You also don't have to be an expert to go and sell these services. Your clients that are paying you $50,000, $100,000 for an engagement, they expect you to be an expert. I just have to be literally one week ahead in terms of knowledge for those people to trust me and to be able to do a good job and deliver ROI.
SPEAKER_02Let me ask you, are you a vibe coder?
SPEAKER_00Yeah, definitely. I'm I'm an aspiring vibe coder and I have no technical background. I got an F in computer science one, but I was still able to figure this stuff out.
SPEAKER_02Nobody wakes up thinking, oh, I need an audit today, right?
SPEAKER_00Right. We actually call it an AI tools assessment.
SPEAKER_02Interesting. But the people that you're talking to, what is the ideal state or the ideal outcome from this assessment?
SPEAKER_00We have a guarantee around it too, right? So the guarantee is hey, if we can't identify at least five hours per week in time-saving opportunity based on what we find in the report, where you implement AI, save at least five hours a week, then we will refund 100% of your money.
SPEAKER_02What is the realistic discovery? Like what are people typically coming in at?
SPEAKER_00So the average is about six hours per week in opportunity. So if we prescribe, say three tools, the average tool cost total across those tools is gonna be $40 a month. If you get nothing else out of this other than this, is to create.
SPEAKER_01Corey Ganem is helping non-technical business owners cut through the AI noise, uncover hidden automation opportunities, and use practical tools to save hours every week.
SPEAKER_02Welcome to Using AI at work. I'm your host, Chris Dave. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, ChiefAIOfficer.com has the answer.
SPEAKER_01We give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day-to-day.
SPEAKER_02We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company-wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs, and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI. Hi, everybody, and welcome to another episode of Using AI at work. My name is Chris Daigle, and I'm the host. And rarely do we have the opportunity to be in the same room as the guest. Last time we had that was probably episode 30 something, and we were at our studio in Bastrup, Texas, which is just outside of Austin, the home of Starlink and uh Boring Co. Elon's, and I guess now X. So this is a podcast where we aren't necessarily talking about theory, we're not talking about I've got this great idea. We're talking to people who are doing the thing. And that seems to be kind of like the the common universal element of all of our guests. And today, no different. Um uh Corey Ganem is our guest, and we'll be uh introduced, letting Corey introduce himself in a second, but I want to give everybody a backstory. So um in February of this year, beginning of February, I guess it was, I was uh had the opportunity to go to Fort Lauderdale and some uh big uh, you know, Pablo Escobar Tony Montoya kind of mansion with about 30 other early uh AI founders, fantastic group. And one of the individuals that was there is our guest today. And um pretty quickly I realized, okay, there were still some people that were kind of exploring that were in that room. How they got in there, I don't know. But Corey was one of those people who was actively touching, breaking, bending, seeing what was working, what's uh, you know, what does it take to make this viable for a business and that sort of thing. And um left, paid attention to what he's been putting out, and his content is very accessible and uh, you know, like certainly good for all levels of individuals who are wanting to discover how do I use AI at work. Um, so before we get into the conversation, uh Corey, welcome to the show. Thank you for taking the time out of your day. And maybe just um we'll pull an Eisenberg. What do you want people to walk away from this episode with?
SPEAKER_00Yeah, Chris. So first of all, thanks so much for having me. And I I do really enjoy getting to do these in person too. I feel like it's a totally different vibe than than online. So yeah, I can I can go into my background, but as far as what I want people to get out of this, I mean, if anything, just a better understanding for how AI works, which tools uh are working at this point in time, right? We're May 2026, that's always gonna change, but uh also the underlying principles. Like the tools are gonna change, but then there's certain principles, certain ways of using AI and applying it that I think is never gonna change. And then, as well as, you know, I'm sure we can go into the AI assessment business model, why that works, why it can be sold as a service, whether you're starting out or you know, all the way to the highest levels. I mean, something you guys are are actively doing in your business is assessing businesses and telling them where they can implement AI. So there's a lot of different directions that we can go, but I think first principles is a good place to start.
SPEAKER_02So let me ask you um, are you a vibe coder?
SPEAKER_00Yeah, definitely. I'm I'm an aspiring vibe coder. So I I know I I know how to be dangerous with you know codecs and clawed code, and I've used all the agents, whether it's Claude Cowork or OpenClaw or more recently, Hermes. I spent the whole morning configuring some new Hermes agents. Uh, but yeah, I I know how to vibe code with and I have no technical background. Like I literally, I tell people this all the time. I got an F in computer science one, my freshman year of college. And, you know, so if that tells you enough about my technical background, hopefully it does. But I'm I was still able to figure this stuff out.
SPEAKER_02So let me ask you, are you an influencer?
SPEAKER_00I don't really like that word.
SPEAKER_02I don't like it either, but like how do you describe the impact that you're having?
SPEAKER_00Because I when I hear influencer, I feel like you know, I feel like or just like hot girl who's like peddling uh like a makeup brand. Yeah, but like so I don't know. I guess if you want to use that term, that's fine. But I mean, really my goal with well, one, with content creation, I do it because it's fun and I genuinely enjoy it. Like that's one thing that I really enjoy throughout my week is you know, if I come up with an idea for, oh, like this post, this would be a good idea, or this would resonate, or this would really help somebody, I'll like file it away in a notion document and then sit down one day and just create all the content, right? So I enjoy it. Um, but in general, I feel like it's I feel like I have a teaching, I guess, spirit for lack of a better term. And I feel like I have the unique ability to convey things in a way that's easy for people to understand. So I feel like I'd be doing people a disservice by keeping it to myself. And so the fact that I enjoy it, I think, is kind of the icing on the cake.
SPEAKER_02So content creation, especially with AI, like like it's nothing has a long shelf life, right? Right? It's gonna go stale within a week or a month or whatever the case might be. So what are you are are you creating the content as you're exploring the tool, a new tool comes out, hey guys, I'm gonna check this thing out, kind of thing? Are you getting your chops with it first and then saying, hey, this is what this is what I like about it, this is what I don't like about it? Like for somebody for our audience, if they're not familiar with you and they want to start consuming your stuff, which I do, right? And one of the things I like about the way that you put it out is I don't have time for the big, the big things, right? But you're giving very good like TLDRs or executive summaries of this is what the tool is, this is how I'm using it, here's a few ideas, and I find that type of content very like boom, got it, on to the next one. So, what is the the content creation process look like for you? And how do you integrate it into what like the deliverables that you're doing for clients?
SPEAKER_00Yeah, so I think one or at least how I approach it is I like to be, you know, I like to obviously know what I'm talking about before I go out there and talk about it, but it's like what's the minimum amount that I could have used this tool or done with this workflow to be able to talk knowledgeably. So for example, like Claude Design just came out, you know, a month ago at this point. And I purposely didn't put out anything about Claude Design on day one or even day three because I hadn't used it yet. So I waited until I had at least uploaded a brand kit and built, you know, one or two slideshows before talking about it. So I guess the, you know, the moral there is like I need to know enough to be dangerous, but that's a lot like a lot less than most people realize before I go out and talk about something or try to teach it because of how quickly, you know, how how many things are coming to market on a weekly basis and how stuff how quickly stuff's changing.
