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Bad Data Causes More AI Failures Than Models Do with Richard Valentine
01:03:14
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This is the Unknown Secrets of Internet Marketing, your insider guide to the strategies top marketers use to crush the competition. Ready to unlock your business full potential? Let's get started.
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Howdy. Welcome back to another fun filled episode of the Unknown Secrets of Internet Marketing. I am your host, Matt Bertram. I just changed my input the mic, so hopefully you can still hear me. I am excited about where we're taking this conversation. I am thinking that the transition that we really haven't made to YouTube this, this episode might bring about that shift. We are up on YouTube. We are going to be changing the format. I do have a whiteboard behind me. We are going to be doing more education. I do need to change the intro, probably need to change the name of the podcast. I'm sorry, guys, I've been super busy. We've been doing a lot of development work. We've been launching a number of things. I've had a lot going on. I do have another podcast out there, maybe launching another one, but what I'm really thinking is maybe rolling them all up into one because I think it's becoming like AI all the time and it's just eating everything. AI is just absolutely eating everything. And we were talking a little bit and I've hinted at persistent memory and like, as you move the shift from like a chatbot to like a teammate. I've been reaching out to some people in my network and I got one of the researchers that's really, really up there with AI and memory to come on. He has a couple of provisional patents, he's published some white papers, he's dedicated some time teaching me some things and so I wanted to share him with the audience. Ricky Valentine, welcome to the show.
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Hi. Thanks for having me. And you know, I. All the time. That doesn't sound like a bad, a bad name to the podcast right there, you know.
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B
Well, you know, the conversations that I'm having, whether it's at kids softball or, you know, at work or whatever, the conversation always kind of, I just seeps back into that conversation with whether it's people concerned about taking their job, about what it can do, you know, about like what they're hearing in the news, different industries, like I can't get away from it and people know that like, you know, I'm pretty involved with it. So I get pulled into these conversations and you know, I spoke at OTC Offshore Technology conference and we were talking about AI on physical devices. So, like that transition out of it, which, where it's really lived in a developer community and it's being applied to actual assets and production and you know, the Internet of things. And like, I mean, it was just really amazing to moderate a panel of some of the top experts and like where that conversation went, not on the panel necessarily, but in kind of little corners and throughout the conference, people having different kind of conversations. What was, was really fascinating. And you know, as we move from, you know, using it as a chatbot to using it not just as a thinking partner, but acts actual, you know, partner or teammate, memory becomes really, really important and the data gets polluted and the, the calls of what it remembers and the challenges versus like when you start working in an enterprise environment. So we've been shifting EWR Digital to AI first company where we're sharing all the like same skills where everybody's connected in on like certain processes so we can standardize and scale and you know, different people have different solutions for different things. And then they, they, you know, like, what is the right solution? How do you standardize it? And you know, you and I have talked for hours, really at different times and you know, different people are all going to approach a problem differently and come up with the right solution for them, but AI just looks at that as like noise or like a bug. And so how AIs remember stuff and for you to be able to work with it and train it and you know, set governance to this, I mean, memory's at the center of it all. So what, yeah, what are you seeing? Like, kind of, I'm just teeing it
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up for you, you know, I guess kind of where, where it all started for me. And I won't go through the life story, but it starts at a young age in the fact of I started out in the medical field and I always hated how much healthcare. I felt like once I got an understanding for technology and stuff, I would see that, okay, wait, we have data analysts that are printing out something from a $2 million system and then hand typing it into Excel. And, and so like that just made me like really like want to fix that solution and like have that desire at a young age. But as I, as I grew older, I realized that the advantage was that when you're in healthcare and in a regulated industry, as you know, you kind of have a crystal ball if you can look outside of your field because adaption just takes so much longer. So if you're looking at where innovation is happening in less regulated industries, then you kind of seem like you're, you know, have a crystal ball because, because I can see, okay, hey, well, you Know, they've sped over there that, how can I incorporate this here? And that's just amplified by having AI because now I don't even have to do all the footwork of, hey, how did these two dots connect? I just have to have the wherewithal to go, hey, can you tell me how this connects to me? You know, and so that's really how, how all this came about for, for me was I just saw the way AI was handling different problems and, and the memory thing. And it was, you know, we've been able to Google something and find the answer at our fingertips for a long time. That's really not new. You know, for those of you, which I'm sure most of you are in the day and age of just good old Google, you would type in something and then you fire up a form and you get two or three different answers. But sometimes, actually more times than not, those three answers would all work, but they wouldn't work for you, or one would work for you. And so to me, it was like, wait, the great thing about having AI shouldn't be like, I have a pretty good memory myself. I don't need it to remember the answer. I needed to remember how I got to the answer or what made that answer the right answer for me. And so that kind of pulled on this little piece of thread that got me to crystallization theory, which is kind of where I started my journey of. So I never touched a line of code until 2024. I'd always been kind of the conduit and mouthpiece between business and technology, but it was a lifetime of developers telling me, well, you can't do it that way or it doesn't work like that. And so when this AI kind of revolution came about, I was like, well, now's as good a time as any to see who was wrong, right? And it turns out we both were. So I mean that in the way that does work like that, you can do those things, but also shipping a product that lasts 15 or 20%, as you know, and you know, the amazing work you guys do at ewr, it's. It's a lot harder than, than the Internet is making it seem these days, you know, and so kind of just learning from those things and going from not being able to make a login page to 4 patents and 8 billion tokens on one platform, it's been both humbling, but also just a lot of hitting every branch on the way down and learning from it.
