Firing Squad: Bryq's Markellos Diorinos


What's your favorite brick-related song? (She's a) "Brick House? "Another Brick in the Wall"? Maybe Ben Folds' simply titled "Brick"? Anyway, startup Bryq is hoping they'll be your new favorite "brick." Don't worry, we'll cover the name and URL - among lots of other things - on Firing Squad when CEO and co-founder Markellos Diorinos enters the pit to take on HR's most dangerous podcast. Diorinos says his company is "a unicorn-to-be." Oh, really? Well, we'll be the judge of that.


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INTRO (0s):

Like Shark Tank? Then you'll love Firing Squad! CHAD SOWASH & JOEL CHEESEMAN are here to put the recruiting industry's bravest, ballsiest, and baddest startups through the gauntlet to see if they got what it takes to make it out alive? Dig a fox hole and duck for cover kids the Chad and Cheese Podcast is taking it to a whole other level.


Joel (22s):

Oh yeah. You know how we do everybody? It's the Chad and Cheese podcast. Your favorite guilty pleasure. I'm your cohost Joel Cheeseman joined as always by my man on the right plane, shotgun, Chad Sowash and today we are happy to welcome Bryq to the show and Markellos Diorinos CEO. And co-founder,


Markellos (48s):

It's such a pleasure to be here, Chad and Cheese.


Joel (53s):

All right, Markellos. Hello. Welcome to firing squad. Before we get into the Q and A, and the judging, let's hear a little bit about you. What's the Twitter bio on Markellos


Markellos (1m 6s):

Thank you for the invitation. And I was in fact born, that is a stated fact, but I like to say that it was in the past millennium. So I won't go into any more details. I did study in Germany and there, I started computer science with my master's thesis in VR. A lot of times people ask me, Hey, how did you make the jump from VR to HR.


Joel (1m 32s):

I'm sorry. Did you say VR?


Chad (1m 34s):

Oh, he did.


Joel (1m 36s):

Oh my God. Markellos talking VR. That's just going to get me all excited.


Markellos (1m 42s):

That was so sick.


Joel (1m 46s):

Sorry. Continue with your walks on the beach and a poetry reading that you enjoy.


Markellos (1m 50s):

You know, I'm a big fan of George Michael.


Joel (1m 54s):

And who isn't? And who isn't? Sorry, I interrupted. You on with the Twitter bio. What else?


Markellos (1m 59s):

So I was saying I studied computer science and this was my first, you know, challenge. I am a, well, I guess self-professed great coder. I love coding. Still do the occasional thing, but I was never happy as a developer. So this was my first indication that sometimes, you know, your skills shouldn't match your occupation and the fact that I can and do code.


Joel (2m 23s):

I'm sorry. Markellos all this talk about code is making me bored. Chad, let's just jump to a what Markellos has won today.


Chad (2m 32s):

Well, Markellos, you will have two minutes to pitch Bryq. She's a brick house. At the end of two minutes, Joel, and I will hit you with rapid fire Q and A and if your answers are droning and you get boring, Joel's going to hit you with the crickets, you need to tighten up your game. At the end of Q and A, you will receive one of these ratings from the both of us. Number one, big applause. Come on, get up, come on, get up and get that Oscar baby. You're going to be a big hit.


Joel (3m 4s):

Hit. Just don't slap Chad.


Chad (3m 6s):

Golf clap. No awards here. You got lots of work to do. And the firing squad. Prepare for Will Smith tohit the stage because baby, this start-up deserves a slap. That's right. So that's firing squad. Are you ready Markellos?


Markellos (3m 25s):

Yes, I am.


Joel (3m 26s):

Your two minute pitch starts now.


Chad (3m 29s):

Let's do it.


Markellos (3m 30s):

You know how you have an ERP to manage your sales, a CRM to manage leads and I don't know, GA for performance marketing. So when you go into HR, what is the backbone with data for your talent? Nothing that's what, and this is where we come in. Bryq is an AI talent intelligence platform. Why? To allow you to make more effective data, support the talent management decisions. We provide a big data platform that gathers validated psychometrics gathered by our own chatbot driven assessment, as well as organizational performance data combined that with our machine learning and translates them into actionable insights.


