really just wanted to know how many messages are being sent out. He wants that number to be higher. So I, so I, and this is a sophisticated, like on many dimensions, world-class company. Um, that's what he wants. And I, I, I, the, the, what I sort of realized through that conversation was his mental model is, um, uh, what I'm hearing from my team is the bottleneck for us not having more candidates in the pipeline is we don't have time to source people. Yeah. So right now I know they're sending out this many messages and I wanna buy your thing and then see that we are sending out this many messages and I haven't had to hire 10 more people to do it. That's like, that is, so there's, we shouldn't sort of be, I don't want to be too dismissive of his take. Like he's reacting to like a real business situation. It's just that of course, the sort of the old model assumed that the quality of outreach was always high, was always quite high quality because it's humans doing it. And therefore if you do more of it, it's better. Whereas if you sort of, if you completely obsess over just sending messages, then I can build you an AI that sends messages to everyone irrespective about whatever bullshit you want. And it's obviously not going to get you where you need to go.

Um, so you think that, that is like a good— so really, do you think, because it is so easy today, and, and I do think, being honest with you, I, I do generally believe starting with like, if someone is at zero and they, and they want to start implementing AI into their business, or like talking recruitment business here, yeah, their day-to-day, I, I do personally believe like a note-taker is, is a great place to start.

Yeah.

But then it's like, if we get bigger than that, like, what is a helpful way to think about agents, AI in my business? So what I'm hearing there through that conversation is like, that person is really seeing what the main bottleneck is and then actually having a conversation around, is MetaView a tool that can help me with that? Versus, I know we probably don't, I know AI is important and I'm speaking to MetaView today because I think we should have AI tools and it's important, but I haven't thought about what that constraint is.

Yeah. Yeah. So, so, uh, And the constraints aren't, they're not, there's like, uh, there's not that many of them, right? They're big constraints, but there's not that many of them. It's like finding, finding people, uh, getting the people on a call or getting them to respond to you, um, getting them pumped about the client you have in mind. And then obviously then just like working them through the process and actually, you know, hiring them that they're quite, these aren't new bottlenecks, they're existing things. So the way I would put, and we'll get like, let's get concrete on that in a second, but The, what you described, hey, note-taking is a really good place to start. I agree. One of the reasons it's a good place to start is because as we talked about previously, this is proprietary data. So you're going to, you are, you're going to need proprietary data. Again, if you're just a, if you're just using LinkedIn the same way everyone else is, and in the future, the same way an AI agent is, then you're not going to have, you're not going to have a differentiated role in the market. So it's really good to start to capture your proprietary data, which is usually in conversations. And then the second thing is, if you want to get the most out of AI, actually, funny enough, the AI having access to your proprietary data makes it better for you. So in a world where if you and your competitor are both just using ChatGPT to do your work, better than not using ChatGPT to help, of course, but you neither of you have any real sort of inherent advantage because the AI would give you the same answers essentially. As you work with an AI that has much more context on you, it knows all the candidates you've spoken to in the past, it knows all the clients you've spoken to in the past, it knows the candidates you've put through in the past that went to do well through the process and get hired. This is all context that means that AI is more tailored to your business, to your customer set, to your workflow. And so that's another reason why capturing the conversations is so key, because that's the context any AI agent you're going to use in future will need in order to do a great job. Anyway, to answer the question of like where specifically to look, the reason people buy an AI note-taker is because people literally recruiting firms quite rightly think of one of their products, one of the sort of the, one of the things a client uses to judge other than just, did you get me great candidates? Did I hire them? One of the things a client uses to judge almost the quality of the recruiting firm they're working with is the quality of these write-ups. Like when you're sending me through it, when you're submitting a candidate to me, A, how many am I getting through? And B, literally Do I feel like I'm getting a quality work product here? Like an output of something that's really useful for me to synthesize whether I want to speak to this candidate or not. MetaVU is really good at taking you from conversation to submission, submission-ready candidate. And like you can save yourself lots of time, but also have a much higher quality product. And if you're, even if you're at a recruiting firm with just a handful of recruiters, the fact that you can design that centrally. So if you're the founder of the firm, you can say, every time you make a submission to a client, I want it to look like this. And then you tell the AI that once and then every single submission you have from there on out, as soon as the conversation's over, you have it ready in that format. And that's just a massive time saver. Now, I think the other sort of big area that people are bottlenecked on often is frankly sourcing. The way that bottleneck manifests itself, some people go to database to source, but most of the time they don't. Most of the time they they go to their LinkedIn, their LinkedIn Recruiter license, and they, depending on their sophistication level, either apply a bunch of filters or put in sort of a relatively complex Boolean string and scroll through candidates until they start to, and, you know, click on each one and then see, have a look at them and think, will this person be a good, good person? They build up their project and sort of add more and more candidates to their project. And then they move on to, so that's bottleneck one. Next step, well, now I've got 50 candidates in my project, I'm going to think about reaching out to each of these. And then you'll get the sort of bifurcation of some folks that will go super personalized for every single one. Some folks will think, okay, cool, let's blast this 50 or this 100, however many with this message and see what we get back. So that's your second bottleneck. There's a lot of people who are in that second bucket of sending this non-personalized outreach, who would like to send it personalized. It's just the work involved makes it is prohibitive for them given what they believe is the right way to grow their business and please their clients. And so those are the two we're working on right now.

