Logan Yonavjak, CEO of Readiness Engine

Ashby and Dane welcome Logan Yonavjak to the TTI podcast. This episode unpacks how Readiness Engine assesses leadership capacity and enables investors to make high-stakes people decisions based on current and future capacity, not past experience or pedigree.

Transcript

SPEAKER_01 0:14

Hello and welcome to the next episode of I believe this one is called the Technologized Podcast. I had to check myself because we got a few podcasts at Stanford University, and I have been on a few podcasts in my life, and our guest today is a podcast regular. She's out on the circuit doing podcasts. But before we go to her, let me welcome my co-host, Dr. Dane Rook.

SPEAKER_00 0:42

How are you doing, Dane? Hey, Ashby. Um, just suffering through some Mark Twain weather. I know we've got summer coming right around the corner with Memorial Day. Uh, my wife and I always call these kind of days in the Bay Area Mark Twain days. I'm sure you've heard the quote before. The worst I've ever spent the summer in San Francisco, and it is drizzly and gray here. So hopefully that clears up.

SPEAKER_01 1:04

I don't think people understand exactly where you're sitting right now. So I often have to remind people that you sit one mile from where the biggest wave was ever surfed.

SPEAKER_00 1:15

Half Moon Bay, we're famous for two things. An annual pumpkin festival, where we've had the world's largest pumpkin, a few Guinness records broken, and Maverick, which is a massive wave that breaks under the right conditions, usually about December time. It's a function of bottom topography, but sometimes you get hundred-footers, and they are occasionally surfable. You won't catch me out there.

SPEAKER_01 1:36

Boogie board? Because it's boogie board, or what are we doing?

SPEAKER_00 1:39

You would just skip like a stone on a book. These are usually about eight, nine-foot boards, quad fins, the full setup to go fast and kind of outrun the monster. So my foam board, that's not I should leave that behind. There's toe-in surfing now, which is like wakeboarding effectively, where you have a jet ski, you have your feet mounted, and you get pulled in by a rope. That's right. Can be safer, can be worse, depending, depending on your driver.

SPEAKER_01 2:08

One of the greatest documentaries of all time is a documentary called Riding Giants, which tells the history of big wave surfing. But they sort of need to remake the documentary today because it was done before Nazaret came online. Yeah. And so they need to like, because they were like, oh, and the last spot is this place in Tahiti called, you know, Joe Pooh or something. Um, anyways, we're going off track here, Dan. But it is important because the AI wave is coming for our workforce. How you like that transition?

SPEAKER_02 2:42

You saved it.

SPEAKER_01 2:43

Yeah. The AI wave is coming, Dave.

SPEAKER_02 2:48

Your own conversational wave.

SPEAKER_01 2:50

Exactly. Um, and this wave is going to touch every part of the investment organization. And so we have gone out of our way to bring in somebody today that will help us understand how our investment organizations can respond. Because we both know, because we wrote the paper together, that investors have people, process, and information in order to produce return. Well, everything those people do are about to be shifted into different jobs. I've been calling it the transition from FTE to FTA, full-time employee to full-time agent. And we're all going to be managers of agents, but how the heck do we know if we're any good at managing agents? Even our kids are managing agents now. I don't know if you knew that. I watch my kids, it's nuts. They're in there managing beings and they talk to those beings like they're alive. The different AI tools have names. You know, I hear them up there talking on, you know, up there. What are you guys doing up there? Who are you talking to? Talking to their AI agents. So, Logan, Yanovjak, welcome to the podcast. I think I got the last name pronunciation. You did, you got it. You d you nailed it. Beautiful. Well, you are, Logan, the CEO of Readiness Engine, and Readiness Engine is an AI-enabled toolkit, but we're going to use this toolkit in the context of AI upending all of the things we do in the investment industry, but in particular, making sure that the people we have in this in this organization, this industry, this institutional investor are ready for that. Absolutely. Yeah. So who are you? We want to know who you are, first and foremost. Where were you born? We like to go back. Oh, go all the all the way back.

SPEAKER_02 4:46

Yeah.

SPEAKER_01 4:47

Take a minute or two. Tell us about you, how you wound up on this podcast, and then we'll jump into your company and why you built it and run you through our case study method.