Markellos (4m 13s):

So you're already wondering why would I care? Let's look at a few areas, talent acquisition, with AI generated ideal candidate profiles based on your job description, blind screening for skills and personality matching hiring is easier than ever before. Results? Customer can boost DE&I, by 119% and that always sounds made up, so this specifically refers the gender mix and increase their interview to hire ratio by over seven times. One of our customers went from one to 22, 7 to 20, and you can understand what that means. Talent development is when you help to choose individual career paths and then up-skill, and re-skill people based on strengths and weaknesses.


Markellos (4m 59s):

Data from our customers suggest that on average, 15% of their workforce has their potential to improve performance through coaching and L&D where they are right now. Talent matching AKA internal mobility. We have a customer who has a call center, huge one. We managed to reduce his churn by 30% in the first three months by helping move employees to the right team, because guess what? People are not fungible after allall. Talent insight is probably my favorite part and maybe the most esoteric one.


Joel (5m 35s):

All right, Markellos. Thank you. All right. Let's get to what I always like to cover first. The name Bryq sounds great, but it's spelled B R Y Q. I'll give you bonus points for at least going with the dot com and not being like goBryq.io or something. But talk to me about talking about the name. Is that a hindrance to sales? Like I'm Markellos with Bryq. Talk about the name. Why'd you go with Bryq misspelled?


Markellos (6m 4s):

The idea is that you build a company using great people and the foundational building block of companies is people. So, you know, we are providing bricks for companies and being the available domains and all we ended up with BRYQ because that's all that was available.


Joel (6m 22s):

It is a.com and it's only four characters. So I will get, I won't, I won't beat you up too much for that. So you guys raised a 1.2 million euros back in September of 2020. Good timing. What have you done with the money? Is there going to be a bigger raise in the future? Talk about that.


Markellos (6m 45s):

There's always the next raise and the reason why we will not raise it. We are about to close this current, this next round is always because there's so much demand out there and we just want to accelerate our growth. And there are so many customers that we need to make sure that we provide top tier support to.


Joel (7m 1s):

Can you tell us how much this new raise is going to be?


Markellos (7m 4s):

I can't disclose, but it's going to be, you know, a few million.


Joel (7m 10s):

Series A like?


Markellos (7m 11s):

Series A probably.


Joel (7m 12s):

Eight to 10 kind of thing. Okay. All right.


Chad (7m 16s):

Excellent. Okay. So we have four easy steps for Bryq, or at least that's what is on the website. First and foremost is the A1 job description predictor. So tell me about this a little bit.


Markellos (7m 29s):

So here's the challenge that our customers have, even when we started there, before we introduced the AI. You want to hire, I dunno, a project manager, or what does a project manager even do? They all look the same, are all going to do exactly the same tasks? Turns out that it can mean many different things. So we were putting the onus on the HR practitioner to figure out exactly what this person is supposed to do and how that translates into, you know, psychometrics, what kind of personality traits this person should exhibit. And HR practitioners are not psychologists. So what we're trying to do with our AI is essentially give you, my team's going to hate me for this, "psychologist in a box".


Markellos (8m 11s):

So this AI goes and reads your job description, compares it with tens of thousands of job descriptions and the Holland codes our main, our main theory that we use for career consulting and then says, look, based on the keywords and the things that you expect from this person, these are probably the traits that are most important. Setting the right goal is 90% of getting there.


Chad (8m 38s):

Where's your sweet spot with regard to types of positions? Are we talking about executive level? Are we talking about middle management? Are we talking about entry-level we talking about high volume, where is your sweet spot with regard to this product?


Markellos (8m 52s):

We have a very wide applicability. We go anywhere from frontline and hourly workers to senior management. Executive is always a challenge. It can never be described. And there are so many other things that play a role. Even though we have some executive recruiters using Bryq because they like the value and the like understanding people more so than matching them to a specific profile. So, you know, we do cover the full gamut.


