#604 AI Can Generate Expertise. It Still Can’t Generate Judgment | Dan Pratl, Founder & CEO, Quadron

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Mehmet: Hello, and welcome back to a new episode of The CTO Show with Mehmet. Today, I'm very pleased, joining me from the US, Dan Pratl. He's the founder and CEO of Quadron. Today, we're gonna talk about, I think, a topic we didn't touch too much, um, about, you know, how still humans are important in this whole AI revolution that we're witnessing in front of our eyes.

Dan has a very special point of view on this topic, and actually he's building Quadron all around it. But before diving into this, something I do with all my guests, Dan, tell us a bit more about you, your background, your journey, and how did you decide to start Quadron, and then we're gonna start the conversation from there.

So the floor is yours. 

Dan: Absolutely. Thanks so much. Uh, love being here. Um, so Dan Pratl, as, as, uh, I mentioned. Um, started Quadron because I had a very serendipitous journey through, uh, a number of [00:01:00] different industries and, uh, economic events. Started at the SEC in the United States during the Great Recession.

Um, got to see how regulation maybe didn't apply as it probably should have, or at least was intended after the Great Depression in the 1930s. Uh, moved on to open source, got to see open source move from an incredibly vibrant social coding experience to something that was something akin to capture up by monopoly.

Moved into crowdfunding, um, you know, democratized or decentralized finance, kind of the V1. Got to see how regulation, uh, really strangled and inhibited innovation. And then went into crypto, um, and got to see how, you know, something that came out of the Great Recession and promised a better tomorrow largely turned into a speculative exercise.

And Quadron is a, uh, a bet on that there's goodness in each one of these regulatory apparatus, the technologies that came out of these experiences that, you know, the people that created them, uh, uh, went, lived through, [00:02:00] and that we can take each portion of them and build what I would call a programmable stack of incentives, allowing individuals at this new, you know, this, this new phase of development where the intangible value of the world around us can now be structured, analyzed, and therefore quantified, programming incentives into a new system for generating assets to actually encourage individuals to do the right thing rather than letting base human interests run amok.

Mehmet: Great. Then I'm gonna ask you a question which I didn't prepare, but, you know, just it popped up in my mind. Okay. Yeah. How that is different from... Because, you know, you s- you, you talked about how the system proved to be kind of broken, especially after the financial crisis back in two, 2008, 2009, and people wanted this alternative, and, you know, blockchain was the solution, and the reward was, you know, when people, you know, participated in mining and all these things, so they get rewarded.

So how, you know, this is different, [00:03:00] and why that one didn't work in the way that it should work in the first place? 

Dan: Yeah. So what, what is actually taking place with blockchains? Uh, because they're just Bitcoin, the first one. Um, it is giving people digital religion. It is giving people a new incentive, creating money from nothing, an incentive layer from nothing, telling a great story about a better tomorrow, and then, um, asking people to do something very specific.

Hold the token, right? Create an inflationary environment, make token go up. And that was great. That was interesting. It, it developed community and strong community feelings and tribal feelings, but that was about it. You know, if you look over the last 10 to 15 years, we really haven't got away from staking and the speculation around staking.

What we're doing here is we're saying digital religion, creating tribes, creating, uh, a community feeling is absolutely critical, but it's not the point. The point is to do something that we couldn't do previously, and that previous, the thing [00:04:00] that we couldn't do previously, was actually construct assets and invert markets, not a place that you go to to trade on tokens or trade on equities or bonds, but actually create assets around ourselves, right?

The intangible value that we bring to bear, and then allow individuals to start investing in themselves. Staking on yourself, on your expertise, sends a signal to the world that you believe in something that you are doing, and that you can back it up. You have an auditable record of progress that you've made.

Staking more creates a bigger signal. Staking less creates less of a signal. Not only are we inverting markets and not only are we creating market mechanisms to allow human beings to invest in themselves and their expertise, but we're allowing individuals to then benefit in a way that they could not otherwise.

Which means that rather than just staking on the token and the token being the point, their expertise evolves. The token is just a mechanism and a proxy for the value of the things that they are doing. It's not the point, per se. 

