How to actually use ChatGPT in 2026: The 7 rules to quickly become a power user

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There's nearly 900 million people using ChatGPT each week, but I've gotta be honest, very few people have a clue what they're doing. It's like being given keys to a Ferrari, but you just use it to keep dry and cover up when it rains. It's not how you should be using it, especially for teams, because ChatGPT at work is an actual competitive cheat code. But the problem is it's nearly impossible to keep up with the updates, the changes, the model releases and all the new features that come and go. And I'm not trying to be mean, but you're still kind of using ChatGPT like it's November of 2022. Don't worry, we're going to change that on today's show because this AI thing is all I do and I'm fairly okay at this Chat GPT thing. I did even get a DM from someone in leadership at Open AI who said that there aren't many people in the world who know ChatGPT better than me. Well, I'm going to share it all with you, so stick with me for the next 25ish minutes as I lay it all out for you in today's episode in our first AI at Work Wednesday series of 2026. So we're going to be going over how to actually use ChatGPT in 2026 and the seven rules to turn you into a power user. All right, let's dive into it. If you're new here, welcome. My name is Jordan Wilson and this is Everyday AI. This is your daily livestream podcast and free daily newsletter helping every leaders like you and me make sense of all the AI updates and chaos and just grab the important insights to grow our companies and our careers. So it starts here with the unedited, unscripted live stream podcast. But if you want to be the smartest person in AI at your company, that happens at our website, your everyday AI.com there. Make sure to go sign up for the free daily newsletter. We're going to be recapping the highlights from today's show as well as all of the other AI news. It's all going to be in the newsletter. All right? And I'm looking at my watch now. It's going to be any minute. We're either launching our free AI inner circle community either today or tomorrow. All right? But I'm not kidding. I checked my email. We have a couple thousand people that are waiting to get in. I kid you not. So if you want to move to the front of the line and get access, including our free course. So if you find today's show helpful, you're going to find the free. It's about a free almost a two hour course. You can take it at your own pace. Prime prompt polish. So just repost Today's show on LinkedIn. I'll get you to the front of the line. We're probably going to let in, I don't know, about 50 or so people a day. So if you do want to get early access, just repost today's show. All right, enough chit chat. Let me give you these seven rules to be a power user and then we're going to dive into each of these and then because it is AI at work on Wednesdays, we're going to going to go live. Liveish. All right, so what could go wrong? All right, ready? Rule number one, do not use the free version of Chat gbt. Number two, you should almost always use thinking models. Number three, you should be context switching between the right model mode or GPTs. Number four, you should use more custom GPTs and projects than you think. Number five, connectors are now apps, but they're still connected and you should still be using them. I'll explain that one later. Number six, ChatGPT is best for teams. Everything from project memory, shared GPTs and even group chats. And number seven, kind of advanced, but kind of not. You should be leveraging chain of thought summaries as your secret weapon. All right, let's start at the top. Do not use the free version of Chat gbt. That is number one. All right, here's why. And hopefully those people listening over there at OpenAI, don't get mad at me for saying this. It's not the best model, right? The version of GPT that you get on the free plan is not what you think, right? When they first announced GPT5, there was this new thing called the auto, you know, the auto model router. And you know, even the free people got it. So you got this new level of intelligence, right? And I did go over this a little bit more on yesterday's show. So make sure, if you haven't listened to that, go click the back button when you're done here. Listen to that one. But you know, essentially there's two different types of AI models, right? least today there's models that can think and reason and plan. And then there's those that can't really. Right. So OpenAI just this was an under the radar update. Not a lot of people know about this. People still assume, no, I can use the free model because if I ask it a tough question, it's going to use that model router and send me to a really good model. No. Okay, so there is a technically a newer version of GPT5.2 that is the latest version of ChatGPT. But if you are on the free plan, it is using a model called GPT5.2 Instant, which by all comparisons is not very good. All right? It's not a type of model that is going to be able to handle a lot of your data. It's not going to be able to do a lot of high level