Everyday AI Podcast – An AI and ChatGPT Podcast - EP 559: ChatGPT’s Updated Custom GPTs: What’s New and How They Work

Episode Date: July 2, 2025

Wanna hear a lil secret?You (likely) have no clue what custom GPTs are capable of inside of ChatGPT. OpenAI just updated their capabilities, yet no one's talking about it. Why? The original hype and hoopla from their late 2023 launched fizzled and faded away, and now many AI users have written GPTs off. Big mistake. You won't believe what the newly upgraded GPTs are capable of.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:Custom GPTs Launch & Initial ReceptionUpdated OpenAI Custom GPT CapabilitiesExpanded Model Support for Custom GPTsBusiness Applications of Custom GPT UpdatesLive Demo of New Custom GPT FeaturesInsight Synthesizer GPT’s Unique AbilitiesMeeting Actionizer GPT for Business EfficiencyPersonalizing with the Updated GPT ModelsTimestamps:00:00 "Upgraded Custom GPTs Revolution"04:52 GPT Building: Web Access Only06:46 "Podcast Rambling Concerns"09:56 Benefits of Using Custom GPTs13:18 Using Custom GPTs and GPT Store17:16 Simple AI Tool Usage Guide21:32 Custom ChatGPT Limitations Explained25:17 Exploring AI's Efficiency in Tasks27:06 "AI Impact Dashboard for 2025"32:03 GPT-4 vs. GPT-3: Agentic Abilities35:33 Reasoning Models Enhance Meeting Analysis36:53 AI Meeting Summary Features40:40 Personalized NVIDIA Stock Insights42:38 GPT Custom Models: New DevelopmentsKeywords:Custom GPTs, OpenAI updates, Expanded model support, No code creation, Custom actions, GPT store, Enterprise rollout, Recommended model, O3 model, O3 Pro model, GPT-4.5, Data storytelling, AI humanizer, Multimodal capabilities, Sentiment analysis, Thematic clustering, Research analyst, Meeting actionizer, Personalized learning architect, Financial snapshot, Web search, Canvas mode, Python coding, Boolean search, AGSentic reasoning, Chain of thought, Knowledge files, Fine-tuning, Domain expertise, Automated workflows, Generative AI, Creative marketing, Information synthesis, Meeting analysis, Decision automation, Webhooks, APIs, Knowledge tokenization.Send 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 for the last year and a half or so, GPTs from OpenAI have largely been ignored.

So in November of 2023, OpenAI announced their custom GPTs feature, a way that people could go in with no code and essentially create a custom version of their popular chat GPT for themselves and for their specific purposes. And I think at the time it was completely overhyped, number one, but maybe more importantly, the GPTs did not have access to the best that chat GPT had to offer. Couldn't it, you know, really take advantage of all of the tools and modes within chat GPT at the time? That now has changed because OpenAI recently updated custom GPTs. So in today's episode, we're going to be going over not just what's new and how they work, but why it matters for your business and show you some live working examples of what the

upgraded GPTs can do. All right. I hope that sounds exciting to you. It sounds super exciting to me. So welcome to everyday AI. This is your daily live stream podcast and free daily newsletter, helping everyday people like you and me, not just learn what's happening in the world of AI,

but how we can make sense of it, leverage it to grow our companies and our careers. It starts here with the unedited, unscripted, unscripted, lives dream and podcast. But if you really want to take it to the next level, be the smartest person in AI at your company. Our website is your cheat code, your everyday AI.com. So once there, go sign up for that free daily in the newsletter.

If you haven't already, we're going to be recapping the most important insights from today's conversation, but also go listen to now more than 550 back episodes from the smartest people in the world that I've gotten to interview. I steal all their secrets. I give it to you. It's a free generative AI university. Go check it out. If you're looking for the AI news, we're going to be dropping that in the newsletter.

Also, let me know, should we do a part two next week? So listen to the rest of this episode, and I swear this time it's actually going to be a little faster. And if you want more, going over some more advanced elements of custom GBTs, such as actions, context stacking, and building specifically for the 03 model, which is what's new, let me know on the live stream, maybe just type in the word advanced, or if you're a podcast listener, I always put my email in there or just reply today's to today's email and just say advance. I just want to know, you know, I can only make this thing better if you tell me what you

want or what you don't want. And what this is, this is our new weekly segment on Wednesdays called putting AI to work on Wednesday. So we're going over, like I said, the new update, The biggest one inside the custom GPTs is the ability to use Open AI's newest and the latest model, not just their 03 model, but all the other thinking and reasonings and some other kind of variations of the GPT series as well. So you know what? Yeah. All right. Let's first go over kind of what's new. Then we're going to jump over, start some things live.

