EP 559: ChatGPT’s Updated Custom GPTs: What’s New and How They Work
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This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. 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 GPT's 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 ChatGPT had to offer. It couldn't really take advantage of all of the tools and modes within ChatGPT 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.

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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 O3 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 to today's email and just say advance. I just want to know, I can only make this thing better if you tell me what you want or what you don't want. This

This is our new weekly segment on Wednesdays called Putting AI to Work on Wednesdays. So we're going over, like I said, the new update, the biggest one inside the custom GPTs is the ability to use OpenAI's newest and 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, right? 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 advanced, if you want to go over that next week, this is where you can, you know, use things like web hooks, APIs, et cetera. But if you are using that, it can only use the GPT-4.0 or the 4.1 model.

And right now, building GPTs is still limited to only paid users on the web. So even paid users on desktop cannot build GPTs in the enterprise and EDU. Rollout is coming soon for the extended version.

model support. So right now, even if you're on an enterprise or edu account, you can still build gpt's but you can't use the new series models, right? That's the biggest one. And I do suppose there is the gpt 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 GPT and Anthropic. 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

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 model.

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 of the, or comment on the one that you want and I'll send it to you. All right. So, uh,

I'll show you after I'm done how to build these. 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 one-shotted these, but these aren't exactly my finest GPT creations. But I wanted to try some things that I thought would be useful for everyday business leaders such as yourself. So the first one,

It's 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 ChatGPT Canvas mode.

All right. So, uh, let's go ahead. Actually, you know what? Uh, 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, uh, 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 you. 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 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, it's 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 GPTs 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 gonna 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 GPT. 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.

Right. Think sometimes, you know, if you've ever been through our prime prompt polish PPP course, you know, you, 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, right?

that it might just make more sense to use a GPT. So number one, it's gonna save you time. Number two, there's actually some additional functionality. And the biggest one is, is you can just click the add button when you are using a normal chat. All right, so let me go back. I'm just gonna open another window here. So if I open a new chat window,

And I'm just going to click the add button. Okay. So when I do that,

I can bring up my recent GPTs. 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 processing.

work, right? We're working with documents, we're creating content, 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 GPTs 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 app mention is a huge time saver, right? 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, so you're researching new laws, new updates, new industry trends. You're

Then you're 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 GPTs. 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 GPTs. And then when I'm done, so as an example on my screen here, I just clicked investor snapshot. I can put in whatever prompt.

Hit enter. It's going to go through and whatever custom instructions and knowledge that I have saved in there, it's essentially a literal custom version of ChatGPT. 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 ChatGPT 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 GPT store. So if you literally just go to your chat GPT 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 GPT. 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 uh etc right so um you can share your gpts across different accounts but you can also go to this gpt store right so there's a like it's like an app store so there's top picks there's categories writing productivity research analysis education uh etc so um as an example i'm going to use a writing one because i'm hoping that they will have updated their gpts on the back end so i'm going to go to this one that says uh

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 GPT. There's a store you go in there. It's done. So any old GPTs, whether they're 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, you know, 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, uh, humanizer, uh, kind of dropdown 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. 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 going to quick 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 fast.

prettier and more useful. All right. If, if any of these GPTs 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 this, uh, the latter half of this podcast probably won't make too much sense. All right. So bear with me, uh, live stream audience. You get a little preview on if things are working or not. All

All right, I'm just gonna 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 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. And the right side, it renders the preview anytime you make a new update or a new change.

So essentially anything that you, 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 GPTs 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 GPT's you can also upload and

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 models.

So on the front end, users or creators can choose which one, but you can also recommend a model. So whether that's using it for yourself, your team internally, if you have an enterprise plan, if you have a ChatGPT 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 ChatGPT Enterprise and ChatGPT 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 ChatGPT 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 actions. So this is actions. So like I said, if you want not just actions, but a couple of other things, if you want kind of in advance actions,

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 GPT, right? The crazy thing is,

I think a lot of companies in 2021, 2022 spent millions of dollars before all of this 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 ChatGPT that was kind of fine-tuned for their purposes and that worked with their data.