That makes sense.

Yeah, I mean, we've got, we've made, as in we have live products that help with it, not fully end-to-end, but yeah.

I guess what we're talking about here is like, if you're listening to this, and I think most people, like, if you're in the, definitely in the recruitment world, business context, like, you will have AI in your face all the time. And I think this is a useful way to think about what are those constraints, what do you spend a lot of time on. Actually, if once we understand what an agent is, oh, actually what you just said there, that is something that someone could do.

Yeah.

Um, because they're searching, they're going and clicking onto profile. If I see this, then do this. So yeah, I think that is a useful way to think about it in terms of like, have though, like actually have those thought experiments and work through it. But yeah, or you start getting on all these demos and being like just getting lost in that noise.

Yes. Yeah. Totally. Obviously what a lot of firms do as they get more mature, which means that the smaller firms are doing it, they're just having to ingest the cost themselves, is they will say, well, actually this like research aspect, this is like a separate job and we specialize. And the researchers, I might even offshore the research. I might even have them like in some other country because I don't think that's like the core thing that my firm does. I think that's just something we have to do because we have to do it. And so if you're a smaller firm, you're ingesting that cost in that you're probably as a founder of that firm or some of your key staff are doing that research job because they have to, because you don't have anyone else that can do it. And that's really where we, that's the bottleneck we're focused on removing is how can we make it so that actually that research job, which is not what separates, I would say, a great recruiter from a non-great recruiter, right? A great recruiter, I think, is more about getting to know the client, really digging deep to understand the rec. Understanding what they can do to bring their expectations in line with the market. They need to know the market well enough to be able to, like, it's a lot of those relationship things that are what separates a great recruiter from a not great recruiter. It's just in smaller firms, you also got to do the research. And so we think we can, we can change that equation. And the magic of an AI agent, certainly our agent, is when you go to LinkedIn right now, you have to sort of be very specific about the filters you're applying. So your workflow is, I'm going to talk to a client, they're going to tell me what they're looking for. They don't speak LinkedIn, they speak, they speak human, they speak English like me. And then I'm going to sort of take that, my understanding of what they said they're looking for, and almost try and translate that into what are the filters I should put on LinkedIn. But they're inherently clunky, really, right? Even no matter how sort of fine-grained you feel the filters are, the reality is when I know what I'm looking for, let's say an AE, I might think, well, I want someone, yeah, someone that has like this company on their resume. That's great. but not if they were at that company in the last 2 years. It's only if they're in that company in sort of, you know, between 2020 and 2022, that's when that was like a great vintage or, you know, and I have this whole sort of almost like almost muscle memory of, or this tribal knowledge I have about what good looks like. Really hard to translate that into specific filters on this LinkedIn UI. But actually, that's something that an AI agent can understand really easily because just like you can understand it when I just expressed it to you there, AI agents speak the same language. And so you can just chuck whatever documentation you have it you can speak to it in the same way I just spoke to you and it will go in, it will think for itself about how to apply the filters. You don't have to sort of like do that work for it.

And also the thing that there is a skill element there.

Yeah.

That like there will be people that have learned it the hard way on Boolean, like how to put together a Boolean string.

Yeah.

What to include, how not to do it. So like you're also removing a skill capability there.

Yeah.

Which is bad if the people do a really good job at listening and asking the right questions and gathering that.

Yeah.

and I could sit next to you, my manager, and say, so this is what they're looking for, these are their non-negotiables.

Yeah.

They would consider an 8 out of 10 person if they had this.

Yeah.

If you can then put that, that's why experience with your product, like that makes complete sense where you can just like talk to it in terms of like these, these are the things that we need.

Yeah.

Versus me having the capability to understand if I put this filter in, then it will mean that. And if I don't include that filter, then it'll mean that. There is a skill piece there as well.

Which is just emerging to me. Maybe one way that we should think about talking about it is stopping it being, yeah, you're right, that is a skill. And so in some ways you've got to feel for the people who've honed that skill because I think that's not going to be a useful skill anymore, basically. The sort of, uh, uh, but one way, one way to think about it is the art of recruiting or the science of recruiting, the craft of recruiting stops being about how can I make a computer return to me people that might fit this thing and instead becomes about what do I know about the market that gives me an unfair advantage of being able to satisfy this client most quickly. And then finding the candidates that satisfy that is easy. I just say it, or maybe even as soon as I think it, you know, I can get the candidates. But the point is, it's the sort of, it's the novel thought that actually, you know what, maybe someone who was at Datadog between this period and period would be great for you because they had this sales leader at that time who was like this. And that's actually very similar to the process you're trying to, like, if you have that level of insight, like, that is valuable. And right now you're almost disincentivized from having that level of insight about a market because the most important skill is how can I get someone like this piece of software to spit out some candidates for me? And that's hard in itself. But how much like more exciting is it in that first bucket I mentioned, right? That's really what we should be.

