Ep: 500 Top Takeaways of Everyday AI So Far Through 500 Episodes
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This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. The generative AI world is barely recognizable from where it was when I started this Everyday AI Show more than two years ago.

And as we celebrate our 500th episode, wow, that's crazy. Uh, but yeah, as we celebrate our 500th episode, uh,

You all thought it would be a good idea to talk about some of the top takeaways from everyday AI so far. So I'm excited to share about that today and talk about some of the future of work discussions, how AI is going to be impacting and is already impacting employment, how it's going to change traditional service industries and even redefining our own human skill and value.

So I'm excited today to talk about the top takeaways of everyday AI so far as we celebrate our 500th episode. All right, what's going on y'all? My name is Jordan Wilson and I'm the host of Everyday AI. This is your daily live stream podcast and free daily newsletter helping us all not just learn AI, but how we can leverage generative AI to grow our companies and our careers. So

Is that what you're trying to do? If so, you're definitely in the right place. It starts here with our daily live stream and podcast, but how you actually leverage this and take advantage of all of this is by going actually to our website, youreverydayai.com. There, you can sign up for our free daily newsletter where we not just recap every day's show, but keep

Keep you up to date with everything else happening in the world of generative AI, large language models that day. So if you haven't already, you need to go read our free daily newsletter. Speaking of our free daily newsletter, well, if you're looking for the daily news, it'll be in there. But in our newsletter, we asked you, said, hey, what do you want to know?

Right. We can do a lot of different things for a 500th episode. I asked you all, hey, do you want former guests to interview me? Should the live stream audiences grill me? Do you want to hear about some of my favorite episodes? But no, you all wanted by a far margin. You wanted to hear the top takeaways of everyday AI so far.

Which is kind of broad. So I just put together a lot of my different thoughts. But, you know, ultimately, this is about you all, right? So first of all, yeah, maybe you don't know. Maybe you just listen on the podcast. Maybe, you know, you don't listen too much to the show at all. Maybe today's your first time. But

what this thing ultimately is, it's for you all, right? And I'm going to get into that a little bit more, but I'd love to hear from you guys. I'd love to hear, you know, if you have questions, if you have thoughts, if you have comments, please get them in. You know, Jay saying, what a great milestone, 500 episodes. Congrats, Jordan. And thanks for all you do for us.

This is our 500th episode. I have a lot of stuff planned that I want to talk about, but mainly I do just want to hear from you all. If you do have questions, whether about AI, obviously. If you want to ask me something personally, sure, I'll

I'll try to answer as much as I can, whatever you want to know. But I do have some of my top takeaways from 500 shows. Yeah. Hotspot for the win. We'll see about that, Douglas. We'll see if the hotspot can keep up with this. So let's get going. Hey, Brian Feltz says congrats on the 500th. Thanks, Brian.

Good lifelong college friend and roommate right there. And Brian's got a great AI podcast now, too. So love to see it. All right. Let's get into it. Let's talk about our biggest takeaways. So first,

It's unrecognizable, right? AI today is unrecognizable from where it was when I started the Everyday AI show more than two years ago, right? At that time, you know, ChatGPT was out, but that was it, right? For the most part, yes, ChatGPT had just kind of gone viral and everyone was talking about it and everyone was using it and everyone was kind of confused, but that was really it, right? So I believe I started this show

I'm looking at the, I think it was April. So yeah, just over two years ago, generative AI was an afterthought, right? Like people weren't talking about it. It wasn't integrated into how we work. It's obviously completely different now.

You can go into any enterprise company and not, you know, and they don't have a generative AI plan. Every single enterprise company has a generative AI plan. It's obviously evolving. Not everyone has it figured out, right? Very few people actually do just because of the speed of developments, but it's completely different now, right? You have, obviously you have every single

single, uh, big player, uh, in the game right now. But, you know, even before we get into that, I should probably start it where this started. Right. So yes, more than more than two years ago, I've maybe told the story once or twice, but not in a lot of depth. And maybe, uh, if, if I tell that story, maybe this will make sense and maybe this will, uh, resonate a little bit more. So I was a writer. I was a journalist, right? Um,

in a former life. So I spent about seven years as a multimedia journalist. Then I spent almost a decade, nine and a half years in nonprofit leadership, but we just really became an activation agency for Nike and Jordan brand. And then I started my own company called Accelerant Agency. So I remember very vividly as soon as the GPT technology came out in late 2020. So this is two years before chat GPT.

I was using it every day. The day it came out, right? All these third parties, there is, I don't know, copy AI, Jasper, a bunch of other ones. The day these pieces of software came out, I started using them heavily. And my agency, you know, all of our teams started using it as well. And, you know, at first it was helpful, but then I learned.

The more I understand about the technology, the more I work with it, the more I learn how to apply it to the work that we were doing at the time. It wasn't just the more impactful it was, but I realized that, wait, you know, I've been getting paid to write for 20 years. I did okay in my early journalism days. I won a Pulitzer Fellowship, ACP Story of the Year. So I did okay, you know, my early days as a journalist. But there was a point where I'm like, wait, this...

AI tool is better than me at writing. And that was weird. It was a hard kind of conversation to have with myself. But that really made me open my eyes to what generative AI is capable of, right? And again, this is two years before ChatGPT. So in that two years, I was using and trying every single generative AI tool that was out. And I wanted to learn more. So I

try to gobble up all the information there was online about this GPT technology. And there wasn't a lot. And we also had some early diffusion models on the image side. And I realized that any information out there, it was super technical. I didn't understand it. It was almost like showing up to a party that you weren't invited for. That's what it was like for me back in 2020, 2021, trying to learn generative AI. And I'm like, this stinks.

I knew how transformative this technology was, but

I couldn't find any good place, any good avenue to learn. So I said, okay, well, I'm going to start it eventually. At the time, I was having one of my best months, one of my best seasons ever at Accelerant Agency. We had a nice little team, good clients. From a business perspective, when I had that epiphany, it was the best month I had ever done in my company.

But at that point, I made a decision. I said, I have to slowly shut this thing down.

It took longer than I would have wanted to in order to be able to do this everyday AI thing daily. It took like a year and a half to kind of wind things down. We had a lot of clients. We signed very long-term contracts with clients, sometimes 12 to 18 months. So it took a long time to kind of quote unquote wind that business down so I could focus on everyday AI. And it actually started in the car.

I had been thinking about it for a very long time. And I was actually driving to a friend's wedding with my wife and one of my good friends, Kenny. And I told them about this idea.

And, you know, so we kind of spitballed it on the way. And, you know, I think both of them told me, you know, like, this sounds like a good idea, but are you sure about doing it every single day? And I don't know. I made that decision back then. And maybe you've come to this realization, too, that unless I was practicing every single day generative AI, unless I was learning about it, I felt like I was going to get left behind. Right.

