Everyday AI Podcast – An AI and ChatGPT Podcast - EP 600: 6 AI myths, 10 AI systems you must learn and 10 AI trends (600th episode)

Episode Date: August 29, 2025

You ever do something 600 times in a row? That's what we're doing today. To celebrate our 600th episode, we're bringing you: 6 AI Myths You Should Stop BelievingX10 AI Systems You Must Learn and X10 AI Trends You Can’t Afford to IgnoreNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:Six Common AI Myths DebunkedAI as Competitive Advantage MythProductivity Gains from AI ToolsAI Copilot vs Autonomous AI AgentsEmpathy and Creativity in AI ModelsAI Job Creation vs Job LossesHuman in the Loop LimitationsTen Must-Learn AI Systems OverviewChatGPT Usage for Business LeadersGoogle AI Studio and Gemini ApplicationsImportance of Agentic Browsers and CopilotOpen Source AI Model AdoptionAI Video Platform Skill DevelopmentAI Coding Tools for Non-DevelopersEvaluating and Benchmarking AI ModelsTen Key AI Trends for 2025Digital Evidence and AI-Generated ContentThird-Party AI Chat Platform DeclineImpact of AI on Social Media AdsChanging Landscape of Web BrowsingSurge in Open Source AI SolutionsWorld Models as Next AI FrontierRise of AI-Native Consulting FirmsExplainable AI and Agentic TraceabilityAI’s Influence on US 2026 ElectionsGenerative AI Impact on Remote WorkTimestamps:00:00 "Mastering AI: Myths, Systems, Trends"04:48 Exclusive AI Insights Offer07:39 AI Tools Misunderstood by Executives12:01 AI: More Empathetic and Creative13:19 "AI's Impact on Full-Time Work"17:51 Partner with Us for AI Training19:28 Essential AI Skills for 2020s22:32 "Google Gemini: Free Powerful AI Model"26:06 Copilot Access and Permissions Training29:20 Evaluating Constantly Evolving AI Models33:24 "Learn AI Coding Tools Now"37:19 "Enterprise AI Survival Prospects"40:48 Open Source's Rise Over Websites44:59 "AI Market: Speed and Accountability"48:20 AI Disrupts Work-from-Home ModelsKeywords:AI myths, generative AI, AI systems, AI trends, AI fact vs fiction, AI competitiveSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

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. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. I think that so much of a company's success when it comes to implementing generative AI can be boiled down to a handful of things.

And three of those we're going to be going over today. What AI systems should we be using? How can we sort AI fact from fiction? And what the heck is coming next? So one of the things that I've realized after doing the Everyday AI show for two and a half years is I've been able to talk to a lot of smart people and I've spent thousands of hours of researching topics and trends on my own. So today to celebrate Everyday AI's 600th episode, we're going to be going over six AI myths you should stop believing. 10 AI systems you must learn and 10 AI trends you can't afford to ignore. I'm excited for this one.

I hope you are too. Let's get into it. What's going on, y'all? Welcome to Everyday AI. My name is Jordan Wilson. And this thing is for you. It's your daily live stream podcast and free daily newsletter helping everyday business leaders, not just keep up with AI, but how we can use it, cut the reel from the BS and grow

our companies and our careers. If that's what you're trying to do, welcome. It starts here with the unedited, unscripted, live stream podcast. But if you want to take it to the next level, you've got to go to our website at your everyday AI.com. There, a couple things you can do, but number one, sign up for the free daily newsletter.

We're to be recapping the highlights from this very episode in there, as well as keeping you up to date with all of the other AI news. But also, it's a free generative AI university. And as of today, there are 600 episodes. You can go watch the videos. You can go read our recaps. You can go listen even to the actual podcast all on our website. It's all for free, sort of by category.

No matter what you're trying to learn, we've probably already gotten all that info from the world's leading experts. So yeah, if you want the AI news, make sure to go check out today's newsletter. All right. We made it to 600 episodes. Can you believe it? Seems like yesterday,

but also two decades ago that I started doing this everyday AI thing. And, you know, I was looking back at, But how we kind of, you know, celebrated or, you know, what shows we did at, you know, 100, 200, you know, 300, you know, 300, et cetera. And earlier on, it was a little easier, right? Like, oh, here's 100 facts you need to know about AI or something like that. At 600, we can't do that anymore.

I'm not going to give you, you know, 600 hot takes or anything like that. You all would fall asleep. So instead, we're doing a little math. Six times 10 times 10. six AI math myths you should stop believing 10 AI systems you must learn and 10 AI trends you can't afford to ignore all right live stream audience good to see you i'm wondering when did anyone start listening to the podcast was anyone around for some of the first episodes they were pretty bad but live stream audience good to see you uh thank you ruth uh saying good morning from boston

and Jackie saying congrats, appreciate it. Peter, thank you for joining Jay live from Grand Rapids, Michigan. Monica saying congrats on 600. Jay as well. Thank you all. Appreciate your support. So let's get into it. So like I said, we're going to tell you the six myths, you got to stop believing.