SPEAKER_02 4:56

Awesome. Well, so grew up in North Carolina, and I had a combination of in-town and country living growing up. My mom's an evolutionary biologist. My dad was a photographer, videographer, an entrepreneur. My grandmother was a professor at UNC. So I come from a little bit of an academic lineage. And my early interests were in psychotherapy. So I think that's probably the most interesting tie-in to our conversation. So I was, I don't know if this is an accolade, but it was something that was said when I was in high school.

SPEAKER_01 5:37

In a yearbook?

SPEAKER_02 5:39

I was at a no, no, no, by an older gentleman. I was at the Carl Jung Society meeting in Chapel Hill, North Carolina. And he looked around and he goes, You're really young to be here. Do you know that you're the youngest member of this society? So yes, there weren't a lot of my contemporaries at the time interested in um psychotherapy, but I truly credit Jung, Carl Jung, with my early interest in just human psychology, human motivation. I thought his archetypal uh theories were really powerful, and they formed the basis of the Myers-Briggs MBTI later on, which ties into the assessment tool that we've developed. So yeah, I started my life in kind of early teenage years wanting to be a therapist. I realized I didn't want to talk one-on-one to people uh in a room for most of my career. At least that's how I conceptualized psychology at the time. So I got into the environmental movement. I thought it was critical that I get involved with what I was seeing as the climate crisis, environment, other environmental crises, all sorts of different inputs that my mom had given me on with her perspective from evolutionary biology. So yeah, I went into college thinking I was gonna solve the land use crisis and basically help conserve large landscapes. I had done a three-month wilderness course after high school. And so I spent three months backpacking, caving, rock climbing. It was like the hardest thing I've ever done physically. And I just, I think it was my adult initiation, and I gleaned a lot of respect for those who had had the foresight to protect land. And so that was kind of my early formative years. And then um I was working in environmental think tank, and I had an experience with the CFO of the think tank I worked for, who made the comment that um when I found out we didn't do anything with our endowment, made the comment, doesn't sustainable investing make mean you make less money? And I just thought, what data are you basing this assumption on? Convincing him to move the portfolio into a sustainable investing portfolio was the genesis of my basically deep interest in investing. So that's a little bit about my I didn't know that last bit.

SPEAKER_01 8:03

Uh not that I knew about your caving for three months either, but um I didn't realize a small portion of the three months. I don't even know if we're allowed to mention the endowment that that was.

SPEAKER_02 8:15

Oh, I think we're he would, I think he'd be fine with it. It's it now has a sustainable investing strategy and a whole uh initiative at the Institute, World Resources Institute.

SPEAKER_01 8:25

Oh, okay. I thought you were also briefly at a university endowment.

SPEAKER_02 8:30

I was at the Yale Investments Office.

unknown 8:32

Yeah.

SPEAKER_01 8:34

Anyway, I didn't I didn't know if that was that story or a different one. Because then you went to Yale into the School of Forestry, which is no longer called that.

SPEAKER_02 8:43

School Yale School of the Environment is now what it's called. And um that the whole point of me going to that dual degree, the MBA and the master's in forestry, was to continue to work with uh with Temos and um private equity firms that were deploying capital into real assets. So that was sort of my the whole trajectory. And then I can talk about why I pivoted to leadership analytics and solving people problems.

SPEAKER_01 9:10

Well, this is the moment where we we were getting a feel for you. What is your company and why did you start it is usually the question we ask. Help us connect the dots between your history and the present.

SPEAKER_02 9:22

Yeah, so just, I mean, I think um, you know, 20 years into my career at this point, I've worked with a lot of leaders. I've worked with a lot of teams, uh, some functional, some less functional, some incredibly dysfunctional. And I was just surprised, even in my MBA training, how little um attention is paid to people's readiness to lead. Um, that can include anything from their ability to hold complexity, relate with others, um, some personality characteristics, just self-understanding and awareness and constructing teams based on people's developmental capacity, which we can get into what I mean by that. I just thought that was a huge glaring missing component of most of the groups I worked for. I mean, I worked in impact investing, and so there was a lot of visionaries, but I would say a lot of their personal capacities were uh there was a gulf between what they wanted to accomplish and and who they had, systems they had built around themselves and their teams to accomplish those goals. So I just felt that, you know, with AI coming on the scene, there was an opportunity to look at people analytics at scale. And a lot of the assessment tools I've come across are really limited in a variety of ways. So there just seemed like a white, you know, white space opportunity, especially in investing.