SPEAKER_02Yeah. You know, I when I'm in person with clients and they're asking about tools, I take them to there's an ai for that.com.
SPEAKER_00Oh, I tell people I'd plug that site all the time. You would think I was an affiliate. Yeah.
SPEAKER_02The reason I do it is to show them how many tools are out there. And their database, last I checked, which was last week, was like almost 50,000 tools.
SPEAKER_00And it segments it by industry, right? Yeah. So that's pretty cool.
SPEAKER_02If you haven't checked it out, audience, go check it out. It's good.
SPEAKER_00Yeah, I tell people that all the time. Like, you know, when we do when we do assessments, for example, for clients, you know, obviously we prescribe very specific tools for their workflows. But a lot of times I encourage them. I'm like, look, we found these tools on there's an ai for that.com or futurepedia.io is another similar, basically competitor.
SPEAKER_02It'll be in the show notes.
SPEAKER_00Yeah. Yeah. And it's like, look, if you, you know, the tools that we gave you are great and they're gonna help with what you're doing specifically. But if you're just curious, if you want to know what else is out there, go poke around for yourself and go sign up for the free trials or you know, sign up for a month and test it out. I mean, there's you could you could go two lifetimes of testing AI tools at this point.
SPEAKER_02And by the time you finished, all the ones that you had already tested were new again.
SPEAKER_00Right. And that's why I think it's important too, is like I think you need to talk about these tools and start putting out content before you're like truly a quote unquote expert, because by the time you feel like you're an expert, either the tool is outdated or it's changed completely. Like it's almost like you have to get to an MVP level of knowledge and then immediately start talking about it, or it's you've kind of lost the opportunity.
SPEAKER_02So for the listener, the takeaway for that, and I feel the same way, like you don't need mastery with any of these tools. They're designed to be easy to use. But also, if you're like, if if you see something, you don't have to get 10,000 hours on claw design to be able to put it to work after two or three sessions. And if you listen to other podcasts and they're talking to the, you know, the tool expert, I was listening to one the other day and a big name podcast, and guy was like, Yeah, I've been using it for three weeks. Right now he's doing like a big podcast. So as a listener, I don't want you to think that it takes a lot more than that. Once you, once you've got like like get your head right about thinking in AI, we call it right. That like please don't please don't think that there's some big learning curve. Use the tools.
SPEAKER_00And another way to look at that too, right? And you know, obviously you, you and your team, you guys are experts. You guys have been in the weeds of this stuff for a long time, like well before it was cool, even well before Chat GPT. But a lot of times, like the the demographic that I'm speaking to are these people that are newer to AI or they're newer to selling services or being a consultant. And the the point that I I try to drill into their heads is like, look, yeah, you don't have you certainly don't have to be an expert to talk about this stuff or create content about this stuff. You also don't have to be an expert to go and sell these services, right? Like, you know, your clients that are paying you $50,000, $100,000 for an engagement, they expect you to be an expert. But when I'm out there selling, you know, an AI assessment to a small business who who has never used Chat GPT, I just have to be literally one week ahead in terms of knowledge to for those people to trust me and to be able to do a good job and deliver ROI. I actually had somebody push back on that last week. He was like, Well, I don't, I don't agree that you know, I think you need to be an expert before you sell these things and before you do these things. And I'm like, dude, you're you're wrong. This is an industry that it's so new that there are no true quote unquote experts. Yeah. So, you know, if you put in a week, if you know how to build a clawed skill, if you know how to create a context file, if you know what markdown means, like all of these things that are so basic and take you 24 hours to learn makes you qualified to sell and to talk about.
SPEAKER_02You know, it's a couple of things. It's interesting because we've been training teams for three years now, I guess. And the expectation was that they could prompt, right? Now, sure that that's helpful, but now the reality is that if a a knowledge worker, staff level knowledge worker that doesn't know how the basics of maybe clawed code, maybe co-work, maybe code, like if they don't know the basics of that stuff, if they don't know whether or not they ever run clawed code from the terminal or anything, if they don't like if they've never seen that before, like I would say that the the baseline for me to qualify somebody as a capable staff level person has risen a lot just in the past three or four months.
SPEAKER_00Yep, 100% agree. And knowing the right tool for the job too is kind of one of the like a point that you could draw out from what you just said. I think that is as valuable of a skill as any right now, is knowing which tool to use for the job, right? Like, for example, there's there's plenty of little scenarios where it's just a you know, one input in, one output out scenario. And it's like if somebody wants to go and automate that, creating a clawed skill might be overkill, right? That might just be a simple zappier zap, which is not even an AI workflow. It's literally just a workflow automation. And then there's things that are more uh technical or more complex, and then for those workflows, it's like, well, what makes more sense here? Do we turn that into a skill? Do we turn it into five individual skills with an orchestrator skill that calls each five in parallel? Does it it should it be a clawed code routine? Or do we do we build this in codec because of XYZ? Right? Like there's I think certain decision-making points that again, if you haven't been in the weeds and you don't know what each tool can do, it's harder for you to make those judgment calls. So you just either you freeze and you don't do anything, or you make the wrong decision.
SPEAKER_02So for those of you listening, if you're not familiar with this concept of a skill file or a skill.md file, um, it's kind of like for us, we did a lot of work in chat GPT for a number of years because it was the better model, right? Yep. And we built so as a result, we built a lot of custom GPTs that were uh in the SOP environment. Hey, this is how this is how the company wants it done. Use this as your your copilot, your guide, right? Yep. And then uh we kind of made internally, and clients even made a switch to Claude over the past several months. Now I'm kind of going back to GPT 3 5.5 a little bit, but um uh skills are essentially you can use them the same way that you would a custom GPT. Set instructions, anybody can call it and get you know a likely result.
SPEAKER_00Yep, and the kind of how I explain it to people is so a skill is kind of like a recipe, right? And so for people who are listening, if you're familiar with the concept of an SOP, a standard operating procedure, a skill is kind of like an SOP where it's hey, this is how we do a task, right? It's this is the checklist we're doing that task, and a skill just turns that checklist or turns that recipe into a repeatable process that you can just hand off to the AI. So it's like we turn the SOP or the recipe into a skill, and then we hand that skill to the AI agent, and then the AI agent can go and execute that skill. And what's cool about skills is that the AI agent is gonna do that process the same way every time, right? There's there's no deviation. Whereas if you were just to prompt it, or if you were to, you know, just do it from scratch every time, it might get a step wrong, or you might forget to include step seven, or you know, more is left up for interpretation.
SPEAKER_02Yeah, or if you're just leaving it up to the individual to be like, oh, I I don't need a list.
SPEAKER_00Yeah, or I can just I can just prompt it. And it's like, well, that's yeah, skills are just more efficient. And from like a token use perspective, too, right? It's it's way more efficient to just for the AI or the LLM to just call a skill, it knows exactly what it needs to execute, it does it the same way every time, it's just cheaper overall, too.
