Episode Transcript
[00:00:04] Speaker A: I can't actually think of any process we support companies with that are not AI enabled. Doesn't mean we replace anything we do with AI, but it augments it so that the team can really create those human connections that help us understand the company so much better.
Hi, this is Josh Burson.
Welcome to the what Works podcast where Josh Burson company analysts talk with innovative HR and business leaders about what's really working in talent, technology and the future of work.
[00:00:33] Speaker B: I'm Kathy Anders, SVP of Research and Global Industry Analyst at the Josh Burson Company. I'm excited to sit down with Matt Hoffman, the head of talent and a partner at venture capital firm M13 about using AI to support early stage founders to build a talent first approach. Matt, I'm thrilled to have you. Thanks for joining.
[00:00:53] Speaker A: Thank you. I'm super excited to be here.
[00:00:55] Speaker B: So let's jump right in. Tell us a little bit about yourself and about your company.
[00:00:59] Speaker A: Sure. I am a partner of Talented M13, a venture firm that focuses on seed and series A businesses. We like to say that we invest in visionary founders building disruptive software businesses. A lot of VCs will say that. We think what's unique about us is that we really take a full stack approach to working with the companies we invest in, which means we don't just give them operating capital, we give them operating advice and expertise.
So we all work very closely with the founders, especially at the early stages, to help build up their business when they really need that experience. So in my role as head of talent, I will work with portfolio companies, really build up their entire HR and talent infrastructure. So that doesn't just mean recruiting, although of course it does. It means really thinking about the strategy, the infrastructure behind how they hire, how they reward, how they compensate, how they develop, how they grow their people, everything across the board to build healthy, sustainable, high growth organizations. Me and my team will help founders do, and that's how M13 operates. But what's great about it is in a lot of ways, very different businesses. They're all dealing with some version of the same challenges around scaling and managing and leading and developing and hiring their people. They're all working through that and so we can see the patterns at a platform level and help them across the board and do things in a way that no individual company can do. So for people like me who love working with a lot of different founders and building really repeatable, scalable, institutionalized processes, on the talent side, this is like a dream role.
[00:02:28] Speaker B: Many of these companies, I'm sure they're technology companies. Right. So they all have an advantage in terms of understanding AI and new technologies.
[00:02:36] Speaker A: Very rare for a company at this point in time to get significant venture capital funding if they didn't at least have some AI component to what they're doing. So they're often at the forefront of AI in terms of building and how they're using it. That doesn't mean that they wouldn't benefit from real repeatable best practice. On the talent side, you've just got to take that old school knowledge and that old school approach and then apply it to the current cutting edge technology that AI supports in the processes.
[00:03:03] Speaker B: Yeah, which is fantastic because their business is usually AI driven and now you're infusing AI into your advice and practices also. So how are you using AI to support all of these things that you're doing for your portfolio companies?
[00:03:19] Speaker A: There's a number of ways you can't be an effective people or talent leader unless you're effectively leveraging AI. Probably the most obvious one. And this is also just because this is a core part of what we do on the venture capital side is on the talent acquisition and hiring. AI is an enormously helpful and be almost impossibly successful without it. It's completely indispensable in terms of hiring and just looking at the volume of candidates and talent across, across the portfolio. Those are things that AI is really good at. So how do you target people with very specific skills? How do you target people with very specific experiences? How do you look at the broadest, most diverse pool of talent possible and use AI to really help you find the best of the best and the most appropriate people to surface? Hopefully get connected to your venture firm's community so you can connect to portfolio committees. It's a perfect use case for AI. Right. So we use a tool called Findem. We can do very specific things, for example, that you couldn't even imagine a few years ago. Everyone always wants to hire someone from Google because they've got pedigree, they've got the experience. But a lot of early stage companies don't want someone who's successful at the 500 1000, 10,000 size organization. They want someone who's seen the growth. Right. So a lot of conversations that me and my team will have with founders is I want someone who's working at Company X, where Company X is your competitor, but maybe five years ahead the success that you want to have. And so it's very Easy even pre AI to just look at their team, go on LinkedIn or whatever. Tool you want and say here's your executive team or here's our second level and pull those people. What we can do with AI and tools like find them and other tools is that we can actually say you don't want the