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You know, one of the things that I think is important for People like, there's a lot of web developers that listen to the show. There's a lot of SEO people, like when we start talking about agents, they're really like, that's short for coding agent, right? It's a coding agent that developers use. So like if you're not familiar with a lot of this stuff and it's really new to you, it's because you haven't been in the developer world. But the developer uptake on a coding assistant is like over 90% right. So like dev heavy environments are utilizing this technology at a rapid pace. And you know, for someone to go from like, you know, understanding like analytics and business to be able to use an agent and orchestrate like a system and all that, it takes some system thinking. It takes understanding how applications are built, like going to get some basic Python knowledge. Not saying you have to code it, but saying how it works. Like what you're saying of how it fits together is really important. But the caveat to that is anything you can think of, this is what I believe currently anything you can think of in your mind is now possible. So if you can map out a workflow, if you can map out guardrails, if you can think through the problem and the second order, well, the first order, second order, third order effects of what you're going to do and how that's going to impact it for developers. For example, you got to think about throughput. You're vibe coding something. There's a bunch of people say it's just super easy to do it and you vibe code this thing, but you can't necessarily go to market with it. And like, once you start getting like a lot of users, all of the actions that are happening are getting processed one user at a time. That was like, even when we were talking about Bitcoin back in the day, like it can't process out the throughput of like a credit card. Like, right, like you can't billions of transactions. So you got to think through, through this of what the end state looks like going forward. And there's been a lot of debate on can you vibe code something or do you have to do it the traditional way? And you know, I, I was kind of watching that debate and you know, again, I'm not a developer but I project managed some things and I'm going, well, if you train your system to code it with the traditional like subject matter expert knowledge of how you're going to build it, it's going to assist you to build it faster. So it's not this or that. It's. It's the same thing.
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Yeah. And you try and explain it to one of the two camps and they don't. They don't. Because for the people that want to spend three months planning, like, I'm like, no, like, we got to iterate quick. And then the people that want to iterate too quick, I'm like, no, but you got to have a plan. And so, like, I sound contradictory to both, but you're exactly right. And that's where I landed was, you know, there's a famous quote, it's attributed to Abraham Lincoln, but they say it's. It's not really. We don't know who it said it, but it rings true nonetheless. And that's. Give me six hours to chop down a tree and I'll spend four hours sharpening my ax. And, you know, it's. It really is that way in this day and age is that, yes, we can iterate quickly and so we should. But at the same token, you can save yourself a lot of heartache, no pun intended on, you can save yourself a lot of heartache if you really do think it out. That was one thing that I never having worked with developers and stuff, I didn't come into this as somebody that was like, oh, I'm going to spend a couple hours a week and I'm going to get good at this and I'm never going to have to learn anything about code because I just simply knew that that wasn't true. I knew that I could, I knew that I could use it as a crutch, but I knew that, you know, from, from starting out where it was just pattern recognition of. Hey, I notice every time I'm doing authentication, like, I get messed up here. Okay, we need to tell it to watch out for that. Like, not even knowing what I'm really trying to watch out for. I just know that, like, hey, when we get to this point, and this was back when we had context windows of just like 16,000 tokens, 32,000. So, you know, it is one file and it's like, where am I? Like, are we building something today? It's like, yeah, we just built 200 files. What do you mean? So. And then also with the regulated industry thing, because of the fact I had a passion for healthcare, luckily I was able to get in the Azure Microsoft Founders Hub program and have credits and be able to utilize a lot of their railing, you know, and pipeline for. I feel like that's one thing that a lot of people, the hybrids of, of business and development, they're really finding the sweet spot. And I think it's because of things like, because I didn't have the skill I had to find, you know, not necessarily the way around it, but the way that I could get that, you know, HIPAA compliance without me knowing, you know, hey, like, okay, well, what's a pen test? You know, and so it was utilizing things like, you know, now I still had to have my code be solid and so I kind of used myself as the scout, if you will, so I would kind of like move forward and make prototypes and things. And then I'd have, you know, my development team come from behind and it allowed us to kind of, they could work at the pace they wanted to and really have things mapped out, but it didn't constrain the freedom of, of being able to try new things out. So. And now it's totally different these days in the fact that like, you really can do a lot of things if you're willing to just spend some time planning and, and so, but we still have a lot of things, I think, in the way of governance. And I know that this is something that even though me and you've known each other for a while, kind of where we, where we started having a lot of really long conversations was on governance. And you know, that's a dividend that's not, not gonna really be be paid or, or a debt that's not going to be collected for, for probably another year for a lot of people because they don't realize what, because things do appear so easy and, and they're not because like you said with the throughput and everything, you know, it's really easy to make a Supabase back end and, and you know, mismanage API calls and. Oh, I just had, you know, there's one person on my platform and I had 15,000 API calls in a day. You know, like, so you amplify that into something that's just, you either have, you know, Richie Rich as a brother or, you know, you're, you're just sol.