There's so much bad information out there. People are listening to these common AI myths. We're going to debunk some of the most common ones. Then I'm going to tell you the 10 AI systems that you need to be learning and using. And this might come as a surprise to some, but we're going to get into it. What makes my top 10 list there? And then I'm going to tell you some top trends that you need to pay attention to. And they might not all be relevant to your business lives, but these trends, I think, really are going to help shape how the world works in the future.

All right. Let's. Oh, and one other thing. This was so hard. This was so hard to come up with this exact list. Y'all, like, I was thinking the other day, I'm like, I waste, quote unquote, waste 80% of my research and 80% of my content. You all think like these shows are long as is. Y'all, like I only give you the top 10 to 20% of information that I, you know, research on, compile, etc.

So I think I'm going to start doing more of these like, hey, go. repost the show and I'll send you all my, you know, not all my notes, but I'll send you the next tier that just missed the cut, right? So I did put together seven more AI myths debunked, seven more AI systems to learn and seven more AI trends you can't ignore. So if you want access to that, I'm not going to keep you for, you know, another 45 minutes and tell you those things. So just go share this LinkedIn post. So we live stream to LinkedIn, trying to really get a bigger footprint there. So if you want access to those, it's already made, it's ready to go. Just go repost this and I'll send that to you.

All right. Six AI myths. You got to stop believing. Let's get into it. Number one, AI can be your company's competitive advantage. No, it can't. Right. I still, you would be surprised.

It is the year 2025, y'all. Still companies that were, you know, super slow to adapt. Essentially one like this, 2023, they sat on the fence. 2024, they did a terrible year-long pilot. And then 2025, they're like, all right, we're going to do this AI thing because this is going to set us apart. No, it won't. Right. If you are in the year of 2025 actually thinking that using AI can be your company's advantage, absolutely not.

I'll say it like this. If your company top to bottom wasn't already implementing generative AI in 2024, you were at a competitive disadvantage in 2024. So not only is the messaging in kind of the competitive landscape, they're flipped in many business leaders' minds. You are already very far behind. If your entire company has not been trained on Gen AI basics, let's just say, I would not want to be working at your company. And I'm being serious with that. The fact that there are still large organizations out there that don't have AI policies. that don't have an AI business operating system,

that haven't trained their employees top to bottom, whether it's C-suite, you know, junior workers. It is so few people, right? Companies are investing billions and billions of dollars in, you know, building, fine-tuning their own models, which I think for the most part is a waste of time. They're spending a lot of money monthly providing access, right? Companies just think like, oh, okay, we're going to, fine,

we're going to do this AI thing. here's some Microsoft co-pilot licenses. Here's some chat, GPT enterprise licenses. Problem fixed. Wrong. That is not your company's advantage. Next. Going along with that,

thinking that just providing your employees an AI tool means that productivity is going to go up, right? And then we saw those early studies, you know, from McKinsey Digital, you know, that said generative AI will be able to automate up to, to 60 to 70% of daily manual task for knowledge workers. And I think some decision makers, somewhere up there in the C suite that haven't touched a computer in a couple of years,

took that to heart in the wrong way. And they're like, all right, fine. You know, it's a line item. You know, it's going to cost us, you know, for bigger organizations, a couple million dollars a year to provide, you know, tens of thousands of employees with the AI tools that they need. There we go. There's that 60 to 70%.

savings, absolutely not. It's literally like saying, okay, well, we're going to require now our employees to speak a different language, to communicate in a different language and thinking that's it, right? Like if you're a U.S. company, all right, let's take our U.S. employees and we're going to go to South America. We're not going to teach anyone Spanish, but we're going to give them a Spanish keyboard. It doesn't work like that. You have to teach people. This is a brand new way to work. right? I always say, get rid of the words re-skilling, upskilling, because I could vomit. No, you have to unlearn and then relearn. It is literally like learning a new language. Learning to move your day-to-day processes into a generative AI system, it's like learning a new

language. So just giving your employees access to AI tools does not equate to an increase in productivity. And no matter what you do, don't read these. I stop myself. I didn't want to say anything too bad. Don't read these terrible studies like the MIT study and believe anything. I should have started with that. All right. Number three, companies thinking AI is a co-pilot, right? Yes, Microsoft named co-pilot. And I'd say in 2023, you could look at the world's most powerful frontier AI models and AI systems and be like, yes, these are co-pilots. Not anymore. Not anymore, right? We are in the Waymo area, right? Today's best AI is autonomous.