person who's doing it now, you want the person who did it at your size and stage and help you grow to that point. So an AI query we can do is help me find someone who worked at this company when it was at this size in this role, what are they doing now? And so you can really get that specific. And AI is great for that, can serve tons of people. So you're not just forced to rely on your immediate network. You can really service that very specific example that's relevant to where your company is now and where you want to be and find people who have exactly that one. So that's a really great use case for AI. The other thing that we like to do is we're never just helping companies hire for one role or one company. We're helping to fill multiple roles from multiple companies. So we really take a platform approach. And so we want to expand and create as much of a talent community as possible. We want to be connected to as many people as possible even if they're not looking for a role now, because most likely they will be looking for a role down the line or there's multiple companies we can place them in. And so we can use AI tooling to do automated interviewing or to do video recordings of those interviews, take the transcripts, analyze them. We use brighthire for something like that and be able to really look over those transit over time so that we've connected to someone six months ago. We don't necessarily have a match for that person till six months later. And we can look at the data we've collected, just people that are a good fit way before the role even opens up. And so tools like that AI is just enormously helpful in doing that type of platform scale recruiting. And it's a very different approach in just rolefill than you might on an individual company. That's incredibly helpful on the recruiting side and you can apply it across the board. We use AI in the coaching now. We support portfolio companies with a company called Mento. We use it to build our compensation banding and our benchmarking. I can't actually think of any process we support companies with that are not AI enabled. It doesn't mean we replace anything we do with AI, but it augments it so that the team can really create those human Connections that help us understand the company so much better.
[00:07:09] Speaker B: I loved what you said here because these examples really show that this is not just doing things faster. Right. Because a lot of times we hear, oh yeah, we're using AI just to do things faster, but you're doing things that you could never do before.
[00:07:22] Speaker A: I think it's exactly right. We probably do things a little bit faster. The value is we can actually do things at a much deeper and impactful level, or couldn't do at all.
So you see the productivity and the efficiency gains, but it's not just about speed. I don't believe in hiring or any of that stuff at speed. I believe that you're better off taking the time to do it thoughtfully and do it right. We definitely use technology and AI to do that better, not necessarily faster. Whether it means creating much better job descriptions, much better benchmarking when you're designing the role and you can figure out the right compensation and the right profile, the right level of the person and obviously the hiring process, AI makes all those better. I wouldn't say it makes it faster, but I don't think it should be faster. I think it should be better.
[00:08:05] Speaker B: Totally agree. I'm always a little bit struggling with the notion, for example, that you measure recruiting effectiveness with just time to build because you might do faster and then you hire the wrong person. It takes you longer, it costs you more.
[00:08:17] Speaker A: You measure recruiting success over six to nine to 12 months. That's how you measure recruiting success. If you just stop at one person's in the seat, you are not measuring anything but speed and it actually creates the wrong incentives because you will hire fast, but you won't hire good. So that's exactly the type of example we think. AI or technology in general are really just great processes can make better hires which will save time and money and productivity in the long run, but not necessarily get someone in the seat any faster.
[00:08:46] Speaker B: Totally. And I think especially in your portfolio companies, every hire counts so much, right?
[00:08:52] Speaker A: Totally. So imagine you're a 10 person company.
Every time you make a hire, you've increased headcount by 10%.
[00:08:58] Speaker B: Right.
[00:08:59] Speaker A: Which is a big deal. So yeah, it definitely can make it quicker and more efficient to do things at the top of the funnel. I'm not going to pretend that's not true. But hopefully you take those efficiency to really get to know the best candidates and understand who you're hiring and use those time savings to make better hiring. And if they stay with you longer term and are higher performers and higher productivity, that certainly Pays for itself in the long run. Sure.
[00:09:21] Speaker B: Your example before too was so insightful because you're really looking for a very specific experience, very specialized or very deep criterion. I mean, if you're looking for a person that has been at a similar company, but earlier on in that stage of that company, in that industry, that's
[00:09:38] Speaker A: a conversation we have, right? And I think a lot of it is educating founders on what they think they want versus what's actually going to benefit them. And so much of startup hiring is not just finding the best talent.