SPEAKER_01 10:49

I why are they limited? I think many of us have been subjected to the Myers-Briggs. Um, I think I once sat through the the Ray Dalia principles assessment tool. Um, how is what you're building different from those traditional things that I think most of us have at least bumped into in our careers?

SPEAKER_02 11:09

Fundamentally, there's a lack for the most part. I'm not speaking to every single tool, but for the most part, there's a lack of developmental roadmap. Like, how do you actually grow as a person from a baseline? And so we all are capable of reaching um great heights and self-actualizing, but I think there are a lack of tools to actually point us in the direction of how to climb the mountain. And so a lot of the assessment tools are personality based, they're self-reported. I mean, how many people do you know that are accurate in assessing themselves from a 360 perspective?

SPEAKER_01 11:49

Zero. That is that is literally the point of therapy, I think, with self-knowledge.

SPEAKER_02 11:55

Most of the tools are, you know, you you talk about your own preferences, you talk about your own skills, and so you're it's coming from you. And so this is fundamentally different in that it's providing a third-party, more objective assessment of people, providing that developmental roadmap, and it's measuring very different things than skills and personality traits.

SPEAKER_01 12:19

And so let's talk about what those things are and how you measure them.

SPEAKER_02 12:23

What we're measuring is developmental capacity. It's based on a body of work of about 40 years. There's a couple researchers, uh, Cook Schroyder, um and and others, Torbert, that my co-founder can speak at length about. He's very adept. That's why I chose him as my co-founder to build this tool. But this is based on 40 years of developmental psychology. So, how do adults evolve and self-actualize? And what are the patterns that show up in those developmental milestones? And so this hasn't really been brought into the mainstream for a variety of reasons. One of which is people have a little bit of an aversion to being ranked. So you have to be careful of like how you speak about, oh, you scored here and this person scored higher than you. So there's a little bit of that that showed up. And then there's also just a lack of being able to analyze the data in a rapid, high volume, and low-cost way. So the way that uh vertical development or developmental assessments have been done in the past is you hear someone answer questions and then typically grad students hand uh score these uh these assessments. And so that's not very scalable. Um, so what we've done is take that capability and and make it a, you know, we AI'd it. So uh now AI can do this at a rapid speed, at um higher volume and at lower cost.

SPEAKER_01 14:01

And hearing you talk, I'm reminded of a few authors that have written call it pop books, which might be familiar to people more than the Torbed and and other academic papers that you're referencing here. But I'm sure people are familiar with Duck Work's book on grit and the power of grit to deliver success, which includes like concepts of deliberate practice and suffering in the right direction. And then Simon Seneck writing a whole bunch about how do you measure trust. And, you know, he he goes into the whole thing on SEAL team six, how actually like the most elite special forces operators in the world, like their primary focus is on trying to find trustworthy humans, even more so than high-performing humans. Like once you're in the selection for SEAL team six, the assumption is you're pretty good at shooting guns and running around hallways. Uh, what they don't have yet is trust. And so a lot of those selection criteria are meant to unravel those capacities, right? Would I trust you with my life and would I trust you with my wife is the saying he often talks about.

SPEAKER_02 15:08

No, okay, that's catchy.

SPEAKER_01 15:10

Isn't that a nice one? You know, when I and I I should be fully transparent, I did your assessment. I did 45 minutes of being assessed, and and I at the end of it, I felt very seen by the assessment. Like it was kind of a shock. Like parts of it were like a little depressing and in not fully realizing that I needed to work in areas, but it felt like it was building measurement around things that I think I kind of had a sense for, like I was good, like I had a sense where I was good and where I needed work. And you actually provided me that. And so building metrics in places where no metrics have existed. First of all, I know I'm kind of rambling, but I that's kind of the excitement of AI. It's like, oh, we're gonna start building measurement in new ways. But also you're gonna start communicating things about me that I didn't even understand. And so I don't know if any of that resonates to you or comments.

SPEAKER_02 16:05

Well, first of all, I'm so glad that it's it resonated with you. I I think we've gotten really great feedback from most of the people who have taken it. You know, I think it's kind of like when someone makes an argument or uh you notice something in your surroundings that maybe doesn't is a little off, but you keep it in the periphery and you kind of think, uh, you don't put your full attention on it. I think that's a a lot of people have a sense of their own limitations and growth opportunities, but maybe they just don't take the time or have the vocabulary or skills to actually put it in the forefront and structurally go and and develop themselves. And that's what I think is missing in a lot of situations is not that people are not open to growing or that they have an aversion to it. Some people do, but I think that they just don't have the tools, literally, or awareness or vocabulary to actually know what to do next. And so I think that's a lot of the value we're providing.

