Ep 549: Custom GPTs, Gems and Projects. What they are and why you need to use them

Topics Covered in This Episode:

1. Harnessing Custom GPTs for Efficiency
2. Google Gems vs. Custom GPTs Review
3. ChatGPT Projects: Features & Updates
4. Claude Projects Integration & Benefits
5. Effective AI Chatbot Usage Techniques
6. Leveraging AI for Business Growth
7. Deep Research in ChatGPT Projects
8. Google Apps Integration in Gems

Keywords:

Custom GPTs, Google's gems, Claude's projects, OpenAI ChatGPT, AI chatbots, Large Language Models, AI systems, Google Workspace, productivity tools, GPT-3.5, GPT-4, AI updates, API actions, reasoning models, ChatGPT projects, AI assistant, file uploads, project management, AI integrations, Google Calendar, Gmail, Google Drive, context window, AI usage, AI-powered insights, Gemini 2.5 pro, Claude Opus, Claude Sonnet, AI consultation, ChatGPT Canvas, Claude artifacts, generative AI, AI strategy partner, AI brainstorming partner.

Podcast Transcript

Jordan Wilson [00:00:43]:
You probably think that you're saving yourself a lot of time. Whenever you go into your favorite AI chatbot and you click that new chat button, and then you spend some time getting it to respond just how you want it, sharing your files, and you get an output that you're happy with. You saved yourself time, right? Maybe, or maybe you just wasted a ton of time by not knowing how to use things like Google's gems, OpenAI's ChatGPTs GPTs and Claude's projects and OpenAI's projects. You see these things have changed so much in the last week or two, whether you're a new person learning the basics of these AI chatbots, or you're kind of a seasoned vet using them for hours a day. There's been some under the radar changes to these projects, GPTs and gems that I think change how we should be using these AI chatbots. Because if you're just going in there every single day and clicking that new chat button, you're actually probably not saving yourself very much time. All right.

Jordan Wilson [00:01:55]:
We're going to be talking about that today and a lot more on everyday AI. What's going on y'all? My name is Jordan Wilson and welcome to everyday AI. This is your daily live stream podcast and free daily newsletter helping us all not just learn AI, but how we can leverage it to grow our companies and our careers. If that's what you're trying to do, you're in the right place. It starts here with the unedited, unscripted live streaming podcast, but where you actually can leverage what you are learning is on our website at youreverydayai.com. So there, yes, in our free daily newsletter, you can sign up for it. We keep you up to date with everything you need to know that's happening in the world of AI. But maybe more importantly, we pull out the most important insights or things that we didn't even have time to get to from today's episode.

Jordan Wilson [00:02:38]:
So if this is helpful, you're really gonna wanna go not just sign up for today's newsletter, but read it. Alright? Because that's how we actually can become the smartest people in AI in our companies or in our departments. Alright. So if you're here for the AI news, just go make sure to go check that out in today's newsletter. But I really wanna talk about these recent changes to custom GPTs from OpenAI, some updates to OpenAI projects, feature Google gems and Claude's projects. Because if you are just going to click that new chat, every single time you open your favorite AI chatbot, probably not saving as much time as you think. You may actually be wasting a lot of time. This is difficult.

Jordan Wilson [00:03:25]:
Let's be honest because to learn a new skill, it takes a lot of practice and repetition. Problem is these AI systems that we use so much. And some of us have become reliant on almost for, you know, our day to day, work in business. They change too quickly to actually establish those good routines and those good habits. So unless you're spending hours a day like me, to understand these things, you're probably actually maybe wasting some time. Is using an AI chatbot in this way faster than doing things manually? Absolutely. But the bar is continuing to rise. So you and your skillset, you have to do the same.

Jordan Wilson [00:04:12]:
You can't become complacent just because you're using AI. Right? You have to always stay up to date and take advantage of the biggest updates. And that's why we've started this new segment, calling putting AI to work on Wednesdays. Right? So hopefully you like this. These shows have actually, even though this is only our third, I think it take a lot of planning. So, if you wanna see more of this, let me know. And this is what this ultimately, has stemmed from. A lot of people are saying like, hey, Jordan, I listen to your show all the time, but, you know, I get maybe once a week or, you know, and once every other week, I get some important insights and people ultimately are still asking, like, how are you using AI? So that's what I'm doing.

Jordan Wilson [00:04:53]:
I'm actually giving you all a little look into, you know, everyday AI, how we operate things we're working on our stats. Right. I'm literally just, you know, pulling the, the cover off here and allowing you all to look underneath, but also to see how we're using these, you know, front facing AI chatbots as well. So hopefully you can learn, but as we go along, I'm gonna be giving you examples of what we're doing, but you need to before we start on these Wednesdays, you first need to get into the frame of reference of, okay, get your use case first. Alright. So keep that in mind. We're gonna be going through my use case, but this is gonna be applicable on Wednesdays. It's gonna be applicable to just about anyone.

Jordan Wilson [00:05:33]:
You just have to first think and say, okay. You even hit pause if you need to and say, okay. What's my use case for for, custom GPTs, for gems, for projects, etcetera. Alright. So we're gonna do this one a little different. We're actually gonna start live. Alright. This isn't edited.