Yeah, you got to love doing live demos. Nothing ever goes wrong when working with generative AI. All right. So here is what's new in custom GPTs. So this is from OpenAI's website, but it is expanded model support for custom GPTs. So creators can now choose from the full set of chat GPT models, GPT 40, 03, 04 mini, and more when building custom GPTs, making it easier to fine-tune performance for different tasks, industries, and workflows. creators can also set a recommended model to guide users. So when they say creators and users,

if you're just building it for yourself, you are the creator and the user. But if you didn't know, GPTs, there's also like a store element. So you can just put it out there to the open public. You could, in theory, keep it as a private URL and sell access to it. So there's some different things you can do.

So some key details, and this is from OpenAI's kind of help docs. So GPTs with custom actions can use the model picker to select from all models, or sorry, without custom actions. You can use any model. If you do use custom actions, and let me know, like I said, having the word advance, if you want to go over that next week, this is where you can use things like web hooks, APIs, et cetera.

But if you are using that, it can only use the GPT40 or the 4-1 model. And right now, building GPT, is still limited to only paid users on the web. So even paid users on desktop cannot build GBT's in the enterprise and EDU. Rollout is coming soon for the extended model support. So right now, even if you're on an enterprise or EDU account, you can still build GPs, but you can't use the new O-Series models, right? That's the biggest one.

And I do suppose there is the GBT 4.5 model as well that you couldn't build with previously. All right. So let's just jump and do this live. And as an FYI, y'all, we did about two weeks ago go over the difference between custom GPTs, which is what we're talking about now, Google gems and also projects inside of Chad GBT and Anthropics. So if you do want to listen to that one, I recommend going there to episode 549. All right. So go listen to 549 if you are interested in that. But let's just start live. So we're kind of starting at the end.

All right. So I have a series of GPTs that I built here on my screen. So for our live stream audience, I already have, these aren't like long prompts. They're like a sentence, right? Because actually the power of these is in the custom instructions that I've already built. So I'll actually probably open a new one here and jump to it later. All right. But for each of these custom GPTs, I'm going to be using the new O3 model.

I could use the O3 Pro model. I think it'll actually just take too long. And I swear every time I'm like, I'll do this podcast in 30 minutes. And then it ends up being 50 minutes. And people are like, this guy should stop rambling. So I would have to ramble more. So we're just going to do the O3. And you'll see in my settings at least,

I did say that's the preferred model. So if I end up sharing this with anyone, I don't know. If you want any of these, just I don't know. Leave the comment on the one that you want and I'll send it to you. All right. So I'll show you after I'm done how to build these. Right. But right now I want to get these different GPTs started.

They're probably not all going to work. I'm not going to say I've one shot of these, but these aren't exactly my finest GPT creations. But I wanted to try some things that I thought be useful for everyday business leaders such as yourself. So the first one is called Insights Synthesizer. Okay. So this GPT acts as an instant research analyst and the user.

So me in this case provide a topic and it executes a structured multi-source web search for the most recent and relevant information for the topic that I put in. It will then digest everything performing a sentiment analysis and thematic clustering. and renders a professional one-page dashboard in chat chvety canvas mode. All right. So let's go ahead. Actually, you know what? I'm going to go ahead and get all of these started.

All right. So live stream audience, don't worry. I'm going to come back to these and explain what I'm doing. But I'm doing these live. They're probably going to break. There's going to be some issues. I've already, I did just run them once before. They all worked the first time, which you meet.

Like if you've ever done a demo, if you do it once. And it works and then you go do it live in front of a bunch of people. Or in my case, you know, at least thousands of people on the, on the podcast. It's going to break. It's not going to work. But that's fine. That's why I do these things unedited, unscripted. So you can see how AI actually works because generative AI is generative.

You get something different every time. All right. So the next one is data storyteller. And I already have my short little prompt in there as well as a spreadsheet that I'm uploading. So GPs are multimodal. All right. I'm going to the next one, which is meeting actionizer.

And I'm really excited about this one. I'm actually, I'm like, why didn't I build this one before? I'm going to be using this a lot. So I have a short prompt as well as a meeting transcript. All right. Then I have the investor snapshot. I have a short little prompt here. I'm hitting enter.

