EP 583: ChatGPT’s New Study Mode: How non-students can take advantage

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. OpenAI recently released a new mode inside of ChatGPT called Study Mode. And although I think it's extremely helpful and useful for students and hopefully it'll fight off that old AI brain rot, I think that most people are overlooking the utility of this if you're not a student. So on today's show, we're going to be going over ChatGPT's new study mode and how non students, everyday business leaders like you and me can actually take advantage of this new mode. All right, it is time to put AI to work on Wednesdays. What's going on, y'? All? My name is Jordan Wilson, and welcome to Everyday AI. 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So ChatGPT's new study mode, I think probably bad naming, if I'm being honest. They probably just should have called this Learning mode. Because I think when you think study mode and OpenAI seemingly very much directed this towards students, and I get kind of the reasons why. Right. I think in academia and this is an area that OpenAI and other of the big AI players are trying to forge up big partnerships, you know, with teachers unions, with large educational institutions. So it's smart in one way to kind of be like, hey, like, you can use OpenAI for more than just getting answers. And I think that's ultimately what Study Mode is about. But what about for everyone else? Right? You know, I'm guessing the overwhelming majority of OpenAI users in chat GBT are not students. So many of you and us are going to look at this new Study Mode and be like, okay, well you know, I'll tell the student in my life that there's this new mode. But no, it's actually great for non students and we're going to be going over it today. So on today's show, I'm going to tell you what Study Mode is and how you can use it. I'm going to give a live use case of how I'm using Study Mode one example live. So hopefully that works. Love doing these things live. And then last, I'm going to give you three tips and tricks to get the most out of Study Mode, even if you're not a student. All right, let's get straight into it y'. All. And hey live stream audience, thanks for joining. And if you are listening on the podcast, this is one of those that you might want to watch the video version of. I'm going to try my best to explain what's happening on the screen. I am sharing my screen and we are going to be doing a live demo. So I'm going to try to do my best. So if you do want the video version, you can always go to your everydayai.com we put all of that on there on a website. You can listen to the podcast and watch the video on our website or you can check it out on the YouTube channel. So yeah, a lot of people are always asking like where's the video? All right, I just told you those two places. All right, so here is what OpenAI. Here is their description of Study Mode. So it says and this is from their announcement blog post. They said today we're introducing study mode in ChatGPT, a learning experience that helps you work through problems step by step instead of just getting an answer. Starting today, it's available to logged in users on free +Pro team with availability in ChatGPT.edu coming in the next few weeks, ChatGPT is becoming one of the most widely used learning tools in the world. Students turn to it to work through challenging homework problems, prepare for exams and explore new concepts. But its use in education has also raised an important question. How do we ensure it is used to support real learning and doesn't just offer solutions without helping students sense of them. We've built Study Mode to help answer this question. When students engage with Study Mode, they're met with guiding questions that calibrates responses to their objective and skill level to help them build deeper understanding. Study Mode is designed to be engaging and interactive and to help students learn anything, not just finish something. And I think that's the big takeaway of what OpenAI is hoping to kind of reframe the conversation around ChatGPT in academia. And one of the biggest things is what? Well, they didn't say it here in their little release, but I'll say the quiet part out loud, right? All students. All of them, right? Or I was like 99.9%. I'm sure there's one student out there that's like, not me, right? But almost every single student out There is using ChatGPT to write their papers. And without me accidentally going on a hot take Tuesday because it's Wednesday, the higher education, especially in the us is screwed. I'll just say it like, very simple. I've done a couple episodes on that in the last couple of months. But so many recent graduates, especially in 2024, 2025, are finding it hard to get jobs. And that's one of the reasons, one of the main reasons is employers are looking at recent graduates and they're saying, all right, here's going to be my. My AI whiz kids. And they don't know anything about AI because all they've used AI for is they use ChatGPT to write their papers and then they ultimately are learning less. Right? Kind of the, the viral epitome of this was UCLA graduation. This kind of video went viral. The after graduation, the camera cut to a student that had their kind of final paper up on the computer screen. And so, you know, I guess the cameraman was like, oh, cool moment, right? Here's their final paper. And then they swiped over and said, like, showed that it was from ChatGPT. Right, but that is not an edge case. That is, y'. All. I talked to plenty, plenty of students all the time. They're all just using ChatGPT to do their homework. So they're not learning enough, which is one problem. And then the other problem, you know, most higher ed systems in the US have no clue