Stephen: What if you took Web3 and combined it with the broken recruitment process? Well, we're going to find out today when we bring in Adam Zec and Joshua Sklut The CEO and chief people officer of MyStandard a new Web3 process for recruitment and talent acquisition. They talk deep about tokenomics, about how they're going to use their mistoken to facilitate engaged recruitment processes where both the candidate.

And the company are staking some of their crypto to actually find a job that suits both of them. We talk about what's wrong with the recruitment process, why LinkedIn has kind of sold us out when it comes to facilitating natural relationships on the platform. And we go deep into what they're seeing, which industries, which regions.

How are they using this technology to bring together both the recruiters, the hiring managers, as well as these desperate candidates that are looking for real jobs. We talked a little bit about ghost jobs and this phenomenon of fake jobs in this industry. I love these episodes. You guys know I light up when I talk about recruitment.

This will probably be one of the best episodes of 2025. I encourage you to think about using this company or at least investing in seeing what they're working on and spending a little bit of time and exploring this tool. Reach out if you like this podcast, I'm super excited.

Stephen: This is the around the coin podcast. You guys know I love talking about recruitment, especially when it's innovative in tech and today I have Adam Zec and Joshua Sklut chief people officer and the CEO and co-founders of MyStandard. Changing the way that we handle data ownership, but more importantly, doing it for the best use case when it comes to Web3, which is actually recruitment, which is what we're seeing a lot of now.

Gentlemen, welcome to the episode. Maybe just, Adam, just start us off. Give us a little bit of background. I know I'm going to dive deep into some of your questions and backgrounds a little, but Adam, just give us like the one minute elevator pitch of who you are and how you got here.

Adam: Yeah, so I was in talent acquisition for like 13 years or so mostly on the sales and consulting side. I actually didn't really use too many of the tools. I just consulted on like what to use. I was like the shoulder to cry on when a fortune 50, fortune 500 company had like a problem, call me and be like, well, here's the problem.

We got this thing going on, kind of triage it, figure out the solutions, figure out the problem, whether it be staff or solutions, did that for a long time, and I was encountering a problem, which had no solution. Which was how do we make it a more equitable hiring process so that like Recruiters and hiring managers weren't exposed to too much information on like the race ethnicity You know skin color name school that people went to because those things created bias in the recruiting process And I was trying to solve that problem at the same time as being a full time Crypto web3 investor and I heard about a solution called zero knowledge proofs on a on a conference, I was listening to a conference for chain link.

And it just kind of connected. It was like, what if we could use their knowledge proofs to prove to an organization. That a candidate is the right fit without exposing all that information until the candidate wants that information to be shown. And then we'll put an incentive structure in front of it.

So the candidates are incentivized to share their information with an employer, but not forced to. And that kind of created the initial idea of my standard. And then I was able to meet Josh, who enhanced the idea and brought the recruiter perspective of how to make the solution make, you know, make sense for recruiters to use it.

And then we said, let's, let's do this. And it turned into a project that we've been doing for four years now. So both of our experiences, you know, really played into making this company alive. And I got three kids young ones under the age of 11. So life is busy in the startup world and outside of the startup world.

But you know, we're very mission driven here. I have an awesome team and excited to talk today about what we're doing.

Stephen: That's awesome. And you know, the recruitment landscape for those kids is going to look significantly different. And it's funny, Josh mentioning that I think you mentioned like the way LinkedIn and a lot of these recruitment firms, it's almost like the, I think you said the tenderization of recruitment.

So I'd love to, you know, you've worked in tech recruitment since 2003. Talk to us about maybe the shifts and changes that you saw over the last 20 years of recruitment, because, you know, it looked a lot different than me at that age, just getting out of high school and college, the recruitment game, like I use, I remember taking my resume and knocking at doors at organizations and going up the elevator and dropping off my resume.

How has the landscape changed for you in the last two decades?

Joshua: Yeah, honestly, I wish it was like that again because it was a lot more of an honest process to be, to be transparent. Yeah, it's, it's, you know, it's, to your point on other podcasts, I've mentioned what I call the tenderization of LinkedIn. LinkedIn is just Tinder, but for resumes, right?

You're, there's a million reasons to create bias, your picture, your name, your school. Anything can be used against you. It's none of it's there to help you. And in the last 20 years, I've seen the market completely change from these social media sites like LinkedIn and, you know, indeed, et cetera, being a helper to being a giant hindrance and being a giant roadblock for everything that for everything recruiting supposed to be, I come from the old school and what we're trying to do is bring it back to the old school, which is, it should be about a relationship.

It should be about a one to one connection between you and a good recruiter. Good recruiters want to build relationships. It's not about the hire that they make today. It's about the hire they make in six months, 12 months, and 18 months from now, right? So with my standard to Adam's original point, how do we, how do we make a system where both recruiter and candidate are in a better position to really find a job, right?

Good recruiters job, put person in seat, whether it's for an outside client or an internal client. Hiring managers. You know, and you know, this is well, hiring managers don't care where you found the person, right? They just want the most qualified candidate that's going to do the job. Well, that's our whole thesis is let's make it simple for both sides to have a more equitable situation without bias.

So that they can get the best job possible and the experience for them is an ownership experience, not only of their data, but of the relationship itself. So I think the future of recruiting, it's going to come back to that because we've drifted so far away from that over the last 20 years that it's, it's basically unrecognizable right now.

Stephen: And what made you decide in the middle of the pandemic to start this mission? You know, is, was it like, you know, this, that the landscape, Hey, a lot of things are shifting now, middle of pandemic, nobody's going in person for interviews. Or was it kind of like looking back at some of the, you know, I would say the missteps with our data when it comes to meta and other, you know, frankly, everyone that has our data and the credit bureaus.

Was it more on the data ownership side, or was it like, Hey, we're moving to a more remote world. We need a better process now. Even if, you know, companies start going back in person, we can see how much the process is broken now that nobody's going in the office and everything's being done via the online.

Adam: I don't think the pandemic really like shaped our decision to start the company. Like that wasn't like what we talked about at the time. I think what we talked about was you kind of originally, what I, what I talked about when my intro is like, let's solve this problem. And then as we started solving that problem, we realized like, well, we're solving a lot of problems at the same time here and then the, the, the company kind of, structure.

The mission kind of became a little more complex. We realized the amount of data ownership abuse there was expanded way outside of just talent acquisition, which is why our roadmap consists of use cases that move outside of just talent we're just onboarding the whole company through talent acquisition as a way to look at it.

And you know, the, the, the society speaking, people are starting to realize their data is being abused. And I think what you mentioned with like Facebook and Brexit was the first time that people kind of woke up to the abuse of these middlemen that they could just do whatever they want with your data, sell to whoever they want.

They're not very. Careful with it. As we've seen with a lot of the hacks and the leaks that have gone on. I think Equifax, I think it was Equifax had a leak right with our social security numbers. So centralized databases have centralized risks. And I think you know, centralizing our data infrastructure allows us to just kind of mitigate just like the inherent security of the blockchain allows us to mitigate a lot of those risks.