And then I have the personal, the personalized learning architect. I'm hitting enter. All right. So hopefully that shouldn't. take too long. All right. So now I want to jump back into the kind of edit mode in a GBT. Well, actually, no. Before before I even do that, let's just go ahead. Give me, give me a second here. I'm just going to bring up the actual like GPT interface. All right. So this makes makes a little bit of sense. So there's different ways that you can use GPTs. Okay. And in short,

they are a smaller customized version of the main model. And you might be wondering like, okay, why would I ever need a GPT? Why wouldn't I just use the main model? Well, there's a lot of reasons. One, it's saving time, right? Think sometimes, you know, if you've ever been through our prime prompt polished PPP course, you know, you know, you might spend 20 or 30 minutes just getting one chat to work exactly how you might want it.

Right. And then there are some things, you know, without getting too technical, like context window, you know, memory, some new things from chat GPT that impact this behavior. That, you know, it might just make more sense to use a GPT. So number one is going to save you time.

Number two, there's actually some, some additional functionality. And the biggest one is, is you can just click the ad button when you are, are using a normal chat. All right. So let me go back.

I'm just going to open another window here. So if I open a new chat and I'm just going to click the ad button. Okay. So when I do that, I can bring up my recent GBT's. So you can be having a conversation or you could use as an example, deep research and then you could transition right away and start using GPTs. So especially when you think. of your work and think of you probably do a lot of the same things over and over.

And it could be very repetitive. It might be mundane. It might not be, but most of the work that a lot of us do, it is repetitive knowledge work. Right. We're working with documents. We're creating content. Uh, we're, we're summarizing. We're researching.

We're synthesizing and personalizing information that we've ingested all of these things, not just chat GPT can do, but custom GPs can do as well. So using these different GPTs and then mentioning them at different points of your kind of chat with chat GPT by using the ad mention is a huge time saver. So let's just say you have five key tasks that you do pretty much on an ongoing basis or there's a three hour project that you do once a week. Maybe it's a little bit of researching. It's uploading an old document. you know, so you're researching, you know, new laws, new updates, new industry trends. You're in, then you're, you know, updating the old document.

Then maybe you're building some sort of dashboard, right? Those four different steps right there. Those could all just be GBTs. So you don't have to sit there and reprompt each time and try to get it just right. Right. So you can get it right just once. Save that as a GPT. And then at mention each of those GVTs.

And then when I'm done, so as an example on my screen here, I just clicked Investors snapshot, you know, I can put in whatever prompt, hit enter. It's going to go through in whatever custom instructions and knowledge that I have saved in there. It's essentially a literal custom version of chat chbt. It's going to spit out the result, whatever I have programmed it to give me as a result. And then I can go on X out of that GPT. And then I can click the next one and keep going.

Right. So it's an easy way to work with multiple smaller, specific custom versions of chat chvety using the same context window. All right. So let's go back in and talk a little bit about the different ways to use GPTs. So one is building your own, which I'm going to show you here in a second. But the other one is there's a GBT store. So if you literally just go to your chat GBT account, even on a free account, you can use

GPTs, but you have to be on a paid account to actually build them. So you can share them with your. team. You can share them across accounts, right? That's something I do all the time. I have like, I don't know, I lost track eight paid accounts or something like that for Chad GBT. We do a lot of consulting work for other companies. So we have accounts for them. But I think even for everyday AI, I think I have like three or four different accounts. You know, I have a pro account, a team account, a plus account, et cetera. Right. So you can share your GPTs across different accounts, but you can also go to this GPD store. Right. So there's like, it's like an app store. So

There's top picks. There's categories, writing, productivity, research analysis, education, et cetera. So as an example, I'm going to use a writing one because I'm hoping that they will have updated their GPDs on the back end. So I'm going to go to this one that says AI humanizer. All right. So essentially you put in some text and it makes it sound less robotic and more like a human. All right, I'm going to click Start Chat. So again, it's as simple as that using a GBT.

There's a store. You go in there. It's done. So any old GPTs, whether there are GPTs that you made or someone else made and put them in the GPT store, they can be upgraded and use the latest models. It's a one-click thing in the settings. That's the good thing. You don't have to rebuild it if you built it in November 2023 when GPTs first came out and you're like, ah, these aren't that great. And it's been sitting there.