thinking, reasoning, planning. The outputs are going to be bad. All right. And most numbers suggest that more than 95% of chat GPTs, you know, 900 million users are on the free plan. You shouldn't be. Right. Open AI is not paying me to say this. Right. And I feel the same way about Google, Gemini, about Anthropic, Claude, about co Pilot. You shouldn't be on a free plan. I understand. Right. Economy's tough. Getting a job is tough. Yes. It is criminally cheap. Any. Right. Any of those plans for $20 a month, you can go out there and compete with anyone doing anything. Right. Whether you're trying to get a job, whether you're trying to get a promotion, whether you're trying to push your company forward. You can't do that on the free version of anything, Period. The fact that you can still get this level of intelligence for $20, it is mindboggling to me that people don't pay that. Right. One time me and my wife went and got a coffee and it was more than 20. It was some fancy coffee. It wasn't even that good. Right. But think like again, even if money is tight, right? Or, or maybe you're making the decision for your company. Single prompts to me have saved me dozens of hours. Single prompts, right. Not just the time that you can save. Right. You have to be able to quantify and put a price tag on that your time is valuable. Right? Because you might say, oh, I don't, I don't have $20 a month. Okay, well, there's always this saying, money can buy you anything, but it can't buy you time. Well, yeah, it can't if you're using large language models. My gosh. Right. So what could you do with another couple hours a week. Well, you could go, you know, apply more jobs if you are job hunting, right? Or whatever the case may be. So rule number one, do not use the free version of chat gbt. And rule number two is kind of related to that because rule number two, you should almost always be using the thinking models. I get it. You and by you. We as a society, we as humans for the most part are lazy and impatient. And it's actually weird. Like as these AI models get more and more capable, as they get more robust, as they get smarter, as their agentic capabilities increase, it's almost like the default for us humans is to do the opposite, right? Is to kick back more, be even lazier. Right? But we just want things faster. So sometimes I see people just using like the instant model, right? Or just using the kind of the, the default auto, right? No, don't do that. You should almost always be using thinking models. All right, so our live stream audience can see this. And if you ever do want to see the video version of this, you can always go to our website. All right, your everyday AI.com the video versions are there. It's a library. You can go, listen, watch, read everything on the website for free. So literally a university of free unbiased information on AI. All right. But I do have a screenshot from Artificial analysis. It's one of the best unbiased third party benchmarking sites uses a series of different benchmarks from other companies and they run these different tests and put their results up. You'll see the free version, GPT5 2, the basic version. Well, not just the free version, but the basic version of GPT5 2. It is the 25th best model. 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 ChatGPT 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 your everydayai.com 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. Let me Repeat that. The 25th best model, the high thinking version, is the first. It's tied for first with Gemini 3 Pro. Let me repeat that. Gemini 3 Pro and the, the thinking, the high thinking version of GPT5.2 are in first place. The version that you're probably using is 25th. Right? I don't know. You need to be patient, right? Sometimes people just want something in 10 seconds or less and they don't want to wait, you know, a minute, two minutes. Oh, my gosh. Okay. I don't know. Maybe I should take my own advice, right? It's like, oh, what do you do during that one or two minutes? Well, I have way too many subscriptions, I think. I have 3 or 4 paid plans to OpenAI. I have at least 2 paid plans to Google Gemini. I have a max plan to Claude. So, you know, normally when I'm waiting for one, I'm working on two or three others or having an agent go read two or three others, and I'm reading the agent's recap of two or three other large language models. Right? But I don't know, while you're waiting, I don't know, do some push ups, send someone a text, right? I don't know, don't doom scroll, don't go on sora. Right? But the, the difference. And this is not just some, you know, door key benchmark. This is facts. This is stacks. This is science. This is outputs. All right, this is your career. This is your company. This is your department. That choice that you probably aren't making. Right? A lot of people don't think. They just use whatever's there by default and you assume it's good. You see? Oh, it says GP. You know, it says, you know, GPT5 on it. So it's good. Or, you know, it says GPT 52. So we're good. No, no, we're not. All right, don't use it. All right, Rule number three. All right, here's one of my little