what they're doing. They banned CHAT GPT for too long instead of just teaching Gen AI basics. That's not today's issue, Right? Today's issue is this new study mode. All right, yes, I, I did reference this twice, but this putting AI to work on Wednesdays. This is our new Wednesday segment where I'm showing you how to use new modes, new features, inside kind of large language models like ChatGPT, Gemini, Copilot, Claude, et cetera. So let me know if you like this new segment? So that is the quick overview of what ChatGPT's study mode is. So you'll see here they don't really push use cases or even from a definition standpoint of non students, which I thought was a pretty decent mess here from OpenAI. But I get it, what they're trying to do. I'm not trying to say this is, you know, pr, but it's a little bit of pr, right? Because AI and you know, in general has gotten a little bit of a black eye when it comes to higher learning in the US because it took like two and a half, like it took universities two and a half years to learn that. Oh, yeah. Even when we try to ban AI or you know, when we say you can't use it, it. Oh, there's no way to police that. Right. A lot of, you know, universities were bamboozled into thinking AI content detectors, which were a thing, which they 100% are not. Right. So, you know, they kind of had this false sense of security for a while. And here we go. Students not learning as much. Right. They're just copying and pasting stuff from ChatGPT and passing their classes at a higher rate. So that's, I think, ultimately why ChatGPT and OpenAI didn't angle this toward the everyday business professional. But I'm gonna tell you today how you should be using it. All right, so let's look live. And again, this is a way that I'm using AI in my kind of day to day, right. I'm currently not in school. I do teach, you know, I did recently teach a course at DePaul University on AI. I'm not currently a student, but I have really enjoyed kind of study mode so far. So let's give, I'm gonna give one example here in live stream audience. Hopefully you can see my screen. If you could let me know, that would be fantastic. I think, I think we have it here. Like I said, podcast audience, I'm gonna do my best to describe what's going on, but if you want to see the video, we are gonna have that on our website. All right, so let me go to a different window here. Here we go. Okay, so I am in a normal chat GPT window for this. I'm using GPT4O, although I've never really used GPT4O. I always use, you know, 0303 Pro or 04 Mini if I'm in a little bit of a hurry. All right, so all I'm doing, I'm going to do A normal chat. And I'm saying explain the difference between RAG retrieval, augmented generation, and kind of this newer term or trend called context engineering. So I'm saying explain the difference between RAG and context engineering as it pertains to large language models. Focus on 2025 info only. So right now I'm in a normal ChatGPT conversation and I'm going to go ahead and kind of send this and we'll see the response that we get. I'm not going to read the whole thing, but what's happening right away? ChatGPT's searching the web and then it's giving me a. It says, here's a clear comparison in 2025 between retrieval, automatic generation and context engineering for large language models. So it breaks down rag. I'll just read the first part here, just so hey, we can all learn a little bit too. So it says rag. Rag is a technique where LLMs retrieve relevant documents from external sources, such as vector index documents, knowledge graphs, internal corpora at inference time, then augments the generation prompt with those retrieved passages. Right. A couple more bullet points and then we go down to context engineering. So it says context engineering refers to the broader system level design of what information a large language model receives. This includes system instructions, user history, retrieve documents from RAG tool metadata, API outputs, memory embeddings, even sub agent outputs. Then there's a couple more document, a couple more bullet points, and then there is a kind of chart here. It says relationships and key distinctions between RAG and context engineering. And then little bullet points about why it matters and a summary. Okay, so overall, this is a pretty good overview on, on the difference. But I can read that and maybe I'll learn it, maybe I won't, right? There's a saying, and if I'm being honest, this is a big reason. Not a big reason, but one of the reasons why I really wanted to start a podcast three years ago on generative AI. Because I wanted to learn it at such a fundamental level. And you know, there's a saying that you haven't truly learned something until you can teach about it. I love learning. I, I do say, even though I'm not a student, I'm a lifelong learner. I'm always trying to keep up with, you know, latest trends. And I've been like that my whole life. I, I love reading about technology, innovation, et cetera, but really learning and understanding, right? I'm one of those people, I like to, when I'm truly learning something, I'll print it out on paper, I'll. I'LL highlight it. You know, I used to make a lot of flashcards, right? So if I actually care about learning and if I were to do, you know, an episode on the difference, you know, or, you know, maybe doing a show on the difference between RAG and context engineering, you know, it's not the best comparison because it's two kind of unrelated things. Kind of related. Kind of unrelated. Right? But I, I probably the way I would learn this right now is to use something like Notebook lm, which I love, right? And I love having the interactive audio overviews and being able to ask questions. So this Study mode inside ChatGPT is a different way to do something similar. So now I'm going to run that exact same prompt inside again, GPT4O and I'm saying explain the difference between RAG and Context engineering as it pertains to large language models focused on 2025 info only. All right, I'm going to click go. And. 