[00:00:00] Chris Meador: That's laziness, and I'm sorry. Look, AI is not this magic solve. It's not this magic solve. It can build real value and benefit to your process, your workflow and all that, but it's not a magic button. And this is when I talk about, like, let's just be clear on what AI slop is. It's just not. It doesn't give me my information. It doesn't answer my question. It's not easy to read. It's just not good work. That's all it is. And for some reason people believe, well, it's not my work, and that's just not true.
[00:00:34] Jeff Dillon: Welcome to another episode of the Signal. If you work on a college campus right now, there's a good chance someone handed you an AI tool and walked away.
My guest today has a name for that problem and a practical plan for fixing it. Chris Metter is an AI coach and the founder of Yes and Thinking, where he runs workshops and coaching that help leaders and teams adopt AI with shared standards, real skills, and human judgment. Firmly in charge, his approach starts with people, not prompts. Chris has spent nearly 20 years helping organizations adopt what's new. He led brand and video solutions globally at Facebook during its shift to mobile and video, directed global product marketing for Xbox at Microsoft, served as VP of marketing at Wistia, and held senior marketing roles at NBCUniversal and History. He's a certified executive coach and has lectured at Northwestern and Hofstra and co founded Daisy, a live graph of local events built for people and AI search. Today, we're asking a simple question.
What if you needed a driver's license to use AI at work?
Chris, welcome to the show. Great to have you today.
[00:01:53] Chris Meador: Thanks for having me, Jeff. I'm excited to be here.
[00:01:56] Jeff Dillon: Well, you studied to be an actor, and from your own account you said you walked away from the health insurance. I know that from your theater training. What do you still hold on to when you're in front of a room full of maybe skeptical people about AI?
[00:02:14] Chris Meador: Yeah, I just want to start in the beginning and say thank you for bringing me on and having the AI conversation. What a strange world that we're talking about smart robots that do all these things and these are strange conversations. And so I'm excited to have a. What I hope is a little bit more fun in it because I think there's so many AIs that we can talk about, you know, the AIs that will destroy the world. And I'm not going to talk about those today because I can't touch those. I'm talking about the AI that we're being faced day to day with that we have to figure out how to manage for while it's here. And so to answer your question, I think the first thing I take away from my theater training is, is the ability to just think through what the other person is going through. You know, it's. We call it empathy. But then that feeling, you know, it's. You know, but it's what is stopping them, what is in their head? Why are they not seeing what I am seeing? What is that gap? It's actually why I spent the majority of my career in brand marketing was my whole job was to understand what that gap was between what we thought and what people said. And to me that's where the work is interesting because that's where you need to figure out the plan to move forward. So that's kind of the first skill, but the second skill, which is why I named my company yes. And thinking is we just have to say yes and I'm going to work with a robot. I mean that would have been an office skit from years ago. Come on now. But this is where we're in. And we can't question the prompt that comes after it because honestly, I don't know your age, my age, myself, I've seen a lot of things in my life I did not expect to now live through an industrial revolution. But cool. I'm here for it. And I just think this idea of like how you say yes through them is just the only path forward.
[00:03:58] Jeff Dillon: Yeah. I love that take. I do have you by a few years, I think. And I've written about the connection between all these sci fi movies that we've used to just watch in awe about. Even some of the more the newer ones. But even.
[00:04:12] Chris Meador: Yeah.
[00:04:12] Jeff Dillon: Gosh, like ex machina when newer one. And you know Hal, remember Hal, like this
[00:04:18] Chris Meador: vision quest right now is all about AI.
[00:04:21] Jeff Dillon: Yeah.
[00:04:22] Chris Meador: It's just you realize how there's a lot going on.
[00:04:24] Jeff Dillon: Yeah. And I'll even throw one more out there. The TV series, you know, TV is better than movies now. Almost Pluribus. And I think that's a take
[00:04:32] Chris Meador: on.
[00:04:32] Jeff Dillon: On if AI could be as forgiving as possible. It's still going to be a pretty dystopian world. And it's not directly you got to think of that. Everyone watch that show.
[00:04:40] Chris Meador: I agree.
[00:04:41] Jeff Dillon: So you've had this front row seat to some pretty significant technology shifts over the past couple decades.
What I've noticed in higher Ed is that every new tech comes with these huge kind of expectations. I remember mobile was the thing that no one talks about really. Yeah. Anymore. But getting people actually change how they work is really the harder part. And I think AI makes us feel like we're moving really fast and institutions aren't really keeping up. So you've helped people adopt mobile and video and Facebook and Xbox and Microsoft and video as a core strategy at Wistia. Right. You call AI the fifth big shift. What feels genuinely different this time and what feels maybe like the past.
