Candidate Fraud Stops Here with Etan Bernstein

0:00Joel Cheesman: Hide your kids, lock the doors, you're listening to HR's most dangerous podcast. Chad Sowash and Joel Cheesman are here to punch the recruiting industry right where it hurts. Complete with breaking news, rash opinion, and loads of snark. Buckle up boys and girls, it's time for the Chad and Cheese Podcast.

0:22Aww yeah, it's the podcast your dog sitter warns you about. You may know us as the Chad and Cheese Podcast. I'm your co-host, Joel Cheeseman. Joined as always, Chad Sowash is riding shotgun. As we welcome Eaton Bernstein to the show. Eaton is the co-founder of the Velocity Network Foundation. Eaton, welcome to HR's Most Dangerous Podcast. Thanks. Great to be here. Good to have you. Good to have you. So a lot of our listeners, viewers probably aren't familiar with you. Give us the elevator pitch on you, the person, and then we'll get into the business stuff. Perfect. So I'm an HR guy. I've been an age guy for 35 years, love the profession, spent many years in large organizations like Intel and Applied Materials, and then moved on to be a consultant working with companies all around the world.

1:07And through that, really discovered how much friction and fraud there is in the talent acquisition world, which is what caused me a few years ago to get some of my friends together and say, let's try to solve this really big, hairy problem together. I live in Israel, but my work's really been global for my entire life. I have three marvelous children and a wonderful wife. Are the kids still around or are you an empty nester? No, close to an empty nester. My 14-year-old baby is still around. Chad's got tips for the almost empty nesters. So if you need some side notes, just give him a call.

1:41Joel Cheesman: Send him to school and don't tell him where you move.

1:47Joel Cheesman: So friction and fraud. I mean, my big hairy problem is Joel Cheeseman, but everybody else is. friction and fraud. I mean, it's an AI dumpster fire out there, man. You've been floating through this industry for about 20, 25 years. You've seen the shift from paper to PDFs to LinkedIn. And now this absolute dumpster fire of 11 ,000 fake applications a minute. Did you hear that, kids? A minute that recruiters have to play around with, or they have to at least try to sift through or try to figure out what's fraud, what's real. Is the resume finally dead? Is this what's going to kill the resume? We've been talking about this for years, Eaton.

2:28Joel Cheesman: Please tell me, oh God, this is what's going to kill the resume. Can we finally blame North Korea for the resume? That would be a great story. They are a player with this issue, yes. Well, I hope so, but I think it's going to be a longer process than that. And I don't think it's about the resume being dead or not, I think it's about changing the way we approach this. And what I mean by that is you said, you know, in our generation, and yes, I'm old enough to remember, I started my first application actually sending, even before fax, I actually put a stamp on a letter and then faxes and then emails with attachments and then a LinkedIn profile, right?

3:03And then PDF files, right? We've gone through, it's not that the industry is stagnant. The industry has gone through these generations, right? And things have changed.

3:11Joel Cheesman: Get off my line, you no good punk kids. But, you know, but through that process, what's really interesting, we still have only self-reported data, right? What's the problem with the CV? It's a marketing document. You write whatever the fuck you want. Sorry for my language. No, have it. And that was fine, you know, when you had to invest in writing this revenue all over again in a cover letter. But now with AI, it's just become impossible. And that's what's really changed this. Self-reported data that had to be verified has always been around. and people exaggerating and lying and actually being fraudulent has always existed.

3:45But the AI challenge has really blown that all apart. I mean, everything's falling apart, right, in terms of our ability to deal with the slop and shit we're all getting through these processes. And something has to change. So who was it that said by 2028, one in four candidates will be – was that Robert Half that had the one in four by 2028? We obviously know it's a problem from the job seeker. Software's popping up. Agents are popping up. Give us the other side of the ledger from your perspective, the employers who are playing a game of whack-a-mole, and they're going just as robotic and automated as the job seekers are.

4:17So talk about that side of the table a little bit. So I think it's this real bad war to the bottom, right? It's a battle to who knows what horrible situation where individuals have learned that they have no choice, right? They're using agents not because they all think it's wonderful, but because they know that unless it's a numbers game, unless they're using agents to apply on their behalf more and more, they have no chance, right? And with the economy being what it is, and with young people have struggling so hard to find jobs anyway, I have nothing to lose by having an agent take my resume, adopt it to every job description, just send it out.