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B
So, yeah, I mean, I think that that's what I saw first. Right. And I think that what, where you came from is really that sweet spot. Like you're, you're interacting with developers so you understand some of the vocabulary and then you understand the business piece and you're like sitting in the middle of it. And so if people are on one or the other, they need to go try to build that vocabulary and understanding from that other area because that's, that's really where we're sitting as like a human in the loop, as a bridge. We're, we're a bridge between the, the coding agent and what, what the final output is and what the business or the goal is that we're trying to achieve. And you're, you're the one that is going to facilitate that. So if you're a solo operator or if you're working at a company, you're still building an operating system, right, that you're operating in or you're operating in together and you're coagulating like different systems. And then really it's about standardizing those systems. It was just like in digital marketing, the biggest issue that we had previously was data fragmentation. Like, data was all over the place. And also the biggest issue right now in moving into like OT is the data that is being produced is unclean. So even the div or what you're talking about is about the penance or that's not the right word of just not utilizing your data properly. Like anybody that's using a CRM, there's a lot of people here that are using CRM. Is your data pristine? Right. Would you trust your life on that data? All right, how up to date is it, how current it is? And you know, like, I know a lot of people that are using Salesforce or Hubstaff or whatever, but they're not using it the way that developers intended it to be used. And so the data is unclean and it can't be processed. Now you amplify that to using something on a physical device of like a pump on a. Well, that data better be right because you're running all kind of math and heretic, like that thing could blow up, right? Or something bad could happen. And so you got to trust the data and you got to also the latency is a really big issue there. But like all of these, these like sins or I don't know what the right like frame is to think about this, but they're all going to come too. And, and so from an operations background, the thing I zoned in on was like, oh my gosh, you've got to have the governance set up, right? And everybody's got to agree if you're working in an enterprise environment and okay, why, why are these hallucinizations? I can't even talk happening? Well, it's because of bad data or you didn't give it enough information. Like it's not the AI, it's the human user. And so I don't know. I Doubled down on that. And then there's now regulatory laws that are coming down the pipe that people are not expecting. I'm going, okay, like, why don't, like there's a period, you know, it's September, but they might have pushed it out a little bit. On motopoint, I set up like a countdown timer because it was like, it's coming, right? And so it's like, get yourself ready, audit your tech stack, understand what's going on, map out your API calls, like, bring your token usage down. It's going to be a win, win all around if you set up the system properly from the beginning and get everybody onboard on that system. Because if not the problems you're having, let's just use the CRM as something that everybody can follow is going to get amplified. The problems are going to just get amplified with AI and the noise and degradation and you're just trying to fill up the context window of all this information. And you know, when you're talking to AI after a certain amount of time, it like will compress the conversation, but you lose context. And you were having this great conversation. And then up like now it doesn't even remember like what you said. And when I was using AI as a thinking partner a couple years ago, that was like the most frustrating thing ever. I was like, oh, I was in like this really good place and you like, wanted to keep that chat that way. And you know, and then like I Remember when chat GBT like 4.0, like they upgraded it and they took away the persistent memory and that was when I switched to Claude. Like, I was just like, I just lost my thinking partner and it can't remember anything.
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But at least with Claude, like it would tell you, hey, start a new conversation with Chat gbt. You know, you'd be thinking nothing was wrong and then you'd be like, wait, you just got a lot dumber. Like, you know, and to your point. So I was actually with a good friend of mine, Hank, and, and he's a vice president of treasury at a, at a. One of the bigger, bigger bank. Bank brands. And we were out one night and I was talking about, you know, how, look, we have to, you know, I've been so focused on the viewpoint of like not making a, a world where, where there wouldn't be hallucinations because I thought that that was the crux of enterprise because the, you know, remember that I've just gone through my like odyssey of like coding the past year. So I kind of lost touch with like a little Bit of my business activate while I was in the hole. And, and he goes, ricky, they're not worried about the models hallucinating, they're scared of their own data. And just there was, you know, that's in the top five most profound moments that I've had in the past year. And then to him, he's like, ricky, like, what? Like, are you okay? Like, know, like, do you see something? And I'm just like, you know, molding this over. And I'm like, dude, I never thought of that. And so as I'm working through these problems, I'm thinking about, okay, now we have to go back, we have to look at ingestion, you know, and, and, and, and backtracking that to the point where at one point I was like, just convinced that, hey, okay, we're just gonna have like shadow hospitals and like shadow billing companies. And like, all they're going to do is like, you know, just basically sit there and be like, non biased, like, okay, we're going to decide what like, has right authority. And like, what gets like saved is memory. Because, you know, when you think about it, you know, there might have been that period of time where like, Susan, you know, was out on maternity leave and so your books aren't, you know, like, you know, you had a tenth that was, you know, doing bookkeeping. And so, you know, those things that you don't really feel so much at the time when you have something that can remember all of this and it's using those data points to the T, you know, you know, back then, your CPA just came in at the end of the year, he said, oh, I'm going to fix these things, you know, did some, you know, magic with the numbers or got you some, you know, electric vehicle credits or something, and you were on your way, you know. But when, when each data point, you know, and that's where really I got frustrated too, was it was all or none. And that's where like my work has kind of been in memory is, you know, it's either shaving everything down to fit one answer or it's remembering everything and then what's the point? You know, and it's the same thing with context. You know, it's either taking everything too literal or like not remembering. I'm like, didn't we just, you know, and so kind of threading that needle and that's where, looking at that. And back to my analogy, the forms and making crystallization theory is basically as you compound those answers and as more people in your network, you Know, validate those answers. And it has to have human right. Like a human is the only one with right authority. And you know, that's another thing that kind of drives me crazy is I'm such an efficiency person, but even I can't get through my head like, wait, you know, we're saving all this time so we can't use some of that save time to like double check the work and like, you know, like we want everything to compound, learn and just get smarter. I like to say it gets smarter, but it doesn't get wiser. You know, like, so we're just, we're saying more, more, more, get it smarter, get it smarter. But it's, I'll take, you know, it being wise and being able to produce something, you know, that, that has some merit that I didn't think of or, you know, that. And so that's kind of, kind of where, where I, I left with that and I'm kind of losing my.