Mehmet: Right. Now, [00:05:00] when, you know, we go and, um, try to think about how AI is, is, you know, generating a lot of information, there's a lot of, uh, you know, things that are being generated today at the speed of, of, of light, I can say this, right?

Yeah. So verification and credibility becomes like something very im- very important, right, in the AI economy. So what exactly breaks when intelligence become abundant? And I think we are in an abundant intelligence today with all the frontier models and, you know, all the agentic also frameworks that we are seeing.

Like we, we, we look like we are living in the future. But why, you know, still the trust doesn't scale with the abundance of intelligence? 

Dan: Yeah. So knowledge and commun- uh, knowledge and, uh, execution have largely been commoditized at this point. Um, [00:06:00] high quality stuff can be generated at the speed of light, as you said.

Um, what that means is that it creates a, a, a problem shift. You know, uh, high quality output in the past meant that you had invested time. That's no longer the point anymore. Now, the opportunity, uh, is to show that an individual actually believes in the thing that they are putting forward. So to verify your work, we call it a finishing layer, to verify your work on Quadron, um, needs to be a byproduct of personal ambition.

You're getting something for identifying the high quality thing, not just throwing all everything into a Google Drive and throwing it to somebody, but saying, "This thing over here, not the 16 other documents. This thing over here is the finished one, the one that I believe in, and implicitly the one I stand behind."

Right? That is the opportunity here, is that you need an ensemble approach, a finishing layer that says, "Develop wherever you want on whatever model. Identify the valuable thing, bring it here, have it [00:07:00] associated with you, build it into your broader context of who you are and what you're doing, and then stand behind it."

And then, because no man is an island, no person is an island, you're going to collaborate with under- uh, other individuals. The deeper opportunity here is to drive novelty. Again, the thing that human beings do and, you know, don't real- and the models last time I checked aren't doing, is coming up with fundamentally new insights.

If you identify op- i- identify artifacts, if you stand behind them and others can find you, you more rapidly not only identify yourself as credible and protect your secrets, protect your information, but you can actually start driving novelty in a structured way and start monetizing it earlier. 

Mehmet: Right.

Then I'm gonna ask you something als- also a lot of people, you know, I, I, I think it's top of mind topic. Now everyone's talking about, like, how AI m- makes expert looking like work nearly free, right? So i- i- [00:08:00] it's, it's like, it's a reality actually. And because if you think about it, any topic you and me we can come up with now, you know, we can go and do a deep research with any of the tools, and then we can ask it to go summarize it to us and, you know, do this, do that.

If that's true, does expertise itself becomes, like, less valuable, or does verified judgment become, you know, the most wanted asset and the most scarce asset in your opinion? 

Dan: Yeah. So we, we've grown up and we've lived in an environment where the artifact was the point. Um, I mean, think about our intellectual property system.

It's now, what, 200... Look it, I'm looking at the date here. It's 236 years old, written into the Constitution of the United States by James Madison. Um, it is archeological. It's backwards looking. It assumes that the effort to create the artifact was the point, and then protecting the artifact is what the, uh, you know, the monopoly on enforcement that comes from, from, you know, IP law, uh, that that is the point.

[00:09:00] That's no longer the point. The artifact isn't the point. It's not even the claim that you're making that's the point. The claim is the revol- resolvable opportunity. It's the insight that evolves that we are capturing, uh, that is actually the thing. We call it a lens. Um, so hopefully your audience is, is familiar with MCP, Model Context Protocol.

Mm-hmm. Skills, these deployment objects. Think about that as a snapshot, a point in time. You've come up with something to deploy or even code and then deploy by agents. That doesn't evolve. It's not persistent. Uh, it's still a creature of code. You go to GitHub, you download it, you, you put a star, and that's pretty much it.

Now, now you have a version of it. That is version one. Version two is your insight evolving that skill, that skill becoming yours, that skill being hardened by you making claims in the world. The artifact that it generates, 'cause you can still run it like a skill and have output, that artifact that generates is not the [00:10:00] point.

