Logan Yonavjak on Making Smarter People Decisions, Assessing Leader Readiness With AI, and Why Coachability Beats Pedigree Every Time
In Brief: Logan Yonavjak (founderready.io), Co-Founder and CEO of Founder Readiness Institute, joins host Dan Freehling (contempusleadership.com) to discuss how AI-powered assessment is giving investors, enterprises, and leaders a new window into leadership capacity. Logan explains the concept of vertical development and why it is the theoretical underpinning of Founder Readiness Institute’s work (00:08:35), addresses concerns about AI bias and shares how it can counter traditional human biases, and discusses what she learned from taking her own assessment (00:29:17). Logan makes the case for coachability as the most essential leadership construct (00:27:08) and explains why human leaders in an AI-augmented world will need to hold increasingly more complexity (00:32:42).
Recommended Reading: "$100M Leads" by Alex Hormozi.
Transcript
Dan Freehling (00:00:05): Hey everyone, Dan here. Welcome to another episode of Forward Looking Leadership. Today, I'm honored to be joined by Logan Yanavyak, who is co-founder and CEO of Founder Readiness Institute. Logan, thanks so much for joining us on Forward Looking Leadership.
Logan Yonavjak (00:00:20): It's great to be here, Dan. Thank you so much for having me.
Dan Freehling (00:00:23): Thanks for taking the time. I'm excited to dig right into it. So the leadership development space is pretty crowded already, and the leadership assessment space seems to be no exception to that. And there's all of these different assessments out there that everyone knows the names of. What is it that really drew you and your co-founder to the leadership assessment space?
Logan Yonavjak (00:00:42): Yeah, no, it's a great question. And we like to think of ourselves as more in the leadership development than assessment space. And I think those words are important or the definitions are important. We started out as more of an assessment company and have realized that our technology actually has so many different use cases and applications. So I'm excited to dig into that a little bit more. But in terms of my particular story and how I found my co-founder, Benjamin Whitehurst, I started out in the finance world and investing world. I've been really passionate about deploying capital into alternatives and real assets. I've worked in private equity and venture capital, and I've also started another company. So I've been in and around early stage investing for a large part of my career. And for me, it's just been a lot of observation of leadership and teams that led me to want to start this company.
(00:01:37) I've seen a lot of interesting business ideas or fund strategies stall out because the leaders weren't necessarily ready for the roles that they were undertaking, didn't have all the skills and capacity required to succeed. And I've had a longstanding interest personally in Carl Jung and the MBTI. And so I've used my MBTI. I'm an INFJ and I've used that analysis on myself for many years. So I'm familiar with leadership assessments. And then my co-founder's a psychologist and data scientist. We met probably four or five years ago now. And when he was coming out of his MBA program most recently, I pitched him on this idea of could we use an assessment tool to help venture capitalists make better decisions on who they deploy capital to? So that's kind of the long/short story, but we're coming together with these different skills, me from investing and him from the psychology, data science and MBA perspective.
Dan Freehling (00:02:40): Yeah. It's a great backstory and a kind of a cool approach to get into the digital development from the perspective of having been in that VC seat and having seen what it's like to be a founder yourself as well. So some reality kind of coming into the mix here, I think, in a world that can be really kind of esoteric and academic and all of that, also being able to bring that in.
Logan Yonavjak (00:03:01): And that's one of the things I like that you said esoteric. I think a lot of people, it takes a bit to understand what's actually being uncovered in terms of the patterns that we're looking at through our tools and our platform. So it's been a bit of an educational journey, I think, for people who are used to, or maybe they haven't been exposed to leadership assessments at all, or they haven't really gone through coaching or ... People come from a wide range of backgrounds. So anyway, we can get into some more of that, but it's been an interesting journey in terms of educating the market as well.
Dan Freehling (00:03:35): What is it that distinguishes Founder Readiness Institute and your various assessments and various other services and tools like that from what was already out there? Why not just say use the MBTI or something?
Logan Yonavjak (00:03:49): A couple things. One is that we are not measuring personality traits or communication styles primarily where this is not a self-reported multiple choice or forced choice answer process, which is typically how assessments are done. And what we're doing is we're assessing somebody's capacity to lead. And what that means is it's bringing this concept of vertical development, which is based on adult vertical development theory. It's about 30 plus years of academic research. And it really looks at someone's ability to think, behave, and act under complexity over time with kind of increasing levels of complexity and variability and volatility and pressure. And so we design this specifically for high pressure roles and to see how someone articulates their ability to basically do that over time. So it's got a dimension of momentum like this person is ... We're predicting that this person is at this level and they can improve it, but they're likely going to go here next.