And don't get me wrong, even though I spend the majority of my days now doing that exact same thing, right? Like getting to talk with some brilliant people here at the Google Cloud Next conference and learning from literally the smartest people in the world. But I still feel that way, right? I still feel like, man, it's so hard to keep up with what's possible now and how we work. So that's kind of how this thing started. If I'm being honest, I didn't think that the podcast...

Uh, would, would turn into what it's turned into. Um, mainly I started podcasts cause I'm like, I'm a writer and I'm going to write a daily newsletter and you know, I want exclusive content in the daily newsletter because there was, you know, a handful of good, you know, uh, daily AI newsletters at the time, but they were all the exact same. I'm talking copy and paste.

They covered the same things. They talked about the same things. It was formatted in the same way. I'm like, I want to do something different. So in my newsletter, I want to be able to talk to smart people, bringing in my old journalism days, I guess. And each day, I want to write like I used to. For me, writing is important. I still write the leveraged portion of the newsletter daily.

with these fat fingers, with my own two hands. You know, I don't hand it off to generative AI, which, by the way, I was using M-dashes way before generative AI. Brian can probably attest to that, right? Brian, tell him, use the

M dashes way back in the daily Egyptian days. So I thought actually that the podcast was just going to be so I can create fresh daily content for the newsletter, but it was actually, you know, the podcast that, you know, got kind of popular and not the newsletter, but that's okay. Right. You know, in business, as with anything else, you have to be adaptable. You have to be flexible. So that's kind of the Genesis of everyday AI. And yeah,

It's much different now, right? Doing this every single day and being able to work with literally the biggest companies in the world. You know, I'm very fortunate. And I hope that, you know, this journey over 500 episodes, you know, I hope you found a little bit of value here. Yeah, here we go. Okay, Brian's...

uh, Brian saying this, he said, I distinctly remember Jordan telling me about Jasper AI six ish months before chat GBT came out and telling me AI was the future. Looking back at it, it was a clear inflection point for me using AI tools on the regular as he was usual, as he was usually ahead of the curve. In this case, the AI boom, boom. Yeah. Um,

All right, let's keep going. Let's talk a little bit about the future of work. And y'all, if you do have questions, I'd love to tackle some of your questions, you know, kind of as we go along. As I'm seeing some of them, I'm starring them, you know, I'm going to get to them, you know. So thank you for all the congratulations. But yeah, if you have a question you want me to tackle, please let me know. It is like 5.5.

45 a.m. in where am I? Vegas. I got nowhere to be. I got nowhere to be. All right. But I'm not going to keep this one going on for too long. So let's just quickly talk about, you know, like when it comes to top takeaways of 500 episodes, I mean, the biggest one has to just be the future of work.

I've been saying this for a long time. I didn't say this day one, right? Because this was before every single, you know, big player was involved. So now, you know, Microsoft with their co-pilots, amazing in all the updates that they just announced over the last two weeks. Google, obviously, right? Meta,

pivoted from, you know, at the time they were, you know, social media company. Now I think most people know Meta as a, an AI company. Um, and then you have every single, even legacy, uh, tech company has transformed in the last, you know, four to five years since the GBT technology kind of hit the scene. So, you know, uh, everyone from, you know, IBM and Intel and Oracle and

Dell, Salesforce, Adobe, right? I just saw Bank of America just invested $4 billion into their AI efforts, right? So every single big enterprise tech company, everyone's turning into an AI company. So if you don't think yet that generative AI is the future of work,

I mean, probably if you're listening or reading this, you probably know and you probably understand that. But that's the biggest takeaway is I was having a conversation with someone at Google last night about this very thing. I don't think that we're going to have a choice soon.

to not use AI, right? You'll have to kind of go out of your way soon, right? Obviously, you know, the, all the enterprise software that we use is being, you know, infiltrated in a good way with generative AI with large language models, right? So if you're a Microsoft Windows organization, obviously with Copilot, Apple is like, you know, 30 years behind, but I think eventually Apple intelligence will be able to do more than, you know, add two plus two. And,

and obviously everything with with google right so most people you know you're either a google or a microsoft organization and those two companies have obviously been huge leaders in the space along with open ai with nvidia you know really going from a company no one had heard of you know if it like if you weren't a gamer you didn't know what nvidia was like three or four months or three or four years ago right now nvidia you know depending on when you look they're the

biggest company in the world when it comes to market cap or at least a global superpower, literally driving the future of the economy.

So generative AI is the future of work. So anyways, what I was saying in this conversation last night is I think it's going to be very hard for us not to work with AI soon because I think that even everyday non-technical people are starting to see the benefit of generative AI. You know, a funny story here. I'll share another personal story. Yeah.

My wife, she's amazing. She, you know, she listens to every single episode. You know, she's taken like, you know, my prime prompt polish course a lot of times. And, you know, she's trying to help me improve and all these things. And funny enough, right, even though I talk about generative AI every single day, it was when I was at the NVIDIA GTC conference two weeks ago.

And I came back and she had replaced her searching of Google with now she's just talking with perplexity. Right. And I was joking about it. And I'm like, oh, you decided to take the time when I was gone for a couple of days to start using generative AI in your day to day. But

I'm starting to see this shift. Uh, you know, another one of my good friends, uh, his, his fiance, you know, same thing. She's like, Hey, now I'm using chat GPT for everything, but she's not, you know, a technical person. Um,

I am now seeing non-technical people start using this generative AI technology that I think a lot of us, if you are a more avid maybe listener of this show or if you're someone that's using AI every single day, I think we've been in this bubble sometimes and I forget that. But now I think that the average person

even non-technical person is starting to see huge value from using AI, right? Not just in time savings, but in the quality of outputs, right? So generative AI is the future of work and it's going to be very hard in the future to do any work without using generative AI. Just like right now,

it's pretty much impossible to complete any work of real business value without in connected to the internet. Right. I think the same thing. And as we talk about generative AI and, you know, models getting smaller, better edge AI, right. Like, you know, right now on this, on this iPhone here, right. There's technically a small language model because I have the newer iPhone, but I would assume in two years, two to three years,

on the average smartphone, we are going to have a model that lives locally that is more powerful than today's state-of-the-art model, right? Yeah, it might not be Apple first. You know, you might have to have a Google phone or something like that. But I do believe that we are going to have in two to three years a local model running on the average smartphone that is more powerful than a GPT-4.0 as an example.

So even your personal life, your work life, you have to understand generative AI is the future.

of work. There's no way around it. And that's both good and bad because it changes how we work. And I'm going to get to that a little bit later when I talk about agency and when I talk about human skills and human value. Yeah, like, you know, Monica here says, you know, looking forward to using agents at work one day. I think that one day is coming for people much quickly than we all may realize.