The skill itself is simply a deployment object. It's a snapshot to make a, a machine go do something. It's what you learn about being right and wrong and iterating and evolving it, and being able to communicate that and show an auditable record that is the point. That is the asset. Now, we're not gonna trade our lenses.

They are a creature of prediction markets, likelihood of efficacy and resolvability by some point in time in the future. That is the asset. The asset is you betting on yourself, investing the time to make your assets, uh, sharpened, hardened, if you will. And over the course of time, you become a more robust individual because your, your, your, your, your, uh, your auditable record becomes, uh, more robust, more sophisticated, um, you know, more, uh, like hum- human expertise.

Grows over time. 

Mehmet: Now let me ask you this, Dan, as a follow-up. How would that be different from when... Still, I [00:11:00] think we, we see it in some platforms, someone rates me, right? Like, or maybe they endorse me. They, they say- Yeah ... yeah, like Mehmet, they write a recommendation for me, right? So, so how, how this will be, you know, different, um...

And if I think about it, I don't want to go too much technical from the data point perspective. So if I manage to, to your point, like, to, to stake myself and, you know, put all these things and I, I manage to get people to endorse me. So h- what would be like, I would say, you know, the, the correction mechanism for this to, to make sure that, you know, me as, as someone who's claiming this knowledge is really, you know, verifiable and I can say, yeah, like probably this guy is the right guy.

Um, the reason I'm asking you, Dan, because one of the use case I can think about this is, you know, how usually companies, they evaluate talents, for example, right? So, so we, we [00:12:00] just-- we, we, we, we look at their resumes, we look at the places they work. So- How would that, you know, as a prediction market, as you describe it, would, would be able to replace the status quo?

Dan: Yeah. So the world today runs largely on social proof, prestige networks, um, individuals, you know, having qualitative anecdote- anecdotes around, uh, a person's efficacy, uh, productivity, uh, utility. Uh, that really worked in an analog world or a somewhat of an analog world where we could go and verify if you are who you say you are.

Um, you have on your, you know, digital resume LinkedIn that you went to this school. Well, I can go to the clearing house that is that school and, and check if I really want to. And that's, you know, that works in a world that, that, that, that, that operates at a slower pace. Now we can't have that. It doesn't work anymore.

Those are all largely collapsing. These social proofs and totems of competence like a degree are largely collapsing. Things are [00:13:00] simply moving too quickly. You need to have a system that allows you to have a verifiable, quantitative record of progress or lack thereof. And if you wanna lay the social component on top of it, that's fine, but there needs to be a quantitative record, a durable quantitative record that's, um, you know, completely transparent and most importantly, follows you.

Think of it like a credibility wallet. So you sign up for Uber, Upwork, Fiverr. I'm thinking of any of these networks or platforms where reputation, uh, is critical. Um, first off, it's typically just a star system. Think of GitHub. It's still based on a star system, and let's say you do something or you annoy someone or you piss someone off and you get kicked out, your reputation doesn't travel with you.

It's tied to that platform. It's owned by that platform. What we're building is a decentralized credibility wallet that follows you. Now, much like a financial market, you and I can have different perspectives of the thing, the [00:14:00] value, EBITDA, future cash flows. I'm trying to think of oth- other financial, uh, lenses to lay on top of looking at an equity or, uh, a, a bond.

We can kind of choose our own adventure based on what's interesting or valuable to us in our analysis. Same thing here. We're providing a robust and deep intelligence environment, uh, information environment, and as well as the intelligence to, to scrutinize it, and then people can kind of choose what they'd like and what they'd like to prioritize.

So quantitative all the way to the floor, fully auditable all the way to the headwaters, to the genesis, and most importantly for the individual, it travels with them 

Mehmet: Then one of the point that just came to my mind now, so sometimes, you know, and we see this in organizations a lot, and this is why, you know, we see people leave sometime because they had ideas and, you know, they wanted to, uh, to do something, to change something in different way.

And then, [00:15:00] you know, these ideas, they get buried because, you know, no one gave attention to them, and then you see someone went to another place. And the reason I ask you this because you just mentioned something about, you know, the, the, the, the, you know, uh, this knowledge and- The wisdom of, of the person, so, you know, this wisdom.