SPEAKER_01 17:08

I do really want to build an investment strategy around this toolkit. Like I am just fascinated by the idea that we could, you know, imagine we were Y Combinator and we had hundreds of thousands of people applying to our program and we could subject them to this 45-minute assessment, or frankly, use your tools on all of their publicly available podcasts and things and score them that way. Like I I want to see if that drives you know founder success. Because I know, I mean, let's be honest, you started your business trying to understand if founders were ready to build companies.

SPEAKER_02 17:48

Yeah.

SPEAKER_01 17:49

And so your initial interest area was from venture capitalists being like, are is this founder ready? And now you're being pulled into the whole AI readiness world. But am I right that we might be able to use this in an investment strategy? Like, is the research strong enough there?

SPEAKER_02 18:04

So I'll I'll back up and talk a little bit about the research. Um, so we took about a thousand research articles that we found that are mostly publicly available. Um, and then we down selected to 300 that basically articulated the constructs we chose and showed directional correlation, positive correlation with specific startup outcomes, whether that was follow-on funding, whether that was exits. And so the constructs we chose, leaders that had been evaluated showed one or more of them at a high level. And so that's why we selected these six constructs, because the research teed us up to say these are the kind of the most important things that are showing up. And now we need to further validate the tool with more data and really look at different applications of these constructs in the wild. Um, so that's kind of the underpinnings of what why we chose these was, and again, it was for founders, so it was high pressure, highly complex situations, which can apply to a lot of innovation roles, but um, yeah, was originally constructed for the founding community. And I would love to apply it to um an investment thesis. I think that I can't I've been waiting for someone to to suggest that to me and and launch a fund because I think that's the next step of this is putting this into a pro, it doesn't have to be a proprietary, just how do we apply this across the portfolio?

SPEAKER_01 19:36

I can think of a few maybe softer like it's a big lift to say, hey, let's take 50 million bucks and go back the best founders that score the highest here. But but I could imagine, and now we're gonna chat about how you're helping investors, but this is every organization is gonna face high complexity, high pressure, high stress in the next five years as they are transformed and have to frankly reconcile you know, do I pivot this person into a new role or do I not and actually let them go because roles are gonna be changed and eliminated? As painful as that is to say out loud for a lot of a lot of people are thinking this. And so they will inevitably in this retraining process find themselves sitting in front of a platform. It may be yours or it might be one like yours, right? It'll be ours, it'll be yours. So you're gonna be there, yeah. But how do you think you're gonna help the investment community?

SPEAKER_02 20:36

Yeah, I mean, we've been talking a lot about these um, these kind of three different areas. One is internal team development. Well, it could be hiring, promotion, development within the actual investment firm. So I think there's a lot of work to do internally. Just I know you have better data on this, but just um talent retention and talent, um, just attracting talent in the institutional investment space, uh, it seems like it's um a bit of a challenge compared to other industries. And so how can we how can we double click on that and understand what's happening a little bit better and how we can solve for is it a mismatch of who's being hired? Is it not focusing on some of the dimensions of leadership that could be augmented by some of this development work? Are people just feeling like, I don't know, that there's not enough um attention paid to them or or their team structures off? I think there's a lot of things to uncover there. Um, there's also working with portfolio companies and not necessarily mandating, but uh inspiring the portfolio companies to leverage this developmental intelligence platform for their work. Um, so yeah, I think there's multiple use cases that we're exploring, you know, which one. Product market fit, what's kind of the of most interest and highest use uh for the investment community?

