The AI Marketer's Playbook

11 | Jordan Wilson on Growing Everyday AI from Content to Consulting

Audrey Chia, Jordan Wilson Season 1 Episode 11

In this episode of AI Marketer’s Playbook, host Audrey Chai sits down with Jordan Wilson, founder of Everyday AI, to discuss his journey from multimedia journalism to launching a top AI media company. Jordan shares how he identified the power of generative AI early on, experimented with GPT technology, and grew Everyday AI into a daily podcast, live stream, and newsletter. 
Discover how Jordan balanced consistency with business growth, key themes he’s learned from AI leaders, and how AI is transforming the future of work.


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Audrey Chia:

Hello and welcome back to the AI Marketer's Playbook, where we cover actionable frameworks to help you leverage AI in business. I'm Audrey Chai, your host, and today I have with me someone really, really special, someone whom I deeply respect and admire, Jordan Wilson. Now Jordan is an AI strategist. And the founder and host of Everyday AI, one of the top media companies helping everyday professionals grow with AI through its daily live stream, podcast, and newsletter. He has also thought from engineering basics to thousands of people from entrepreneurs and small business owners to Fortune 100 executives. Welcome to the show, Jordan. I am so excited to have you.

Jordan Chia:

Audrey, thank you for having me. I'm excited. You know, talking about AI every day, if I can double down and go twice in a day, I'm like, I'm so stoked. So thank you for having me on your on your show.

Audrey Chia:

Wow. And I just wanted to say that you were actually the first person to invite me on an AI podcast. At that point in time, that was I think last year, I was really, really nervous. So I want to say a huge thank you for inviting me to be your guest and also inspiring this amazing journey that I've had so far.

Jordan Chia:

Oh, you're welcome. And clearly you have a knack for it, right? Yeah. It's, it didn't go all that bad if it turned into your own show, right?

Audrey Chia:

I hope so. I hope so. We'll see about that. Yeah. But enough about me. I think what would be amazing, right. Would be for you to share a bit of your journey with us. You know, how you went from content writing and marketing all the way to launching your own AI business.

Jordan Chia:

Yeah, for sure. I'll try to, I'll try to, be very short because it's, it's actually, a story that, you know, goes over multiple decades, but, you know, essentially I've had three kind of distinct points in, in, in my career so far. so first I spent about, about eight years as a multimedia journalist. then I worked about 10 years Leadership. But at that nonprofit, we essentially just became an activation agency for Nike and Jordan brand. so I was doing, you know, creative activations all throughout the country for the better half of a decade. And then that led me to start my own company, which turned into companies. So I started a digital strategy company, and then I kind of saw the writing on the wall in about 2020, just, you know, the power of generative AI and large language models, I'm a software geek. So we were using the GPT technology very early on. And when I saw the power, of these, you know, Even the GPT three technology and saw what happens when you know how to properly work with it. That's when I decided to start my own, AI media and consulting company everyday AI. So yeah, it's really been a culmination of like 20 plus years, that I've been working in, in various, you know, MarTech and in comms, industries that, that led me to where I'm at today.

Audrey Chia:

It's like it's meant to be right? It's almost like you were building the different skill sets for this magical moment and unlock this amazing for a lot of us marketers, right? but I would also love to know, because you were one of the first movers in the AI space, right? How was it like in the beginning? Like, how did you get the information that you needed? How do you find the experts that you needed? Because it was so new to everyone.

Jordan Chia:

Yeah. I mean, if I'm being honest, it was a little harder, right? Cause yeah, I, I started a daily live stream and podcast around generative AI like 18 months ago. so, you know, not every single person had even heard of, you know, or even knew what a large language model was. So, you know, early on, it was really just. You know, finding other smart people such as yourself that we're talking about generative AI early on in the days and in reaching out to people. I mean, for myself, it was through a lot of early experimentation. right. So, our team at, you know, my other company called Accelerant Agency, we'd been using, you know, large language models through different, you know, third party services, On a daily basis since like late 2020. So, a lot of our personal experience, with these kind of earlier, kind of GPT systems where we're, we're through our, our day to day operations. And, you know, it, it kind of, as I saw them personally, both get more powerful. And as I personally learned and, you know, taught our team how to get more out of these models, that's just when I really shifted and said, well, I think the future of marketing is everything is going to be shifting to AI first, AI native. And that's when I really started to shift, you know, my companies and my personal focus on, you know, being AI everything or every day AI.