So, so if... And it's not related to AI, right? So, so me as a, as a person, maybe I've seen the situation that I'm dealing with hundreds of times and, you know, probably I know how to do this, you know, brainstorming to find solution for the problem that the company is facing. Now, how I can, you know, quantify this, or how I can, you know, put, put a value on this and put it in the, in the production market so to I make sure that this wisdom of this person...

And, you know, resume, again, you know, and, and experience and maybe you, you wrote a lot of things, it doesn't, you know, extract this. [00:16:00] So this human knowledge, how, how we can also make it part of, of, uh, you know, the, the formula here? 

Dan: Yeah. So human knowledge is fundamentally accretive, right? It builds on itself.

No one is born into the world a fully formed being, right? Uh, and, and that's, I'm talking emotional, I'm ta- Same thing with, with, with your knowledge. It's always iterative. It builds on itself. And what we've done is we're trying to get people comfortable with the fact that when you come to Quadron and your version one of your lenses are not perfect.

Version 20 won't be perfect. But you will see how they grow and mature over time. Now, the great thing that I think that we've been focusing on is that there are two realms to most professional lives and personal lives, and that is personal and professional. Um, we've seen this episode before. This is GitHub.

This is Slack. You have things that you care about professionally and personally. Sometimes they overlap. Sometimes they don't. And importantly, there are implications on [00:17:00] what you've developed where. So if you work in a professional realm, there are encumbrances on the artifacts that are probably largely owned by the organization.

But your expertise is not, and that expertise needs to be utilizable by that organization and by yourself. So think about your life. It's very much a, a sequential journey. What we want to have is an evolving expertise portfolio of tools, uh, think of them that way, that can be leveraged by you, by your employers, and by others if you so choose.

Um, and by allowing other individuals to use them for their own benefit and organizations to continue to use them to make sense of the, the artifacts that you've generated for them, you are building a more sophisticated and deeper tapestry of information about yourself. So your expertise is always approximated.

It will evolve. It will be- get better with time. And the more you open up to the world and you allow organizations, [00:18:00] individuals to collaborate with you, the w- the more round, well-rounded your digital encoded experience of, of, of expertise becomes as well. 

Mehmet: Then how do we put a, I'm not sure if the, it's the right word, a, a, a price tag on this, right?

So, um, in traditional ways, you know, and if I want to talk about blockchain, so, you know, like the value, it's like, um, supply and demand and these kinds of things. Like if, if I have a knowledge, so people would say, "Okay, this is the range that this expertise would, would be, you know, per hour," or something like this.

So if you want to turn judgment as an economic asset, how do we measure it without, you know, make- reducing, I would say, everything to just a scoring or something similar? 

Dan: Yeah. Well, Mehmet, uh, first thing I have to say, I have to preface everything that comes out of my head, uh, in the next 30 seconds. I, like I, I don't have, uh, the silver bullet.

I don't have the answer. I think I've been thinking about this longer than [00:19:00] most in the proper, in the, in, with the proper framework. Um, but these are early days, and I have a couple ideas, and we have a couple opinions that we've, we've developed, and it's that you can monetize in a number of ways that look very similar to the world today, and some that are totally new and novel.

Um, think about a consultant. A consultant trades effort for money, right? Effort for money. If you have done it for longer, you have more credibility, probably through word of mouth or a good website, but you're really doing effort for money. We can encode that and make that scalable, so an individual can, for example, uh, allow an individual to utilize their lenses.

We call it streaming insight. Uh, for, a- and allow individuals to tap in via directly and manually by a human being or via an agentic layer. Uh, in addition, you on the other side get to set the price for your, your lenses. Uh, you say, "This one has quite a deep background. It's quite [00:20:00] useful. I can monetize it a la carte directly," and it's just what a consultant does now in the encoded digital realm.

Alternatively, you can collaborate with individuals, create bounties, allow, uh, create signals in a digital marketplace for individuals to be attracted, uh, to what you're working on, and you create basically a reward system to work with me and work on this, and you get something. This is where a, a, a token, like a, a cryptocurrency token becomes quite valuable because, you know, the signal in fiat could never be encapsulated and ensconced like it can be in a digital token.