(00:04:56) There's sort of an incremental growth trajectory to ... And most assessments don't add that dimension of time. They're not measuring at intervals typically, or leadership development professionals aren't implementing at intervals. So yeah, that's one of two of the main reasons. And AI is just enabling us to ... We've trained AI to basically look at these patterns in transcript data, and so the volume at which we can evaluate people has gone up just exponentially.
Dan Freehling (00:05:28): It's really fascinating. Can you walk us through this really tangibly? What does this whole process look like for being implemented and what do the outputs look like?
Logan Yonavjak (00:05:38): Yeah. So we have two pathways to getting the information we need. One is you can sit down and take our ... We have formal assessments you can take. You can sit down in front of a camera for 45 minutes or so and answer open-ended and scenario-based questions. We designed it that way because it's more difficult to game. When you're talking into a camera and you're speaking about yourself in an unstructured fashion, you have to find the way to answer the questions in two to five minutes. There's really no right or wrong answer per se. There's no way to know really what we're looking for except for the construct labels. Or we can take transcript data from a podcast like all of your podcasts, we could analyze your leadership capacity from those podcasts. Interesting. So we just need transcript data, enough of it to look at the same patterns.
(00:06:30) You can think about it as in quantitative linguistics. So we're taking sentence structure and we're looking for these markers that you are able to process information in a complex way and under pressure. And we look at six dimensions right now. We can change what those are, but currently we're looking at coachability, emotional resilience, how you manage teams and how you pivot, like how you make decisions quickly and strategic complexity. And I'm forgetting the last one at the moment. But yeah, so we have six total. And basically what we're giving you is an output of all the scores in those six dimensions. And then we can do a coaching report, which basically highlights here are the main three things you can work on right now that would improve these capacities.
Dan Freehling (00:07:23): It's again, just really interesting and totally different from that forced choice kind of mechanism that you were mentioning. So it's really cool. And you're saying this is newly possible to do at scale because of AI, right?
Logan Yonavjak (00:07:35): Yeah. I mean, we really saw the wave coming with AI and basically went ahead of the curve, I would say. I know others are probably tinkering with this, but in terms of training, we have thousands of pages of scoring manuals that humans have developed alongside AI. We've digested thousands of research reports looking at the directional predictive capabilities of like these constructs in predicting startup outcomes. And so we've just done a lot of work, analytical work to be able to train AI. I wouldn't recommend anyone go to ChatGPT right now and say, "What's my coachability score based on call transcripts?" It's just not able to do the analysis because it hasn't been trained to do that.
Dan Freehling (00:08:21): And why vertical development? So we've had previous guests who've talked about vertical development, so some listeners will probably be somewhat familiar with it. Can you give a bit of an explanation of what vertical development is and then why this is underpinning this assessment and all of your work?
Logan Yonavjak (00:08:35): Yeah. Well, I mean, originally going in, this is my co-founder's deep expertise. He's been studying vertical development for 25 years and he's the one who recommended it as the basis of the assessment. He's familiar. He's encyclopedic in his knowledge of all the assessments and who's the research underpinning all of them. So if you want to have him on, he'd be a great kind of deep dive on this front. But it's really this developmental capacity piece that really underpins vertical development in the sense that it shows a maturity and momentum of a person's development over time. And by placing someone along a trajectory, you're sort of able to see a roadmap of their ability to grow and evolve their thinking and behaviors. And so it adds this dimensionality that most assessment tools are looking at the skills, like adding more skills like, how can you be a better listener or how can you communicate in a different non-violent communication?
(00:09:36) Those are all important and there are clusters of skills associated with different levels of development. And so we're not negating the need to have both horizontal and vertical. We just felt that the verticality piece was not present in a lot of the assessment tools.
Dan Freehling (00:09:53): How is the momentum playing into this? I know you've talked about this a little bit. Is this basically kind of potential and trajectory coming together? Is this something different?
Logan Yonavjak (00:10:04): Yeah. I mean, think about it as like, here you are at this level, you're likely going to stay here unless there's some intervening force or you make a decision to change, or people tend to grow at an average pace of they'll go one level up in about 10 years if they don't do any intervention. So I think we experienced this anecdotally in our lives. We all know people that are sort of stuck and that's kind of a generic way to put it, but where someone's just sort of, they've been in the same patterns for a long time and it seems like you've aged about five to 10 years and you're still kind of hanging out here. Well, they're probably, they've not received coaching, maybe they're not seeking outside counsel. Nothing in their lives has really provoked them to have an insight. So people can kind of hang out at a certain level for a while.
(00:10:59) That's why we advocate learning about these patterns and setting the baseline so you can understand, "Okay, well, if I do want to get to this next level or my colleague or my job's demanding it, this is how I can actually progress." Most assessments don't show you a roadmap of development like that.