Chad (9m 19s):

Okay. So when we're talking about job descriptions and we're trying to predict off of job descriptions, generally, that's just garbage data. And to be quite Frank, most of the requirements that companies have, have been around and they've been cobbled together over the last few decades and to be quite Frank, they suck. So how do you take this garbage, that is in a quote unquote "technical document" called a job description and actually make sense out of it because we have a garbage in garbage out kind of scenario. How does your AI actually understand what is worthwhile and what is not? Because many of those job descriptions are just ridiculous, horrible, and they suck.


Markellos (10m 4s):

We trained our AI based on those, some ridiculous, horrible job descriptions that are out there. And that helps, but I'll tell you things. We had customers who said, Hey, I put my ridiculous, horrible job description. I looked at the profile and then I said, this can't be right. So I went back and looked again at my job description. And that also helps, you know, giving you a loop of validation that says whatever I put in this job description actually means ABC and D. And when that doesn't make sense, it helps you go back a step. But the get-go issue is a big problem. You have to start from somewhere, right? If I give you a list of job descriptions, then that's going to get you into another path of making mistakes.


Markellos (10m 48s):

So yes, there is where the recruiter has to have some post, spend some effort to say, this is better not great.


Chad (10m 59s):

Gotcha.


Joel (10m 59s):

There's a ton of competition in your space. I don't have to tell you that. Talk about your differentiator when people, you know, when prospects ask you and I'm sure they do all the time, how is this different from everybody else? What's the answer that you give them?


Markellos (11m 13s):

We don't see as much competition. You're thinking of the pre hire assessment space, where there's a ton of competition, where we define our sweet spot is really into helping people after they've been hired. You know, how we're spending all this time and energy to hire the right people. And then there's this institutional amnesia and we forget about all the things we learned and we treat them as we know nothing about them. What we're trying to create here is a system of record for talent throughout the company, throughout the employee life cycle. So from the point we hired people to the point that they retire. We want to constantly be thinking about what are the great out, how can we help them? How can we help them move to the next position?


Joel (11m 53s):

Ok.


Markellos (11m 53s):

And I always say the great resignation is just about that. We put people in a box and then we expect them to do things based on what they've been doing before and never once considered, would this person be great at doing something different?


Joel (12m 5s):

This may be an issue, cause I thought you were in that space. So you're more of taking your current talent pool and basically mobilizing them, upskilling them, getting them into other positions within the company. Is that correct?


Markellos (12m 20s):

Well, we do both, both talent acquisition and what we call, you know, internal and so on talent intelligence kind of is the full gamut, right. From hiring to retiring.


Joel (12m 29s):

Okay. So as part of the differentiator, like we don't just do the pre-screen like top of funnel stuff we do after the fact and help people upscale and get mobile within a company. Is that correct?


Markellos (12m 45s):

Definitely.


Joel (12m 45s):

Okay. Talk about your high volume hiring tool. I'm curious in particular about how the talent and the process or the candidates interact with the solution or do they at all?


Markellos (12m 55s):

Oh, they do. Because the challenge when you're dealing with candidates and it's the problem that you described, right? If I start with the candidates based on the resumes, then all I end up doing is that I'm parsing data that's not good to begin with. So in order to set a fair base, to start helping people, we need to run them through an assessment. And we try to make the assessment as how it was like to say fun but people say I'm over selling. As pleasant as possible, where they go through a simulated work environment, different people come a stupid chatbots if you like, because they come with very predetermined roles and they ask you questions and gather data from you. But this is the essence of what we do, right?


Markellos (13m 36s):

Once I start having a clean set of data about who you are, in terms of what your cognitive skills are, what are your personality traits and how they are pronounced, then I can start making all sorts of great things for you and make you better, more successful.


Joel (13m 51s):

Why do you say to stupid chatbots? You're obviously not a fan, but I'm curious specifically why?