phrases I used to use a lot. Context switching. This is actually a huge advantage that chat GPT has that other large language models don't. All right, without getting too deep into the context window. Right? Again, just repost this show and get you in the front of the line and we'll, we'll, we'll go deep into the context Window and why that's important, but more or less right, with some other large language models, even Google Gemini, even Claude Copilot, right. When you're switching from model to model, or maybe when you're switching different modes or different features, it stops. Right? That's one thing I love. Gemini 3. The, the, the deep research from Gemini 3. It is so freaking good, right? But one thing I usually like to do is context switch. So after I do a deep research, I like to continue chatting. But not in deep research. But you can't do that in Google Gemini. Same thing with, with, with Claude, right? When you switch, if you want to switch over from a more powerful model, maybe you know, Opus 4.5 with reasoning and hey, I need to kick it over to Sonnet. Can't do it, got to start over. And you lose all the context, you lose the work. So it's like you start with a blank document. That's bad. So this is one of the biggest cheat codes I'd say that most average users skip over is not taking advantage of a built in feature that a lot of people don't know. And it's not just between the models, it's with the modes as well. Right? We're not going to get too much into that in today's episode. That's not, it's a little more advanced, but I wanted to keep this one a little shorter. But even if you're using the different modes, right? GPTs, canvas mode, study and learn, right? Whatever mode you're using, you can keep it going using the different modes and not have to start over, right? You know, not having to re. Explain yourself, not having to copy and paste anything. ChatGPT doesn't skip a beat when you change a model or mode. All right, number four, use projects in custom GPTs more than you think. My gosh, this is good for me to say out loud because I'm also reminding myself I literally thought like two days ago, I'm like, okay, Jordan, this is like the third time this hour that you just clicked new chat when you should have either went and found the project you already built or you probably should have built the GPT or something like that. All right, so we cover this in our free courses in our everyday AI inner circle community. But there's a lot of crossover between GPTs and projects and there's also some unique features, but the simplest way to think of them IS projects and GPTs are ways that you can, without any code, create customized versions of ChatGPT and attach your data to it. All Right. But it is sometimes easier or human nature or the default of using a nice interface like ChatGPT to just always go and find that new chat button and get to work. Right. Take the time. You know, projects are a good way to organize your chats from a hierarchy. Right. Like a folder file type hierarchy. Right. But there's other benefits to there, putting in custom instructions, uploading your files in there, as well as the, the other, you know, big version that I love or the big advantage that I love with projects having project only memory. That's huge. Right. Especially when you can share that with your team. All right, number five, this one, little confusing. Stick with me here. Connectors, not connectors anymore. All right. Yeah, this is another one. It kind of snuck under the radar around the holiday season here in the US So this is only a couple of weeks old. Um, but connectors are kind of phased out. But if you had a connector connected previously, it still works. If you didn't know, a connector is just an, an easy way to connect your version of ChatGPT to business data. So there's, there were connectors for things like, you know, Dropbox Box, you know, Microsoft SharePoint, different email service providers, Gmail, Google Drive. Right. There's dozens, actually. Different CRMs, different project management. And it just brings all of your data in. Right. So it's mini rag. We talked about that on the show yesterday. So connectors are now technically called apps and some of the features and functionality has changed, as has the terminology. So just FYI, and we went over this, I don't know, probably five or six months ago when connectors first came out, but there was three different types of connectors. There were chat connectors that were kind of instant and they indexed everything. There's Deep Research connectors. So certain connectors that are available via Deep Research, which is really cool to do, right? To only run a deep research on your company's data, mind blowing. And then there were synced connectors. So that's something that you didn't have to like wait for. Like the model didn't have to go and agentically search around your, you know, Google Drive or something like that. They're synced connectors that essentially were, is always indexed, I believe. Like some of those were like Calendar, your Gmail, etc. So now again, some of the functionality is a little different, but the terminology is definitely