MEDIASCAPE: Insights From Digital Changemakers
Join hosts Joseph Itaya and Anika Jackson as they dive into conversations with leaders and changemakers shaping the future of digital media. Each episode explores the frontier of multimedia, artificial intelligence, marketing, branding, and communication, spotlighting how emerging digital trends and technologies are transforming industries across the globe.
MEDIASCAPE is proudly sponsored by USC Annenberg’s Master of Science in Digital Media Management (MSDMM) program. This online master’s program is designed to prepare practitioners to understand the evolving media landscape, make data-driven and ethical decisions, and build a more equitable future by leading diverse teams with the technical, artistic, analytical, and production skills needed to create engaging content and technologies for the global marketplace. Learn more or apply today at https://dmm.usc.edu.
MEDIASCAPE: Insights From Digital Changemakers
Behind the Curtain: How Advanced AI Agents Transform Modern Advertising
What happens when a seasoned digital marketer embraces AI not just as a tool, but as a foundational part of their entire business operation? Justin Lane of Adalane Media Group pulls back the curtain on his agency's remarkable AI transformation in this eye-opening conversation.
Justin reveals how he's built a sophisticated system of custom AI agents that have fundamentally changed his marketing approach. "I fire up a new agent for everything I do," he explains, detailing how he trains specialized models for different marketing tasks—from analyzing Google Ads performance to generating platform-specific content that doesn't sound AI-generated.
The results are striking. By analyzing client phone calls, Justin's AI discovered keywords that customers mentioned but never searched for online, leading to 800 targeted LinkedIn posts addressing these hidden pain points. His systems can personalize websites for individual visitors, rewrite content to match stakeholders' preferences, and even generate code so effectively that Justin admits, "I'm done writing code. I literally just have it write it."
What makes this conversation particularly valuable is Justin's candor about both capabilities and limitations. He explains the technical concepts of LoRas and RAG in accessible terms, distinguishes between hallucinations and creative output, and acknowledges that despite these advances, human creativity remains essential. "All of this AI was trained on things that creative people built," he notes.
For marketers wondering where to start their own AI journey, Justin offers practical advice: begin with accessible tools like ChatGPT or Claude, focus on asking the right questions, and systematically build your knowledge base. The competitive advantage, he suggests, belongs to early adopters—at least for now.
Ready to explore how AI might transform your marketing approach? Listen now and discover what's possible when you embrace the AI revolution happening right under our noses.
This podcast is proudly sponsored by USC Annenberg’s Master of Science in Digital Media Management (MSDMM) program. An online master’s designed to prepare practitioners to understand the evolving media landscape, make data-driven and ethical decisions, and build a more equitable future by leading diverse teams with the technical, artistic, analytical, and production skills needed to create engaging content and technologies for the global marketplace. Learn more or apply today at https://dmm.usc.edu.
Welcome to Mediascape insights from digital changemakers, a speaker series and podcast brought to you by USC Annenberg's Digital Media Management Program. Join us as we unlock the secrets to success in an increasingly digital world.
Speaker 2:It is truly a privilege and honor to have Justin Lane of Adeline Media Group on the podcast. We have known each other almost since when your business started in 2019. We met shortly after that. Justin, again, I'm so thrilled to have you here and I'm really, really excited about what we're going to be talking about today. You've been in digital for quite a while, so I wanted you to share a little bit about your background, google and AdWords and all of that stuff, and then we'll get into the really exciting stuff, which is how your agency has even transformed from the free gen AI world into this new world. That's not just generative AI, but all of the really, really cool things that you're doing that I must have in my life today.
Speaker 3:Let's do it. Thank you for having me. I'm excited to be here. So yeah, if we go back 20 years, my first entry into advertising was when Google came out with their organic search engine and I was a programmer developer at the time and I was tasked with developing hundreds of websites programmatically to game that and take the top listings, the top 10 search results of everything, and I've been playing that game. How do I generate enough content? How do I understand an algorithm and then generate enough content to get in it? That just transformed into the paid side as well. So how do I do really good at paid and what systems? Legalzoom was my first entry there, when they started writing systems to help them manage their big budgets and moving through.