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B
Yeah, no, so there's two things that you said that, that I want to highlight. We've started to change our workflows, okay, we've, we've started to change our workflows where we have some power users that can produce massive amount of output. But QA QC becomes critically important because as of today, I can't trust the output's going to be perfect every time. And unless you even set hooks, for example, if you're on quad, sometimes you set a rule, it forgets the rule because it gets lost in the context window. Because it doesn't reread everything all the time. Well, I think it, it does and that's why you use so many tokens, but it doesn't weight them like right to what you were saying and what you keyed in on. And, and I believe this is happening to kind of bring some of this back to digital marketing for, for everyone listening because this is a mindset shift. All of these platforms are already working on math, okay. They're already running formulas like all the different social media platforms and Google are all, you know, already running these things in the background. And one of the things you're talking about is like the value of authorship, right? Like who's saying what the degradation rate of. When did they say it? Like the importance of how current it is. You're seeing all these things kind of come to light when, when you're using agents and when you're looking at memory. But like Google for example, you know, a review on Google or a comment on a social media post, who the person is in association with the post and typically in association with you because sometimes they show it to people that like your content or they show it to your network. Like so there's different weighting factors. But then what it is they're saying, right? Short, long, is it related to the post? And then when did they say it? You'll actually see on posts, like there's a rating system, right? And so you'll see it on the post that the most recent post typically stays at the top. It gets auditioned and then it falls to kind of where it sits. And so think about that with memory. And I think you and I were talking about this before, like when someone goes to sleep, I think your brain is like compressing all that knowledge and like what does it choose to remember and not remember in short term and long term memory and even a lot of where all this memory stuff is going is the most elegant piece of equipment is the brain, right? And we're starting to replicate the brain in a lot of ways is what, like I just see a lot of parallels. I don't know.
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So you know, I, I've lived a lot of lives and in one of those, I was working in brain mapping for personal injury cases and we used a really great machine that was quantitative eeg, EKG and evoke potentials test that was able to ctbi but also be able to see. And I'm gonna circle this back to.
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Yeah, I don't know what you're saying.
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But anyways, so it was, it was a great scan and it allowed me to kind of like learn a lot about the brain that you know, get just be very interested in it. And so one of the things that I put in my, my memory program is, is the ability to forget. You know, like that is the decay. So I use a weight formula that has a decay. And then based on the importance, kind of exactly like you were saying, based on the importance and the weight of that is at what rate it decays. And you know, when it comes to like the other day I was thinking of things in terms of us, an agency, you know, for, for digital marketing. And like, you know, people don't realize like how much governance is like it affects every industry. So like, for instance, you know, you don't know if, you know, somebody might not know if their employee, you know, did as much work or that, that that subcontractor did as much work as they say they did or, or what have you. Well, that's drift, you know, like that's, you know, the it is, is the, the digital truth.
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B
What is the, what is that? What is this? Like where does the truth start? Like what are you using as the reference? And then what's that deviation from that or that drift of, of where it's going? Because you're like, okay, and that's like scope creep guys. Like that's basically what happens is you're like quote this and you're like, oh, everything's going to go perfect and I can charge this and the feedback from the client's going to be immediate. Like you have to start building in knowing that, that there is going to be that, that scope creep. But how do you limit how much of that there is? And I look hats off to all the other digital market. I'm going to a conference next week actually that's just for agency owners, right? Because I really want to see, I want to kind of benchmark too, kind of where we're at versus all the other agencies where, what they're talking about how people are dealing with the injection of AI into their workflows. But there's not a lot of really big agencies, Ricky. There's like, you gotta really scale your business to get those efficiencies of scale. There's a lot of like a couple people and a dog. I say like, you know, there's a couple guys, a dog in a house like agencies or there's a lot of freelancers and hopefully if you're one of those people that has your dog right next to you, please don't be offended because sometimes my dog will be here as well. So, so I, I meant that I fit the stereotype, I'm talking about myself. But there's not a lot of agencies that can scale, right? And that are in that phase of scaling because there is so much governance and there's so much domain knowledge and there's so much that has to happen. But the shift with AI is you can start building teams and agents that have domain knowledge that you can build governance around that can start to help you fill in those gaps and to get through that, that area of like the scaling from the small company to the large company. But it's so much thinking that has to go into it. And you're not just building one brand, you're building multiple brands for other people based on, you know, the lead gen, that if that's the focus of what you're doing for those clients. And, and so I think, and you're starting to hear it to talk about with AI, there's going to be billion dollar businesses built with AI, I think the job of a digital marketing agency is like 10 times harder because you're not just building your business, you're building businesses for other people. And all the inputs and the workflows and how that client likes to work and the communication and the personality is constantly in flux and changing and you got to plug in all these other systems to fit into your system. And that's where I think, you know, like this agent economy is, is gonna, there's gonna be standardization of how businesses interact potentially. And, and I don't know, what are you, what are your thoughts around that?