It's actually, I'm not saying it's easy, but it's relatively easy to discriminate or find the best talent using technology and tooling in lots of ways. The trick is to find the right talent for your role, your company, your mission, your values, where you are at the stage.
Most people don't fail because they're bad at their job. Most people fail in startups because they're not the right fit for where the company is. And that's just as much on the hiring team as it is on the candidate.
So we use tooling and working with founders just as much to help identify what good looks like, focusing on the success outcomes than just finding the best talent. Because someone can be an awesome fit and awesome talent for one company and be completely wrong for another company or another role. That doesn't mean that they're bad talent. That means they weren't the right fit. So we really try to distinguish between the two when we work with these early companies, we, we like to as much teach them about what great hiring looks like as just fun of them great people. And so much of that is focusing on those success outcomes that you talked about. Just as much as getting great talent. Of course you want to keep the bar high, of course you want to get amazing talent in. But understanding what makes someone amazing for who you are and where you are, that's as much as a recruiting process. Anything else, and that is actually something that we think we're quite good at that might distinguish us from other untrained venture firms for sure. That'll just give you a list of candidates, say, here's great people, go talk to them.
[00:11:10] Speaker B: How do you distinguish that? How do you find out if somebody's going to be a great fit for the company?
[00:11:16] Speaker A: Look, the truth is I'm not as good a judge of who's a great fit for this company as a founder. The hiring managers, what we try to do is work hand in hand with the hiring manager or with the founder to Help them figure out what great for their company looks like. Because again, you can be a really good fit for one company, same job, and not a good fit for the other. And that's entirely based on helping the founder understand style. How do they manage, what is their blind spots, what are they good at? What does a culture look like? What type of people will be successful? What type of behaviors do you want to reward? What type of areas do you not want to encourage? Having those conversations directly with founders and helping them to think about that is what enables that again, we can totally and have sent them lists of just people we know and trust, people we've connected through our talent committee. Be like, these 10 people are really good at their jobs. They've got a great track record of success.
Will they be successful in this job for you? Well, that's a conversation we're going to have, right? So we can use AI to funnel more great candidates forward. And that gives us more time to have that conversation, which is so, so critical. And one of the best ways to make sure that they're focusing on success in a role is when we're doing hiring our head of recruiting, we'll usually sit down with them and say, what is the outcome you're trying to achieve? How do you know what does great look like? How do you know when they'll be successful? Six, nine months from now? And then let's work backwards from there and create the right job description, create the right skill and competency profile. We can do all of those things. And of course AI can help enable that much more efficiently. That conversation cannot be replicated. That is a critical part of it. And so there are things that we like to do at a platform scale like meeting talent and thinking about how we can expand this community and moving people to potential multiple roles in multiple companies. But it's really important that each company is unique, especially at the earliest stage. And being able to identify that is so critical.
[00:13:05] Speaker B: And I think what you're also doing is maybe teaching the founders how to think about.
[00:13:09] Speaker A: Exactly. We've got an awesome talent acquisition team.
There's four of us in total supporting close to 100 portfolio companies.
And we cannot be the full time recruiters for all of those companies. The most important things that we think we can do are one. Exactly what you said. Teaching the founders and the leaders how to run effective hiring processes, how to interview properly, how to identify great candidates, how to make sure you know what success looks like and build that talent first culture from the ground up. At the early stage, we Work with them. So that's, we think is actually the most important thing we can do. And then the other area where we think we can be successful is we can look platform wide, build out that community, find great talent, not just for one role, potentially number of roles at different times across our portfolio. That gives us access to much broader talent. We can share and connect those people to the founders. We can provide insight, but we certainly can't interview and hire for every role across our portfolio. So we really focus on where we can have the biggest impact directly with the founder and then across the platform, going very deep at a very specific point in time at the beginning, and then going broad to create as big a talent portfolio as possible.
[00:14:18] Speaker B: So how do these founders, once you help them think about this talent first approach, how open are they to using AI for these practices?