Speaker 3:So incorporating technology to really amplify my output has always been the core of what I do and I think, like seven years ago, openai started providing tools to semantically process data. So I've been doing that for SEO etc. And then when all of these models came out for us to access, that's where my whole world changed. I quit writing code. I have AI that writes the code and remembers my code and keeps iterating over my code base to write the code for me so I don't have to write code anymore, just quit programming almost altogether.
Speaker 3:And then for the marketing side of it, it's been critical in understanding signals that I couldn't detect that the algorithms themselves, like Google's AI or other systems, have made shit. Like I move my budget this much and all of a sudden two ad groups have a higher CPC. It understands like maybe there was too much inventory and now Google is focusing on two ad groups have a higher CPC. It understands like maybe there was too much inventory and now Google is focusing on two ad groups and the other two it's just going for the top click Like really interesting theories are coming out of it and then we test the measure against that. So AI has just I fire up a new agent for everything I do honestly on my local computer.
Speaker 2:Okay, this is yes, so let's talk about that. You're in marketing tech, advertising operations. When you started the company, what did it look like compared to now? And I know that's a very lengthy question answer perhaps, but let's get into it.
Speaker 3:Yeah. Well, when I started it it was almost out of necessity. The company I was working at previously was an affiliate management company and they were large and they wanted to move into the measurement of e-commerce space. They were acquired and that digital measurement platform the new company didn't want anymore, so my whole division was laid off. So a good friend of mine went to W Promote and wrote Polaris. He was on the team with me and then so I kind of went off and said, well, I was testing on these large clients at the time MusclePharm, kings, hawaiian, testing this stuff for free. I was like I'll just say, hey, now you got to pay me and I'll be your agency of record. So that's kind of how it started.
Speaker 3:The transition from being the talent in the company to being accountable for everything and just trying to humble down as fast as possible was probably the most brutal thing ever. So after I went through a few of those things, I really got to the core of like what does the client need? And I'm still have friction because there's levels of optimizations that I know I need to apply. And then there's business logic where they're like but we feel like it should be this and I'm just like. Well, me and these systems don't agree with you. Historically that's been table data and charts and visualizations to explain it and they're kind of like we don't get it.
Speaker 3:Ai has bridged that communication gap and said here's a bunch of complicated data and this guy is super poor at explaining it to you. Let me try. And it just there it is. So I've leaned into AI for everything. I've had to account for the hallucinations and the training of specific things like the temporal memory of it, remembering our last conversation, or even going back let's talk about two weeks ago what we did. So I've had to incorporate that kind of temporal knowledge into the context. But now I basically take a model like a llama or something and I'll just build a Laura specifically to handle Google ads and I'll attach that Laura and it's that is the model parameter training that was done against that model, and then I can let's talk about Google ads, where do we leave off, et cetera. And now I'm deploying that for each client. Like their website is an agent that understands its marketing and all that stuff that comes through and it writes content is pretty wild, yeah.
Speaker 2:Wow. Now a question on that, because I've talked to other people who are. You know, personalization is such a big thing now, whatever that means, right? Does that mean, though, that somebody could come to a website and that the website, as an agent, would have input if that person is an existing customer, on kind of their purchasing habits, color waves, whatever it is that they might purchase from this company, and then be able to personalize the website for each person?
Speaker 3:100%, wow, 100%. Yeah, that is the new temporal knowledge graph that they're putting out. So there used to be. The RAG concept was like just feed me information that basically, in simple terms, gets prepended to my prompt.
Speaker 2:Wait before you go further for the audience. What does RAG stand for?
Speaker 3:I have to look it up. It is RAG and Laura I have to. I think Laura is low ranking Retrieval, augmented Generation, and then Laura is the other important one and that is low rank adaption. So if you think about when you go to chat GPT, you need to feed it a document and then say, okay, we're going to reference this document. I'm going to ask you a few questions about it. That's basically rag.