So that's something that already exists, bounties and rewards programs, uh, using that in the digital realm. That already exists. So we've gone from replicating and making scalable the consultant sphere. We've now spoken about how you can attract individuals to work in a certain way, very similar to what happens in Web3.

Um, the things that I'm most interested in are the last two Over the course of a career, you have this kind of [00:21:00] monetary trail of when your lenses have been utilized. After, say, 15, 20 years of doing this, you've created a passive annuity structure. You've actually created a quasi-UBI, universal basic income, for yourself based on your work.

These passive annuities pay because people are using your tools, and you're being rewarded in almost like a royalty for where, uh, the, the, the output of, of your, your insight. Uh, I think that's very much on the table, and I think if you think about how UBI gets implemented, it probably looks something like that, payment trails and being rewarded for doing certain things.

And then the last one I think is, uh, I think it's really novel, and I'm, I'm pretty excited about it, and this is the one where I'm most confident that it's coming and least confident what it looks like, and that is truly investing in yourself. Now, I have a, uh, I have a, a thesis that markets will unbundle because the information environment becomes, uh, frankly, uh, the volume and the speed at which it happens, uh, is going to beyond, go beyond our ability to analyze [00:22:00] it as a human being.

Um, and this looks a lot like media in the last 30 years. In the United States, 1990s, you had this monoculture thanks to ABC, CBS, NBC, right? You went to a place, you got your media, you watched the news. That was the end of it. The internet allowed individuals... Well, first off, it increased the pace and volume of information, and then because of that, individuals started self-selecting into information silos.

And, um, the in- information monoculture and monoculture really started to unbundle. And we started to self-select the stuff we wanted to consume, and it realized probably its truest form in Reddit, a network of communities with individuals as the nodes across a vast number of communities. I think- And especially because the CFTC and the SEC, the regulatory agencies are being, uh, are playing nicely.

I think that's gonna happen for markets. That's the point. That when markets unbundle and they're driven by machines that are reliant on our very limited resource called our, our attention, what does that look like? So when [00:23:00] markets unbundle and we need to use agents to sift through all of the noise, what does that look like?

It looks like an information economy that we self-se- we self-select into. So a network of markets with us at the intersection of them. We get to identify the things that are valuable. We get to, uh, verify them ourselves, and we totally disintermediate the notion of a middlema- uh, a market maker or a middleman.

And that is what I'm very interested in. That's where my heart is, because it really gives humans full agency on their own value. They get to participate where they get to identify and assign value as they'd like, and alternatively, they cannot. They can pull back. Um, last time I checked, I can't pull a- an equity off the New York Stock Exchange, tell Palantir that I no longer want to invest in them, tell General Motors that I don't wanna play nicely.

I just don't invest in them, and they still persist. If I want my, my assets to no longer be in the market, that's totally my own choice. Giving individuals human agents, uh, full agency, that is the real opportunities I see it, and who knows [00:24:00] where that goes. 

Mehmet: Yeah. We- uh, time, time will, will, will unveil to us.

Now, you know, f- there is also, like, growing conversation, and this is again, based on, you know, what we do, our ideas, the information, the knowledge, all what we, we just discussed. We even, like, sometimes we generate IPs as well, right? So, um- Now, with the rise of the other part, or let's say the dark side of, of the AI, like the deepfakes and, you know, the...

Actually, sometimes it's not like dark, but, you know, w- you can do bad things with it like, um, your digital twin, right? So, so you can just have a similar synthetic identity of yourself. So do you think, like, people will have difficulties in, you know, establishing this trust and, uh, w- how you define maybe the, the infrastructure problem, how, how this [00:25:00] will shape the infrastructure problem maybe for, for the next era that would be a- ahead of us?

I don't know how long that would be. This is why I'm not giving you a timeframe for that. 

Dan: Yeah, yeah, yeah, yeah. The, the, so deepfakes, the visuals, like putting faces on, on bodies, can't touch that. Not a, not my, not my forte. Um, but I will say after I left my last role last January, January 2025 to now, there's a couple of things I've learned, uh, and uncovered, and one of them is that verification in the future will be a byproduct of human ambition.