All right, let's get on to my next big point, right? Because we talked about big techs all in pivot, right? Which I've mentioned a couple of times on this show before, but this is the first time in US history when you look at the economics of work, right? And that's something I always do. Yes, I know on this podcast live stream, I ramble and sometimes I seem a little disorganized,

But I promise you, I do a lot of research. Right. But I don't know. I don't I don't want this show either to come off as, you know, overly prepared because there's enough things out there. And those all sound robotic, if I'm being honest. Right. So anyways, I've talked about it once or twice on the show before. But, you know, talking about this big text all in pivot to everything AI, right.

Never in the history of the U.S. have all six of the biggest companies when it comes to market cap been from the same industry until now.

Right. It's always been, you know, very, very diverse. You know, you have people in energy, you know, your mobiles, you have people in commerce, you know, your Walmarts of the world. Right. So if you go back and look over the last, you know, 30, 40 years at the biggest companies in the U.S. by market cap, it's always been very diversified. It's not anymore. Right. Which, you know, there's downsides to that as well. But the big downside.

The six biggest companies in the U.S. when it comes to market cap, they're all just now AI companies. Microsoft is an AI company. Google is an AI company. Amazon is an AI company. NVIDIA is an AI company. Meta is an AI company, right? You get the picture. And they're the biggest companies in the world. And that's really impacting not just employment, but also business models, right? Yeah.

Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Gen AI. Hey, this is Jordan Wilson, host of this very podcast.

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I don't know how to say this. AI is going to take a lot of jobs, right? I've never been one to beat around the bush. I've said since the very first episode of Everyday AI, which is a little bit, it's a little cringe if you want to go back and listen to it. But I still think a lot of the first points that I made hold true today. AI is going to take a lot of jobs.

AI is going to have a net negative impact on traditional full-time U.S. employment. All right, let me say that again. AI will ultimately have a net negative impact on traditional full-time U.S. employment. Let me unwrap that. I think employment is going to change very much.

Because at least especially for the last, since the digital revolution over the last 30-ish years, where now we sit in front of computers, right? Since the 90s, you sit in front of computers and you're paid for your knowledge, right? You're paid to create business value. You sit in front of computer. You create new business value for a company with your knowledge, right? That's what we do as knowledge workers, right?

Knowledge work is going to completely change because guess what's more knowledgeable than all of us sitting in front of a computer, a large language model, right? Go use, you know, Gemini 2.5, go use, you know, open AIs of one pro you could get. And I don't, I don't care who, who argues on the contrary, right? If, if, if you argue the flip side, that just makes you not smart.

right? To think that, or to not understand that a single AI system is exponentially more intelligent than the world's smartest humans. Going back to my story, right? When I was using these tools and I'm like, they're a better writer than me. Everyone, if you haven't had that moment yet, you're going to have that moment, right? Where, oh my gosh, this AI is better than me. And that's okay, right? Like,

I think if you ask the same conversation, you know, 10 years ago, hey, are you smarter or is the collective information on the Internet smarter? I think most people would say, well, the collective information on the Internet. OK, that's what large language models are. They are literally a collection of

of the best intelligence, hopefully the best intelligence on the internet. Yes, large language models hallucinate. Yes, large language models can go off the rack, off the rails, right? Humans can too. You know, it's always funny when, you know, people look at these benchmarks and they're like, oh, well, you know, looks like it only got it right 93% of the time. So we need humans. It's like, okay, let's have a single human take that benchmark.

Right. Let's have a single person, a single human take the MMMU or the MMLU or the ARC-AGI test. The smartest human I know is going to get about zero correct. So think about that. But let's talk a little bit about business models and how that's going to change. Well, I think traditional full time employment as we know it.

is going to look very different, especially here in the U.S. It's going to look different in other parts of the world. But here in the U.S., where the majority of our listeners are from, think of it like this. You know how a lot of people now, there's this gig economy. You have people...

It's not uncommon for someone, especially in a bigger city, I think, to just be full-time gig economy, right? They're, you know, oh, I do a little DoorDash. You know, I do some Uber and then I do some TaskRabbit, maybe. I don't know, right? It's not uncommon, especially in bigger cities. That's what's going to happen.

with professional services that's what's going to happen with knowledge workers i'm not saying that no one's going to have a full-time job in five years it's not what i'm saying at all but i'm saying it will be common to know professionally uh educated people people who have been in corporate america and leave and then they just have essentially the equivalent uh right of knowledge work based jobs so think like you know kind of fiverr slash upwork but think if there was you know um

for whatever your industry is. Let's say you work in marketing in the logistics industry. Okay. There's going to be like

50 different Uber-esque or Fiverr-esque or Upwork-esque services just for marketing in the logistics industry. It's going to be very common in five years for the average American worker to have multiple jobs, to have multiple, I think even businesses, multiple side hustles. But I really think we are going to see this reemergence

of entrepreneurship. And unfortunately, I think that's going to follow mass layoffs, right? We're already starting to see it because when you talk about AI's impact on employment in traditional business models,

Right. Most enterprises, not all of them, there's still some. And I hope there's many enterprises that when they see and fully realize the gains of generative AI, that they'll make good ethical decisions. Right. That's why AI ethics is good. That's why I've for literally a year and a half when I tell people and when when companies hire me to consult for them on AI implementation and strategy, I say you need to go solve for the why.

and solve for the what happens when, right? What happens when you become 50% more productive?

Right? Yes. You have to train your people, which no one wants to train their people. Everyone just wants to hand out easy buttons. That's not how generative AI works. But what happens if you roll out generative AI the correct way? What happens if you invest in training and unlearning? That's what I say. We need to stop with this upskilling, reskilling. It's unlearning and relearning. That's what we need to do. But what happens if you're an organization of 5,000 people and you go through that process and you see 50% gains?

What happens when AI works? What are you going to do? Are you going to go to four-day work weeks, keep everyone on board? Are you just not going to hire new people? Or are you going to lay off 30% of your organization? I think, unfortunately...

A lot of especially public companies are going to do the latter in that scenario. They're going to lay off a lot of people. Well, number one, they're going to stop hiring, especially as we get this. I think it's now is a good time or bad time, depending on how you look at it. But it's a convergence of all these things happening, right? So we finally have large language models that are agentic, right? They're able to on their own.