Audrey Chia:

Yeah. Everything or every day or everything and every day. Right. So, yeah, that's awesome to hear. Even for me, when I first. You know, saw the power of chat GPT, right? I knew that it was not going away. It was the moment where you're like, yep, this, this thing is super powerful. I cannot ignore it. And I have to learn how to leverage it. Right. Which is why I think your podcast is so useful for everyone. And I would also love to understand, right? Because. As AI evolves, your business also evolved, right? How did your business evolve or pivot over, you know, the past year? Has it actually pivoted or were you like dead set on doing like consulting and training for your clients?

Jordan Chia:

Yeah, that's, that's a great question. And, you know, kind of full disclosure when I started this, I said, let me do this. Every day for a year, which is like wild, right? To talk about doing a daily live stream, a daily podcast, a daily newsletter, every single day for a year. So, but I said, let me do this every day for a year before I worry about money, before I worry about clients, before I worry about, you know, creating a, you know, business value, which is probably, you know, terrible advice and a terrible way to run a business, if I'm being honest. But, you know, I'm glad I did it. because if I would have made decisions based on, you know, partnerships or money early on, I think I would have maybe, or we would have lost our way and we would have started focusing on things that maybe weren't important. so to be able to work through literally 365 days of generative AI, without being influenced by, oh, I need to do this for this client. And, you know, there are plenty of, you know, Plenty of opportunities that we just really didn't, prioritize until we hit that year mark. And, you know, so things have obviously changed, in the last couple of months, since that's happened.

Audrey Chia:

For a lot of business owners who are in the AI space. We would have seen, you know, different pockets of opportunity, right? But also finding the focus or knowing when to pivot and move out of something that isn't working is very important Especially in a field that's always changing, right? And I think I would also love to know since you have had, you know, so many guests on your show 365 days. It's so insane, right? What are some of the key themes that you have noticed recurring themes that your guests have also shared?

Jordan Chia:

So, I mean, there's, there's the, the obvious and then there's kind of the, the under the radar. Yeah. So, you know, doing this over the last, yeah, I think we're at seven, 17 months now, something like that. I mean, So some, some obvious ones, right? generative AI is changing how we work, literally top to bottom. So, you know, we don't cover one particular, area of business or, or one niche, you know, in, in the business world. So we really cover AI from all angles, all industries. So, I'll, I'll say one common, well known theme right now is generative AI is the future of work. Right. And I think this depends on where you're located, right? So, I'm in the U S there's like zero regulation. There's, there's very few, actual, laws or anything like that. So, implementation, I mean, it's been fast, it's been messy. but I, I don't think you can argue with the future of work is with generative AI. At its core, right? you know, the six largest companies, in the U S which are, I believe six out of the eight largest companies in the world, they've, they've gone all in, they've gone all in on AI. So, you know, your Microsoft, your Apple, your meta Nvidia, et cetera. Right. so they, they really dictate. How we all work. So whether, you know, if, if you're still listening out there and you're still kind of quote unquote on the fence about generative AI, or if you're a business leader, you know, and you're, reluctant to, you know, implement large language models in your, in your business, I mean, you're, you're asking to fail because, you don't get to make the rules, right. the, the, the companies that dictate how we work. Right. Microsoft. They dictate how we work. Apple. They dictate how we work. In many cases. Meta. Google. Alphabet. Right. They dictate how we work. So, you, you can't continue to play this non generative AI game. when the playing field is going. Generative AI. It's going AI first, AI native. So that would be probably one of the more obvious things that I've learned by talking to literally hundreds of the world's smartest people in AI. maybe one of the non obvious or more under the radar learnings that I've I've seen. It's just a lack of, of training and education, you know, companies, you know, even the big tech trillionaire companies, I don't think are doing a great job. If I'm being honest at training their employees, top to bottom, fortune 500 companies. Aren't doing. I mean, there are some that are doing a good job, and then there's some that aren't doing a great job. So, that's that's what I would say is, you know, two of my biggest findings from talking to a lot of smart people. And, you know, there's really, almost a juxtaposition there, right? When, everyone's saying the future of work is a I, but very few people are, investing in in proper training and teaching employees.