Dan Freehling (00:11:17): So you talk about this tool being able to combat some of these well-known biases of confirmation bias and affinity bias. How do you think about the other side of this, of any sort of bias that this could introduce having whatever the AI training data set is, for example, or is this going to be missing somebody who might not fit into this kind of mold of leadership? I can see this being some concern somebody might have about either this being used with them or bring this into their organization. How do you think about that kind of flip side of bias on this?
Logan Yonavjak (00:11:52): Well, there's so many different dimensions I'd love to speak about here. I mean, one is that the best alternative leadership decision making process right now is humans and everyone comes with their own bias, some of which you may or may not understand. So when you're applying for a job or going up for a promotion or going up for a venture capital investment, you don't really know what the person across the table from you is thinking or their bias and they do exist, right? Some people are a lot more objective than others, but we all have bias seep in and things like confirmation bias, verbal acuity, charisma, these things all influence us. So that's one thing I always say to people out of the gate, your best alternative is you're being judged and you don't know how. What the AI at least is at the very least is introducing is at least you know what its biases are.
(00:12:45) Like you can ask it to state its biases or you can look at a negative space analysis and say, "Okay, well, you ran this analysis. What is missing in your analysis that you might not be aware of?" There's ways you can actually talk to AI about its own bias in an objective way, which is really powerful. And what we're saying with these tools is we always need to see it as a blended solution. We wouldn't recommend you just have an AI make a decision. It would need to be an augmented layer of information that you're threading together so that it's like you're using the AI as another perspective. And another layer of the AI that's really exciting is you can ask it to play different roles, as in you can ask it to be trained as a different kind of personality type, if you will, or have a different approach to evaluating a person.
(00:13:39) So you can have like five different AIs looking at the same data. So that's another way you can kind of cross train and prevent some layers of bias of just one perspective of AI. So I think there's just some really exciting ways to train AI. And I don't know that we can ever get away from any bias at all, but I do think by looking at transcript data and not necessarily even knowing the person's name, age, race, ethnicity, neurodiversity factors, you can really do a lot to scrub the process from as much bias as you can.
Dan Freehling (00:14:15): No, it's a really interesting perspective of what is the alternative, right? And it's currently extremely biased people, right? And it's like it's another factor to bring into this and hardens to hear that it's not just like, okay, replace all of your decision making with something like this.
Logan Yonavjak (00:14:32): Be scared of
Dan Freehling (00:14:32): That, right?
Logan Yonavjak (00:14:34): So I think that it's this really interesting augmented layer of insight. I'm just happy to have its perspective, but I ultimately need to rely on myself and the cues that I'm getting as well. I mean, there's a reason that people are in positions of leadership and they have decades often of experience and pattern recognition. We don't want to discount the human element. It's just that if you just take the venture capital deployment factor, I know this gets thrown around a lot, but the fact that two to 3% of investment are going towards minorities or women led companies, there's a lot of reasons for that, right? Women and minorities might not be applying for a lot of funding. There might be all sorts of factors there, but it's still a very small amount. And I do think that the venture capital industry is largely led by older, typically male, white males.
(00:15:31) And so they come with their own bias of what's going to be a successful leader. And so just, it's an area where we can disrupt thinking and at least offer a more diverse perspective. And that makes me excited.
Dan Freehling (00:15:46): Can you walk us through these different use case pillars? I'm not sure how you would internally refer to them, but there's the VC one, the more like enterprise one and any other kind of use cases that you have for those.
Logan Yonavjak (00:15:56): Yeah. Well, I'm a very a systems oriented thinker and so is my business partner. So we think a lot about like, where can we influence systems change? And I started out in the venture capital. My hypothesis was that it would be a better way to make decisions in venture capital because ultimately the way innovation is funded is primarily through venture capital. And because we're seeing these low rates of minorities, women, people of color, et cetera, I think there's just that alone is one bias and it could be preventing all sorts of interesting innovation outcomes. Not to mention that nine out of 10 companies fail that are invested in from a venture capital perspective. There's just all these layers of distortion in a sense. And can we use better people analytics to improve company outcomes and therefore improve innovation outcomes? And so that's why I started there.
(00:16:53) We ended up moving towards LPs because they can write bigger checks and they have more influence over VCs. And so that was a kind of systems lever decision. So we have a fund manager evaluation tool as well, hoping that that will be a better way to actually influence the venture capital industry and family offices, et cetera, are a good source for that. And then the enterprise space, obviously corporations, especially middle market companies, already have HR systems in place. They might be familiar with assessment tools. So we are targeting them from a business go-to-market strategy. It just makes a lot more sense for us to grow.