[00:05:25] Chris Meador: Yeah. The thing that's the biggest difference for me in this technology shift is it's going to come for us all. Every person, every role is going to have some sort of impact, whether or not it's a direct usage or it's being integrated in the product they use.
This is truly this first technology that's going to change all of our behavior just by the way that it's using. And we can even see it today. I always like to say to folks like, how often do you let Spotify create a playlist for you? That's AI. How often do you let Gmail finish an email for you? That's AI.
And I just think we have to be a little more intellectually honest with each other. And I think it starts with first realizing that the conversation that we're having is not the conversation that's having the media right now. And I think about this idea of big AI versus little AI. Big AI is the frontier models, the usage, the breaking out of sandboxes, the fluffy bunny, whatever. Well, you know, I know name is, but like all those funny names of what it does.
It's the AI that will hit us and impact us, but we have no influence on nothing we can do.
[00:06:37] Jeff Dillon: Yeah, you really sprint some thoughts. Because I'm of this generation that I grew up in tech, but I'm on the, you know, I've seen so much evolution. I'm not a voice guy. My kids, all these other young people, voice people. I do not like using voice for anything. I recognize I'm different in that way. But what I'm seeing out there is the, the way we interact with these systems is becoming some of the best AI is embedded into the systems we're already using, just like you said. But even more obviously now I use things like for lead generation, I use Apollo and I'll use HubSpot and just tools on the back end that I would usually go to a filter and say, I want this list, I want to type it in. I Want a black and white answer. And I would never trust asking AI to do things for me in a software. But now I'm using the AI tools within these software platforms and it's easier and it works better. And so there's this differentiate.
[00:07:30] Chris Meador: So I'm going to stop. Do you know why it works better?
[00:07:32] Jeff Dillon: It knows me better.
[00:07:34] Chris Meador: Right, but why does it know you better?
[00:07:36] Jeff Dillon: Yeah, I. So many reasons, I guess.
[00:07:38] Chris Meador: You spent the time to build these platforms, you spelt the time to build your context, you spent the time to give it information, you spent the time to nurture it and help it understand what you do.
So AI is actually not making the guess of what you do. It's an automation that's been built with it. And I call that out because, you know, we're also entering a world and this is maybe for later in the conversation where anyone can build software. And so, you know, that's a truth. But the thing that sits underneath that, which is what I want to call out, is it starts with the information you give. And I think as an educator, and I know educators, obviously, you know, in droves listen to it. I would say that training a model is in a lot of ways, like when you think about a classroom, which is what are the information and tools that you need to give something to then deliver the results that you're hoping that they achieve?
[00:08:28] Jeff Dillon: Yeah, I totally. You're spot on with that. And I think there's this distinction between intentional AI. I'm going to go out and use this AI tool versus embedded AI.
[00:08:36] Chris Meador: Oh yeah.
[00:08:37] Jeff Dillon: And we're all just going to be using embedded AI all the time. And it's. Yeah, like you said, people are using it,
[00:08:41] Chris Meador: but we have to know when we don't want to use it because I'm going to give you. So you gave two examples of where it's great. There are so many platforms that are now charging 50 bucks or more a month or upping their price and the AI experience is lousy and you're now paying that premium. I'm not gonna say what those brands are because I don't wanna hurt your sponsorship opportunities. But like it's in the mass brands I know you and I are actually using right now in our stack. And so that's the other issue we're facing, which is there's also. That's gonna go too far. And so we have to just be aware and smart enough to say, like, do I want that? Do I not want that? And how do I use it?
[00:09:14] Jeff Dillon: Yeah, you better make it work first. Before you make me pay. Because I would never click a button that says pay for another AI tool at this point. Maybe in the future I will because I trust that brand so much and they're so good at it. But,
[00:09:24] Chris Meador: well, they're upping your price slowly, month, month by month and putting in new features that they hope you become addicted to that keeps you in. So the thing that's been interesting is I have a few friends who've moved into that tech space and who came from the Facebook worlds, the metas, the Googles have moved over there.
And a thing that they keep on saying to me is why are the tools for educators not better?
[00:09:46] Jeff Dillon: Yeah,
[00:09:47] Chris Meador: why are they not better? They're like, why have we not built world class technology for them?
And maybe I'm not right to say that I'm not an expert in the space, but that's what I hear. And what worries me is you start then putting in not world class AI features into that, you're going to create a terrible, terrible mess.