Audrey Chia:

Yeah, this is a lot of us in this AI space on LinkedIn or online, right on Twitter. We, we are in a specific bubble. So the content that we see are all AI related content, but we don't Realized that a lot of people out there beyond this bubble are still pretty new to chat gpt So interestingly, I also held a workshop recently I thought that most of my participants would have had some experience with chat gpt and There was still a huge bunch of folks who haven't actually tested it, haven't actually downloaded it, haven't actually, you know, tried it which was really surprising but it was also heartening to know that they were interested in taking out a skill because they recognize that it's important and it's the future, right? So I think that's something that we are, we will take some time to transit into but I think there will definitely be a need for training and consulting. and with that, I would also love to know, is there Anything that you know, or was there anything that surprised you during the podcast that you've had? Was there a moment where you're like, wow, I did not know this or a super surprising fact that stuck with you?

Jordan Chia:

Yeah. Gosh. I mean, you'd think after doing like 300 plus episodes, I w I would have a list of them, but I would actually say probably not. you know, very rarely, you know, am I interviewing a guest and the guest says something that you know, I'm completely shocked by. I mean, part of it is, you know, we, we, we do a decent amount of research. but you know, like I said, probably. again, the biggest thing that is technically shocking to me is, you know, you have companies, you know, like I said, fortune 500 companies that are investing, you know, six, seven, eight figures, into their, generative AI efforts and just aren't training their, their people. So to me, that's the biggest one is, you know, companies. I like, I think if they move too early, they might've screwed themselves over a little bit, but you know, companies that finally started to deeply invest in generative AI and, you know, fine tuning models based on their data, you know, in 2024, like I said, You know, companies that seemed like we're fine, you know, throwing, you know, six, seven, sometimes eight figures, at this generative AI solution, but the, you know, it's, it's like they were investing pennies on the dollar in terms of teaching, you know, their hundreds or thousands or tens of thousands of employees, how to actually use these systems that they were investing in. So, I would say that was probably the only big, you know, kind of, Takeaway or, or one of the biggest surprises that, I guess I'm continually running into.

Audrey Chia:

And based on what you've observed, right, why do you think this gap exists, right? So it seems like people know that there's potential, they're investing money, but yet there's still a gap between, you know, management and everyone else, right? Do you think that it stems from, you know, the way people work or function? Any insights around that?

Jordan Chia:

Yeah. Oh gosh. Any insights? I mean, I could talk for like three hours just on this topic. you know, I guess. A couple of main insights. One is very few people, aside from your, you know, actual people who are building your AI systems, those with, you know, deep learning machine learning backgrounds, very few people actually understand large language models. right. Like there's this, you know, sometimes they're called, you know, a black box and, very, I think very few people, actually explore, the Like what happens under the hood, right. And it's, it's, it's really not difficult, to understand large language models, right? You can, in a couple of hours of, you know, exploring and reading, you can actually come to a great understanding, of large language models. And, I think when you come to that understanding and when you actually, try to educate yourself a little bit, then I think you spend much less time, on the back end. Trying to fix or improve outputs. And then you also spend less time on the front end, you know, trying to strategize or build, your generative AI solution if you actually understand how it works. So, I. I think people, have a false kind of sense of, of what a large language model is. And they think, Oh, I need to be, you know, someone with a deep learning background to really understand a large language model. And it's like, no, you don't write a couple of hours again, and you will understand the basics, right? You're not going to be an expert in a couple of hours, but a couple of hours. actually reading, understanding, you know, going into, you know, kind of the sandboxes or playgrounds that, you know, open AI and, and, and thropic, and, and Google set up, right. going in there once you understand it and going in there and playing yourself, I, I think is, such an under utilized, feature or aspect that so many people, especially marketers, but so many people. Should be doing that, right? it's super simple. it's, it's, you know, essentially no code, low code. So anyone can go in and do this and explore and learn firsthand. And that's what you need to be doing.