Speaker 3:So imagine, like the actor analogy I like to use and I don't know if it's great is like an actor, they will have to learn a British accent to play a British role. So you're altering the parameters of how they speak in general. You're not giving them new knowledge. You're saying do what you do, but do it differently. That's altering the parameters of the model. And then when you feed them the script, that's the rag part of giving them context. This is what I want you to do with it. The model, however, doesn't take up any of your token space for the prompt. So that's why we would train the model to be intimately familiar with the high level concept, topic, website, client, whatever all the products and services they have, so we don't have to keep reminding it in the context. Let's talk about this product. And, by the way, this is what this product is. Don't forget, we've already kind of modeled the parameters in the altered, the parameters in the model for the LoRa.
Speaker 2:For that, that was a lot Is a poor man's way of saying of this. I'm just thinking with Claude because I like to use Claude. I have projects set up right, so in the projects I've fed them here is everything about this project that I'm doing. Here's some language that other people use that I like, and then I can ask it for certain things based on different prompts that I give. So it's that, but on a much broader scale.
Speaker 3:No. So I'm going to sue. Claude's probably going to hate me and there's probably going to be some AI people out there that know how Claude's actually doing this, but I'm going to super simplify it. So Claude, basically, is taking all of that information and summarizing it into the appropriate tokens that it needs. So it's super condensing it and prepending it to all of your queries, saying talk like this. So it's just taking everything it needs to know about all of your documents, but giving a brief enough summary about it and tokens to say and we need to be this different when we respond back. And it's stacking all of that before you write your prompt. Then you write your prompt and then it's like, based off of all of this, I will answer that question this way.
Speaker 3:Okay, that is still retrieval. It is still going out and capturing context each time you query it. It's going out and grabbing what you did and coming back. It's not inherently training itself to always understand that whenever you come and just write a prompt with no context, to say this is what I understand. That's what the LoRa training is is to make it fully understand.
Speaker 2:One thing that I know that you and I have talked about recently was the fact that you stack all these models. So I'd love for you. You know I don't want to get you to give away your secret sauce, certainly but I do feel like what you're doing is so different than what a lot of people in traditional agencies are still doing and that you know, while they might use some Google Analytics AI tools, you know other tools and different programs. You have a full system.
Speaker 3:Yeah, and that came from like trying to to prompt everything my way through it and I found like there's times like I'll go through. Here's an example of a client. They have a blog, they have 600 posts and they every day there's a business update. We would like to be more about AI, so all of those posts need to now incorporate AI into it. So the system reads all 600 blogs every day and gets the context of the business goals what is the business about and what is it and it will rewrite those blog posts and they just sit there as an MD file. We don't use them.
Speaker 3:We could, but then from there it takes all of that content and says if you were to rewrite this here's a LinkedIn post, here's a meta post, here's a Reddit ad it builds all of the content you would need for distribution. That gets tricky because all of those different places require different text lengths for their distribution, et cetera. So I have another model that I've loaded the web page of the requirements. It says go get the requirements of a Reddit ad and then I put it in what's called an open API format. So it's almost like a schema, if you will and it basically says it needs a headline and it should be this long, et cetera. Right Running against that schema.
Speaker 3:Even then the AI doesn't really get character lengths right for building an ad. It's somewhere too long. So I'll add context and say be careful to do this and be careful, so all of that context is stored in that model. I don't have to go to the original model and say rewrite this article and then write an ad and also don't forget about this ad. I don't have to prompt all that. I basically just hand off the content to this other one and say let's write a Reddit ad and its only job is to be good at writing Reddit ads. It's its only job. Same with Google, same with Meta, et cetera. So that's when I just ship these over to do that.
Speaker 2:Wow Okay, amazing.
Speaker 3:So it sounds like your workflow, your work life, has changed a lot, even in the last two, three years. Yes, in the last few weeks I've been working on this stuff for clients in a silo, and not even telling people. I do it Like clients, because I don't publish. By the way, this was all written by OpenAI, right? I don't tell anybody that it's happened, I'm just like here's.
