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Unlocking the Potential of OpenAI's Deep Research Updates for Business Growth
In a rapidly evolving world of AI, decision-makers and business owners are constantly on the lookout for tools that can provide a competitive edge. One such groundbreaking development is OpenAI's Deep Research updates. This isn't just an incremental improvement; it's a transformative leap in how businesses can leverage AI for comprehensive research and strategic planning.
The Significance of Access
Recent updates have made Deep Research accessible to all paid users of OpenAI's services. Previously limited to the $200 a month pro plan, this powerful tool is now available to users on the $20 ChatGPT Plus plan. This democratization of access means that businesses of all sizes can now tap into an AI tool capable of synthesizing vast amounts of information and performing complex research tasks.
Harnessing the Power of Enhanced Research Capabilities
Deep Research is not a new model, nor is it a mere feature upgrade. It represents a new era of AI utilization by employing advanced reasoning tools that can navigate extensive datasets and provide actionable insights. For businesses, this means the ability to perform detailed market analysis, uncover latent opportunities, and make data-driven decisions without the extensive time investment typically required for such tasks.
Advanced Data Analysis and Customization
One of the standout features of the recent Deep Research updates is its improved ability to work with complex datasets. Whether it's evaluating large volumes of search query data or understanding website performance metrics, Deep Research can dive deep into the specifics, identifying trends and providing recommendations tailored to specific business needs. This level of customization allows businesses to refine their strategies with a precision that was previously hard to achieve.
A Game-Changer for Content Strategy
For those in the content creation space, the advantages of Deep Research are particularly noteworthy. By analyzing search trends and user behavior, this tool can help businesses identify content gaps and opportunities. It can suggest highly specific, trend-aligned content ideas that are not just relevant but also timely, ensuring that your content strategy is both proactive and reactive in addressing consumer interests.
Strategic Implications for Business Leaders
The introduction of accessible, advanced AI research tools like Deep Research empowers business leaders to make more informed decisions. By understanding and predicting market movements, companies can position themselves as leaders rather than followers. The capability to delve into high-value opportunities and strategically guide business development is enhanced considerably, creating a robust pathway toward sustained growth and innovation.
Conclusion
Incorporating OpenAI's Deep Research into your business strategy is more than experimenting with new technology. It's about embracing a tool that can fundamentally change how you interact with data and make decisions. As businesses strive to stay ahead in an increasingly competitive landscape, leveraging AI for deep research provides a substantial edge, fostering innovation and driving growth in ways previously imaginable only in fiction.
Topics Covered in This Episode
1. Accessibility of OpenAI’s Deep Research
2. Deep Research Capabilities and Features
3. Use Cases for OpenAI's Deep Research
Podcast Transcript
Jordan Wilson [00:00:16]:
I think one of the biggest AI updates of the year so far just dropped, and hardly no one's going to notice. Because it's not a new model. I'm not talking Claude SONNET three point seven. I'm not talking GROC three. It's technically not even a new feature, but this is OpenAI's deep research updates that just dropped. It's exponentially more powerful, but the big news here is actually the access. Deep Research is now available to all paid users. So, yes, if you are on the $20 ChatGPT plus plan, you now have access to what I think is probably the most useful AI tool that I've ever used, and I've used thousands of them.
Jordan Wilson [00:01:13]:
Alright. So I'm excited to go over today, not just going over this access. Right? And now there's hundreds of millions of people that now have access to this tool that maybe couldn't, you know, shell out the $200 a month for the pro plan, but also to look at some of the new features inside of Deep Research. Alright. I'm excited for this one. I hope you are too. If you're new here, welcome. Thank you for tuning in.
Jordan Wilson [00:01:40]:
My name is Jordan Wilson, and you're listening to Everyday AI. This thing's for you. It's your daily livestream podcast and free daily newsletter, helping everyday people like you and me not just learn generative AI, but how we can leverage it to grow our companies, to grow our careers. And I want you to be the smartest person in your company at AI. That journey, well, it starts here, but then it continues. Right? You can learn everything here, but how you leverage it, it's on our website. That's youreverydayai.com. Sign up for our free daily newsletter.
Jordan Wilson [00:02:12]:
We're gonna be recapping today's shows, as well as keeping you up to date with everything else that you need to know. Alright. Before we jump into what's new at Deep Research, and there's a lot, let's first go over as we do almost every single day, what's new in the world of AI news. So first, Meta is considering a $200,000,000,000 AI data center project in The US. So according to the the information, Meta is planning a $200,000,000,000 data center campus for AI projects. Potential locations include Louisiana, Wyoming, and Texas with executives visiting sites this month. This would be one of the largest AI infrastructure investments yet as Meta aims to expand its AI capabilities. So Meta CEO Mark Zuckerberg recently announced 65,000,000,000 in spending for AI infrastructure in 2024.
Jordan Wilson [00:03:08]:
This is obviously a lot more. Competitors like Microsoft and Amazon are also ramping up, AI data center investments with budgets of 80,000,000,000 and 75,000,000,000 respectively. Although it was reported, that Microsoft might be scaling things back a little bit. And this comes just hours literally after the Apple news that Apple was investing 500,000,000,000 in AI infrastructure. Alright. Let's go from big money to no money. So Microsoft Copilot is expanding its free access to advanced AI powered by OpenAI's o one model. So Copilot is rowing rolling out free unlimited access to its Think Deeper feature, which is powered by OpenAI's o one model, and it offers users advanced reasoning tools to handle complex decisions and tasks.
Jordan Wilson [00:04:06]:
So think deeper if you haven't, used it, and it enables in-depth analysis for decisions like comparing electric cars, planning career moves, or evaluating home renovations, helping users make smarter data driven choices. So this new update also includes unlimited use of the advanced voice feature, the Copilot version of it, allowing hands free extended conversations for tasks like practicing languages, mock job interviews, or real time recipe guidance. I've actually used it for that many times. So Copilot Pro users maintain early access to experimental features and better performance during peak usage alongside integration with Microsoft three Microsoft three sixty five apps. So, yeah, pretty crazy. Copilot just said, hey. We're gonna give everyone unlimited access to advanced, to their, voice mode and to their think deeper, which uses o one. You heard that right.