Jordan Wilson [00:05:48]:
This isn't, scripted. You know, this is one of the reasons why I do these things live. I know sometimes I ramble on a little bit, but generative AI is generative. Sometimes things work well, sometimes they don't. And I want you all to see the realness because if you just see these polished finished products like everyone else does, you don't see sometimes where things go wrong or how long they take. So, we're gonna start live. So, also for our podcast audience, thank you for tuning in. This might be one of those check out the show notes.

Jordan Wilson [00:06:13]:
You might wanna watch the video on this, although I'm gonna do my best to describe exactly what's going on. If you are choosing to do this one audio only. Alright. So I'm gonna share my screen right now and all I'm gonna do. I have a Google gem, a, Chad GPT, custom GPT, a GPT project, and a Claude project. They're set up the same way. They have the same instructions and access to the same file. So more on that later.

Jordan Wilson [00:06:40]:
So all I'm going to do right now is I'm going to drop the same exact prompt in each of these. So we're going to see them all work live. All right. So first I am going into, my Google gem that I created and I even named these the same. They're just called everyday AI all stats June 2025. Alright. I'm gonna put this prompt in. We're gonna talk about it later.

Jordan Wilson [00:07:01]:
Alright. So now my Google gem is off and running. Now I am in my ChatGPT custom GPT, and I'm using the oh three model. Some more on that later or sorry, oh three pro. All right. So we'll see how long that takes. It's probably gonna take a minute. Now I'm going into my ChatGPT project.

Jordan Wilson [00:07:20]:
Same thing I'm using o3 pro. Also FYI, the Google gem is using Gemini 2.5 pro. And then I'm going into, Claude and I'm actually, I was gonna use Sonnet, but let's go ahead and use Claude Opus four, which is their most powerful model. And I do have the extended thinking toggle on for Claude. So essentially, for each of these, I'm using the most powerful model, that they have access to. And the reason being is because I'm asking for a lot. All right. So more on that.

Jordan Wilson [00:07:51]:
And we're going to get back to that probably in like, probably fifteen minutes. All right. I do expect some of them may take up to eight to twelve minutes, but we're doing this live. It could blow up in my face. We'll see how it goes. All right. So let's talk a little bit about the problem. Just using these AI chatbots, whether you're using, you know, Gemini, Claude, ChatGPT, Copilot, Meta, Mistral, right? Whatever you're using, if you're using something on the web, I would say most people, they just go in and they click that new chat, which is actually dangerous because one of the biggest mistakes people make is overlooking things like context window, organization, right? I'm even doing this show as a reminder to myself because I'm right there with you.

Jordan Wilson [00:08:39]:
Sometimes it's human nature when you're using AI now it's, it's, it's almost become like a default mode for me. I always just go to that new chat button as well, and I'm constantly having to remind myself, like, take advantage of the most powerful technology that we have available, which is not just going in there and clicking that new chat. So number one, it becomes disorganized, and you have all these chats. Right? Think of how you use it. For me, I use ChatGPT all the time for everyday AI. I use it for other clients, other projects, multiple things in my personal life. So what happens if I'm not using, you know, whether we're talking about, projects that have more of this folder in this organizational structure, or if I'm not using GPTs, what happens is I can never go back and find this. So, you know, generally, if you've taken our free prime prop polish course, which I know we gotta kick the the the the next round off, guys.

Jordan Wilson [00:09:34]:
I know. Thank you all for being patient. You know, we've had, I think, more than 11,000 people, take our live prompt engineering course. But one of the biggest problems is we aren't taking advantage of the context window, and then we're also not taking advantage, of the true capabilities that these, large language models have. And that's one of the things is being able to take advantage of context window and the knowledge that you can share with it. Right? So sometimes you're still going through, but you're having to redo that each and every time. So think maybe you want ChatGPT or Claude or Gemini to respond in a certain way. Maybe you want it to be your brand voice for your company.

Jordan Wilson [00:10:14]:
Right? Maybe you're updating a a blog post or creating a a new, SOP, and it needs to be in your company speak. So you're spending that time to get it to respond exactly how you want to, and then you're sharing some files. Right? But then where did that check go? Maybe you go in and you search for it. But most people I would say are just wasting time. You're wasting time by being more productive, but not in an organized way, which I know sounds backwards. But this is where using Google gems, custom GPTs from ChatGPT projects from ChatGPT and projects from Claude can help erase this problem because the solution is literally right in front of us. So here's what we're going to do. We're going to talk about why GPT gems and projects are essential for any business leader using large language models.

Jordan Wilson [00:11:02]:
We're going to quickly show the pros and the cons of each, and then we're going to do this live demo. The live demo is already underway. We started it. We're We're gonna get back to it. Don't worry. Alright. So, podcast audience, I got a nice little chart here, a little feature comparison matrix, and hopefully this will make a little bit more sense as we go along. But we have our Google gems, our, custom GPTs, our projects from ChatGPT and projects from Claude.