It can go out. It doesn't mean it's good if you're not investing the time and the resources, but those companies that are investing the time and the resources, AI is no longer a co-pilot. It's a pilot. It can fly itself, right? You don't need a human anymore to click a button and make the generative AI go. That's so

2024. All right, three more AI myths before we move on to AI systems. In live stream audience, I would love to get your your thoughts on this. This might be one of those, you know, I might just screenshot some of the most

valuable or entertaining comments and just share those in the newsletter. You know, I love making this community effort. So I'd love to hear your hot takes or, you know, myths or even, you know, just kind of your thoughts and the ones that I'm sharing. So the next one, AI can't be as empathetic or creative as humans.

That is absolutely false, right? I think one of the biggest issues is people make individual judgments on these myths based on their own expertise or usage, which oftentimes is nothing or next to nothing, right? someone goes in for the first time and they use an AI system. They don't know what they're doing. They're using an old model. They don't know how to, you know, the basics of quote unquote prompt engineering. They see something and they're like, this is absolute garbage.

No, your skills are garbage. The most powerful AI systems when placed in the right hands are more creative than humans. And they're more empathetic than humans. Multiple studies have shown this. There is a study in 2024 and in 2025 that essentially looked at the bedside manner of chat GBT versus doctors. Guess what? Chat GPD in large studies, right? These weren't MIT studies. These weren't marketing pieces. These were real studies done correctly with sound methodology showed that chat GPT was more empathetic. Similarly, there's been blind studies at the university

level that judged creativity blindly between college students and AI systems. Guess what? The AI systems were deemed in a blind study done the correct way with proper methodology to be more creative than humans. Doesn't mean that it's going to happen every single time or if you go in and say, give me 10 creative ideas about blank and you're like, humans could do better. No, that means that you need to put in more work on the context engineering side of using a large language model, but I don't care what anyone says. Period. AI models, when used correctly, are more empathetic and more creative than humans. Get that myth out of your mind. Next. Now, AI will create more jobs than it will take. No, it won't. Sorry.

Y'all, I think some people think that I'm rooting for AI to take jobs. I'm not. People think I'm rooting for AI. I'm not, right? I like humans. Humans are cool. AI is cool as too. Um, but AI will not create more traditional full time jobs than it will destroy. Period. That is corporate speak. I'm not here from corporate. All right. I think the future of full-time work is going to look very different. I'm going to be sharing if you haven't listened already to our 2025 AI prediction and roadmap series. I have a screenshot of those coming up here in a couple of slides for my live stream audience. You need to listen to them, but AI will create millions of new full-time roles.

But it will not create the same number of new full-time roles. you know, I'm going to say in a five year span, five to 10 year span, there will be way fewer full-time jobs that exist here in the U.S. I don't know what the impact is going to be abroad in the EU as an example, you know, companies that are actually legislating and regulating AI. That's not how it's going here in the U.S. And ultimately, this is driven by corporate agree. I think AI could in theory create more full-time roles than it destroys, but it's corporations that are looking at headcount. And when they see, when they implement AI in the right way and they're like, hey, head count goes down, revenue goes up, stock goes up, they're going to

keep doing that. All right. So I do think we're going to see a massive shift over the rest of 2020 on what full-time employment actually is or what employment actually is as we undoubtedly achieve the AGI and the world that changes a little bit. So, but that's not true. And if you believe that, that's fine. This is one of those things. Bookmark this and, you know, let's talk in 2030. And let's look at the numbers because numbers don't lie.

But yeah, the number of full-time roles will reduce dramatically because of generative AI. Last but not least, human in the loop, leads to agentic success. No, it doesn't. That is a myth and that is terrible. And I don't know anyone else out there who has been railing against human in the loop as long as I have. It's a crutch that can't support the weight that is leaning on it. So many organizations that, you know, they're like, we kind of know what we're doing when it comes to AI and, you know, they're trying to be on the cutting edge. So all right, agents, here we go. Whether you're building those in Microsoft co-pilot studio or you're using building on top of OpenAIs, agent SDK responses, their new responses API.

Right. There's so many agentic systems out there now. Most of them aren't really agentic, as we saw by the Gardner study that said 95% of companies and vendors promoting agents, they're not actually agentic. But companies that have pushed out real agentic AI, they think. okay, human in the loop. I'm sorry if your name is Bill from IT. This is always the example I give, right? Because I've talked to organizations and they tell me this.

And it's like, okay, you have this financial agents, right? You have this marketing agent that is out there autonomously doing financial forecasting or doing marketing work. Who's overseeing this? Who's your human? Who are your humans in the loop? And everyone's like, oh, it's Bill and IT. That's wrong. human in the loop is a recipe for disaster because of agentic drift.