Audrey Chia:

You see it about just doing it right. And learning from the experience. And I think. A lot of people don't realize that AI is basically a new skill set and like with any other skills that you gotta put in the reps, put in the work, try and fail and experiment and that's how you learn right? and that's how you grow a lot, a lot faster. So going into the, the idea of like training and learning, right? How should someone get started if they are new to it? I know you also have, you know, your CHAT GPT foundations and basics for beginners. Would you like to tell us more a bit about that and also how you would recommend someone to get started?

Jordan Chia:

Yeah, if I'm being honest, that's, I think, yeah, am I biased maybe, but also not. Right. So, yeah, we've taught, I think now like 7, 000, business leaders, how to use chat GPT, right. and it's through this understanding that I think you can also have a pretty good baseline, of just large language models in general. So we do this, usually like twice a week. it's. Free, there's no catch it's live. It's not like a recorded webinar. And, you know, Audrey, like one thing I, you know, not fresh. Well, kind of frustrated if I'm being honest, right? Like I get frustrated because people are out there on, on LinkedIn and Twitter. And, you know, they're, they're pushing all of these, you know, chat, GBT, this, this, and this, and I'm like, you know, if I'm being honest, 90 percent of what I see out there, it's, it's things that are incorrect. it's things that are, ill. Research like they're, they're, they're just not research and it's just false. And it's just, you know, people are just, you know, pushing, I think a lot of times like snake oil, right. we build this from scratch and we update it every single week. And it is free because I feel. you know, and maybe this is me, you know, really wanting businesses to succeed and kind of my nonprofit background, but you know, there's not a lot of people I think out there that you can trust, right. And that, Oh, are they actually going out there and are they, you know, testing things, are they experimenting? Are they talking to experts? Right. And that's literally all we do at everyday AI. We go, when we try to break things, right. We talk to the smartest people in the world. we test out all the models and we don't just take what a company tells. Tells us to, to put out there. Right. so that's why I think it's like our classes, I think amazing. Right. And we literally have people from, you know, those same tech companies that I mentioned earlier, the largest companies in the world that take our courses. Right. And I get, you know, testimonials all the time. People are like, I spent 2, 000 or I spent 1, 000. Spend a weekend, you know, at this, you know, chat GPT seminar or this large language model conference. And they're like, I learned more in your 90 minutes, than I did at this paid thing, right? because so many people I think, are just worried about getting people into a sales funnel and selling them. and what I'm really trying to do is to flip that and to just provide value. And free education, because I'm, I'm big on that is, you know, being able, maybe that's also my background as a investigative reporter, but, to be able to investigate these large language models and simplify them and make it easy, for the everyday person to understand and how they can actually start going, use these, you know, AI models the correct way.

Audrey Chia:

It's amazing to hear. And I think like what you said, I do agree that there is quite a lot of content out there where it's really hard. to apply whatever they are sharing. Let's just put it that way. And I think people who actually use AI in their everyday would realize that you can't just copy these frameworks or these prompts or this like, you know, cut and paste thing. You really have to figure out how do you plan your human expertise and AI execution to get like quality results. And again, that comes through putting in the work and experimenting and figuring it out. Or like what you said, attending your 90 minute webinar, which I'm sure is power packed with value. And with that, I would love to see if you could share something with our audience. How can they get started with, for example ChatGPT

Jordan Chia:

Yeah, no, for sure. Yeah. I'd love to, share that. So I'm going to go ahead and bring up my screen here. All right. So I'll try to do my best describing, what this actually is. so this is our. prime prompt polish course, right? So this is just one, one slide, you know, there's probably, I don't know, 150 slides or something like that. So, you know, take this with a grain of salt. This is just something in the middle of the good stuff. You know, we're bringing the good stuff for, for Audrey and, you know, I rarely even talk about this on the podcast. you know, yeah, this is, this is just, you know, some stuff that is really, you know, I I'd say part of our secret sauce, but, so I'd say Audrey, one of the. biggest mistakes that people make, inside chat. GPT is copy and paste prompts. if I'm being honest, they don't work. That's not, that's not how large language models are built. I know that's great for LinkedIn and don't get me wrong. It's great to get people to give people ideas, on what large language models are capable of. but the best way to work. With a large language model is iteratively, it's to have a conversation. It is to, essentially train, right. So to train a chat, or to train, you know, if you're building, a GPT or a projects in Claude or a gems in, Google Gemini, et cetera, but you know, you really want to have a conversation, with a model and to give it examples. Right. so to get a little, mathematical or, or, or scientific. here, you know, any study that you read, right. And I read these a lot. I spend my weekends, I'm a dork, you know, reading, a lot of papers that come out on, different large language model benchmarks, different prompting methodologies, across all these different large language models that, you know, are getting updated. It seems like now weekly, right. And every single study shows, the more essential, shots, that That you have in a prompt, the better the output's going to be regardless of the model, regardless if you're using, you know, GPT four, Oh, latest, or, you know, Gemini, Oh, eight 26 or Claude three, five sauna. It doesn't matter what large language model that you're using. The prompt, the prompting methodology. stays the same and that is the more shots or the more iterative you're prompting, the better the results are going to be every single time. so what I'm showing here on the screen, this is our refine Q portion of priming, right? and essentially what this is without, accidentally talking for 30 minutes. this is, this is essentially training a model. So you go through refine Q stands for roll examples, fetch, Insights narrate, explain, and question. and I'll kind of read out the bottom. So question is you do not ask for an output. You ask what chat GPT, you ask chat GPT, what questions it has. And this is essentially right. People always rush like, right. Like if I'm being honest, like human nature. you, you want to be as lazy as possible. And so I think when people are working with these large language models and you see how powerful they are and oh, they're great. Right? So you think, oh, I'm going to spend, you know, 10 seconds and I'm going to get 10 hours of work. That's not the case. Right? like I said, I'm, I'm a huge, advocate on working with large language models the correct way. And so this refined Q method here is essentially a step by step process where you have a conversation. So what happens after this is before you are asking, you know, before you are asking the model for an output. So let's say writing landing page copy for everyday AI, that's the example here, right? So. At the very end of this long, refined queue, we are not asking for landing page copy, right? We are essentially turning chat GPT into a consultant and you know, what happens after this, after this refined queue, which is part of our priming process, you essentially have a conversation with chat GPT and this, sets off a string of essentially back and forth conversations. So in the same way that, you know, if you hired. you know, 100 new employees at a company, you would take them through a process. You would take them through an onboarding, a training, reinforcement, learning, quizzing, knowledge, retention. You would go through a process with these, humans. If you were to hire a bunch of humans. And, that's essentially what the refined Q step, in our priming of Prime Prom Polish. That's what we teach people to do, because once you go through this and yes, it is, it can be a little bit time consuming. It can take, you know, 15 to 30 minutes to go through our whole prime prompt polish process. but then at the end, you essentially have an expert, right? that is going to give you, exponentially better outputs, than if you were to just, you know, drop in some long copy and paste prompt where you are immediately. Asking for an output. so I'd say that is, you know, when, whether it's marketers, content writers, advertisers, people in communication or anything, right. but people always rush to ask a model for an output when, you know, generally you're probably going to be going back and forth, at least a dozen or a few dozen times before you actually, are asking for that output. Output, whatever that output may be. So that's just a kind of long drawn out way to kind of talk about what's on the screen here.