Jordan Wilson [00:11:28]:
And where this gets confusing is the core functionality is kind of the same. Right? And I would separate these into one category is your GPT slash gems and your other category is projects. Okay. But ultimately they kind of do the same thing. You give them a set of custom instructions and you give them a, project files. And then depending on how your instructions are written, right, usually, anytime you go in chat with the Jammer GPT, number one or number two, anytime you go chat, or create a new chat within that project, folder, it is going to look at the, custom instructions and refer to the files, the project files that you upload. So on the surface, the two very different setups have a lot of, crossover in terms of utility, right? That's the base utility, but from there, they do get a little bit different. So I, I, I want to talk about a little, some of the things that differentiate each.

Jordan Wilson [00:12:34]:
So when we talk about Google gems, I would say one of the biggest differentiators is number one, it uses the Gemini 2.5 pro model, which until we get full benchmarks for o3 pro, it's the best model in the world. Right. The other big advantage that you have using GBTs is you have all of their apps integrations. So if you are using a workspace account, which I know many of us are, in, you know, Google. So if it's, you know, like our email is info@youreverydayai.com. So, you know, it's Google workspace. So if I go in there, I have access to all my workspace apps, which is great. Google drive, Google docs, Gmail calendar, etcetera.

Jordan Wilson [00:13:18]:
It's all in there, which is great. Actually, if you're using your personal Gmail though, you have more access, to different apps. So I hope that eventually Google allows that. So even when you're using gems, you can still click the app button and you can at mention, some of these apps, which is good. But like I said, your personal Gmail, you actually have access to more. You have access to things like YouTube, YouTube music, Google flights, you know, just some things that you don't have access to if you're using a workspace plan. Alright. So Google Gem, again, think of it like a personalized customized version of the big model, and you can use, at mentioned Google Workspace apps.

Jordan Wilson [00:13:58]:
Alright, let's go to GPTs. So GPTs were just updated a couple of days ago, and this came under the radar. OpenAI actually didn't really announce it at first. They updated some projects, which we're gonna talk about here in a second, but they, enabled anyone to use any version of their model for GPTs. And this is why it's huge. You know, OpenAI kind of started this this phase of the, you know, GPTs. And we thought, oh, it's gonna be like the app store, right, for AI. And it never really took off.

Jordan Wilson [00:14:30]:
One of the reasons I think is because you can never choose which model to use. So, you know, as we got these new models that can think in reason like Gemini 2.5 pro or like, you know, Claude sonnet four or Claude Opus four, we were still stuck using GPTs these non reasoning models until a couple of days ago. So now you can use the most powerful models, including, you know, o3 and o3 pro. So didn't even announce it at first. Right? So it was kind of this under the radar update. So it's extremely exciting. So some differences, with the GPTs. Well, one big one is you can actually connect via, kind of external APIs or actions, which is pretty unique in terms of ChatGPT, what it can do, in GBTs.

Jordan Wilson [00:15:17]:
You can't really work with, not directly, third party, APIs any other way, an indirect way here in a minute. Alright. So then we look at chat, projects. Okay. So first we went over GPTs and gems. That's kind of their own category. I like to think of those as just small little personal, you know, versions of the big model that follow you around. Similarly, projects are a little different projects.

Jordan Wilson [00:15:41]:
I think originally people thought of them as just a folder structure because there's it's a folder structure. Right? Whereas, GPTs and gems, not really. So people think projects are more of just a folder to organize, but it's much more than that because like I said, not only, yes, if you go into a project and start a new chat, it will be found and it will live there. That helps you be more organized. But like I said, any chat that you start in there has access to the custom instructions and the files. So similarly, how a GPT or GEM would. The difference with these projects is a lot of times you get other capabilities that you don't have, in these GEMS or GPTs. The big one in ChatGPT projects would be using things like canvas mode, would be using things like deep research.

Jordan Wilson [00:16:25]:
So that's a new update. You can actually in ChatGPT projects now, you can do deep research using just the information in the project. Brand new update, no one else has that. So that's a very unique, thing for, projects inside ChatGPT. But in general, the projects are good because you can still use the full capabilities of that model. Whereas on GPTs and gems, in Google and OpenAI, you can't use things like deep research. You can't use things like Canvas, but you can inside, projects. You can use ChatGPT Canvas and you can use Claude's artifacts, which are kind of their version of projects.

Jordan Wilson [00:17:05]:
So a big benefit there. One last one to talk about is integrations. So again, there's some things available in ChatGPT projects that are not available in the custom GPTs. So deep research canvas, but also, having that memory across the projects. On anthropic project side, you have access to, your Gmail, so just the different integrations. So you have Gmail, Google Calendar, Google Drive, but then you have MCP, their model context protocol. So this is something, again, a very underlooked aspect, that you can use the, the MCP protocol in anything inside of cloud projects. So that's kind of like a version of API, but for the web.

Jordan Wilson [00:17:50]:
Alright. So I know that was a lot, and hopefully this will make a little bit more sense as we dive in and take a look, but that's just kind of an overview. So, let's go ahead and, actually, we'll take a quick break here. I gotta take a drink, and also quickly shout out our sponsors at Google.