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 Genai. 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 built a straight path to ROI on gen. And you'll see here it spits out the information right away. So a couple things to keep in mind. It didn't do the same job, the study mode at browsing the web. All right, just keep that in mind because that's important. All right, so here we go. So I'm going to look now at the results from Study Mode. All right, so the first again, I'm not going to read every single one, but it gave a good first an overview and then it says retrieval augmented generation. The purpose is to enable large language models to Retrieve relevant external documents from a vector database and generate answers using that retrieved concept. All right, pretty good, pretty good. Then let me go down to context Engineering. So purpose it says manually or programmatically craft the prompt and context window passed to the model to optimize understanding and output without external retrieval. So you'll already see even in the way that it definition that it defines these terms Study mode by default, right? It takes a step by step approach, right? This is essentially just prompt engineering in practice without having to prompt engineering engineer, if that makes sense. So it's really going to break things down by default even if you don't ask for it in a much more kind of chain of thought or step by step way. It's much more organized by default. But then here I am, I'm going to kind of scroll to the end in the, in the study mode again it came with a chart with some differences, some bullet point definitions and here's, here's where it obviously is different. So I'm highlighting this on the screen here. Whoops. There we go for our live stream audience. So in the normal mode all it did, it just finished, right? It gave me the information. That was it. All right. In study mode it says let's make sure this. Click let or sorry, let's make sure this sticks. Want to find, want the large language model to find knowledge use rag. Want the large language model to understand and use context Better use context engineering. Then you'll see here is the big difference. ChatGPT is asking me questions. It is acting as a study guide, as a tutor, as a side by side assistant without me having to instruct it. Hey, make sure to ask me questions. Right? So it says would you like a visual chart quiz style recap or a real world example to drive this home? So I'm going to say give me a chart, which we'll see how it does. 40 is not known for creating charts. So we'll see how that goes. I don't think it's going to go well. So I'm going to say give me a chart and a quiz. All right? That's all. So I said give me a chart and a quiz. All right? So when I said chart, it didn't mean a visual chart, it just meant a literal text based chart with features and then the differences between RAG and Context Engineering and then a little quiz. So you'll see right now and hopefully you can understand immediately even if you're not, even if you're not a student, immediately how this could be helpful, right? Yes, Large Language models can give you the answers. Yes, they can. In the same way they can large language models can write your essay, they can do your work assignment, right? They can. Which is what a lot of companies are rushing to do, right? And then, you know, oh, we're worried about AI brain rot. Well, yeah, of course. And I've even talked about this personally, how sometimes the more and more I use large language models, I'm not using them as a shortcut per se. My biggest problem is retention, right? Doing this every single day might be hard to believe. I forget a lot, right? I've mentioned this on the show many times. Sometimes I'm trying to learn a topic, you know, I'll put it in chatgpt or Perplexity or Gemini or whatever. And one of the sources that it pulls from is from my own podcasts. I just forget things, right? Doing this every single day. And I've been using, you know, obviously cutting edge AI tech since the day it comes out, right? I forget so much. That's why something like Study mode for me is going to be extremely helpful, right? So there are some downsides, I would say, to NotebookLM, one of my favorite tools, right? And especially I think hands down the best tool for learning something, right? The ability to upload all of your sources, the ability to, you know, have conversations and interactive conversations with the AI overviews when you can join the conversation. Fantastic. But the downside of NotebookLM is you have to manually upload all of the sources, right? So its biggest strength is actually maybe a weakness, right? Because if I wanted to go through and learn, you know, kind of the differences between rag and context engineering in NotebookLM, what I would have to do is first I would have to manually go find the sources, right? Which isn't that hard. It would take a couple of minutes to get those high quality sources. But sometimes speed is everything. Sometimes I don't feel like taking two to five to 10 minutes to find all those high quality sources. So since Study mode came out for some things, it is taking the place of what I might Normally be using NotebookLM for, which for me is not good because I love going back to notebooklm all the time. Especially now with the new, the new updates, which we did go over, FYI, what episode was that? That was episode 578 last week. Some of the new updates where you can create multiple AI audio overviews, multiple video