Ep 766: ChatGPT Images 2: How Even Non-Creatives Can Unlock Growth With Images 2

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Maybe you've said this yourself or you've heard it 100 times in your business. I'm not a creative person. Well, that sentence might have just stopped working. For decades, enterprise leaders have outsourced visual thinking and their business creativity to designers. Designers got the brief, the budget, and then at times the bottleneck. But that whole arrangement might have just collapsed. That's because OpenAI released their ChatGPT Images 2 this past week, and it generates legible text on photos, creates photos that look the right amount of real, and and pixel-perfect UI mockups. It maintains character consistency across 8 images from a single prompt and handles multilingual outputs without hesitation. It thinks, uses the internet, and can leverage the history of your ChatGPT account. And it does it all from a simple prompt. So if you've been telling yourself you don't think visually, I have great news for you. ChatGPT's new Images 2 model, does think visually, and with only a few simple prompts, you can expand your company's entire visual world. That's what we're going to show you today on Everyday AI as we put AI to work on Wednesday. So here's the big picture. AI image generation, I think, changed forever, right? I think we've talked about, you know, AI images kind of having their ChatGPT moment with the Nano Banana, Nano Banana release, but as we'll see today, ChatGPT Images 2 is so much better, not just than their last model, GPT Image 1.5, but then literally anything else out there, and it's not even close. I think now the biggest difference is ChatGPT Images 2, the generation reasons through business briefs and your chat history and your iterations rendering, uh, before rendering a single pixel. So in the same way that if you use a non-thinking large language model and a thinking model, you know, the outputs are much better. But that same pattern across text-based outputs just compounds across image outputs. And the great thing, this is already live on every single ChatGPT plan today, whether it's free or not. You obviously do get a little more with the paid tier, so you can start using this right now. So that's what we're going to be tackling on today's show, our weekly Putting AI to Work on Wednesdays. Here's what you're going to learn. You're gonna know what's actually new and why the thinking mode changes everything for creators and non-creators. You're gonna learn why every non-creative business leader now needs a creative mindset and how you can develop that, and 10 specific use cases and pro tips that your team can deploy this week. All right, let's get to it. Welcome to Everyday AI. My name's Jordan Wilson, and while we do this every day, uh, I hopefully can serve as your daily guide to understand the nonstop developments in AI across our daily livestream podcast and free daily newsletter to help you learn and leverage AI to grow your company and career. So starts here with the unedited, unscripted livestream podcast, but make sure you go to youreverydayai.com, sign up for the free daily newsletter. We're going to be recapping today's show as well as all of the other AI news you need to know to stay ahead, right? So Have you used Images 2 yet? If not, well, I think this one's gonna blow your mind. Let me just say that. All right, and this is one of those podcasts, FYI, you might wanna go watch the video version. This is gonna be a very visual show, especially when we go hands-on. So in the first half, I'm gonna go over what's new, how it works, some of the use cases, et cetera. And then on the second half, we're gonna go live. So yeah, we do kind of live demos on our AI at Work on Wednesdays. Sometimes they turn out well, sometimes they don't, honestly. Right? So we'll see how it goes, but make sure you can go to youreverydayai.com, click on the episodes tab at the top, and then you can go watch today's video if you do want to see what's happening on screen. All right. And I did also, FYI, I put together a PDF brief with a bunch of different examples that you can look at as well as the prompts that were used to create that. So if you do want access to that PDF, make sure to repost this show on LinkedIn and I will send that to you. So yeah, in the show notes, if you're listening on the podcast, just go ahead and repost that LinkedIn show. All right, here's what's new. I think that there's a couple of big shifts. So number one, the biggest new thing in Images 2 according to OpenAI is the new thinking mode. So this plans the composition of your image, the typography, and any constraints before rendering anything, right? And that's huge, especially if you remember the very early days of AI image generation, right? I remember using the original DALL-E with OpenAI, you know, you could ask for a picture of a basketball and it looked nothing like a basketball, right? Now, as we'll see, it's extremely realistic. That's one of the biggest differences. The other thing, well, it's grounded in the real world with real data. That's because Images 2 has live web search and it grounds those visuals in real-time facts and current data. So you can say, you know, create me, which I think is one of the examples that I have in the PDF if you want that. You know, I said, go look at today's, you know, newsletter, uh, you