SPEAKER_00 22:07

You mentioned the talent acquisition and um retention question within the institutional investor community. It's a major, major problem. I was having a conversation the other day, and someone likened it to the money ball situation of having massive constraints in terms of what you're able to spend on talent relative to what is conditionally or is is historically perceived as the type of talent that you're looking to attract as an institutional investor. Because a lot of times folks see themselves as themselves being institutions competing with hedge funds or private equity funds for talent. And the ability to remunerate isn't necessarily at that level. This to me is Max was something that actually could help and advantage institutional investors in finding the right assembly of skills that might not have necessarily shown up in platinum pedigree uh tenure at a particular hedge fund or performance results. I'm really interested in the team construction aspect of it because at the end of the day, institutions are teams. Like Ashby was pointing out, there are aspects of individual performance that matter individually, but at the end of the day, these are still organizations that must work together. And I'm kind of curious about how what you're doing wraps up a lot of these constructs and moves from the individual level and saying this is what this particular individual might need to progress in their career to what the organization needs from them as part of a collective.

SPEAKER_02 23:28

Yeah, I think that team, we've act we've gotten a lot of demand for the team construction piece, by the way. It comes up a lot in conversation, like, oh, what can you do to actually help us understand how people will fit together and who are the teams deficient? Yeah, so I have a really concrete example that I really I like to point to. It was a founder we evaluated a while ago. Um, he came up pretty high. So we have six constructs. I don't think we've actually named them, but uh the two I'm gonna talk about one is relational intelligence, which is somewhat self-explanatory, but it has to do with your ability to empathize and put yourself in someone else's shoes and um you know listen and understand where the other person or or team's coming from and be adaptable in relational um in your relational intelligence. And then purposeful agility is how well do you pivot under pressure while holding the goal in mind. So you have a mission you're you're going after, or maybe it's a uh quarterly goal. And how do you ensure that you're listening to information coming in objectively and pivoting accordingly? So those are the two constructs I'm speaking to right now. We evaluated this founder. Um he came up really high on the relational intelligence score, but his purposeful agility score was much lower. So it turns out that he is uh he has harmony bias. So he loves listening to other people, he loves taking into their account their feedback, he's very consensus oriented, um, and he's in the CEO role. But he has trouble actually acting on that information because he's afraid to hurt people's feelings and he doesn't, he, yeah, there's just sort of like once it turns to him to make a decision, he just doesn't, he doesn't know what to do with that. So that was identified in the assessment. And we gave him six, 12, and 18-month recommendations, as well as you need to have a COO type person who's good at purposeful agility and potentially a mentor who's gonna hold you accountable. So you need to bring up specific conversations you're about to have with your team or specific execution areas, and you need to talk through how you're gonna make a decision in a timely fashion. So, like that's just one kind of dynamic that came up that I think is just fascinating, how you can be high on something and then lower on something else, and how it can really cause friction in your ability to lead.

SPEAKER_00 25:54

I was gonna say, in terms of sort of subtle diagnostics, that's that's really impressive to be able to suss that out, which is not something you might conventionally get from just simply taking one of the standard personality assessment, skills assessment type of diagnostics. But I'm curious about explainability, because that is a major issue writ large in AI is how do you explain an assessment or a score or a decision that comes out of an LLM or whatever other underlying architecture? Um, to what extent is does that factor in in terms of being able to go through and back out from a score and look at site-specific statements the individual made, or how does that go about? How does that function?

SPEAKER_02 26:33

Well, we provide evidence for why we selected that person a specific score. We talk about a developmental range. So you have a good day and bad day self. And so you might be showing up on a good day, you might be a half point higher than you typically are, and in a bad day, a half point lower. We're measuring like where you show up primarily, like where most of the data was pointing to. And so I think that helps. Um, it's like easy an easier pill to swallow than just saying, here you are. And then it talks, you know, we talk a lot about like um paring it down to about three things you can focus on. So for Ashby's report, it was like three specific things that you can focus on um to get you to the next level, just so it doesn't overwhelm people. Right. And we talk a lot about in the dashboards, we talk a lot about how we score. And so this is what we're looking for for higher levels, this is what we look for for lower levels, um, just to try to orient people. I personally think most people need a human to debrief them. I think it's a lot more powerful when you have someone sitting across from you and just kind of explaining what the scores mean. That's obviously not for everybody. I mean, we are building a scalable AI-backed, you know, company. So we do have many options for where people can just get their readout and dashboard and just walk through it. That's the goal is for it to be very digestible. But I do think, like, if it's just me talking as myself, I do think it's really helpful to have a person kind of just lay the foundation, at least in the beginning.