[00:10:06] Jeff Dillon: You know what I love about that I have you on the show is that I haven't had many, I would say true creatives. It's a lot of tech people, founders and higher ed leaders. Maybe they're creative, I just don't know it. But a couple weeks ago I had a founder of a creative it's called Common Time Pathways to connect creative students to scholarships. Why don't we recruit artists like athletes? And what I realized working with Aton, the founder over there is that people like you and Aton, the creatives, like an actor and a musician, are going to excel in this new world because number one, you have to be naturally curious. And if you're a subject matter expert and anyone can use these tools, but you have this huge advantage that you can also communicate with people and present better and it comes through. And it's just I'm glad that these people have their time now. So it's exciting.
[00:10:55] Chris Meador: I wish the current you could Talk to the 21 year old version of me when I was a junior at Northwestern. Really like going like I don't, you know, hitting that wall. I mean, I always say I left acting because I realized I needed health insurance. And while that became the real like concern, it was truly the I knew the roles that I would play and the path that if I was successful I would have. And that's not the career I wanted. And as an adult I can say that. But I will also tell you my theater skills have always been the differentiator in my career. And it's always what I said to, I mean I, when I worked in an office, I used to do a bunch of talk back to college students and theater kids will always say like, can I have a career? It's like, oh, you're going to be great. Just you wait. And it's just. And that's, you know, we're in a world where if you can dream it, there is a path to build it.
[00:11:44] Jeff Dillon: Yeah, it's so true. It's so obvious to me now. If you're skilled at communicating with other people, you're going to have this huge advantage. I have been in higher ed for 20 plus years in IT and marketing and many times I've watched schools invest hundreds of thousands of dollars in new tech and they're giving you a one hour training in a PDF. You often point to the stat that 71% of workers got no AI training in the past year. Why do organizations and colleges in particular keep handing people the keys without the lessons?
[00:12:18] Chris Meador: Because everything to this date has been about adapting to the technology versus now in a world where the technology can adapt to us. And so that reverses the process and reverses the path forward. If you think about how we had to adapt to the technology, it started with process.
This is the process you have to snap into.
Here are the people who are going to be the gatekeepers for that process and manage it CRMs, you know, education systems. Think about all the systems, the cloud managers, all there and then people. We're going to help you figure out how to use it.
The problem is that you're in a technology that makes your process better, which means that you have to start with the people and help them understand what's the value that brings to them, what is this going to unlock, what are their values attached to the technology?
Like you have to have that conversation because there are going to be some folks who are going to say I'm never going to use it. And we have to respect that. Organizations might make another call on what that means, longer terms, but that's a different conversation. We have to understand where people are blocked, what they think of so that you can have that conversation. You and I just have, which is the cognitive dissonance. We live in a big AI versus little AI, and if we live in little AI, how do we then make that tool enable us to do something more different and give us time back that we can invest in more meaningful ways?
[00:13:45] Jeff Dillon: Totally on board with that makes so much sense. I love this idea of an AI driver's license because it makes something that's pretty abstract feel practical. You know, I, we wouldn't hand someone the keys to a car without expecting them to know the rules of the road and demonstrating they can drive.
If a university required an AI license before faculty or staff could use the tools at work, what would be on the written test or what would be on the road test?
[00:14:13] Chris Meador: Yeah, digital literacy would be a big piece of it. I have a 14 year old and a 10 year old and for years I have been showing them, I mean, worked at Facebook for years. I, I've been dealing with fakes for a while. I understand this world. Unfortunately, I've always showed them images and go, tell me what this means, Is this feel real or not? We're in that same world again. So I think this idea of literacy, no matter who you are, is important in a lot of ways. Our generation suffers by it more, you know, because younger folks are at least have a better eye to catch that and you can catch it and you have to learn that now because while it's going to get better, there's still always going to be signals.
I think another piece has to start. Then going out of that becomes like what does your gut say?
[00:14:55] Jeff Dillon: Yeah, yeah.
[00:14:56] Chris Meador: Because most people's gut is right to a degree if they listen to it and work with it. I think then the other thoughts are what does it mean to actually drive the car? That's when I talk about this structure that I built out around direct feed, control and own because like how do you drive the car when you go to put into drive, you have to remind them to put your foot on the brake.
[00:15:18] Jeff Dillon: Even the next level you're at a very basic level which is driving. Right. You're 16, learning to drive. Even at the next level of like I feel like I'm behind in AI because I talk to people, like all the people that are so good at it and
[00:15:29] Chris Meador: yeah,
[00:15:30] Jeff Dillon: I talk to some beginners and they'll use it to create ideas and to generate content and.