Google Gemini [00:18:11]:
This podcast is supported by Google. Hey, everyone. David here, one of the product leads for Google Gemini. Check out v o3, our state of the art AI video generation model in the Gemini app, which lets you create high quality eight second videos with native audio generation. Try it with a Google AI Pro plan or get the highest access with the Ultra plan. Sign up at gemini.google to get started and show us what you create.

Jordan Wilson [00:18:42]:
All right. So let's first go check-in now, on the prompts that we started to begin with. So like I said, we're doing the exact same thing and it's the exact same setup in Google Gems, ChatGPTs, GPTs, ChatGPTs projects, and Claude's projects. So let me first explain, exactly what we did. So I did the same prompt for each of them. I said, please carefully analyze my files for everyday AI seen at youreverydayai.com. Do not do additional research on the web when or sorry. I I said you can do additional research on the web when needed.

Jordan Wilson [00:19:18]:
Do not make anything up. Take your time. Be take be detailed, blah, blah, blah. So here's essentially what I'm asking it for. I'm saying give me 10 of the most impactful stats or trends that are obvious. Okay. So first I wanna make sure that it can find the obvious things in all of my files that I'm send I'm asking for 10 of the most impactful stats or trends that may not be obvious. So I'm testing its ability to really, connect common threads, and I'm gonna tell you what files I'm using.

Jordan Wilson [00:19:43]:
Then I'm gonna say 10 problems or opportunities I should start working on ASAP. Then I'm gonna say 10 of the biggest blind spots that I'm not aware of based on this data. And then last but not least 10 extremely specific or creative ideas you have based on my data in your research. So ultimately I'm asking for 50 different things. Now this is a lot. All right. Now let me quickly, let me just open up, actually I'll just, I'll just tell you, what we have access to here. So I shared a lot of different things.

Jordan Wilson [00:20:15]:
All right. I actually am just gonna open a new tab here. All right. So you'll see here. I'm I'm sharing my Claude project file. So I have a lot of different files in here. I have 10 in total. Unfortunately, Claude would only accept nine, because it has a file limit.

Jordan Wilson [00:20:34]:
Alright. So anything over 30 megabytes, you cannot upload. So I had a spreadsheet that was like 60 mega or no. It was, like, 42 megabytes or something like that. And Claude couldn't take it, whereas Google Gems and GPTs could. Alright. So, instant kind of bummer for Claude, but, you know, it is what it is. So here's the different, files that I uploaded.

Jordan Wilson [00:20:54]:
Now think this is again where I want you to think of your use case. So I updated, I would have to go and look, but I uploaded hundreds of thousands of rows of data, a lot of data. All right. So here's what I uploaded. I uploaded, Google search council data for different terms that are bringing, traffic to our website. I uploaded Google search council page data, so different pages and how they're appearing on the web. I uploaded, two different actually three different, kind of files from Google Analytics. So everything that's happening on the your everyday AI website, I uploaded our buzzsprout.

Jordan Wilson [00:21:33]:
So we use buzzsprout for our podcast hosting. So just literally all of our stats, the history, every single episode, you know, downloads in the first couple of days, locations, etcetera. And then I also uploaded, let's see. Did I get my oh oh, no. This is the file that wasn't, that Claude wasn't able to upload. So this is a bummer for Claude. The big file was the one from Beehive. So that's what I use for our email newsletter provider.

Jordan Wilson [00:22:01]:
So it's every single, email that we've ever sent, which is that's why it was a huge file, because we've sent, let me do the math, almost a thousand emails. Maybe not quite, but like eight, like 800 emails, I believe. Or maybe like 700 emails, but it has the content of all of those emails as well. So Claude couldn't handle it, but we have that as well. And then I have one other thing which I think is kinda cool. We have this, albacross, file, which this is a piece of software on our website. It's kind of like b to b lead ID. Alright.

Jordan Wilson [00:22:33]:
So, a lot of data, I dump this all. It would take I obviously know this data because I've been looking at it for a long time. If I were to hire a consultant, it would take them forever just to understand what this data is about. So notice all I did, when telling, oh, I actually didn't even tell, what the data is. I probably should have done that. Oh, wait. Hold up. Sorry.

Jordan Wilson [00:22:57]:
I'm getting distracted here. In the custom instructions. Okay. This is good. We talk about the custom instructions. So in the custom instructions, I did tell them what each of these things are. So I said any file labeled g e or sorry, g a is Google Analytics. Anything labeled g s c is Google search council.

Jordan Wilson [00:23:13]:
Oh, YouTube. I uploaded some YouTube data there as well. I think I missed that. Beehive is our email newsletter. Buzzsprout is our podcast distribution, and Albercross is a b two b lead ID software. Alright. So all the models have all of those files except Claude couldn't take one, and then they have that set of custom instructions. And I'm asking them for 50 different insights that are gonna be extremely valuable for me and my company and hopefully our growth.