overviews, right? So I'm going back to NotebookLM a lot more than I was previously because you can, you can, you know, generate multiple, you know, AI audio overviews, AI video overviews, mind maps, etc, but sometimes I don't want to have to, especially if it's a quick hitter and I'm like, oh, I'm probably not going to reuse this a lot. That's something I would normally just use a large language model for. I would use Gemini, ChatGPT, you know, Claude Copilot, etc. Now I'm finding myself using study mode more because like I said, one of my problems is knowledge retention, right? I can retain, you know, the details and the bullet points for, you know, couple of days, right. But I consume so much information. This, for me, the study mode is great. So now I have a couple, a couple things on the screen here. We'll see, we'll see if I, if, if I get these. I don't know if I want to go through. All right, there's only five. I didn't read anything, FYI, that it put through. But hopefully I won't completely blow this quiz. Right? I know the basics of context engineering. It's kind of a newer trending term that kind of came about. So I'm going to take this quiz. So what happened here in Study Mode? I asked for the chart because again, it prompted me, hey, how do you want to take this? Let's learn, right? It's pushing me to learn. It's not just handing me answers, it's helping me actually break the concept down step by step to hopefully make sure I can retain the information. But now it's, it's quizzing me and it's, and it's, you know, responding back with the information in a new way. All right, so number one, and hey, live stream audience, if you want to take, take, take the quiz with me, let's do it. You know, go ahead, put your, put your, put your answers in the chat. So number one, which method would be more appropriate if you want a large language model to answer questions? About 5,50,000 internal PDFs. I'm going to say that's one is a rag. All right, so I'm not going, I'm hitting a shift enter here. I'm going to put all my answers in at once. So two, it says you're building an AI assistant that uses a calculator tool. It needs to maintain state between user turns. What technique do you use to manage behavior and memory? So I would assume that is, number two is context engineering. All right, so number three, which approach requires semantic search and a vector? Your database. That was an easy one. That one is a rag. All Right. Number four, you want to inject two to three well chosen examples into a prompt to guide model behavior. Which method is best? That is going to be B. Context Engineering, I hope. All right, five. True or false. In 2025, many advanced AI agents use both RAG and Context engineering together. That's true. All right, so here's what I did. Podcast audience, it gave me a quiz based on the information in the chat. So let's see, I'm going to go ahead and respond and let's see how I did. All right, so the good thing is it's going through and it's kind of checking my work and luckily it would have been a little embarrassing if I got all these wrong. I got all of them right. But the good thing is it gives you more context. It doesn't just say right, right, right. Okay, so as an example, number one, you answered a rag. That's correct. If you're working with a huge volume of documents like 50,000 PDFs, rags essential context Engineering can't scale to that many tokens. Retrieval is the only practical way. Right. So that's great. So not only is it telling you it's number one, it's creating a quiz to make sure you retain the information. You're able to actually take the quiz. Number two, and it graze it. But then it gives you additional context. And something that I didn't like skip over but I haven't talked about yet is how you can personalize this to you, right? I just started off hot and just said, hey, here's the difference. Right? But what you would want to do, whether this is in your custom instructions or not, or you should share some information with ChatGPT first, say, hey, here's who I am, here's what I do in my role, here's what I'm trying to learn. Here's some sources that, that I'm working at now. Explain the difference between RAG and Context engineering, right? Because then not only are the responses going to be personalized to you and bespoke and just really hopefully resonate better, but then also so will the quiz and the follow up. So this is great. Again, very simple, right? This isn't something that you're going to look at and be like, oh my gosh, I haven't seen anything like this before. Because all this ultimately is. It's prompt engineering, right? And OpenAI even did say this in their, in their announcement post. They said all this is all study mode is it's custom instructions, right? So there were actually some great GPTs in the GPT store that did essentially this. And the good thing here too, right? I didn't get any of these wrong, but if I would have gotten gotten any of them wrong, it would have. Instead of just at the end of this, let's see what it said at the end. Okay, so at the end it said you're clearly solid on the core distinctions. Want a next challenge like build your own rag versus context engineering scenario, A deeper dive into tools or Common mistakes in 2025 Real world product examples. Right. So it's still taking it to the next level. But the good thing is if I get, if I got a couple, two or three of these wrong, it's going to immediately start building a new lesson plan for me based on the given context that I give it. In this example, in this live demo, I didn't give it any context because I'm trying to go through these kind of quickly. All right, so that's Study mode at a high level. Again, if you want to see the video of this, make sure to go to your everyday AI dot com. Now