SPEAKER_02You know, man, and you bring it up like another thing that I hadn't heard of or really wasn't a big deal, even just maybe two months ago, a month ago, was token budget. Yeah, right. Like, and all of a sudden if you're training these people, like you're going back to that concept where I said at a base level they should know how to do this stuff. Well, if they're doing that stuff, they're probably plugging into an environment where tokens are getting burnt. So now all of a sudden you've got all these people that are creating all these experiments that cost money, not the $20 a month subscription, costs real money. So kind of explain to the listeners why this token budgeting matters and what like what can happen. What's the downside of yeah?
SPEAKER_00So again, for the the folks in the audience here who maybe you've been on a free plan or you've been on like a $20 a month Chat GPT or Claude plan, and you've never run into it's called a rate limit, right? And all a rate limit is is it's basically you ran out of your usage for your subscription. So when you run out of usage, you have to wait a certain number of hours or a certain number of days for your usage to reset. Once it resets, you can start using the AI again, whether it's Claude or Chat GPT. And so, you know, how do people run into those limits? I mean, simple enough, they're just they're just using it a lot, right? And why is that important? Because a lot of times people are using the AI in a way that's not token efficient. So for example, and I I was guilty of this early on when I didn't know any better. I'm sure a lot of people, their default way of using AI is they just have one long chat thread, right? So it's like anytime I need to ask Claude a question or ChatGPT a question, I just ask it in the same thread that I've asked at a hundred other questions. And the issue with that is every time you ask another question in that chat or you put another prompt in that chat, is it has to go back and process every other earlier prompt in that chat all over again. So, you know, by the time you get 10 prompts deep in a single thread, it's having to process 10 prompts every time instead of just the one, right? Your most recent question. So, like the the takeaway for the audience, that's probably the simplest thing you can stop doing to save tokens is every time you, you know, you switch topics or you log into Claude or ChatGPT again, just open up a new chat. And you know, I I I'm not gonna pretend to be like an expert on token efficiency or you know, these micro optimization strategies. But overall, it's like I tell people you don't need a higher tier plan. Like a lot of people, they start off with AI and they're like, oh, I'm just gonna get the $100 a month plan or I'm gonna get the $200 a month max plan. And I'm like, that's not necessary. Like just start off with the 20 a month. And once you start hitting rate limits consistently, then upgrade to 100 a month. And then once you start hitting rate limits consistently there, then upgrade to 200. But you know, you only want to, I guess, upgrade when you need to. I feel like a lot of people are so gung-ho, they want to go like max plan from the start.
SPEAKER_02So great advice for sure, with that nobody needs that mega thread that's got everything from vacation plans to.
SPEAKER_00Yeah, that's how I used to do it.
SPEAKER_02Yeah. But so if you're an active user, I guess this makes this is where projects would make a lot more sense. Where listeners, if you're not familiar with it, a project is you know, multiple chats around a certain subject. And it's not necessarily calling the context of every chat, but if it needs to, if you prompt it to go out there and like evaluate what it's done, you've created this kind of contained memory on that subject without the mistake of this massive uh token eater of a thread.
SPEAKER_00Right. So one again, the way that I like to describe projects to people, and so again, just to kind of differentiate. So ChatGPT has what are called custom GPTs and Claude has something that are called projects. They're the same thing, right? They're just ChatGPT's version is called custom GPTs, Claude's version is called projects. And so what I tell people is think of a project or think of a custom GPT as just siloed context, right? So for example, I'm a big fan of Russell Brunson. I know you're familiar with Russell Brunson. So I wanted to create a Claude project that's basically Russell Brunson's brain, so that way anytime I ask a question inside that specific project, I'm getting the an answer based on Russell Brunson's teachings or his content or whatever. So how I set that up is I took PDF copies of all three of his books, expert secrets, traffic secrets, and um dot com secrets, and I turned those PDFs into, I think it was like 11 or 12 individual context documents. So basically, Claude took the full you know, PDF transcripts, chunked it down into these individual uh context files, and then I saved those context files as the what are called the project knowledge inside that project, right? So you've got the project knowledge, which are the context files, and then to tie it all together inside the project, you're inside the custom GPT, you can add what are called project instructions. And all that is is that's like the the system prompt for the project. That is what tells Claude, hey Claude, here are the 11 uh context files that are inside your project knowledge for this project. Here's what each one means. Here's when you would use each one, right? Here's what each one does. It's what ties. Everything together. So once you have your project knowledge and then your project instructions, then every time you ask a question or put a prompt inside that specific project, it's going to function based on your project instructions and based on the context documents that you gave it. So now, for example, inside my Russell Brunson project, anytime I go to write a new email sequence or fix my positioning or write a landing page or anything like marketing direct response related, I always do it inside that project because it will give me the output based on the uh you know the project knowledge, all the Russell Brunson information. And it will reference it specifically. It'll say, hey, you know, you need to write the email sequence like this, because this is how Russell structures his soap opera sequences. Or this is how Russell, you know, leaves a cliffhanger at the end of each email to get somebody to open the next email, right?
SPEAKER_02Yeah. So a couple of things that I'm taking away from that. I wasn't using project instructions like that. So how I'm seeing this as you're describing it is almost like a skill file where you open up the folder and it's like, here's the instructions, here's what's in this skill, use this if you need that. So it's almost like a same mechanism, right?
SPEAKER_00Except almost like a broader skill, right? Where a skill is for a very specific business process. Like, for example, I could have a skill that writes email sequences, and I do, but if I use that skill inside of my Russell Brunson project, it's going to kind of take into account like, hey, here's like the strategy behind this email sequence, which is going to be at the project level. And then the actual, like physically writing the copy is going to be done by the skill, right? That's like the very specialized this is how, you know, this is the subject line we use. This is all the various pro uh process specific information is going to be handled by the skill.
SPEAKER_02So you mentioned three books, but you turned it into 11 context documents. Why?
SPEAKER_00Because Claude told me to. I uh yeah, so I went into Claude and I said, like I literally, when I was coming up with the idea for this project, I told it exactly what I wanted to do. I said, Hey, I want a project that is my Russell Brunson brain. And I even asked it, I said, Well, hey, I have a PDF copy of each of his books. Obviously, they're like 250 pages each. I it was like, Claude, can I just include these three PDF files as the project knowledge? And then you can just use that. And it was like, well, no, that would actually be a bad idea because for one, you're you're asking Claude every time it gives you a response, it's gonna have to read, basically read three books and then give you a response, which is going to eat up your entire context window in one prompt. And two, it's obviously going to be very expensive. So the the 11 or 12 context files are what Claude recommended. It was like, well, hey, based on you know the content of each book, we need these context files. One is like positioning, two is email sequences, three is you know, your ICP, right? And it kind of just broke it out. Yeah, yeah. And then I approved that plan and I said, okay, that looks good. Here are the books, right? Here are the PDF copies, generate the context documents. And it did it one after the other. It generated the 11 or 12 individual markdown files to where all I had to do is just save those and then upload them to the project knowledge inside the project.