Markellos (13m 56s):

No stupid chatbot in the sense that it doesn't have any intelligence, it feels like you're talking to a person, but you can see that it's canned responses.


Joel (14m 5s):

Okay. Who's your target audience, or what does a typical client look like? Is it big? Is it a certain industry? Is it international? Is it a specific to a certain region? What is your client usually typically look like?


Markellos (14m 17s):

Half of our customers come from the U S and Canada. The rest come from, the rest of the world. And you know, the span anywhere from, I don't know, France and Germany to the Philippines. We're looking mostly at upper SMB and tender price customers and the main common theme is they are people with a pain. What does the pain mean? That people have pain in turn. Call centers, MNA situations where everybody turns over within a couple of years, they need to make sure that they retain talent. They're high volume companies who hire a lot, frontline workers, again, call centers, whatever, what have you, they need help in bringing the right talent.


Markellos (14m 59s):

But we also have a significant chunk that is hiring quality. These are your hyper-growth companies, your unicorn startups, where they say, Hey, I'm going to be bringing 20 or 30% of my workforce, sometimes even 50 & 60% this year. I need to make sure that I keep building a company that's great. A company that, you know, around surround a common theme and people can talk to each other and understand them, not just a mishmash of people who are just randomly hired.


Chad (15m 27s):

It sounds like there's nobody that you won't talk to is what I'm hearing is like you will talk to small companies, medium-sized companies, large companies, ones who want high volume all the way to executive it. Tell me, is there a niche that you won't touch?


Markellos (15m 45s):

A niche that we won't touch? Look executive, doesn't make a lot of sense for us they have different requirements, for example, some people will use us, but this is not what we're going after. And again, it's where we get the ROI where you have a big pain, and this is why our customers are getting increasingly larger because once you can have that reduction in turn, because you can have that increase in hiring quality, it makes so much more sense in volume. So some of our customers are fortune 500 companies and we see a trend of getting more, not less of those.


Chad (16m 20s):

Okay. So let's pivot real quickly to the candidate assessment, which takes 20 minutes. And it's via a chat bot. Now, is that a chat bot that is specific to your site and app that they have to use, or is that SMS and text? How does an individual interact and does that 20 minutes have to happen all at once in one sitting or can it happen throughout a couple of days or a couple of weeks as the candidate wants to respond.


Markellos (16m 51s):

This all happens on our website. We have an app website and they can go through their laptop and, you know, do the full interaction. We actually have a frontline version designed, especially for, you know, those hospitality and call center workers that is designed to be mobile first. So you can complete the whole experience with your mobile on your web browser. And we do suggest people take the time to do everything in one sitting. However, you can never guarantee that you will have the luxury to do things in one sitting, right. Stuff happens.


Chad (17m 23s):

Right.


Markellos (17m 23s):

So if you do get interrupted, you can always go back and pick up where you left off.


Chad (17m 31s):

Okay. So quick question with regard to ejection rate, we just received a survey information a couple of weeks ago. I think believe it was from Appcast where it demonstrated over 90% of individuals applying for jobs today, over 90% ejected from the application process, what is your ejection rate using this chatbot process for this assessment evaluation?


Markellos (17m 59s):

It varies from the company and the position. We've seen companies that have ejection rate that's in this low, sorry, in the low single digits, you know, one to 5% to not complete the assessment. And that's when you have, you know, a very highly desirable fortune 500 company and people really want to go for that. And we've seen, we've opened the position, for example, for a content writer, for hiring at Bryq. And, you know, we're a unicorn to be, but not quite famous yet, but we got 2300 applicants. So how do you choose 2300 applicants? How do you find the best one from those? You send out 2300 assessments and there, I think we had the slightly over 60% completion rate.


Markellos (18m 43s):

It does vary as I was saying.


Chad (18m 45s):

Okay. So after they have the assessment and they complete assessment, that's when you can actually go in and start matching and then surfacing candidates who matched to those positions is that what I'm hearing, they have to go through their set of information and assessment before you actually start the matching.