No code, right? That's the thing people don't realize. And there's some announcements. I should have wrote down what time the embargo here at Google goes away. I think it's maybe still, I'd be now, might be 30 minutes. So I can't talk about it, but okay. Microsoft Copilot Studio. If your organization has Microsoft Copilot set up correctly,

Even if you are not a technical person, you can go into Microsoft Copilot Studio. You could probably spend an hour. It's no code, low code. And you could probably build an autonomous agent that does one of your most annoying manual tasks without any experience. You could probably get it doing 80% of that one task.

autonomously, right? So when we talk about autonomous agents and how they're going and people are always a little bit confused and I get it, right? Essentially you have large, like you have generative AI or large language models, right? I talk to chat GPT, chat GPT gives me answers back. Then you have AI workflows, right?

which is I talked to chat GPT, chat GPT has access to all of my files and some tools, and then it comes back to me. Right. But I still have the agency, right. And I'm choosing in that instance to, to give decision-making power temporarily to an AI agent. So that's not, or sorry to a large language model, but that's not an agent. So me talking to chat GPT, that's not an agent. Me talking to chat GPT that has access to my files. That's an AI workflow. That's not an agent. An

An agent is when it doesn't need me. I go in one time, I go to Microsoft Copilot Studio as an example. I set up an autonomous agent. It sets on a trigger. Anytime I receive this type of email, people asking me for a quote or

I don't do that anymore. Right. Like it's going to go through. It realizes, you know, yes, this is someone reaching out, asking about a quote. It goes and looks at all your all your dynamic data, all your most up to date information, you know, across multiple parts of your organization. And then it goes back and it can reply to that email automatically. That's agency.

That's an agent, right? That's when you set up the guardrails. And a large language model has tools. It has a defined role. And it goes out without you telling it to, without you handing or handing over that agency or asking it to be agentic. It's working on its own. And that's where we're at. And I do think, unfortunately, once companies see and realize the gains of this combination of agentic AI

Number one, models that are much smarter and models that are reasoning. Number two, in costs going down. Unfortunately, that means a lot of big companies are going to be laying people off. But ultimately, what I think that means is there's going to be first. And I talked about this on the on our 2025 AI roadmap prediction series. It's going to be a huge disruption in traditional service industries. OK, slow, expensive sectors, right?

are going to be rocked. Okay. I'm talking about consulting, finance, legal, tech writing, accounting, CPAs, right? High priced, slow, expensive service services. They're going to get crushed.

Right. Check, check in the newsletter we're going to be covering. I can't talk about this because they, they, they did release this information before the embargo. Google just updated its deep research tool to Gemini 2.5 pro. Right. I think open a eyes, right.

Deep Research is one of the more impressive AI tools I've ever used. Google did update theirs a couple of weeks ago to Gemini 2.0. Now that it's Gemini 2.5 Pro, I've only used it very, because it just got released like last night and been a little busy here at Google Cloud Next. That's going to be extremely disruptive. I don't see, if I'm being honest, right? So let me just give an example here.

Let's say right now there's a thousand consultancies in the US. I know that's not the right number. I know there's more, but I'm here for easy math. It's still 6 a.m. here, local time. Okay, let's say there's a thousand consultancies. I think half of them are going to persist with their traditional business models, right? They're going to keep charging an asinine price.

They're going to be saving a lot of time because these deep research tools, there's a reason why when OpenAI launched their deep research, they partnered with Bain, right? One of the biggest consulting firms in the world. And you go look at that little case study and it's like, oh, okay. Yeah. Like you could see that deep research tool can do the work of a junior, right?

probably better and exponentially faster. So what happens then? Are these consulting firms going to continue to charge the same amount they're charging, right? If an AI tool can get 80% of the work done in 10% of the time, okay? So I think half of them will. They'll continue to do business as normal, whether they are outwardly communicating that they're using these new deep research tools, which is essentially a consultant tool

but better, faster, more accurate. Sorry to my friends in consulting. I already came to that realization myself. Chad GPT is a better, faster writer than me.

Okay. If you're in the consulting industry now, open AI is deep research. Google's deep research, um, open it, uh, even, uh, Microsoft announced theirs, um, within a month or two, once they've worked out the kinks, it's going to be better than most consultants. Okay. So out of those 1000 consultancies, I see half of them continuing to go on with traditional methods. And I think that they're eventually by doing that, they're going to lose the top

and bottom 20% of clients, all right? Because the top 20%, they're going to know and they're going to have their own essentially internal consultancy spinning up and they're going to be like, all right, we don't need to pay this big four company eight figures a year anymore. We're cutting that. And then they're going to lose the bottom 20% of clients, right? So those smaller businesses where normally hiring a big four is a huge expense and it's painful, but they feel they must, they're not going to do it either.

So these big consultancies, I think they're going to lose the top 20% and the bottom of 20% of their clientele over the next two years. And that's going to cause massive layoffs because they're going to get crushed, right?

The other half, I think, are going to do it the right way. They're going to adjust their prices. They're going to provide better, faster and more accurate services. Right. You're not going to have to go on a quarter long seven figure endeavor with some of these consult big name consultant consulting companies anymore because they'll realize, OK, if we want to stick around this in the long term. Right. You're seeing all these stories now. The big big four consulting companies aren't hiring as much anymore because

Because I think they're starting to understand that this is a threat to their traditional way of doing business, right? So what I think half of those, so again, easy math, 500 are going to have massive layoffs. 500 are going to pivot and shift their business model. But for those that have massive layoffs, what's going to happen is you have very smart people that are going to be out of a job. What are they going to do?

They're going to crush their competitor. They're going to crush their previous employer. Because they're going to know, oh, wow, you know, we're using AI and, you know, we're just, you know, pocketing the profit. Let's come in. Let's do the same thing. Let's go steal these clients and let's charge them 10%.

Let's charge them 10% of what they were doing at the big four, the big eight, whatever. Right. And I'm not trying to call you guys out. I know we have listeners there. So hopefully you all aren't mad at me for saying this, but this is the truth.

You're going to have consultancies spin up that are going to be 10% of the price. It's going to be the same people that were working there. And it's going to be faster. It's going to be better because they're going to leverage AI and they're going to do what I like to call expertise in the loop. I think we need to stop talking about human in the loop. I just had a great conversation with someone last night from Gardner, actually on the shuttle ride back from the Sphere, which was a fun event. Google announced...

You know, they're kind of like remaking with AI with their VO tools and or VO tools and others. You know, they're kind of remaking the Wizard of Oz with AI, you know, to fit on the sphere big screen, which was pretty cool. So I was having a conversation with a researcher from Gartner on the way back about this, about this very thing. And just, you know, how I think we're going to see.

hundreds, hundreds, and probably thousands of hyper niche consulting services. So now apply that same scenario applied across legal. Legal is going to get hit hard. Financial services, CPA accounting, et cetera. That's what's going to happen. We're going to see a huge disruption in traditional service industries. All right. Yeah.