Jordan Wilson [00:05:07]:
Unlimited o one usage for free because, yeah, you don't even get unlimited o one usage on the $20 a month ChatGPT plus plan. So pretty crazy. Alright. Speaking of new things for free, one last piece of news, OpenAI has also introduced their free version of advanced voice mode. So the advanced voice mode in ChatGPT is much better than the voice mode in Copilot even though it's based off similar technology. ChatGPTs is just much better. So, OpenAI did say though it is going to the free version is going to be based off of GPT four o Mini, a lighter cost effective model than the paid version of advanced voice mode, which is based off of GPT four o. So again, the paid plan gets the advanced voice mode based off GPT four o, and the free version gets the mini mode.
Jordan Wilson [00:06:03]:
So free users will see a preview of advanced voice mode displayed across the platforms, though OpenAI has not specified exact usage caps. The strategy is seemed designed to attract new paid users while also maintaining server demand. Don't worry. If you're that, $20 a month plus subscriber, you still retain full access to the GPT four o powered advanced voice mode. So they're not making it, you know, a mini for everyone. They're just creating a essentially a light version of advanced voice mode, for free users. Alright. So, we're gonna have a lot more on those stories and a ton more in our daily newsletter.
Jordan Wilson [00:06:45]:
So if you haven't already signed up, make sure you go to your everydayai.com. Alright. I'm excited for this one. Live stream audience. I hope you are too. You know what? I'm curious, at least for our livestream audience. Are you using the free version of ChatGPT? Are you using the $20 a month, plus version, or are you using the $200 a month pro version? Or maybe you're on an enterprise plan. You know, I'm I'm always curious, just so everyone knows.
Jordan Wilson [00:07:18]:
I use them all. Right? I have free accounts. I have paid accounts. I have teams accounts. I have enterprise accounts because companies, you know, Fortune 500 companies, hire us to teach their hundreds or thousands of employees how to use ChatGPT because this is all we do. And I also have a pro account. So I have every single tier. I use ChatGPT every day, and I wanted to put that out there, to talk about deep research because I've been using it since it came out, since the day it was released, February 2.
Jordan Wilson [00:07:52]:
So like I said, up until today, Deep Research, has only been available if you've had that $200 a month pro plan. So very few people have been able to actually take advantage of deep research. So here is how OpenAI describes deep research. They say it is an agent that uses reasoning to synthesize large amounts of online information and complete multistep research tasks for you. It's good. Let me just say that, right? Actually, first, let me, kind of set the stage and then I'm gonna jump straight forward into deep research. Alright. So like I said, right now, the limits have also changed.
Jordan Wilson [00:08:40]:
So, previously, if you were on the ChatGPT Pro account, you had 100, deep research queries a month. Now that's been up to a 20. And now starting today, if you are on any other paid plan, so, ChatGPT plus, Teams, Enterprise, or EDU, you get 10 deep research searches a month. So it's not a lot, but follow along with what I do and it's going to make it worth it. And soon, CEO Sam Altman, OpenAI CEO Sam Altman has said that free users will get two a month that has not rolled out yet, but plus Teams enterprise and EDU, you now have access to, by far, it's technically even the most powerful model in the world. Because as far as I know, o3, what this is based off of, has not been benchmarked. So, we've seen, o3 Mini and o3 Mini High benchmarked from OpenAI, and this is their, advanced reasoning model that came after, o one. Right? So we went, o one, o one pro, skipped o two because of some copyright, reasons, and now we're at o3 Mini.
Jordan Wilson [00:09:56]:
And o3, the actual o3 full model is not available except in deep research. So it is a fine tune version of o3. It is mind bogglingly good. So we're gonna do this one a little different. Livestream audience, I need your help, please. Let me know if you can see my screen. Also, I'm going to be bouncing, between a couple, a couple windows here, so hopefully this works out okay. Nothing more I love than doing, live demos.
Jordan Wilson [00:10:27]:
That's a little little bit of humor. I'm actually not the biggest fan, but you all reach out to me all the time and say the live demos are super helpful, so I'm gonna do it. Alright. So here's what we're gonna do. I'm gonna get this started. I'm not gonna read the full prompt to you yet, because it's probably going to take a while. Alright? But here's essentially the prompt that I'm putting in in, podcast audience. I've opened my ChatGPT account.
Jordan Wilson [00:10:57]:
I'm on my, pro account, but it doesn't matter. I could be on my, you know, any of my other, paid accounts. Alright. I've pasted in this prompt. So one thing that might be a little confusing, and I actually wish that OpenAI would clear this up. So as an example, you have your different modes. Right? So, you know, you have your GPT four o, GPT four o with task, o one, o3 mini, o3 mini high, o one pro, etcetera. Right? You can click deep research.
Jordan Wilson [00:11:26]:
It's actually a button, that is right under where you put your text in. Okay? Which is a little confusing because when you click the deep research button, it still shows up as whatever model you're using. So as an example, I can be an o one pro, and I can click that deep research. That doesn't mean it's using o one pro. So, it's a little, it's a little confusing. But, essentially, once you click that deep research button, it should be down there by the search button. So look for the little telescope. Right? And if you don't have it yet, you know, try logging out of your account, logging back in, and it should pop up there.
Jordan Wilson [00:12:05]:
But essentially, once you click that deep research, icon, it's going to override whatever, you know, model or mode that you chose in the model selector. So it's the this is the only instance that does this inside of, ChatGPT. It's a little confusing if I'm being honest. Alright. So here's what I'm gonna do in this long prompt, and I'm gonna show you, some of the things that I'm doing. Okay. So I've exported a ton of data here out of Google Search Council. Let's see.
Jordan Wilson [00:12:36]:
How many okay. So I have about 6,000 cells here of data in spreadsheet one, and then I have a spreadsheet two here. Let's see how many rows of data. It's probably roughly the same. Let's see. 8,000 rows. So I have just under 15,000 rows of data. So all this data is well, it's it's a lot.