Because then you layer on top of that, like most, take your AE example, most great AEs are going to be in C. Yeah, typically.

Yeah.

So then it's not only understanding from you what you believe would be what's important, non-negotiables, things you consider, not consider, but then if I'm a good recruiter, I'm gonna go, okay, so, well, you know, most people I'm going to speak to are probably in a position. So like, what do you think is going to be a compelling reason as to like why they should consider—

yeah, yeah.

And then it's understanding the whole what the actual seller is. That, that's what a great recruiter is going to be able to do, is going to go to market and get that from you in terms of like why should someone consider MetaVue? Like, what is it that you're offering here? What's the future opportunity? Because most people are going to move for not for the 30-day pay increase, but for the, the 2-year journey that they get. What does that look like? And then you can use that. Yeah, if I understood that correctly, where, where my mind goes is like, okay, if I've done a good job on building my talent network, I should have had those conversations. Yeah, what does your future look like? What do you care about? What's really important to you? And then I go, okay, Yeah, go to my sourcing agent. This is what I think ambitions-wise people should— yeah, what would make it a good match? Like they want to be here, but they're not there yet.

Yeah.

If I could just put that in there and then it also helps me understand like from the conversations I've had.

Yeah.

Enough people like that.

I think that'd be pretty cool. Yeah. Cool.

You're not going to have to put that on the filter, are you?

Exactly. Exactly. But that brings together two things, right? One is the proprietary data you have, which is, well, of the, you know, even if you've spoken to thousands of customers, uh, candidates, sorry. Of course, that's still a very small subset of all of the candidates that might be a fit. So you want really enriched data about those people. You get that enriched data mainly through your conversations, but then there's still a way you can use AI to navigate and traverse this just huge database of profiles that exist out there on the internet. And that's also, AI is also very useful for that. Okay. Yeah. Maybe one thing to sort of stitch these two together when you get really sophisticated. I don't know, maybe we want to talk about what is like, what does recruiting look like in future? I think this is a cool example of like a very specific case. Uh, uh, let's do, let's continue with AE hiring. I hope that's like relevant for enough of your audience. Um, but, uh, obviously when you speak to AEs, you end up talking to them about their quota attainment and all these things. And you usually try and put that in context. Okay, sure. You were at, you know, 110%, but like, what was that relevant, like relative to everyone else? And, uh, you know, how was the company doing at that time and that sort of thing? But of course, in a world where you've got a small, even a small firm, and you've got many different of your team speaking to different candidates at different times, you can start to sense check what you're hearing back from a candidate, right? Like, okay, this candidate said that they were over quota in 2024. And that was amidst a whole team of people who were way under quota. And like, right now, if I hear that, I have to sort of just take that and maybe until I get to references, I'll just take that as true. Whereas actually, AI that's been part of conversations with other candidates from that same company, other parts of my business, might be able to tell me, hey, this is a little bit, that doesn't sound quite right. We've actually spoke to someone else who mentioned, who provably was here on their quota, you know? And so really starting to truly treat all of the conversations you're having with these candidates as not just proprietary data you can access, but proprietary data that is surfaced to you in order to help you submit the right candidates to your client is, I mean, that's what it should be. Yeah.

You, you mentioned it there, but that, that is where I wanted to go next in terms of, I think like, I feel like it's even a big part, like it's sort of how you've, what your mission is, right? In terms of like to help recruiters and talent leaders figure out how humans and AI can work together. Yeah. And I think the real like catchphrase, I feel like from the position that I'm in being a small business owner serving the recruitment industry, the Um, is AI is going to enable recruiters to do like great work and all this. I just want to talk about from someone in your position, your seat, like how you view just, just the next like 12 months really. Like when we think about 2026, I think it's still crazy to think that ChatGPT officially got released like November 2022 or something like that, right?

Yeah.

So for someone in your position, you have to surely be spending I don't know, you can tell me, like an amount of your time thinking about where things might end up because you're in a business, you're in an ecosystem where there's just so much money being pumped in.

Yeah.