SPEAKER_02Did you review them?
SPEAKER_00Yeah, for sure. And like, I mean, I didn't read everyone word for word because they are pretty lengthy, but like at a high level, I was like, you know, it gave me the plan. It was like, hey, I think we need these 12 context documents. And I was like, okay, based on what I know about Russell, like that makes sense, right? So I approved that, and then it started, it built them one by one. And like the first one I read through, and they're all pretty, they just take his concepts and just segment them, yeah, is essentially what it's doing. So yeah, uh, it's it worked really well. And I I use that project every week.
SPEAKER_02Yeah, I bet. So when we were teaching, I guess, new users about AI, we teach them this concept. I learned it from my buddy Mark Moss, but it's 1080-10. The first 10% is you being clear on what you want, next 80% is after you hit enter, the model does its work. Final 10% is you putting, you know, like making taking it from synthetic to authentic.
SPEAKER_00Yep.
SPEAKER_02Right. How much how much 10% on the back end are you doing once you've because this is a big investment of time and thought and building and all that? How much better is the output than if you obviously you're saving time because you're not having to reintroduce how you want things done, but are you spending less time on the the back end?
SPEAKER_00I'm definitely spending less time on the back end. Yeah. So, like, for example, right, to use that email sequence example again. So that like I had that project, that Russell Brunson project, I had it write an email sequence that it was a five-day sequence that goes out to anyone who downloads uh one of our lead magnets, right? Our our the template for how we deliver the AI assessment. So, you know, I gave it a simple prompt, essentially, hey, here's what the lead magnet that somebody's opting in for. This is what they get. This is our offer that I need you to CTA in the fifth email. Write me the email sequence like Russell would write it. And then, you know, 60 seconds later, I have a full five-day sequence. And so that, you know, the 10% was me specifying more so just like here's what our offer is and here's what somebody's opting in for. So make sure the email sequence is relevant. It writes the whole sequence. And then when I go to transfer that into our email marketing software, really the only changes that I'm making are around like formatting. And I mean, there's some, of course, I read every one, like that's something I'll read beginning to end. And there's some sentences where I'm like, this is redundant, or this sounds kind of weird, like I'm just gonna rewrite it. I'd say I spend you know, five percent of my effort actually critique on the back end, yeah, yeah, you know, dialing things in. I could have shipped it unchanged, copy-based, but it just it wouldn't have felt right.
SPEAKER_02It's good to know that if you needed to copy.
SPEAKER_00Yeah, you I mean, I yeah, you absolutely could, but you'd get away with that. And another, I mean, another reason that I think that works, at least for my setup, is because I have a really strong underlying brand voice skill, and that's something that everybody needs to have. Like if you're listening to this, if you get nothing else out of this other than this, is to create a brand voice skill. And so all that is is it gets called anytime Claude or Chat GPT needs to write something that sounds like me. Anything from an email to a marketing material to a tweet to a whatever, it uses the brand voice skill. And you know how that works is, and you can ask Claude, like, hey, interview me to put together a brand voice skill. But essentially at its core, it's like, hey, this is how Corey sounds. These are words that he likes to use. He's concise, he's to the point, he doesn't beat around the bush. These are words that he never uses. And the reference files for that skill are five of my podcast transcripts. So like I could go and take the transcript from this podcast here, give it to that skill so that it has the most up-to-date, essentially, way of how I talk, right? As well as written examples. So it's like, hey, also in those reference files are 10 of my best LinkedIn posts or 10 of my best tweets. And so that way it has a really good idea of one, how I talk because of the podcast transcripts, two, how I write because of the social media posts that it has access to.
SPEAKER_02You know, I did so 100%. We're gonna talk about your audit and how that one particular document is part of that. What I did was I had um one of the models I said, look at the last 50 Slack messages that I've sent. Yeah, right. Because my style is not formal. Um I if I gotta be formal with you, uh you know, we'll do the ceremony, but that's not gonna help either one of us, right?
SPEAKER_00Right.
SPEAKER_02So my style is very casual, and um I had it to do that, and then it built out what it saw was my style, and now like that that's the document that I'm using, it's nailing it. So for those of you that haven't done this, we're gonna talk about it in a second, but good idea. So, with that, let's talk about you've you guys have kind of hit on a um uh a hot point with these audits that you're doing. So, talk to me about like what you've discovered with that, who's interested in it, what do they do with the information? What makes a good audit? Just kind of like the whole like because this is obviously something you've you've dived into. Yeah. So I want to hear your your expert perspective on this paradigm.
SPEAKER_00Yeah, so I'll kind of tell you how it came about first and foremost. So I was having lunch with uh two friends of mine, both business owners. This was probably five or six months ago at this point. One of the guys, he's a very successful commercial real estate broker, and because of that, he's very busy, right? They're always, you know, he runs a fund, he's they're listing properties, he's got a bunch of agents under him, but he really wants to use AI and he knows he needs to use it, he just doesn't know where to start. So he was like, he kind of made it, it all started really with an offhand comment that he made at this breakfast. He was like, Man, Corey, I wish, I wish I could just pay, he's like, I'll pay you a thousand dollars to just come into my office and just follow me around for the day and tell me where I could be using AI. And and he like, and I know he meant it, if I would have said right there, like, okay, I'll do it, like he would have cut the check. But like it kind of it literally, I will never forget that because I'm like, hmm, if he feels that way, right? If he's having an issue, then chances are there's so many other business owners in his position who feel the same way. So I didn't take him up on that just because right off the bat, I'm like, sure, that'd be great, but like that's not scalable. So yeah, if anything, if I want to run with this idea from the start, I need to figure out a way that allows me to do this without being on site, you know, with a client every day. So that led to the first iteration, which funny enough, was asking clients, like, hey, we're gonna add you to our Loom account, and we're gonna have you hit record on Loom on your screen while you work for 90 minutes, two hours, three hours, whatever. And then we'll take that recording, feed it to Google Gemini, which is the only model that can trend that can analyze video, and have Gemini tell us, hey, based on how they're working, these are the opportunities for improvement. That's a nugget. Right. We'll come to find out there was a lot of friction there. People don't, you know, they're hesitant to record all their actions, or you know, they're self-conscious that they're scrolling Reddit or whatever. So there was friction there. So we're like, okay, well, what if, what if instead of having them record their screen with Loom, we just did like a 45-minute Zoom call with them, and we can create a question bank designed to pull out their pain points, right? Almost like a, you know, an interview, but the the goal of the interview is not to prescribe or tell them what they can fix. It's literally just to diagnose, right? It's where can you save time? Where is work piling up? What have you tried to automate in the past that failed? Right. So we we've kind of developed this question bank that allows us to really efficiently pull out a bunch of opportunities for AI in a 45-minute call. So that's the current iteration of the model. We've actually built a voice agent that can do that that piece. But I've done a lot of those interviews myself with business owners. So we conduct the interview, whether it's me or the voice agent, we take the transcript, and you know, to simplify it, I always tell people we just give it to Claude, have Claude go research off-the-shelf AI tools that they can implement to you know fix some of those pain points. And then we prescribe those tools. But it is a little more detailed than that. It's not just a simple prompt. We built actually a series of skills that do a very uh you know thorough deep dive to find the exact tools that meet their needs. So we, you know, we find the tools and then we compile that into a report. And this is not just like a Google Doc. This is like a, it looks like a five to $10,000 Mackenzie deliverable that we built in a tool called Gamma. Yeah. So we you know we put that into a report that's basically, hey, here are the three to seven biggest bottlenecks that we identified. Here are the three to seven AI tools that can fix those bottlenecks. And then we schedule a 30-minute review call to go over it with them, right? And the purpose of that review call is twofold. One, we're sharing our screen and going through the report line by line to make it so that so that they understand the opportunity. It's like, hey, you said you had pain point X. Well, here's tool Y. This is how much it costs, this is exactly how it can help your problem, right? So that's part one is we're trying to actually help them with their problem. Part two is that's uh an upsell opportunity. Yeah, right. So that's where the client, you know, they're like, well, hey, this is great, but I'd love if you could just, you know, help me out. Can you just do this for me? Or a lot of times we'll uncover bottlenecks that it's not it's not simple enough to where, hey, an off-the-shelf tool can fix this. It's like we can help, but it's gonna be more of a like, we need to build an agent or we need to integrate XYZ AI tool here. It's not just a download. And so that gives us a lot of opportunity to upsell additional services. So that's really the model in a nutshell.