All right. You need expert driven loops. Can we all start doing that? I made it up, EDL, expert driven loops. That's what we need. Human in the loop, a lot of companies are looking at that as a crutch because some smart people said it two

years ago and it's an absolutely terrible way to think of agentic AI. It's a false sense of safety. When you do human in the loop, that way putting Bill in IT as you're human in the loop. No, you need multiple experts driving a loop. That's how it works. Ha! Hot takes.

Yeah. Jay said easy there, Jordan. Is this turning it into a Tuesday show? Are the takes a little hot? All right. All right. Do you guys agree, disagree with those? Let's get into the AI systems.

You must use and learn. 10 of them. Ready? We're getting a 600 through 6 times 10 times 10 math. All right. Let me say this. I want to take everyone back to, you know, maybe 20 years ago, 15 to 20 years ago. Think of the type of skills that you would put on your resume, right?

I know this sounds weird if maybe you're a younger audience sitting in. But, you know, 20-ish years ago, multiple decades ago, on your resume, you might put something like typing speed, right? Words per minute. Here's what you can do. Right. You might have put some skills like, you know, Microsoft Word, right? As the software industry took off in the early 2000s, right?

You might put, you know, Salesforce, you know, building Salesforce pipelines, right? There was all these different types of tasks that were considered important. Okay. Now, I think there's 10 AI systems that everyone needs to learn, regardless of what your job, role or responsibility is. And unfortunately, you might be having to learn some of these on your own personal time, because your company shouldn't, right, your company probably shouldn't be giving you access to all of these 10 different AI systems anyway.

But I think these are actually fundamental. skills, right? In the same way that using a computer was a fundamental skill of the 90s and early 2000s, I think understanding and knowing the basics of these AI systems is going to be a foundational skill set in the rest of the 2020s and 2030s. All right. So ready? Here they are.

And I put them in the order that I actually use them. Okay. So number one, chat GPT. Even if your company is not a chat GPD organization, they have the most users. 700 million active weekly users. Chat GPD is huge. It's growing. Even as Google is out shipping them and outperforming them in many ways, the one area where

Open AI still continues to dominate and why I think it's essential that everyone learns chat GBT is it's stickier, right? One of the issues with Google and Microsoft is their respective AIs, Gemini and co-pilot, they're everywhere. You can use them everywhere. And sometimes when something's everywhere, it ends up getting used nowhere. Or it's just too hard because it's too fragmented. So that's one of the main benefits of chat, GPT.

Everything is centralized, right? And it's much easier to give employees access where sometimes it's like, all right, well, we don't know how to give this group access to co-pilot across these seven different instances, right? Are they using it in Teams? Are they using it in PowerBi and Microsoft Copilot Studio? Do they have the right, you know, dynamics permissions, right? It's convoluted and complicated sometimes. Even if you are a co-pilot Gemini organization, you should be learning chat GPT. Number two, Google AI Studio. Foundational skill. I kid you not.

I use AI Studio all the time. Google AI Studio. They've started to put limits on there, but they're still wildly generous free tiers on there. If you're not using Google AI Studio, you need to start, right? You can use Gemini 2.5 Pro, which right now, according to most benchmarks and eVal's is the most powerful model in the world for free. the context window is larger and longer than it would on the front end of, you know, Gemini.gov.com if you're using Gemini on the front end. So you just even, you know, and then there's some basic dev controls, right?

You can control temperature. You can control outputs. You know, there's just a lot of more granular control. So even if you're not technical, so shout out to the team there at Google that has really made, I think, Google AI Studio a force to be reckoned with. And they've made it easier for non-technical users as well. Next, Google Gemini, right? Especially if your company is a Google organization.

You need to start using it and understand it. Number four, an agentic browser, right? There's not a ton now, but I think to be prepared for the future of work, I'm very bullish on the fact that agentic browsers are going to have a more immediate impact than actual agents, right? I think in the long run, the ceiling for agents is obviously much higher. But when you talk about agenic browsers versus AI agents, well, one of the advantages to agentic browsers is you don't have to rely on Bill and IT, right?

Comment, I'm using comment from perplexity more and more. There's Dia, there's a handful of other sound agentic browsers. Next, notebook LM. Y'all, if you're not using notebook LM, I don't know if we can be friends. I'm kidding, of course. But again, one of those systems that is so incredibly powerful to be able to ground Gemini's 2.5 in your own data only. So if you are brand new and you don't know what notebook LM is, right? Let's say your company does logistics.