Stephen: And I think, you know, the Echofacts was bad, you know, people's credit scores and, you know, personal data. I think the Ashley Madison was probably worse for a lot of people were like, hey, nothing's in..

Adam: That's a good one too. I never, I never bring that one up when we do pitches, but yeah, that would be a good one too.

Stephen: That's the one that I think impacted more people's lives than their, than their 550 credit score because they didn't pay their Home Depot credit card.

Adam: I like that a lot, actually, maybe I'll bring that one up. But yeah, that's so I think, you know, we're, we're, the timing is right for us to put the solution to the market.

There's some education needed here, but it's not as heavy of a lift as it would have been like five years ago or 10 years ago regarding like why you should want to own.

Stephen: Let me ask you both. I think this is a great question. I look at data ownership the same way I look at privacy, right? People say they care about privacy. And my favorite is like Uh, analogy is, but you know, to get 10 percent on bed, bath and beyond, they're willing to give up all their information online.

So do people really care about that ownership? Or it's like, you have to educate them. Like what's the worst case scenario. Okay. Facebook, you know, sold my dad and made billions, but I still connected with my friend from high school. So, you know, I, I'm not really, you know, I'm not, I think there's a lot of outcry at the time that incident happens, but I don't see people are like staying up at night, like, Oh my God,  I can't believed that Instagram has my information. Talk to me about like where you're seeing the biggest impact and why that educate us today about why that ownership and give us some of those scary horror stories of what's going to happen in the future if we don't change the way that, you know, our shift perspective about that ownership.

Joshua: I think this, both of us can answer this question. I'll take on one section of it. I think the reality of the situation is, is that people have been so programmed to believe that they're giving their data away for free as normal. And once we cross the Rubicon and people start to realize that that data has value and that they're going to actually get to monetize it for themselves, as opposed to for Mark Zuckerberg or for the owners of Twitter or for LinkedIn, and they get to monetize that data, that's when the power shifts.

And that's the biggest hurdle to overcome. So I think from, from our perspective, we've always seen the ownership premise being a key catalyst that, yeah, people are like, I don't care because they don't understand that it actually has value. And the very first time somebody gets to monetize that data and gets money for it.

They're never going back. That's the reality of the situation. Once where they've crossed and said, Hey, somebody is willing to pay me for this. Yep. They're never giving it away again for Frey.

Adam: Yeah. I agree with all of the things Josh just said. And also with the rise of AI, kind of like taking people's data and doing more things with our data. You know, LinkedIn has a default opt in for you to share your data on LinkedIn with AI. LinkedIn's generative AI platform. Like, that's not okay.

And people are going to see their data being exposed in more and more ways they didn't ever permission. And I think the desire for them to take control of this and pull it back in, rein it in a little bit, is going to increase as we go.

Stephen: It's funny you talk about AI, I had to use AI yesterday because I couldn't believe some of the stats I was hearing about ghost jobs and fake jobs in the market. I'm like, there's no way this is true. Like, you know, the internet lies, Google's bad, but AI started kicking back some, you know, percentages of. 70, 65 percent of jobs out there are ghost jobs and fake jobs as naive as I was and dealing with so many companies that we're hiring. I figured, you know, it's not so much like purposeful. It's like, Hey, they just don't really know what they want. They have these big aspirations to get everything for, you know, 100, 000 when they want a top C level that wants to get their hands dirty.

But now I'm realizing like this is all part of a game to whether it's gained traction on their website for investors. Whether it's just the gathered data that they're using as part of, you know, their solution and tool.

Adam: the algos so they point more people their direction. Because if you see like this company is always posting for customer service jobs, the algos are going to kind of point customer service people a little bit more toward those people, even if there's not a job that actually is waiting for them on the other side of that job.

So it's, it's a whole, that's kind of like one of the things we're doing is to put. Skin in the game, right? For candidate to sorry for company to put up a job or ask people for the data. They gotta buy some tokens. They gotta use them. They gotta ask those people for their data. Like those are those are in play, right?

They can't just throw them out. And on the candidate side, if candidates want to apply to jobs, they're gonna have to have tokens too. And they're gonna have to have some skin in the game that I actually am serious about applying this job because I'm putting some collateral in place. So having some You know, some steak is going to weed out all that spam is is our pri is our thesis.

Joshua: Yeah. you know, can you continue on with that? Like with LinkedIn, LinkedIn is a subscription model, right? So we all know that the only object of LinkedIn's game is to get you to re up every single year. Right. So they're not going to do anything to help anybody. LinkedIn doesn't care how many. If you're a company, LinkedIn doesn't care if you hire one person or a thousand people, it's not their, their business model, right?

They're basically just giving you access to a database. They're providing you no other tools as a recruiter. You're still having to do all of that work, you know, to your point about all the statistics. I don't know if you looked up how many profiles on LinkedIn or FIC, I think it's like 16 percent or something like that, or just not even real.

So both sides of the equation are losing in the current structure. Right? If a company really is serious about hiring someone, you know it and they treat the situation completely differently than just putting up a random job on linked in or reposting a job after they've had hundreds and hundreds of applicants, right?

It's just an exercise in futility. And you know very well if you're applying to a job and that job has 9000 applicants, you're not getting that job. You're not getting an interview for that job. No one's going to contact you. And maybe in three months, you'll get an email that says, thank you for applying, but we've passed on you, right?

That is not an effective way to run a business and it's not an effective way to, to, to hire people. So to Adam's point with our structure, if both sides have skin in the game, right? You're not going to get a reach out from a company that's offering to pay you tokens for your resume. Unless that job is real, right?

Because now they've got money in the game and they're not going to pay for a resume unless they genuinely want to hire for that role. So with our structure, you instantaneously know that that job is real just based on the incentive structure that's set up. There's no district. There's no value proposition for a company X to send you a money unless they really want to hire somebody.

Stephen: I love that. And I think it's funny that you're kind of using Web3 which is notable for, you know, removing friction and seamless payments and seamless transactions. You're adding friction on the front part of the hiring purpose on the hiring process, which is what most companies aren't doing. Like LinkedIn is making it so easy to apply and I'm not knocking LinkedIn, but like from a hiring and recruitment standpoint, all of the companies, indeed, everyone's making it so easy to apply. They're putting the friction on now the company that once they get all the applications, they now have to siphon it or use AI to get the best candidates. You're putting the friction on the beginning, which is like, yes, if you're dating, I don't want to just swipe, right?

I want to go meet somebody. The person that's going to meet me for a coffee makes more sense than the person just swiped right. And sends me a, you know, a copy and paste message. That, you know, they won't even put my first name. And I think that's what you're introducing is, can we add the friction where it matters, which is like getting the right people.

I'd rather have 30 people ready to apply for a job and have skin in the game than have 3, 000 people when really and truly it's only 30 people that are even eligible for that job in the first place.

Adam: You absolutely nailed it.

Joshua: you, can you, have you ever heard of the, the, the sales structure two, not three? Do you know how that works? So I'll break it down. So basically the whole object here is never go beyond three choices. Once you have too many choices, once you're looking at a cheesecake factory menu, you can't make a decision.