There is an element of like, obviously you have to be really focused on building a world-class product. I think that's going to stand the test of time. That's probably going to be one of the best ways that you can future-proof your business. There's so much money coming. There's going to be so many players that enter. Be interested to see how many players are still here in another 5 years' time. Yeah. But I'm sure for someone in your position, you could get caught up in that race, or like, fuck, right, I know we said that this could be a good idea, let's just, let's just execute it, let's just start it. So what this is leading me to is like, you must be thinking about the world that you serve, which is talent, which is recruitment, like what that looks like. Because I think a lot of people, they can say this is what I think it's look like, but no one really knows. I think right now, I know obviously you serve a huge part of the talent acquisition ecosystem. I'm obviously on the other side of that. I like from my, from like the way that I view it at the moment from my conversations is like there's never been a time now where TA teams have had more tools at their disposal to like do more with less really. I think if they, if they. If they really think about their workflows, their constraints, they partner with the right tools, they get their tooling right, like a TA function could be doing what, I don't know, a team of X could do. So I think when you're a recruiter speaking to a TA team and you're trying to understand what their constraints are, what their issues are, I think recruiters now today are coming up against like TA teams just having more capability because no longer now is put more headcount into TA means we can get more candidates through the funnel, which means you can interview more. Like I do think that's been massively challenged. And then you've got actual tools that are basically, are basically targeted and built to take recruitment agency spend market share. Why deal with a recruitment agency who just cares about their fee? Yeah. Um, so it's like the Jack and Jill example, like, as a product to reference. It's like you've then got all these companies that are just trying to take the market share. It's like, why deal with a recruitment agency? Just use AI. You don't have to deal with all the stuff that comes with it. So all of me to say, like, it's a really— I feel like it's an interesting— yeah. There's a lot of few, like a lot of things at play. I think my lens on the TA piece, you're closer to it than me. I feel like that, that surely has already been hit, is being hit around do less with more. Like I think a recruitment agency's perspective, typically when they deal with certain companies that have TA, oftentimes where they get in is like the recs that are really hard or really niche. And that's hard for a team of one.

Yeah.

To do with everything else.

Yeah.

So I don't know what you're like, how you're thinking about the future, because you must be making bets on like a TA team is going to be operating like this with less people. So we need to make sure that MetaView is an absolute tool that's a non-negotiable in that tech stack. Yeah. I know you also said recruitment agencies, so like what their future looks like. Do you spend a lot of time thinking about this or no? Because you can't— there's only— we try.

We don't zoom— I think we zoom out in we don't zoom out that much. I think you do, because I, you mentioned us, our mission statement, figure out how humans and AI are going to work together to build teams. And that figuring out is very, like, it's very on the terrain. Figuring out is by building stuff, getting it in people's hands, talking to them, understanding what they did next after they used your thing. Like, that is how you figure stuff out, because we're building totally novel capabilities. So we spend most of the time in the workflow with customers to understand how to make them more efficient and more precise. Those are like the two things we focus on, efficiency and precision. So, but when we do zoom out, I'd almost say we zoom out even a little bit further than that. We just think about, well, what's the big macro shift that's occurring here? Well, software budgets have always, since the inception of software, they've always been increasing at this sort of like monotonic rate. People consistently spending more on software, not usually, at times it will be at the cost of labor spend. Like it might say, well, now we have this thing. Doesn't have to be an AI thing, but we have this thing, actually, we don't need humans to do that anymore. And so there might be sort of a point in time where a certain class of job ceases to exist, and then there's disruption, and then those people find something else to do in future, or however it shakes out. So that's going to continue to happen. And we think that AI is an accelerant on the total, like the amount of money that businesses spend on technology is going to increase, not decrease. Certainly in absolute terms. And I would say even in relative terms. So if they're spending, for ease of math, $100 on total in their business on a certain like year or whatever, and let's say 5 to 6% of that, $5 to $6 of that is software spend now, we think that's going to be $10 or $15 in the future. And, you know, we're going to have to work out how the rest of it is divided. Obviously, the reason they do this is because they think they're going to grow faster. They do it because they think it will help them grow faster. And so the belief will be you also create, in absolute terms, you still end up needing just as many or maybe even more people in your company in order to win because you're just achieving more as a company and you need those resources for want of a better word. So we sort of only really think about those two levels, totally macro versus the micro. The sort of literally what is going to happen to, we do speak to TA teams that are saying, we want to invest, you know, they might have a mandate top down saying, you cannot hire anyone until you explore AI solutions to this. They may literally have that type of a mandate. We come across that quite frequently. On the agency side of our business, which we have like a lot of, is very substantial as well. I think what we tend to find is they're on average more proficient at adopting AI than—

Proficient?

Yeah. Yeah. To like do the work. That they move faster than in-house talent teams. And so I think there's a lot of folks who are using it, seeing it as essentially an advantage for them in many cases, especially the smaller, more nimble firms. The larger firms are seeing AI as a way to finally live up to this idea of their database of candidates really meaning something because they can now traverse it and gain knowledge from it much more easily than they used to. Like you'll have You know, name your Shrek firm, of which we have a couple of customers, uh, who will be talking a lot to their clients about the value of their database, right? Because they've got decades and decades of conversations all in their proprietary database of candidates. They know things about these people that no one else does. Well, now they have AI to help them make the most of that. So for them, AI is also proving a competitive advantage to win more clients. Um, so yeah, I guess what I'm saying is we're not seeing it in such a like a zero-sum way. We're not seeing a lot of people saying, let's fire these people and fire this firm because we're going to do this instead. We're not seeing that a lot. I'm not saying it's never, I'm not saying never. And I'm not saying it's not going to happen in future, but we're not seeing it a lot. We're seeing mainly people thinking, this is an opportunity for us to do better than our direct competition in this talent war. And You know, both sides of the table seem to be gaining from it.