Jordan Wilson [00:23:41]:
So will this comp like, will this replace, like, hiring a big consultancy? Maybe, but let's be honest. I couldn't afford to go hire a 6 figure consultant, but I think right here, we have the makings of it. Right? And again, in this case, I use the most powerful model. What's your use case? Right? And a lot of times, I think people are like, okay, Jordan. Well, I'm not a business owner, so I don't have access to all that data. Well, you probably have access to a lot of data that you're not just thinking about. Right? So what what of your company docs can you put in there? What about, industry white papers? What about information about your competitors? What about information about your brand voice? What about the last, you know, 50 projects you've worked on and completed? What about, spreadsheets that aren't, you know, private? So, you know, obviously, only, put data that you have the the, you you know, access to put in there. But think of all the different context that you can put in there.

Jordan Wilson [00:24:34]:
And then every time you go in now think. Instead of go clicking new chat, now all of a sudden, if you just unload your brain, unload everything about your position, put your job description in there, who you are, who you work with meeting transcripts, right? You can fit so much information in these gems, GPTs, and projects that all that time that you would normally spend trying to get the most and explain things and feed all this data to a large language model. If you just set it up correctly and then use it every single time, think of not just how much time you're saving, but how much better the outputs are gonna be. Now, even for me, even if I don't necessarily, have a data question for everyday AI, I should probably still just use this. Right? Because again, now this gives these models context, a huge amount of context, even if I'm not asking for specific stats, if I'm just using, you know, any of these AI chatbots as a strategy partner, as a brainstorming partner to help me plan things, why wouldn't I wanna give it access to all of this information? This is my brain. This is my brain and then some. This is my brain and my computer's brain. Right? I would probably go through go through here at a later time and, you know, upload a bunch of meeting transcripts.

Jordan Wilson [00:25:52]:
I would probably go through and do, a couple, like, one hour recordings of myself, just word vomiting. Right? Hey. Here's what's going right, with our website. Here's what's going right with the podcast. Here's my biggest opportunities. Here's my challenges. Right? I would probably go through and upload those and sort those as well. So think you should be doing the same thing.

Jordan Wilson [00:26:12]:
Right? Even taking that unstructured data, your thought process, your domain expertise, talk it into a microphone, transcribe it and dump it into Google gems, ChatGPT, GPTs, or folders. All right. So enough and do let's just go and check and see how they did. Well, let's first see if they're done. Alright. Hopefully, they're done. Alright. So I'm sharing my screen now.

Jordan Wilson [00:26:34]:
I'm not gonna go through all of these, and I don't know if you want to see these 50 things for all, four of these. I don't know. Go go repost the episode. I'll put them all in the document if you care that much, and I'll share them with you. Right? If you really wanna see the, the juicy details, go go repost this on, LinkedIn or, Twitter, and I'll send it to you. How about that? Alright. So I'm first gonna see, did all of these properly go through and do the things I asked? All right. So let's look at the Google gem first.

Jordan Wilson [00:27:05]:
All right. So, 10 of the most impactful stats or trends. The obvious ones got me all 10, the not so obvious stats and trends. Let's see. Got me all 10. Good. 10 problems or opportunities I should be working on. Got me all 10.

Jordan Wilson [00:27:18]:
10 of the biggest blind spots. Got me all 10. Good. And the, creative ideas. Got me all 10. So, Google, on their gems side passed the test. And the good thing is, right, I can also go in here and click this show thinking, which is good. It looks like Google, which is really cool to see Google Gemini, 2.5 pro, which you can use the most powerful model in your gem, which wasn't huge advantage, for gems until a couple of days ago when, ChatGPT allowed you to have the most powerful model.

Jordan Wilson [00:27:49]:
Because before that, gems had a big advantage, in that department. But I can click here. It looks like I can see I can see the code or hide the code in the chain of thought, but I can go through here and see the chain of thought, see how it thought, see how it thought. So actually, you wanna get super meta. Probably what I'm gonna do is I'm gonna upload a transcript of this episode, and I'm gonna dump all this into all of these files, and I'm gonna copy and paste the chain of thought as well and be like, how can I improve this process? Right? If you wanna get super meta and into my brain on how I work, there you go. But like I tell you all every time, you need to be reading this chain of thought. I'm not going to read it right now, but this tells you because we're using these either reasoning models or hybrid models that go between reasoning and non reasoning. But the quality of my prompt was very low, right? This, the, the, the custom instructions were not very great.

Jordan Wilson [00:28:40]:
So when you don't spend a lot of time before you go and set these very powerful models on motion, you don't really know how they're going to respond. Generative AI is generated. It's going to be different every single time. So by reading this chain of thought, it's gonna tell me how I should improve my inputs to get a better output. I should probably be more descriptive in certain areas. I probably might need to, you know, use some, some more, data to begin with, some better custom instructions, a better prompt. I just wanted to do something basic that I could read out loud on the podcast and not get too into the weeds. But, going over here, looking looking at what, Google, gems did, it looks like it did a pretty good job.

Jordan Wilson [00:29:20]:
It found some errors. Looks like it's, you know, it says diagnosing column mismatch. So it looks like it did a pretty good job. It found some issues with my spreadsheets. That's the other thing. There's literally hundreds of thousands of rows of data in there, and they probably weren't all super clean, super correct. Sometimes when you export something, you have to do a little bit of cleanup. I didn't do any of that.