different. So the chat connectors are now called apps with file search, the Deep Research connectors are called apps with Deep research, and the synced connectors are apps with sync. But Like I said, a little bit of the feature, features and functionality not quite the same. I'm still getting used to it. Like I said, I have a lot of different accounts. You know, there's other, there were other connectors that were in a business plan that weren't previously in a, that weren't in like even if you were on the pro plan, the 200amonth plan. So there were certain connectors that were only available if you had a business plan. So I'm still going through and you know, testing out all the apps and you know, trying to remember or looking at old videos to see like, okay, this is how the connectors work. Do they work the same? So OpenAI is making a big push with chat GPT apps. I think it's great in the long run, right? But it's, I think there is going to be a little bit of learning curve for everyone in the short run, you know, figuring out how these apps work. But regardless, you know, being able to connect chat GBT with very little technical know how. You don't have to know anything about retrieval, augmented retrieve retrieval, augmented generation. You don't have to know about vector databases. You can just click a couple buttons and the world's most powerful large language model has access to dynamic data from your company and you don't have to do really anything. That's amazing and it's something you shouldn't be skipping over. All right, number six, ChatGPT is best for teams, period. The future of work. I've been saying this. Good thing. I have receipts on the website. I've been saying this for a long time. Before it was a popular thing to say, the AI operating system. I've been saying that for a very long time. I do think in the same way that you know, through the 90s and the early 2000s, right, most businesses made a choice, right? Are we a Windows organization? Are we a Mac organization? Are we a Linux organization? You have to do the same thing with an AI operating system and you have to move your day to day business processes. Your entire team. You better just do it now. There's no need to wait. But you should be using moving your day to day processes inside either a teams or enterprise or sorry, a business or enterprise account in Chat GPT. Google Gemini has the same offerings, right? They have a business and an enterprise account that's different from their normal Gemini. Same thing or similar thing with Claude. You know, co pilot's a little bit of a different story since it's more desktop based, right? Even Grok, you Know, just came out with a business version. Although I wouldn't touch that with a 30 foot pole. That's just me. But I mean look at some of these stats. So 92% and this is all from OpenAI's enterprise report that just came out a couple of months ago. So 92% of Fortune 500 companies use ChatGPT or OpenAI technology. There's over a million business customers with 7 million active ChatGPT work seats, weekly messages. And ChatGPT enterprise increased 8x over the past year. Usage for enterprise 8x increase. Crazy. Speaking of those projects and custom GPTs 19x increase year over year for those more structured workflows According to OpenAI, here's a big one. 320x. A 320x increase in reasoning token consumption. So yeah, if you think ah, companies, yeah they're, they're just, you know, maybe given some people a couple seats and you know, toy. No, people are putting their highest resource workflows in rebuilding the future of how their company works inside of ChatGPT. Also a, their study said that heavy AI users save more than 10 hours per week. Okay. So yeah, the future of ChatGPT is collaborative work inside of a business or an enterprise account. All right. And there's so many of those great features, like I said, being able to share projects and shared project memory, that's huge, right? Yeah. People think of projects as like an organizational folder. I like to think of it as an insights and answer machine. And then when someone else goes through it and they get an answer or an insight, if you have that project memory enabled now, everyone on the team that's in that project has access to that because it has memory of a different user chatting in that project. That's a, that's, that's an enormous unlock, right? The same thing with GPTs, right? That you can no code have a GPT that does amazing things. It can, you know, read and write code, it can go through and you can build, you know, certain functionality that would normally, you know, three years ago, take millions of dollars. Anyone can do it. No code, low code. And then share it across your organization. Right. This is so much untapped potential there. All right, and then rule number seven, leverage chain of thought summaries as your secret weapon. I talk about this randomly on the show, but if you really want to separate yourself from being or your company or your department, you need to be doing this right. I cannot emphasize enough, especially if you're using a model like GPT5.2 Pro. Look at the chain of Thought, right. I was actually, you