But they're number one. They're not building their own profile, they're not building on what they've done. I mean Cheryl, to know something about you and you know what's happening I think at a lot of schools is they don't have the access.
I recently connected Claude to my Gmail and I mean it's a couple, it's been a few months but I was always reluctant, like I don't want that, you know, I turned off right. Access. It's not going to send emails on my
[00:15:55] Chris Meador: behalf. Yeah. Yeah,
[00:15:56] Jeff Dillon: but I'm like, I got to do that. I can't believe I did it because a year ago I would say I would never do that. But you know how organized it helped me. And I. So I tell people like, hey, you gotta do this. It's kind of. I think that's basic at this point. But,
[00:16:08] Chris Meador: yeah,
[00:16:08] Jeff Dillon: we can't do that. Our organization, there's no way they're not going to let us do that. There's this kind of resistance.
[00:16:13] Chris Meador: It's a real struggle. So the couple of thoughts I have about that, number one, is it's a builder's world. You have to know what you want to build. And building can be you're solving a need, you're solving a problem, you're building an idea, but identify that thing. So what I'm talking about is basic, but I can take my framework and scale it up very quickly. You want to talk about under control? Let's talk about getting more specific of models of platforms, of how you play them against each other. Where do you want to start thinking about, like building some backend local server, right, for yourself? That kind of outlines, builds everything over. Like that all can get figured out, but it all starts at the beginning.
What do you want to do and where do you want this to fit and how do you build it up? And I think that conversation is not, you know, what I discovered. So I spent the last five months in a hole and by a hole in my office just beating my head against my keyboard to try and figure out how to use CLAW to build a brand, to build a website, to build products.
Not because it would be easy. It would have been a heck of a lot easier to pay someone money to do it. But it helped me understand what the limitations of these are. And the only thing that didn't stop me was I told myself I couldn't stop. I told myself, this is my job. I'm being paid to figure this out. And that was my motivator and that was the need that I was solving for. And I think everyone needs to identify that. And it's easier when you do it on your own, but in the workplace, you have to figure it out as well.
[00:17:39] Jeff Dillon: I have a prediction that the big brands are going to do really well. And there's one in particular that I've never. I've been kind of on the. On the neutral with this brand. And it's Google. Google has always come through and kind of killed it. Whatever they do, it might take them a while, but whether it's launching A browser and taking over the entire market in a few years. Look, I don't use Gemini that much but for image stuff I'm like, I'll go to Google. And now they're embedding tools within the Google workspace that are so easy and free. I'm like, gosh, that works really well. And they have all the data, they have all my, all the YouTube. So I'm just no plug, there's no sponsorship here and they don't pay me. But I just see it's going to be so easy when people already trust this company that I'll just use that AI so they have this huge advantage.
[00:18:24] Chris Meador: I agree. I think there's actually going to be two camps I create out of that. I think they're going to be the ones who say all my data lives in Google already. My ecosystem is there, so let's just use what's there because that what makes sense. And then there are going to be others who are going to say let's actually figure out how I build my own ecosystem. And that's going to start with them building that database of them that Google has inherently through your emails, your drives, your chats. And that is, that's the decision we're all going to have to make individually and corporations. That's going to be the trade offs we're going to have.
[00:18:57] Jeff Dillon: Chris, one of the things I appreciate about your approach is that you're not just teaching people how to write better prompts, you're, you're changing how they think about working with AI. And I think that's an important distinction, especially in higher ed.
[00:19:10] Chris Meador: Yeah.
[00:19:10] Jeff Dillon: Where people are juggling dozens of responsibilities and they don't really have the time to become AI experts. Walk us through using it for a real campus task, like a marketing team drafting a new program, new program pages, an advisor writing, outreach to students who maybe stopped out.