Dan Freehling (00:17:33): Does the underlying tools, assessments, all of this kind of stuff change based on the use case, or are you seeing that leadership is largely fundamentally the same across these different spaces?
Logan Yonavjak (00:17:45): That's such a great question. I mean, I think we have hypotheses about that. We are building our data sets all the time, and that's an important factor of this. We want to be able to be like the go-to group that can dial into these different leadership capacities. And we also use other assessment tools, by the way. We have a partnership with a group called MillerMatch, and they've been around for over a decade, and they look at behavioral characteristics. So we're not opposed to layering in other information, but I think that it's dependent on the circumstance insofar as some roles require more pressure than others, and some require more systems thinking. And so what we're targeting initially is more executive promotion hires or executive hiring because of this complexity piece. So we're making the assumption that if you're going to continue to get promoted as a professional, especially with AI in the mix now, you need to really be able to manage a lot of complexity and deal with a lot of pressures.
(00:18:47) Someone who's working at, and this isn't to diminish any particular role, but if someone's working in the plumbing industry or more of a blue collar, a services role, they might not need to juggle massive amounts of complexity or high pressure situations. We probably wouldn't evaluate them in the same way or need them to be as high in their development there. So it definitely depends on the roles, but how we're developing our tools is for specific use cases around more executive hires and promotions.
Dan Freehling (00:19:20): Yeah, that makes total sense and the situational kind of approach to it. And you can definitely see how a startup founder getting VC funding and under tremendous pressure to make the next kind of unicorn company would be different than somebody who's running a more local services business right?
Logan Yonavjak (00:19:39): Yeah. And we don't need ... It's an ecosystem approach. We need all sorts of kinds of people to work in the world and to make decisions and to ... We need people who are earlier in their careers. We need more seasoned professionals. We need people in high pressure situations. So we're kind of targeting the high pressure, but we can measure all sorts of factors because at the core is our technology, which is analyzing transcript data and telling AI how to do that under different circumstances now that we have the tools is a lot easier.
Logan Yonavjak (00:20:13): That's one of the other differentiating factors I wanted to share about what we can do is we're not just locked into these six constructs. We can measure all sorts of things now that we have the capacity for AI to analyze these transcripts and see patterns.
Dan Freehling (00:20:28): Yeah. On this transcript data, could you just again walk us through what gets fed into this? What constitutes a transcript and how does that work?
Logan Yonavjak (00:20:39): We need enough of a person speaking and talking about themselves to be able to run a material analysis. And the AI will tell you if it has enough information, but in terms of like tactically, we have just a drop, it's sort of like when you drag and drop on your computer, you can just drag and drop as long as the transcripts say your name or like isolate who's talking, we can run that analysis essentially. So we want to make it as seamless as possible in that you can just drag the transcripts on your computer and then it goes into our process. Obviously there's data privacy issues. We are very careful about that, who hosts the data, what we do with it, how we anonymize it, but then almost immediately we can get you that first pass and then usually a human reviews it if we're going to do a readout for someone.
(00:21:31) And yeah, that's basically, it's pretty simple.
Dan Freehling (00:21:34): Yeah. How do you think about the utility of 360 feedback? So I know some assessment tools that I've used in the past of, you'll have supervisors, you'll have peers, you'll have subordinates kind of all reporting into something. Do you find that useful, not useful, something worth considering?
Logan Yonavjak (00:21:53): We're actually working with a group right now to basically run their 360 analysis for that reason that we can ... I mean, if we know who's speaking, we can basically flag that as commentary about the person and that will also get analyzed in terms of creating a more holistic perspective of like, here's what the person says about themselves, here's what we would rate them along the constructs, and then here's what other people would say about how it ... And the AI will connect the way the person talks about the individual as related to one of the constructs. And so yeah, that's absolutely something we can do and I'm very excited about because private equity, for instance, uses a lot of 360s, but it's very onerous to get the information. So in theory, you can get a lot of that from calls and you can also interview people and ask specific questions in a different way so the AI can see the patterns.
(00:22:51) One thing we see with 360s is people are nervous about providing like really genuine feedback. So that's why augmenting it with conversations or like team meeting notes, if people are comfortable, that can also kind of mitigate against some of that.
Dan Freehling (00:23:08): It's a really good point on the ... Our 360 is actually giving you honest information and can approach like this, do this in a better way that gets beyond some of that. Because you're right, some people are not going to be willing to say something negative about somebody who might have positions of power in the organization might be a nice person and don't want to hurt somebody else in that way, but it's not helpful for their own development too.