know, from Everyday AI and put it together in a newspaper form, right? Or, you know, some of the, uh, you know, kind of examples that have gone viral, or, you know, find the, you know, the marketing industry's latest news for today and, you know, lay it out in a magazine layout, right? Those things are extremely impressive because it shows off, uh, both the thinking capabilities, it shows off the ability to ground it in live search, and then obviously the design prowess. You can also generate up to 8 cohesive images from a single prompt. All right, some of the other things that really, I think, make this a step change above anything else, the text rendering is nearly flawless, right? I think we got that nearly flawless step with Nanobanana. So this is not necessarily new across the industry, but this is new for OpenAI. In their first Images model, the text writing was not good. In Images 1.5, it was pretty good, right? You might have to clean up a few things. So far, using Images 2, I don't— maybe one thing I've had to clean up out of a lot of generations. I mean, we'll see how today's live tests go, right? Yeah, watch, today's gonna be the one where it just spits out all gibberish, even though it's been, you know, pretty flawless so far. But that piece is huge, right? Because even if you remember during the kind of the earlier Midjourney, you know, phase, kind of one of the other popular AI image generators, you know, even some of the later versions of Midjourney from, you know, 2024, 2025 did not have coherent text rendering. Right. Like I said, I think Google really changed that with Nano Banana. Some of the other, you know, Chinese, you know, AI image models did a great job with that as well. But I do think now it's a completely new leap that we've seen with images too. Also, there's fun things you can do. You can literally create functional QR codes, barcodes that actually scan to real-world destinations, right? So this isn't just something that creates images. It can create, well, interactive experiences. You know, some of the things that have kind of gone viral online is, you know, you can create a 360 image, right? So if you open it in a 360 image browser, you know, you can literally scroll around, right? Like you are there, you know, and then the aspect ratios are all over the place, which is a good thing, right? So whether you want to do 16 by 9, 9 by 16, 3 by 1, 1 to 3, right? Whatever you want to do. There's so many different, uh, aspect ratios. So here's how it actually works. Well, I think the simplest way to put it, if I had to summarize what this is in 3 words, I would say visual thought part, right? It is like having a super smart designer that you can just give a brief to and then you can walk away and they're gonna do all this research and they're gonna, you know, grab all your data, you know, match everything up. And it is, I think I have felt this a little bit with, you know, the newer versions of Nano Banana, kind of its ability to understand the context, and to ground in real-world search. Like I said, we did get that with Nano Banana, but something about images too. It just feels a little bit better. Uh, the agentic harness, it queries the web, synthesizes data, and then it renders the final pixels. And then you can also, well, treat your prompts as just creative briefs and not necessarily literal visual descriptions. And I think that's huge. And if you have used AI image generators in the past, this one might make sense to you on why this is a big deal. If not, let me explain it to you. Right. Again, let's go back to Midjourney because I think Midjourney was one of the most popular AI image generators, you know, of 2023, 2024, etc. But I think early on, especially in the, you know, the V3, V4 days, I forgot the exact years on that. Right. But you almost had to speak Midjourney to it, right? And I think some of the earlier AI image generators were like that as well. You know, you had to use a certain type of language, you know, you had to describe the focal length of the camera if you really wanted these great, you know, these great photos and say, hey, I want that, you know, soft depth of field with bokeh and, you know, crisp highlights. And like, you really had to almost have a visual mindset to get anything visually great out of it. And this is not the same with images too. You can have some of these simplest prompts that maybe have hardly any creativity in them, yet get outputs that reflect something that would, you think, would require a lot of creativity. So right now, here's how it absolutely crushes all other models, right? We did share this in our newsletter last week, but I think it's worth showing. So, uh, LM Arena does blind, blind tests, right? So you put a prompt for an image in, you get 2 outputs, you vote on which one's better. Nano Banana 2 was great, right? It was a huge jump ahead. Images 2 from OpenAI absolutely crushed not just Nano Banana 2, but every other AI image generator for now, right? I do have to point out, you know, Google's I/O conference is in like 3 weeks. Who knows, maybe we'll see something new from them. Maybe we won't. I actually don't have any inside information on that yet, so I can, I can say that out loud. So right now though, AI moves too fast to follow, but you're expected to keep up. Otherwise, your career or company might lag behind while AI-native competitors leap