SPEAKER_02So nobody wakes up thinking, oh, I need an audit today, right?
SPEAKER_00Right. And we like to call it an assessment too, because a lot of you know, businesses when they hear anybody when they hear audit, it's like immediate turnoff. Yeah. So we like to refer to it as like, hey, it's an AI. We we actually call it an AI tools assessment.
SPEAKER_02Interesting. Yeah. So we we we I don't uh talk to the sales team, I guess, to get the latest language, but I think we call ours an opportunity audit.
SPEAKER_00Okay. That's definitely better than just like AI audit.
SPEAKER_02Yeah. So, but what are people the people that you're talking to, they're what are they wanting? What what is the what is the ideal state or the ideal outcome from this assessment?
SPEAKER_00Yeah, so and good question. So we have a guarantee around it too, right? So the guarantee is hey, if we can't identify at least five hours per week in time-saving opportunity based on what we find in the report, where you implement AI, save at least five hours a week, then we will refund 100% of your money, right? So again, the business owner goes into it with the kind of the yeah, the mindset of like, okay, if this doesn't work, if they can't find five hours a week, I'm out 45 minutes. Yeah. Like that's that's the only risk. It's worth it. Yeah. So I basically either I buy back five hours a week or I lose 45 minutes, right?
SPEAKER_02What is the realistic uh discovery? Like, what are people typically coming in at?
SPEAKER_00So the average is about six hours per week in opportunity, and the average tool cost to the business owner. So if we prescribe, say, three tools, the average tool cost total across those tools is gonna be $40 a month. Because, dude, you'd be shocked how many of the tools we we find where it's like you literally need a fathom note taker. Yeah, it's free. Or you need Sanebox, it's seven dollars a month. Yeah, and you know, we're talking like one client that we we did one for recently, we're doing further engagements with him as well. He owns a business brokerage. This guy's drowning in email, two hours a day of email. Yeah, and the tool that we prescribed him, Sanebox, Sanebox.com, not affiliated, seven dollars a month. All it does is it puts an AI layer over your inbox and it forces you to batch prioritize your inbox. You have your main inbox, which is everything important and urgent, and then we have what's called Sane later, which is anything that's not urgent and not important.
SPEAKER_02Just throw a match on that.
SPEAKER_00He came to me, he came to me a week later. So we we always send the report before we do the review call. So I think it was like a week between like when we sent this report and the his availability for the review call. But he emailed us before the review call and he was like, guys, I I I went ahead and got Sane Box, like I read the report, I got Sane Box. It's it's crazy. And I'm I saw him in person two weeks ago. He said it's saving him about an hour and an hour and a half a day. Yeah. And so, like, and it's a seven dollar a month tool. Yeah, so that's a kind of opportunity there. And another great example, actually, some guys that that you met, I met at the Fort Lauderdale event, yeah. They own uh a, I guess, an e-commerce pharmacy. Yeah, yeah, sure. And so, because of that, they because they ship products in all, I think 46 states out of the 50 states, they're responsible for uh filing and remitting sales tax in 46 states. That's 46 different departments of revenue, that's 46 different sales tax returns, either monthly or quarterly, right? And so Adam, the co-founder of the business, whose time is probably worth about a thousand dollars an hour, is doing this manually every single month. Yeah. And one of the tools that we prescribed him is not an AI tool, it's literally just a SaaS called taxjar.com that 100% automates the filing and paying of sales tax agreements.
SPEAKER_02That was worth the fee right there across every state.
SPEAKER_00Yeah. And we ended up doing, we did an assessment for him, for his co-founder Taylor, and then for their uh head of pharmacy, Nathan.
SPEAKER_02So you typically do it at at the individual level, not at the team level or anything like that.
SPEAKER_00Correct. Yeah, we find because I mean, most of our clients are small business owners. They're probably actually some of the bigger business owners that we've worked with because they have multiple businesses, but yeah, it's at the individual level. So we'll do it, you know, we've done them with like uh realtors or like a one-man show. Yeah, yeah. Uh all the way up to like the business owner themselves.
SPEAKER_02Yeah. So this might be for if for the listener, if they're part of an organization, they might just say, I'm gonna pay for that for my own damn self.
SPEAKER_00Yeah, and I mean, it would be worth it. Now, I mean that said, we have had requests to essentially create like a bigger assessment product of like, hey, can you come and assess our department or you know, our whole business if it's an eight-person business or 10-person business? And that's certainly on the roadmap, but we've we've had a lot of demand with this just kind of single stakeholder product that we've just been doing a lot of those.
SPEAKER_02I'll tell you what, as we talked about at lunch, the more people, the more complex.
SPEAKER_00Yep.
SPEAKER_02Man, if you can hit that sweet spot with just the like the individual professional who wants to know how to either run my business better or just perform as an executive better.
SPEAKER_00Yep.
SPEAKER_02Um, interesting. You crack the code, turn that into the soccer mom angle too.
SPEAKER_00Yeah.
SPEAKER_02Then you're in business. How do I run the house better?
SPEAKER_00Yeah. Oh, yeah. I love that. The only issue with that is like, and like take my fiance for example, right? Like, she's she knows I'm obsessed with AI, but she kind of gets not weird about it, but like she's like, Well, you better not ever have the bot like talking to me. Yeah. You know, like I feel like there's gonna be a lot of that pushback. She's like, I feel like there's gonna be a lot of that pushback from people who aren't in tech, or like, you know, take like a soccer mom, for example, maybe not even in the workforce, they they like the idea of AI, but they don't want it to replace some of that, like per yeah, which you know, of course you'd use it tastefully, but yeah, I just thought that was that just reminded me of that.