4:53Worst comes to worst, I'll say no, but I have nothing to lose. And that's what's causing a lot of the slop. When they say one to four candidates are fraudulent, I don't think that's even the big problem. The problem is good candidates, real good people who are finding no choice but to use tools to try to get their ability out there and represent themselves. And they don't really check whether an AI is changing some of the information in their resume or exaggerating on their experience or writing a degree that they don't have because they just want the opportunity to get in front of an employer and represent themselves, right?

5:26So I can understand the candidates completely. On the other side, you have the employers. What are they going to do? If they're getting 10x the number of resumes they got beforehand and they all look perfect, what choice do they have but to try to use more and more automation and AI to try to shift through that? But that is creating, both sides are losing out of that to a degree that even some of the analysts are saying, maybe we need to go back to face-to-face and paper. Of course, we don't need to do that. But there is something fundamentally broken in where we're going right now on this path, which is where we believe that something needs to change.

6:00Joel Cheesman: Yeah, we try to paint this broad brush for a lot of organizations where they shouldn't go back to face to face interviews. In some cases they do. I mean, there are some roles in some organizations that are smaller organizations that might have smaller departments and that might actually fit very well, especially with their culture. And then you have high scaled organizations that there's no way in hell that a human or their human department is going to scale fast enough to be able to understand all of this. Now, Joel, he talks about whack-a-mole a lot with regard to literally it's just what tech does and you're literally just trying to fight the tech with the tech.

6:38Joel Cheesman: But your whole thought process, instead of like blacklisting, it's more like whitelisting. It's around trust. And everybody loves the word trust, even though it's dying on the vine, for God's sakes. What does that actually mean in the network? How does velocity and how does this whole structure and concept work around trust? What does that even mean? So as I mentioned, right now, all we're relying on is self-reported information, right? You can write anything you want in your resume. It's bullshit, yes. And as a result of that, an employer or recruiter needs to look at that, hope that most of it is true, and then throughout the sourcing process, the recruiting process, and so on, try to rule out who's lying, who's exaggerating, and so on, right?

7:20So you have to be checking those things. And what a lot of the staffing companies are doing now is try to identify a fraud early on in the process. For example, by adding IDV, an identity verification process early on, so we rule out when it's a bot from North Korea, right? Or do some form of verification whether the application happened within two seconds, probably a bot filled out the application. Or if someone is inconsistent between their resume and their LinkedIn profile, although AI does consistently great, that's a sign that things are not good. So everyone's looking for fraud signals. But AI is going to get so much better that you won't even be able to find those very quickly.

7:57So what we need to do is instead of looking for fraud signals, we need to embed trust at the source. What does that look like? It actually means that I, as an individual, have verifiable information that I can trust from the beginning when I present myself, not everything that will be in my resume, but the fact that I am a human being and that I'm a citizen and can work in this country and that I have this education, that I've worked at these companies, that I may have passed these assessments and so on. real facts that anchor my CV so that the employer can rule out that at least these things are true.

8:31Then there's always the marketing and exaggeration and storytelling, which will continue to be important, but I don't have to start from scratch. A really good example to that, Chad, we were talking about that, is what the credit card industry has done. So for those of us who remember when we had credit cards with a magnetic strip on them, there was incredible amount of fraud in the credit card industry, right? Because it was very easy to pick up the credit card information and reuse it. And then the credit card companies got together and say, let's solve this with the chip that everyone recognizes on their credit card, right?

9:02That's a global standard that has basically limited, it builds trust into the process. There is no way to cheat with a credit card in a physical interaction. There's still web-based problems, but that's really solve fundamentally build trust into the payment system. And that's what we're doing with the resume, basically.

9:22Joel Cheesman: Eden, when you talk about that, that was actually burning billions of dollars of their own cash from the banks, right? So the banks were losing money. And in the case of HR tech, vendors actually profit off of all this chaos. There's more useless AI detectors and extra screening. We've got this Indeed creates their own, you know, apply, you know, easy apply, which then today loads resumes. Oh yeah. Oh yeah. And you're allowed to have more than one resume. So, I mean, they're creating the chaos and that is just more money in their pocket because it makes it harder for them to actually find qualified people, even though they're saying, oh, we want you to find qualified people.