Speaker 3:One of the big ones was all the phone call transcripts from one client. I consumed all of that and we analyzed it and we said what keywords are we buying and what's the gap? And then what we found out was no one searches for a particular keyword, but they always mention that that's an issue on the phone call. We should probably talk about this particular product offering that we have and incorporate it. So then that wrote a bunch of LinkedIn content, 800 posts of problem solutions. Cause it from the phone calls. It identified from all of those phone calls where they mentioned that product there was a problem and then how we're the solution or this client is the solution.
Speaker 3:And then it crawled all of their blog posts and ranked them and said which of these blog posts is the best suited to present to someone to explain how we solve the problem in this area. And then did all the published all of those. Here's your LinkedIn post, here's the problem, here's a solution. Read more at our blog that talks about it. So they had 800 posts to choose from, to put it anytime they wanted to, to pump out. And they didn't know that was all AI. They're just like you must have a bunch of content writers. I'm like, well, we use some programs, right. So I've been shooting down this AI tunnel rapidly, thinking I'm way behind and everyone else is way ahead, and I am, in the last two weeks, just now, coming to the surface of like, hey, there's probably some cool tools here that people could use.
Speaker 2:Yeah, exactly. There is also the question I had this discussion earlier today about AI creating images, creating graphics. You know creating our posts, and are they too generic? How do we make sure that they are relevant for our audience, that it's not just you know making a sea of sameness when it comes to what we see from. Okay, this, you know, from this certain category, like all vacuum cleaners now have the exact same copy, or the, you know, everybody who's a service writer in this area have the exact same copy, the exact same images. So how do you counter that?
Speaker 3:Yeah, so this is. There's probably going to be AI experts that are like that's not quite how it works, but basically there is one wise old man and that is the AI that consumed all of the knowledge and that's the chat GPT that you talk to. It has one tone and since most of the content that it is consumed has been storytelling and fantasy that kind of stuff it will always start with in a world and be that dramatic. Right For both images and the models for generative AI. You just need to take a Laura on both of them and say I know you want to talk like this fella because that's your default mode, but if you can just feed it some tokens tokens is the language that they speak in feed it some tokens to say, when you talk, just be this different you will completely alter the conversation.
Speaker 3:So I have one of my core agents that I use and I probably shouldn't say this until I get sued but it is trained on David Ogilvie, so it writes just like high impact fact hitting. This is how we write content to get conversions coming through and it is completely different than what you would get Like. I'll run them both. I'll run the normal one and then the David Ogilvie one, and they're just night and day different. And then clients sometimes have their own authors. So if they have an author I'll download their stuff to talk like them.
Speaker 3:And then I don't really train off of this because it's not a lot of data, but when I publish something to like a Google document for the client to review, each individual, each stakeholder will leave comments and I'll take those comments and use AI to summarize them and turn them into some type of context to lean into when we review. So it's like what would this stakeholder think of this piece of content? Or alter this content to satisfy the stakeholder? Either one right. So it's almost like I'll write a piece of content, or AI will write a piece of content and then I'll get feedback from the other AIs of the stakeholders to say this is what they would think. And before I present it to the client I can kind of say, yeah, I think they're all going to like it, that kind of thing.
Speaker 2:Yeah, this is far above and beyond, I think, where most people are right now in their AI journeys. So how are you sharing this with clients, or what are you doing and how are you getting more clients? Are you using these same techniques? Are you doing any advertising? Is it all word of mouth at this point?
Speaker 3:Nothing. You're probably the second person that even knows that I do this, even through my clients. So no, I tried on my website and I was like I'm going to build these agents. But all of these other systems started coming out where like, oh, we have these AI agents and you upload your data and understand your context and I'm like, yeah, but read the end result Even like SEO seems to be the go-to example for all of these agents how to crawl things and do this.
Speaker 3:And when you read the end result, it is like everybody else's, like it's just what an ai would say. There's no like we need to really heavily modify the output of this to have the a better tone, like the client has. So I got a little bit discouraged on saying I just don't want to be another one that does AI because I actually download the models and actually train them for the client. So I just haven't said anything at all, and even the clients that I have don't even really fully understand what I'm doing. So there's no testimonials or use cases of us actually using AI, right.
Speaker 2:But there are testimonials for the results they've gotten and the work that you're doing for them.