know, talking about this a couple months ago with my. With my stepdad, first time showing him a thinking model. And, you know, he has a background in. In chiropractic consulting. And I showed it to him and he was like, wait. He's like, this is exactly what I would have done. He was kind of, like, blown away, you know. You know, him and my mom, they use the normal version of chat GPT, right? But when I showed him this, and I'm like, okay, we're gonna click this button and we're going to see step by step, exactly what this model thought. And then, you know, we need to verify, we need to make sure is it doing the right thing. And he, you know, took, I don't know, five or 10 minutes, you know, read through all the steps, all the sources, you know, gave it a pretty complex problem. I built him a GPT and he's like, wait, this is exactly the steps I would have done to solve this, you know, kind of difficult case. So you need to be leveraging the chain of thought summaries as your secret weapon, because sometimes they're not going to go right. And normally that's because maybe you didn't give it enough context. Right, the whole context engineering thing. Yeah, that's extremely important. All right, so that's a wrap for the seven rules. Now we're going to quickly jump in, we're going to do a little bit of learning live. What could possibly go wrong? Right? Well, this is live ish. All right, so, because some of these things take a long time, and I didn't want this to turn into. Right. One of my goals for 2026 is to hopefully always keep shows at like 33ish minutes or less. And sometimes doing the live, live demos. Right. I'll just be sitting there chatting, waiting for something to finish for like 15 minutes. We're not going to do that to you, but we are going to at least look live. And I'm going to show you. I'm going to show you all hopefully a pretty good example or two exactly some of these seven rules. All right? And I'm doing a very, very simple use case here. And I think we're going to be. I. I think we'll tackle at least, at least six or seven of these kind of different rules here. All right? So, and again, as a reminder, if you are only listening on the podcast, this isn't a super visual walkthrough, but it might be helpful. Okay? So make sure for the video version, go to your everydayai.com or you can check the show notes of the podcast. Just click on it a little bit easier. Click on the episode page. All right, so let's start. So I already did this, right? I put the cake in beforehand. The cake's done, but I'm going to show you all the ingredients, show you how we put in the oven, all that good stuff. So what I started with here is I started by using connectors. All right? Or in this case, I think I'm on. Let me zoom out here. Yeah, I'm on my, one of my business plans. So in the business plan there's something called company knowledge. Okay, so those are previously, those were connectors, but in a team plan they're still kind of formatted a little bit differently. But okay, so this would be using a connector or an app. So what I did is I said in my Google Drive, find the Google Doc titled 2026 AI predictions. Please give me a high level overview of what's inside this doc. So you have a little drop down over in the, near the input area where you would put a prompt in ChatGPT. All right, so if you are on a, a team, you know, sorry, a business or an enterprise plan, you can toggle all your different data sources on or off. So what I did here is I, you know, toggled everything off except Google Drive, right? And then it went through and it found that. And I was using a thinking Mode. I used GPT for this one. I just used GPT5.2 thinking. Oh yeah, because on my, on my team account, I think I was out of pro queries. All right, so here's what it did. It went through and well, it pulled from that document and, and I can see, because if I hover over, I can kind of like cite it or source there and I can see it went through that. All right. And it's, it's actually funny how I came to this document, right? I didn't manually make this. I don't manually make stuff anymore. But I was actually just on Twitter with Chat GPT's Atlas browser and I just had it scroll Twitter for like an hour and just be like, hey, anyone that's sharing, you know, 2026, you know, AI predictions go through, you know, write them all down, put them in a document. So that's actually what this is. So it went through, you know, everyone from Sadia Nadella to, you know, Logan Kilpatrick who's been on the show a couple of times, Sam Altman, Ethan. Ethan Mollick. So you Know some well known people who are sharing kind of their thoughts on 2026 and AI. It went through, grabbed all this, then this simple GPT52 query, but using connectors went through and it pulled all this off. It's correct, nothing's hallucinated. I went through and looked at it. Everything's accurate and cited. Cool. So now here's where the context switching comes in. So what I did next is I switched over to Deep Research mode. All right, and if you haven't used deep research mode, you'll kind of love it. It's again takes seven to 18 minutes, give or take. Right. But in this case, I allow Deep