Logan Yonavjak (00:23:31): And often, if people don't have a baseline of understanding of their own leadership capacity, feedback, sometimes they don't know what to do with it, just to play devil's advocate. I think I've received ... Early in my career when I knew myself, I didn't know myself as well, I would receive constructive feedback and it's like really helpful, but where do I place it in my own development? Nobody ever really gave me a roadmap for what to do with the information necessarily unless it was skills-based. So it can be kind of a deep thing for people to get a bunch of feedback from their colleagues and they don't really know how it fits in the mix of what them as a person, their own development. And I
Dan Freehling (00:24:14): Have a colleague who talks a lot about kind of strategic ignorance on some of this stuff, but you'll get feedback from particular people that will be on a very kind of parochial area that they really care a lot about, but it's probably not what you need to level up to this next stage of development. And it's like, okay, this person just cares a whole heck of a lot about this one kind of an area or they have some other alternative motives in providing this. And it's like not all feedback is created equally.
Logan Yonavjak (00:24:41): Yeah. No, absolutely. Yeah. People sometimes go off on tangents about things that they care about, but it's not necessarily the most constructive for the individuals. So yeah, no, this is all, I think, leveling up understanding of leadership. I think this is all creating more ... One of the things I love about our reports is it talks about what's missing. So it talks about what the person doesn't mention. It says, "Oh, this person said this and this and this and this relates to their development here." But it also says, of note, they didn't mention any of this. They didn't talk about how they felt around their colleagues. They didn't talk about any somatic awareness. They didn't talk about other people's perspectives. And so those negative space analyses are really powerful in knowing what someone isn't doing.
Dan Freehling (00:25:29): It's fascinating again of what's not even on your radar and how does that factor into things. Yeah. And I guess with some of the more traditional ones, it would prompt you to talk about those, but this one wouldn't, right? So you actually be able to see what is completely missing from what they're thinking.
Logan Yonavjak (00:25:44): Yeah. Because it's open-ended and it's showing the internal map of where someone's headspace goes when they're under a little bit of pressure and they have to answer a question. It's like there are grooves in our mind. We've literally built these habitual patterns of how we think and behave about our think about ourselves and tell stories. And so when you're kind of a little bit under the gun like, "Oh, I have to answer this question," you kind of revert back to where you typically sit. And again, there might be aspirational days where you're at a level above where you typically are. And we account for that where we say, "This is you on a bad day, this is you on a great day, here's your growth edge." Because we know you're not always going to be your best when you're on these calls or when you're doing the assessment, but I think it sort of gets at the general state of play.
Dan Freehling (00:26:35): How do you think about this whole debate around strengths-based leadership versus this kind of gap analysis? There's this whole idea of, do we want to develop well-rounded leaders, so to speak, or is the spiky leader also something worth considering? I know a lot of people think about this with, is the right feedback to someone like, let's say a Steve Jobs or something that you need to be improving all these different areas of leadership, or is it enough that you can do this one or two things exceptionally well and that's going to carry the day?
Logan Yonavjak (00:27:08): I've heard so many different perspectives on this. I have my own now at this point. I wanted to say two things about this because this is the question I really, I think has the most diverse perspective. I've heard some coaches or mentors in my life be like, "Oh, you need to work on things that are difficult for you and get well rounded." Other people are like, "No, just focus on the things you're really good at." And my intuition has always been build a team, focus on what you're good at and augment with the team to make sure that you can optimize where you can spend your time. That being said, I do think that coachability is one of the most important constructs that a person can bring to the table because if you're not coachable, then you have a fixed mindset and you're not able to, your identity's not very flexible in so far as like sometimes when you do have to push yourself a little bit in a direction you're not comfortable with or you need to realize you're not good at something and bring someone else on, that is such a foundational ability to be coachable and be flexible.
(00:28:14) And I think if that's not present, that's really challenging.
Dan Freehling (00:28:18): Do you think that's something that can be taught, that can be grown over time, or is that kind of inherent in who you are by the time you're in professional life?
Logan Yonavjak (00:28:27): I've run into people who have a very fixed mentality. I think there's always somebody who can reach them, or if something really material happens like a big health scare or they lose a family member or a friend, something really jarring can often shake people from that. But if someone's really fixed in their perspective, I have found it's pretty challenging to move them just in conversation and things like that. So I really do look for coachability as one of the most important factors in whether I want to work with someone or if I were to deploy capital, that's one of the main things I'd want to know.
Dan Freehling (00:29:08): Have you used your own product on yourselves as co-founders and how have you changed as leaders as a result of that?
Logan Yonavjak (00:29:17): Oh yeah. No, I mean, I am so grateful I've taken this. I want to take it again actually now that I know more about it. When we first started the company, it's interesting how you can have an intellectual understanding of something and then go through it. And so it's interesting, I scored fairly high on all of the constructs, but not as high as I thought, honestly, especially with a ... I'm a big systems thinker and I always pride myself in being able to hold a lot of complexity and do that objectively. One of the things that came out from my report is that I don't reference the systems or the frameworks that I'm referring to enough in my conversation. So sometimes my teammates can feel lost in my decision making and how I arrived at a decision and what perspectives I'm holding. And so I've tried to then take that and just be more explicit about how I arrived at a decision and what pathway I took and what frameworks I'm referencing and being more almost quantitative in my speaking about what's affecting the business, for instance.