Jordan Wilson [00:13:00]:
So this is our, for our website, youreverydayai.com. This is our Google Search Console data. So, I've been doing SEO on and off. I mean, technically, I've been doing it for, like, twenty five years. I've been getting paid to do SEO in some way, shape, or form for more than fifteen years. So I'm a dork. I spent a lot of time in Google Search Council, and this is one of the reasons why I want to do this in deep research. So what I want you to think of, as you're staring at, all of these numbers, on the screen if you're joining us live, think about tasks that you do all day that require a lot of research.
Jordan Wilson [00:13:41]:
For me, I do a lot of research on what type of content that I'm going to cover. Right? So all of our podcasts, right, we put the transcripts on our website. We put the YouTube video. We actually put the the the podcast itself. So you can go to our website. Literally, it's for free. You can go listen to 500 episodes, read our write ups, look at the transcripts, watch the video. It's all on the website.
Jordan Wilson [00:14:07]:
So essentially, you know, we hope to attract a lot of, search traffic by putting all of this information for free on the website. But I do spend a lot of time researching, new content types that we should be covering, based on a lot of things. So I still do a lot of old school manual research. Well, I did before deep research. So I say all that because I'm trying to invite you into my world. I'm always, using some advanced Boolean searches, to find, different trends and and all of these things of things that we should be cover, things we should be covering more, things you all care about. You know, we take requests in our newsletter. We do polls, say, like, hey.
Jordan Wilson [00:14:48]:
What do you want me like, what do you want us to cover? But I still do a lot of research. So this is an actual use case that I am refining, to hopefully use a lot. So it's it does a couple of things. It's trying to improve areas, where we were getting a lot of traffic before, but maybe we don't anymore. Right? So maybe we used to get, you know, I don't know, a hundred people coming in from mid journey, and we don't need more. Right? It would take me a lot of time to go through this data and to start piecing all these things together because we have thousands of web pages, and we technically rank inside of Google search for thousands of words. So let me just give you one one example. Right? So, something that brings in a decent amount of traffic to our website is the term ChatGPT free.
Jordan Wilson [00:15:36]:
Right? So usually about three times a year, I do a podcast that is just ChatGPT free versus ChatGPT paid. I do it for a couple of reasons. One, it brings a lot of users to our website, and they find our helpful content. But number two, ChatGPT changes what's free all the time. Right? I it was just one of our news stories. So this content often becomes stale. So think of that. If you have thousands of words that bring in organic traffic to your website, it's it's changing all the time, especially in something as fast paced as AI.
Jordan Wilson [00:16:10]:
This changes all the time. Alright. So essentially, I have these two different spreadsheets. I'm going to be exporting them, and then I import them into Deep Research. And I'll read this long, this long prompt that I'm putting in here, but I wanna get it started. So I have this prompt. I'm going to upload, these two files. Alright? And I'm gonna explain this, but the first thing that ChatGPT is gonna do is it's gonna ask me questions.
Jordan Wilson [00:16:40]:
Right? Which I love. So, without getting into all of it right now, I'm essentially having ChatGPT spot trends in my data and then go do a bunch of research, right, and come back and report to me. So one thing I like about OpenAI or, you know, ChatGPT's deep research, before it gets started, because sometimes it can take anywhere from five to thirty minutes, it asks you questions, clarifying questions. So I need to answer those. So I'm gonna go ahead and answer them live. It's gonna be shorter answers than I would normally do because I don't like typing live. So number one, it says SEO goals. Besides improving rankings and traffic, do you have specific conversion goals? So I'm gonna say more traffic, and newsletter sign ups.
Jordan Wilson [00:17:24]:
Okay. Then number two, it says competitive landscape. Are there direct any direct competitors you want me to consider when analyzing ranking potential? No. Three, content focus. Are you prioritizing any particular AI related subtopics? For example, business AI applications, generative AI, AI tools, ethical AI. I'm gonna say pretty much anything related to AI, GenAI, AI tools, LLMs, etcetera. Alright? Then number four, content types. Are you focused on long form blog posts, pillar pages, guides, videos, or other I'm gonna say all.
Jordan Wilson [00:18:06]:
Focused on all of those things. Alright. And then number five, it says keyword difficulty tolerance. Are you open to targeting high difficulty keywords with long term potential, or do you prefer lower competition, quick wins? So I'm gonna say a mixture of all. Okay. So what I wanna do now before I get back into, kind of the rest of the show, I wanna make sure that deep research is starting, so then we can check back in on it in about ten, about ten or fifteen minutes. Hopefully, it should be done. So you'll see here it's giving me a positive message that says starting research.
Jordan Wilson [00:18:44]:
I always like to wait until I actually see this bar start, and then you can click on this bar, and this is great. And you can actually follow, deep research step by step activity to see how it researches, and then you can also go and click on the sources tab. So right now, it's just compiling sources. I don't see much activity yet, but it does look like it's about to kick off because, we have a heading that says SEO analysis and future content strategy for everyday AI. Alright. So I think we are good. Alright. So let's jump back in and go over a little bit more about Deep Research in general.
Jordan Wilson [00:19:28]:
And let me answer the question that I don't know if any of you are thinking, but I'm just gonna go ahead and answer it. OpenAI's version of Deep Research is the nineties bulls. Unfreaking stoppable. Right? Yeah, there's some other teams. There's some other versions of Deep Research that have their pros. Right? But OpenAI's version of Deep Research is the pro, period. Right? So I've covered them all. And like I said, I had been using OpenAI's Deep Research since the day it came out.
Jordan Wilson [00:20:04]:
I've used it almost every single day since it's came out, even on the weekends. It is very hard for me to do much of anything, if I'm being honest. You can imagine as someone that covers AI every single day, the amount of research that I do, the amount of time, that deep research has giving me has given me back, I cannot even begin to compute it. I would need literal GPU computes to compute how much time this has saved me. But I've covered all of them. I've given each and every one of these except, some of the newer ones, but I've given the main deep research tools their own dedicated show. So even if you wanna listen, you can go listen to episode four twenty five. Google's deep research was the first deep research tool, came out in December.