But what you do see a lot, which never would have been a thing, is before we sign off on extra budget for you to hire someone, you're going to have to show me that MetaView can't help you with that sort of part of the problems. Yeah.

Which is not, to be clear, I'm not saying every company is doing that.

No, no, but a fair amount.

You've said that quite often. Yeah.

Yeah, that is interesting.

Yeah. But I, but again, I wouldn't— my belief is not that I wouldn't interpret that as sort of like a sign of things to come. I would interpret that more as there's this moment in time where our workforce has some minority of people who are AI fluent and the majority of people who are not. And so what I see that as is more business leaders using as a forcing mechanism. I'm going to force you to get AI fluent. Before you can start to almost like solve the problem you're telling me you need to solve with people. I don't see it as a, I think the future is we don't need to hire people anymore because we can use AI. I think that would be a misinterpretation of that. I just think it's, we think there's this new sort of well of efficiency that we can dive into, which is using AI to get work done. So I want you to do that. And then when we've maximized, when we sort of like at a reasonable point in our AI adoption, then of course we can start to, you know, add more people to it and they'll be higher leverage and more impactful because we have better AI workflows in our company.

So tell me if you think about, again, this is like more of a macro thing, but with the business that you're building, like, do you also, like, how do you feel about this sort of statement around like AI is going to create more jobs or the counter to that, like there is going to be a real period of like mass unemployment when this rolls out into law? I don't know if that's something that you think about or—

Yeah, I think it's above everyone's pay grade in a way. It's like, whatever's going to happen is going to happen on that level. And it is happening. It's inevitable that you can't get the toothpaste back in the tube. And it's like, we all have a role to play in defining how we use AI. But there are some forces way beyond me for sure in that sort of way. The way I see it is, I think we should get over this whole, hey, don't worry, it's just going to augment you and make you better. Like you have to have like, I think people need to be quite serious. Yeah, this is like a technological ground shift. You don't want to be the, you know, the, I don't know, the farmer who thought it didn't, I don't want to adopt a tractor because I like to sort of walk the fields and sow the seeds myself. Like, but obviously there's still like, we still sort of produce a lot of food via farming, you know, it's just that we do it much more efficiently. And obviously there's less, far fewer of our population is spending time doing farming. So I guess What I'm saying is, I believe that, uh, this is getting very philosophical at this point. I believe humans are status-seeking animals. And, uh, a lot of the reason, a lot of the thing that, you know, even inspires us to start a business, do well in our company, it's a lot about, and like an inherent sense, uh, intrinsic sense of we want to achieve things. I think humans will always find a way to satisfy that and we'll use money as a way to sort of reward people for different of those elements. But some of the tasks might very significantly change and recruiting included in that. I would say, I think the bit that is going to really sort of become the, again, the difference between a good and a great recruiter is going to be this sort of like constantly moving understanding of relationships and market. And to do that, you need to speak to a lot of people. You need to be in your market and understand it. And that's what you can bring to the table. I think maybe a good inspiration is when you think about like sports teams, obviously like recruiting is one of them, is the most important thing that any sports team does. The recruiters or the scouts in a sports team, they don't sort of, they have like a really deep understanding of, well, this is the tactics my team is playing. This is the stuff that matters to them. Actually, there's this striker in the French division too, who is playing for this terrible team, but it's a very similar system and they're doing really well. So maybe there'd be like a, maybe there'd be a there there with them. You know, that's, again, I know it's, you can't, it's not, you can't perfectly analogize, but I think that's sort of the, a little bit of the craft, whereas the sort of the current thing of just finding profiles, pinging them, slinging emails their way, that will still happen. It's just AI will do a lot of that.

Yeah. The reason is why I said to you at the start, like, just really, like, we don't often, I don't often sit down with people like you, but ultimately you're building, you're building every single day, you're thinking about building a world-class product for the podcast and people I interview. So I'm just curious, for someone that, again, outside looking in, you're, you're running a business, you're part of a journey which so many recruitment companies love to be involved in, like VC, bat, all that. So like a lot of recruiters are speaking to people like you. So I just think it's really curious just to get your take on these types of things. I think people will be interested in it because I think for the most people that listen to this show, like, you just got— you can't avoid it now, like, in terms of like hearing people talking about it or have an opinion on how you're gonna use AI, these types of things.

Yeah.

Something that I just wanted to just, uh, on this, I dunno if it's also something that, uh, is part of this equation. You said there, uh, in terms of like what we think would make a good recruiter or a great one is that consistent shift of like market, people, relationship, speaking to people. How do we feel about AI in terms of like I think it could be used in the wrong way. It could be one of the quickest ways to like erode trust.

Yeah.

Because that is the other thing that I think is part of this equation. I know we said earlier in terms of like a lot of people trying to use AI to solve that problem with sales and then you get loads of these spammy messages and all that. But I think now, again, taking a step back, seeing a video on my timeline and actually a question in my head is like, is that real?