SPEAKER_01 28:18

I did like that. You know, I had the chance to have Benji tell me what all this meant because it's heavy, heavy science, right? So, you know, a lot of the words I have a doctorate from Oxford, I needed to double check, right? So that that gives it, by the way, some of the credibility. It's like, oh, this is not just random AI slop, like this is you know, peer-reviewed insights that have you know survived 40 years of assessment. So, but I do think there's a piece as we get into this where people are probably going to be more comfortable engaging in kind of a private tech environment where you know, you're like, I I at the very least know this is just for my eyes, you know, and and so I can kind of be open to more criticism. Maybe I don't know.

SPEAKER_02 29:07

I mean, a whole area that I'm fascinated by, and I we haven't dug into this yet, but it's on on the docket is AI coaching. So some people love the idea, some people, you know, want to throw up at the idea. I I feel like any new technology that'll land somewhere in the middle eventually, where you know, there's gonna be some people using it for kind of low-cost insights and and engagement, some people who don't want to use a coach or therapist, and then other people who just always have an aversion to using AI for self-development. So, yeah, I mean, I think there's a lot of opportunity to develop and gamify some of these insights. I'm really excited about that piece. I think getting, as we build our company, having um people who are specialized in understanding how to gamify and make things interesting and engaging will really take this to the next level.

SPEAKER_01 30:00

I uh I admit that up until this experience, when I I might have been one of the people who would groan when people would say I'm a coach, you know. I oh, I'm uh, you know, manager coach. And I'm like, oh come in, you know, but now I have to admit, like I get through this, I'm like, actually, I probably could benefit from some coaching in certain domains. Like, I'm a little bit too soft on people, you know. Um, and so one of the things that I think I want to work on, uh Dane, I'm gonna hold you, it's gonna be so tough for you now after this, Dane. Uh I'm gonna become the you know, the tiger boss. You know, just really learning how to be your best self, you know, and make make the best of it. So anyway, let's focus here not on my assessment, but on your company and how you're helping investors. One of the things I just want to understand as we get near the half hour is how how does this help the investment community 10 years from now? So if you're wildly successful, I have a hunch you are going to help pension funds make the best use of the talent they have been able to recruit. You've got people in the door, and those people are more effective because you help them spot the areas where they could be best applied, but also help them spot areas where they can grow. And so, was that a way you think about it? Where do you see this entire industry in a decade?

SPEAKER_02 31:36

The way I conceptualize it when I got into the impact investing space was that if we had more developmentally adept individuals and teams allocating capital, we would see more positive outcomes in the world. So that was kind of like my highest order perspective and leverage point. Like, but I realized that it was, and I worked with a lot of family offices in one of my roles. And I realized, you know, there's these individuals out there with hundreds of billions of dollars in many cases. And so much hinges on, because family offices are so in particular, are so um not I wouldn't say unstructured, but there's a lot of leeway in what they can, what they can do and how they can form themselves. It really so much hinges on the principles and their own psychology and their own orientation and self-development, all those things. So I found that really inspiring to like how do we reach these individuals? And then, of course, those who other asset owners who manage these large pools of capital have so much authority into what happens in our society ultimately. I mean, these are we're talking about trillions of dollars at this point. Um, so I'm very passionate about those leaders and how they're constructing their teams and just um being able to retain and grow talent who think long term and who think about impact and widening the aperture of what we've traditionally thought about in investing beyond just, I mean, of course, returns, but also how we're impacting society, how we're impacting the environment with our investment decisions.

SPEAKER_01 33:18

My and my last question, and I'll let Dane go deep on his thinking. But when I hear you say all of that, I almost hope that the tools you're bringing to human beings today to help level them up in their thoughtfulness and their ability to integrate long horizon factors into short-term decision making. I'm sure those are all parts of your assessment tool, which is great. Are you then going to be able to help make the agents that do this work better?

SPEAKER_02 33:53

I'm so glad you brought that up. Yeah.

SPEAKER_01 33:55

Yeah.

SPEAKER_02 33:56

So, well, so my uh Benji will talk about how um, you know, he played around with this a lot initially as we were learning how to use AI with with what we were building, but he his perspective was that AI, for the most part, is coming from kind of a mid-tier of development. And that wow makes that makes sense. It has a harder time with levels in our construct, levels five and six.

SPEAKER_01 34:22

Six is the highest.