Speaker 3:Yes, but those, oddly enough, are in the form of like now we had this expectation to meet of providing this much content for social media right, and now we're hitting that goal consistently and our team isn't struggling to make it, and all of the content we're generating is really thoughtful and contextual to the environment. If there's a trade show happening, I also crawl. So for every phrase or keyword that a client has, I crawled a Google search engine that I built for them through Google and I get the top two results or the top two pages of results. So I'm always understanding who's ranking where and what's happening.
Speaker 3:So if news comes through of like a conference or something, the AI will understand that oh, it looks like there's a conference coming and we have content about this, and so its recommendation would be let's publish this LinkedIn article versus all these other ones, because the conference is coming. And so just to be ahead of the curve, like to say I'm going to write about this, is that cool? And they're like, oh yeah, we forgot that was coming up, like that's a good idea. Just to be ahead of the curve frees up so much resources for folks to just get their content out, not some AI. Let's pretend like we're an authority at something right. It's their content what they're going to do, but just get it out in a low friction highly distributable way.
Speaker 2:So your workflow and your life has changed a lot. You're also saying something that I think is really important, which is you know, there's one school of thought that you need to know AI tools because you're, when you're, you know, the person who knows the tools versus the person who doesn't know the tools is going to have the job. There are other people say, well, ai is probably going to replace a lot of these jobs completely, because the technology that you're sharing right now, but you had to program that you had to put all of these together to, in essence, make sure that all of these different models are doing exactly what you want for each specific client and for each. In essence, make sure that all of these different models are doing exactly what you want for each specific client and for each. You know each goal of each client as well.
Speaker 3:Yes, I coded all of that. It's probably that component of my software itself is probably 10,000 lines of code. I say I coded it, but I have all like Claude coding it for me Well take the credit.
Speaker 3:Yeah, yeah, take the credit. But the thing that you have to be careful of and I think a lot of people will talk about this, especially as you get into the more agentic world, where you have agents talking to other agents and doing stuff and the agent is calling other agents is they all still hallucinate a little bit. So if they don't know something, they'll make something up. So I have one of the instructions. When I write code is I have a tremendous amount of output. I did this and here's why. So almost the reason why we did things, if I can get reasoning logic out of it, this is why we're coding this and this is the response. So, as a human, I can review it and say that's not that far fetched. That's cool. Fortunately, I'm in advertising, so hallucinations make it more creative. But if you were doing something super complex that required precision and a deep knowledge, I don't know that AI is the place for that, but yeah, I've coded all of this up sitting on a server at DigitalOcean, believe it or not. Yeah.
Speaker 2:So, yeah, agents are here. Right, I listen to a lot of AI podcasts and a lot of the advertisers are like the agents are coming. Well, they're clearly here. It's not a reason utilizing them to the full effect. And especially people like me, who I'm not a technical user right, I'm learning from the business perspective. I do know a lot of people in the ai world. I know a lot of founders of some of the smaller tools, so I'm getting to learn them. But what else do you think people who are in marketing advertising, specifically on the digital side, what are the most important skills that they need to have? Because it sounds like it's beyond just knowing how to use ChatGPT or Cloud or Notebook, lm or Gemini or Copilot.
Speaker 3:It doesn't have to be. You could use those. So if you really break it down and take away, like the actual Laura training that I'm doing, I'm just doing really sophisticated prompt chaining, right. So that's even the context. Like I'm taking big sentences like instead of saying I got 15 drops on me today, it's wet outside, I can just say it's raining today and that token is very small and I can put that in and still have a token allowance in the GPT prompt if I want to for context, right.
Speaker 3:So I think a hundred percent, like OpenAI, ChatGPT is moving to an enterprise model where they want to store all your information. Like just understanding fundamentally how the AIs work in the models but then getting really good at prompting them. You can't go wrong. Any engine you cannot go wrong or any model going and prompting I think is tremendously powerful and Clod is amazing because it just has so like millions of tokens you can put in. So just dump a graph in and say, tell me about this advertising and generate a graph. Right. Like, definitely go, do that A hundred percent. You could get through your day to day and make yourself worth 10 of you just using these free and open source tools, Right? So I would say Claude Lama and open, like Chad GPT, play in them equally. Right Lama is freaking awesome. I guess Glock too, but in Twitter, but I don't use that that. I guess Grok too, but in Twitter, but I don't use that that much, but I want it. I have nothing against it. So definitely keep prompting right, Because how you ask it doesn't matter if you built your own custom solution or whatever.