(00:30:30) So I don't know if that makes sense, but making sure that I'm referencing all the different patterns I'm seeing explicitly.
Dan Freehling (00:30:38): Yeah. Making that implicit, explicit, if you're referring to a framework that's really important for you. I'm thinking about this a lot myself now of when I'm working with new people on my team or even different coaching clients of I have all of these different frameworks that I've blended and developed and furthered over time. And it's a tough ask to ask somebody else to imagine what those could be. So I'm really glad you said that of like, okay, here's what I'm actually basing this off of and here's that kind of foundational framework I'm using.
Logan Yonavjak (00:31:11): Well, there's a dimension of like, I think I have a need for speed. I know that sounds silly to say, but our culture is moving at an ever ... It feels like an ever increasing pace. And when someone news brought on or when you're in sales or when you're even having these conversations, you have to remember that level set where your perspectives are to be able to really have a meaningful conversation. And so there's education involved and you have to slow down to speed up sometimes. And I think just having the patience to really be in a space with someone and realize where they're coming from and have to maybe repeat yourself a hundred times and to get a point across. I think those are nuances that have really emerged from not only just being out front in sales and partnership development, but also the feedback I got from the assessment.
(00:32:06) Just try not to have speed be the main objective of speed and efficiency because it's often not as efficient as you think to try to move fast.
Dan Freehling (00:32:16): You have a company that's on the cutting edge in a lot of ways of AI in the workplace. And it seems to me that you're still betting on people being the most important factor here for organizational success. Can you walk me through your latest thinking? I know nobody knows the answer to this, but what do you think is going to happen as AI further develops and further enters into the workforce?
Logan Yonavjak (00:32:42): Well, that's partly why we're focusing on the executives piece, because just from a pragmatic perspective, I think like any major new technological advancement, I think the answer will lie somewhere in the middle of like we're seeing this, there's extreme predictions of, oh, there's going to be like 10X efficiency factors in coding and things like that. We won't even need most coders anymore. On the other side, people are like, "Well, humans are still relevant for the next 10 years and X, Y, Z." I think it's just, we don't know and it's going to shake out, but it's probably going to be somewhere where we're hybridizing between the humans and the AI decision makers. And I don't feel like I know enough about how the pace of advancement with a lot of the AI tools to really be predictive in terms of like timelines, which I know isn't that useful.
(00:33:36) But I feel like what we're trying to solve for as a company is the people who do remain in positions of leadership who are working with AI, they need to be at a high level of ability to hold complexity and pressure. So that leadership capacity and readiness is kind of more important than ever. If companies are putting limited resources into hiring and promoting people and using AI for a lot more, those that are going to be managing AI need to be, we need to assess them for their abilities there. So that's where we're positioning ourselves as a company from like a pragmatic perspective.
Dan Freehling (00:34:12): That makes a ton of sense. And it's all of these factors that have been part of executive leadership are just going to get magnified as all of this capacity increases for organizations.
Logan Yonavjak (00:34:22): Yeah. That's a great question. I mean, what do you think?
Dan Freehling (00:34:27): I have no idea where this is going to go. I mean, you're articulating these points both of like, is everyone going to lose their jobs basically and it's going to be an entire world and companies run by AI or is it going to be kind of nothing and this is all over hyped. And I personally think about the same thing as you, that it's going to be a big efficiency boost and a big capacity boost, but that it's still going to be kind of the leaders are still going to be what matters in organizations and being able to get above that average level of everything will be able to be done kind of in a mediocre way and it's, can you do things that are exceptional that drive exceptional value? And if you can't, then I think I'm really worried for all of these companies and people who are kind of middling and doing like average work.
(00:35:17) And I think it's either going to be kind of the most efficient or the best and there's going to be very little in between.
Logan Yonavjak (00:35:24): Yeah. Well, and it's also, there's this dimension of like in the past, when different efficiency technologies have come online, whether it's the smartphone or just a variety of other tools, people often find new work to focus on. It's not like people ... There's this predictive, like almost sci-fi perspective where like everything's going to be so automated that nobody has to do any work. But I find that people just fill the gaps with doing more kinds of work or adding in new tools or trying out new things. So yeah, I don't know. I think that what we've seen in the past at least is that it just makes more space to do even more stuff.