[00:19:28] Chris Meador: Actually the thoughts that come in mind right now is a friend of mine who's an AI expert, just wound up becoming a the head of ergs up at Williams College. I have a lot of colleges around where I live fortunately. And just think about all the ways that AI can help there. First of all, think about the first needing beginning of the year, which is how do you actually bring the leaders of all of those ergs together, help them understand the rules, what they can't do, what they can't do. What if actually you could build a chatbot where they could ask questions into the guide to answer their question that suddenly helps them go, oh, so that you can Help them move forward in that. What if you actually built the database of best practices and said, help me build the best practices for building X, Y, Z new erg. And it could then input that information because you already have the database and tools, you're just giving them a different way to input into it and access the information. But that's tailored to what they need. So that's just the initial thought and what I'm talking about. A lot of it can be you opening up a chat in a Claude code or a chatgpt codex or anywhere else and saying, what if we built this idea? How would we even do that? And allowing the technology to start to run. So I bring that up because what changed and what I think about in my approach is it's about mindset. If you can't help people have a mindset and a framework, then they can't build and they can't grow. You know, it's that visual organizer again. I have 10 and 14 year olds and so we talk a lot about that. And so for me, you know, the first part has to be with like, what do I want to do and how do you start to build that out? And that's why the framework becomes important. So think about direct. Direct is actually about like building the. The brief of what does good look like? What are my expectations? What do I think I want this to do? What do I think I don't want this to do? What do I not want this to ever be? Like nosy are frankly more important than yeses because you don't know what to say yes to, but you know, might know where you want to say no to.
[00:21:34] Jeff Dillon: Totally give it the guardrails. If you don't know what you want, just give it great guardrails. I totally agree.
[00:21:38] Chris Meador: And then spend the time to say, talk me through that. And if you're having a hard time, I am a talker. So you know what I say sometimes? Hey, interview me, give me, ask me a couple of questions that you think would unlock what we're trying to do. Again, my thoughts, it's my brain. It's just I'm trying to, you know, until they develop a pipeline into a computer or a better drug for my adhd, like, you know, this is how I get that information out. So that's why direct becomes important.
[00:22:04] Jeff Dillon: I think it's easy to blame technology when something goes wrong, but really ultimately someone made the decision to do something and they approved it.
[00:22:12] Chris Meador: Yep.
[00:22:13] Jeff Dillon: Having worked in university marketing, I know how quickly a poorly written message can really become A public problem.
When you start scaling across AI across an institution, that potential for mistakes grows really quickly. What I'm getting at is you've said there's no Such thing as AI slop, only slop created by people using AI on a campus. One bad AI written message can land in 30,000 inboxes. Where does individual accountability end and the institutional responsibility begin?
[00:22:44] Chris Meador: So I think a lot about this and I'm not sure there's a line. And the reason I don't. I'm not sure there's a line is I want to talk about corporate America, which, yes, can be a little allergic in maybe this setting, but there's still about a management piece of it that I want to bring in, which is any message I sent from the companies I worked at. I was a representative of the company and I was accountable for what I sent. If the company did not like it, the they were accountable to communicate it to me, to reorient me, to set my expectation if I did not do it right the next time, to accept accountability for it. Accountability, that's ownership. That's a big one. And then from there do it better the next time.
I think that cycle's broken a little bit in higher ed. I see that right now. I do guest lecturing. I do other work. I think that, you know, we have to be more open to say, this was a mistake, here's how we do it better the next time. And that's why I think about this idea of that line is the individual, they are the voice of the university. And the university is responsible for making sure that they are the right voice. And those two have to work together. And if they are not working, then that's a problem.
And I believe there are software solutions to get it there. You're seeing this play out more and more is team workspaces. Team workspaces, where everyone is using.
Think about a model being built into an interface where suddenly if you're in marketing, you can say, here's what I'm doing, here's all the rules. I played with all that. Hey, Legal, please look at this. It's being reviewed actually by Legal's own bot before it goes to the person. And then you're actually then being able to get the quick alignment there and going like. And then the ica, I approve it go out. The first time might be tiring, but then once you can systematize it, it moves faster and it's easier and it's more in line.
[00:24:33] Jeff Dillon: Yeah, you have to spend time setting it up. The Right way. Like, if we get lazy, all of our outputs are going to get lazy. Back in the day, one of
[00:24:41] Chris Meador: my
[00:24:41] Jeff Dillon: most embarrassing faux pas in marketing was sending out an email. I was in charge of sending the campus emails out for some different scenarios. And in the subject line, the word president was spelled wrong. S and the I were transposed. And someone above me didn't catch it either. But I mean, I was just, oh, it was a horrible day. What a minor thing. Looking back on it now compared to, like, what happens with the stuff that goes out the door now with AI and like a whole paragraph is based on a wrong premise and no one looked at it. Or like
[00:25:08] Chris Meador: the
[00:25:09] Jeff Dillon: word extraordinary is listed like six times in a paragraph. You're like, that sounds like AI.