Um, and what does that mean? Yeah. It means that organizations need information, the artifacts, as well as where it came from verified. Human beings won't do that unless they're incentivized because it means structuring information in a certain way, exposing it in a certain way. Um, hard effort. Good, you know, good friction in a way is the way I would describe that.

Um, to do that, the individual needs [00:26:00] to be incentivized and rewarded. So human am- and this is kind of like the programmable incentives. We're getting back to that To be a decent, uh, uh, credible individual in the Quadron ecosystem, you have to expose your information in a certain way. So at least in the, uh, the, the, the, uh, professional context, what we're doing is we're saying this isn't a technological problem that we resolve with yet another widget or another technological layer.

This isn't just a philosophical or a psychological problem where you tell people additional information, you educate them, and things get better. It's a blend of the two, and this is what programmable-- you know, programming the incentives is so critical. If you verify your information and structure it in such that you get rewarded, that, uh, that, that means that you, as an ambitious individual, receive a reward.

It's a giant, uh, flywheel. Verification infrastructure has to pull from both realms, the human realm as well as the [00:27:00] technology realm. Any other way is kinda not only defeating the purpose and the point, which is to make human beings, uh, feel rewarded and enriched and, and, and a part of the system, but it's also kinda undercutting the system because people just won't participate, you know?

And lack of participate-- l-lack of participation creates agentic drift, right? Uh, the only reason these models are so good is that over 20, 25 years of using Google, uh, we told the world what was and was not interesting to us. That needs to persist, but we need to be much more clear about the value of human beings participating.

Mehmet: Right. You mentioned a couple of minutes ago about, you know, the universal, uh, you know, uh, income, right? And now we're seeing more voices mentioning this than also as well. And the reason I brought this back, because one of the things that I'm trying to discuss with everyone, whether it's on the podcast or, like, uh, offline, is about AI agents, right?

[00:28:00] And AI agents that they can make decisions. Of course, the underneath layer is the model. We know this, right? So, uh, but, but these AI agents are becoming more powerful, and sometime I've seen people giving them full- Mm-hmm ... authorization to do some, some, some work, right? And sometimes even we saw like, uh, when, you know, OpenAI Claude came up, and then, you know, like there was a complete website, you know, similar to Facebook.

I think they call it the Claude Book. Mm-hmm. And, and, you know, like the, the agents start to talk to each other. So the, the thing is when, when, when the agent is doing the work, right? Um, and the agent is somehow-- I'm not sure if we can claim this today, but because the models are so good that they're not generating, you know, the content based on the way like today a ChatGPT or a Claude or Gemini generate things for you.

No. But actually generate pure new knowledge, right? So let's [00:29:00] assume, because it, it has autonomy, it can go do research, and now we're seeing like even- Talks about how we can get the agents into the physical world, right? So when, when you go to the physical world, you're gonna get the new information. So here Where do you see eventually, you know, the, the, the AI systems need, you know, more, I would say, attention?

Is it like the identity part, the reputation layers, or like, like a more human agents, you know, um, common scoring for, for them? And the reason I'm asking you, back to the why I mentioned universal income, because, you know, saying, okay, maybe humans will not be able-- will not be needed in, in the whole thing anymore, and agents are gonna go and, and work for us, and we're gonna be...

I don't know what we'll be doing. So I know it's kind of a, you know, utopia kind of question, very futuristic, but every sign today shows me that at some [00:30:00] stage we're gonna reach there. And back to what you're doing currently with Quadron, how that, you know, would look like today. And even like without reaching there, today if an agent is doing the work, you know, and, and we want to ch- can, can we actually give, um, you know, some rewards and, and, uh, reputation to agents today?

Can we, can we do that? 

Dan: Yeah. It's, it's a hard question. It's a, it's a, kinda-- it's a multi- multifaceted question. Yes. I'll try to respond to it as best I can. So you need a human being to set what good is always at the beginning. There's always a human being saying, "This is the thing that you're intending to do.