Jordan Wilson [00:29:40]:
I just clicked export all on all of those and just dumped it in there and said, yo. Here's here's what these files are. You know? Figure it out. Right? Figure it out. Alright. So, Gemini in their gems at least pass the test. Alright. So now I am going into, the, GPT, I believe.

Jordan Wilson [00:29:59]:
Yeah. So the problem is I wish that, ChatGPT would change back, some of their user interface. It was a little easier to see before they made this update, but that's okay. So the first one I'm using the gem or sorry, the, the GPT. So you'll see here I can go and now choose whatever model I want. So I use the o3 pro in this GPT, and let's kind of scroll and see how it did. So it actually didn't take long. I thought it was gonna take much longer than this.

Jordan Wilson [00:30:27]:
It only reason for four minutes and fourteen seconds. So unfortunately, with JetGPT, you only get a summarized, a very summarized, kind of chain of thought. So not a ton of value right here. I can't really see what went right and what went wrong, but I can very quickly look at the results. I like how these results are formatted. This is pretty nice. So let's see. Okay.

Jordan Wilson [00:30:53]:
Interesting. So it said I'm unable to open any of the data files you uploaded. The Python environment that normally lets me read and analyze spreadsheets and CSVs is returning empty results for every file access attempt. Because I because I cannot inspect the underlying numbers, I would have to guess, which would violate your request and not make anything up. Okay. Interesting. So, in my original testing, and I'll probably just wanna, I'm gonna open up a new tab and see if I can, grab my one that I did, when I was planning this show, because I thought it didn't happen. It didn't happen the last time, but I'm gonna have to go through and double check here.

Jordan Wilson [00:31:33]:
Love doing these things, live. So let's see if I can find it here. Alright. Okay. It looks like the same thing might've happened twice. Okay. So for whatever reason, I might have to diagnose this a little bit more. It looks like the GPT, was not able to access, the file.

Jordan Wilson [00:31:57]:
So I'm gonna go into edit GPT, make sure I put them all in there. Yeah. I put them all in there. Okay. So, unfortunately, it looks like we had, kind of a little bit of a misstep here, on the GPT. So I'm trying to see if it actually gave any ideas. So it says, you know, please reshare data in a way I can access. The sooner I can open the files, the more okay.

Jordan Wilson [00:32:18]:
So, what I'm actually gonna do is I'm gonna manually upload in these in the, body of the chat. All right. I don't think this is going to make a difference. But let me just go ahead and do this and see if it works. Although I don't think it's going to. All right. It's giving me an, error. I'm trying to upload too many files at once.

Jordan Wilson [00:32:42]:
There's a limit of uploading 10. So let me just upload a couple fewer. Let's see how many this is. This is 12345678. Oh yeah. That's way too many. All right. Let's do this.

Jordan Wilson [00:33:02]:
Alright. I'm trying one more time. So now what I'm doing, in the GBT, we got the little error. So I'm just reuploading the files in the body of the chat, which in theory shouldn't make a difference. But for whatever reason it is. Okay. So I just found a little bit of an issue, that I hope OpenAI can iron out. So it looks like it's opening.

Jordan Wilson [00:33:27]:
It was able to open about half, of those files when I shared them in the body of the chat. But when I, uploaded them as, files in the project, knowledge, it didn't work. So that's interesting here. A little bug, like I said, this new these new, updated GPTs have only been out for, a couple of days. So, I'm guessing we just discovered a bug, so I'll have to, reach out to the team over at OpenAI if they're not aware of this. They might be, but it looks like now it's taking some time to reason. So let's go through the projects in chat QPT and see if we ran into that same issue. So I'm guessing not because I'm looking at the reasoning right now, and it says it reason for thirteen minutes.

Jordan Wilson [00:34:12]:
And what's interesting here is when I look at the reasoning in a project, I get a lot more information. Right? Maybe because it was actually able, to go and look at all the files and maybe I would have gotten a similar amount of information in the GPT if it would have worked. All right. So let's see if we actually got good results here. All right. So same thing. So the, the projects in ChatGPT similarly, said at the moment I'm unable to open or read the spreadsheets or CSV files that were uploaded. The execution environment is blocking any attempt to list the directory or load the files.

Jordan Wilson [00:34:54]:
So I'm wondering what it did for, that long. All right. So unfortunately it looks like we got a couple of strikes, from, ChatGPT, which in my original testing, I'm going back now. And I'm, I'm going to double check when I ran this one last night. Okay. So I'm going to share this one. Interesting generative AI is fun. Y'all all right.

Jordan Wilson [00:35:21]:
So exact same thing. When I ran this last night in the projects and it worked. Alright. So when I scroll through here, in the projects, I have the 10, obvious high impact stats and trends. I have the 10 less obvious insights. I have the three problems and opportunities to tackle immediately. I have the 10 blind spots. I have the 10 creative data driven insights.

Jordan Wilson [00:35:48]:
So interestingly enough, ran the exact same thing twice. The second time, it didn't work inside ChatTBT. It might be running into some issues. I don't know. That's why we do these things live. That's why I always do things multiple times, because pretty interesting, but you need to understand this as well. Generative AI is generative. Just because it doesn't work once, doesn't mean it's broken.