ahead. But you don't have 10 hours a day to understand it all. That's what I do for you. But after 700+ episodes of Everyday AI, the most common questions I get is, where do I start? That's why we created the Start Here series, an ongoing podcast series of more than a dozen episodes you can listen to in order. It covers the AI basics for beginners and sharpens the skills of AI champions pushing their companies forward. In the ongoing series, we explain complex trends in simple language that you can turn into action. There's 3 ways to jump in. Number 1, go scroll back to the first one in episode 691. Number 2, tap the link in your show notes at any time for the Start Here series, or you can just go to starthereseries.com, which also gives you free access to our inner circle community where you can connect with other business leaders doing the same. The Start Here series will slow down the pace of AI so you can get ahead. The Images 2 inside LM Arena with those blind taste tests. It set absolute records and it wasn't even close, right? So it won 93% of blind comparisons on the LM, on the LM image arena, right? Where normally a leading model might win like head-to-head, it might win like, you know, 60%, maybe 70%, some of the models winning 93%. That means it's, it's almost like an undisputed hands down, right? At least according to, you know, all LM Arena stats so far in the, um, its Elo score, right? So after that voting process, you get an Elo score. Uh, Arena said that it broke the record for the biggest lead ever. And I think this is important because yes, there's other great visual tools out there. And I think one, uh, you, you know, you might be thinking, oh, the new Claude design, right? Claude design's great. Uh, but Images 2 does the things that Claude Design does well, right? It does things like wireframes really well. Claude Design does things like, you know, UI/UX mockups really well. Images 2 probably does better, right? And I think a lot of people, you know, and even how can this play the part of, you know, in my creative process? So if you already are a creator across multiple disciplines, right, I think the rest of the show I'm probably going to more focus on are non-creative people, because if you're a creative person, I think you already see the potential in Images 2 and you're already crushing it, right? But for actual creatives, I think this new outputs from images too serves as a baseline. So using these as, you know, inputs for AI video, right? Whether you're doing that in VO3, SeedDance, whatever, you know, Sora is unfortunately, you know, no more. But starting with these image outputs for videos, I think is a huge level up. And then the same thing starting with this for design. right? I think that's one of the big things that was actually talked about in the release on, you know, yes, GPT-5.5 and Codex and in general, not great at front-end design. So if you're trying to build an app inside Codex or with the GPT-5.5 model, it's well documented and it's definitely true. It's not that great at design by default, but you can use images too, right? So if you're using Codex, I've been doing this all the time. I'll just create a, render of something first with Images 2, and then just say, all right, well, go build this now. Now that you see something that looks good because it has, uh, in its training data, I'm sure has gobbled up every single, uh, you, you know, user interface that's ever won an award, you know, all the most popular ones, the trends. So the, on the images side, because it has that, you know, kind of that world knowledge and it can think about things, it can create great starting points, whether you're bringing something into Claude Design, whether you want to code something, uh, you know, in another platform, it's a great starting point. Even if it's not going to be your endpoint. Also, the type of creative work that this unlocks is a ton. So it collapses research, copywriting, and layout into a single prompt for one operator, right? You can have multiple steps of an output just with one text input that doesn't have to be overly creative or technically specific. You know, product managers, I think this is great. You can describe new features and, you know, into images too, and then give it to Codex and it will write that front end instantly, right? That's something I've been doing. You know, I'll take a screenshot of an older app I've been working on. I'll say, hey, I want this type of feature. Can you render out what it should look like given this is what the app looks like, right? I think that's a great use case. Also marketing teams, right, to localize your master creatives globally without, you know, having to rebuild it or, you know, work with translation vendors. You know, you can literally just upload an image that you've already done. Maybe it's a graphic and have it you know, translate the text and reformat it, right? Maybe it'll be more characters, fewer characters. So maybe you lost the, you know, the Photoshop file or the design file that has all the different layers. Well, it can take care of that for you. You don't have to go in and, you know, get the eraser and, and go to work manually like it's, you know, 2020 anymore. All right, so let's talk about 10 use cases that you can deploy now before we start looking live. So First, product packaging mockups with perfectly spelled nutrition facts and brand