Well, you can just go in there and change the model. So all you have to do is click. So in this case, I'm clicking the AI humanizer, humanizer kind of drop-down. menu in the upper left hand corner of chat gpt i can hover over model so yeah this one did not update their settings yet but it's super simple to do all right so then i can go in here and use any gpt in the gpt store all right but i wanted to show you all real quick there we go uh kind of the basics of how these are built all right so i'm going to go in and edit this gpt so this is the insight synthesizer all right and i'm just got a quick uh live stream audience

Don't worry if you're seeing a bunch of things flash on my screen here. I'm actually just going to go through each one of these. If they are done, I'm just going to say make it prettier and more useful. All right. If any of these GPs are already done. It's something I always tell people, never use the first version of something. And in case any of them are broken, I just got to fix them. Otherwise, the latter half of this podcast probably won't make too much sense.

All right. So bear with me, live stream audience. You get a little preview on if things are working or not. All right. I'm just going to go in and drop for ones that are working. I'm dropping in my, you know, make it prettier, make it work better. Some of these, it looks like, have some bugs because I'm using some coding in here. Good thing is, while I'm using Canvas mode,

there's a thing that just you can click that says fix bugs. So we'll see how many of these actually, actually work. Like I said, doing it on the first shot. It can be hit or miss. All right. I'm just going in here. Looks like most of these. I had five of them.

I think four of them used canvas. And I think only one of them did work on the first try. So not bad. All right. So going back into our GBTs and how you can create them. So there's different ways. So it's simple. Don't think you need to be technical.

You don't need to know a lot about prompt engineering or coding or anything else. You can literally just chat like you would with chat GPT and say, I'm trying to build a GPT that does blank and it will go ahead and build it for you. So you can build it in a chat interface, which is kind of meta. Or you can go, if you're a little more advanced, you can go into the configure section. So your screen is split in two. And the left side, that's where you build it. In the right side, it renders the preview anytime you make a new update or a new change.

So essentially, anything that the GPT bot builds for you automatically goes into the configure tab. For me, I've obviously built a lot of these. So I like to build them by hand in the configure tab. So I can type what goes in the instructions manually because you have a little bit more control. All right. So here's kind of the description. of what's new. So now I'm in the configure tab again inside the GPT builder.

So you can give it a name, give it a description, and then here's the important part. This is the instructions. All right. I'll quickly show my instructions on the screen. I do this a lot, guys. Don't worry. It looks, well, all right, this one is a little crazy, right? I may or may not have spent way too many hours putting these GPs together because I

wanted to show you guys some impressive. things, right? So I have a lot of custom instructions in here, which probably looks like gibberish, maybe to some people, but it's actually not that crazy, all right? Or at least not compared to things that I built in the past. All right, so I have some custom instructions in here. You can add conversation starters, and those essentially appear then as little buttons that you can click and get a conversation started. For me, the way that these are built, they're all very specific. So I don't necessarily want a conversational starter. And you'll see as I describe what I put into each of these five GPTs. You can also upload knowledge files, which I didn't do. All right,

and I did that kind of intentionally because I wanted to ensure on a quick demo that this worked. However, you will see that I did upload files on the front end. All right. And it's kind of, again, built to do that. And here is the big new thing here, the recommended. model. So on the front end, users or creators, right, can choose which one, but you can also recommend a model. So whether that's using it for yourself, your team internally, right, if you have an enterprise plan, if you have a chat GPT teams account. And if you do, by the way, reach out to us. That's one of the things that we do is we train teams on the right way to use chat GPT enterprise and chat chbt teams. I don't know many people who spend more time in

chat GPT than myself, you know, yeah. So just trust me, reach out to us. And then you can toggle capabilities on and off. So those different capabilities are web search, Canvas, which is essentially a way to render Python HTML and React inside chat GPT in the Canvas mode, 4-0 Image Generation, and then code, interpreter, and data analysis. And then there's a section that says, create new action. So this is actions. So like I said, if you want, uh, not just actions,

but a couple of other things. Uh, if you want kind of in advance, uh, version of this next Wednesday, just type advanced. And if you don't, that's fine. All right. And that's really it. Right. So just in that, you know, three, five minutes of me talking. I gave you a way that you can essentially create your own version of chat. GBT, uh, right. The crazy thing is. I think a lot of companies in, you know, 20, 21, 2022 spent millions of dollars before all of this, you know, nice no code technology was out, creating essentially this, right? Literally, countless companies spent millions of dollars to create this, right? Essentially, a version of chat GPT that was kind of fine-tuned for their purposes and that worked with their

data. Granted, you know, if, if you're thinking that you're going to upload, you know, a hundred files in this knowledge, it doesn't really work like that. Also, keep in mind the context window in the retrieval mechanisms that GPT use, that GPs use without getting too technical, they're a little haphazard in the way that they tokenize. All right, but that's, that's more for our advanced users. So it's not like you can go in here and upload, you know, 50 files or anything like that. I would say you start to see kind of degraded quality, usually after like 10 files, depending on how large those files are, although you can push it for a little bit more. And that's it, right?