these are part of my tips here. So I'll actually flip back over and then I will describe these tips. Okay. Yeah. Actually first let's go over business use cases. All right, so a couple of business use cases. One, a simple one, Market analyst. Right. A rapid competitor teardown. So how many times have you been like, hey, you're in the big meeting and you know, your boss asks you, hey, what did our competitor do with this? And you're like, oh, I read that, but I don't remember. So what you could do is upload your competitors, you know, annual report from last year and ask Study mode to walk you through Socratic style, through extracting different differentiators, SWOT grid, and two, positioning statements you can reuse in a pitch deck. It's a great use case. Right. Interactive learning is always stickier than just reading information. Right. The more that you engage and converse with knowledge, right. This is like a whole new thing of, of, you know, having large language models because it's like being in a room with a hundred of the smartest tutors in any subject that you choose, right. If you, if you know how to do it correctly. So just interactive learning in business is huge. All right. Another business use use case, a new higher orientation kind of valid core values drill. So what you can do here is you can upload. So let's say you have a bunch of new hires, you can upload all your super not boring onboarding docs. They're Boring. You know, your company mission, your value statements, org chart, all that stuff. And then have employees use Study Mode and essentially quiz them, right? Until they can actually learn and retain and be able to spit back each value verbatim. So in the same way that I showed you, right. It created a quiz on, you know, on the difference between rag and context engineering. You can do the exact same thing with your company's data that you are onboarding new people on. All right, and my third simple use case here for sales reps. How about a catalog flashcard, right? So how many times are you just opening up a spreadsheet, you know, looking at different skus? Or maybe it's different regions that you serve, right? And you're just constantly having to refer back to a boring document. All right? Instead, Study Mode can turn those specs and price tiers into adoptive style flashcards. So you can work on those weak spots, right? If there's always certain services or things that you, your company sells that you, you are always like, ah, man, I always forget that in a sales meeting. And I'm always like, oh, I'll have to follow up with the answer, right? That's happened to all of us. So use Study Mode and go through like I did, right? You saw that example. I got five out of five. Right? But, you know, let's say you do a quiz of 10 things or a quiz of 20 things. The good thing is Study Mode will spot trends, right? It seems like, hey, you're always getting, you know, products from, you know, before 20, 24. Wrong. It seems like you're retaining all the information about your, your company's newest products, but it seems like you're struggling with older products or products from different regions. Right? So again, it's going to be able to spot trends and weaknesses that you may not even be aware of. And you don't even have to do anything. It's autopilot and it's going to take it over and help you and help you become better at it without even having to do anything yourself. All right, so now let me go over three tips and tricks. All right, so. And I'm going to show you some of these real quick live. We're not going to drag this on, but use the O3 model. So remember what I said, Study Mode is essentially just custom instructions. So what that means is you can use any model in Study Mode. All right, let me jump over, let me jump back over to ChatGPT and I'm going to do my, the original one. Explain the difference between rag and context engineering as it pertains to large language models. Focus on 2025 info only. All right, so let me go ahead. I'm going to open a new chat. I'm going to switch to the O4 model. The way you use this, I should have said this at the beginning, dang it. Right? But you need to go to your tools in ChatGPT and then just click the study and learn button. Okay, so now when I do this in O3 for the audience that was watching it, do it live using the 4O model, which is a transformer model versus an O3 which is a reasoning model. Now you'll see it's taking its sweet time and it's doing some step by step research again almost every single time. The thinking model is going to be much, much better than the non thinking model GPT4O. Right? So it's going to take a while, but it took about a minute here and now study mode, I have it active in the O3. I'm not going to go through and read all this because I don't want to drag this episode on, but just looking at it already, I can tell it is much better. It is much better. All right, so that is one of the tips and tricks. And then let me show you another example of that and how you might be able to use that in a different way. So model switching. All right, so what that is, it's actually a huge benefit that chat GPT and OpenAI have that most of the other big players don't have and they all should. You can switch models and modes inside ChatGPT and keep all the same context. So in this example, I did a deep research on this exact topic, right? So you might be saying like, okay, why would you, you know, do a deep research on this and then switch over to study mode? Well, when you do deep research, you have really granular fine tuning control over the information that gets pulled in, right? Because number one, you can go have it pull in specific information that you want, say only use reputable sources or only sources. You know, in this case maybe I