Right? Like you go to Cheesecake Factory, there's 75 pages of crap you can eat. How do you know what's good and what's not? But if you go to a restaurant that has two or three dishes that are their signature dishes, you know what you're getting, you know it's going to be good, and you know how to order.

Right? So you always want to be able to take things away as opposed to add more. To your point, adding an Easy Apply button does not make Have anyone ever gotten a job clicking that Easy Apply button?

Stephen: no,

Joshua: never, never, never. All it's doing is taking away friction from a, from a process. That's already too much.

No recruiter is looking at 5, 000 resumes. This is why AI tools, like you said, come in that basically disqualify people out of hand. That's not helping either. There's too much noise, right? So if you are, if you are incented and you have stake on the process, you're going to treat it differently. And you're going to get a better result.

Stephen: what's funny about that cheesecake analogy is that most likely you're gonna go with only two to three things Anyway that

Joshua: going to get a hamburger.

Stephen: there's because there's so much you're like, hey, I don't want to try just anything I'm gonna stick with what I know and most likely get the chicken tenders and fries because you know, that's that's probably sick

Joshua: not going to order the shrimp fra diavolo at, at cheesecake factory. Right. You're going to get a cheeseburger and you're going to be happy with it. So they could have had one page and that would have been.

Stephen: You talked a little bit about tokenization basically, you have a mistoken where people, when you say state, people are basically buying tokens in order to facilitate whether they want to either see a candidate or whether a candidate wants to apply for the job. How important was it to use the blockchain, Adam, and to use this tokenomics as part of your plan?

And what would happen if you didn't have the tokenomics? Without the tokenomics, is it basically going back to indeed where it's like basically a free for all of people applying and rejecting each other for jobs?

Adam: Yeah. Okay. So a couple of things there. Yeah, the mist token is I guess there's a lot of utility built into it. There's many layers that we could talk about it and maybe in another discussion or, but regarding specifically to the, how it works within talent acquisition. The token really needed to exist in order for us to have incentive structures in place for both ends of the spectrum.

So we are incentivizing candidates to respond quickly. And the faster they respond, the more they earn that kind of thing for employers. But we're also incentivizing employers to validate information on our people. When the company validates their information on a candidate, they also receive missed rewards, which equal additional candidate flow.

So by putting like the right incentives in front of each party. You know, we were able to like have a token that has utility for both ends and is kind of in a complicated mousetrap where it's sent from company to person, from person back to company, and the selling of the token is a possibility, but it isn't the only thing what we what we've seen in crypto is a lot of utility tokens end up just being sold.

And obviously there's the meme coin side, which is just like basically just something you hold and sell. There's not like a functional use for these things. So what we did is we spent a lot of time saying, well, how can these be used in the ecosystem outside of just them being sold? Being sold is just a part of it.

But it isn't the whole thing. So being able to do things like add them to a token sink where they're kind of held in a certain state. And in order for them to apply the job, they have to be there. Or for a company to have to buy them and use them in the platform, ask people for their data. Or if you want to host like an event or something, like you want to put something out there that anybody can apply to or, or, or join, you have to like stake tokens in order to do that.

Just kind of make sure that people are always like serious about what they're doing. But what's also nice about tokens and an incentive structure is we can also punish people. Right. If you make a fake profile and, you know, companies report you as somebody who's a bad actor on the site, we can remove you from it.

Now, all that like, like social, like collateral and all the things you put into it are all like lost because you decided to lie, cheat or steal on the platform. So it also can like, you know, incentives can encourage, but they can also punish. And that's essentially what tokens are. They're like a global incentivized, decentralized incentive structure.

And then by putting them in this like Web3 State with, if my standard decides one day, we don't want to do this anymore. We're gonna walk away from this project. Josh and I have had enough, like the platform when we get to the right state can actually still exist without us being involved. So that people don't lose all their value.

Like they, they, right now they have to trust us a little bit. It's not, you know, they're going from LinkedIn where it's a hundred percent trusted to like, now it's, we have to trust this company a little bit that they're going to build something properly. That's like trust minimized, but when we get to the trustless state.

Like this thing gets bigger and has its life of its own outside of like the company who built it.

Stephen: Talk, can you talk numbers? This is fascinating, by the way. Can you talk numbers? Like what, maybe just on average, I know it's hard, you know, based on the roles, like How much are people still like, how much would I get if I'm like, Hey, I'm looking for a C suite job. I want to share my data. Like obviously it's not just one company that's going to maybe send me tokens to have me like, how much would you think I would make on an average job for one person that's actively looking?

How much are we talking? Are we talking like 18? Which is still not bad. You know, if I'm applying for a job

Adam: I mean, we're giving it away for free right now, right? It's found money for the candidate. But yeah, the

Stephen: We're in a deficit. It's not free when you're spending all this time applying for jobs that don't actually exist. You're spending hours day even if you had the minimum wage job, you'd probably be making a lot more.

So, I think right now we're going in debt trying to look for these jobs.

Adam: No, I like that. I like that idea. And you know, in our MVP, it's flat price. You actually pay for as much data as you want to see from the person. So you actually pay more if the person that if you're asking for more data and the person can actually share some of it or all of it. The most a person can earn on the platform today is 23.

That's if like a full profile. So like your contact information, work place, preferences, your employment history, your skills and your education are all shared, asked for and shared. It's 23. For a value, but where it gets interesting is when we kind of open up the marketplace to like, people could set their own price or here's your price recommendations, given your skill sets, here's what you should be asking for.

But if you want to ask for less, you might get more job requests. You want to ask for more, you might get less job requests. So it, it kind of like allows the marketplace to start, you know, figuring itself out, but we'll provide data and analytics. So people kind of have an idea where their benchmark is, but there's a, there's a world where what you just said exists for like CEOs.

And you know, that's something Josh was doing, like executive recruiting, like that, that would change that world entirely. Right, Josh?

Joshua: Yeah, let me chime in on that. So this is where I get really excited because there's two extremes. Okay. Let's take the lower extreme. Let's say truck drivers, truck drivers are probably the most difficult job in the country to fill because there's a lot of turnover and there's really no way to find a truck driver.

When you think of hiring a truck driver, what do you think of? You're going to have this in your head. You're driving down the street and on the back of the truck is a little panel on the back of the truck says, if you'd like to work here. Give us a call at this phone number. So it's not an easy thing.

They're not truck drivers are not on LinkedIn. Okay. But truck drivers have a phone and truck drivers like to make moves based on the amount of, you know, whatever their criteria is. So for a truck driver to get their access to their commercial driver's license, maybe they get 2 or 3. That's fine. That's good money.

And it's something more to the earlier point than they've ever, you know, been given before, right? So they're going to be responsive. Now, let's go to the other side of the equation. Let's say you're a CFO at a fortune 500 company and you've turned off all your notifications on LinkedIn because you're tired of being reached out for every nonsensical thing. That's good, but you're also probably missing out on opportunities, right? Genuine opportunities. Let's say that person has a my standard profile and they get a notification on their phone and company X offers them a thousand dollars for access to their data. serious? Absolutely. Does that a game changer?