Audrey Chia:

That's a super hot teaser you have for your course right there. And if you guys don't already see the value, I, you're missing out. But yeah, thanks for sharing that, Jordan. I think what you said about, you know, it's an iterative process, right? That's what people need to know. Because. Even for myself, when I'm prompting, I'm having that conversation, I'm giving it enough information, and your framework of Refine Q gives AI enough context to then have that frame of mind to solve a problem rather than you're just asking it to solve a problem without the right context, without the right framework, without the right examples, and you're gonna get a not that great output.

Jordan Chia:

Yeah, exactly. And yeah, it just all, you know, stems back to this, you know, an example of a shot. So that's like an input output pairing, right? So you have to, through conversation, just like you would a student, right? You have to go through, you know, train it up, give it an assignment and teach it what's wrong. And yeah, it's, you know, it can in theory seem like counterintuitive to go through. And, you know, you might think, Oh, if I can just put A single prompt in and get something decent enough on the output. Like, why would I waste the time to go through this? Well, Hey, for, for, for marketers out there listening, our audiences are getting drowned out by literally just C C level. Right. C plus maybe on a good day. Right. But we're getting drowned out by C plus level content generated by large language models. so, I mean, you can keep doing these, you know, one shot or, you know, zero shot prompts, but your messaging is. Is not going to resonate with your audience because, personally, I'm, I'm tired of seeing so much content written by AI because even people who think, Oh, you know, if I, if I just put this in my prompt, it's going to sound like a human. No, it's, it's, it's not. you know, and I think consumers are, you know, getting a little smarter, to starting to know how to. Tune out, you know, even if they aren't doing it intentionally, because we are just getting literally bombarded, with this, you know, average content, not now it's everywhere, right? You really have to take it a step further to stand out, not just in your content writing, but anything that you might be using a large language model for.

Audrey Chia:

Definitely. And I think one thing I would love to add to that is, I think as the world becomes more AI, being human is going to be even more important, right? Because your unique human voice, that perspective, the stories that you have, they are uniquely yours. I think that as a writer or marketer, these things are going to stand out. And even like for brands, right? Branding is going to be all like even more so important, especially when everyone's creating content at scale..

Jordan Chia:

Yeah, absolutely. And that's why you like humans need to spend more time conversing with models before you ask for an output, whatever that output is, right? Whether, yeah, whether you're using it for marketing purposes, content, writing, analysis, automation, whatever it is, right. You need to spend as much time as you can with these large language models. Having a conversation. So we can better understand human tendencies, human nature, what makes humans tick, right? because another thing that people don't talk about is these models are getting larger and larger and, you know, large language models are generative, they're not deterministic. So, you know, the same, you can run the same, quote, unquote, prompt 100 times and get 90 different results. You can get three different results with variations, right? so because the training data in these models is so large, there's a lot of just bad. Garbage, low quality data that ends up in these training models. Yes, smart humans do a pretty good job of weeding out the bad information and training the models on the good information, but it's not always going to be a hundred percent, which is why I think right now we are in an epidemic of subpar marketing, because people don't really pay enough attention or go through the proper process of learning the models and they're just fine with putting more. Of, you know, more C plus content out there, right? Oh, before we could only get, you know, two articles or three social media posts a week. And now they're like, Oh, now we can do 20 articles and 50 social media posts a week. Well, it's like, are you doing anything? If all you're doing is putting out more, subpar content.