Doug was saying consultants could be some of the $20,000 a month access to OpenAI service that had been referenced. Yeah.

Uh, that's a good point, Douglas. Yeah. There's, there's always these rumors out that, you know, all these big, uh, you know, tech companies are working on these versions of their models that are going to cost thousands of dollars a month. So yeah, maybe, maybe there is something, uh, much better. Obviously open AI did, uh, announced that we're going to see an Oh three full, uh, we're going to see an Oh four mini soon. So I do assume that they're deep research, um,

Their deep research tools are going to get updated because Google's that they just announced in looking at some early benchmarks. It's extremely impressive. Yeah. Monica saying I already see on LinkedIn people leaving huge companies and high level positions to start their own businesses and their specialty. That's a great point. And I'm not I'm not going to name names. Right. But I've had.

many, many conversations. Many people reach out to me and I'm like, Hey, Jordan, I'm at a big company companies you all have heard of. Right. And they're like, I know I can go out and start my own thing. And that's going to happen a lot. Um, and that's why, you know, my kind of point number three, uh, you know, kind of the, um,

impact on future employment. I don't think traditional full-time U.S. employment is going to look the same because of this very recent, right? And I don't think it's wild to think that people are going to spin off and they're going to have multiple,

They might have two or three of their own businesses that they own and they provide services, and then they might be kind of freelancing for five to 10 more. I think that's going to be very common. Just like I said, it's common for maybe your Uber driver to also do TaskRabbit and to also do...

I don't know. I forget, you know, DoorDash, right? So it's very common for someone that's already in this gig industry to do two, three, four, five. And I think it's going to be the same. Knowledge workers, you know, with 15 years of experience in corporate America, highly educated, you know, they're going to be doing this exact same thing. All right, let's go to five.

this one's tough. If I'm being honest, again, these are, you know, some of the, the highlights of my first 500 shows. And, you know, I, it goes without saying, or maybe I should say it, um,

You know, I've obviously got to speak with some of the smartest people in AI. So these aren't just my thoughts, right? That's the fun thing about having a podcast. I can just say, I can open my email and, you know, any given week, I have a couple dozen people pitching to come on the podcast. And I can be like, who do I want to steal knowledge from today? Right? Who do I want to...

Like, I want to get some secrets from someone and I want to share those, you know, AI secrets with everyone else. So, you know, I've been lucky enough to kind of steal some secrets and, you know, absorb knowledge from people across all different industries, you know, huge, you know, tech trillionaire companies to startups to, you know, medium enterprise businesses. But one of the biggest things that I see is redefining human skill and value. And that's got to be tough, right? Yeah.

I think it's going to be especially tough if you are in like the 30 to 50 year old range right now. If you're younger, you know, maybe you grew up on the tail end of chat GPT or, you know, if you're still in college, I think it's going to be a little easier. You know, if you're more closer to retirement, I don't think this is going to impact you as well. But, you know, for the most part, for 30 plus years, the way that business has worked here in the U.S., you get paid for what you know.

Right. And then you have to be able to sit in front of a computer and you have to make your company more money based on what you know. It's not going to be like that. It's not going to be like that anymore. It's weird. Right. And the more smart people I talk to about this exact thing, sometimes the harder it is for me to even grasp it. Right. But I mean, let me just talk about even myself. Right. So so my skills. Right. So I've been working full time since I

when I was 16 or 17. So more than 20 years, I've been working full time. And for the most part, you know, those have been in roles like, you know, I was a writer, strategist, marketer, advertiser, et cetera. So let's just say digital, marketing, advertising, writing, et cetera. My skills don't matter there anymore. They don't. Matters in a different way. It's almost like I think that many of us are going to become

tastemakers in very niche ways. I don't know if that makes sense. But now as an example, even what I do, right? Yes, I still sit down and I write my newsletter. But aside from that, for all those other things, I'm using AI. And so

doing jobs that I used to do, right? Even researching. I used to spend so much time researching. And, you know, as a former journalist, I really valued my, you know, my researching and analytical skills. I'm a tastemaker now. So what that means is

is I hand that job off. I give agency to go do that research, to go be the creative strategist to multiple large language models. And then essentially it's like, oh, I have them report back to me. I am a curator and I am a tastemaker in terms of my skills for things that I've been doing for 20 years, right? So

Hey, different AI models, go out and write this. Hey, different AI models, go put together a strategy plan on this. Hey, different AI models, I need new advertising. Here's all the data. Here's our results. Go out and work. Go do this. And then they come back to me. I curate and it's almost like I taste make, right? I'm like, okay, this is good. This is passing. This is passing the vibe check. This isn't, right?

So I think as we look at where our skills are, because here's the thing, that thing that you've been getting paid to do for 10 years, in most cases, if you haven't already found the AI tool or the large language model that does it better, you will very soon. And a lot of times it's just going from the piece of

to the system, right? And that's this phase of generative AI that we're in right now, right? So from large language model, going to AI workflow, going to agentic AI, going to multi-agentic AI, right? With huge context windows, with RAG, right? With up-to-date dynamic data. So I'm not saying your skills are useless. You're just going to be using them in a different way.

Right. So hopefully that example where I used to physically go, right. Right. I still do that. But a lot of times for some things, I mean, I'm still getting my input in on the front end for that. For like for some things, I used to be the digital strategist. Not anymore. Right. I used to be the marketer. Not anymore. It looks a little different now. Right. Because unfortunately, the business world in the U.S.,

It's make more money in less time, right? It's especially if you work in a public company. It's sad. It's sad to think about. You know, we are a headcount. Companies will fire you tomorrow. Doesn't matter if you're a director of blah, blah, blah, or senior manager of important project. Doesn't matter.

As soon as that board, you know, and they're looking at the stock price and they're like, oh, look, when we use AI, this sector of our business is bringing in so much money and this sector isn't. They don't care about it. They don't. Right.

I'd hate to be that person. Unfortunately, in America, corporate greed is at an all-time high. I did a show on that. It was actually very telling, right? How much executives at these large, you know, Fortune 500 companies make. And when they see, oh, when we can, you know, implement AI, multi-agentic AI in this way, we can cut, you know, 20% of that department and still make more money. They're going to do it.

They don't care about you. They don't care about your experience. They don't care about your background. So that's why I think it's important that we start to redefine our not just human skills, but also our value. Right. And I kind of shared a little bit with you all about what that was like for me. It was weird. It was weird when I saw all these different AI tools that could be a better writer than me, could be a better digital strategist than me, could be a better marketer than me, could be a better advertiser than me, could be a better researcher than me. It's weird.