research to go to my Google Doc and the web. So here's what I said. I said great. So after it went through, summarized that document. So I said, please research these main core recurring themes from the Google Doc titled 2026 AI predictions. Shoot for between 12 to 15 common themes you spotted from these predictions. And then I said find trends, supporting facts, gaps, connected dots, reasons the predictions may or may not come true. Also give me a category for the prediction. Right. So I'm having IT do some, you know, turning unstructured data into structured data. So I'm having IT give me a category for the prediction, a likelihood score out of 100 based on your research and a list of industry or sectors that these predictions may impact the most. Please make sure your responses are formatted in a cohesive and consistent way across the 12 to 15 common themes you identified. All right, so there we go. It first asked me some clarifying questions, which is something I love, I love that ChatGPT's deep research has done this since day one. I wish all the other deep researchers would do this because before it goes off on a 15 minute adventure, hopefully down the right route, you want to make sure it has the right information. All right, so I went through, I answered the questions, then it went and it got to work. So let me just see, is this the right one? It is the wrong tab. Okay, so same, same thing, just different tab. All right, so after, after that it went through and it did the deep research. All right, so let's skip over, let me zoom out a little bit here on my screen and let me skip over to number seven. Right. How you can leverage the chain of thought summaries as your secret weapon. So this, a lot of people don't know this because it's kind of hard to see. It's usually in grayed out font. Anytime you use a thinking model or anytime you do deep Research, in this case, it says, you know, research completed in 13 minutes, 28 sources, 160 searches. So I can click that and then it's going to pop out on the right hand side. Essentially this is a summarized version of chain of thought. So this is the difference between, you know, the old school transformer or non thinking models that are essentially just next token prediction. Right. You know, there's some other things. Top P, top K. Right. Not getting into that, but the thinking models think like a human. So I can go through and read it on the right hand side. So before it got started, it did, you know, went into my Google Drive, it thought about some things, went back into the Google Drive, right. So it, I, I can literally see how the model is tackling this problem. So this is the same thing if I had a team of researchers, but they couldn't think in their head. They had to just talk out loud. This is great, right? And this is the way I think you ultimately go from an average ChatGPT user or an average, you know, AI native team. Right? All those buzzwords to actually being able to crush the competition. The issue is, right, these models always change under the hood. Things are, you know, usually hopefully getting better, but definitely changing. So you have to be able to read how the model tackles this problem, what they do in the right order, all these different things. All right, so what we got from the output was a very impressive report here. It says the analysis of core themes in 2026 AI predictions. There we go. It went through, found some supporting trends and challenges for these different core themes that it identified from the original list off Twitter. That atlas went and found on its own. Pretty cool, right? All right, so I'm scrolling through these, you know, if you want, I'll probably share this in the newsletter today, so. Or no, you know what, if you Repost this on LinkedIn, I'll bump you to the top of the the everyday inner circle list and I'll send you all this stuff if you want just because it's pretty fascinating. It's good stuff, right? Okay, so going down, going down to the bottom, a long report here. Wow. Okay, so here we go. Now we're going into back to, I think number four, which was using projects and GPTs more than you think, but also a little more context stacking here. So what I did is hit the app key, all right. And then I have a GPT that I built called the SaaS dashboard canvas. So all this is, it's a GPT that I use frequently. I continually update more or less. I tweak it so I don't have to type out a long prompt each time and iterate. All this GPT does is it takes whenever information is in that context window, and it essentially builds the equivalent of a SaaS dashboard or a KPI business dashboard without you having to do anything. So it uses Canvas mode, right? We're not going into all the different modes, but, you know, I essentially have that enabled on the back end of the GPT. Again, you don't have to know code. You don't have to know anything. It's simple. There's actually a literal GPT builder. You can just talk to it and say, here's what I want this custom version of GPT to do. And then the cool thing like you just saw here, and I did that part live, right? Anywhere in a normal chat, I can just click that AT button