SPEAKER_02So I like this concept. So the and it's something that that can be done in 45 minutes of bandwidth, because the number one thing that when we're working with companies, early on, pretty much you're like, well, how much time is this gonna take? It's like they're just gonna take what it takes. It doesn't take a lot. I don't want the listener to think that it takes a lot, but it's also not, you know, a fairy godmother magic wand that somebody's just like ding, it's done. It's a process for sure.
SPEAKER_00Yeah. And so again, for our our very specific assessment product, it's 45 minutes on the front end for the business owner, and then 30 minutes on the back end for the review call, right? And then in terms of my workload, 45 minutes for the assessment, uh, you know, it takes us roughly 30 minutes to put together the report, a little less, and then 30 minutes for the review call. Now I did mention how we do have an AI agent named Annie who can handle the initial discovery call now, right? And so we built her.
SPEAKER_02What's the voice agent you're using?
SPEAKER_00Uh retail AI.
SPEAKER_02Okay.
SPEAKER_00So it's she's built on top of retail AI. But again, the idea with that is uh a lot of times business owners, you know, when they're talking to me, another human being, things tend to go off track, right? We start bantering and we're talking about whatever, but we find that when they're talking to Annie, like they know they're obviously they know they're talking to a bot, it's not a secret. So they're just like very direct and to the point. And so Annie can get an assessment done in 20 minutes that would take me 45. Yeah. And she's and and honestly, not to toot her own horn, but she does a damn good job. Like she's she's designed in a way where she starts off broad, asks kind of more general questions, and then she'll kind of drill into very specific use cases. Like if she finds that, like, okay, well, you know, sales is a big problem here, she's gonna drill into sales, and we're gonna we're gonna uncover a lot of uh very specific sales use cases when it comes to AI. I can see a lot of uses for that.
SPEAKER_02Man, I I'm kind of uh on on repeat, let's say. There's something that's been on my mind a lot since I first got turned on to it about six weeks ago was and I don't know if you paid attention to it, but Jack Dorsey fired a bunch of people from block. 4,000 people they fired. It was a when you read the terms of the layoff, it was it it was a kind gesture for sure. They get well taken care of. Me, I just thought, oh, AI got them, right? They came in, they did some stuff like this, they did an audit, they identified some opportunities for um efficiencies and that sort of thing, right? But that that's not what happened. Did you are you familiar with the paper from hierarchy to intelligence that he? Came out with um about a month after that announcement.
SPEAKER_00So I I heard people talking about it, but I'm not familiar. Maybe you can educate me.
SPEAKER_02Yeah. So basically he was saying that we were, you know, we're AI forward, we were evaluating our company, and asking the question of what does the organization of tomorrow look like? And he said our our analysis we it revealed that a big portion of the middle layer of our org chart that looks like a pyramid, right? Big portion of their role is they get information from somewhere, either externally or internally. They do something to it, they review it, they compile it, they analyze it, um, and then they ship it back out, right? Or report on it or make a dashboard.
SPEAKER_00All things that can be done by agents.
SPEAKER_02Bingo, right? And and he said that's what we did. It wasn't about that that we made a better mousetrap with the existing organization. He said we just flattened that organization. Yep. So I know that when we were at lunch, you talked about how when you guys are evaluating these processes, that you're looking at the processes not just as is, because you know, odds are it can be a better there's a there's a there's fewer moving parts required to get the deliverable from the company, right? So you guys evaluate the process once it's captured for efficiency in general and then introduce the AI angle to it. Are you guys taking into account like preparing companies for I don't know uh their data today, still usable, but ready for ingestion in the future by some intelligence or an agent?
SPEAKER_00Yeah, so you what you kind of hit on is something I've been just kind of like talking and tweeting about recently, talking about the concept of building an internal knowledge base, like a second brain. Yes. Kind of the popular wording for that recently. Now, again, because I'm not like a data analyst, I have no technical background, I'm sure it is more complicated than uh the way I'm envisioning it in my brain. Maybe not. But maybe not, you're right. But but really at its core, it's like you know, my and my business partner actually created a really good uh pyramid style graphic to depict the like kind of the levels of of AI and the foundational layer is data, right? It's you know, your internal data, your internal knowledge base, everything from emails to call transcripts to copies of proposals to SOPs, like everything in the company is at that data layer. And I think the companies that create a really strong structured data layer of all their internal data, it's gonna make it so much easier for them to be AI forward and for them to, you know, deploy AI agents and start AI projects because again, that data is the foundation of every AI, everything, right? So it's like if that day if that foundation isn't in place, there it's gonna be a lot more difficult and a lot slower for them to roll out AI versus if they do the work to build that foundation one time, everything builds upon it and they can launch, you know, they can ship AI projects so much faster. So what I've been saying is one, there's that's gonna be a multi, multi-billion dollar industry of people offering what I call second brain as a service, going to you know companies like your clients and saying, hey, we will help, we will build your knowledge base or essentially create the data systems that'll act as the foundation for all your AI deployments. So that'll be that'll be a whole multi-billion dollar industry. And then two, companies are gonna start to do that internally too. Like if you're a you know, one to 10 person business, you probably don't have the funds to go out and hire somebody to build that for you, but it is something you should build yourself for sure. And I was at a a workshop, I think it was last week. One of the guys presenting talked about, I guess Arthur Anderson, the the hospital, did a, I think it was Arthur Anderson or no, MD Anderson, I believe. Yeah. Um, the hospital system did uh an AI pilot with IBM to something around piloting their Watson AI technology. They were like, it was something like they were $58 million in and hadn't treated a single patient with the initiative. And the reasoning come to find out is because the the data layer was not intact at all. They jumped straight to in the, you know, the using the image that my business partner created, that they jumped straight to the top of the pyramid, which is you know the agent harness on top, basically the automation layer and the LLM, and they completely neglected the foundation, which was the data layer. So it's like if they would have built that foundation first, interesting, and then you know, jumped to the automation and the the LLM layer, they would have had a much higher chance of success.
SPEAKER_02Well, man, I hope it I hope that companies can work with sloppy data because I mean that's a big lift, especially for like a small business or something like that. Yeah. They're just yeah, they're just hanging on, right? So for them to prepare. So I can see that certainly being a role that so we've got this this situation, right? Where you're you're you're talking to people, I'm talking to people, and you and I probably have an expectation that, oh, everybody knows this or everybody knows that.
SPEAKER_01Yep.
SPEAKER_02And what I'm realizing is that even when I try to dumb it down, um, the feedback that I get from smart people is like, oh, that was over my head kind of thing. Right. And I would say that's the bulk of business people, staff level for sure, even executive level, that's the bulk of it, right? So that's that's what the American workforce looks like today. But the technology continues to improve, right? Like like the whole last six months with Claude Code and co-work and blah, blah, blah, and all that stuff. Agents, ClaudeBot, Hermes, all that. That what didn't exist or it wasn't as usable, right? So we've got these people who they're they're still they still need to learn like the basics of prompting, but the technology continues to pull away.