A hundred percent? Cause whoa, that's a lot of money and to nobody's going to spend a thousand dollars unless they're serious. Right? And if you're the company, do the math. I'm going to donate, I'm going to give 5, 000 to this project, right? And I'm going to get five relationships with five CFOs. They're all going to say yes.

Right. So you've developed five relationships. What's a typical retained search firm fee? Like a, like a corn fairy, a hundred thousand dollars, 200, 000, right? For that same thing. So instead you spent five grand to build five relationships. If any of them hit, you've, you've got to win, but picture the other four.

Now you can reach out to those people again and again and again, every time because they're always going to remember you. Hey, I'm Josh. I'm from E and

Stephen: Josh, thousand dollar Josh, yeah, like I got you saved in my, in my phone.

Joshua: correct. I'm now 1, 000 Josh forever. So they're going to tell their friends about me. They're going to talk to me. I'm always going to be able to connect with them because I've paid them such a significant amount of money.

I've, I've invested in that relationship, right? There's no incentive structure right now that's currently out there. That even comes close to that, and that's what we can potentially do here is every to Adam's point, every value proposition. There's sort of an there's sort of an algorithm that says, you know, software engineer, New York, 150 K.

Yeah, that's worth 25 grand, right? Or excuse me. That's where the software engineer 150 K. That's worth 25 at the extremes. On both sides, there's giant wins to be had and only with our structure. Can we, can that be done?

Stephen: Now, are you guys getting invited back to the recruitment conferences after this? Because it seems like this is a two fold, yes, you're improving the experience, but recruiters are looking at you like, Hey, I get 30%. You guys used to probably get 20 to 30 percent for your organizations. And now they're like, Hey, for that same 150, 000 job.

I don't like to do public mass. Well, I'm 30 percent you're looking at about 40, 45, 000 that you're spending. They're like, I'd rather gamble right now with like 10 applicants at a thousand dollars. And even if I don't come up with something, I can even still supplement because recruiters are only getting paid.

If they find somebody, I can still now supplement my job search or at least earmark those 10 people that I really wanted and use a recruiter. If they bring something to me. Are you like, where does, how are recruiters looking at what you're doing? Or are they like, Hey, I'm going to use your company to do exactly what I'm doing to help kind of lower, you know, the amount of applications for certain jobs.

Joshua: Yeah. I mean, I think it's a combination of things. I think as we start to, you know, tread into the market of who our customers are going to be, one of the obvious silos is going to be recruiting agencies, search firms, et cetera, because to your point, they're there for multiple reasons. They're there to build a database.

They're there to build a relationship. They're also there to fill jobs. So if they can have another arrow in their quiver of search. They're going to definitely utilize our services, right? And there's no reason why they wouldn't. You know, one of our larger clients that we are targeting right now that we have a relationship with is a large billion dollar consulting firm.

And you know, one of their divisions is who we're going to end up connecting with. It is for executive level hires, right? So their biggest challenge is the shortage of qualified talent. That's actually interesting. So they're looking at our, our structure is perfect for them because this is going to be an area where They normally won't get penetration.

These people aren't going to be responsive on LinkedIn. These people aren't just lying around looking for a job. And as a recruiting agency, you're always looking for what's called a passive searcher, right? Passive searchers, someone who's happy, you know, I put in air quotes, happy in their job, but always open to potential opportunity.

So we see that as a giant potential market for us is all of is search in general, because if you've got a qualified opportunity, they're very stingy in money that they're going to spend, but if it turns into a value by a valuable relationship for them, they're willing to, you know, make the investment.

Stephen: and I think one thing to mention is that what I've seen, especially in the crypto space where it's so niche, right? You don't want to be applying for a job with a certain recruiter. You know, recruiters talk to other recruiters. You don't want the, you know, to get back to your boss that you're looking for jobs.

I think this is one of the reasons why a lot of people don't like applying for some of these high level jobs. To to somebody's whispering at a conference. I like, Hey, you know, that person over there is looking it could get back to their employer. And I see that a lot with friends. Like, Hey, I'm not actively looking.

Don't give my information over to the person yet. Let me get some more details. I think this is what you're facilitating. I'll give my data once I get confirmation. Once I get a little bit information. How are they picking and choosing what data to give? You said a full profile item, like what's the most popular data?

Obviously, I'm assuming work experience you know, schools. But I, I think I remember Josh mentioned in another interview that that's some of the information that people are using, you know, to create biases as part of the recruitment process. So how are you working through giving the right data, but making sure that it's useful for the actual can or company.

Adam: This might maybe just talking a little bit about how it works might answer that question for you. So company just puts in what their dream candidate is. I'm looking for job developer, 18 years of experience, they work for IBM, they work for Johnson Johnson, they work for whoever, right? They have these skills, these supplemental skills, dream candidate.

And the system just says, here's how many of them there are. You know, how many of them do you want to court? So then they can say, alright, I want to see all five of them, you know, or I want to see just two out of the five. The second they send that data request out and they put a timeframe on it. Like, I want to see these people, like they have to get back to me in an hour, a day, a week, or a month.

So like, there's an urgency here. So let's say they say an hour, as soon as they hit search, all five of those people who are a fit are going to receive a data request. If they're only asking for two out of five, it'll say if they were too slow, like, Hey, this was already filled, come back faster. Never miss out next time.

Be quicker at answering your, your, your phone. Or if all five of them are open, then they have one hour to respond. And if they don't respond, we'll send them a notification when it's about to expire, you have an expiring, you know, job request or data request to my standard, like get to it now, or you're going to miss out, never miss out with my standard, you know, something like that.

We're trying to push them to getting back like a little urgency. Right. And so after they share their information, then the company gets to see things about them, but they don't get to know anything, actually, not a single thing, because there's a number of people on the platform. Who are fit for this job that you haven't already seen.

They're already in your back, in your, in your, in your bank of candidates, and they don't currently work for your company. So we take those people out of the equation. So people can't ask for their own employees for their information. So we take those people out. These are people you haven't talked to on my standard, haven't seen.

They're not your employees. How many of them do you want to see? So that's how it works. So after the candidate shares information, the employer gets to see everything. But we kind of kick that, right? The opportunity for bias downfield a little bit to after there's already an exchange of value. You know, the candidate company priority gave the person a call.

There's a blockchain record that these people interacted. There's a little bit more onus on the company to follow through with everyone they called. Because if I got my standard data request and you know, I'm a certain ethnicity, but I know the company never called me. And then I see that they filled that job with a, you know, a white guy, you know what I mean?

There could be like a moment where I'm like, well, why never, why did this company call me? And then we can maybe see patterns like it just keeps consistently happening. People start complaining and then you get, Hey, we all have these blockchain records that like this companies keep contacting people. But anytime that person is a, you know, a skin color, they don't call them.

You know, that like, there's a public record now that we can kind of put together. And you can piece it together really easy for, you know, whatever, like a class action, you know, whatever it might be. So like, at this point, companies really have to follow through with everyone they contact and give them a fair shot because, you know, they're all the same candidate.

They're all qualified in the same way. So like, let's give them a ring. So that's kind of how the system works. And it maybe kind of answers that question regarding like, you know, like, are the companies seeing too much or too little or how do they ask for the information? And then also like. You know, our goal here is to build this out so it's not just.