So you can upload all of your information in there. And then if you ask notebook LM about marketing, it's going to be like, I don't know, bro, right? It is one of the best ways to get rid of hallucinations in large language models because you feed it, whatever information you have. And if you ask it anything else, it's not going to know because it only uses the information that you upload, which is an extremely powerful way to work with AI. All right. I'm going to go through these next ones quickly, but copilot. You got to know co-pilot, even if you're just starting to use it in the browser. So yes, co-pilot uses a lot of Open AIs models, but there's differences in how they

behave. There's differences in the functionality, right? And in the future, we've heard from Microsoft, they may start offering other models, even on the default co-pilot. Obviously, if you're building in Azure, you're, you can use just about any model out there. But you need to be using co-pilot, period, right? So many of the world's largest enterprise organizations

run on co-pilot, I get the gripes. I hear them, right? Co-pilot can be, I think it's, I'm gonna blame Bill. Bill and IT needs to do a better job. Explain if, gosh, if I know anyone named Bill and IT, they're never gonna talk to me again. IT departments or whoever is managing access in co-pilot, you got to do trainings, right? On just here's how to access co-pilot.

And you need to make sure the right teams and the right people have access to co-pilot in the right places because this is still, believe it or not, still one of the number one hurdles when it comes to co-pilot integration and usage going up across teams is access in permissions and knowing where they have to use it. Right. I think one of the biggest pros of co-pilot and Gemini. It works everywhere, but then specifically co-pilot is like, well, it's everywhere. How do I use it? It kind of behaves differently when I use it in place A versus place B. When I use it in place C, it can access these files, but when I go to place D, it can't. Right. So yes, there's obviously learning, education, training, and ongoing development that needs to

happen. But one of the biggest things is just understanding access and permissions. All right. Number six, you need to be used. using an AI video platform. Even if you are a non-creative, go in there once a week, create one simple video. All right. I do think I see the future of content consumption being highly personalized and highly targeted. So even if you're not a creative, I think it's important to understand the basics, right? Just as if you weren't a full-time creative, if you had Adobe, you know, creative suites on your,

resume 10 years ago, even if you weren't a full-time designer, full-time, et cetera, right? Companies would look at this and be like, okay, they have a baseline understanding of an important sector, an important part of our business. I think it's important for people to understand how to use AI video. It's not hard. Next, the 10 AI systems that you must use and learn. You need a quick model eval, all right? What that means, oh, I left one off my list.

All right. We're going to make it 11 because I can't forget this one. But you need a place to quickly evaluate models. All right. So one of the things that people don't understand is we should be building AI solutions when you're talking about using an API. All right. So I'm not talking about front end users.

Now I'm giving a little bit of strategic advice for our back end people, people building solutions and those people using those solutions that are a little bit more custom, you should be building everything in a modular way. What that means is let's say, you know, your company has been using, you know, GPT40 and they get rid of it. Or your company's been using, you know, Claude 4.1 and then they get rid of it or Claude 4.2 comes out. And maybe it's not as good at certain tasks, right? Because they started to focus on something else differently in the model. You need to be able to have your, uh, either your individual, your team or your company wide use cases. And you need to be able to quickly benchmark and evaluate those and using something like

hugging face or LM arena, super simple, free, but being able to go in, look at models side by side and evaluate them for your individual use cases because these models. And we're not just saying like, oh, when you go from, you know, GPT 40 to five, no. These models get updated all the time, usually multiple times per month under the hood. Right. So you might have had something set up that was working. And I'm just going to use a, you know, Gemini 2.5 flash as an example. Maybe you had some workflow set up for Gemini 2.5 flash that were working perfectly.

Google does a under the hood update. And all of a sudden, you're like, wait, what's going on? Right. Well, first of all, you have to pay attention to those. Go look at the change log. see if you can find out exactly what was changed, but you have to be able to evaluate models on the back end quickly. What happens if one of these quality of life minor updates to these models

actually slow things down in a big way? Maybe you were using a cheaper model like a Gemini 2.5 Flash or, you know, GPT5 Mini on the API side and they changed something and you were using it for, you know, customer service responses or something. And now you're like, wait, now they're bad. Now these responses are terrible. You have to be ready to be modular. You have to have plug in place.

You have to be able to quickly evaluate models. All right. The one I forgot on my list, open source. You need to be using an open source model. So even though they're not great today compared to the frontier models and the state of the art offerings, the gap is getting smaller. The technology is improving, right, in terms of being able to actually run these models locally. But the fact now, you have models, I think probably the most impressive. open source model that I've used is GPTOSS, right?

The GPTOSS model. So in a lot of regards, this is very similar in terms of capabilities to GPT4. Right. So if I would have told you a year ago that you could download GVT4O, never pay for it, all the data that you connected to it would be completely private, because it runs offline.

It runs locally on your machine. You don't even need internet. If I would have told you, people that, right? People would have said, this is nanobananas. I can't believe this, right? But you should be using and experimenting and maybe eventually using some of your more proprietary or sensitive AI use cases, maybe those that you haven't been tapping into AI on the cloud side, bringing them open source. There's great tools. You know, Olama is probably the one I use that allow you to run models locally.

And again, as the hardware catches up, right, GPUs are getting more powerful. You know, your average PCs are getting more powerful and more capable to run these models locally. All right. Next, uh, Claude. All right. Yeah.