Granted, you know, if you're thinking that you're going to upload, you know, 100 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 GPTs 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. Um, I would say you start to see, uh, kind of a degraded quality, uh,

usually after like 10 files, depending on how large those files are. Although you can, you know, 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 add 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 O3 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 uh 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 agentic in nature, especially O3. I think O3 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 GPT-4-0 model, but the gap in terms of what these things can accomplish, what a GPT can actually do with a GPT-4-0, 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 GPT-4.0. 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 if you

Like I said, go listen to episode 549. There's some key benefits to GBTs that projects don't have. All right. So are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Gen AI. Hey, this is Jordan Wilson, host of this very podcast.

Companies like Adobe, Microsoft, and NVIDIA have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for chat GPT training for thousands,

or just need help building your front-end AI strategy, you can partner with us too, just like some of the biggest companies in the world do. Go to youreverydayai.com slash partner to get in contact with our team, or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on Gen AI. 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 what these different GPTs do, and then we're going to look at the results on what they did. And hopefully we'll see. And 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 used,

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 backend 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.

Then 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 GPT. 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 GPT that could do that one thing very, very well.

So insight synthesizer this, uh, 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 digests everything performing a sentiment analysis and thematic clustering and renders a professional one page dashboard in Chad GPT's canvas mode. Uh, so my answer,

uh prompt very simple i said generate an insight uh synthesis 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 uh and the info should be specific and then i just did my you know i announced it for our podcast audience uh 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

It 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 AI.

cans 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, it 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. It 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 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-4.0. 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 points in a bullet point insights. So all I did for this one, and you'll see, uh, if

If livestream audience, you can see the amount of data that I uploaded here. Pretty decent amount of data. It looks like 500. I uploaded podcast episodes. So 500 and it looks like 10. So at least 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 and obvious findings right uh the rest of the instructions on how it could complete this were obviously in the custom uh in the custom instructions inside gpt but you'll see here i got like the world's most basic uh like slideshow but it's not bad all right uh so on the right hand side here uh i got a little slideshow 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 and for a podcast audience,

The big difference here in the GPTs that you didn't have in GPT-4. 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.

and 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, 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 the 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, 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%.

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. Yeah.

and then an appendix and methodology. Cool. All right. Let's look at our other GPTs, 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. Right. Sure. Cool. But none of them use reasoning models. Right.

So all it does, you know, yes, the transformer models, GPT-4, uh, 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 on 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 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, uh, 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 a

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, right? So this is,

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 gold y'all. Um, I should probably just build this. Should I just quit everyday AI and just build this thing? It'd probably make a trillion dollars. Cause 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. And 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-dos and then it went out and it just went and did the to-dos 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. Man, anyone else feeling this one? This one's called a meeting.

The meeting actionizer. Oh, I love that one. I'm going to go, I'm going to make this one a lot better. Uh, and I'm probably going to duplicate it inside, uh, Google gems, uh, and duplicate it inside of, uh, Claude, uh, in, inside of Claude project and, uh, using artifacts as well. Uh, 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. Cause I'm

Everyone hates meetings. And then it's like, all right, everyone has to do the same thing. And 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 GPT to just start the process for me. And then I just make the decision and 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.

Uh, 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 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 service,

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, uh, revenue growth year over year, dividend yield shares, outstanding offer and video 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. Uh, 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 webpage in 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 its 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's

Python for data analysis, a 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 GPTs 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 advanced, but I just really want to quickly recap everything.

So what's new is you only before could use the GPT-4-0 model inside custom GPTs, right? So if you wanted to make your own custom version of ChatGPT, upload your data, your own custom instructions, and then use it in a lot of different places inside the ChatGPT ecosystem, you

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 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 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, right? You can now as a business owner, as a business leader, you can now start to automate huge chunks of your company with GPTs and keeping it all in the same context window, which is something we can go over in the advanced mode and 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 listening 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 GPTs. I'll just put them in a doc 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 brother's mothers, which is your mother's, your brother's mother's best friends, babysitter's teacher and say, Hey, this is helpful. I'd appreciate that. I'd also appreciate you going to your everyday AI.com signing up for the free daily newsletter.

See you 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.