and start typing. Just like if you're tagging someone on Microsoft Teams or Slack or anything like that, or social media, right? I can go find that GPT that I've given specific. A specific role to, right? I can put files in there, etc. But all this one does is it uses the entire context window. It uses Canvas mode, which can write and render code, and it's going to build me a SAS dashboard, and I don't do anything, right? So then I scroll down here. I see, again, looking. I can pop out the chain of thought, you know, saying, oh, I'm supposed to use Canvas mode and, you know, build something. And I can click the preview here. Ready, y'? All? Let's see. Is it gonna work? Bam. It works. Okay, podcast audience, this is really freaking cool. All right? It built a really slick dashboard. Let's see if it's interactive. Let's see if it works. I haven't tried it yet. Okay, that's. That's pulling the slider. Okay, so there's a. There's a search. Oh, this is really, really cool. Um, so there's a thing that says an average likelihood, right? Cause I had it quantify a lot of these. This stuff that I didn't want to spend the time to quantify and categorize, right? And what's crazy is technically Atlas, ChatGPT's browser, went out and found all this stuff anyways, put it in a document. Then I had ChatGPT go through this. This is. This is how I like to learn, right? I don't like reading plain text anymore. I like agents going out and doing things for me, bringing back, you know, I use my taste and My feedback, you know, my orchestration skills, whatever you want to say. But I love interacting with data. So I have an extremely nice looking dashboard based on all of this, right? So it says the average likelihood, the top impacted sectors, the highest likelihood. There's a search bar here, there's a drop down category that works. Very cool. There's a slider. So if I just want to see the ones that are, you know, that have a lower likelihood or if I just want to see the ones that have a higher likelihood of coming true based on the deep research, based on the, the GBT5.2 thinking based on the, you know, on the atlas scrape. Right. Very cool. So I can scroll through here. Cool looking dash dashboard. There's a strategy lens here with different tabs I can click on. This is an extremely impressive dashboard that it put together. So there you go. That's it, That's a wrap. I gave it to you. This isn't all of it, right? But if you can stick to these seven things, these seven rules, your personal growth, your company's trajectory, your businesses outcomes are going to drastically improve, period. Let me tell you again the seven rules and we're going to wrap up. Ready? Number one, do not use the free version of ChatGPT. Don't do it. Number two, you should almost always use thinking models. Number three, context switch between the right model mode or GPT. Four, use projects and custom GPTs more than you think you might. Number five, still use connectors even though they're apps. Use apps or connectors, whatever they're called technically. Number six, use chat GPT for teams. It is a cheat code. And then number seven, last but not least, leverage chain of thought summaries as your secret weapon. Read them iterate, reiterate, improve things. Dang, y', all. I hope this was helpful. Now you know how to use Chat GPT a little better than before. But if you really, really want to become an actual pro. You think this was good? The good stuff is inside of our free community. That's right. All right. And if you want earlier access than everyone else, and I'm sorry, so many people emailed me, I. Some I forgot to email back, some ended up in my spam. I did a terrible job. There's a lot of people waiting. I'm going to be working hard, working overtime getting people into the free community, getting people access to this course that is freshly updated and we're going to continue to update it. Probably anytime ChatGPT comes out with an update, we're going to update the course. It's going to stay. You take it at your own pace. It's pretty good, right? But if you want access, just repost this show on LinkedIn. I'll bump you to the top, get you in there as quickly as possible. And again, FYI, what do I. What do I repost this LinkedIn post. So if you're listening on the podcast, go look in the show notes. There's always something that says, you know, join the conversation on LinkedIn, find today's show. Go click that. Repost this. All right, and let's all dominate 2026 together by being a little bit better at ChatGPT than we were yesterday. Because it's more than just a personal tool. It's more than just an AI chatbot. Do strongly believe, right? Not just ChatGPT, Gemini, Claude, Co Pilot, everything else but Chat GPT, right? It is the future of how we all work. So let's all dominate 2026 together. I hope this one was helpful. Thank you y'. All. If you haven't already, please go to your everyday AI.com Sign up for the free daily newsletter. We'll see you back tomorrow and every day for more Everyday AI. Thanks y'. All.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going for a little more AI magic. Visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.