Even though I'm not a big Claude fan, you should still be using it. All right. This is the Microsoft Word, Microsoft PowerPoint, right? That goes on your resume. You need to understand the basics of how Claude works. All right. again, think of typing. Think of Microsoft Office.

Think of, right, if you are in any analytical position, right? People would always get like, you know, I got my Google Analytics certification, right? Even if they're not working in Google Analytics, there's certain foundational skill sets that you just have to go through and understand to make you an adaptable, an employable person in the future. And even learning Claude, learning co-pilot, learning Gemini. learning chat chbt those are included and then last but not least an oh an ai coding tool whichever one it is you need to learn one of them at least i'm not going to say learn all of them because there's a ton so rather whether that's cursor open a i's codex uh googles gemini cly replet zgit hub copilot etc find one right and i'm not saying you have to turn into a developer

build yourself little applications they're not hard You can literally build yourself, right? If you look at software that was impressive, you know, desktop software that was impressive 10 to 15 years ago, you can go build those types of solutions now in less than an hour, right? And run it locally on your own machine, something that solves problems for you, right? The way I started doing it, I started with simple Chrome extensions, you know, doing little simple web apps, right? Start solving your own problems first. but I think you need to ultimately pick one of these AI coding tools. Here we go.

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creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible so you can refine, redirect, or take over at any time. You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at firefly.adobie.com. We're in our last section. Celebrating 600 episodes, six AI myths, 10 AI systems you must learn in 10 AI trends.

So now as we pivot to our last section, because some of these trends, I'm not going to say they're random, but these aren't the most important AI trends I'm looking at. For those, make sure you go back and listen to episodes 443 to 447. I should have done like a midterm update on these. I was planning on doing it and then things got busy in life. But go listen to them.

All right. It's a five-part series. They're very short episodes. I know sometimes I ramble in these episodes turn into very, very, you know, long listens. And I apologize for all the people that say, oh, I listen every day on the treadmill. And then I feel bad.

So go listen to those. They're very quick. There's five of them. They're 25 minutes each in going over 25 AI predictions and roadmaps for 2025. So these next AI trends to pay attention to, they're not necessarily the biggest or most important. But these are some of the ones that have either. they're falling through the cracks, maybe didn't make that original series or something that has

emerged in the last few months, kind of out of nowhere. All right, here we go. Digital evidence will be a thing of the past. All right. So I'm not just saying this from a legal perspective, but even just thinking what you believe, right, things you read and see online. Anything digital, I wouldn't believe it. I know that sounds weird, right?

That's why, if I'm being honest, that's why I do this as a live stream, you know, and that's why as much as I can, I try to take questions and comments from the audience, right? I want to be your, your human friend in AI. I literally still get people leaving comments on the live stream, right? I saw one last week. Someone's like, oh, this is an AI. Like, this isn't a human. Like, now, it's, it's me, right?

But I get that. You should be skeptical of everything you see online because the AI systems, voice cloning, uh, digital twins and avatars, um, the AI photo, AI video. It's so good. I mean, look at the nanobanana. Literally I can upload a photo myself. I'm going to get a complete duplication. I can put myself anywhere doing anything, then load that into V-O-3 and it looks real, right? And this is the, worst the technology will ever get. Think about that. Digital evidence gone. I'm not just saying from a legal perspective. Next, I think third party AI chats are going to start to die. So there's great ones that I think are obviously going to stick around, right? But essentially,

there's literally thousands of platforms. And I'd say there's hundreds that are well funded. And I'll say there's dozens that have enterprise footing. So you, need to be careful here. I think eventually some of these bigger ones are going to die. I'm not saying the you know, you dot coms and the pose. I think those are obviously going to stick around and keep growing. But there's so many of these like second tier third party services that all they do is they're like, okay, you can come on here and, you know, use every single, you know, large language model, right, for $20 a month or $15 a month, right? You're not going to stick around for long because I think what kept them going on early on,

was the ability to use different models because a year ago, certain models just didn't have all the features and functionality of others. That's no longer the case. Right. So I think early on, these third party AI chats were more just identified gaps in Frontier Labs go-to-market strategies. And I think the big players have already adjusted that. So I don't see, And especially on the scaffolding side, right, the tools, right? Because early on, you know, I mean, even Claude, like, I don't know, five months ago, Claude didn't have access to the internet, which, I mean, they shouldn't have just went out of business just for that because that was an asinine predicament, the fact that, you know,

we were in the year 2025 and Claude didn't have access to the internet, right? So essentially, there's all this, the scaffolding or tools that these third party chats would provide most of the models right when we talk about co-pilot clod uh chat gbt and jemini they have all the scaffolding they have all the tools now right and it's it's very similar so i do think they're going to start to die off so i wouldn't put a lot of your day-to-day business processes into any of those third-party chats next social ads aren't real let's be honest if you're seeing any social ad assume it's fake assume it's a i and it's probably is right and and maybe that's better maybe that's better right uh this is kind of related

to one of the uh 2025 AI predictions i i said AI video is going to catch up in 2025 and uh not kill uGC ads but essentially make them obsolete or put a expiration date on them and i think that's already happening next web browsing will start to die oof it's a hot take I know it's not popular for people in the media. You know, I was formerly a journalist. I think traditional web browsing is going to start to die. And that means a lot for the future of media. And I'm not going to get into it too long.