Audrey Chia:

And then the idea of quality versus quantity. So again, like is one or two. Quality pieces better than just 10 not that great, you know pieces That is something that's a food for thought for people right and and with that also, Do you have any hot secret tips that you have for using chat GPT or AI that you personally love? I'm sure you have a couple in your pocket

Jordan Chia:

Yeah, I mean If if if i'm being honest, I don't have any short Tips and tricks, right? Because my process is very in depth. It is very, detailed and in thorough. one thing that I will say, a kind of hot tip, and it's not necessarily, chat GPT related, but kind of, right? but I'll say for Small tasks, make as many custom GPTs as you can. I think people miss the mark when it comes to, you know, whether we're talking, you know, custom GPTs from open AI, chat GPT, or whether we're talking about projects from Claude or whether we're talking about gems from Google, I think people try to stuff too much. into these, you know, kind of, many, are personalized or bespoke AI systems, right? And they try to, you know, really do very complex multi step tasks. so I'll say break it down, right? especially with GPTs inside of chat GPT, the fact that you can reference or edit. At mention multiple GPTs in the same window under the same context window. Right? Like that's huge. That's something I think, you know, chat GPT still has an advantage. I don't see how, you know, Gemini and, Claude can't be implementing this feature in the near future. It's too powerful. Right. But when you think of those, those tasks, whatever you're doing, whether it's in. marketing, ideation, brainstorming, automation, whatever it is. If you can just take those down and break them into very bite sized chunks, and then go through kind of like a process, like I just had up on screen for each of those chunks and then turn them into GPTs, right? Like that is a huge, a huge hack. I think GPTs, you know, when they were first announced in November, there was a lot of fan, fanfare, but then that fanfare I think kind of waned, because I think again, because of stuff that gets shared on social media, people think, Oh, I just need to get a longer prompt or I need to get longer system instructions into a chat GBT. And it's like, no, that's not literally not how it works. I don't know why people want to argue with math and science. you know, it's, it's irrefutable, right? So have a conversation, break it down into smaller chunks. That's why in theory, a chain of thought prompting is always more effective, right? So when you break something down step by step, not only is that the correct prompting methodology, but that's even the best methodology for when you want to, you know, get into kind of the, Beginner of a more agentic workflow or working, you know, with multiple bespoke versions of these models is you need to break it up into smaller, you know, thought, you know, think chain of thought, think of, you know, what's that process that you go through all the time, break that out into small chunks and build a GPT around each of those chunks.

Audrey Chia:

So like when you see it, right, stepping back from your own workflows and then figuring out what is your thought process? What is your workflow? And then. It's actually spending time building out, you know, the AI systems or the AI prompt frameworks that you personally will use for each step and not being afraid to Try and fail during this process is extremely important I have a feeling a lot of people think that AI is a shortcut, right? So they're thinking hey I just want to see results But they also don't realize the work that has to go in in order for you to see See those magical results that are of high quality. Yeah. And also Jordan, I think one interesting thing I would love to, to have a chat with you about is your journey of entrepreneurship. So I know it's everyday AI, right? Oh, have you managed to stay consistent? Every single day of the year. It's insane. Like you have to have so much grit and determination to, to make it happen. Right. Can you talk us through that process?

Jordan Chia:

Yeah. So, I mean, part of it is I found myself before I started every day, AI spending more and more time. Exploring ways to use AI to improve, my other company's workflow to improve outputs for our clients. And yeah, you know, I kind of referenced this earlier, but I, I, I came to a realization that, number one, you know, very early on, I, I noticed, cause I have a background in, you know, marketing and communications, I noticed that generative AI was, you know, Was going to really flip the business landscape and change how we all work. so part of it was I didn't want to personally get left behind. the other part is I felt there weren't a lot of good resources for kind of everyday people, if that makes sense. Right. I fancy myself a little bit of a dork. Sure. but you know, I, I didn't, up until that point, I didn't have a, You know, a deep learning background. I didn't have a machine learning background in, you know, 2020. I, you know, I've done since I've done, you know, executive education, you know, certifications, all of that, to, you know, kind of still get the academic side, you know, under my belt, but, you know, Practice, right? Like there's, there's the saying that you haven't learned something until you can teach something. And, you know, now we're, you know, teaching, you know, hundreds of thousands of people, you know, through the podcast. Right. So I knew even for myself personally, for my companies that we weren't going to be able to keep up and help clients and, you know, help those companies that we were, you know, doing AI strategy for, we weren't going to be able to help and Give them actual, good advice and to steer them in a correct direction, unless we were practitioners. Right. So that's why we do this literally every single day. Right. And that's why I can, you know, sit in, you know, a room of people that are like, like from, books or certification or, kind of, you know, some of those perspectives, they might be smarter than me. right. But I can keep up and I can speak the language because I'm practicing it Literally every single day, right? It's like, if you're trying to learn a new language, like the best way to do it is through immersion, right? it's, it's much better than, Oh, once a week, I'm going to, read a textbook or once a week, I'm going to, you know, practice my Spanish. No, it's better if you immerse yourself in it. Every single day. And if it becomes a part of, of who you are, how you think, how you work, right? So that's a decision that I made, you know, multiple years ago. And yeah, so doing it every single day has become a habit, but it's also become, really the foundation for how I work and how I think.