logos. Next, UGC-style ad creatives for, you know, TikTok, Meta, whatever, with native text overlays. It's actually really good at that. I was kind of surprised. Next, UI/UX specs that front end— or sorry, that product managers can hand to coding agents for instant code. So if you are working with, you know, product managers and you're trying to describe a design to them, you don't have to necessarily get a designer involved. First, right? So even if you are not the end creative, you know, I had Richard from Google on a couple of months ago. One thing he said that still stuck to me to this day is like demos over memos, right? So think of sometimes you might have to describe something to a creative, right? If you are not the creative on your team, but you're working with someone, it might take a long time, or you might have to bring in a designer just to help you, you know, translate or communicate a message. You know, maybe it's something for, you know, your customers, your clients, whatever it may be. But now you could just use images too for that. Next, instant multilingual localization. That's huge. You can do YouTube thumbnails. It actually does a surprisingly good job at that, you know, creating those, you know, eye-catching, you know, text contracts, text contrast where, you know, jumps off the page and it gets every word right. Next, you know, you can turn internal training visuals that, you know, turn those dense SOPs into scannable job aids, sales one-pagers, another great example with industry-specific mockups. Or, you know, imagine creating, you know, a sales one-pager at scale personalized for, you know, 10 different demographics against, you know, 10 different countries. As an example, if you have one winning creative that has done great for you for customer acquisition or, you know, client success, whatever it may be, imagine being able to localize that and personalize that at scale. You know, boardroom strategy maps that translate written plans or meeting transcripts into executive-ready visual briefings. That's a big one. All right. Next, live data infographics, you know, pulling current competitor stats into ready-to-publish leadership reports. And then, you know, before and after marketing shots showing transformation outcomes for client pitches and proposals. I mean, there's no shortage of use cases, but There's 10, you know, I think regardless of what job you work in, one of those 10 you can literally go try today. Even if you have a free ChatGPT plan, right? You're not going to get all the features of Images 2, but if you have a basic $20 a month ChatGPT plan, you can probably use 2 or 3 of those examples I just gave and instantly grow your business, or at least grow your business opportunities, strengthen your internal or external communication, you know, give your homepage a little pop, whatever it may be. All right. But this is our AI at work on Wednesdays. So let's get live. Let's go demo style. All right. Hopefully this works. I am— oh, there we go. All right. So how did I know I was going to run into some issues? All right. So I am— if you haven't seen— okay. So now we're going to run into some issues here. Let's see. Let's see if we can get this going. All right. I'm actually— if you are watching the video version of this, I'm in San Francisco, not in my normal Chicago home office setup. So, um, did get a new computer as well, so I'm having some issues sharing my screen, but I think I got it there. Let's see. All right, hopefully we have it. Livestream audience, let me know. You see my screen? Hopefully you do. All right, let's get to work, right? What could possibly go wrong, uh, doing live, uh, live demos of generative AI? All right, so I'm going to go ahead and paste in a little prompt here and then I'm going to read it to our audience as it works. So nothing special here. I'm going into ChatGPT. If you haven't seen this, all you're going to do is hit the plus button in the prompt bar. You're going to click the create image. Then there's other options. So, you know, once you do click that create image, you're going to see there's different options for aspect ratio, auto, square, portrait, story, landscape, widescreen, etc. I'm not going to touch anything there because I have designated in the prompt. So I'm just pasting this in, and I am hitting enter, and I'll read it. But for our livestream audience, you'll see this kind of this new animation that I really like. It kind of shows that the model is thinking, right? And you can— it still has the thinking trace that I can go and look and literally read what the model is thinking based on my prompt. So always do that. It's gonna give you better outputs. I know you're probably— if you're a longtime listener of the show, you're probably tired of me saying, like, read the chain of thought. But you absolutely have to read the chain of thought always because models always change. Generative AI is generative, not deterministic. So if something goes wrong, looking at the chain of thought will give you clear insight why. All right. But here's the prompt and it is working. So it's been about 30 seconds so far. So I said, I need a 6-slide presentation context sheet. Create a 16 by 9 image showing 6 polished slide thumbnails for a Fortune 500 leadership briefing called the AI Capability Gap. Right. One of our Start Here series episodes that we did recently. So this is a real