SPEAKER_00Yep.
SPEAKER_02Right? So like where does that meet up? Where does the does it get to the point where it's just so easy that this that the workforce at large can say, oh, I can just use this tool. I don't I don't need to know how to prompt. I don't need to know how to do anything like that. Or kind of what do you see happening with I don't know, the the trend in adoption?
SPEAKER_00Yeah, I think I think it'll get easier. Like I think it'll just get even like there we'll get to a point probably in the next two to four years where like people's grandmas are gonna have a an AI agent in their pocket or on their phone, right? Like it's gonna be so user-friendly where like take open claw right now, for example. Like setting up a simple cron job sometimes takes like an hour of debugging to do properly, or you know, connecting, like there's you run into issues trying to connect it to Gmail or whatever. Like that, that's just not gonna be an issue. Like, I think it's the technology is gonna improve to a point where it'll still it'll all be natural language in the sense that I can just tell my AI agent, hey, call this restaurant and book a reservation for 8 p.m. and it'll just do it and it'll just work. Whereas, you know, right now it's like, well, before it can do that, I've gotta I've gotta get a phone number through Twilio and then connect it. And then I've got to set up an 11 Labs voice profile, and then I've gotta make sure that you know I send it the proper URL for the restaurant. All that is gonna go away. You're just gonna be able to tell it to do things, and it's just gonna work.
SPEAKER_02So I know that when when we met in February, you were already ClaudeBotting, right? But my experience with ClaudeBot was a huge pain in the ass.
SPEAKER_00Yeah.
SPEAKER_02Right? Learned a lot, yep. But like I think maybe I've got one chief of staff that's up and running, but I don't even use it, right? Yep. Um, but you said over the past few days you've been messing around with Hermes. Better.
SPEAKER_00Better so far. So yeah, so that's kind of like my background with ClaudeBot. So that's really how like when I really started getting into the weeds, it was with ClaudeBot, and it's because my business partner, he's very technically minded, he's a developer. On day two, so this was like January 3rd or something.
SPEAKER_02Yeah, because you presented on it, yeah. Yeah, yeah, yeah.
SPEAKER_00So we had been using it at that point. So I presented on it. That was probably January 27th or 28th. I had been using it for maybe three weeks at that point, only because my business partner discovered it on day two. Like it was still completely unknown. But he messaged me one morning, he's like, dude, you've got like we've got to start messing around with this. This stuff is crazy. And he built actually Annie, the voice agent that I mentioned, the first iteration of Annie was as an open claw agent. So I started experimenting with her, and on day two of using her, I was like, I could never picture myself without this technology again. Like it was that impactful to me that early on. And so we just got a three-week head start on everyone else, which is the only reason I was able to present on it at that event. But I say all that to say, and the reason that was so impactful is and just open claw in general to like our little bubble of the world, is that was the first, I think, like real powerful demonstration of agentic AI, yeah, and that coming mainstream, right? Like that was the first time where you could tell an AI agent to do XYZ and it would go do it, and it had you know no guardrails, and it was smart, and it would just like it would just get the job done. And yeah, and and you just uh that wasn't possible before that. So, you know, I was open claw everything for two or three months after that. Really, I have I've stopped using open claw almost entirely over the last probably two months, using mainly like clawed cowork and perplexity computer, not as powerful, but better user interface and they just work better. Yeah, now that Hermes is kind of the big thing on the scene and kind of replaced OpenClaw in the I guess the vibe, for lack of a better term, right? Yeah, everybody's kind of switching to Hermes because people like people say it's like Hermes just works, right? Out of the box, it just works. It's not as finicky as open claw, it's not you know, it doesn't get stuck on these loops or like cron jobs don't fire, like it literally just works. So, one thing that I actually spent my whole morning this morning doing, are you familiar with G-Brain? Have you heard of G Brain? Gary Tan? Gary Tan's that's his kind of open, and so Gary Tan's the CEO Y Combinator, which is like the knows a thing or two. Yeah, most prestigious uh VC incubator in the world, but he created this open source project called G Brain. What Gbrain is, is it's just my understanding is it's it's essentially a knowledge layer for AI agents, but it's very robust. Like it can ingest uh it can ingest thousands and thousands of context files and documents and notes and everything, and it it has a retrieval system that it can easily retrieve that context as needed, right? So, for example, this morning I spent the whole morning building out my G-brain, connecting it to my Hermes agent. So I I've set up my G brain in a way where it pulls in. So what you know, when I get on a Zoom call or a Google Meet call, it uses Fathom. That's a note taker that I use. Yeah, right. Every every Fathom call generates a call transcript. Yeah. So I set up my G-Brain to where every call transcript that's get that gets generated for my Fathom automatically pulls into G Brain. So that if I at, like if me and you had a Zoom call today, and a year from now, I can ask my Hermes agent, hey, what did Chris and I talk about on you know whatever today's date is? It could easily, quickly, cheaply and accurately look up that transcript because it's in my G Brain and tell me exactly what we talked about. And then I can anytime I create a new Hermes agent, I can connect it to that G brain and all that context is there forever. So I connected my calendar to it, my Google Drive, my emails, and my call transcripts. So it's just a big shared knowledge base for all my agents.
SPEAKER_02So for the listener, this this is a trend you're gonna start hearing and seeing a lot about where people are just they're not using Chat GPT like a drive-up window where they ask for something, they get their answer, they leave. They're gonna be integrating it through the connectors and through the agents and through all this, the ingestion of all of these uh business artifacts like your email and your Slack and your Fathom transcripts and all that sort of thing, so that you're gonna be able to have this uh, I mean, literally second brain, except something that on demand or will even surface things that you're not even thinking to ask. Hey, Chris, maybe you should think about this kind of thing, right? That's gonna be a trend that I think that the those, and you don't have to be like great at quote unquote great at AI to set that up. I mean, like you can get that going. But once you do, I think that those are the people that you're really gonna notice, like, oh my gosh, they're like they've got a superpower.
SPEAKER_00Yep. And so to your point, right, it's not like the kind of the benefit of having that G-brain or or whatever second brain you end up building, it's not so much so that if I, you know, six months from now, I need to figure out what Chris and I talked about on May 29th. It's it's more so exactly like you said, it's like the AI is going to be able to draw parallels between inputs that you would never be able to draw. Yeah, right. It's like what it might say, like, hey, Corey, you know, based on your last 50 call transcripts, yeah, every prospect you talk to, every one of them has this one objection. And like sometimes you overcome it, sometimes you don't, but in all your sales materials, you should be optimizing for this objection. Yeah. And like that one insight might make you an extra $50,000, $100,000, $500,000 in a year.
SPEAKER_02Save you a ton of time.