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It's, I do have to say hats off to the agency owners because as I've been doing more, you know, me, and you've been talking more, so I just, you know, I'm naturally curious and I don't know what agencies did the AI, but like, they do not see you as a tam, like, like a market to go to like you did. It was, it sounded personal. Like every time I would question AI about like, hey, making this solution to that solution. Because, because you're right. I guess there's just, you know, there's, there, there's kind of like, there's big agencies and then there's you know, kind of like mom and pop operations. But one thing that tip my hat off in all seriousness too, is that you have to standardize the result, but make it different for every customer. You know, talk about a paradox there. You know, like, I need to have consistency in my deliverability, but no two answers can technically be the same, you know, so I know that just being WordPress was kind of like my, my first love, so to speak. And I know that that's really the
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B
hardest,
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that's one of the hard times that they're having over with, with WordPress with AI is yeah, sure, you can get it to do anything, but try and get it to do 200 SKU product, product descriptions the same way. And you know, like, even if, and so if you don't understand, you know, and even me, and even then it can still take its own turn on it, you know, if you're not making those outputs in the schema, you know, outputs that like, hey, this has to be like this. If you're just relying on a, on an, you know, a large language model to just, hey, it's going to come out this way every time even with the prompt. There's going to be some variants.
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Yeah, no, I was just.
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Oh yeah, keep going.
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I was, I was basically, I was just saying you could do that with a harness, right?
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Yeah, yeah. But even then it just, it's, you do that with, with, with, you know, to be honest, I don't know, I just, I went through a lot of different scenarios that like I come from regulated industries and after looking at like what a, like mid level agency because like first off you're like, you're in a, you know, if you're kind of, you know, in the, in the middle or, or kind of higher up, like, if you're higher up, like somebody's, you're making a custom solution and like you already have had it for a while. Like if, if you're in the middle, you're not a big enough market for somebody really to build for you, but like you're building for everybody else. So then how do you build for yourself? You know, like, so, so I just, I, I, I consider myself like a man that walks between silos and solves problems. And even I was like, I spent a whole night just like, well what if I used Docker profiles? And, and each client had a profile and then it was like, well, yeah, but then, you know, permissions. Okay, well then we're gonna make an MCP that then, and then I was like, what about Ephraimial containers? You know, like, like and so making the client come to you instead of you logging into the client. And it just, it was a fun thought experiment.
- [36:48]
B
But yeah, I'll give you some tools that have gone down that path and that has actually been like the scalable solutions to basically, you know, install something or they have to plug into it and they're working within your system. But then you get into data governance issues of like they're collecting everybody's data and process. And so there's a, there's, this is a tough, this is a tough industry and it's, it's certainly tough if you're coming in to crack it. How I have perceived it today and I've been bringing on different agency owners that have moved from through this path and where I see them going is, and this is how I view myself as well, I'm trying to build an elite team that thinks about AI because
- [37:41]
A
I saw how cool this stuff and I won't, I won't let the cat out of the bag. But I saw the cool stuff. Like you were kind of like the trajectory you're taking with ewr. And I was like, that's cool, I want to think about that for a little bit. And then I was like, no, I don't, that's hard. Like I don't. No wonder, you know, like that's, that's a difficult, like I don't know how you put together. So what you put together because yeah, I did that for one night and I was like, yeah, I'm going back to regulated industries. Like you can have that.
- [38:11]
B
Yeah. No, and AI. What will like say, oh, this is not where you should be spending your time? Well, here's the thing. I think with that knowledge and all the domain knowledge that I've picked up from different industries, building an AI first team and building elite like team of project managers, right, you can now take that and apply it to anything. Okay. And I think the whole game now is to take your business and add that AI layer and make as many people at the possible as possible AI first. And so that's why I think smaller teams where everybody can talk the same vocabulary and language and wear those glasses and look at problems their own way and then also interact and understand governance of like, we're going to, I'm going to have like my enterprise, I'm going to have my like individual, then I'm going to have my agents and then I have agents that have like different skill. Like you need to understand that hierarchy or that structure and be able to have that in your mind's eye of how those operations work. And then you can just take AI and you can start applying it to different industries. And so one of the things that I'm actually working on, we were, we were kind of talking about for this call is, I mean I just went through this Goldman Sachs 10,000 small business program. If you're a business owner, I would encourage you to go look at it. It's a completely free program. It's, it's basically the same hours as NBA, but it's applied to your business. And I was like the only real true agency owner in my cohort. But I was also the, there was maybe one or two other people that were using automation. They weren't maybe using like agentic AI or autonomous AI or whatever word your industry is, is choosing it. It's a similar vocabulary. But, but, but they all are asking me to do a talk about, about this and like they all understand the potential of what it could be their business, but they don't know where to start or where to apply it. And I was like, okay, let me do like a exercise to get your mindset right. So you have the mindset shift. And I think we're kind of doing that right with this call to, to hopefully to agree you're you're grabbing on what we're saying and you, you can kind of see, see the trajectory now and kind of see a better picture of where things are going. And, and we can apply this. Like I have workflows to apply to social media and I have it to apply to paid ads. Like Mantis, for example, has been ingesting all the data of Meta, right? And so like if you want to do, if you understand the basics, the fluency of AI, and then you want to apply it to Manus for paid ads because really if you're going to be running like Facebook or Instagram ads, like it has so much of the data set that maybe the others don't have that layer on top of the model, right? And so you can get more customized output, but if you understand this, you can pivot, you can change and it's just what are you going to put your focus on? And so what I'm trying to build is an elite team that all speak the language and work together and we can apply it to any business problem. And those are the businesses today that are winning. The businesses that have already gone through not just digital transformation, right? Everybody's like, oh, I just made it through digital transformation, sort of. And now you're like, now it's the next mountain or the next peak is like, you need to start climbing AI, because the people that are already up there, they're gonna be, they're gonna be so far ahead of you that it's gonna be really, really hard to catch up. And these moats are starting to shrink of these big companies that are utilizing their brand and their trust that they've had for 40 years. I mean, that's gonna go a long way, but it's getting eaten away at. And so you got a lead team of people that say, we're going to tackle this business problem and we're going to extract value from this, that this, this kind of arbitrage, like it's just AIs eating the world. Like what I was saying at the beginning of this call, AI is.