Like those four data blocks, it's going to create more robust data blocks more data that you can ask for on people like maybe testing scores and viability, but also there's a, there's some companies who've asked us, like, can you do like a, like a race ethnicity, like, you know, that type of data block.

So we can ask people like, Hey, are you, we don't need to know anything about you ahead of time, but if you want to disclose this to us, you could share us your profile because companies are starting to, you know, because of. You know, certain D. E. I. Initiatives and such. They're trying to, like, you know, give, you know, an extra shot to these.

So there's there's a way to play that and make it work so that people are still like everyone gets a fair shot. But if you want to share extra information, you can companies paying for it, right? They're paying to find out that information, and it's up to the person to say not or I don't want that to be part of the consideration.

So I don't want to share

Stephen: interesting. Josh, you were going to add something?

Joshua: Yeah. Think about what their problem with the order of operations is going to be right. They're going to go through the process. They're going to receive this person's information. They're going to have their contact information. They're going to see that they're qualified. The next thing they're going to do is probably go on their LinkedIn profile and cross reference right.

But it's the, the, instead of then saying out of hand, no, they now are going to just, they're using it to qualify to make sure to sort of prove that what they've got is accurate. They're not going to just get rid of it out of hand because they've paid for it. Because they've already made the investment of time and money, right?

So instead of LinkedIn becoming a Tinder, LinkedIn becomes the backup, right? Like, Oh, this person is real. They have a, they have a picture on, you know, and they're not going to just get rid of them out of hand. So we flipped the script on the entire process and created that sense of investment. So that now, you know, this person is legit and you have their contact information.

If you're a good recruiter. I know what I do next. I'm picking up my phone or I'm sending an email right away. Hey, you just accepted our, our, our transaction. You've just accepted our request. Are you open to an interview? When can I talk to you about this job? Unlike LinkedIn, where you never know when you're going to get a response, you'd get a response late in it's in real time, the gamification of it.

It's in real time. And they've accepted this request. You've now can start to build that relationship that you've been looking to build.

Stephen: It's funny, I was just listing a couple jobs I saw in the crypto space on LinkedIn. And I asked one of the recruiters, like, hey, I see this job application is closed. Like, are you still looking for the person? They're like, yeah, but it's expensive to post on LinkedIn. So we had to close down the applications.

Cause you're spending money and you're not really getting sometimes the candidates that you would like. Where are you seeing the majority of the jobs that like that pop up? Is it region based? Also yeah, region and maybe even like sector based industry. I'm assuming like it professionals, this seems like a really good place with them.

Highly competitive. You know, they really want to put their best foot forward, but they just don't want to get like these random people that are just like spamming every job that pops up on LinkedIn,

Adam: Yeah, we just launched in the basically November is when everything got launched. So, you know, we're still trying to feel out like what our marketplace shape is going to look like. But we're attacking it from a few different perspectives. So I, like Josh indicated earlier with truck drivers, like we're, we're actually going to do some like underserved jobs, underserved categories of people, like efforts to get them on the platform because there isn't really a tech forward solution for them to find jobs easily.

And then on the other end of the spectrum, the natural people who are going to find us are like. The, you know, like you said, like the tech people will find this like cutting edge blockchain solution, excited about that. Like they're going to be joining the platform. We did, we do see a lot of people who have told us they like the idea that they could stay anonymous until they choose not to be, but they can still kind of see what they're worth on the market.

So that kind of plays into something you mentioned earlier as well as like, you know, people being able to apply to like, like be open to changing jobs publicly or, but, but privately at the same time, like. Like if that's kind of what we're able to do here, like if you update your LinkedIn profile, everybody knows you're kind of like looking but you know, on us, it's all anonymous, right?

So you can say no 99 times in a row, but then like the perfect job hits you say yes, then. So we really are, you know, kind of able to support both the people who are like, not really interested in changing jobs, but curious. But also the people who do want to know what's available to them.

Stephen: And will the candidates see the actual job description? Like, how does that work? Like, I know the company only has certain visibility when they're sending out the request. What are the candidates see? Do they see the full spectrum or do they have to? Still like, you know, commit before they see all the information as well.

Adam: Yeah. They just have to a candidate is going to receive a job request directly to their phone and it will say, here's the company and here's the opportunity. That's all the candidates have available to them right now. So it's like set up a profile. It takes five to eight minutes. Forget about it and then we're going to start notifying you when you're a fit for stuff or when we're doing network testing rewards and you're getting like just some tokens for free just for being a part of the network.

So we're gonna be doing both those things over the next, you know, few months and as we build out, build up the network and get more employers on there. And then I would say in Q4 ish probably. Maybe Q3 is when we open up the marketplace for people to actually use the tokens to go and apply to jobs as well.

So like we're building this out progressively over time, but in what's currently available is like just setting your profile, forget it. You get some rewards. You're going to get some job requests. And you don't have to use the app. It's not a social media app. Just like wait for those notifications to come in, answer them, move on with your day.

Yeah.

Stephen: a lot of that, you know, applications, especially recruitment is trying to drive this social media feed, right? Like, it's not just like, Hey, here's a job. It's like, Hey, can you help this? But like, they try to add things into the platform where you're actually doing the opposite.

When you're trying to remove everything else and just focus solely on jobs. How do you monetize on something like that when you're not creating active engagement where advertisers can't come in and say, Hey, like, I see you have all this activity. Let me put a banner, a digital banner ad there and try to, you know, monetize off this.

How do you monetize if you don't mind me asking?

Adam: So LinkedIn aligned with their clients, right? With companies, like they give all the value, all the power, all the control, all the data for the companies. We did the flip, we flipped the script. So we aligned with our users. When our users make money, we make money. So when a company buys data from us, they're paying 28 for a full profile.

We send 22 and 50 cents to the candidate. We take 5 and 50 cents for our revenue. So when we create more earning opportunities for people, when we create more use cases for people as we get more companies on the platform and more data requests are going, like we make more money too. So we, it's like a, kind of a exponential revenue model that really does like make it so that people in company are aligned really well.

So that's how, that's our revenue model in itself right now. And there's some subscription ideas and other things that are, but, but that's the core of it is that. That piece of aligning with people.

Joshua: If you think about it, it's a, it's a, it's a 20 percent spiff, right? That we take on every transaction. So obviously we're incented to create as many transactions as possible. For the candidate, it's a win because this is found money. You know, they, they, they aren't going to begrudge us, you know, Oh, well, how come I didn't get a hundred percent?

Because this is money that they would have never seen previously. Company doesn't care. Cause their, their cost to them is the same. Right? So in a lot of ways, we're sort of like a credit card company being that that that middleman who is just taking a transaction fee. And, you know, it's it's easy enough to justify it because of the value proposition that both sides of the equation are getting.

Adam: Yeah, I mean, as long as we're putting out more and more opportunities for people to earn, they're not going to be upset at my standard takes a 20 percent cut or whatever percentage cut we end up taking, you know, to build this platform out for them.