use case. Right. And I can maybe go share this in our community based on, you know, what we put together. So I'm decide— I'm just describing the scene backdrop. So I said clean ivory canvas with subtle grid and elegant slide shadows. I said I want 6 distinct 16:9 slide thumbnails arranged 3 across, 2 down, each with unique composition. I said I want this in the style of a premium strategy deck with McKinsey clarity plus magazine editorial punch without copying either. I said composition, all 6 slides are readable. As a contact sheet, not one giant infographic. And then I give it a color palette. I said ivory, charcoal, deep teal, signal red, muted gold. And then I gave these slide tech for each slide, text for each, you know, the gap. AI is ready. Most companies are not, etc., etc. Right. All right. It's already done. So first version. All right. Am I testing the first version of— in my testing turned out a little bit better. This isn't bad. All right. Let me tell you you why I like producing it this way. So I just essentially created a slide deck with very minimal information, right? So it did a pretty good job stylistically, right? But the reason I did all 6 slides on one prompt before I, you know, versus doing them one by one, and I made the prompt this way specifically. So this is a little tip or trick for you is if you are going to create a slide deck in Images 2, you would do, you would probably want to do so one slide at a time. But I like telling it to first, you know, render 3 across, 2 down, so I can see how all of the slides look together. So this is a very minimal, uh, output here. So what I'm going to do now is I'm actually going to open up, uh, I'm opening up in another tab here our episode on this, right? So I'm going to copy and paste all of this back in, and I'm going to say Update it with this content. So I'm going to give it no other— I'm going to say update it with this content, no other feedback. Right. So now I want to see— it did a pretty good— visually it looks good, right? It followed all the directions. It gave me the 6 slides, some of the content that I did give it, you know, kind of as placeholder content. It did a great job, right? It labeled the 6 slides as I wanted to. Number 1, the gap. Number 2, capability. 3, usage. 4, profit. 5 bottleneck and 6 metric, talking about the AI capability gap that we actually tackled on the Start Here series, episode 755. So it did a really good job visually. It's nice, it's clean. I think it lacks a little bit of information, you know. I mean, it's, you know, there's a slide that's just, you know, one bar chart with a label, right? It looks good from a zoomed out version, but I would probably want a little bit more information All right. So I did just— you can't just iterate inside the thread of any conversation. So one thing I've noticed personally about Images 2 that I think is much better than Images 1 and Images 1.5 is its ability to iterate usually does a little bit better because previously iterating within the, the the same kind of context window or the same chat thread, for whatever reason, it was very hard. And if you had something that you liked originally in the first prompt and you were trying to refine just a couple of things, right, let's just say, oh, you know, I want this shirt to be green instead of red, right? Then it might add glasses or it might change, you know, the background completely. So I did— I have noticed that iterating usually does a little bit better. So now in my follow-up here, all it did I just said update it with this context. It didn't actually do much of anything. And I'm wondering if because when I pasted it in, you know, there's this new feature in ChatGPT that says paste as an attachment. So it didn't really add any of this. I'm going to try it again. So I'm going to say update it with this content. I'm going to paste it in and I'm going to make sure it shows as the text field. All right. And then I'm going to say there should be probably at least I'm going to say what I'm going to say, 20 to 50 words per slide. All right. So we'll see if that works. And as we give that a second to cook, I'm going to go ahead, open a new tab, and we're going to start a new example. So that was one slide deck example that I think did a really good job. And a tip as well. I like working instead of one slide at a time. I like working in that 6-slide view or the 9-slide view. I haven't really tested it, you know, how far I can do it with one image. But even the fact that it was able to, within one single image output, it was able to show a 6-slide preview and everything on there is correct, right? It didn't have the amount of information that I wanted, but everything on there was correct. It followed the design brief fairly well. You know, it created images, right? So for the number one, it's about the gaps. Right? So it not only, you know, created the text and the graphics, but it has this nice kind of image of a canyon gap, right, with some dark background and light text on top. So from an aesthetics standpoint, this first— I mean, the first and the second version are really good, right? It didn't do as well as I would have liked on the content side. But like I said, maybe that's— I actually didn't check as much as I should have on how it handles those text as attachments. So we'll see on the on the second iteration here. Let's see if it's done. All right. It's