SPEAKER_00Or save you a ton of time. So it's those insights. And I when I tell people, because a lot of times people, when I've been kind of telling about this concept of the second brain, they have trouble wrapping their heads around like, well, what's the ROI here? I was like, well, I can't tell you because I don't know what you have under the hood. Yeah. But what if every bit of information your business has ever had, if you were able to ask AI one question, it's look at all my information and give me 10 things that will either save me more time or make me more money based on every bit of context you have about my business. And then I guarantee you you will be baffled by put a price on that. Yeah, you'll be baffled by the information that you get. So that's the exercise.
SPEAKER_02That's a and that's a great um point. If somebody says, what's the ROI? Like, I mean, I'm locked in, right? If you're not that engaged with your career or anything, maybe it's not gonna have that big of a difference. But if you're locked in and your business is important to you, having another you, like, dude, if I was my own co-pilot, forget about it.
SPEAKER_00Right. For sure. I mean, that and that's what you're building, right? And yeah, you can have a bunch of them. Like, that's what I like about Hermes.
SPEAKER_02You can have a bunch of them.
SPEAKER_00Is you can have it with Hermes, it's called profiles, right? So I can have, I have right now my main Hermes agent, which is kind of my you know, operations slash executive assistant, but on my to-do list this week, actually on Wednesday, I'm creating two additional profiles. One is gonna be uh a marketing slash content profile, and one is gonna be um my CFO, my AI CFO. So each of those, that's essentially three individual Hermes agents, they're all gonna have access to that G brain that I mentioned. So that's like the shared context layer. And then in addition, each of those Hermes agents, it's gonna have their own individual private G brain. So the the content agent is gonna have a content G brain, the finance agent is gonna have a finance G brain, but they're all gonna have access to that shared one. Yeah, yeah, right, that has the call transcripts and the email and everything. So it's like imagine it's literally like me building out my org chart of AI agents that one get better over time, because that's what Hermes is fundamentally designed to do. And then two, have shared context across everything that you're doing, you know, from a general level, and also have private context. So that way you're not muddying the waters with, you know, your finance agent doesn't necessarily need your content pillars, right? And your content agent doesn't necessarily need to know about your May PL. Yeah. But for the context that does matter, they all have access to that.
SPEAKER_02Yeah. So, man, we've covered a lot of ground and this has been awesome because I don't get a chance to to geek out with somebody that I know. Most of the people that are on the podcast, we've we've had a pre-interview. I'm interested in their subject matter, of course, but like we don't really know each other, right? We haven't, and we broke bread a couple times, all that jazz. Um, so if if you're listening to this and you're like, whoa, I want you to think about something. If you if I ask you, hey, where are you on a scale of one to five when it comes to using I? I get this all the time. I have you know enthusiastic executives tell me, Oh, I'm I'm four. Like, great, man, what are you doing with it, right? You use it all the time. Okay, great. Well, tell me what it is. I use it to write emails and summarize documents, right? And that's great. That's an awesome use. And the fact that you're using it regularly for those things only opens a door for you to go, oh, I could also like it's part of the process for sure. But what we've talked about here, and this is like like Corey is literally like on the edge of things trying to break these tools. This is where this is where a four or a five is. They are they are thinking about these uh boring documents that are very powerful, but it's the design.md, it's the skill.md, it's the context document, it's the company brand voice document. It's all of those things that aren't really like that's not AI, right? That's you documenting uh the soul of your business, really, like all these different elements. And that's great. You get one context document, it's better than nothing. But then you start getting into you know these l levels of it. Now I've got an agent. Well, great. Now my agent has specialized agents that that agent can call on to. Like that, and you're not doing this for a major enterprise, you're doing this to run your business to allow you to be somebody who who whose influence is much greater because the the ability for you to touch the full spectrum has gotten so much easier, or it's being done on your behalf because you invested the time to think about well, what do I want this agent to do and what skills should it have and how should it be structured so that I'm not spending $1,500 a month on this one agent and its tokens and all those sorts of things. So, folks that are listening, we've had a wonderful conversation, but like there are layers to this stuff, and we we could have gone all like yeah, but we we were toning it down a little bit. So fantastic conversation, and then now you're off to uh go enjoy the fruits of your labor.
SPEAKER_00Yeah, yeah, yeah. Very cool.
SPEAKER_02Corey's on his way to get his his new Tesla.
SPEAKER_00Yep.
SPEAKER_02So nice. Well, thank you for taking some time out of the day here. And um, I want people to plug into what you're doing. So if you don't mind, maybe take a minute and just kind of share like where you're because you I know how much time and energy you're putting into creating this content.
SPEAKER_00Yep.
SPEAKER_02I read the content, I don't waste my time. So for all of you that are uh listening to this, I would encourage you to pay attention to all the places Corey's about to tell us to go catch up with him.
SPEAKER_00Yeah. So I mean, the main place I would send people is my so you're listening to this podcast, you obviously enjoy podcasts. Go listen to slash subscribe, build with AI. That's the name of my podcast. The build with the link to it in the show notes. Yeah, and so you know, check it out on audio platforms, of course, but it's best experienced on YouTube because I do my podcasts in screen share style. So every one of my episodes, we're sitting down, we are sharing screen and we're building, it's called build with AI. Like we're building things live or we're testing tools or we're, you know, tweaking workflows. And and you can get the the video version of the podcast over on my personal YouTube channel, which is just my name at Corey Ganum. Um but yeah, that's where I'd send people. And then, you know, if folks are interested in an assessment or they want to work with me directly, they can send an email to Corey C-O-R-E-Y at return my time.com.
SPEAKER_02So I mainly follow you on X. Where else are you putting out content?
SPEAKER_00Uh X, LinkedIn, and then YouTube slash podcast. Yeah, okay. Yeah, X, I mean X is my X is definitely my most active in the sense of like when I come up with an idea, I fire it off on X, and if it does well, we turn it into a YouTube video. And and YouTube's where we go like super deep on a very specific build or agent or topic.
SPEAKER_02I didn't know that, so I'm gonna have to catch those as well.
SPEAKER_00Yeah, yeah.
SPEAKER_02Very cool. Yep. Corey, thank you so much for taking the time, man, and everybody, thank you for uh being a listener of Using AI at work. I always strive to bring people, again, who are doing the thing, not just um selling a product or whatever, so that we can get into these types of conversations and you can see what what it's really like to be an AI fluent, you know, uh ass-kicking executive or business owner out there. So uh if you enjoyed the episode, please uh think about sending this along to somebody else you know who is on the journey. And we'd love to have them as listeners. So thanks everybody. We'll see you on next week's episode. Thanks for tuning in to using AI at work. Don't forget to subscribe for more conversations about how to use AI at work. And a special thank you to our sponsor, Chief AI Officer, for empowering businesses with AI education and training. Visit their website for a free AI readiness assessment and AI strategy guide to help you get started using AI at work. That's www.chiefaiofficer.com. Follow us on Twitter at the handle UsingAI at work and visit www.usingai at work.com for free resources to help you harness AI in your role.