Jordan Wilson [00:36:12]:
Right? This is why I encourage companies that I work with that hire us to, you know, don't just do something once and write it off. You need to be revisiting these things, whether it's biweekly, bimonthly. Right? Depending on how many people are are using this technology, what kind of processes that you're building within your organization. You know, never try something once and say this is good enough. Right? You don't have to go the full, like, benchmarking route of doing things, you know, 50 times and, you know, finding the mean or the the the median, the average. You don't have to do that. But generative AI is generative. Right? I would always encourage you, especially if it's something that you're gonna do over and over and over and roll it out within your organization.

Jordan Wilson [00:36:50]:
You should at least be testing it minimum five times, minimum, and you need something to measure. Because you saw in that case, if I did this once for 10 g p t, I probably would have given up. But because I did this multiple times, I know that it had already worked once, in the project setup. Alright. Now let's move over. We've done three of our four. Let's look at Claude. Alright.

Jordan Wilson [00:37:14]:
So it looks like let's see how long it took Claude, to go through this. It looks like it went through fairly quickly. A couple of seconds, not even a minute, which I don't know how, I mean, again, I'll I'll later look at all these and, and let you all know which one was best. I don't know. I don't have a ton of of faith, in the fact that Claude went through all this in a couple of seconds. Maybe it'll still be good, but I would have even hoped even a large language model would spend multiple minutes on this, thinking about it critically, trying to connect dots between the different data patterns, etcetera. Alright. But let's look to at least see if this quad project did the job.

Jordan Wilson [00:38:00]:
So, number one, ten most impactful stats or trend that are obvious. Got it. Number two, the 10 most impactful stats or trends that may not be obvious. We got all 10. The 10 problems or opportunities I should be working on ASAP. We got all 10. Okay. Interesting here.

Jordan Wilson [00:38:16]:
In the middle of this, Claude went out and did some research, which is good to see. Right? So it started doing, it started doing, some things without going to do research, and then it stopped midway through and said, alright. I'm gonna go research some things. So that it got me the 10 biggest blind spots that I'm not aware of based on this data. Then it got me the 10 extremely specific or creative ideas based on my data and research. There we go. Alright. So Claude did a pretty good job, although I'm gonna have to go be the judge and see which one actually did the best.

Jordan Wilson [00:38:49]:
So we saw some, some failure issues, for ChatGPT in certain instances on the second time I ran this, because again, I ran it last night. It worked fine on the GBT side and the project side today, not so much. So it could just be an issue. Chad GPT's, been having a lot of downtime, the past couple of days. That might be it, or this could just be a bug because they did just update both their projects and their GPTs. So I'm probably gonna have to come back to this one at a later time to ultimately be a judge on which one I'm going to use the most. You saw Gemini 2.5 gems. It looks like it did a pretty good job.

Jordan Wilson [00:39:27]:
Right. I'm trying to see here. It didn't show me how long that it thought, but I looked at the chain of thought. It looks like it did a pretty good and a pretty thorough job. It identified, some mismatched columns, and it told me about this. So, again, I can't judge the accuracy of everything just yet, but it looks like, Gemini off the bat in Gemini in the gems, I might have the most confidence in before looking at everything, just looking at how it handled it. And it looks like Claude also did a pretty good job. I like that Claude halfway through said, yo.

Jordan Wilson [00:40:00]:
Hold up. I gotta actually go research some more because in order for me to, you know, find out this information, I'm not sure. So I like that midway through. It actually did some research on, it looks like it went out and searched for AI podcast market size growth, 2025, and analyze some things there. Alright. So, overall y'all, as we start to, wrap this thing up, I wanna just show you which one should you use. Alright? And I actually, am sharing something on my screen now, which I think is really cool. And, hey, just comments, what should you comment? Comment gimme.

Jordan Wilson [00:40:40]:
Alright? And I'll send you this, this little link here. Alright? If you wanna take a look at this, because I think this is actually pretty, pretty helpful. So the, I went in and used Google Gemini, which y'all, the new canvas mode in Google Gemini is so freaking good. Probably one of the most unique things of any AI tool I've literally ever seen is this one little button. No one else has it. So in the canvas mode so, right, Chad GPT has a canvas mode. Claude has their version of it, which is called artifacts. So I just dumped in a bunch of data, and I said, hey.

Jordan Wilson [00:41:16]:
You know, build me something that helps me choose which one I should use. Who, Gemini gems, custom GPTs, ChatGPT projects, or cloud projects. So now on my screen, I'm sharing this, and it's a super cool it's actually a little website, so it's actually responsive. So if I, you you know, move my my browser, now I'm in mobile mode, and it's like a mobile responsive, like website. It's it's interactive. There's nice animation. So it did a great job of creating a visual that can help you better understand which AI assistant to use. But what I love about Google Gemini, no one else has it, is it has this ability to one click and you can actually add AI access to the thing that you're building.