Dan Freehling (00:36:06): I think that's so right. And I mean, I think about this a lot where we already have spaces where automation can do things equally as well, if not better. And everyone can get a multi-thousand dollar coffee machine that does every single thing that the local coffee shop can do, but there's still something nice about human interaction and I think the case across. You can already get a cocktail making machine, but people are still going out to bars and that's not changing.
Logan Yonavjak (00:36:36): Yeah. Yeah. There is this element of just enjoying being with people. And I find that with some of these podcast interviews I've done, it's like at home, I'm at my home office a lot and I am using AI and I'm getting a lot of the outputs. And it's really exciting to see the way that it's able to process information so quickly for me. But then I crave talking to my co-founder or getting on a podcast or going to a conference because I want to hear what people have to say and just hear ... Yeah, it's so important to maintain both. That's why it's a both end. I'm excited about that part.
Dan Freehling (00:37:15): So you've done a lot of this in your own life and you have a fascinating career background. I work with a lot of people in social impact and I think of social impact pretty broadly of not just nonprofits or charities or CSR or things like that.
Logan Yonavjak (00:37:30): Because I'm glad. Yes, I can talk about that for a long time. Yes.
Dan Freehling (00:37:34): What would you say to people who are socially impact minded and are approaching their career decision making of, as we look at the kind of state of play of this, where would you suggest they focus? What kind of frameworks do you use in your own head to think about like, how can I have a life and a career that is impactful?
Logan Yonavjak (00:37:55): So first and foremost, I would say understanding yourself is one of the most important foundational pieces. I am not just saying that because I'm of the company I'm running now. I think I've seen a lot of people stall out or have burnout or lose directionality because they didn't really know themselves in the beginning and they didn't know what brought them joy. And it's hard to make a lot of great decisions about your career if you don't know yourself very well. So tools like this can really help uncover leadership patterns and maybe areas of weakness and areas of strength that can inform what you do. And I always like to think about ikigai as like that Japanese term of what's the world going to pay for, what are you good at and like what brings you joy and what does the world need? And so that Venn diagram, starting with yourself, you can at least know what your strengths and weaknesses are, and then you can get a sense from the markets and read patterns and talk to people in areas that of interest to you like where are careers going in this space?
(00:38:59) If you did want to do early stage investing, go talk to a bunch of venture capitalists, go look at their bios, go look at what they read and see, like put yourself in that perspective. Do I want to be that person? Do I like what they have to do every day as a job? Really get into the weeds, like become a method actor and pretend that you're a venture capitalist and like put that, wear that hat for a while. And then what is the true like financial viability of a career? Really, we have more access to data than ever. You can really understand like what the comps are. If you're going to go into an environmental think tank, you're probably, if you look at the 25 years of income, I didn't understand all of this when I started my career, but you're getting a bonus and a base salary, but you're not getting equity, you're not getting all these other like incentive structures for ... So where are you financially as a person and what do you need to feel robust?
(00:39:58) Because it's really hard to make an impact if you don't have your financial life in order. And I've seen a lot of people go gung ho into nonprofit sectors or other social impact opportunities without really having a good financial base and then they feel they get midway in their career and they're flailing. There's just all these decisions. I'm being very pragmatic because I don't think people are pragmatic enough about these decisions. And having an impact in the external world, it comes, in my opinion, second to making sure your own base is covered.
Dan Freehling (00:40:34): Yeah. Starting from that position of strength and prosperity and being able to then be generous with your career and do things in a creative way rather than-
Logan Yonavjak (00:40:43): Like your cup overflowing fast versus trying to lead from an empty cup is just, I've seen it over and over and it really doesn't lead to good outcomes. So we need people who know themselves, who are financially stable and who are resilient emotionally to have an impact in the world.
Dan Freehling (00:41:04): I've very much come to a similar conclusion of doing things that are good for the world starts with having a really sustainable, robust place to start from. And yeah, there's all of these different, you should be kind of martyring yourself for working in the social impact space. And it's actually kind of the opposite because you can stay in it longer term and you can do bigger and better things starting from this place I've been making financial sense too.
Logan Yonavjak (00:41:30): And also I think when someone's ... I use this word conscientious. When someone is in integrity and they do what they say they're going to do and they show up and they're consistent, there's a lot you can do in the world with that. People really appreciate when someone's conscientious and you're likely going to find a job if you're conscientious and your reputation is built and people are like, "That person said they would do this. They did it. They did a good quality." They showed up a person of their word. You'd be surprised how many flaky, just like all over the place people I've worked with myself. And it's just like, yeah, you say you're about social impact, but you're not thinking deeply about the impact you're having on me as a professional working with you or like, yeah, it's not just about these abstract communities or ecosystem impacts far away.
(00:42:18) It's like impact is where the relational day-to-day stuff too.