still cooking. So let's go in. Let's do one more. Let's do one more live. So for this one, I'm going to do a UI mockup, right? I'm not going to do all these images, right? I wanted to do something that I thought would be great for the, you know, average business leader, right? The average business leader. You may not be going in here to, you know, play around with photos, right? And to create realistic photos of, you know, a man in his forties walking around downtown Chicago, right? It does very well on that, obviously. But I, I really wanted to get into the, uh, bread and butter of some of the business utility, which I think is just, you know, being able to create decks, being able to create wireframes, being able to create mockups, all of those things. All right. So our second one is this. It is a UI mockup. So I'm describing this by category. I said the as— the asset type, it's a mobile app. App plus desktop dashboard product user interface. And I said create a polished product design mockup showing a retail field operations AI assistant across a phone app and a desktop dashboard. I said I want a clean Studio product UI presentation with a subtle retail operations background. For the subject, I said it should be a phone screen for store managers, a desktop dashboard for regional leaders, and small task cards and exception alerts. The style, I said it should be a premium B2B product with UI, practical and believable, like a serious SaaS launch image. Then the composition framing, I said 16 by 9 with phone on the left, desktop dashboard on the right, connecting workflow cards in between. So I did, you know, I was somewhat specific. I didn't give it the actual data that it needed. All right. And it's already done. So let's take a look here. And in terms of prompt adherence, I mean, this is pretty good, right? I don't necessarily personally like the design, uh, cuz the, the design itself of the, you know, of the user interface to me would not be something I would prefer. But I think that's a preference because I think stylistically it's re— really good. This does have a premium, you know, B2B SaaS feel, right? I, this looks like something, I don't know, that I currently pay for in one of my subscriptions. Like it looks really good, but it has the the StoreOps Assistant mobile app, uh, on the left. It has the pullout of the tasks, uh, kind of displayed, um, in the middle, you know, you know, and it's showing how all of those things make their way over into the desktop app. So in terms of prompt adherence overall, you know, maybe this played it a little safe, but I'm just going to give it now just natural language feedback, right? So I'm going to say, you know, pretty good, but this feels a little, you know, 2000s cheesy. I'm going to say give it a sleeker and more modern, uh, aesthetic. And then I'm going to say, uh, I'm also going to say let's test some of the grounding. I'm going to say, you know, pull, uh, you know, real-world data from a real company or market instead of dummy data, right? So nothing more I love than doing live demos than typing live when my mic's in the way and I got to do my sideways T-Rex arms. All right, let's go back to our first version. So remember, this was the capabilities, the AI capability gap deck in the first iteration did pretty good. But there wasn't a lot of text. So now I'm looking at it and I see, okay, this is good. Now it added, you know, I said there should be about, you know, I think 20 to 50 words per slide. And it looks like we have that. So now what I'm showing on my screen, we have 6 stacks. It followed the color scheme. It's actually really good. I didn't even tell it to rotate, you know, having like every other, right? So, you know, the first slide has more of a darker tone, still following all the guidelines I gave it. The second one is that lighter kind of ivory cream. The third one is dark. So good slide decks do that, right? If you're saying, you know, a consultant company, etc., you know, good ones, they kind of rotate so it doesn't look the same every single. So even though I didn't give it that, that requirement, it did it on its own. And that's one of the, you know, that was one of my points when I started this. I said, even if you are a non-creative person, you are going to be able to get creative outputs. I don't think an output like what I have on my screen now would have been possible with GPT-4. GPT-1, or sorry, GPT Images 1, GPT Images 1.5, but it definitely is in 2. I do think you could probably get something like this in Nano Banana Pro with a very similar prompt, right? But in terms of the output, this is a really good output, right? And then if I wanted to, I could say something. I could say, great, let's design each slot in full one by one, right? So the advantage, right, little tips and tricks of doing it this way, this is also because I I've, you know, been in and out of different types of design for, you know, 20 years just working, you know, small business marketing, et cetera. Right. I know sometimes you want to be able to see that zoomed out view to see how this looks as a whole. Right. And it looks really good. So now I can say, great, let's design each slide in full one by one. All right. And then it's very likely going to go through and do that. But we don't need to wait around and check. So let's go to our UI mockup. And one thing I'm going to pull out here is I