Jordan Wilson [00:20:52]:
You can go listen to four fifty four when I did a deep dive on OpenAI's deep research. Alright. Four sixty four, I covered perplexity deep research. And then the next day, I did a deep research throwdown, perplexity versus Google versus OpenAI. Now I'm sure a lot of you are gonna be like, yo. What about Grok? Grok is amazing. Grok has a new deep search. Grok? No.
Jordan Wilson [00:21:16]:
Don't use it. No. I mean, if you use it, use it with, like, like, a grain of salt that's bigger than this pot can that I'm holding on screen. Here's why. Grok deep search is largely based off Twitter data. Yes. It browses the Internet, but it also browses Twitter, which is bad. Right? Studies have shown that Twitter is the number one in terms of misinformation and disinformation amongst all social media networks.
Jordan Wilson [00:21:47]:
So I'm personally, and I would advise you, again, huge grain of salt before you jump on board and you're like, oh, grab grok deep search. Right? I wouldn't. It's almost like searching Google in reverse order. Right? Page one is usually the most highly authoritative, pages. Right? If you're searching for something manually on the Internet, and then when you're on, like, page 30, you're like, where am I? That's what it's like, I think, if you're using axe or Twitter posts to search something for business, I don't know, unless you're trying to search something pop culture or a recent news event, I would not use, Grox, deep search for anything if I'm being honest. But what I'm trying to say here is OpenAI's is in a league of its own. Alright? There's certain things. Google Gemini, deep research does great.
Jordan Wilson [00:22:37]:
There's certain things, perplexities, deep research does great, but it makes up so much. OpenAI's deep research, I think, is the AI tool of the year. It's early twenty twenty five so far. But the amount of time that it can save the average everyday person, mind boggling. It it really is. Right? I think so many of us either, number one, don't realize how much time we do spend researching something, or number two, we really only scrape the surface because it is so time consuming to research things at the depth that we may want to. So instead of doing a level research on a project that you need or on a on a, you know, on a on an assignment that you're completing and you're spending a, you know, couple hours on, you just might not have the time to weed through twenty, thirty, 40, 50 different websites, make smart decisions between those searches. Right? And and, you know, think of it like I think of deep research, OpenAI's version, like a fork down a road.
Jordan Wilson [00:23:43]:
Right? You go up and you meet a fork in the road. But instead of it forking into two, it's forking into four. Right? And that is when OpenAI's model, o3 model, makes a decision for you. Right? So it doesn't just take this wide, you know, cast a wide net, kinda like the Google deep research does. It makes very smart informed decisions. It visits one page, it makes a smart decision and goes to another page. And sometimes, somewhere along that tree, it will go in a different direction that maybe you or it thought it would originally go because it acts like a smart human researcher. It's fantastic.
Jordan Wilson [00:24:27]:
Alright. Let's keep this going and talk about what else is new. So number one, the biggest new update here that you need to keep in mind, I already said, it's out to all paid users. So there's gonna be, I believe hundreds of millions or at least tens of millions, of paid users that are gonna get access to deep research right now. That's number one. Number two is now it can embed images, with citations in the inputs. Alright. That may or may not be helpful for you.
Jordan Wilson [00:24:58]:
If you're a visual person or if there's, visuals that are highly relevant to what you're trying to do, research on, I'm sure that could be helpful. But the thing that I'm interested in and that I showed in this demo is it is now better at understanding and referencing uploaded files. That's huge. That is a a huge update that I think is going under the radar, and that's why I did this little demo that I did. Also, OpenAI did release a deep research system card. Before we talk about some of the things that are in that system card and some of this new information that we got. Right? So that's more or less a system card is a technical report, essentially, that research labs put out on different models. Alright.
Jordan Wilson [00:25:45]:
So we do have that. But first, I'd like to explain the difference between some of these new, agents that OpenAI has released and agent esque behavior. Alright. So OpenAI has released tasks. So that is when you can schedule open, schedule ChatGPT, specifically, g p t four o to go do anything semi autonomously. Right? You schedule it, but then it does it. So you could have it do do it every day, have it go do something at 9AM. You can't schedule deep research.
Jordan Wilson [00:26:18]:
You can't schedule operator. But in task, you can go have GBD four o do anything that you want. Operator is an agent. Okay? Operator will use an actual virtual computer. So that is a little different. Deep Research is not using a virtual computer per se, and you can't have it, you know, go log on to your, you know, your email or your LinkedIn account or something like that, like, you can with operator. You can have operator, you can take over the screen. You can log in to certain things with your credentials, have it perform tasks for you.
Jordan Wilson [00:26:55]:
Deep research isn't like that. Deep research is literally something that's just gonna do a bunch of research for you. Alright. So a little bit more on how deep research functions. So and a lot of this is from the model card. Some of this was already known. So it is based on o3. This is an early version of OpenAI's full o3 model, but it has been fine tuned for web browsing capabilities.
Jordan Wilson [00:27:27]:
Multisource analysis is the big thing, so it searches across the Internet to gather, interpret, and analyze text images and PDFs, establishing connections between, different information sources. Also, it has Python integration, so the system can write and execute Python code to perform calculations, analyze datasets, and generate data visualizations. That's huge because that's what I'm gonna be showing you. Also, there's an advanced reasoning framework. So I talked about how in between each, essentially, web page it visits, it reasons. Right? This is a reasoning model. This is not a transformer model. So it literally goes to a web page, it analyzes it, and it makes it a decision.
Jordan Wilson [00:28:14]:
Like, hey. Where am I gonna branch my research off next? So it essentially continues to accumulate knowledge, and depending on how good you are at prompting it. This is when prompting actually really matters, because it does have that advanced reasoning framework. Here's something that's pretty interesting, that we just found out in the model scorecard. So it actually has a dual model architecture. So, deep research utilizes a secondary o3 minutei model to summarize complex chains of thought, making extensive reasoning processes more accessible to users. So, yeah, it has a fine tuned version of o3 full, and then it has a secondary o3 minutei model. So there's technically two different o3 models working on this deep research.