10:06Joel Cheesman: So what is going to force this industry, much like the banking industry to actually feel it in their pocket. So they make the change. So I think you're hearing it in every conference you're at and with every forum you're meeting recruiters, the employers. The employers are suffering. They're saying, OK, it's great that we get 10 ,000 resumes, but we can't do anything with them, right? And so the pain is there. The pain of being able to hire high-quality people quickly and effectively and fairly is basically not working. And so we're hearing employers everywhere demanding a better system. We have to change this.

10:41Yes, there are forces to keep going in the direction we're going, but there are also forces to say enough is enough. This is not working for us. We want to do something different. And that's an environment where innovation comes out, where the incumbents may not, you know, they may have an interest in keeping the world the way it is. But there are enough people who have an interest in helping make it a better world. So your credit card example, although a good one, you know, there aren't a lot of credit card companies. There's a great amount of disparate systems in employment. We just talked about the job board, the ATS, how many ATSs are there, how many job boards are there.

11:14There's just so many moving parts in that. Thoughts on that? And then also, what percent do you think of job seekers really are lying? And what percent are really just saying, hey, this is a new technology. I can be more efficient. I can apply to more places. They're not necessarily lying, but they are using automation to get into more companies and apply to more jobs. So curious about the disparate question. And then also how many are really lying versus how many are just using the technology and being truthful? So I'll start with the latter question. I don't have statistics. I don't think anyone really, really knows.

11:48But I think a majority of people are just trying to get in, right? And they're using technology. And by the way, I think that a candidate that uses AI to apply is a good indication that they feel comfortable using AI. If I'm an employer. I think most employers want AI to be used to some degree. Exactly. I want to know that this candidate knows how to use an LLM to write a good resume, knows how to use a bot or use an agent to apply for jobs. That's an indication that they live in the modern world, right? Those are skills that show that there's value. So I think most people who are using these tools are not bad players.

12:24I think that they're not sensitive enough to the fact that many of these tools exaggerate. The tool is built to match the person's resume to the job description. What is the tool promising? watch the videos of any of the AI agents. They're all promising to pass the initial screening. What does the initial screening do? It compares the resume to the job description and sees whether there's a good match. So the AI tool is basically taking your resume and adopting as much as it can possibly tweak it to try to fit the job description. And individuals are not taking the personal responsibility to understand that in that, it's actually creating fraudulent resumes that are not representing them correctly.

13:04Many times they don't even read them. Some of the AI tools, you can see the application for every time and make a decision about it. But most people are putting them on autopilot and just asking them to send out as many resumes as you can. They're not even making the effort to try to understand whether there's anything wrong there. And that's where I think most of the, yes, there are North Korean fraudulent and there are bad players that are utilizing these technologies. I'll bet those are very few percentage. And the majority is good people just trying to get jobs. Is this starting to slow the hiring process?

13:35I mean, when chat box, for example, came out, it created such efficiency and speed and people were talking about getting hired in hours versus weeks and being interviewed instantly. Is the reverse starting to happen? Are we creating so much complexity that it's slowing the process down? Absolutely. And creating confusion on even how to act. So I'll give you a good example. I just came back from a conference in Germany. In Germany, many of the public companies, banks, government have to review every candidate who meets the job descriptions for good purposes, right? For purposes of ensuring that there's no – that the people of different ethnicities and genders and so on are not discriminated against.

14:14And historically, if you published a job for a bank, you'd get 70, 80 applications. 20 of them would pass the job requirements. So you'd have to bring 20 people in to interview them. That is something you can handle. Now they're getting 300 or 400 applications because agents are doing it. And 280 of them or 350 of them are passing the job requirements. The companies are like, what do I do now? How do I even start addressing this flood of resumes if I want to be compliant to the legal requirements? I really want to give people an equal chance of being able to get through my screening process. I'm stuck.

14:54And that's a real problem. It's slowing down these processes.

14:57Joel Cheesman: Yeah. So a couple of different things. We talked about we know that there's a problem out there. The biggest issue we've seen over the years has been adoption. We saw Taleo create a universal resume back in the mid-to-late odds, right? We saw Alliance Q actually had, it was an association of organizations, huge organizations that shared candidates and validated, verified those candidates. And we also here just recently saw a couple of industry veterans in Richard and Beverly Collins with CV Wallet. That network went down as well. So from an adoption standpoint, we have the employers and they just haven't adopted yet.