[00:14:27] Speaker A: One of the cool things or most impressive things about the technology extension and using AI is that it's actually much harder for early stage companies to differentiate themselves just on the quality of the technology alone, because it's much easier to build that technology now. So really what's going to distinguish the winners from every other company at the early stage is their ability to execute on a great idea and great talents. Right. And a great product. So executing on that means amazing founders and amazing employees. So you've got to take this talent first mindset because the business ideas themselves are less differentiable. It's all about the quality of the founders. There's certainly something we believe very deeply at M13, but it's also about the quality of the employees. And you've got to take that talent first mindset. I think most founders are very open to using AI. Really what we help them do is balance what can be done most effectively by AI versus where you really need to take the time to dig in as the people and that's building a relationship with a candidate, taking the time to really understand what success looks like and really digging in an interview and assessment process. AI can absolutely enable that, make it more efficient, make it more productive. It can look for biases in places there weren't before.
It's not, at least for a while, I would think in a fully replaced where the humans sit in, our job is to help teach them how to balance those two things.
[00:15:44] Speaker B: And I think that's what corporate HR teams and recruiters in, maybe corporations always thinking about that too. I think that's something that's very relatable to them as well. Where can AI fit and where do humans fit?
[00:15:58] Speaker A: The value for that proposition is not in replacing as many talent professionals. It's about amplifying their ability. Right? Making them superhuman at what they do. Really giving the bandwidth and ability to do things both deeper and broader than they couldn't before and do the most value added stuff. To me at this point in time, that's where AI adds the most value. It's not in a replacement necessarily, cost efficiency per se. It's about taking the people you have and enabling to be so much more productive with that AI copilot next to them.
[00:16:30] Speaker B: I think that's a mindset that we are talking about too. And we're talking about super workers, for example, and super recruiters or super HR people.
[00:16:37] Speaker A: I think that's only going to exponentially get better. But it's a different mindset than replacing. It's augmenting and making to your word, superhuman, which I think is a fantastic analogy. That's what it's doing. The ability to scale and grow and dig in and find that talent and develop that talent. It's really quite remarkable.
[00:16:56] Speaker B: Any lessons learned that you have some surprises as you are using AI in talent practices and in recruiting and in hr.
[00:17:04] Speaker A: I think there's always the unintended consequences. Certainly the ease in which we as recruiters can evaluate and find candidates is equaled by the ability of candidates to get their information out to recruiters. I don't think I'm saying anything new, but there's just been a surge in that the number of people that will apply for any one role anymore. And part of that has to do with kind of market conditions. But I think a big part of it is just much easier to find and apply and use tooling to make your resume better. To find these jobs cover letters. And so in some ways it's great because you expand the talent pool. It enables you hire a broader, more diverse group of people. It helps you find people you might not have been able to before. Those are all great. It also means it's a lot more work for recruiters and talent evaluators to sift through, through all those applications in the noise and find the best people. Typically what happens then is that the jobs just stay open for less time, which is problematic because you're just closing a window in which people can find a connect and it just might take you longer to find that perfect person.
So I think that's something to balance out. How do you use AI to be more efficient? But how do you not let it overwhelm you in a way where you're just missing out on Opportunities to find really great candidates. It doesn't obviate the need for sourcing. It doesn't obviate the need to build strong referral and community networks. We do all those things, we support, we encourage our portfolio companies to do those things for sure. Again, you have to use it in a way where it augments to work, not replaces it. Otherwise you're just having AI agents back and forth between candidates and employers without anyone really understanding what you're looking for. And you're totally going to miss a forest through the trees with that type of approach.
[00:18:34] Speaker B: That's so true. Any specific advice that you would give to HR leaders, talent acquisition leaders, Anybody in the HR area that is thinking about using AI much more broadly, what would you say?