So now, you know, in this insight synthesizer, I can go in and use it at any time, whether in a new chat by hitting the at button and starting to type it, or by going into the GPT section and clicking on it and working on it in GPT mode. All right. So let's quickly wrap up why these updates matter. Number one, better guidance. So all the different models, whether you're talking about GPT 4.5, that has a very high EQ, you know, 4-0, which is a fast workhorse, you can go all the way up to 03 pro in your

GPTs, right? So now you can really control. And even internally, you might build some that use 03 Pro. You might build some that use 04 mini high, which is a thinking in a reasoning model that's a little faster. Right. So all of these different models from OpenAI excel at different things. So now that you can use these multiple models, it really does change what companies can do internally just with chat GPT. Also, the domain expertise.

All right. I think now that you can use these reasoning models that are agentic in nature. That's the key thing is you can use, if you look at the O3 model, you can use everything that that model can do. That model can research. It can agentically decide when it uses certain tools. So it might start researching, then it might start writing some Python to try to solve your query.

And then halfway through writing Python, it might go look at your knowledge docs that you uploaded. Then it might go research again. Then it might go write. a little bit more code, right? So it is agenic in nature, especially 03. I think 03 is one of the more impressive models I've ever used right up there with Gemini 2.5 Pro.

So that's the key thing is, you know, before nothing wrong with, you know, Open AI's workhorse GPT40 model. But the gap in terms of what these things can accomplish, what a GPT can actually do with a GPT40, a non-reasoning model in the O3, it's night and day. in terms of capabilities. And the biggest thing is now there's no more model limits, right? Because you're not just stuck with GPT40. That's why, if I'm being honest,

I haven't used GPTs a ton over the past year, especially not over the past six months until this update, mainly because I'm constantly working with these reasoning models and we were able to use them inside of projects. Although, like I said, go listen to episode 549. there are some key benefits to GBT's that projects don't have. All right. So, Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience.

Meet Firefly AI Assistant now live in the Adobe Firefly app, the all in one creative AI studio. Powered by Adobe's Creative Agent, Firefly AI Assistant lets you start with your vision, just describe what you want, and shape the outcome as it. takes form with the assistant. The assistant orchestrates multi-step workflows, drawing on 60-plus pro-grade tools across Adobe Creative Cloud apps, including Photoshop, Illustrator, Premiere, Lightroom Express, and more to help bring your ideas to life. You can also get started with 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. Let's get back. We're going to wrap this puppy up. Well, after we look at what was actually produced.

All right. So the first one, Insight Synthesizer. So let me first tell you, uh, what these different GPTs do. And then we're going to look at the results on what they did. And hopefully we'll see in all of these GPTs were created specifically with the O3 model in mind to show off what they're capable of. So even if you can't envision yourself taking advantage of these exact GPTs or the simple

prompts that I use, think outside of the box and think what are those repetitive knowledge work tasks that you do over and over. And when you think about it, if you're honest with yourself, and I will argue, AI is better than you at those individual tasks, right? You the human, you the expert, you're still needed, right, to on the front end, the back end, human in the loop, putting these pieces together. But if I'm being honest, right, I spend so much of my time just orchestrating large language models, right? I'm not going to pretend that I can research better than Gemini. I'm not going to pretend that I can write code better than Claude, right?