Stephen: And for them, they don't care. It's not like, oh, they're getting a notification on things that don't apply to them. And I think that's the toughest part about people trying to build community, is how they have to engage that community to kind of keep up with their monetization, where they end up, you know, that's why you see so many communities fail, because nobody wants to invest the time, resources, where people are just there for a job anyway, so just give them the job, and then they'll be happy.

I'm curious, you know, yeah, the Winkleboss, Capital Invest, Ava Labs. Big, you know, tech, tech, traditional tech and crypto players. What made it a no brainer for them? Was it they're probably their own hiring process where they're like, Hey, if I can, if I can solve that, I'd rather invest in this to work for me versus trying to solve our own recruitment problems.

Adam: Yeah, I mean, it's different. It's definitely different per pitch. You know, everybody kind of looked at this from a different perspective. So we have some people who looked who invested in us like angels because they wanted us to create an equitable hiring market where the LGBTQ community wasn't alienated from jobs.

Like the way it kind of worked today, as I was explained, is kind of like, you know, you look at somebody's profile and if you look at their like Instagram, you see that they're replied, then you kind of like judge that person, right? And this, you don't get to do that. Like, you have to like pay that person for the data, right?

And like, go through all those steps before you find out the person's name or see their picture or anything like that. So, you know, we were able to make a more equitable hiring process, you know, through this platform and Gangel's like that. Winklevoss Capital is obviously heavy in Web 3. So for us creating like a use case for Web3 something that made Web3 more than just trading tokens and holding tokens, like is you know, it was what, what drew them in.

I remember on the pitch, I like to say, and I say this to a lot of Web3 people is everybody who's in Web3 and I've been like full time crypto for many years, it's like, you hear somebody who's like, I hope that whole thing's a Ponzi scheme, it's a scam. Well, I'm trying to make a solution here where the same person who says my, you know, crypt is a scam also says, yeah, I found a job on my standard though. Like they don't even know because we abstracted the whole process that they're a Web3 user. So like, we're just creating like the pipework and the software using all this stuff, but we're not leaning into it. I'm like, you'll never hear me say like, we're the Web3 for LinkedIn or anything like that. We're just my standard.

Yeah.

Stephen: probably not gain you much more investor.

Adam: So it just depends on which investor you're talking to. And then we have some investors coming from more of the web two space, but they have no exposure to Web3 But this makes sense to them. Like a lot of this stuff's really complex. The white papers are complex. They're hard to read. Like I have somebody who says they always put their white papers through chat GPT and says like, tell me what this company does.

Like, you don't need to do that. My standard, you read our white paper, you'll get it. You'll understand what we're coming from. The token isn't so complex. The ramifications are complex, but the token in itself and the tech isn't so complex that you're going to lose it. And be lost and like, not really sure what you're investing in, what you're interacting with.

So it really does appeal to different audiences for different reasons. It's

Stephen: the recruitment process, the industry is still so broken? You know, you see the odd recruiter trying to do it differently. Is the incentive so high that people just can't act in the best interest of one side or the other? Why is the

Adam: lack

Stephen: process 20 years AI? And it's, it's kind of like, you know, why is this still broken

Adam: Josh, tell me your experience at HR tech. Josh was at HR tech and it was like, what did you see? Like what innovations were you seeing?

Joshua: Nothing. Everything is, I mean, the, the, you know, it's all just basically trying to build a better mousetrap over and over and over again. I, if I'm really breaking it down to the actual problem from my perspective is the resume itself. The resume is very outdated, right? Like the whole concept of, of, of, of having to.

Make sure that you're Taylor making a product for whomever your audience is. That has literally nothing to do with your ability to do the job. That it's just, you know, a picture of a thing. Like I've seen conversations on LinkedIn where these people from LinkedIn come on and they're like. Now, remember, make sure your fonts on your resume are this exact type.

And like, that's, that's the, the old school. That's in my opinion, the, the, the, the heart of the matter, right? The process is broken from jump, right? I call recruiting the second oldest profession because it really is because the concept of getting a, getting a fee for making an introduction is as old as time.

Right. So if the incentive to your point, if the incentive structures are just so out of whack, right, where somebody is getting 20, 25, 30 percent for one person, that company is going to do everything in their power to make that happen. Right. They aren't going to care about the finding the right job for the right person.

They're just going to try to get that body in the seat. Okay. So if we have to really kind of figure out what the problem is, it's that the whole structures are, are incorrectly incentivized and with our structure, the incentives are accurate and clear. You're only going to pay for stuff that you need. You're only going to get to see candidates that match. Candidates are only going to apply if they're, if they're going to reply, if they're interested.

So we've, we've tried to, you know, this is a big lift, right? Because this, it's been done this way for forever. If we can get past that initial hump and get people into this process, there's no going back and they, and they'll always be users of our product for life. And they'll, and they'll actually have better options, opportunities presented to them.

Adam: Yeah, we,

Stephen: You guys are in the US, so you may remember this. I remember a Bar Rescue episode where, you know, the owners of the club We're paying the, you know, a person, the promoter to, you know, they get 20, which is the cover for the club for everyone that they brought in. And this is kind of like the recruitment, right?

If you're paying somebody to bring in anyone to the club to your job, they're going to bring in just about anybody off the street into that job to make sure they get their 20 bucks. So I think, you know, you have a very similar scenario if the incentive is just getting somebody in the door, then they're going to just pretty much get anyone in the door.

I'm curious though, like when you talk about this. You know, there's a, you know, interview, I think it was Adam, you talked a little bit about chain link which is a great Oracle amongst other things, infrastructure, interoperability, but you mentioned about like, you know, being able to basically take credentials, put them on the blockchain, which is not a new concept, but pretty much add them to your, my standard to kind of, you know, validate that this person went to the school that they went to.

I know back 10 years ago, like, you know, the big scam of fake colleges in India and all over the world, I shouldn't just say India, but all over the world. Yeah. Is that still a thing? Are people still worried about that when hiring? What are your thoughts?

yeah, I mean, we had it happen to us. We had a guy who's helping us do some work and. Said he was from Harvard, his LinkedIn profile said he was from Harvard, and then we found out he took a class, an online class about Harvard. Like, like that stuff happens. So that's why one of the next you know, great frontiers with MyStandard is to work with Chainlink using their functions app using their functions infrastructure.

Adam: We've already talked to them about this, and they're excited to start development with us. It will allow a university to essentially have a portal they log into. They can put in your MyStandard ID number, which you generate when you create a profile with us, or you can give them your email. If you want to give them their email, either one links back to your profile.

And they would put in your, you know, degrees, your transcripts, etc. They'd have signers at the university. So it's not just like nobody can, just one person can upload data. So there's no risk of fraud there. A chain link oracle system will actually ensure that data is correct, the right signers are there, send that data into your MyStandard profile, the user cannot edit it, and now we have a cryptographic immutable proof of your, you know, degree.

And then this this, this infrastructure that I'm, we're talking about can be used to repurpose for all sorts of things outside of just universities. But that's one, you know, that's one way that we can help universities never have to go and prove this information about themselves again. Likewise, if, you know, we're hanging out, I can prove to you like, yeah, I actually would.