only want research papers, I only want journal articles, et then research mode always asks you questions. So it is much better just the quality and quantity of information available versus if you're just doing a normal study mode, it's just going to be like a normal GPT4O response or a normal O3 response. So in the same, in the same vein of why would you ever use deep research? Well, it's much better, right? In the same way, if you start with deep, deep, deep research, and then essentially model switch or mode switch over to study mode. It's going to be great. So in this example on my screen here, I just did a deep research here. And then I'm just going to switch over and I'm going to do the study and learn. And I'm going to say use the context above only, right? So now it's going to use all of this content above that it pulled from the deep research and it's going to go through and do the exact, exact same thing. So in the same way that I said number one, tip and trick, you can use O3, which I don't think. I think a lot of people are just overlooking that because this is simply custom instructions. Well, take it a step further. You know, run deep research first. Start with your own personalized context first. Then do a deep research, Then do study mode. My gosh. Like go through those three business use cases that I just did first. Add your own personal context, any documents. Then do deep research on whatever topic that you're trying to learn or competitor. Then do study. The results are going to be much better. That's how I do it. So, hey, this is putting AI to work on Wednesdays. I'm showing you how I use it. Use it like I use it. You're going to like it. All right, and then our. And here, we'll scroll down here. Good stuff here. All right, then let's go ahead and do number three, tip and trick. Don't overlook it uploads. All right. Oh, but hey, I did give the example of like, oh, you know, uploading a math problem that you just can't solve. Sure, that's okay. How about all those brainstorming sessions, right? Maybe you walked in at the end or maybe something is just over your head. Right? Take a picture of that. Again, I would first start with some context, some back and forth. Really take advantage of the context window of ChatGPT, but then use study mode, right? So it's not just the information that you enter, it's not just what it pulls from the web or its own internal database, but uploading screenshots, photos, PDFs, documents, etc. In order to kick off study mode. I think those are three tips and tricks that are really going to help. All right, that's a wrap, y'. All. So, to quickly recap, here's what we went over. ChatGPT's new study mode. It's technically kind of basic. It's just system instructions. But I think it is sorely needed. And it's not just for students. I think this is a mode that all of us should be using, right? Especially when it seems like information has become transactional, which is kind of weird, right? If you're someone mid career, the fact that the world's most powerful information has become transactional is almost like a. I'm not going to say like a sad statement, but it's weird, right? The fact that I can learn personalized, conversationally, anything, it's almost unheard of, right? To remember having to, you know, ride my bike to the library to look at like an encyclopedia if I wanted to know something specific. Right? Yeah. I age myself there. This is huge. So being able to turn ChatGPT into a study guide to help you actually retain this mountain of information that we have at our fingertips. Although on the surface it's literally just system instructions, right? It's actually, I think much more than that. And I think where maybe the biggest gains can be made is not students. Even though OpenAI very clearly is making this for students, because I think that they want to be very educational friendly. On the surface, I think this is. Business leaders are going to get probably a little more utility out of this because here's the reason why and why I think we can start turning information consumption away from being transactional via large language models and transformational. Because when you can personalize it and it's literally like having the world's hundred smartest tutors on any subject instantly, right? Whereas before it wasn't really like that. It never really seemed like that with an AI chatbot. It just seemed like, all right, well, I asked the question, it gives me the answer, and hopefully I remember it when I need to. So I hope this episode was helpful. And do you like this new thing? Do y' all like the new layouts? Right? We do the news AI News that Matters on Monday, Hot Take Tuesday, where I just riff on something, give you my opinion on something trending or happening in the AI world. On Wednesdays, we do these more live demos, actual use cases. I show you all how I'm using a new AI tool or mode and encourage and give you examples on how you can do the same. And then for the most part, Thursdays and Fridays, we do cut out of interviews where you can learn from some of the smartest people in AI. So I hope this was helpful. Going over ChatGPT's new study mode and how new students can take advantage, please go to your everydayai.com Sign up for the free to Handling newsletter. We're going to be recapping the best from today's episode, as well as some more information that we didn't get to. If you're listening on the podcast, make sure if you want the video version, we're going to be linking to it in the free newsletter@your everydayai.com or you can just go check it on the website. So thank you for tuning in. Hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'. All. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. 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