Speaker 3:How you ask these questions is going to be critical because it's going to take the tokens of that question and run it against its token database if you will and say how should I answer this?
Speaker 3:So that's critical. And then just a fundamental understanding of if you go to chat GPT, you're probably going to get the voice of chat GPT, that model, how it trained, like the grandfatherly voice of I know everything. How do you make it sound different? You can do that with prompting or you can use LORAs for both the images to make the images come out different when you generate them, as well as the text. So just understanding that and how they get context and temporal data. And honestly, you can go ask ChatGPT like, hey, can you explain to me LORA and RAG and temporal data and how that would all be used to do this, and just read the answer and know it, and then keep using those to do your job in media, because there's still the interfaces that you have today that are free for the most part are incredibly powerful. Incredibly powerful for it, so I'd say, keep going.
Speaker 2:Okay, nice. Yeah, I will say that most of my students know maybe not everybody listens to this podcast, but I'm also in school right now and for some of my classes I will put in. Can you explain this concept to me, exactly what you're saying? Because, to be perfectly blunt, claude explains it a lot more clearly to me than the videos. The textbook sometimes the professor, sometimes the professor, you know it breaks it down so that I can really. Okay, now I understand how to use Tableau appropriately, or how to you know, because I just finished a data and business analytics class and had to work in Solver and Power Query and Tableau and like all these different things to create graphics and images. But so I didn't ask you to do the work for me, but I asked it just step by step. Tell me you know I'm getting the wrong answer.
Speaker 2:What should I do differently? Can you look at what I put in for my codes? And so it's been a really amazing asset. I sometimes call it my best friend.
Speaker 3:I would challenge you in two areas there. One, before you ask it to explain something, give it some context and maybe things you're familiar with Say, I'm used to Excel, Right, and I know how to do this in Excel, and also I need to understand this because I'm going to teach it to other people and that will dramatically change its response out and give you scenarios on how to help you do that. And then the second thing would be if it can do it, let it do it. Let it write the code. I haven't written a SQL query in over a year. I dumped the database table and I say I need to know this about this and it will write a SQL query and I'll paste it in and I don't even think about it anymore. Nice, Like it's perfect.
Speaker 3:So as a developer who writes code and was like and I have an advantage in this ecosystem of advertising because I can write code to do things faster, I'm done writing code. I'm literally done with it. I just have it write it, I compile it. If it works, I'm like great. Could it be better? I don't know, but it works. So we're done. It's pretty wild.
Speaker 2:So, justin, what does success look like to you today? Because I'm sure it's changed also since you started your agency.
Speaker 3:Yeah, I don't. I really don't know. This is probably the first time where I really don't feel like I have an advantage, because this is becoming accessible to people so rapidly. So everything that I've been working on, in a year's time everyone will have access to. So this is almost like the wild wild west the first to deploy it and be the agency of record, if you will, to help people get integrated. They're going to win, but in a year from now, me to come in and say, no, use me. Instead, there will be no advantage. That I have right, because AI is the same as AI. If they already have an AI consulting agency, I won't win their business unless they just absolutely suck, and I doubt they will. You know what I mean. So it's almost like be the first one there, but then after that, once everybody has an AI agent, there's no room for people to build AI agents because they have AI agents that will probably build the new AI agent. So I'm decently terrified that I won't have a home in the world in the future and I don't like where I would make money. It would still be in advertising, but again, like bots will just see.