To Bradley university, here's my proof. Or if you're trying to hire me, I can send you that proof. And it's as good as if you call the university themselves. So it saves the university a lot of time and effort too. So that is a big problem. That's why verified credentials are a huge thing. To your point, we've had a lot of blockchain solutions trying to tackle this in various ways.

We're not the first one to do that. I think we'll be the first one to actually tap into the direct source of the information. I do, I haven't heard anybody doing that the way we're doing it in that partnership with channeling, but also like we didn't start off trying to be an ID solution. We started off trying to be a marketplace.

And the reason is, is like, there's a use case there. So like, I'm, we're not, I guess we're not a solution hunting for a problem. We were a problem that found a solution. First, and I think that's the problem with a lot of those ideas, solutions that we're seeing in the marketplace today is they're still trying to figure out where's our product market fit, who's actually going to use this idea thing that we created.

Stephen: And it's also ad hoc, right? If your whole profile there and now this is a verified credential on your profile, it's one place where people are visiting you versus like all my information is on LinkedIn, but I have this like transaction hash that I'll give you to prove that I have this, you know, like companies don't want to go through all of those hoops.

They just want to go one place. And I, you know, LinkedIn

Adam: Yeah, one of the

Stephen: do this verify

Adam: about that is the idea that people could pre background check themselves and things

Stephen: Yeah, exactly.

Adam: send this information with my profile and now the company sees it all right off the bat. They know they're gonna hire me, they know I'm gonna pass their background check, they know I'm a good fit for their job.

Like, it's all packaged up real neatly. And instead of them waiting two or three weeks to run a background check after they already put through an interview process and then find out you failed it, they can find out that information on day one that like, I would pass the background check. And now that they can, like, take that candidate a little more seriously.

Make them a better offer or whatever they need to do to bring them in. And without worry that like, you know, all that time and effort was wasted. So it changes the way that recruiters think about data as well. It makes them value my standards, you know, upfront data ownership you know, platform or structure as well.

Stephen: How are you going to protect your users data? I think that's always the concern. You say it's not a full trustless system. So I think people, especially companies and candidates, you know, now that you have a lot more engaged community, it does make that data a lot more valuable to be quite honest. So how are you going to ensure privacy and ensure that, you know, you're the companies are exploiting users data because it is so rich and accurate.

Adam: Yeah, so the both the user and the company's data, I'm sorry, but the user's data when they're holding it is stored with a private key that only they have access to when they open the my standard app and log in that key is a lot. We don't have access to that key. I can never see it. I can never touch it.

We actually re architected the platform because we found out that at one point when a user shares information with a company, it kind of passes through my standards visibility just for a moment. Like, Technically speaking, if someone was in our server, they could see the data when it was being shared because we were kind of creating that sharing mechanism.

So we rearchitected so we can't even see user data. What's being shared directly from person to company without us ever having exposure to it. And when a company is holding on to user data, it's also stored to centrally. So it's not even on a centralized server after the company buys it. Now, after the user sells their information to a company, the company has access to that data forever.

We had considerations of like, maybe it only is there for a few days or weeks or months, or maybe they get updates on the data when it comes out, but we decided that, you know, the best way is to get a carbon copy of the data as it is today with the company. And then if they export it to their app and contracting systems and things like that, like we can't really control that.

We, we anticipate that a lot of companies are going to want to do that to follow up on candidates in a more structured way, but, you know, as far as like our platforms concern, like security is literally built into how this system was architected and

Stephen: I don't think it matters if they have your data. Like people are scraping your LinkedIn data all day anyway, and harvesting that information. So a company that paid for it, you know, especially if they're reaching out to you only when a job fits you. I don't think that's a, you know, that's much of a problem.

Is there any downside to this, especially maybe psychologically, like, Hey, you're only getting maybe one reach out a month and you're, you know, although some of the, you know, the BS recruitment practices are there, it does people keep people engaged at least, you know, for a moment they feel there's some kind of hope I know longterm that doesn't work out, but it does help people with their confidence knowing that there's all these potential opportunities, even if they are, you know, down the pipeline, maybe are fake or, you know, misrepresented.

What are your thoughts on that? Are you more supplementing the entire recruitment ecosystem with a more direct and accurate tool? Or like, do you think that people are like, Hey, I got one request in the last three months. What's going on? I'm a terrible candidate.

Joshua: I think it's probably a combination of both of those things, right? like there's always going to be incentive to make your profile better, right? Cause you want to appear in more searches, but by the same. But the same token, the reality of the marketplace is that every good recruiter probably has five or six different methodologies by which they go about finding candidates, right?

They, this is just another option for them. It's not just, you know, I have LinkedIn, I have this subscription, I use this search firm. If we can kind of penetrate that market, I always think if we can take. A small percentage of LinkedIn's spend for a company. If a company spends, you know, a hundred thousand dollars on, on LinkedIn licenses, and they give us 10 percent of that they're going to get a better outcome with that 10 grand with us than they would with LinkedIn.

That they're going to continue to use us. So. We're not going to take out LinkedIn. You know, again, they're, they're a billion people on LinkedIn and they, they have, you know, they've got the, they've got the market share, but if we can take a small percentage away from it and people get a better result, then our tool becomes valuable resource for them that they'll continue to use over and over and over again.

Adam: And I don't think candidates are going to think I'm a bad candidate if I'm not receiving requests. I think as our system gets smarter, we start to you know, encourage candidates to fill out the profile in new ways, you know, add in some new types of data to fill in some new data blocks. And then we're always going to be kind of like giving them rewards for being good users on the platform.

You've had a good profile. You haven't been flagged in the last three months as a bad profile. Here's some rewards. Like they're kind of always getting teased by the platform. The carrot's always there. That they should be doing more and sticking with this thing, regardless if they're getting a lot of data requests or not.

And then also when we start looking at our marketplace and saying, Hey, we have a lot of people on here who aren't receiving data requests who are bio, you know, chemists, like, then we start to go out to the marketplace and say, Hey, companies hire biochemists, like we got a supplier. They're waiting for you.

Like they're an eager audience. Like it'll be an easy sell to get new companies on the platform then.

Stephen: that's amazing. What happens with the missed token? Where do I cash out? So I got like, you know, I got 46 of missed tokens. A couple of people reached out to me. What do I cash out, you know, on the app? Do I have a credit that I can use to purchase things directly? Like, what's the infrastructure there when it comes to the

Adam: Yeah. I say, so in the MVP right now, as it stands, you're just collecting tokens. You know, if you're a little more savvy on the blockchain side, you could transfer those to another wallet and sell them if you need to. That's just like the moment. Where it's going next is the infrastructure has improved so much on the off ramping side.

So there's actually a company we've already talked to called BeamCash. There's a few others that are available if you didn't use BeamCash, but it's the idea that you can connect to a bank account through like Stripe. They'll take like a, you know, 3%, 4%, you know, cut, but then you just like connect your bank.

You have to KYC yourself. You'll, you know, catch a bank count and you can cash out directly there. So, you know, you'll be able to get value directly from your tokens pretty quickly if you'd like to. The next iteration after that is what I mentioned earlier, where you're going to be able to actually like.