You're going to run into that. Right. But hopefully you can hit it head on. Right. Because I think we do. You know, we've we've kind of traditionally hung on our hung our hats on a job title. Right. It's like, you know, you meet someone new and they're like, hey, I'm a marketing director. Oh, OK. Well, wasn't asking about that. Right. But people play so much of their identity in their job title.

And I think that you have to be willing to pivot from that, right? And re-look at what your human skills are and what your value is as a human, right? There's great deep podcasts on this. Sometimes it's people that maybe like, okay, Bill Gates, right? He's had some great podcast topics on this.

Obviously, he's different than all of us, but even him talking about, okay, well, what do we do in the future? What's human purpose, right? When AI is more powerful, maybe when we tiptoed toward this artificial general intelligence, artificial super intelligence. So I think you really have to

I love using the term unlearn. It's a term I like. I think I coined it. I didn't hear anyone else talking about it. You know, people are talking about upskilling and reskilling. But I think for this, we have to redefine human skills, human values. So you need to, if you haven't already, develop AI literacy. That's why I do this every day. You can join me for, you know, I know sometimes these podcasts go a little longer. This is my five-minute show, y'all. I'm not going to make this a 20-minute one.

But you need to practice it every day. You need to learn because ultimately, I think what a lot of us are doing, instead of sitting in front of a computer, creating business value with our fingers and with our brains, I mean, we're still going to be doing that. But AI and agentic AI is going to be doing the heavy lifting. All right. Number six. I got two more, y'all. Two or three more. Human in the loop. I already talked about this, but I really think

active human engagement in AI orchestration is going to be big. I really want to control alt delete, uh, command a delete. Every time someone talks about human in the loop, I think it's dangerous, right? When we don't really explore what that means. Right. And, um,

You know, maybe you're new to AI. Maybe you're tuning in for, you know, the first or second time. You're like, okay, what's human in the loop, right? You know, this is one of those like blanket terms people say to kind of, you know, give everyone ease. It's like, oh, well, is it weird to, you know, be handing all this out to large language models and, you know, agentic AI? And they're like, don't worry, human in the loop, right? That's going to keep us safe. No, it's not, you know, because I think human in the loop, it's a problem because, you know,

Number one, you have thousands of companies promoting, you know, agentic AI is the best thing since sliced bread. Um, also with sliced bread, like that big of a deal. Sometimes I just love getting a hunk of French bread and just biting into it. I don't need to slice it anyways. You know, everyone's like, Oh, agentic AI, agentic AI. Right. So, uh,

as business leaders, you know, making decisions on, you know, what, what tools and models your company should be using. All you're seeing is agentic AI and you're like, no, we're human in the loop. You're safe. Guard rails, your data, you know, you ethics, human in the loop, human in the loop, right? What's that mean to me? I don't think, you know, these, these thousands of companies trying to push us agentic software necessarily care about human in the loop, right? It's, it's, it's more of like a,

You know, it's a warm blanket on a cold day. It's not fixing anything. It's just making you feel better about the exterior situation. I really think we need to pivot to talking just like we shouldn't be talking about upskilling and reskilling. We need to talk about unlearning. That's what you have to do. We also need to talk about expertise in the loop. Human in the loop, I think people are looking at it as passive.

It's like, okay, yeah, I'm going to read the prompt. Let me check in on the agents. Good job, agents. All right, I'm going to sit here and sip my coffee. I'm the human in the loop, right? I'm on an assembly line, you know, making sure the assembly line doesn't break. That's not it. Expertise in the loop.

Organizations need to be sticking the right expertise in this agentic AI loop. And I talked a little bit about AI orchestration. So if you're interested in that, go back and listen to our 2025 AI Roadmap series where I did have some dedicated things on agent orchestration. But

I don't think that's going to happen this year completely. I do think that we're going to see roles being created at large companies. I've already seen it where someone's role is essentially an agent orchestrator, right? And they're essentially overseeing agentic systems. But we need expertise in the loop.

Because as we hand off more and more agency, that's what we're going through right now in 2025. And that's one of the biggest takeaway over 500 shows is we're giving more and more agency chat. You know, this generative AI wave started as like, oh, this little program, this AI chatbot is fun. Right. And now we're at the point where organizations are trying to offload as much of their manual knowledge, human work as possible.

So it's different now. We need to be intentional about sticking expertise in the loop. And that's not just someone who's, you know, a great prompt engineer or a technical person. It's security. Make sure you stick your expertise in that loop, right? Don't let the, you know, one person, don't let a generalist overreact.

oversee a multi-agentic AI operation, right? You need multiple people. So I do think that's another way how our human engagement in our roles are going to change is we are going to have expertise in the same way, right? Like, oh, you have your people, they check in on your CRM, you know, you have your project managers, they're checking in on the projects. I think those, they're all just going to shift now, right? You're going to have these agentic loops performing a lot of these manual knowledge-based tasks, right?

that are hopefully fine-tuned on your data, but that's what it's going to turn into. All right, two more quick ones, and I'm going to get to your questions. If you do have anything, any questions, please, please let me know. Some of these comments are making me laugh, y'all. This is funny. All right, number seven, the AI race. It's exciting, right? It's one of the top takeaways. You all wanted the top takeaways. The AI race is exciting, right? I'm a Chicago guy.

You know, growing up watching the 90s Bulls was an unworldly experience, right?

Um, no one, no one could compete with the nineties bulls, right? Uh, you know, the two, three Pete's, you know, MJ, uh, Scotty Pippen, Dennis Rodman, no one, no one could compete when that group was together. Um, you know, I know that they kind of swapped out characters there, uh, between the two different three Pete's, no one could compete with them, you know, um, a couple months ago.

I would have said that's how the AI race is going. You know, maybe, I don't know, maybe like October, I would have said OpenAI is, they're the 90s bulls, right? They're running away with this. No one can touch them. Google and Microsoft have made things very interesting. Very interesting, right? I'm fine saying this. I'm literally partnering with Google. I'm at Google Cloud Next. A year and a half ago, I told people, don't use Google Gemini. No, don't.

That started to change, you know, in quarter three and quarter four of last year. I think Google made some great hires. They made some great restructuring. I think bringing Gemini under DeepMind was probably a good call. And now Google's right up there using Gemini 2.5 Pro.

It's such a weird experience, right? As someone that uses large language models way too much, it is baffling how powerful that new model is from Google. And then Microsoft as well. Microsoft has slid under the radar. I don't know how with a lot of their recent co-pilot announcements, right? Last Friday at their 50th anniversary celebration, they just announced like

seven, like, like essentially I called it like a greatest hits. They like, I don't know if this is what happened internally. Right. But they saw all these other, you know, popular AI modes and they're like, yeah, let's just go ahead and release that for copilot. Right. Oh, like notebook LM. Right. We can put all your information and it's going to create you a customized podcast. Yeah. We're going to do that for copilot. Oh, deep research. Yeah. We're going to release that. Right. Microsoft went a little bonkers and

We're going to get a lot more announcements today at Google Cloud as well. But what I'm saying is like the AI race, it's actually a race now. Whereas, you know, like I said, maybe nine months ago, you know, so for the better part of 18 months, it was just the bulls dynasty. No one could touch them. It was not close.