I'm not going to pretend that I can synthesize information better than chat chb t. I can't, right? So again, think where you spend your most manual time. And then what if you had a small version of custom or, you know, a custom version of chat chavit that could do that one thing very, very well. So insight, synthesizer. This, oh, I think I did already read this, but let me reread it. This GPT acts as an instant research analyst. You provide a topic and it executes a structured multi-source web search

for the most recent and relevant information. It then digest everything performing a sentiment analysis and thematic clustering and renders a professional one-page dashboard in Chad GPT's Canvas mode. So my prompt, very simple. I said generate an insight synthesis. this dashboard on the topic, the impact of generative AI on the creative marketing profession in June 2025. So very specific. And I said, make it pretty. And the info should be specific. And then I just did my, you know, I announced it for our podcast audience halfway through anyone that was done. I just said, make it prettier and more useful. Right. I always like to do that just to see what it's going to come up with. All right. So when we look at what was created here, not pretty

necessarily. But I did, FYI. I was very strict in my custom instructions in terms of instructing it what to code and what not to. So I knew that I wouldn't get the most beautiful thing, but I sacrificed this working on a live demo to make it not look that great. We could obviously make it look better, but that's not the point here. All right. So what we got here, we got a nice little quadrant that actually, I mean, it looks fine. It's, you know, plain HTML. nothing exciting, nothing that looks great. But we have an executive summary. And I do want to see.

So it says generative AI solidified its role in creative marketing in June 2025. Brands like Adobe rolled out tools that optimize visibility across AI interfaces, broadcasters like Channel 4 began serving fully generated AI ads and CMOs at Cns, lines, reported workflow efficiencies and deeper personalization. This is all, this is good. This is interesting. So then we have a sentiment analysis. It says 80% of the news was positive, 20% was negative.

We have some key themes here. And then we have some sources that we can click on. So overall, looks like it did pretty good. And I can go check to see exactly what it did by clicking the thought section on the left hand side of this GPT. So you'll see here, it broke the task down into multiple parts. It first started by searching the web. It reflected on what it found.

realized it needed to go search a little bit more. It did it again. Search a little bit more. It was, look at this. It was doing some advanced Boolean search, which is pretty cool. It was searching for file type PDFs with the word generative AI in creative marketing, which is pretty cool. It was specifically searching for PDFs, probably to find more in-depth, like, white papers

or something like that. So very cool. It's going down there. Then it starts analyzing code. Then it reflects on everything. analyzes, creates more code. So you'll see here this agentic step that the O3 model goes through. You couldn't do a third of this with the old GPTs when they were using GPT-40.

So you'll see here it actually does a very good job going through. And then we get a dashboard, although the dashboard's not super pretty, but that's fine. All right, let's look at the next one. Let's see if it actually worked. We'll see. Got a little error message. but all right, looks like it worked. Cool.

So, and again, if you want to use any of these, just drop the name of it in the comments. I'll send it to you. All right. So this one is the data storyteller. All right. So this is a GBT that transforms raw spreadsheet data into a clear, compelling narrative.

So you upload your data and it automatically cleans it, identifies the most important trends, and generates a 10 slide data. story in canvas mode, complete with, well, we'll see if it worked, complete with charts in bullet point in bullet point insights. So all I did for this one, and you'll see if live stream audience, you can see the amount of data that I uploaded here. Pretty, pretty decent amount of data. It looks like 500. I uploaded podcast episodes. So 500 and it looks like 10. So at least, you know, 5,000 rows of data here. And I just said, here's our podcast data.

What are the most important trends here? Be specific and unearth the most valuable insights, not topical in obvious findings, right? The rest of the instructions on how it could complete this were obviously in the custom, in the custom instructions inside GPD. But you'll see here, I got like the world's most basic, like slide show, but it's not bad. All right. So on the right hand side here, I got a little slide show that I can flip through. It looks like a very basic like PowerPoint deck.

But again, I did this with, I didn't do anything. Right. So again, going through here. And again, I'm calling this out because I want you to see and understand for a podcast audience, the big difference here in the GPTs that you didn't have in GPT4. Number one, obviously the quality in what the O3 model can do. But why I built these the way I did, which was a little intense. was to specifically show you its agentic abilities, right?

The O3 model from OpenAI and Gemini 2.5 from Google, they are agentic in how they work because they make decisions on their own. So in this case, it started by writing code, right? So it started writing code immediately. I don't think I had it research anything. We'll see if it ended up researching anything. It looks like it just wrote a lot of code with Python. It thought about it.

analyzed it, et cetera, et cetera. Did. Created a chart down there. Cool. We'll see if that shows up. So pretty good. So we have a 10 slide. So it says podcast audience explosion.

Downloads are up 152%. It's actually a nice little like animation, right? Not bad. So I did see our chart was in the chain of thought, right? So when I went and clicked on in, And when I'm reading all of these things, y'all, it's on the left-hand side. It should say, like, thought four and then a number of minutes and seconds. That's the chain of thought that I'm reading.