Markellos (19m 3s):

Yep. I have to match you based on something. Right. And once I have that objective data about who you are, then I can match it to my ideal candidate profile that I created, maybe using the AI, maybe I created using bench marks or all sorts of other fancy things that I can do internally and I can make better choices.


Chad (19m 23s):

Okay. So I'm hearing, you're not using the resume to match against the job description, is that correct?


Markellos (19m 28s):

We don't touch it at all and this is one of the ways how we boost DNI because we're totally unbelievers of any of the data in the resume I don't know your race, your gender. And in parallel, we've run a ton of studies on our own data because we do get a race and gender information voluntarily from people who will fill it out. And we see that there is no significant, no significant bias in any of the protected classes. So I can say that women score better than men in this or that or any other difference. And that let us tells us that our database is clean, meaning that the data we acquire is not biased. And then we can actually go and make this whole process and help make the decision based on data that is clean.


Markellos (20m 14s):

That's why I said before that we had the customer who boosted their gender mixed by 119%. And interestingly enough, that customer was hiring more women than men. And we helped them hire within equilibrium, not just women anymore.


Joel (20m 29s):

You're throwing out a lot of customers. You got big customers, little customers, all kinds of customers. What is your secret sauce in accordance to sales and marketing? Tell me about that strategy.


Markellos (20m 44s):

GTM is one of our favorite items and you'll see that it's interesting, probably 40% of our leads is incoming organically. These are people that was the problem knocking on our door because we provide such a unique solution.


Joel (21m 1s):

And how'd they find you.


Markellos (21m 2s):

They find us on Google. They look for the problem.


Joel (21m 6s):

Okay.


Markellos (21m 6s):

They look at some of their content. I actually don't know how they find us, right?


Joel (21m 10s):

So you're not paying, you're not paying for ads on Google. These are, you're being found organically for the problems that you're solving. No money to Google. Okay.


Markellos (21m 20s):

We've tried Google ads and they never paid out for us. They make no sense.


Joel (21m 25s):

Okay.


Markellos (21m 25s):

And then another 30% or so comes from partners. And sometimes it's partners our systems that we integrate with, you know, we have 15, 28 years, is that we integrate with, we're now adding a bunch of HRISs, But it also comes from another kind of partner that we actually love and hopefully we're going to get more and more of those, which are HR consultants or MNA consultants, management consultants, people who are working with customers who have this problems and they need the solution to provide better solutions for their customers.


Joel (21m 57s):

So in terms of your team, do you, I mean, I assume you have a sales person or someone that handles sales. Is there a marketing team, like talk about that internal structure?


Markellos (22m 8s):

We are very sales heavy. So I think that sales is well, our second biggest team after product. We are a product led company, so product comes first, then sales and our marketing. Have you been to our website? You know, that our marketing team is small. What we put an emphasis on is content. And we like to provide valuable content.


Joel (22m 29s):

So you're saying the 71 followers on Instagram, aren't bringing in a whole lot of business to the company, I'll just assume that. So your sales team, is it remote?


Markellos (22m 39s):

That was 71 customers.


Joel (22m 41s):

Oh yeah, I'm sure all those followers are customers. So how many salespeople are we talking about? You know, are they global?


Markellos (22m 50s):

Mostly US based, but we're at 25%. Right. Okay. So we have about 10 people in sales. Maybe half of them are devoted in a lead gen as the RS and PTRS and the other half are sales force.


Joel (23m 2s):

And you, you touched on the integration strategy, repeat how many you have and more systems like talk about what that's meant to the company and how important that will be going forward.


Markellos (23m 12s):

We think that HR practitioners have a hard enough job as it is, right. They have to tackle what is the current stat I was reading the other day that the average TA stock is maybe 27 systems deep. So they have 27 disparate tools that they're trying to juggle. So we don't want to make this harder. We do integrate with a number of ATSs and we keep adding. I think we are that pinpoint and ASPE lately, but we have, you know, Greenhouse, Lever, blah, blah, blah, all the usual guys. And that makes sense for the TA part. Now we're starting to build integrations with HRISs because deep in our heart, we care about closing the loop. So it's always about, Hey, I'm going to propose a change. I'm going to make it.