Speaker 3:I just had a conversation today with someone and they were like we have 3 000 domains in their prime real estate, domains like razorbladecom. That wasn't one of them, but it could be and I was like that doesn't matter to me anymore. Like, yeah, you're going to get type in traffic, but ideally what you would do with that is you would put up razorbladecom, you would put a model behind it, train it on everything it needs to know about razor blades and just have a prompt and say you could go to chat GPT and it'll tell you what it knows about razor blades. But if you come to razorbladecom, this thing will tell you, up to date and with precision, everything you wanted to know about razor blades. Right, and it's just a prompted website. It's not even what you just come ask it. I just don't know. I have no idea where I'm going to be in six months, no idea.
Speaker 2:Let's talk further about this. The last prompt that I gave to my students for the first quarter of the program for DMM 510, which is all about advertising you know data analytics. You know how to measure ethics, privacy, implications. We got into mad tech, but I also like to also incorporate AI tools into every class. And the last prompt I said, instead of doing the participation prompt, read this press release from a guy who I was on his podcast. He's in, I think, sweden. You know about Web 4. And here's what he's trying to do and here's what he thinks Web 4 is going to look like. And it was very puppies and sunshine and butterflies and rainbows oh my goodness right like it's going to solve all the world's problems, and this isn't this.
Speaker 2:This will happen out of it for me. I just get excited to think about and I'm sure I can do this now and you're gonna have to teach me how you know having an agent of my own, like my personal assistant agent, like go through these emails. You know, having an agent of my own, like my personal assistant agent, like go through these emails. You know, put them into categories by X, Y, Z, put them in this folder. These emails answer this way because I get 20 million guest requests for my podcasts on a daily basis and you know the people follow up if I don't respond right away and I don't usually have time to respond right away but to yeah, okay, book this appointment for me because I don't have time to look through their calendar, find time that syncs up with all of that kind of stuff, and then also being able to talk to other people's agents, as you mentioned.
Speaker 3:Yeah, that's here right now and all that needs to happen there. I think you'll start to hear people more talking about an API driven web versus like a dub, dub, dub web. And that's because if, like, you could go in and tell your AI agent, your specific personalized agent, this is what I ate today and now I'm feeling this, like I feel sick. If you tell it everything you're doing, the pattern recognition will be tremendous and it can tell you. On a Tuesday, you typically eat a lemon today, but every time you do it you don't feel well after. Maybe don't do that today, and here's the reason why. Right, but you have to feed that data. But if everything's an API your calendar, all of your emails, your health apps, all of that it can just consume it and detect these patterns without you having to prompt it. So you will be the blocker for having a great AI agent because it just won't have enough of your data to make really good decisions for you.
Speaker 3:So, yeah, I would say definitely, build your own AI agent and figure out how to get all of the data that matters to you into it and it can have temporal knowledge of, like let's just review yesterday, what was yesterday? Like. Or you can say let's go back and review all the times I ate a lemon Is there a pattern there of me hating that or something like that? Right, and it'll just like. You can just talk to it and say let's talk about lemons. I eat them. Why are they great for me? I no. Every time you eat it, you feel horrible and here's probably five reasons why. And here's some substitutes on what you should do, game changer. But it needs that data, that context about you.
Speaker 2:Yeah, well, and for the lay person right, a person who's new to AI, maybe they're in the field of marketing digital media already, maybe they're not, because I do. We have a lot of students who come to the program who already are working in the field. We have a lot of students, equally, who you know have done other careers or adjacent things, and they know that they need this knowledge. So what are some tools that you would recommend for them to start exploring so they can understand agents, understand how to create their own.
Speaker 3:Oh, my goodness, Honestly, I don't think I would leave ChatGPT or Claude. I wouldn't leave to an external resource because all of these external resources I've built AI tools in the context of how they want to monetize AI right.
Speaker 3:But, you could almost say that Claude and Gemini and ChatGPT are like their own, like they're going to be honest with you and tell you the evolutions of what's happening. So if I were brand like I don't know anything about digital marketing and I want to be a digital marketer, right, I would first what do I need to know about digital marketing? I would ask that, put that in a Google doc right, Start a folder. And then I would go research all of these topics. So what does the Google platform say about media buying and what are its best practices? Load it. Let's summarize that. What does Google say about it? Now, let's come up with some phrases and keywords that we can search in Google and let's go see what Reddit and Quora, what people say specifically Like I've tried that Put. Say specifically, like I've tried that, put that in.