told it, I said, pretty good, but it feels a little 2000s cheesy. I said, give it a sleeker and more modern aesthetic. Pull real-world data from a real company or market instead of dummy data. And then if I look on the right-hand side, I can see exactly what it's doing. So kind of it's the steps that it's going through. It says clarifying image with real-world data, deciding on real market data for UI. It says I could use a neutral data like the US grocery region view. Right. So it's going through in its chain of thought like, hey, what kind of data would work well here? It says avoid fabrication while using real stats. All right. Clarifying image creation and sourcing data, editing image with updated modern aesthetic. Here we go. Using real data for dashboard. So it said I found some solid data, but I'll avoid using logos as requested. It says instead I can mention specific specific Walmart stats, like the number of US stores, 4,605, and associates, 1.6 million, along with their net sales of $462.4 billion, right? So it pulled real data from Walmart. It didn't use the Walmart logo, but it does have kind of the Walmart vibes. Okay. So now, you know, when I'm looking at this, the design aesthetic did not improve greatly. It did technically take a step in the better direction. So another thing, if you didn't know, when you are looking at these images kind of in full screen mode, then there's thumbnails on the left. So, you know, I'm looking at the first version now and then the second version. So the second version is definitely a little cleaner overall. It's still the similar aesthetic, but it did make it a little more sleek and a little more modern. And it did pull in actual, you know, data. Right. I'm sure that number of stores in Walmart has changed since, you know, it seems like a new one opens, you know, every day. but great, a great use case and a great example there. All right. So that is a wrap, but I did FYI, y'all, I did put together a nice little guide for you. So let me show everyone quickly what that looks like. So, ah, nothing, nothing, nothing I love than being on a, being on a laptop trying to do these, uh, you know, things where I'm, I'm sharing my screen. Always, always fun. All right. So I did put together a little guide for everyone. Just a PDF. All right. Well, maybe— maybe. All right. You know, I said I did just get a new laptop and apparently I'm not able to yet share that. All right. Here's— here's what I got to do. Thanks. Thanks for sticking with me, everyone. All right. I'm not going to be able to show you the PDF, but regardless, yeah, I got to update my Chrome settings, reset it. I don't know why. Anyways, I put together a simple PDF with, I think, about 8 different examples so you can see exactly what they look like. You can see the prompt that was used. So if you want to try them yourself, including the 2 that I just did, are on there as well. So if you want that document, I will send it to you. Just make sure to go repost this on LinkedIn. All right. So what's my takeaway here as we wrap up today's show? You do not have to be technical or creative to change what your company can do visually, right? So obviously this helps on the marketing side. It helps on the brand messaging side. You can upload, you know, all of your brand guidelines. You can upload, you know, certain photos, certain designs, and iterate off those or have those serve as the base. That's important, right? But I think this is a big step in the direction of democratizing true creativity for even non-creative people. So if you've always had maybe a vision in your head but didn't have the skills, if you work in a large organization and, you know, maybe you're running into constant bottlenecks of getting certain creative approved, right? And maybe, or just to really be able to, you know, flesh your vision out, you know, on paper, on screen, maybe it takes too long with your current setup. I think this is a great way that is instantly not only going to save save people time, right? But it's also going to, I think, change what a lot of companies can do. And yes, you know, this FYI, I'm sure, you know, there's going to be hundreds of, you know, new creative, you know, AI companies that are just using this image, you know, to bring products. So this isn't just with ChatGPT and their images too. I do think this is going to— you're going to start to see this kind of everywhere. So it changes what's possible. And if nothing else, I hope you see from today's demo You just have to start thinking a little differently, right? It doesn't take a lot. You don't have to be an AI image generation expert. You don't have to be a creative person. You don't have to be a marketer. You know, upload things you like, upload examples you like, talk in natural language, see the output, iterate with it in natural language. And like I said, I think it's going to unlock some things that you didn't know were possible. All right. I hope this show was helpful. If you're listening on the podcast, hey, could you take 10 seconds? Make sure you are followed and subscribe to the show. If you could leave a rating, I'd appreciate that as well. And then make sure you go to youreverydayai.com. We're gonna be recapping the highlights from today's show as well as all of the other AI news you need to know to stay ahead. Thanks for tuning in. 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.