[00:25:14] Chris Meador: Yeah, well, that's laziness and I'm sorry. Look, AI is not this magic solve. It's not this magic solve. It can build real value and benefit to your process, your workflow and all that, but it's not a magic button. And this is when I talk about, like, let's just be clear on what AI slop is. It's just not. It doesn't give me my information, it doesn't answer my question. It's not easy to read. It's just not good work. That's all it is. And for some reason people believe, well, it's not my work. And that's just not true.
[00:25:45] Jeff Dillon: It's so clear to me too. Like when you're using AI to write, if you do have it, write your first draft. If you're that bold, you better be putting a lot of edits in in on that. Like, it's just a starting point. Everybody, when you're, when you're doing things like that,
[00:25:58] Chris Meador: or it's a review point, like it's a multiple point, however you need it. But this is where I go back to mindset and you asked the question earlier. Where would people start is don't start with what the job is. Really break it down. Like, what are my tasks? What are my micro tasks? What are my steps involved in getting this done? And then think about, like, where do I start to put in AI to help me in this?
[00:26:23] Jeff Dillon: Yeah. And at the very least, president should not be spelled wrong, right. I'll have a check for grammar. You know, implementer and I should not have that. I mean, AI can save you in that way every time.
[00:26:33] Chris Meador: Well, but here's an important one. You'd have a bot that actually has the name, spelling of everyone correctly. Because those things just get mixed up. That would then go through it and make sure everything was corrected, because that's a very specific thing. And you can very clearly give the very single data that needs to be changed. And so that's a black and white
[00:26:50] Jeff Dillon: change.
You know, one thing I've always believed is that you learn a lot more about technology when you actually get your hands dirty with it. And like you're saying you're building something, you're making yourself, you know, use it. And there's a big difference between using a tool someone else built and trying to build something yourself.
You're building Dottie, I think a personal AI context layer.
[00:27:12] Chris Meador: I'm building too many things. I'm building so many beautiful things. It's great. Yeah. So one thing I'm building is Dottie, which is when I talked about that idea that I think there's going to be two camps. There's going to be the folks who go all in with Google and use everything related to it versus there's going to be the folks who want to own their own data and then bring in different software tools into it. I'm building that context layer for businesses and individuals to be able to do that. And to me, context is how I work, how I think, my style, what are the hats I wear, what is all the data that's coming in across emails and audio in terms of transcripts of conversations and meetings and calendars and all of that? And then how do I just use that data in order to have it structured? So. Or how do I structure it so that can be used by myself, whatever tool I attach to it?
[00:28:05] Jeff Dillon: Well, Chris, I want to bring this back to this idea. We started with this driver's license. We talked about training and accountability and human judgment and what it really takes to help people use AI responsibly. I think one of the takeaways from this conversation is that universities don't necessarily need everyone to become an AI expert. They need people to understand the power and the limitations. If you could put one rule of the road on the dashboard of every faculty and staff member of their AI tool for their AI tool next semester, what would that say? And where can listeners find you in the work you're doing at. Yes, and thinking,
[00:28:43] Chris Meador: yeah, I mean, I would implement two hours of guided play. I think they're very smart people. I don't want to give anyone more tools or more lessons.
I think if more people got into a room with each other and had someone there to help guide them through what can we go build, stop and play for two hours and Just play for two hours. Let's see where that goes.
[00:29:08] Jeff Dillon: I love that. Maybe you asked to report, like next week we're gonna go over what we worked on.
[00:29:11] Chris Meador: Well, there's so many places you can go for it, but I think that you asked for the basic.
My basic would be figure out a way for everyone to get two hours to play, to really play, to be. To be and help and tie and whatever format that is. Because that is going to be the thing that unlocks the folks with their who want to play. And it's going to help you get a view of your organ, is going to help you understand where you are and where you want to go. Like that.
[00:29:39] Jeff Dillon: Yeah.
[00:29:40] Chris Meador: And then where folks can find me. I mean, I named my company after an improv technique. Yes, and thinking.
Yes and thinking. Com. I was amazed it wasn't taken when I bought the domain years ago. But I bought the domain in, what, 22 and then realized, oh, oh,
[00:30:03] Jeff Dillon: that's great. I love it. We'll put links in the show notes so no one has to jot that down or anything. And we'll have a link to Chris's LinkedIn as well. So, Chris, it has been a pleasure talking to you. Such an interesting perspective and I really enjoyed it. Thank you.
[00:30:19] Chris Meador: Thank you for having me. And thank you for having this conversation. This was a blast.
[00:30:22] Jeff Dillon: All right, bye. Bye, everybody.
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