Markellos (23m 53s):

And then I want to make sure that what I made actually makes sense and to have created an improvement there. Or not and if not, I want to fit this back to my model so that I can learn for next time.


Chad (24m 5s):

Okay. I'm going to jump back to go to market since you love it so much. When we're talking about that type of strategy, it's all about the difference between a direct to brand direct to logo versus a strategic partnerships that allow white labeling to integrate into some of the big systems. Where are you guys focused? Are you focused on a direct to logo conversation to be able to get these organizations involved? Or are you focusing more on partnerships with bigger systems?


Markellos (24m 37s):

We're more direct local people buy Bryq and that's really key, right? Because we offer a lot of functional is the third essential. We have a very strong partner strategy, but this is more with people who can take Bryq and help customers become successful. It's not easy, right? And especially when you're selling something that doesn't quite fit into a box. If I'm buying an ATS, I know exactly what I expect and how to do it and people have probably worked with 10 different ATSs. If I'm buying a talent intelligence solution like Bryq, I'm not quite sure what it does. I'm not sure how it fits. I'm not quite sure what kind of changes my organization is going to need. And this is where the partner play comes in really strong and Hey, call out the partners, come join us.


Markellos (25m 19s):

Let's talk about it. Let's help customers become more successful because this is how you rewrite the future of work, right? With people starting little by little to change the way that we do things and make them better.


Chad (25m 30s):

Okay. So last but not least, this is a lot marketing Markellos. This is a lot so it's gotta be expensive. What does this cost, how do you price this out to a customer?


Markellos (25m 45s):

Fairly. Reasonably. We have two main pricing ones, right? When people hire, we charge them a fee per open headcount per month. And we put a lot of emphasis on not charging per user. We really want to make sure that DNI is there. If you need to test 10 people fine. If you need to test 10,000 people and assess them, understand who's the right next one for you, also fine. Very predictable in budgeting. And when we go into talent intelligence, we charge you a fee per employee per year, that depends on the size of the organization. In both instances, our fees are a small fraction of what it costs you to have a new hire, right. And new hire is what, $4,000 each hire?


Chad (26m 24s):

So do you price it per hire? Do you price it per seat? How do you actually price it? Give me some type of answer. Markellos, come on.


Markellos (26m 32s):

For TA, we price it per open headcount per month. Okay. Okay. So if you need to do to hire 10 people, then we'll charge you 10 times or fair or whatever.


Chad (26m 40s):

Okay.


Markellos (26m 40s):

And for talent insights per employee per year. So if you have a hundred employees is going to be, you know, our fee or fixed times to a hundred, and this is what you end up paying.


Chad (26m 48s):

So why are you guys even hitting the bias conversation out of the gate? I mean, is it even necessary if you're doing your job the way you should be doing your job, that shouldn't even be a part of the conversation, but yet it seems like every single platform that's out there today has to put DEI on their website. And it just seems so fake. So why do you guys do it?


Markellos (27m 10s):

Because we believe in DNI, we believe that it is important that you have an equitable process and look at what the EOC mandate is today. You have to make sure that there is no bias in your process. And if you look at a hundred employers, 99 are probably going to fail the test.


Chad (27m 28s):

Yeah. And that's on them.


Markellos (27m 29s):

It's on them. But Hey, it's also in the industry. What are the solutions? We want to go with a solution, people can understand, people can use, people can apply and they have better results. Again, I repeat myself, but this is the future of work. Right? When you change the little things and you have big impact.


Chad (27m 48s):

Agreed, agreed. So what's the end goal? Are you looking at becoming that unicorn, that DECA corn?


Joel (27m 53s):

He said, he's a unicorn to be, so yeah, I have, your plan has to be a IPO, right?


Chad (27m 59s):

Yeah. Are looking at IPO? Are you looking for acquisition? There's a lot of both of those things happening, Markellos, where are you guys ending up?