- [42:34]
A
And I think what's interesting and different about AI is, you know, usually you have to, you have to drag people into new technology because it's more tactical to practical. You know, it's more, the, more the, you know, the, the innovators or the really high tech people that get to first. But because we have this consumer component of it that has grown so rapidly now, it's like businesses and like, you know, everyday people that maybe aren't so technically inclined, they know that they need it but they don't know, you know, and the people that they're calling on like not you but like, you know, they're calling on people that they think know AI and it's like they don't inevitably. So, you know, one of the biggest things that I like to tell people, I kind of like had made this like almost like a daily devotional on my website that like, and I was just posting it because my like family, it really started with me like trying to teach my family how to utilize AI.
- [43:27]
B
Yes.
- [43:28]
A
It's like look, it's not in modules or like learning how to do it, it's in learning. Like look, just talk to the agent. Like gone are the days of like I need a prompt. Like, you know, that's like people when they would carry their like floppy disk, you know, and you had a program on like, you know, it's like look, just talk to it and experiment and just talk to it like you would a person like, hey, can I do this? Can I do that? And, and by doing that and just you know, getting comfortable with it because I see so many people, it never fails you. You're, you're walking them through utilizing AI and they want it so badly. Like, they want every word. Like, because the, one of the first things I do is install like whisper Flow or some sort of dictation on there. I'm like, look, you don't even gotta type. But they, they focus so much on those first three words and they can barely get them out. I say, look, relax, just talk to like just talk. And then that flows into, you know, now I have my mom, like she's running her whole business like from a folder on her desktop and Claude code. And I'm like, you're doing better. She's like, oh, you know, I'm sorry Ricky. I'm like, no, I'm just glad finally somebody's like, you know, like all my tech nerd friends are like there, you know, or like people that, that they think that they want my, my advice. They, they, they're more hard headed, they're more send their ways. But, and that's where I think people that you might feel like you're late to the party, you might feel like you're getting left behind. But truly like you can be a thought leader in this space if you dedicate 12, 8 to 12 months, just you know, a little bit of time each day and just you know, compound interest. It's, it's not pretty, it's not vibe coding an app in A weekend and it's making money next week. It's not pretending like that and selling a course about it. It's getting in the trenches, getting like, you've done, you know, all the education and, you know, I'm lucky that I just get to kind of like, hey, Matt, like, yeah, talk to me about that. Of course, you know, and so between that and. And, you know, get up, I get. I. But. But yeah, people don't realize how there's no one's. We're all figuring this out. You know, it's kind of like when you're coming of age and you realize that, like, your parents are just trying, you know, they're doing what they can. They don't know. You know, that's the same way with AI. Like, there's nobody that. We don't even know how these things. And this is a conversation for another day. We don't even know how they actually work. Like, no one does. So you can't, you know, I wouldn't consider anybody an expert at this point if we don't know how they're made.