This is what good looks like. This is what the finish line looks like." Um, agents are very good, especially when they will eventually make the hop to the physical world, in getting to some type of outcome that's been predetermined or been defined. Um, I actually-- this is why I think that there will be more patents in the future than less, um, because set in a particular direction, [00:31:00] um, and in the medical space as well, uh, develop a novel protein, right, that does XYZ.

It'll be very good at doing that. Uh, i-i-empirically, it'll test, it'll test, it'll, uh, come to a, a, a, a finished conclusion. Whether something is protected is totally up to humans, but I think that is where agents will be very good at resolving something, and there will be a testable outcome, and good can be defined by, uh, by humans, and they make the decision to protect or not.

Where the real opportunity as I see it is where the intellectual property system has never reached, uh, ever, which is in the ineffable interstitial moments where taste and judgment, the little incremental steps where a human being is absolutely, uh, critical to say, "This way, not that. That way, not this."

That stuff that, you know, the invisible value that the economy runs on, that is the opportunity where human beings can really not [00:32:00] only, uh, be rewarded and recognized, but be compensated effectively. Um, so the world as it is will probably continue to happen. This is why I think we'll have more attorneys, we'll have more claims, we'll have more patents.

I think the trade secret law is going to Absolutely explode because right now trade secrets run like a cottage industry similar to like cap table structuring and management before Carta, right? It was just like pay an attorney a bunch of money and then like it was difficult to do, and now you just have a machine doing it, and that didn't mean that attorneys went away.

It means that attorneys are handling a bunch more companies because as, as clients. Same thing with trade secrets, same thing with intellectual property. The real opportunity is where we were never able to reach in the old economy, and that is where human beings are actually being, uh, compensated for telling agents right and wrong at those interstitial incremental moments, um, where, you know, I think real taste and judgment is absolutely critical on the path to a resolvable outcome or a defined end.

Dan, 

Mehmet: do you see that companies who [00:33:00] doesn't, um, any company that doesn't, you know, now start to think about, you know, all the things today would collapse in the future because they just kept optimizing for the status quo instead of, you know, all the things that we discussed today? Are we in a moment in another sense?

Are we into an internet moment where we saw like some businesses, you know, disappeared or when, when the, uh, mobile phone came, we saw the same thing again and, you know, now with the AI. Uh, do you see this as part of what might cause some companies to, to be wiped out if they don't give attention to? 

Dan: Yeah, that's a great question.

I think this moment is for individuals if we do it right. This-- like there's so many doom and gloom out there about AI taking jobs. Complexity always breeds complexity, which means that there's always going to be opportunity. I think this opportunity is again going [00:34:00] to that invisible value that the economy runs on, not only revealing it, but structuring it, making it a valuable, and making it monetizable.

That is a human opportunity, an individual human opportunity. Organizations that don't understand and appreciate how humans operate, human psychology, how you incentivize individuals, how you capture that information, and how you make it redeployable will be left in the dust because companies, the companies to come are the companies that respect individuals, allow a-a-and reward them for structuring their judgment and exposing their judgment so that organization can utilize it.

This is very similar to open source versus closed source software development in the 1990s. Open source was laughed at. I was at Red Hat for a long time, so like, like first they laugh at you first and then you win. Um, I think that's- Right ... absolutely going to apply here as well. The organizations that view encoded expertise as a true asset class and uti- and, and incentivize and utilize it in that way are the ones that are going to win.

Mehmet: Dan, do you [00:35:00] see with what you're doing at Quadron today as a A, a try to define a category? Because honestly, you know, when, when I research, I didn't see much. So is Quadron gonna be defining this category, and w- where we can position this category in the bigger picture of, of, uh, you know, the whole AI thing that's happening?

Dan: Yeah, I'm a student of history. I, I really am a history nerd. Um, and I view us as category defining is a good way of saying. I say it's the preconditions as well as the catalyst. Imagine if Uber came up with the geo-locating device that was the iPhone, and then developed Uber on top of it, right? We're doing both, um, because I think we're- I think the marriage of the technological as well as the philosophical psychological, uh, is necessary for this moment.