It's close now, right? Which actually makes it a little more difficult, I think, for all of us, for business users, right? I talk sometimes about you need to choose your AI operating system. Actually, it was a lot easier nine months ago. Sometimes you might have to use multiple, but it is extremely competitive, which I think is both exciting and also frightening, right?

Right. Because now, you know, the race toward right. Like you have a lot of these companies now openly working toward artificial super intelligence. Right. And that can be scary.

And I like I get that. Right. So, you know, I guess if Microsoft and Google hadn't, quote unquote, caught up to open AI, you know, as business leaders, it could have made the AI adoption and the AI transformation journey a little less stressful. Right. But now, both fortunately and unfortunately, you know, I think we have three major players that are on that like first tier.

And I think now you have to constantly be evaluating the quality of these models for your domain. Right. So I think it's always a good start to look at the kind of like quote unquote scientific benchmarks, right. To look at the, you know, MMLU and the MMM, MMU, the, the, the diamond, all those things. And then the human preference as well. So the ELO scores, you know,

you know, on the LM chatbot arena. But I think also companies, if you haven't already, you need to start developing your own domain specific company specific evals. Right. So it could be as simple as, you know, a hundred different, you know, quote unquote prompts or, you know, a hundred different tasks. Right. And, you know, as we talk about, you know, what happens when you start, you know, gaining, you

Gaining time back. Well, this is what you need. You need an evals team and they, and this is going to be one of your busiest teams in your organization. They need to be constantly manually running those, you know, 100, you know, tests, those 100 use cases through these models on a weekly basis and doing your own quote unquote internal evals, right? Because the large language models themselves are becoming commoditized, right? You can, you know, there's,

systems pretty easily. You know, if you're working on the API side, you can swap a model out fairly easily. So you have to understand what all the major players are doing. You have to know how to evaluate them all internally in order to keep up.

All right. I'm going to tackle a couple of these questions. So thanks for getting them in. And I have one more thing to wrap up. I'm going to end on a personal note, if that's okay with you guys.

So Melissa says, what's the most impressive or game-changing AI development you've experienced to date? Melissa, that's a tough question. I've talked about this. I never had the ChatGPT moment. When ChatGPT came out, I was like, meh. I think at the time, their GPT technology was being better used and better utilized by third-party people. So ChatGPT, that wasn't it for me. If I'm being honest...

I would say Notebook LM was probably one of them. I'm still astonished at the team that put that together. I'll also say OpenAI's Deep Research

you know, uh, which now might be Google's, you know, I'll have to see. Um, I would say those are probably some of the most impressive. Uh, but again, um, I don't impress easily, I guess also a GPT four Oh image gen, uh, you know, that just came out very impressive. Uh, Jackie is asking, have you switched to Android? Not yet. Um, I don't like Jackie, you, you, you probably know I can't text. Um,

You know, if any of you guys ever like text me or, you know, DM me, I can't do anything on my phone. So that's one reason why I'm still on a Mac is just so I can text people on my computer a little faster. Brian, Brian, thank man. Brian's been showing up for like two years. You're awesome. Brian's asking, what are you most excited about from an AI perspective over the next six months? Oh gosh, that's a good question. I'm most excited about non-technical people.

Finally, discovering what the rest of us have been doing for the past year or two. That's honestly what I'm most excited for because then it makes education a little bit easier, right? Companies hire us a lot to train their employees and whether it's a dozen or hundreds and it's difficult. It's difficult to go train someone on generative AI, right?

When I go into a room with a hundred people and you know, uh, a third of them use generative AI for three hours a day. And, uh, a third of them have never done it. So I'm personally like, maybe that's a cop out. I'm personally excited for people that haven't used generative AI. Um,

to start using it and to start discovering it because what that happens is, you know, it's like, oh, it raises the tide for all ships, right? It does. And I think, you know, so many organizations have been limited on the top side just because, you know, like such a high percentage of their organization doesn't know what generative AI is. They don't know how it works.

Another good question here. Any suggestions on how to get late adapters to embrace and see the value of Gen AI? I think a lot of it, you know, I kind of gave the example of my wife, right? I'm always telling her like, oh, you know, hey, this, this, this. And, you know, bless her for like still, you know, listening to me, you know, two years later, talk about AI. But for her, I think she needed help.

AI in her personal life. Right. I think, you know, it's like quite literally hands full, you know,

Talk to perplexity. And she's like, oh, wow. And now I think, I don't want to speak for her, but I think maybe she'll think a little bit differently. And I think this is just more in general. When people find value of AI personally and give them a couple of months, then it's just going to change their brain. It is this unlearning process.

You know, so I think that for late adapters, right? It's not like, all right, let's sit down in Microsoft Copilot Studio and we're going to no-code your job away. No, it's like, hey,

Oh, what's that? You have three kids and it's hard to get a meal schedule because, you know, one is allergic to peanuts. One only eats peanut butter. And, you know, the other one hasn't touched a vegetable. And, you know, OK, use chat to eat a meal plan. Right. Like talk to it. Right. So I think when when business leaders who are still not using generative AI, you can't continue to.

to fight the battle on the same battlefield, right? They need to get it at home. And I think that's what we're starting to see a lot in 2025. You know, strangely, strangely enough,

All right. Let me just double check any more questions before I, I, I wrap this thing, uh, wrap this thing up. Um, all right. Good, good one here from CM on YouTube saying, how will the new economies work in practice? If white collar workers don't have jobs, how will they pay for the people who do the manual work? I'm trying to imagine how the new systems will work. Yeah. I don't know. Um, this is why, you know, a lot of there's, uh,

And I did say this in my 2025 AI prediction and roadmap series. I do think UBI, I don't think it's going to happen, universal basic income, but I think it's going to actually be a common discussion now, right? Especially with how the US economy is headed right now. So I don't know. What I will say to this question is I think, like I said, I think full-time

nine to five employment in 10 years is, is going to be, it's going to look a little antiquated. Right. And when I said that the first time, like a year and a half ago, I think people thought I was weird. Um, and then the LinkedIn CEO, uh, said something similar and now people are like, oh, okay. Yeah. That, that adds up. Right. Um, you know, saying, Hey, traditional nine to five,

It's not going to work in the future of AI. It's just not. It's not going away, right? But I do think a lot of people, you know, are going to have multiple side hustles. They're going to have multiple companies. They're going to have multiple freelancing opportunities, right? I do think that's how it works, right? Obviously, there's still going to be, you know, I think the majority of U.S. workers are still going to have nine to five jobs, but not by a lot.