[00:18:47] Speaker A: A lot of times with any technology adoption, I find that it's very easy to say, oh, look at all the cool things this technology can do now. Let's find a use case for it. And then you build and adapt your processes to where the technology is. And I always find that to be very short sighted and it never quite gets you where you want to be. I really encourage HR leaders, I encourage founders, anyone I work with. To start with, what do you want to get better at? What is the outcome you'd like to see? And then from that, find the way that technology can augment that. Right? So you're not compromising on your visions for success, you're not compromising on the outcome. You're saying, this is what I need to achieve to move the business forward, to move our portfolio forward, whatever that is, more talent, strategy forward. And then how can technology enable that versus oh, look at that cool shiny object. I'm going to do that. We're going to start changing, right? You're doing the same thing, but the order really matters and the intention behind it really matters. And I think that's the best way to do it. There's so much incredible AI technology out there, it's very easy to get distracted. But if you focus on what success looks like, focus on development around that, there will be enough tools to help you do that. Keep in mind where you want to end up and work backwards from there.
[00:19:57] Speaker B: Oh, I love that. We call this falling in love with the problem, not with the solution.
[00:20:01] Speaker A: Yeah, I love that.
[00:20:02] Speaker B: I know we're almost out of time, but in the last few minutes, where are you taking this next? What's your next step on the AI area?
[00:20:10] Speaker A: I think what happens, and certainly AI will support this is many VC firms and very talent teams really focus on the Talent acquisition side of the stack. And of course we do, because at the end of the day, our companies need to grow and need to grow with great people. So we're always going to prioritize recruiting and talent acquisition support. But that stuff doesn't happen in a vacuum. If you're not thinking about the entire talent stack, the entire HR organization, and you're just focused on recruiting, you're either going to have an issue where you're bringing people in at the top of the funnel and they're coming out, or you're not thinking long term about how they're going to grow and develop and stay in the organization. You're not thinking about how to compensate and reward them properly, how to incentivize them, how to help them grow and support their development. All that stuff ties together. It's not enough to get great people in. You need to get great people in, have them stay, have them grow and develop with the company. That's one thing that we really focus on when we work with our founders saying, how do you think about things in the entire HR or talent life cycle? And AI can actually support all of those things. And in fact, the way that this works best is when it all ties together. And sometimes that can be a big complicated thing to get your mind around. That's an area I can help. If you know why people keep leaving your organization, right. You can actually hire to make sure that you're not bringing in those type of people.
AI can help you see those patterns in a way that can before, whether it's analyzing your engagement surveys or analyzing your exit surveys. If there's a continued repeating pattern where people of these type of backgrounds do not last in the company, AI can identify those patterns and you can tie it to your recruiting process. If you constantly hear that people are not leaving because they don't see this same type of growth, they don't feel that the managers invest in their development. They don't feel like they're compensated fairly. They don't understand the value of the total rewards. AI can surface those data. It can also help you find ways of better communicating that and making sure that managers are better at that stuff. Right? So there's tons of AI tooling that helps managers have better one on ones. There's tons of AI tooling that help them set better goals, give better feedback, deliver more in the moment, real time stuff. Coach better. We use coaching a lot. All of those things across the life cycle will help you keep, retain and grow your people better. And if you're not doing that. Don't waste your time recruiting because they're just going to leave anyway. So there's lots of areas that AI can help and my recommendation to companies think about this is don't just focus on using AI for the tooling, focus on using AI to really understand everything that employers are doing across their life cycle that will make each individual thing better and undeniably lead to better outcomes.
[00:22:44] Speaker B: Yeah, we see that HR and all talent practices are really a system of things and I think that's what you're talking about here too. Fantastic. Matt, thank you so much for your time and for all your insights. It was a pleasure talking with you. I learned a lot, so thank you. Me too.
[00:22:59] Speaker A: Thank you for having me on.
[00:23:01] Speaker B: And that's a wrap for our conversation with Matt Hoffman, Head of Talent and partner at M13. Matt explains how he's using AI in helping early stage startups scale their talent practices right, building what he calls a people first approach from the outset rather than just tapping the same People who went to the right schools have made the right connections all the time. AI has allowed him to build talent communities tailored to the executive needs of that startup, which in turn makes all the difference to the success of the company. Corporate HR&TA leaders can use the same approach to broaden their talent access and find much better candidates. Thanks for listening to our what Works podcast. Until next time, keep pushing the boundaries of the future of work.