Audrey Chia:

That's amazing, and I think it also shows a lot of your internal, like, belief systems and values, right? That ability to learn, and then that want and desire to share that knowledge is also really beautiful to see. And I think so many of us, including myself, have learnt so much from your show. I know of many creators who are like, Did you hear his podcast? It's amazing. So, you know, we are all, we are all like, this is, this is a really great show. So thank you for the work that you've been putting in. I think it's, it has been amazing for so many of us in the business of your show. And with that, could you tell us a little bit more about Everyday AI, what you guys do and where people can find you?

Jordan Chia:

Yeah, no. And thank you for those kind words, Audrey. That, that, that means a lot. so yeah, I'd say every day AI, it is the best place to come and learn AI for free, right? Unbiased as well, right? Because yeah, companies put out great content trainings and, you know, free certifications. But a lot of it is like, Oh, well, you do this and you come learn our model, right? You learn our software, you get into our infrastructure. So every day AI we're, we're different, right? we, we, we teach and we talk about all the different, you know, AI Do we have a lean toward chat GPT? Sure. A little bit, because that's probably, more popular than the other, you know, next eight large or sorry, the next like eight, generative AI systems combined. Right. but we teach everything. So it's a one place through our daily practice. Live stream, right? So to come on and be able to ask, you know, experts from, you know, Microsoft or Amazon or IBM to be able to ask them questions and get answers in real time. I think that's huge, right? And that's why, you know, we really are education focused in teaching people the right way and and. Having, answers and, and, and tackling tough subjects like, like ethics, and in governance. Right. but doing it hopefully in a fun way. So, you know, please, join us. Yeah. We do it the live stream and that goes out on a podcast every single day. and then in a newsletter every single day, that's free as well. So yeah, that's a big thing is just, giving everyone free access. to unbiased AI education that you can learn it, you can put it into practice and grow your company and grow your career. So that's what we're about at everyday AI. so yeah, you can join us on, on LinkedIn, YouTube, just looking up everyday AI, or just go to your. Every day, AI. com and go, go, go listen to the podcast with, with Audrey. It was great. Go, go type her name in there. You know, you can, I'm sure, I'm sure she dropped some secrets on our podcast that maybe she hasn't even talked about with ours. So yeah, we, we've had, you know, hundreds of great guests like Audrey. So you can go in and literally like, if you want to, like, Learn about marketing. You can just type in marketing in the search bar. And literally we've talked to, you know, the marketing director at NVIDIA, the, the, the director of a digital marketer, right? The president of digital marketer, right? Like, so no matter what you are trying to learn, you can literally just go to our website, type it in. And there's probably dozens of. In depth, high quality episodes, resources, emails. You can go back and read. It's, it's all there. It's just a huge free generative AI university.

Audrey Chia:

It's mega. And if I were you, I'm not going to miss this. Okay. So please do. So check out everyday AI and thank you again, Jordan, for joining us. It was a pleasure having you on the show and thank you guys for tuning in. Don't forget to subscribe to the podcast and hit the bell for more actionable marketing insights. See you next time.