Jordan Wilson [00:41:59]:
Literally, no one else has this. Maybe everyone else will copy and I can't believe more people aren't talking about this. But now there's literally Gemini is embedded in this thing that I created, and anyone can go use it. So now I can go in, and let's go to, you know, custom, GBTs. So it tells it tells me what it's best for, some of the key features, some example prompts, and then it says this thing of generate more examples. So there is literally an AI element built into this that gives it a dynamic and unique experience for anyone using it. Alright. So I can click the, I might have to refresh this here.

Jordan Wilson [00:42:36]:
It's not working. I was, I was, trying it earlier and it was working. All right. So for whatever reason, this isn't working, although it was working earlier. All right. But I did this one last week. If you want to see that AI feature, actually was able to create a presentation, and an actual, like, literal chatbot. So I'm trying to go.

Jordan Wilson [00:42:57]:
If you wanna check that out, that was last week's work with us, on Wednesday. So that was episode five forty four if you wanna go check this out. But let me wrap this up by actually reading, what Google Gemini canvas mode put together. Because at the end, I showed you some of the pros and cons. Some of the issues I had, you might not have them. You might. Right? But let's go and wrap this up and say, Gemini gems, OpenAI's GPTs, OpenAI's projects and cloud projects, which one's best for what use case. So Google gems are best if you are using the Google ecosystem.

Jordan Wilson [00:43:34]:
It's best for Google ecosystem power users who need real time access to their personal and professional data. So the best features are native access to Google Workspace, Drive, Gmail, and Docs. It integrates with consumer apps if you're using the personal version such as YouTube flights, YouTube flights and hotels, and it's powered by the most powerful model, at least the ones that's been benchmarked to date, Gemini 2.5 pro. Alright. For custom GPTs, this is best for creating reusable purpose built AI assistance for highly specific tasks and workflows. Some of the key features are they're modular and highly personalized with custom instructions. They can be equipped with tools and API actions. And the thing that I didn't even get to talk about is you can instantly call them from anywhere, inside ChatGPT.

Jordan Wilson [00:44:23]:
You're using a GPT model, which is a big benefit over projects. So you can be in any chat. And if you want to call on or use your custom GPT, you can just click the app button and you can start chatting with that GPT anywhere. So another unique feature for the custom GPTs from OpenAI. Although, I do know that, Google has been testing that feature out, on Google Gems for a while. They just haven't released it. So, another, kind of good use case there for, GPTs. Then ChatGPT projects is best for organizing complex work with persistent files and memory for deep research and synthesis.

Jordan Wilson [00:44:58]:
That's the big, the big unique factor there in ChatGPT projects, the ability to do that deep research just on the information in there and as well as using all the models and capabilities, available like, Canvas, Deep Research, and this new memory, across all assets within the projects. And then Claude projects is best for deep AI work that requires strong integrations with external applications like Google Workspace. Some of the good features connects to Google Calendar, Gmail, Drive, and more, supports deep research and artifacts, and it has access to their most powerful models, Claude, Sonic four and Opus four. All right. We went over a ton. Y'all let me just wrap by saying this. Don't click new chat. Don't do it.

Jordan Wilson [00:45:46]:
This is also a reminder to myself. It's a habit. Right? Also I use voice mode a lot and by default, it just jumps in into, outside of these modes. But if I go into, you know, a project or a GPT, first or a gem first, that's what you should be doing. So spend the extra, you know, ten to fifteen seconds when you're using, AI chatbots and get organized, right? Because to get organized takes one step. Right? So now, as an example, all of these, I'm going to update the files, I'll put in more information, but there's no reason for me not to go use these gems, these custom GPTs or these projects now, even if I don't think I'll necessarily need them, think of all the extra context. So I essentially turned my AI usage from using a general large language model, which might know everything. It might know nothing to having a fine tuned literal, like, 6 figure consultant ready there sitting.

Jordan Wilson [00:46:46]:
So even if I don't think I need all of this data in this context, it's there. It's only going to make all of your results exponentially better. It's going to save you so much time. So whatever you do, don't click that new chat button, Do it the right way and put AI to work for you on this Wednesday. Alright. I hope this was helpful. Y'all do you like these segments? Let me know. Yes or no.

Jordan Wilson [00:47:08]:
Literally just type yes or no in the comments right now. If you wanna keep doing these things, I hope they're helpful. But if I'm being honest, there are a lot of work to put these together. But I want to make sure that you can show up even if it's just once a week. Maybe this is the only thing you care about. Maybe you don't care about our you know, when we do our AI news shows on Mondays where we recap the latest news or, you know, our hot take Tuesdays, where, you know, I try to come with a hot take on something in AI. And then usually on Thursdays and Fridays, we're doing more interview styles, you know, talking to great guests. So maybe this is the only thing you care about or maybe you don't care about.

Jordan Wilson [00:47:44]:
Regardless, is this something that is worth investing the time? Do you like this? Let me know. Yes or no. Or, if you're just, gonna be reading the, email newsletter today, just respond yes to AI work on Wednesdays, no to AI work on Wednesdays. It's up to you. Thank you for tuning in. I hope this is helpful. Please go to youreverydayai.com. Sign up for the free daily newsletter.

Jordan Wilson [00:48:04]:
I'll see you back tomorrow and every day for more everyday AI. Thanks y'all.