Markellos (28m 7s):

We see so much strength in what we're doing that I cannot foretell the future, but I find it unlikely that we get acquired somewhere. I don't see how someone could give us more value than what we have. What we want to do is keep building a platform and making sure that people have equal access to it so that, Hey, we can do our thing. I want to say, make the world a better place, but that would sound cheesy.


Joel (28m 36s):

Cheese is all right, Cheese is okay. All right, Markellos, are you ready to face the firing squad?


Markellos (28m 44s):

Ready as I'm ever going to be.


Joel (28m 47s):

I'll go ahead and go first. Try to hash my way through this. So you have a lot going on and it's hard to sort of in a 20 minute Q and A really nail down how I feel about the company. I do feel like you have smart people. There's PhDs there. Obviously the technology, a lot of companies are finding value in it. You're obviously profitable. You have another round of funding. So you're finding success there. I think the sales heavy team is probably working for you. I think you obviously recognize that the marketing needs to improve and hopefully with the next round of funding, you guys can tighten that game up quite a bit.


Joel (29m 33s):

I do think there's a lot of competition just for the mere fact that you have to cut through the clutter of all the solutions and services that are out. I remember famously a call-in day from iCIMS told us his biggest headache was trying to get people's attention. And that's going to be a challenge that you have as well. So for me, it's just really hard, cause I it's hard for me to put you in a box and decide what I feel about you. But I also think that there's an opportunity there with the technology that you guys are providing companies are obviously getting value out of it. I think you personally have balls of steel with some of the comments. You're a very confident person. I think that's going to carry you far in this business.


Joel (30m 16s):

So for me, it's like, I'm just sort of on the fence, not quite how to figure out what I think about you guys. So I'm just sort of golf clap and I'm going to be in kind of a wait and see mode with you. I'm going to keep my eye on you Markellos and see how things go. Chad, you're up buddy?


Chad (30m 35s):

Excellent Markellos. Just having the conversation. It is way too broad for being in startup phase because you do so much. But one of the things that in advising startups for over a decade now, one of the biggest issues that startups have is they go too broad, too fast. They try to please everybody all at once. And whether you're talking about the regions or serving all of the globe, whether it's high volume, entry-level, mid-level, you know, being able to do all of these different things, DEI, you know, I get it. You want to be able to please. But one of the best things that we can do in our industry is say no and focus and be experts in some areas.


Chad (31m 18s):

Being able to focus on also the chatbot, which I think is awesome, but I think it would be even more awesome if you got a chance to do text SMS, WhatsApp, and then start to allow that engagement, which is more focused on me, not you. You're asking me to do things your way now, the way that we see things in surveys from candidates, candidates love to be able to SMS, to be able to text, to be able to use WhatsApp. When you force me into your box, whether a psychologist is in it or not, I don't want to do it, but overall, let me tell you, man, I love the idea. And I love the guy who has the idea of killing the resume.


Chad (31m 59s):

And there are plenty of you that are out there today. It's hard to change a hundred years of behavior, but it needs to change. And I'm one of those guys that is behind you. I also love the idea of using AI as a validation methodology for being able to choose candidates. What is your job description actually saying that you're looking for, oh, wait a minute. That's not it. What the hell am I doing here? Right. So I love the technology. I love the idea, what I don't love as the carpet bombing, get more into, I think a precision targeting system, which I know that you guys are, when you get there, I'm going to be a big applause.


Chad (32m 42s):

But right now, sir, I am a golf clap.


Joel (32m 44s):

There you go. Markellos.


Markellos (32m 50s):

Thank you, gentlemen. You made me feel just like Tiger Woods today.


Joel (32m 54s):

Well, you're a little bit bloody, but you have survived the firing squad and Chad, that's another one in the can. We out.


Chad (33m 2s):

We out.


OUTRO (33m 13s):

This has been the Firing Squad. Be sure to subscribe to the Chad and Cheese Podcast so you don't miss an episode. And if you're a startup who wants to face the Firing Squad, contact the boys at chadcheese.com today. That's www.chadcheese.com.

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