Right now, it's like, OK, I look around at everyone I know. It's like, OK, 90, you know, 99 percent of everyone is either a full time worker or, you know, you know, raising kids and their spouses is a full time worker. I don't think it's going to be like that in five years. You know, maybe it's going to be 60 percent. Maybe it's going to be 70 percent. I don't know. But, you know, it is it is hard to tell. All right. Let me wrap this thing up here. I just want to end by talking a little bit personally.

If I'm being honest, I started this show a little selfishly. I kind of started it almost for myself. I did not envision it would become this time intensive.

Right. Maybe I should have listened to my wife and my friend on that drive that one day when they're like, are you sure you want to do this every day? Right. But for me, and at least where my skill sets were, I knew my skills were some first to go. Right. Writing and marketing and advertising and, you know, some of those things. I'm like, this is low hanging fruit, even though at the time.

My agency had the best month we had ever have. I'm like, this isn't going to stick around for too long. Right. We weren't a, you know, a multimillion dollar, you know, organization with hundreds of employees. You know, we're small. I did not envision that everyday AI would, would turn into what it's turned into. But I selfishly, I did start it for me, but I started it probably for you. Right. Because I was able to go through that process in 2020 and,

2021 of learning AI. And I'm like, this sucks. This is hard. And I'm like, this is my background, right? I was a journalist. I interview people. I talk to people. I tell stories, right? And I've been in, you know, different, you know, MarTech comms roles for 20 years. I'm like,

From 2020 to 2022, I feel I at least figured it out. Right. I got from a zero to a five. So I wanted to selfishly get from a five to a six, five to a seven. So I'm like, all right, let me start this everyday AI thing. You know, maybe it'll fail. Maybe it'll go for, you know, two months and no one will care and I'll stop.

I'm glad I didn't because here we are 500 episodes later, you know, partnering with Google. I've had partnerships with Microsoft and NVIDIA and Adobe, some of the biggest brands in the world. So I'm very, very lucky and fortunate and feel blessed and a big sense of gratitude to you all for tuning in. Like who, like how the heck are there still people?

You know, all of you people, I'm rambling. You know, I'm an hour 10 in. So thank you all. But I also did start this for you, right? There's a reason why, you know, our domain is your everyday AI. I mean, number one, everydayai.com was not available when I started this thing. But I do want this to be yours, right? So as I look at the future, like, will we have another 500 episodes? I don't know. I don't know. Maybe, maybe not, right? I'm a human.

I'm tired. Personally, I am tired. I am exhausted. This is hard. This is hard work. Yeah, this is hard work. I don't sleep a lot. I miss out on a lot, which man, like, bless up. Like my wife, she's amazing. So if you benefited from everyday AI, say thanks, Jordan's wife.

I'm lucky I get to show up, you know, click go live at 7.30 a.m. Central and hopefully it helps you. And I know it has because I've literally heard from hundreds of you that have left testimonials and I read them all and hear those stories. But personally, this is a lot for, it's been a lot for me to take on. And I feel sometimes I fall short.

But I think that's reflective of...

probably how everyone feels about AI, right? Um, because it's like, Hey, no matter how much I try, it feels like I'm always falling behind. It feels like, um, you know, Oh, as soon as I got this, uh, this AI implementation going in my department, it seems antiquated now, right? There's all these new things and it's hard, right? Um, succeeding in today's business with the pace of AI is difficult. So, you know, I just personally, I wanted to thank you all, uh,

Um, my, I mean, my, like in my wife, I mean, she's amazing. Like what she's able to do behind the scenes too. Uh, cause let's be honest. Uh, I, I intentionally knew I wasn't going to make a dime off this thing in the first year. And I could have, right. There's a lot of people, you know, as, as the show started to grow a little and they reached out and, you know, they're like, Oh, you know, I want to,

you know, pay you and I'll give you money and I'm going to put my product on your podcast. And I'm like, no, your product stinks. Right. So it was very hard for me to not make a dime, right? Not make a dime from this endeavor. Yes. I still have my other business. Uh, we still have clients, but I spend the majority of my time on everyday AI and I had so many opportunities, you know, um,

to monetize this thing so maybe i could sleep a little more uh right maybe i could be a little more present in my personal life um but i didn't want essentially right even it's it's hard to say no to money when you're start starting something right uh i didn't want to to bring on you know advertisers and you know for you all if i've gained your trust

I didn't want you to start using these things. And then it's like, OK, six months later, they're gone. OK, Jordan, why did you why did you bring this little AI startup? And, you know, I trusted you and, you know, I got my company on board and now this thing went under. Right. So it's been extremely hard to do this 500 startups.

straight Monday through Fridays. Right. So first of all, I wanted to thank you all, uh, your, your, your words of encouragement, you know, sticking with these rambling, uh, podcasts, but you know, I, I hope they're helpful in some regards. Um, like I said, I, I feel so much, uh, information now about AI, uh, just information in general. It's, it's, it's robotic, right? Everyone uses the same formula. It's copy and paste. Um,

That's not me. Uh, I'm real. Uh, I want to be able to tell you when something's good, when something's bad, when something's hard, when something's easy, uh, and this hasn't been, you know, 500 episodes hasn't been easy, but it's been worth it. Uh, so, you know, I, I do want to thank, you know, all of you, uh, you know, our, our partners, you know, at places like Google, Microsoft, um,

you know, Adobe, NVIDIA, you know, that's obviously been helpful to work with big brands. You know, all of you that have supported me, you know, sometimes it's just like one little comment, you know, I'll have a bad show and, you know, at the bottom, I'll say someone, you know, someone that I've never seen before, right? They're like, you know, I've been listening for, you know, a year and a half and this show was so helpful, right? Because sometimes I'm like, man,

you know i put in eight hours of prep for this one show and i bombed it and you know and it sucked right and then someone's like hey i got tons of value out of this and i went back to my company and we were very uncertain in this area and now we're certain so

Thank you for that. I don't know. What do you guys want for the next 500 episodes? I'm not getting any younger. I wouldn't encourage everyone to go back and screenshot maybe me from two years ago. I've probably aged like 20 years. It's been fun. It's been an adventure. So my top takeaway is...

I'm grateful for you all. I'm grateful to my wife, to everyone who's shown support out there at all. So thank you for tuning in to 500 episodes. If you haven't already, please go to youreverydayai.com. I don't know how I'm going to wrap this one up, but I'm going to do it anyways in our daily newsletter. So thank you all for all of your support for Everyday AI. I hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'all.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.