I'll probably do a dedicated episode on it now. But I think that you can probably even say personally, I go to so fewer websites, myself, right? I'm absolutely loving Google's AI mode. They've made it so much better recently. So between AI mode, between deep research from Open AI and Gemini, I'm not going to the websites. I'm not going to websites a lot. Right? When I have eight tabs open in Chrome, it's because I got co-pilot open. I got Gemini. I got chat GPT. I got Google AI studio. Right. I have Claude. That's why I don't have 30 different websites up.

And I think that it's going to lead to a lot of, you know, I've always said the three choices media publishers have, but I think actually going to websites is going to start to go away. Open source will surge. That's our next one. You know, there's been this promise and premise of open source models for a long time. But up until about a month ago, when GVT OSS was released, I don't think that. there were a lot of capable models that the average person could run on a consumer computer. Yeah, when I say consumer computer, you probably got to spend at least like three grand,

but you don't need a supercomputer. You don't need a server. You can literally go out there by a higher end consumer laptop and you can run a model that's as powerful as GPT40 and GPTOSS locally. I think open source is going to surge in the next couple of quarters. I think that companies, like I said, that were fence sitters because of maybe not wanting to handle certain private or sensitive data, there's no need to now. There's no need to have that hesitation. Yes, you still have to have expert driven loops.

You still have to train people how to use them. You still have to be able to look out for hallucinations. You have to understand the basics of, you know, context engineering, which is essentially our. prime prompt polish framework, right? But open source is going to search. Our next couple, I'm going to wrap these up quick here. I think world model competition is going to go bonkers. We've seen Google lead that with Genie 3.

I think we're going to see something soon out of world labs. I think world models are going to be the new race of 2026, but I think we're going to start to see that form a little bit in 2025. And if you didn't see Jeannie 3, we've been sharing about that, Make sure to go look that up from Google. I think that the ultimate, and I've been talking about this for a long time, the end goal of generative AI is out in the real world, right? Training data. I'm not saying we've hit the cap, right?

But all these frontier companies are training on the same internet. Yes, Google has a huge advantage because they have access to YouTube. You could make a case for GROC that GROC has an advantage because it has access to X data. but a lot of data on X is just garbage anyways, right? But for the most part, these companies are training on the same internet. What comes next is training on the real world in models that can marry your traditional, quote unquote,

text or multimodal models with real world data. All right. Next, I think we're going to see a new wave of Big Four type consulting, consulting groups. So, you know, you have your traditional consulting groups, your Accenture, your KPMG, your E, EY, et cetera, right? And obviously after dragging their feet in 2023, most of them woke up and started to try to

become a little more AI native. But I think we're going to see this new surge, almost like we saw startups, you know, in late 20, in the late 200s. How do we say that? In the late zeros, O's, aughts? How do I say that? Right. You know, your Facebook, your Twitter, right?

We almost saw this new category of businesses, the startups, the early startups. I think we're going to see the same on the consulting side. I think we're going to see some names that no one knows today or maybe they haven't even been created yet. And I think in five years, they're going to be just like known as well as the BCGs, as the EYs, as these big consulting arms. But I think they're going to start from nothing or they start. from nothing in the past year or so, and they're going to become juggernauts, right?

Look at Open AI. Open AI is literally providing consulting services on their own products, and they're charging millions of dollars. I think that there is a market for that. I think even though the big fours in the, we'll say that the tier one management consulting companies have shifted to be a little more AI friendly, AI native is always going to be faster, and I think we'll win. Next, explainable AI.

becomes a key focus in agentic AI. That's because I expect a lot of big lawsuits to finally be decided because of hallucinations or because of AI model behavior going badly. We obviously saw the very sad story of the teenager that tragically died. In part, the family is alleging because of the conversations with chat GPT. I think we're going to see a lot of stories very similar to that. that and in the business sense, where companies weren't spotting hallucinations. They weren't spot behavior.

And this is with one-on-one chat spot interaction. But when we think about agentic AI, I think explainable AI and traceability is going to make a researchance, right? These were all things that we were talking about, you know, people were talking about these things obviously in 2022, 2020, 23. And then they kind of hit a pause while we all talked about rang and Identic AI, but I think explainable AI and traceable AI is going to become a huge focus point in the coming quarters. Next, 2026 midterms in the U.S. are going to be the AI election.