And I'm kind of saying like, oh, it's agentic in nature because A, B, and C, that's because that's what I'm reading. It's the chain of thought here. So I did see that it created an image, but it unfortunately did not insert that image into the slide, kind of this slideshow. It looks like it tried to, but it failed. But let's see. It gave me some median downloads in that chart that didn't work.

some key takeaways. Okay. Pretty, yeah, pretty decent stuff here. Okay, this is interesting. I didn't know this, but it said the single biggest leap occurred between quarter four, 2024 and quarter one, 2025, an 86% growth quarter to quarter,

which I didn't necessarily know. But that's cool. So some key takeaways here. Some trend deep dives. Again, just going over my podcast data, segment breakdown. It said Friday releases outperform Monday drops by 20%. Ha!

Didn't know that. Also, it said episodes featuring the term AI agents pull a median of 6,300 downloads, 67% above the series average. Drivers of change. So it's telling me some things that are helpful. Benchmark comparison. Future outlook. Cool.

and then some strategic recommendations. All right. All right. I like this. And then an appendix and methodology. Cool. All right. Let's look at our other GBTs.

See if they worked or if they failed. This is the one I was excited about. All right. It looks like this one worked. Sweet. So this is the meeting actionizer. And this is something. I'm like, why haven't I just built this before?

Right? There's so many AI tools and I have them all. Right. And it gives you a summary. This person said this. Here's the to do. Sentiment analysis. Blah, blah, blah, blah.

Right. Sure. Cool. But none of them use reasoning models. Right. So all it does, you know, yes, the transformer models, GPT4, you know, they do a good job. But when you can apply a reasoning model to a meeting transcript, it picks up, it picks up so much more nuance.

Not only that, what I did here, and again, all this prompt was, I said, generate the meeting hub. That's what I called it. Make it useful and pretty. It wasn't really pretty. Again, I was very restrictive in the code that it could write inside canvas mode, so it would hopefully render and I wouldn't get a bunch of bucks because, you know, the more sleek and modern and bells and whistles you throw inside while trying to render

this code, the more likely it is to fail. But what looks looks like what did happen. Let's see. All right. So again, I'm looking at the chain of thought and it's just kind of reading through. Yeah, here we go. Here we go. This is what I wanted.

Right. So I had this. And the instructions on this one were a little intense. But I essentially said, yo, like, yeah, go do the normal meeting analyzer stuff. You know, fine. Give me an executive summary, which we have here on the stream. Give me decisions and action items that were discussed. Okay.

There we go. This was an internal meeting of ours, of our team from a year ago, talking about some different ad strategies. We were just testing a couple of things out. So nothing crazy, right? But what's cool here is the things that we talked about in this meeting that we're like, oh, yeah, we should look into A, B, and C. Let's go, you know, hey, next week when we meet, let's research this and talk about it and come to some conclusions and come up with some. It went and did this. So this GPT, because it's using O3, so it went and did the normal, you know,

AI meeting transcript stuff, right, gave me, you know, an executive summary, decisions and action items, key decisions, dates, charts, all that stuff. It gave me a discussion, mind map. But here's the goal, y'all. I should probably just build this. Should I just quit everyday AI and just build this thing? it probably make a trillion dollars because this is what people want it actually went out and did all of the work that we talked about it went out in researched it so you'll see here you know

it's in the middle of this it's going out and it's searching the web all right it's talking about things that our team was talking about uh it went out uh it made kind of like hey here's the to do's and then it went out and it just went and did the two do's and it's recommending things so uh that was called the research brief and it already provided potential solutions that are actionable. They're up to date because I did that in the custom instructions. I made sure and it's really good. Like I'm looking back, this meeting was like a year ago and I'm looking back at some of the recommendations and I'm like, yep, that's that's what we came to.

So very cool. Ah man, anyone else feeling this one? This one's called meeting the meeting action. Oh, I love that one. I'm going to go, I'm going to make this one a lot better. And I'm probably going to duplicate it inside Google gems and duplicate it inside of Claude, inside of Claude project and using artifacts as well. I can't wait to see.

And I'm going to spend some time on this one. I think it's going to be really good because everyone hates meetings. And then it's like, all right, you like, everyone has to do the same thing. And like, I have all the AI meeting tools and they provide me summaries and all this. but then I still have to go out and do all these things. I would love for this GBT to just start the process for me. And then I just make the decision. And, you know, I can keep chatting with it from here.