Yeah.

That didn't used to be a thing.

Yeah.

Then it's like, if I get a message from human to human on like LinkedIn, a lot of us use that. It is something I was like, oh, like, did Sarah actually say that, or was it like AI? So then I'm thinking like when I'm WhatsApping people, I feel like I'm actually speaking to a human. Yeah, I don't know, there's a lot there as well, like when it comes to trust. So I almost feel like as well, that is gonna— it's always been an important currency in recruitment. Yeah, but I think that's something that people are going to really be thinking about is like, how are you building trust?

Yeah.

Because I do think that is something that, yeah, I think that's something that's already, like AI is already eroding that, I feel like.

Yeah, for sure. And absolutely. And we get, there's like some really, one of the things that some of our customers sort of sometimes get concerned about is candidates that are on their virtual interview with them who are not real, you know, just.

Yeah, well, that's a really big, that's a huge thing in The US as well.

Yeah. And so there's like currently, literally the sort of the approach right now is very big. There are some sort of technical ways to try and predict whether this person has some, you know, based on their IP address and all these sorts of things, you can force them to do certain things like go to this website and that you can sort of, they're quite hacky ways. But one of the most popular is getting them to look around is like, you know, because these deepfakes aren't very well trained on like literally like looking to the left and like all these sorts of things. So it's very hacky. So, and that's obviously a game of cat and mouse. That's not, In 10 years' time, we're not going to be asking, how old is Aide? You know, that's just a cat and mouse game that's going to constantly shift. And I think at some point, some smart company will come up with a way of, or there'll become some standard about sort of establishing authenticity of a message from me to you. And that will probably become because, well, actually sometimes, Hishem, sometimes I do want to send my AI agent to go and speak to you. And so I want you to know that that's the case. I'm not trying to deceive you. It's just like an efficient way we both have of communicating. You might do the same. You might send yours. So I think those, I think, you know, AI proxies for us will be a thing. Like, I mean, I'd obviously start with the things I hate doing, right? Which isn't speaking to you. I wouldn't send an AI to do this, but I might send an AI, hey, can you phone my electricity company and tell them that I want to cancel my thing? Like, I really don't want to spend time doing that as long as I can have like a trusted AI counterpart go do that. So I do think that will become a part of how we work. I think the trust will get solved by some protocol or something like that. And maybe with some very manual things that recruiters will end up doing, like, well, I'm going to go and meet that person in person in order to make sure that I'm presenting them to my client. And maybe, who knows, you put in like a bunch of upfront cost in the recruiting pipeline in order to make sure you avoid this problem.

Have you had an experience like that, Matthew?

We have not actually, no. I think that I actually, I actually think it's a bit overstated, the problem. Really? Yeah, I think it's very good for like grabbing headlines.

But nobody does that.

But most, the vast majority of candidates that are, let's say, let's call them fake candidates, they're getting, they're not making it to interview stage. They are, you know, it's hard to create a LinkedIn profile that has years and years of history and likely thousands of connections. But you can start to see clues very easily before you actually get to interview stage with most folks. So I think it's massively overblown.

Yeah, fair. Yeah, it is interesting. And then just another thing, just like curious as well. So recently came back from the US. So a big, like something that's really shifted over the last 24 months, I would say it's always been a thing for sure, but more and more UK-based companies just serve the US market. So I know you've recently opened an office in San Fran, right?

Yeah.

So just overall, like, just curious here, and I think people will be curious. There's a lot of entrepreneurs that listen to this show, but yeah, that's been like a real trend. So everyone that I interviewed, for example, when I was in Austin recently, were British. So there's so many. So it's like there's like layers to it, but mainly like in terms of like competition.

Yeah.

While they're different compared to the UK in terms of population versus number of recruitment agencies, if you look at that stat alone, it's like pretty wild. Yeah. Much less competitive.

Yeah, basically.

And then you have like the average fee could literally be like 5x.

Yeah.

Especially if you target companies in San Fran, like what you pay in AE in London to, uh, compared to San Fran, it could literally be like 3x. So like you could be recruiting the same skill set and be getting, uh, 3 times more. So there's a lot of companies that just serve the US market from the UK, or there's a lot of people going to the US. So the reason I bring all this up is one of the things that I think I often find in like business owners, business owner conversations is like building a business, entrepreneurialism in the US versus the UK.

Yeah.

What's that experience been like so far for you? I'm just curious, like you've opened there.

Yeah.

I think people are interested in that. There'll be a lot of people listen to this that actually are trying to get over to the US.

Yeah.

What's been your experience of that in terms of it being championed or how quickly maybe you've met people? In San Fran that, I don't know, you tell me, like if you're building an AI company, being in London, spend time in San Fran, what's that been like?