Here's why. It's small enough. It's not a presidential election here in the U.S. It's midterms, right? There's going to be so many AI generated ads that decide. key elections, right? Because they're going to come out a little too late and it's going to swing some major elections. Book market now.

The technology is too good, too powerful, too fast, too cheap and too hard to tell the difference between what's real and fake. Literally, there's going to be multiple U.S. elections in the 2026 midterms that are going to be decided by AI. And I actually think it's going to be less problematic in 2028 for the presidential elections because by then, I think that this will have unfortunately become a big enough problem in our society that the average everyday American will know, kind of like we know, oh, like, was this Photoshopped? Right. 99% of people don't know that AI video exists in the way that it exists now. And I think that unfortunately, the 2026 midterms are going to be the thing that exposes that. People don't realize they're around the corner. I believe the first midterm start in March, right? So we are three, six, like six, a half year away from midterm elections.

It's going to be the AI election. It's got to get a little ugly. But literally you're going to have deep fake misinformation, disinformation from AI sway key elections. All right. And then our last trend. I think AI, ready? We're going alphabet soup here, y'all. AI will ruin WFH because of ROI on Gen.

AI. All right. Here's what I mean by that. Work from home, right? We're seeing a big surge in return to office, right? RTO, because companies that have been using generative AI, right, and are either so many still big corporations are either work from home or their hybrid and companies are starting to invest in AI and they're like, wait, where are big returns, right?

There's something happening. Sorry employees, right? So many, so many employees are just automating 80% of their jobs with AI. And they're just pocketing that time. Right. You literally, I think, have a huge, huge section, a huge block of the, you know, work from home or hybrid or second computer workforce that have essentially automated a large chunk of their roles,

and they're maybe, you know, just working five or ten hours a week because they're really good with AI. Or their company has antiquated processes to be able to manage workflows. It's huge. And I think that AI, in turn, is actually going to ruin, quote unquote,

work from home and hybrid because companies are not investing in unlearning their own, processes, right? They're like, hey, here's, here's some, you know, licenses of an AI tool. And, you know, they're like, where's that 40% productivity boost? People are pocketing it. Maybe you should pay people more, big corporations.

All right. That's a wrap. We went over six AI myths, 10 AI systems you must learn and 10 AI trends. You can't ignore. All right. I hope this was helpful. Like I said, there was a lot that didn't make the cut. If you want, seven more AI myths debunked.

Seven more AI systems to learn and seven more AI trends you can't ignore. And these were some really good ones. I'm like, man, I can't believe that this one didn't make my list. But we had to get the math, you know, six times 10 times 10 for our 600th episode. So if you want to access to those, just please repost this. If you need to find the link, it's always on our website. It's always in our newsletter.

If you're listening on the podcast, it's in the show notes. So go find the LinkedIn post for this one, episode 600, repost that. I will send you over those additional resources. I hope you guys like these little bonus things. I just realize so much great information for this show just ends up dying on my desktop. And I'd rather share it all with you. If you just take 10 seconds and just share this information with everyone else. I think understanding and to go back to how I start this as I wrap up,

understanding some of the basics. Good, unbiased, well-researched information shouldn't be gate kept. That's what I'm trying to do with everyday AI. So much of the information out there, it's ultimately snake oil, someone trying to sell you something. It's, you know, a certain big tech company is putting it out. So it's obviously swayed toward them. I want to be able to do this for another 600 episodes. But I can't do it without people like you who are finding value telling people about this.

Right. So please email people in your organization if you find a specific episode helpful. Share it with your colleagues. Please subscribe to this. If you haven't already. share these LinkedIn posts when I say these. I hope I say these things. I hope they don't sound like a broken record. But ultimately, if you find value in this show, I can only do another 600 episodes if you help me out. If you share, if you tell people, if you follow us on Spotify,

leave us a rating, all that good stuff. So I hope this episode was helpful. Thank you for your support over the last 600 episodes. Couldn't have done it without you all. Really appreciate it. I hope this is helpful. If you haven't already, please go to your everyday AI.com. Sign up for free daily newsletter. What should we do in the next 600 episodes? Anyone want to plan all of them out right now? All right. Thank you for tuning in. Hope to see you back. Later. For more Everyday AI. Thanks, y'all. Meet Firefly AI assistant. Now live in Adobe Firefly, the Allman One Creative AI studio. Just describe what you want to create in your own words and the assistant handles the rest, orchestrating multi-step workflows across Adobe Creative Cloud apps, including Photoshop,

Premier Express and more in one conversational interface. You direct the outcome while the assistant accelerates execution. Stand control with the ability to step in and refine at any time. See it today at firefly.adobie.com. 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.

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