Jordan Wilson [00:29:04]:
It's wild. And then it is specialized training. So it is trained on purpose built browsing datasets with reinforcement learning where responses were graded by chain of thought models against ground truth answers. That's wild. It was trained against a dataset of browsing and using reinforcement learning, but synthetic reinforcement learning. Right? This isn't the sys like, I'm like, I'm reading this in the system card, and I'm like, this is so meta. Right? I know it's open AI OpenAI, but this is so meta. Alright.
Jordan Wilson [00:29:41]:
So let's that's all the details. That's the technical details. So now let's jump back in live. We'll see how far along we are. Alright. Let me first read this prompt. Alright. Because it's it's kinda big, and I want you to understand what's happening here.
Jordan Wilson [00:30:06]:
So remember, the other big thing that's new here, and this is why I wanted to highlight this, is it has deep research has an improved ability to interpret, understand, and work with advanced, datasets or files that you upload. Y'all, I uploaded, what was it, 15,000 cells of data, some pretty complex data too. So this is kind of my prompt, to, deep research. So I'm giving it a little context. I'm giving it some instructions, and I'm asking for a very specific output. Alright. Ready? I'm gonna try to make this one go fast. So alright.
Jordan Wilson [00:30:50]:
Here's what I said. This is my Google search council data for queries and pages for my website. This is a year of data. The last six months columns are the most current six months, and the previous six months column is the six months before that. Also, make sure to look at the difference column as that is where certain keywords are trending. This is for my website, everydayai, found at youreverydayai.com in the queries that are bringing us organic traffic via Google. This query data shows comparative trends for clicks, impressions, CTR, and average position. Also, I've added external keyword data that shows average monthly search volume, CPC, and competition.
Jordan Wilson [00:31:35]:
We obviously wanna focus on SEO optimization and improved content strategy for terms with very high search volumes that we have a shot at ranking for. I've also uploaded similar data for pages, but that data does not have monthly search volume, CPC, or competition. In short, a positive click difference shows that we're getting more clicks for that page or query than we were in the previous six months. First, analyze the data to see, number one, where I'm getting the most visibility on queries. Number two, where I'm losing the most visibility on queries. Number three, where I'm getting the most visibility of that should say pages. I made a mistake. Let's see if, operator will even know.
Jordan Wilson [00:32:18]:
I should have said pages there. I'm a human. Alright. So I'm essentially asking for wins and losses on queries, and I was trying to say wins and losses on pages, but I got that wrong and I just repeated it. So we'll see if, for number three and four, if it found, if it figured out what I was trying to do or if it just repeated it. Then number five, I said the 15 biggest SEO opportunities based on the above data. Be extremely specific and give me detailed logic behind your choice without wasting words. This should be either extremely accurate SEO optimization trends or content strategy gaps and opportunities based on high value opportunities.
Jordan Wilson [00:32:58]:
Six, future content plan. Below based on deep research findings. Four, number six, future content plan. Please use deep research to find trending topics, AI related topics in 2025 that may be aligned with my current content or content gaps based on your analysis of my files. Focus on huge areas of opportunities that I may be missing in our SEO content coverage. Make sure these are timely in areas that I'm likely able to rank for if I create compelling content based on trends and opportunities. You should tell me if I should create new content that doesn't currently exist or update current content that is already ranking but maybe losing traction. In the content plan, please give me either 10 new pages, posts, or updated, pillar pages that can bring in the most amount of organic traffic in the near future.
Jordan Wilson [00:33:53]:
Each one should be pinpoint specific and based on specific trends and research. As an example, AI for business automation would be too general or vague and a bad example. Instead, a better example would be AI powered deep research tools, how they'll change business automation. Yeah. Now we're getting meta. Also, each of these 10 pages or posts should not only be pinpoint specific, but they should be extremely relevant to the research and trends from 2025. Also, you should outline in bullet point five to 10 subtopics or statements of facts to cover for each of these oh, I made another mistake. I should say each of these 10 pages are posts.
Jordan Wilson [00:34:32]:
It should say 10. I put 20. Already, two mistakes that I did. None of these should be generic or vague in any way. They should be factually relevant, timely, and provide context to the 10 page post ideas. Be exhaustive in your research. Please act as a seasoned content strategist, making sure to research in in both obvious, needed, and yet unexpected places. That was a lot.
Jordan Wilson [00:34:59]:
Alright. So I had to take a quick drink after that one, y'all. Are you guys following what what I'm asking it to do here? This is I would have to hire an SEO agency to do this, and they would not do this good of a job. I don't even know what, OpenAI Deep Research is gonna spit out here, but I'm already guessing it would do a better job than most humans would do. But I could be wrong. So let's go ahead and explore a little bit, and it looks like we're almost done. This kind of, bar here, it says 15 sources. So let's kind of see what we can do.
Jordan Wilson [00:35:48]:
So it's compiling sources. So right here, it has my files that I uploaded. It looks like it went to Forbes. Alright. And I can click that, later. It should give me the exact page that it went to. Right now, it's just giving me the domain name. Then it went to, sloanreview.MIT.
Jordan Wilson [00:36:10]:
It went to news.Microsoft. It went to explodingtopics. That's great. That's a great website, to look at. It just looks at different trends, in different industries. So I probably should have, in all honesty, prompted it to go to explodingtopics, but that just knows that, deep research is super smart. It knows to go to exploding topics. It also went to Sapphire Ventures.
Jordan Wilson [00:36:36]:
It went to Gartner, and I'm sure it's gonna go to a lot of other places. So I'm not going to read off this entire kind of summarized chain of thought, but in the same way, if you've used OpenAI's Reasoner models. Right? So you have your, transformer family of models, you know, your GPT four, GPT four turbo, GPT four o, right, GPT four o mini. Then you have your reasoner models, your o one pro, your o one, your o3 mini, o3 mini high. Right? Alphabet soup, all these names that are not marketing. Right? So in your reasoning models, you can usually see a summarized chain of thought. So the same thing in deep research, if you go on the right hand side panel. Alright.
Jordan Wilson [00:37:24]:
I would also just recommend always anytime you're using deep research, don't have your sidebar open because it just gets super clunky. So just have your kind of middle, main area open and then look over into the activity. And if you don't see it, right, all that means is look at the bottom and where that progress bar is, that's where you're gonna wanna click. And when it's done, you can still click there. Don't worry. Okay? So when you click there, then it gives you back that activity and sources bar. So let's just quickly look and hopefully we can see, a little bit. So before it even gets started, it says I'm examining everyday AI, data to uncover key insights, analyzing shifts in queries and pages, uncovering top SEO changes, chances, and pinpointing AI trends for 2025.