15:37Joel Cheesman: But then also, as we've talked about with applicant tracking system and job boards, these guys make a killing locking in customers to proprietary moats. And what you're talking about is a more open system where there's one candidate. I mean, one candidate profile, correct? Individual has their own owns their profile. Correct. Right. So they have like their verified work history, their certifications, where they went to school, all of these different things. It's owned by them. When that happens, Eaton, I think this has always been a problem. When that happens, all of these companies who are making money off of that candidate and keeping that candidate profile to themselves, they lose that moat.

16:18Joel Cheesman: So from an adoption standpoint, I can see where employers want to move that way. But from an HR vendor standpoint, how are we going to be able to monetize? Because that's going to be the real key to get these guys moving. How are we going to be able to show them a new revenue model that helps them get away from this old revenue model where they're making money now? So I don't think that the revenue model even today is just based on the quality of the data. They're making money off giving bad data about incorrect people just selling it. So I think the more people have verifiable information, the more the industry will adopt processes where a candidate that's more verifiable is worth more.

17:00They're still sourcing. They're still screening. They're still finding the right people. I mean, the industry will change to some degree, but it's not that the only source is making up fake data about people, right? The industry is more complicated than that.

17:13Joel Cheesman: But don't these companies want to own this, though, instead of saying we want to do this in a bit? Because I remember ISOM saying they want to create Passport. I mean, all of these different companies indeed trying to do some version of this, some weak ass version of this. But I mean, it seems like they're all trying to do this. How do you get them together in one room and say, OK, can't we all just fucking get along? Rodney King, this shit. Let's do this. And that's exactly connected to what Joel was saying about when we have such a fragmented ecosystem, it just doesn't work. Yeah. Right. And it goes back to it goes back to the days of the early Internet.

17:49Right. Think about the days of CompuServe and America Online. Everyone had their own small ecosystems. Everyone wanted to control their world. Everyone was like, but I want my I want to monetize the small. If you have to bring your friend into my ecosystem, you can only communicate to them. And there's great information. You know, they were really thinking, what do we do with this worldwide web? What do we do with this internet? Should we open up to it or not? Now, clearly, in the same way that the internet created incredible prosperity for everyone, including the companies who realize how to take advantage of it, right?

18:22The opportunity for ubiquitous infrastructure for trust will do the same thing. It will generate incredible opportunities. But you have to stop protecting your moat and think about what an open ecosystem actually creates for everyone. And we believe that that creates a great opportunity. That's exactly why we founded the Velocity Network Foundation the way we did. Instead of every one of these private companies trying to build their own closed ecosystem, what happens if as an industry we build one protocol, one shared infrastructure, which nobody owns, nobody controls, like the Internet? and everyone can use in a way that's a public infrastructure, right?

19:00So you can move from one staffing firm to another, from one platform to another. You own your data. You share it with whoever you want to share it with. But it's all interoperable. In the same way I can send an email from every email system to any other email system in the world. I don't care if you're on Gmail or on Microsoft or something else. It all works, right? That's because there's a trusted protocol that everyone adopts. And that's what we hope will really make this to solve Joel's question. really help this work is break down these silos, have everyone join and utilize one open protocol.

19:31Joel Cheesman: Well, and this sounds like the best of both worlds when you're talking about like AOL, they whitelisted things. And I mean, there was obviously some monetization behind that, but they monetized and you didn't get the whole internet when you were using AOL, right? You got what they whitelisted. It sounds like you guys are trying to whitelist all the verified, trusted sources and you're making it open, where before AOL was closed network, but this is an open network, but it's only open for verified trusted sources. So we've created an open infrastructure. Think about like the internet. The internet has no application.

20:06The internet is TCP IP and DNS servers, all these technical things that nobody actually sees. What do you see? You see browsers, you see websites, you see applications. Those are not the internet. Those are vendors building things on top of a shared protocol. What Velocity Network provides is the shared protocol that enables anyone who wants to participate. We're not whitelisting them. We're letting them use a shared protocol. So instead of having a website in America Online, you have a website on the World Wide Web. And anyone all around the world can see your website. Instead of being a candidate in one platform, if you want to, you can share your data with any other platform.