Hey, I might want to actually find jobs or apply to jobs on this platform. So I'm going to keep some value in here. Maybe I stake my tokens to actually earn a little bit more. So we'll give a better, a little bit better interest rate than a bank will. So it's like, Hey, why take these things out and cash them out?

When I could just keep them platform and stake them and get like a, you know, five or 6 percent return yearly. And then while they're being staked, you can actually do some voting. So governance. On like some direction we go, some marketing spend, we do the color schemes we use for the month, the logo for the month, you know, fun things as well as like serious things will be available to each side of the marketplace independently adds another utility to the token.

And also like another options. And then, then if you don't want to sell it, like there's other things to do. But where this is going later is really exciting. Cause like, we're going to have a plug into a new use case which is like advertisers. So I'm a golfer, you know, I like golfing my whole life.

And if Callaway golf wants to send me a video. Of their latest driver, because they know that based off all the information, my profile and whatever information that we connect to also, you know, your bank account and spending history and things like that, like I'm the perfect person to watch this video on the new driver.

I watched the video. I get paid to watch the video. So I get paid from Calving Golf directly. For, for what, for interacting with them and they got, you know, my data was put to use, but now I can also buy the product. So people are going to want to keep tokens in their, in value in their app, because at some point I might get hit up by the right product that knows that I'm a fit for them and maybe they'll give me a deal.

Normally it's 700 for the driver, buy it on my standard right after interacting with the ad. 650. Okay. I saved 50 bucks. I got paid 10. Let me send those tokens back to Callaway Golf and buy this product right now. So there's just going to be so many different things to do with the tokens. Like selling is obviously part of it, but it's

Stephen: And it's like, you didn't have to do anything other than give up your data. And once you fill out that profile, it's not like you have to actively I'm assuming once you respond to a request, you're just pressing accept or some sort. And it's not like you have to keep on going to fill out your information, like when you're applying for a job at the bank, and you have to go in and they can't scrape your resumes.

Now you have to copy and paste your resume and it's all unformatted. Like that seems like a lot more work than just pressing accept and getting 23 and a qualified job opportunity. I'm assuming

Adam: Yeah, exactly.

Stephen: I love it. What are your thoughts right now about the current state of recruitment? Do you have any advice for people, whether they're going through the process with my standard, whether they're on LinkedIn, you know, your decades of recruitment experience?

What's one piece of advice you could give the candidate? Or the companies are looking to hire that could at least improve them. Up until this point, my center is running on all cylinders.

Joshua: I mean, again, I'm old school.

Adam: take the candidate side?

Joshua: Yeah. Yeah. I'm old school on this. I, I believe you should always formulate relationships, right? So find out if you have a relationship at that company, take advantage of that relationship, find out who's posting the job. Don't necessarily hit them up on LinkedIn, but I figured out a way to get their personal, you know, their pride, their professional email address and send them an email directly.

You know, if you've got a, if a company is posting up a job on LinkedIn, go on their website first before you go through the LinkedIn process, because the chances of you actually making that connection directly is higher from their website. And, you know, always, always, always default towards whatever the human direction is, right.

To find the person responsible. We have a person who was on our board of directors. And she basically said how many times she's made great hires from people reaching out to her directly instead of coming through that would have already been rejected by their, their ATS or been rejected by their recruiters. So again,

you can tell what our direction is, make those connections, make those relationships. Don't on LinkedIn to you a job because it's highly unlikely.

Adam: Yeah, for companies. I mean, if your company is watching this you know, get in touch with us. It's very simple. We'll get you set up. We can even sponsor your first few candidates. You're registered, ready to go. And if the platform you know, doesn't have the candidates you're looking for today, because we're still getting this thing going it might in three months, it might in six months.

Like you can always queue up, you can always try it out. We'll keep you informed. But the coolest thing is if you are a launch partner with us we'll advertise your openings. So we'll tell the world like, Hey, this company is looking for these people. We got a lot of eyes on the project. And it will also drive more people to the platform who are the types of people you want to hire.

So just let us know that, you know, you want to be engaged and we'll make it work.

Stephen: I love it. You, you're on the tech side a little as we end the conversation, you're on the tech side. What are like your super technical, your developers, what are things they're playing with on the weekends, whether it's like cool sports, whether it's like, you know, there's all these new treatments and medication and, you know, specialized mushrooms, tech gadgets.

Like what are people that you know, what are the nerds playing with on the weekend that we should look out for that everyone else is gonna be playing with you know, in the next 5 to 12 months.

Adam: You know, the the big thing that is creeping up is this AI agents thing. So, a lot of people are talking about. You know, automating their life through the use of agents. There's some potential things that MyStandard might be playing in that field too, but we're not gonna, it's too pie in the sky, a little too early for it, I'd say.

But if you're engaged with us and follow us, you might see more on that in the, in the future. But that's what I'm hearing a lot of my more techie people, my, my developers, like they're just, they're, they're able to take on more. I just talked to somebody, I don't know if this is true, but this is what he told me.

He said, he's got three jobs right now, all of which would be full time work in their own right. But because he's automated so much about the AI with AI agents and such he's able to actually do like, it's like, he feels like one work, like one. One job's worth of work, but for three jobs at the same time.

So that sort of thing is, it's like a new frontier, right? And the people who are figuring out that the techies who are really tinkering it, getting it to work their way are going to benefit in the early days. And then hopefully we can maybe help kind of make that more mainstream.

Stephen: I think that's probably a conversation for another day. But I had a friend that had three jobs with no AI and no automation during the pandemic. So I think we'll get to that side of the recruitment process another day. Josh, Adam, it was so great. Where can people find you? Are you focused? Are you on LinkedIn or are you focused more on the Twitter side?

Adam: no, no, I'm, I'm I would say, you know, we're, we're on both. I think I'm a little more vocal and use Twitter a little bit more than I do LinkedIn. Just because of the crypto side of it and crypto is like the base, best place for that. But for the business side and corporate side you know, more, more on the LinkedIn side if somebody is interested in, you know, kind of like joining, being a launch partner, they could email us at info at my stand info at myb.

io. Is the the best way to get in touch with us or just like messages and LinkedIn.

Stephen: Awesome. Josh, any last thoughts?

Joshua: Yeah, no. And joint. I mean, we have a telegram channel. We, you know, we have, you know, 80 plus thousand followers on, on X very active. I'm much more active on LinkedIn, I think than Adam is just because of my background because of the recruiting piece. So, I'm commenting and posting all the time. Feel free to add me. I always do a very good job of interacting with everybody who reaches out. So hit us up and you know, we can, we love talking about the product and we love we love our fans and we love our users. So feel free to download the app. That's a, that's the, the best thing you can possibly do.

Stephen: That's awesome. Thank you so much. I do encourage everyone to download this app and get started. I'm going to do so on the weekend. I want to, I want to dabble with, I want to see how many 23 I can make. But thank you so much for this conversation. Great conversation. Great combination of innovative innovation and not just kind of plugging AI into the already process and automating it, but actually doing something to solve the breaks in the process that we've already seen.

We really appreciate you joining the around the coin podcast.

Joshua: Thank you.

Adam: No, thanks for diving in with us. We appreciate it.