Speaker 3:And by the time you're done, you kind of have a really good view of like, well, if I buy a click-based, maximized click campaign, this is what Google says it does. This is the experience people are having with it. Like, maybe, if I were to try something for a client, this is what I would try. And then you ask the cloud or the GPT, like, hey, I'm thinking about trying this for this client 's a website. Here's the thing. What do you think? Oh yeah, you should totally do that, or don't do that. Or here's some other ideas. You could be a media buyer instantly and be as knowledgeable as me. I'm not even gonna lie like my, the competition for media buying if you had the confidence to trust ai enough to say the most professional media buyer is at my keyboard's end. I just have to ask it the right questions. You would win. You would win all day.
Speaker 2:Okay. Well, going back to the other side, you still have team members, so it's not all AI driven. You still have copywriters, right? You still have web designers. You still have other people.
Speaker 3:Yeah, so I mean that's the other part of it is like all of this AI was trained on things that creative people built, inspiring people built. Like it's not making up copy, so you still need people to generate original things. And the thing about AI moving forward if we talk about like okay, you can't, like search engines will go away when people go to find a solution for something, they're going to go to an AI. That AI is going to be looking for general, like inspiring responses that people have created. Like I don't know the answer to this, or I do know the answer, but I want a very updated or creative answer. This person wrote it. I'm going to feed them in and say this is what they wrote and I will describe it. So we've gone from like everyone using AI to write copy to now AI is going to be.
Speaker 3:If it were a human desperate for fresh content, like I'm tired of reading my own work on the web, someone give me something fresh and exciting. So I think there'll be a transition into that of creators really having a space. Now that might be creators that specifically copywriters that write specifically for AI. It might look different than writing for a particular brand, but, yeah, they're necessary and AI, like I said, has its. No matter how much you prompt it, it will always say the thing you don't want it to say. Right, imagine a world or put a rocket ship emoji, like it's always going to just do that and sometimes you just can't tell it not to. It just won't listen.
Speaker 2:Yeah, Wow, we've covered so much and I feel like it's daunting but also exciting.
Speaker 3:Yes, so much and I feel like it's daunting but also exciting. Yes, and I would. I would challenge everyone who listened to how I explain things. Go find two more people that explain it as well, because I am also every day. This changes. So, as much as I follow this stuff technically and read like all the models and what they're doing and what they're good at, like this is hard to like have a day job leveraging AI to do good things and then also understand it enough to tell people. So take the way I said it, but do your own research and say is that really how that works? Hopefully we're close. Yeah, but, chad, you think I'm pretty smart?
Speaker 2:Well, that's good.
Speaker 3:Yeah.
Speaker 2:Fantastic. You've given us a lot to think about, a lot to explore. I really appreciate everything that you've shared and prompted us to do.
Speaker 1:Yeah.
Speaker 2:Yeah, any last words that you want to leave the audience with?
Speaker 3:I would say, just like, the world needs explorers, and now we have better tools so everyone can go explore almost equally. Let's just see where it goes. Keep exploring.
Speaker 2:Great. Thank you, Justin. I will have Adelaide Media in the show notes for anybody who wants to learn more about Justin. I do know that we have one student in the DMM program who's interning for you right now.
Speaker 3:Yes.
Speaker 2:So there may be some other opportunities open for those of you intent in the program. Who actually listen to the podcast?
Speaker 3:Yes, yes.
Speaker 2:Yeah.
Speaker 3:Fantastic, I will be AI heavy, but we will go through all the old school media buying techniques to get history so you can have that advantage.
Speaker 2:Fantastic, and we're going to probably do it. We'll have to do a live demo or a recorded demo at some point as well. So, counting on that. Absolutely Fantastic. Thank you to everybody who listens to Mediascape Insights from Digital Changemakers. Please leave us a rating or review, or both on your favorite platform or as many as you'd like to, because it really does help us get more discovered, find more listeners and get more engagement for our show. With that, I'll be back again next week with another amazing guest.
Speaker 1:To learn more about the Master of Science and Digital Media Management program, visit us on the web at dmmuscedu.
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