20:42And it's verifiable to anyone who wants to see that. I think part of the problem, and Chad mentioned some of the ones that have come and gone and sort of dabbled or dipped their feet in it, is the economies of scale. And I think Velocity Network has that problem as well. And when I look at someone like LinkedIn, to me, that should be where the problem is at least largely solved. A couple billion people on the network, they partnered with Clear, where you can go in and verify that I'm a human being. Now that could be, hey, I'm a real person. You're saying there's also the issue of, am I lying? But if I push back and say, hey, if LinkedIn tackles this and they partner with Clear, like, isn't that a big step forward or is that am I misguided on that?

21:24We were in touch with LinkedIn and I believe LinkedIn is the perfect wallet for individuals to hold their data. And they're already maintaining self-reported data. LinkedIn would be in an ideal position to encourage, just like they encourage their users to verify their identity. And now they use Entra to verify that you actually work at the employer that you claim. You can't verify your actual title, but you can verify that you actually have access to your latest employer. Then wouldn't it be great if I went into LinkedIn and I saw every profile that has certain percent of the credentials or information there is actually trusted, verifiable data.

21:59So LinkedIn is a perfect participant in this kind of ecosystem.

22:05Joel Cheesman: Well, and you would know, and correct me if I'm wrong. So as Joel's talking about Clear, Clear just says that you're a human being. That's baseline, right? You're a human being. We know this is not a bot. That's awesome. But there's so much data that is actually in your profile that's not verified. You can go through that process of going to the universities, verifying that they actually went there and that they've graduated or what have you, going through some of the assessments, maybe even adding background checks and those types of things. I mean, all the way through. So, I mean, this is a much deeper profile, verified, validated profile than just clear at the top saying, hey, this is a human being.

22:48Exactly. Exactly. Think about a child getting born today. You would expect that in the digital age, everything I do, I have digital footprint, right? Why shouldn't I have that control of that digital footprint and be able to prove all these things? Why do I need to go through a background screen every time? Why do I need to go through an assessment every time? Why do I need to wait a few weeks for my screening process to approve me so I can work in a bank or a health care system? All that friction is unneeded. Again, when I'm a good player, the employers obviously want to rule out the bad players or the people who are exaggerating on their skills and capabilities and really get the best candidates.

23:24So everyone wins, in our view, maybe except a few vendors. Everyone wins when the world is based on trust. Wouldn't that be a happy world if we all trust in each other?

23:35Joel Cheesman: Good luck with that one. That would be beautiful. So what's your biggest hurdle so far? I mean, because obviously, I would say probably this whole scenario, like you just said, many of these background check, let's say vendors, they get Chad Soash goes for, you know, three or four different jobs. And I've got to get three or four different background checks for different companies. In this case, I get one because it sticks with me. That's a monetizing model kind of problem. let's say. What's your biggest issue in trying to help these companies just say, look, we've got to get past this. You've got to change models.

24:12Joel Cheesman: You have to evolve because we need something like this. What's your biggest obstacle right now? You hit it on the head that this is a chicken, egg and rooster problem. So it's a multi-sided network problem and it's tough. The issue is adoption. You've both pointed that out very clearly and you're absolutely right. The way to deal with adoption is by building ecosystems, small ecosystems, where you can actually reach a critical mass in a logical time frame, right? So find an industry and a geography where you have the issuers, the individuals, and the employers all working together. So we do that, for instance, in healthcare in the US, specifically in a few of the states.

24:50And we're now doing that in staffing, the staffing industry in the UK, then some exercises on banking in the Netherlands. So how do you build out an ecosystem that creates enough weight, enough adoption within a relatively short amount of time so everyone gets value. And that's the challenge of building out these micro-ecosystems, basically. You mentioned, Chad, a question about the background screeners. The background screeners are very interesting because, yes, they could be cannibalizing their business. But what many of the background screeners have told us, and we have some of them, the leading background screeners in the world as part of our membership, is they don't actually make any money on verifying static past employment.

25:29Chasing down an education institution for a nurse who graduated in Manila is just a pain. It costs more than it's worth. And paying with a work number, Equifax,$100 to get the records is not, no one's winning out of that. They make their money by doing investigative high quality work, now using AI for intelligent verification. All just checking another person again, a person's education or employment 20 years ago is just is not a value added step. And so even many of them are saying, we wish we could get this clicked in a second and then move on to the more value added things of checking things that really put people at risk.