Well, I've always been like a, I'm like a fan of that region, right? Silicon Valley. And like, it's what I, even before starting Metaview, that was like, honestly, it's a little bit sort of shallow to be honest, but like one of the reasons for even starting the company before, like you think about the mission. Was like, hey, I think this startup stuff looks really cool. That's why I just like that part of the world for that reason. In terms of what it's been like, not super surprising because I've spent a lot of time there over the last 10 years anyway. The biggest difference, honestly, is I think there's something cultural about, I think they're definitely more predisposed to believing something exceptional can happen. Like you can be part of something exceptional, uh, and like maybe in a funny way, being a little bit more trusting on that regard. But at the same time, I think a lot less loyal, funnily enough as well. I haven't, we haven't seen that yet, but I just know that sort of like part, you know, people jump around a lot more essentially in their work. And then the other big thing obviously is notice periods. Like that just changes recruiting so much, both as a business owner, but also obviously as someone who's doing recruiting, like when you can actually close a rec and it's like a joyous moment where that person is essentially joining that company 2 weeks later. Almost irrespective of how senior they are versus what we have here, which is, you know, this really sort of tense 3 months where you're like, well, who knows, are they actually going to like show up or do I need to get back in touch with the agency and say, well, you're back on it. So I think that, but that just, that compounds, you know, that ability to hire people quickly really compounds because sometimes when you think about growing your company, you might want to make this hire in order to then think about, well, what are my next set? You know, and it's only once they're in the team that you think about, well, how can we start to bring people into their team? Or, you know, what are the sort of complementary skill sets I now need given that they've been in my company and I understand them better? Whereas when you sort of like have this constant delay, this constant, which obviously I know it serves both sides, obviously it's good to have protection on the other side. You can obviously, you can also fire people much more easily in the US, like, which as a business owner, I look at as like a, I think that's a good thing for vibrancy of an economy, but I can understand people thinking that's a bad thing. So it goes both ways. But I think that's like the biggest difference. And it sort of, I think that also affects the culture a bit, right? Because it's a little bit, it's just more pro-business.

Yeah, it is interesting. And have you found that also in terms of like, just overall you being, because I think a lot of people that I meet, one of the things that always stands out is, and I'm always going to be someone that like champions the opposite of like what typical British culture is, which is seeing you raise the money and go, fucking fuck them.

Is that what people do?

Well, I feel like it. So people that go there would— people that I meet would typically say they champion success a lot more. Yeah, they would encourage— they would, you know, be like, 'Go on, so you're gonna like— I met you, that's amazing what you're doing.' Whereas us Brits like to be cynical with analyzing here. But I was just curious, as a business owner then having that experience going over there, I was just curious because I think that is something that also a lot of people experience.

Yeah. I think, I think the, it's hard to say. I think to be honest, raising $35 million is very alien to everyone I grew up with, for example. Right. So it's not, it's not like, it's almost so far out of the norm for most people in, because it's because tech is not like the center of our economy and it's, it's quite, I think it's hard for people to judge it. I think some people might even think, is Sahil still dicking around with that little company? Like, I'd like to think it's just, oh, there's a weird game happening over there or something. I can imagine they might be, you know, so I haven't really felt that sort of cynicism around it. Whereas in the US, obviously, it's much more well understood and people sort of know that it's still, hey, you're still in with a chance of becoming a significant impactful company, but there's nothing set in stone. Yeah, but I would agree with what you say overall, but I haven't felt the, I would say I've felt the energy associated with trying to build something great in the US. I haven't, I haven't felt a ton of cynicism here.

I just haven't felt it.

Yeah.

I just think, yeah, we're, we're sometimes reluctant to sort of encourage success and yeah. Something, this just popped into my head. I think it'd be interesting for people to hear, just really curious because you mentioned around getting to that outcome of raising money.

Yeah.

The amount of recruitment companies, recruiters that I speak to, interview that say I work with venture-backed startup scale-ups to grow their GTM teams, or insert whatever. Yeah, just really curious what, like, if I, if I saw— I might be too late at this point, but like, if I was to try and get your attention as a recruiter. Yeah. And you, you fit that bill of like, they just raised money. Yeah, signal, clear signal there that they're going on some sort of growth journey or going to be investing in a product. Like, what would make you give someone's attention? Would it be— it might be way before this where you get the money and they go, so one of the biggest reasons why you won't get to where you want to is having the best people possible in seat. Here's our recommendations. We've got trusted recruiters in our portfolio. Here's the intro.

Yeah.

Did you get inundated with like, what would make you give someone's attention? Like, what would—

I think the, the, maybe the harsh reality is, um, it basically like social proof or references matter a lot. Like when you're in my situation where it's like first time I've ever had this much money in a bank account, like obviously, uh, I want to, there are some areas where I really want to innovate with MetaView, mainly on the product, obviously. And there are some areas where I just want to make sure that we're not, not messing up, you know? Uh, and I think you need to, you need to first of all get to the point where you're not messing up. So my, so my first thought when I, when you raise a good amount of cash as well. Okay, cool. Well, what are other companies at our stage? Name companies I recognize who I know have been successful post this stage. Who do they work with? Because I know that they can do this, you know? So I think there's like a massive bias towards those type of names essentially. Now obviously I've worked with a bunch of those and then you realize they don't work out and you realize it's much more important is the actual human who you're working with and do they get you and are they grinding for you? Are they putting you at the top of their priority list of their client? Like all of that stuff matters. But initially I do think there's a, I need to like try out what it's like to work with the sort of the almost like down the fairway company that I should be working with, if you know what I mean.