SPEAKER_02 34:23

Six is the highest. We go from one to six. And his perspective is that, or his theory is that most of the developers and most of the inputs from society, like if you think about um the mid-band of of development, which is like 2.5 to 3.5, that's where most people sit in their own developmental capacity. Um, that's, you know, and people who are involved in the um information economy are coming kind of from that band. So a lot of the training data and a lot of the people developing these tools aren't necessarily at these, at this five to 10% of the population, which are at the higher bands of development. Some of them are and maybe in different ways, but then there's also a skew of um most coders and developers, I would argue, are probably more higher on the strategic complexity or some other kind of higher on the cognitive factors and maybe less on the relational intelligence, less on some of the other things we measure that are more human-oriented. So we've got these biases into AI right now. So we one of our desires as a company, and um something you brought up early on, is can we actually train AI to be more developmentally aware so that it can inform decision making from a higher vantage point? And something, a follow-on idea, which I think is really exciting, is as we're building second brains for ourselves, could we give ourselves the highest version of development to inform our own decision making from a different perspective?

SPEAKER_01 36:03

Like I created a version of me that is sixes across the board, and then I check in with you know, enlightened me before I make a decision.

SPEAKER_02 36:12

It's like the angel on your shoulder. How do you create that using AI? Like that's a it's a pretty exciting possibility.

SPEAKER_01 36:19

Amazing. Thanks. Dane, any deep thoughts or questions? That wasn't deep enough.

SPEAKER_00 36:25

I was deep. I know this is it was very deep and it was very, very good. And I in in hearing all of this, you know, don't laugh too much. But this sounds like the ultimate version of the marshmallow test, frankly, in terms of finding people.

SPEAKER_02 36:38

Oh wow, yeah.

SPEAKER_00 36:40

I'm sure I'm sure everyone's familiar with the marshmallow test. And obviously it's faced a lot of scrutiny in recent years and reruns, and is it actually a robust test like so many other Stanford developed tests, the prison experiment being another one? Um, we're really kind of shameful in that respect. But in terms of being able to filter out and find individuals that have qualities that might make institutional investors more long-termist, this sounds fantastic. I gotta ask: have you ever run ChatGPT or Claude through this? Rather than thinking about how do you build, have you gone and screened? Because people talk a lot about how do we best put up guardrails on advanced agents nowadays? And a lot of it kind of tends to bend back on well, let's set up a bunch of fail-safe rules that it is not allowed to do this, it is allowed to do that. How much would it be able to profile and limit the EQ, for example, of an agent function from a guardrail standpoint? And have you tried this on any of the foundational models?

SPEAKER_02 37:40

Well, this would be a great conversation to have with Benji. He's done a lot of that because he basically has trained three different LLMs to with underlying research and scoring manuals and confines of the research to create what we created. So he's been working and he, but he's his starting point was kind of testing out what where its limitations were or where the different AI limitations were. So that'd be a fascinating discussion to have with him. I haven't been doing that work myself, so uh, but it's a great question.

SPEAKER_01 38:11

I love it. I am uh incredibly curious to see all the insight you bring to investment organizations. Um, you know, if you I would normally ask people if you were going to give yourself advice, you know, 10 years ago, but you're just getting going because this whole world is just opening up. Um, and I have to say, like, you know, we met through a mutual friend. I took the, you know, I took the assessment as kind of uh, yeah, I'll help out a friend. And it like dragged me in.

SPEAKER_02 38:43

You know, I feel I'm so grateful for that.

SPEAKER_01 38:46

And I find myself introducing you to pensions, and funnily, like we've had four pensions that want to work with you, or at least to hear the story. And so, um, and that was enough inspiration for me to invite you on. So thank you, Logan, for coming on and telling us the story of Readiness Engine.

SPEAKER_02 39:04

I'd love to share more when we're farther along, too. I think there's just going to be a lot of interesting things to track for the institutional investor community. And so, yeah, I look forward to future conversations.

SPEAKER_01 39:15

We'll have you back on. I hope you level.

SPEAKER_02 39:18

I invited myself back, basically.

SPEAKER_01 39:20

Yeah, yeah, I know. Exactly. That's a really that was a ninja move right there. You must be operating on another layer of intelligence.

SPEAKER_02 39:29

Um you haven't seen my sports yet, so I have not.

SPEAKER_01 39:33

You've seen mine though, so that's unfair. Um, thank you, thank you, Logan. We're really excited. And for the listeners, we'll we'll be back. For Dane Rook, I'm Ashby Monk, and uh this is the Technologize Podcast.