26:09Chad, did he say rooster? Oh, I love checking cock. Ah, yes. I love it. Eaton, maybe number two in the most timely issues today are the ghost jobs. And on one hand, you have companies, and I know this is an issue, they post a job, they get the mass amounts of people apply, and then they close the job down. Which is also another reason why real people are getting screwed is they're not fast enough as the bots to apply to these jobs. But then on the other side of the aisle, you have companies that keep jobs posted infinitum. So they're obviously getting mass applications. Like what? Help me understand why companies would have ghost jobs when you have the problem of so many automated applicants.

26:52Beats me. So first of all, so in that, just like with the candidates, there are really bad players and there are just people doing things that they think are good. So I do think historically companies had regular open positions relevant in order to build talent pools. And that's not a bad idea, right? Right. If I have an evergreen position that I know that I'm constantly needing to hire for it's and today with today's systems, it's great to build out a talent pool of relevant people. And tomorrow I may need to hire one of those. And it's good to already have that. So that in itself is not a bad, in my view, a bad behavior.

27:27If they're real people. But if you're just flooding it with fake applicants, I just. Right. But by the way, today, one of the major issues on the Internet is using fake jobs. and ghosting jobs in order to get personal identifiable information. People, when they think that they're being hired for a job, they're willing to give very, very sensitive information. And that's being used by very bad players. So there's a real issue there of individuals now being worried about, is this the real employer? Can I share my data with them?

27:57Joel Cheesman: So when it comes down to all of this, who is the perfect, other than a LinkedIn, we heard you talk about LinkedIn, And who's the perfect partner for you to get involved with? Are they applicant tracking systems? Are they job boards? I mean, who would actually help you get to that point of no return where everybody has to actually utilize this standard? Anyone dealing with a lot of human capital data or HR data is a great candidate. So that's obviously the HR tech systems, right? The applicant tracking, learning management systems, HR tech systems, student information systems. Anyone who's dealing with a lot of data is a great candidate, either they're outputting data to the individual or they're receiving data to the individuals, right?

28:43Aggregate data. So the National Student Clearinghouse in the United States is an example, right? They hold all this data of all the graduates in the United States, or a majority of them. So aggregators of trusted data, not just data like LinkedIn. Anyone who's dealing with data is a great candidate to help build out this ecosystem. Going back to ghost jobs a little bit, we're starting to see actual state governments try to tackle this problem. In your mind, does government play any role in policing all of these automated and company screening tools? Like, does government have any role? I can't imagine, but you live this every day.

29:18I don't know. Government's always years behind chasing the speed that these things are changing. By the time most governments pick up on this, it'll be irrelevant. There'll be the next problem. You do see, like in Europe with the AI regulations, that there are governments in the world who are attempting to reduce the big problems, not necessarily just relating to recruiting or HR, but that relate to trust and identity and use of AI. And I think that those laws need to impact the work in our space as well, not just be specific regulations for our world.

29:52Joel Cheesman: Yeah, I mean, it would be a very progressive, very progressive and smart, I think, government that would actually come in and embed a standard. I mean, we have standards for plugs, for electricity, for things that I mean, for infrastructure. Right. We have these things. This should be could be basic infrastructure. But guess what, kids? It's going to be it's going to take a minute. It's complicated. It's complicated. It's complicated. And it's orange. Okay, so you heard it from Eaton, man. Stop hunting fraud. Start embedding trust. That's Eaton Bernstein from the Velocity Networks. Eaton, if somebody wants to connect with you, wants to maybe have a conversation, maybe they want to join the network, how do they get ahold of you?

30:35Just check us out on www.velocitynetwork.foundation or search for Velocity Network Foundation on any of your favorite LLMs or search engines. There you go. Chad, it figures you would schedule a guy named Eden right around lunchtime. That is so you, man. And that's another one in the can, too. I do what I can. We out. We out.

30:55Joel Cheesman: Thank you for listening to, what's it called? A podcast. The Chad. The Cheese. Brilliant. They talk about recruiting. They talk about technology. But most of all, they talk about nothing. Just a lot of shout-outs of people you don't even know. And yet, you're listening. It's incredible. And not one word about cheese. Not one. Cheddar. Blue. Nacho. Pepper Jack. Swiss. So many cheeses and not one word. So weird. Anywho, be sure to subscribe today on iTunes, Spotify, Google Play, or wherever you listen to your podcasts. That way you won't miss an episode. And while you're at it, visit www.chadcheese.com.

31:45Joel Cheesman: Just don't expect to find any recipes for grilled cheese. So weird. We out.