And is that fairly typical that from my interviews when I speak to people, is it, it might not be that direct conversation, but they'd be like, so you're now part, like you get access to all these resources, people, network, and here are, because that is, correct me if I'm wrong here, but like you said, as a team, as a sports team, number one problem most likely will be something centered around people, won't it?

Yeah, but I, yeah, so number one, So the company outreach you gave me, I'm gonna be harsh here. Every founder knows that. When they go and raise money, it says on the deck, it says, we're gonna go from 30 people to 150 people. So they know that the most important thing is hiring. You don't have to tell them that. Like, that's a waste of characters in your email. Like, obviously I know that. It's like 110% of my job is that.

So with those, but I guess the reason why I bring that up was, would the venture, would Would these people that are giving the money and investing, because they know that obviously, they would then go use these tried and tested— Does it happen?

Yeah, not, not, uh, the different firms have different levels of almost like, uh, strength of recommendation. We've worked with ones where it's like, hey, we actually like almost have a special deal with this firm, so you should definitely work with them. You have others that's like, these are like 3 or 4 that we recommend. Let me introduce you to the founders who worked with them recently, because we're a little bit hands off. We don't know, we just, we recommend them, but. And their reputation comes back to us, but really would benefit to speak to the founders and see how they got on with them. So that happens for all like that. So that is when I think about the agencies we've worked with, they haven't always, I say about half of them came through and we've worked with probably not a ton, like 5 or 6 agencies over the last few years. About half of them will have come through something directly through an investor saying, You should speak to these people.

Yeah. And then obviously it's down to them, but yeah, I was just curious for, but yeah, like the point there that is interesting that you make is like, if I could then show up in your world, wherever that may be, and I can say, like saw this, we worked at X company that went on a similar journey.

Yeah.

Like if we can show track record of helping a company that have gone from raising X. Yeah.

Yeah. And I would say I also increasingly, as you move along the sort of the venture journey, I think your network of founders gets larger. So even literally people like on WhatsApp. So I think there's like a, it's probably less, it gets less and less, hey, did this great company use you? And more like, if you know there's someone in my network who you've worked with and they might not be willing, they might not be so tight with you that they'd do the recommendation. But if I text them saying, hey, by the way, how's work with Hishem Azzouz? And they say, yeah, really good. That's going to mean a lot to me. Like just from a de-risking.

Fuck those love because the channel reference.

The risk, I think the risk I'm trying to guard against most as a founder is like a false start. It's like we do this, I want to invest time in getting, in steeping this person in our context so they have a good chance of finding great people for us. Like I'm sophisticated enough about recruiting to know that I should invest time in each partner so that they can be successful. So it does actually create a bit of a barrier to working with someone new because I don't want to do it willy-nilly. And so like even just knowing that, hey, this person's solid, like, and it's from someone who I trust, makes all the difference.

Yeah, for sure. Love it. So really then, like, what, like I was just going to ask you, like, what you're really spending most of your time thinking about moving forward. Is it really back to those, those points earlier that you said, just really thinking about, did you say efficiency? What was the other thing?

Precision.

Precision and efficiency. Like, is that just really what you're spending a lot of your time focused on?

Yeah.

Listen to like what people are getting value from from the product, how we need to maybe evolve it.

Yes, I think there's evolution, but I think we do— we're currently, uh, we have one tranche of work which is quite evolutionary. Like, I think the core platform for your recruiting conversations is, you know, that is a thing. Fast forward 10, 20 years, people are still going to have— like, it started now, people are going to have it in future, and we've got the best product on the market, and we need to make sure that stays true for decades to come. That's going to be a thing. But then there's also like all of these net new, there's also a ton of new things we could be doing. And so we sort of have two, almost essentially two sub-teams, or I don't want to say two sub-companies because they work very closely together, but two sub-teams, one that's focused on let's absolutely make sure we continue to have the best conversational platform for recruiting conversations. And then also let's think about what are the new agents and applications you can build that are almost unfairly good because they also have the reputational context. So we do both. So it's a mix of evolution and like more revolutionary or like net new things.

That makes sense. Yeah. Love it. Genuinely always enjoy our conversations. Yeah, me too. Like, yeah, like I said, like really cool to get to sit down with someone that really is in the trenches of building an AI company. And I think it's like really interesting to hear like how you're thinking about things. So I think there'll be loads of elements there that be really helpful for people that might be overwhelmed with all of this talk around AI technology. How should I implement it? I don't want to get left behind, but I think there's some really useful aspects there. And then also some, some good nuggets for recruiters as well who love to work with venture-backed companies. Uh, so appreciate you coming on.

Appreciate it, man. Appreciate your time.