Jordan Wilson [00:38:16]:
Alright. So it says, I suspect time might be causing browser dot search issue with user files. So it looks like there were some issues with the file, and it looks like it tried to use a different, process to look at those files. So we'll see if it actually did. I did run this search once already. I went through, changed some things, improved the search, for this second one. So hopefully, it works here. If it doesn't, I will fall back to the one that I just ran, like, an hour or two ago.
Jordan Wilson [00:38:47]:
Although, I did wanna do this whole thing, live, but it did look like I might be running into an error. That's fine. Full disclosure, I probably run at least, 80 to 90 deep researches so far on OpenAI. I've only had one error out so far. So just by math, that's like a one point something error rate. Go figure if my second error ever, would be on one of these instances that I'm doing live, but such as life. Alright. So it says, I'm weighing the pros and cons of opening the everyday AI page trends and query trends CSV files directly with Python or through a browser, considering the potential for better content display in the browser.
Jordan Wilson [00:39:39]:
So interesting. It looks like for whatever reason, it is having some issues opening up the files. Like I said, I did do a very similar version of this query, previously, and it did fine. Alright. So it looks like hopefully it did read it. So, again, I'm reading through, kind of the activity summary here. So it looks like, it looks like it did read it. Alright.
Jordan Wilson [00:40:04]:
So it read one file. It read the second one. Then it says I'm analyzing keyword trends and their impact on rankings, impressions, and click through rates. Then it says okay. So I know it did, read the files because it says I'm digging into a certain term. Right? So the term ChatGPT free has 2,700,000 monthly search volumes. Right? That's huge. And it's also showing an impression difference, from a six month period to another six month period.
Jordan Wilson [00:40:36]:
So remember, I essentially uploaded one year of data, to deep research here. It's, the last six months versus the previous six months. Right? And there's thousands of terms, and there's also this data. So, you can see it's comparing. It's comparing the data. So, you know, one example, let's let's just see if I can get an actual actual good example here for y'all, just so you can kinda kinda see what we're working with. Okay. The, I think that the this one's this one is a good example.
Jordan Wilson [00:41:16]:
The just the ChatGPT free. Right? So just as an example, in the last six months, there's been a 62 clicks for that exact term, ChatGPT free. Right. And there's, like, 50 different terms that sound just like that. Right. So chat space g p t free. Right? People type in Chad GPT and ChatGPT. Right? So it's just the term ChatGPT, one word, free.
Jordan Wilson [00:41:46]:
I had 1,062, clicks. And then the previous six months, there was 258 clicks. So, you know, it's looking at the difference. So, you know, as a as an example, if a human were going to to to look at this, they would say, oh, okay. Well, we probably did better or you were receiving more traffic for ChatGPT free ChatGPT free. It could be because more people are searching for it in the last six months versus the previous six months. And then you would to confirm that, you would probably look at the position and the impression. So, you know, as an example, the average, position was 15.6.
Jordan Wilson [00:42:26]:
So in the middle of page two, for the previous six months and for the most recent six months, the position was 11. So essentially for that term, our website moved up to the the cusp of, you know, page one and page two, which is a pretty good place to be, for a term that has, you know, 3,000,000 people searching for it every single month. So you could see how something like that would be extremely valuable to someone like me. Right? If you can show up, on page one consistently, and people land on the page and they'll listen to the podcast or, you know, sign up for the newsletter. Maybe that's exactly how you found us. I don't know. Alright. So let's see.
Jordan Wilson [00:43:08]:
Hopefully, we're hopefully, we're about done here. Alright. We might we might have stalled out, folks. We might have stalled out. Let's see. You can always, click refresh. Oh, good. We didn't stall out.
Jordan Wilson [00:43:19]:
I just had to literally click refresh. It was done. Yeah. Sometimes, the progress bar will fully update. Sometimes the progress bar just stalls. Okay. But what you can do is go down here. Okay.
Jordan Wilson [00:43:33]:
Not bad. So this you might miss it. After your query is done in deep research, this can be easy to miss. You essentially need to go find this thing that says research completed. I really wish there was a little bit better user interface to know, like, oh, I should be clicking this. Alright. But I can click that. It says it took eighteen minutes and it went to 15 sources.
Jordan Wilson [00:43:58]:
Alright. So I can click on it, and then I can see, here the activity. I was starting to read through it. So, essentially, after it went through those two CSVs, it started to identify some trends. Then from there, it started searching for AI trends 2025 predictions. And then it went to an MIT Sloan website, a Forbes for AI trends website, IT Pro Today, Microsoft News. It went into Forbes. And then here's here's where this is pretty cool.
Jordan Wilson [00:44:31]:
So it said, I'm noting a potential shift to Sloan MIT due to Forbes being locked. Right? Like a normal human, it went to a website. It went to a Forbes website to try to do some research based on the data and the trends that it spotted in the 15,000 rows of data that I gave it. It went to a Forbes article. The Forbes article was locked. So it looked for a free a free way to essentially read that article, and it looks like it found it on sloan wire at mit.edu. Right? So then it said, we're examining the Sloan's article on business trends focusing on agentic AI and measuring generative AI return on investments. Simplifying sections and cross checking with a Microsoft news summary might help streamline the process.
Jordan Wilson [00:45:16]:
Right? So they're like, yo. We found some good information here. It was originally on a Forbes article, then it was on this Sloan review. Let's, cross check it with something very reputable to make sure that something that it found was actually a trend and not just a one off thing. Right? Because it wants to do literal deep research. And, you know, if you give it a a lazy prompt, it's not gonna do this good of a job. Right? The thing even with I don't care what anyone says. Even with the o one models, o3 deep research, the better your prompt, the more data you share.