- [46:11]
B
Well, okay, so, like, here's what I'm struggling with right now. Okay? So I have like a, like, I, I didn't talk about AI. I was certainly experimenting. We were using it a lot. But as, as kind of, you know, a thought leader or, you know, somebody that's out there influenced whatever you want to call it. I didn't want to talk about it until I was super educated. And to your point, the, the compound interest of the foundational knowledge and building and building and building. Like, I think certain things are just well understood. But when you talk to people, if they don't have that depth of knowledge and there's some gaps that you have to traverse to get to the next level. Right. And what I want to be able to do is help get those people into that mindset so they don't have to fall in that ditch and go through all that learning. They can expedite it. And, and I. People have been asking me to start a coaching program for a long time. And like, I'm like, like, it's a lot to teach somebody how to do SEO or, you know, digital marketing. Like, there's. I mean, I have like three. The first book I wrote. I read 300 books before I wrote my first book. Okay. Like, and I was like highlighting it up and I tried to cram as much in there as I could. And I'm. I'm working on another book, by the way. I, That's How I process stuff. Okay. Like, I talk about it, you know, I, I, I listen, I read, I write. Like, like, I just, I, I'm just like a, like I, it flows and, and I'm ready now to, to teach people where they need to go. Like, and I feel comfortable enough that I, I do believe I'm somewhat of an expert on some of this stuff. I mean, AI just told me I like top 1%. I just did a post on Facebook about it, but I'm like, But then I also discounted. Wyatt told me that I knew and I was like, it's like just sycophantic. Like these LLMs are going to be a mirror and tell you what you want to hear based upon the output. You get it because it wants to give you the right answer, right? And like you got to know this stuff. And I think that where everything is going and this goes back for me. So people that have been listening to this podcast know my mom was one of the first employees of Microsoft. I was there, I watched it. She was there for 30 something years and she was one of the first employees. I was playing video games when they, like before the Xbox, when they were just coming out with online PC games, I was playing multiplayer games with my mom's like teammates. And she's like, you can't talk to them like that. Like, that's not somebody you should talk. And I didn't know, like I was, you know, I was just like, this is who it was. And you know, yeah, and, and I look, I was going to be a computer science major. Like, like I, I went the business route, but, but I can tell you it, it was a love for me that brought me back to it and I just love technology. And I saw the writing on the wall. I saw what happened with the World Wide Web, right? You put on your resume World Wide Web. I have experience with the world. Like, I can read also. When people put like AI experience on their resume, I, I know about like where their experience level is based on how they talk about it. And it's the, it, it, it's gonna eat everything. It's good. AI is eating everything. So you have domain expertise in what you have. Like just apply AI to it. Expert in AI. Like that's what I want. My kids like understand how to use AI and then apply it to real world knowledge and your domain expertise. And the more domain expertise you have in real world knowledge, as soon as you add that AI layer to it, it makes you really, really powerful. And if you work with a bunch of people. And like I gravitate like right where we, you and I are like gravitating to each other with different kind of experience and there's other people, I'm gravitating to those people and those people start working together to achieve goals. Like you know it's, it's gonna be amazing. It's absolutely going to be amazing.
- [50:18]
A
And I do, I say for, for you know I know a lot of business owners listen and tune in and you know 10,000, 10,000 people a day are, are of retirement age retiring. And what you know some of those people might be feeling at this point in time that, that that kind of their.
- [50:39]
B
Oh yeah.
- [50:41]
A
But they don't realize that like they have their value is so, so like if you own a business today, if you're looking at selling your business today, look at the value of the data. So we've the these without getting too technical about it, you know, these LLMs, these, these AIs they've learned everything they can from the Internet. The, the, the private data of you know, let's say you owned a logistics company, an SEO company or this. So any. For those of you that have been you know, meticulous in record keeping. It is your time. They said, they said it never, you never need that. Well guess what, they were wrong. You can finally shove it to them. And I saw a company actually just got like a 300 million dollar raise the other day talking about just this and it's that look like the domain in a world where that, that technology gap is taken. It's the domain experts and, and understanding the way the processes work. You know the only the, the real unicorns I think are going to be the people that are come from a development background that throw themselves into business, into real world processes because then they'll have both and that, and that'll just be an unfair advantage. But it's, it's, it is you know and I hate when they talk about you know like junior devs are going to be gone but I think where, where they're seeing that is that the it until a certain level domain experience beats technical knowledge right now and then one you know once you get in the upper echelons to take. So I think that's where people may be feeling that disconnect or thinking that's gonna happen. It's, it's more so that look like you know, right now you know but if a technical dev can just get some of that systems thinking I think it's kind of, it's Kind of a Freaky Friday situation where if, if this side could do this and that side could do that, you know, that we're all, we can all be successful. I don't know my true definite. And I'll kind of again on this. My, my thing about AGI is I don't see it. I'm sure we'll get there. But my definition of AGI is AI bringing the best out of people and being your crutch in what you're bad at and helping you identify that. And so I think that's because that's the way I use it. I mean, kind of. I know me and you share this kind of, like, ethos of it that, you know, used for good. Like, yeah, it really can be a powerful tool. Not on a, like, hey, it told me to do this, so I'm gonna go do it. But on a just thought experiment of like, hey, we could, you know, just taking some inventory and, and seeing a, like, am I good at this? Can I get better at it?