That's the other great thing. All right. We're going to go over the last ones really quick. Because once again, we're already at the 39 minute mark. I should stop geeking out about this. Do I need to make these podcasts shorter? Are you guys not hate geeking out? If you do, that's fine.

All right. So this one is the investor snapshot. Here's what this one does. It generates a one page financial and news snapshot for any public company. It browses for the latest financial data and news then renders a concise briefing report in canvas mode. All right. So all I did for this one, I said, give me an investor snapshot for NVIDIA, make it pretty and ultra detailed and recent. It didn't make it pretty. I did save the one I did earlier because I thought it looked like. way better. You know, this one at least made it a little prettier, right? We got the Nvidia green and in all that, right? So, but overall, this is really good, right? This is something I can imagine. You either have to have, you either spend a lot of time to put these type of charts and data together or you just pay for a service that does this.

So is this going to be as robust as, you know, like, I don't know what people use the Bloomberg terminal or no, absolutely not, right? But you can, with this GPT, any company that you care about, and you can tweak this and personalize it and make it your own. You know, I got the current price, the 52 week range, market cap, PE ratio, revenue growth year every year, dividend yield, shares outstanding, all for NVIDIA very quickly. And then I got the latest news, like up to like yesterday. This is news, you know, this isn't from, you know, months ago, but it's also giving me things over the last week or so, right? So it said, NVIDIA could be days away from a $4 trillion valuation. Oh, weird.

I told you guys that like two and a half years ago. So another great GPT that shows the utility and the power of the O3 model. All right. And then last but not least, this one is the personalized learning architect. So this one creates a custom week by week learning plan on any topic. It researches the best resources online and presents a structured syllabus as a clean professional web page and canvas mode. All right.

And all I did here, this prompt was a little bit longer, but nothing crazy. I said, create a four-week learning plan for a beginner to learn Python for data analysis. And here, I really wanted to test the personalization. I said, I don't know much about Python, but I'm a big AI enthusiast. So I understand it's importance. I'm also a basketball fan. If you need to make any analogies, make it pretty. All right.

So here we go. It has a learning plan, Python for data analysis. four week plan. It has four different modules. And then it has, you know, it kind of explains them a little bit, explains the key concepts with a basketball twist. So pretty cool. Then there's some resources over there on the right side.

I can click on them and it brings them up. And they all work. There we go. Very cool. All right. So that, y'all, is a wrap. Anyone else really freaking impressed? I am, right?

So yes, we did cover these GBT's a little bit in episode 549, but I think they're actually this impactful that they deserve their own episode. So, again, if you do want that advanced show, just type advance, but I just really want to quickly recap everything. So what's new is you only before could use the GBT40 model inside custom GBTs, right? So if you wanted to make your own custom. version of chat gbt upload your data your own custom instructions and then use it in a lot of different places inside the chat gpte ecosystem before you could only use the gpt 40 model which was

fine but you know when we had access to these other models it felt like gpts uh were just kind of neglected for almost a year or longer that has completely changed here's why it matters for your business because now as you saw as an example in that uh meeting actionizer. Now you can combine your company's data, the ability for a thinking and reasoning model to go make decisions and to perform actions and to personalize it all for you and also to automate it. You can now, as a business owner, as a business leader, you can now start to automate huge chunks of your company with GPs and keeping it all in the same context window, which is something we can go over in the advanced mode.

the live working examples, I showed you all that. And hey, not too bad, 43 minutes, we've done worse. All right. I hope this was helpful. If you're liking these AI at work Wednesdays, let me know. Or give me an idea. What should we do next? I'll probably put that in the newsletters today to ask you all what we should do next,

maybe after part two, if we're going to do a part two of these. So I hope this was helpful. If so, if you're listed on the podcast, please subscribe and follow the show, tell a friend about it. If you're listening on the live stream, please click that repost button. You know what? If you click the repost button, I'll just send you all these GVTs. I'll just put them in a dock for you.

And you can go play with them yourselves, right? I spend so much time doing this. Y'all, it means a ton to me. Anytime you go repost the show, tell your friends about it, email your brothers, mothers, which is your mother's, your brothers, mothers, best friends, babysitters, teacher, and say, hey, this is helpful. I'd appreciate that. I'd also appreciate you going to Your Everyday AI.com.

I'm signing out for the free day on the newsletter. See you tomorrow and every day. 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, Premiere Express, and more in one conversational interface. You direct the outcome while the assistant accelerates execution, Stay in 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.

For a little more AI magic, visit Your EverydayAI.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.