Jordan Wilson [00:45:50]:
Right. Even when I was answering those questions, I should have gone into much more detail. I just wanted to do it live, and I hate typing live, but you should go into extreme detail and take care, when doing this, especially if you're a chat g b t plus user. You only have 10 of these a month. You have to make them count. Alright? So I'm not gonna go through and read every single line. You know, if you want, if you're if you're listening, just say activity. You you know, just send the word activity.
Jordan Wilson [00:46:23]:
If you're listening on, LinkedIn or Twitter, I'll just copy and paste this because I don't wanna turn this into a three hour podcast. So this is this is great, though. So it's even looking at, like, you know, rumors and trends. Right? So it sees that, you know, GPT five, it went to explodingtopics.com, and it saw that GPT five was a huge, explosion. But then it just started to do some research to see if it was, you know, actual, if it was a trend, if it was rumors, what it was. This is, I mean, this is great. Looking through the activity, this is where OpenAI's deep research shines, because the others don't really do this good of a job, I think, in the decision making process between sources. Yes.
Jordan Wilson [00:47:15]:
Perplexity and Grok and Google go to way more sources. OpenAI makes it count. Alright. But let's quickly look at the report that it put together because I already know the right answers for many of these. Alright. So let's see what it found. So it said, ChatGPT, massive impression surge, gained about a quarter million impressions over the last six months. Correct.
Jordan Wilson [00:47:44]:
Clicks grew. Correct. AI podcast, breakthrough to page one. Yes. That's been a a huge, a huge boon, something I've been personally investing in for about eighteen months to show up, you know, as a top three result when someone searches AI podcast on Google. Not easy, but we're finally there. So operator did that. So why I'm like, why am I spending so much time going through something that was a bunch of spreadsheets? Because this is one of the new updates, inside deep research.
Jordan Wilson [00:48:16]:
Aside from the $20 a month ChatGPT plus access, now it has a better ability to work with files, to understand them, to interpret them, and to do deep research based on them. And I said, what better way than, yo, here's, like, 15,000 pieces of data. Here's what they all mean. Go do a bunch of research. Right? So as I go through here, it always has citations. So the citations in this case early on is the actual file that I uploaded. Alright. So, it's it's doing yeah.
Jordan Wilson [00:48:51]:
It's it's finding all of these, essentially notable queries, etcetera. So that was the biggest what was that? That was the biggest gains. Right? Then it has the biggest loser. So the biggest losers, for our website were the terms knowledge cutoff, Taplio, how to make ChatGPT sound more human, free ChatGPT with a space. That's smart. It noticed that, hey. Actually, free ChatGPT, no space was a big winner. Free ChatGPT with a space, big loser.
Jordan Wilson [00:49:25]:
But it says, this is smart. It's essentially being like, yo, don't worry because the net traffic gain from free ChatGPT, one word, is still positive. So it's super smart. Super smart. You know, let's let's scroll down here. Let's see if it actually found my mistake because, again, I accidentally told it to do the queries, wins, and losses twice. I meant to say pages, so so we'll see if it actually picked oh, it did. My gosh.
Jordan Wilson [00:49:57]:
Deep research is good. I literally told it to find winners and queries and losers and queries twice. It realized that I made a mistake, and it went and did the right thing. Right? When everyone says, oh, AI AI is never gonna be as smart as humans, I'm a human. I made multiple multiple mistakes. Deep research is like, yeah. You made a mistake here. Here's here's what you meant to do.
Jordan Wilson [00:50:20]:
Thank you, deep research. Alright. So top pages, it went through. It found my biggest gains, right, the home page, free chat g b t versus chat g b t plus. What's the difference? Apparently, the Cling AI video review that we did is now getting, I don't know, hundred thousand impressions, something like that. Category page for AI news, AI's impact on society article, and a couple other things, NotebookLM, other big gains. Alright. Let's go down to the good stuff.
Jordan Wilson [00:50:53]:
Here's our top page performance, biggest losers. This is what I wanted. 15 data driven SEO opportunities. So it says number one, leverage ChatGPT free versus paid dominance. Keep the content fresh. That's good. It's telling me make sure to keep that content fresh. It says boost that page.
Jordan Wilson [00:51:14]:
The site okay. So it's essentially saying that that page is hovering around, position 11 to 17, and it's saying cracking page one here is challenging, but even moving from 11 to eight could double the CTR. Opportunity, create a concise guide or a tool page using ChatGPT for free that targets the broad term specifically. Great advice. Alright. Optimize for AI newsletter and AI podcast. Number four, create a best AI newsletter's list post. It's not a bad idea.
Jordan Wilson [00:51:48]:
A lot of people do that. You know, could work. Let's see. Improve the click through rate for ChatGPT plus queries. Revive the ChatGPT sounds human. That's a good one. Right? Good a good piece of advice there. So it says the query, how to make ChatGPT sound more human clearly has user interest.
Jordan Wilson [00:52:08]:
It's essentially saying like, yo, you used to get a ton of clicks and impression for this. It fell off. You should probably update the tone in the article. Some great stuff here. What's interesting is I was I was gonna see if ChatGPT and Deep Research was smart enough to go visit these actual pages. If I prompted it to, I'm sure it may. I specifically did not because I wanted to see if it would recognize if it should or not. It didn't, or at least it didn't list it in the sources.
Jordan Wilson [00:52:42]:
So, you know, I guess, I don't know. Maybe that's when we've reached AGI is when, you know, it does all these tasks that you kind of secretly hope it would without telling it to. Alright. Let's just go down to the good stuff. So it went through. It gave me all my, my my 15 very pinpoint specific SEO optimizations. Here's the thing that I really wanted to see how well it did. The actual research.
Jordan Wilson [00:53:06]:
Right? It went through because people, I don't think, are using this deep research to its full advantage. They're using it as this, like, oh, you know, really good Google. No. No. These new updates are extremely exciting, because it can work better with your files. And when it picks up on nuances, and and kind of, trends in files that you upload, it will go off on its own in research. So let's see if it actually did that. So, again, everything that I just did so far, more or less, aside from reading the activity, of deep research, everything else has just been kind of general okay.