- [53:33]
B
Like, so, so, Ricky, I want to give you an opportunity to, to kind of share some of your papers and, you know, what you have out there. But I want to end on this, guys. Like, Sam Altman started White. Well, I don't know if he started Y Combinator, but he ran White Combinator for forever. And he started a lot of businesses or got involved in a lot of businesses, like airbnb. Like, you should go look at his businesses. He left to go run open AI. If you look at his businesses, all of them can use AI. Like, all businesses can use AI. But it's like a hub and spoke model. He's taking OpenAI and he's going to apply AI to all of his businesses to get that unfair advantage because of how they're thinking and where they're at. Like, that's, that's what I'm seeing on a smaller level, right? I'm going, I'm going. There's the big transition of businesses getting handed off as, as or passed down from newer generation. But there's a lot of businesses that are going to change hands. You got to capture that domain knowledge. But you can apply AI to these different businesses and then apply capital to these different businesses and, and build that kind of operational workflow between humans and agents and scale these businesses quite quickly. I mean, I recently bought out my three partners at the agency because I wanted to take EWR in a little bit different direction. And I already got a number of investors and people that want to do, do different kind of opportunities together that, that know what we're capable of. The team, they've worked with us for a long time. And I'm kind of going, I'm not kind of, but I am going through that process. I'm saying kind of because it's all new to me, right? I don't have the, the, the JV Capital race. Like, I'm getting those domain knowledge people around me to, okay, take something public or to do something like that. And I'm assessing all the businesses I've seen over, you know, a decade plus and going, what are the businesses that we could apply AI to and what industries that could move the needle the most? And so I'm now viewing everything from that skill set and we're starting to move towards that and we're attracting companies like circle, like circle.com found us, they hired us to do some of this stuff and the world is just absolutely shifting. And I think your point on if you have that domain knowledge or you have that data, you are in the catbird seat if that. I don't even know what that really means, to be honest. But like you're in the right spot and if you've now left mainstream, you've been working for somebody for a long time, whatever, and you're stepping into consultancy, like those are the people that are going to really move the needle if they get the basic knowledge and AI. And that's really where I think that opportunity is, that domain knowledge, AI knowledge and apply those together. And hopefully this podcast has encouraged you to say, hey, I can do this, I understand this, this is new. But I've learned a lot of new things and this is going to amplify whatever I do. And I'm just encouraging you to take action now. If you want to like or follow or reach out to us, comment. If you like, kind of where I'm taking this podcast, please let me know. We are going to move more to maybe YouTube and some private trainings, which I've done in the past, but, but really focus on AI and I, I just don't see any other future without it. On the bad side though, right? CPanel, which is based here in Houston, it's got millions of websites taken down. I think that that was probably one of the newer models that people were using it for nefarious things. There's going to be a lot of that. There's always going to be good versus evil sort of thing, yin and yang and you know, like, I'm surprised more bad stuff hasn't happened yet, but, but I'm, I'm, I'm, I believe humans are naturally good and are focused on good and if we have more humans on the good side, making the world a better place, like the world's gonna look amazing in a couple years and I'm excited to see that. So Ricky, how do people get in touch with you? How do they follow your work? How they find more out about memory and kind of some of the other things that you're doing?
- [58:11]
A
Yeah, so I have a website, richardvalentine.dev Dr. Valentine on pretty much every social. So Dr. Valentine's fellow holiday. And so yeah, you're going to be able to. Some of it's not going to make any sense. But then I also have like, there's a whole page, I think I'm on day 20 now of small like 20 minute daily devotionals to AI that like, it starts you from like making a folder. So we're gonna make you your own like brain like on your computer and walk you through the AI to and it's, it's gonna be more of a teacher, man to fish mentality because that's, you know, to your point about the consultancy and stuff, I know it might seem like a crowded space, but you have to understand that all these people that, that, that, that the listeners might be seeing out there that are selling courses, they're not really doing that consultancy. There's so many small businesses that could use your help, your expertise and you know, a lot of these things if you look at it from the workflow level and not in solving a problem. But okay, what is that problem actually made of? You'll notice that all of a sudden that solution you made for one, it dominoes and it can be used in so many other places. So yeah, I'm LinkedIn, Richard L. Valentine. But yeah, I'm sure you'll have the links and always looking to provide value where I can. I don't have a course so you don't got to worry about that.
- [59:54]
B
He's not selling anything. I just asked him to come on because I wanted to, I wanted to share some of our conversations with you because I, I'm like after we get off like a big session, I'm like, oh, we should have recorded that. You know, maybe we will going forward. Right. And you know, I, I think a lot of people are going to need help and I think a lot of people want help, right? And I think it comes down to like trust and relationships, right? Because everybody can say whatever they want to say. That's why I eat Expertise, authority, trust, Google added experience. And they want to verify that in some way in authorship ways. And like they're trying to say, well, all the information, you said it at the beginning, all the information in the world is out there, but how do you use it, what to do with it? What's more important, what's valuable to you? These are all the things you got to get figured out. And I think if you had a guide to help you do that, you could get so much more done. And I mean, I wanted to start a nonprofit, honestly, that could help people with data hygiene issues. Like, we don't get taught that in school, but data hygiene I think is where it starts. And then viewing how to view everything from an AI first mentality is like an indoctrination to a certain extent. And we've had to do that one by one. And I would love to do it in groups with people and you find out with business owners and different people in your network. There's so many commonalities and there's so many ways to work together. And you know, the amount of people that are using AI, really using AI versus the amount of people that aren't, like it's a pyramid. Inverted, right? Or if you understand that analogy, if you're listening, you're at the tip of the pyramid. If you get into it now and it's going to be the tail on this thing is going to be who knows how long. And also when are people going to stop learning and plateau? But it's going to be 10 years. Like, why, if you know where it's going to be, would you not get started now? And that's, I think the biggest thing I want you to take away from this is, and I've been trying to get you, if you've listened to this, take action now because the people that are using it are getting better and better and more refined. And at a certain point, it's going to be really, really hard to catch up. Right now I think you can jump in there, but it's going to be really hard to catch up. So if you like this episode, like I said, please like it, Share it. Follow us Let me know I'm doing a good job. Tell me not to talk as much. Tell me this sounds bad. I want to hear your feedback. I'm having AI look at all my comments and roll them up and let me know about them. So I will see your comments. It's hard on all the different platforms that people comment on. A review would be super helpful. It's called Shaiko Share like Flawless if you've been listening for 16 years. But until the next time, Ricky, thanks for being on, My name is Matt Bertram. Bye. Bye for now.
- [63:06]
A
Bye, guys.