And rather than waiting for somebody to create the, uh, market mechanisms, uh, a- as well, and then, like, thinking about the [00:36:00] assets, we're creating the market mechanisms and saying skills.md, like, like, the, the skills are a V1, let's just go ahead and do both, right? Let's reward individuals. Let's celebrate individuals.

Let's encode expertise. Let's not stop at software developers or somebody that already kind of is in the tech space. Let's find the plumbers, the, uh, the, the, the... I'm thinking of, like, the most ridiculous ones I can. Um, healthcare, healthcare professionals, nutritional coaches. Let's go for everyone because everyone's expertise is going to be valuable, and here's the deep opportunity.

Expertise that has been tested across different industry segments, brownfield expertise, like, like the, the, the, uh, adjacencies. That is where true novel insight and true value is going to be, to, going to come. So yeah, we're category defining, um, and I think that, uh, you have to be to capture the real opportunity, which isn't, uh, Uber for this or AI for accounting.

It's saying the intersection of AI and blockchains [00:37:00] create, unlocks totally new value that was previously inaccessible. 

Mehmet: And you're providing what I can say it's the building blocks, you know- Yeah ... that on top of it you can just hook a lot of things because just, you know, the idea of, uh, you know, the skills MD, you know, for people- Yeah

who doesn't know, it's like the markdown for, you know, if you're using s- ChatGPT or any of these tools, usually they have this, so it has the skills. And, you know, I became very obsessed with skills recently actually. The reason is, you know, it's, it's exactly an imitation of the way how we humans we think and just you try to put it into the machine, and then the machine will learn from you, and then it tries to, to do it the same way, which is the value proposition to what you said, Dan, is like, whatever my profession is, and you don't have to, your point, to be a coder, but you've seen, for example, how certain stuff is done, how you behave in certain conditions, how you do this, how you do that, and just you try to documented it in a way, right?

And then [00:38:00] it becomes useful for, for other people. So really it's like, uh, something where you can build a lot of things on top of it, like marketplace comes on top of mind also as well and, and so on. As we're coming close to an end, Dan, anything which maybe I should have asked you and I didn't, maybe you want to share something and of course where people can know more and, and get in touch?

Dan: Yeah. Um, no, you've been fairly exhaustive , so I appreciate that. I will say, I'll leave you with this. Um, I, I'm, I'm more confident, uh, in this statement than, than most, and that is verification is going to be a byp- byproduct of human ambition. And much like time in the market beats timing the market, getting started sooner will create more value.

So encoding your expertise and getting on the journey of evolving and iterating on that and testing it is only going to benefit everyone. Um, so now more than ever, this is an opportunity for humans, not an opportunity to feel insecure if we do it right. Um, where we are at [00:39:00] is we have our institutional product.

Um, we are launching our beta, uh, for the consumer product, the, the real opportunity as I see it, and that can be found at Quadron.tech. And we have our wait list. We're releasing it to limited individuals. Um, I really wanna hear what you're expert in and what you think you can do that others can't, and let's have a conversation.

Um, feel free to reach out to me at pratl.me, P-R-A-T-L.me, and my email's there. All my, my, my socials are there, and I'd really love to have one-to-one conversations and learn more about what makes you unique and how we can scale 

Mehmet: you. Great. I will make sure that I will put the link in, in the show notes so people can find it easily.

Dan, I thank you, you know, really, really, uh, so much for the time today. It's early for you at the time of this recording, so thank you for making it, and I know how busy it can get, you, you know, especially when you are a founder and you have this great mission, uh, [00:40:00] behind you, so I appreciate the time. And this is how I end my episodes.

This is for my audience. If you just discovered us by luck, thank you for passing by. I hope you enjoyed. If you did so, give me a small favor. Subscribe and share it with as many people as you can. And if you are one of the people who keeps coming again and again, thank you very much for your support, for your feedback, for your questions.

I read them all, and thank you for keeping the podcast rolling by appearing in Apple Top 200 podcast charts across multiple countries. I know I repeat myself every time, but this is not because of me. This is because of you, the audience, who comes, and they-- you, you just keep listening and sharing with other people, so really appreciate it.

And s- as I say, stay tuned for a new episode very soon. Thank you. Bye-bye.