Dan Freehling (00:42:24): Yeah. It's amazing how in short supply that can be too.
Logan Yonavjak (00:42:28): I know. I'm just really passionate about this subject. I'm glad you brought it up because I used to say this and this and this skill and now it's like, well, start with yourself.
Dan Freehling (00:42:38): Yeah. Yeah. I'm glad the kind of skills only movement is seeming to be recognized as like, okay, this is pretty limiting and there's only so far that you can try to map out every single potential skill that a job is going to need and then that be some of the parts. There's like an underlying character to it that's needed. You mentioned integrity and I think it's so right of who you are as a leader is more important than even the skills because these can be learned and relearned.
Logan Yonavjak (00:43:05): Yeah. I mean, I've had people give me opportunities that arguably from a skills perspective, I didn't necessarily have them yet, but I showed up with what I felt, at least at the time, was a lot of these capacities of leadership. And I think that those, for the mature people that interviewed me that shine through and they saw something in my capacity when I didn't know it at the time, I didn't know to label it that, but I think that's what was being evaluated by some of those people. And I thank them profusely when I see them or I send them thanks right now, but it's like they saw something in me that I didn't even know I was presenting, but at the end of the day, that's what got me the job rather than was I an amazing Excel analyst. And now we don't even really need Excel anymore.
(00:43:51) So just goes to show you. Depends on the timing, but ...
Dan Freehling (00:43:57): It's so right. It's all right. So how do you keep current? What books, what resources of any kind doesn't necessarily have to be books? Do you find yourself referencing, going back to, learning from, any of that kind of thing?
Logan Yonavjak (00:44:11): Well, I've been steeped in a variety of different things for my company these days. So I guess I'll throw out like Alex Hormozi has been an interesting resource for developing lead magnets and sales strategies and cold outreach, things like that. So that's kind of a practical book. I listen to Scott Galloway a lot on podcasts. He just has a really interesting perspective on reading the markets and political dynamics that I find really helpful in just like following what's going on and keeping current in the world. But he also has a lot of personal recommendations on how he invests and things like that. I love This Jungian Life, which is a podcast about Jungian analysis because as I mentioned, I'm a huge Jungian fan. So sometimes I listen to that from a storytelling and archetypal wisdom perspective. So yeah, those are kind of three that I go back to regularly in terms of resources.
(00:45:06) The Alex Hormozi is a little more recent, but I think it's good to, at least from a foundational, like how I ingest information, I like to read a little bit of the news. I actually keep up with a lot of colleagues on LinkedIn and I just listen to what they have to say related to my work in terms of like following certain people on LinkedIn. And then sometimes, yeah, the podcasts, I'll just kind of hone in on one or two to
(00:45:33) Get something different, different perspective.
Dan Freehling (00:45:35): Yeah. All great recs and we'll definitely link to those in the show notes so people can check them out. What is it about Jungian psychology that keeps drawing you back in?
Logan Yonavjak (00:45:45): Yeah, I feel like Jung had a really ... He was able to distill patterns in how people take in information and how they make decisions that I find really profound in the sense that he articulated that there's sensing types and intuitive types. So people tend to take in information based on more detailed information and what has been and like more concrete information about how things are and how they have been in tradition versus the intuitive types, which are a lot more big picture patterns and possibilities and future state. And those are profound differences that I've noticed between people in terms of how you take in information. And then how people make decisions tends to be more logical, rational, objective, versus relational and human and feeling and emotion oriented. And so that does seem to be a consistent theme among people that I've noticed as well.
(00:46:48) And so he just illuminated those patterns for me in a way that nobody else did. And I think he was ahead of his time and just a great mystic in many ways. He has so much more than just what people know as the MBTI. He sat in his, I don't know what room in his house, but he had this room that he would go to and he perceived all of these mystical archetypal patterns that he put down in this thing called The Red Book. And it's a bunch of paintings of just his unconscious mind sending him patterns. And he was open enough to kind of delve into that. And I think he had a lot of courage to go places in the mind that most people aren't willing to go.
Dan Freehling (00:47:28): Thank you for sharing that. Logan, how can people follow along with you, follow along with Founder Readiness Institute and get in touch if they'd like?
Logan Yonavjak (00:47:36): Yeah, absolutely. So we're at founderready.io, that's www.founderready.io. And then anyone can send me an email, logan@founderrl.com.
Dan Freehling (00:47:47): Great. Well, thank you so much for coming on today. Thank you for sharing all of your wisdom and learning from your career and from building this company and would encourage people to follow along and reach out if they'd like.
Logan Yonavjak (00:47:58): Thank you so much, Dan. It was a pleasure.
Dan Freehling (00:48:00): Thanks so much, Logan.