Jordan Wilson [00:53:46]:
Here's a large language model doing cool stuff. But now let's see how well it took that information, how well it pulled insights, pulled trends, pulled opportunities out of all of this data based on the pretty advanced query that I gave it, and did it actually go out and do deep research? And I asked a ton of it. Let's see. Alright. I'm liking this so far. Alright. So remember, I said give me 10 timely content ideas. So presumably things, number one, I have not covered.
Jordan Wilson [00:54:22]:
Number two, it went out and researched these things. So it knows that there's appetite. It knows that there's search volume, and it knows it's something either I haven't covered very well or I haven't really covered at all. So this is good. The rise of autonomous AI agents in 2025, number one. It gave me a why. Right? I'm not gonna read this for all of them. Let me go ahead and just do the first one.
Jordan Wilson [00:54:45]:
So, number so you can see the quality that it gave me. So number one, it says the rise of autonomous AI agents in 2025. It says to write a new long form article. Why? AI agents that can be that can act autonomously are a hot trend heading into 2025. Both experts and big tech are touting Agenstic AI as a game changer, and then it, sources two different articles. It says everyday AI can demystify this for readers, and then it gives me subtopics to cover. Oh, this is good. This is good.
Jordan Wilson [00:55:17]:
Right? I could literally use this as an outline for my next podcast, and part of the research is already done for me. So here's the subtopics I should cover. What are AI agents? I need to divine, define agentic AI, give examples. Next subpoint, height versus reality. Discuss why agents are trending. Next subpoint, real use cases emerging. Talk about real use cases, and it gave me some and links to talk about those. Gave me survey stats.
Jordan Wilson [00:55:48]:
A UiPath survey showed that 68% of IT leaders plan to invest in agents within six months, and then I can go click that and read it. This is really good. Agents at work, copilots, and more. Explain how tools like Microsoft three sixty five copilot act as agents executing tasks, summarizing emails, scheduling meetings with minimal oversight. Then it gave me, a link to that Microsoft article on six AI trends. This is good. It says possibly include everyday AI podcast insights if you've discussed agents. Then it says next sub point, risk and challenges, a balanced look at why some are skeptical, how to get started, with AI agents, the road ahead, conclude with an expert outlook.
Jordan Wilson [00:56:35]:
Twenty twenty five is likely the year agents move from hype to initial real world adoption, and then it has, different articles that it cited from Sapphire Ventures. Then it says predict that year by year end, we might see at least one major success story, from AI agents such as claiming a billion dollars in savings. What does that mean for everyday users? Summarize the potential. Then at the end, it says, by covering agentic AI in an accessible way, this piece aligns with everyday AI's mission to explain cutting edge edge trends for a general audience. It should be published as new content, then updated as agents evolve. This is so good. Yo. This is so good.
Jordan Wilson [00:57:20]:
I'm probably I mean, I'm probably gonna do that exact episode with those exact subtopics. Right? Now what I'm gonna do is I'm gonna take this, I'm gonna take this outline here. Then what I'm gonna do is I have, I've done about three or four, maybe five or six podcasts so far on agents. So I'm gonna get all those transcripts. I'm gonna upload those transcripts into deep research. I'm gonna copy and paste this. I'm gonna do a little bit of back and forth, and then I'm gonna have it go plan my show. Right? Fantastic.
Jordan Wilson [00:57:55]:
Fantastic way for me to you know, people are always like, Jordan, what's like, how big is your team? Right? You know, very lucky that that you all listen to this podcast when I ramble on so long and but people are always like, you know, how big is your team? Right? You must have, you know, 50, you know, 50 people. Right? You know, I'm I'm I'm very lucky, you know, that we're, like, a top 10, tech podcast on Spotify and all the other tech podcasts for the most part. They have huge teams. They have big companies backing them with a ton of money, not us. We're a very small team, self funded. Right? This is how we do it because we're we use AI tools to help us work smarter, period. So that's a great first example. Let me just go through the, the other ones here quick.
Jordan Wilson [00:58:40]:
Two says AI personal assistance, your AI companion for everyday life. Three and also let me know, livestream audience, which one of these do you wanna see most. I'll maybe you guys vote on which of these topics, and we'll do this one next. Three, GPT five and beyond, what to expect from the next generation of AI models, new content forward looking. Alright. There we go. Let's see. Number four, AI regulation is here.
Jordan Wilson [00:59:06]:
What new AI laws mean for you? Haven't covered that a lot. This did a really good job. Number five, measuring AI's impact. Are we really more productive? I would love to do an episode on that. Alright. Number six, AI and education in 2025. Personalized learning in action. So it's essentially saying, I have I had an AI and education post that was just tanking, So it's giving me new new idea for new content to put on that page that's a little more relevant.
Jordan Wilson [00:59:42]:
Great idea. Let's see. In all of these y'all, it gave me 10 sub points for each and every one cited and sourced. My goodness. Alright. Let's keep going. Seven, AI and marketing and sales 2025, playbook for professionals. So, yeah, I looks like I had another page, that was losing traffic that I didn't even know about.
Jordan Wilson [01:00:06]:
And then it's like, oh, here you go. Here's, you know, a good start on a podcast outline. Number eight, the new AI search experience. How to navigate AI powered search engines. Let's see. Nine, AI for creatives, how AI is changing art, design, and music in 2025. I haven't covered a lot of art design or music in 2025. My gosh.
Jordan Wilson [01:00:31]:
Deep research did a great job looking at that huge spreadsheet with all that data and then went out and did a bunch of deep research. And then number 10, AI for everyone. How AI is becoming more accessible. That's great. I haven't covered, accessibility a ton. I think I've only done, like, two, two episodes out of, like, nearly 500 on accessibility. Alright. My gosh.
Jordan Wilson [01:00:59]:
I'm exhausted. I thought this was gonna be a quick episode. Granted, the deep research took a little longer than I would have liked, but my gosh, y'all. How impressive is that? Now I want you to think about what you do right now and what you wish you could do. Alright. Yeah. You can go try. Don't get me wrong.
Jordan Wilson [01:01:26]:
There's some good things about Google deep research. There's some good things about, perplexity deep research. There's I don't know. If if if if you love Twitter, maybe you can find some, some utility in Grox deep search. I personally can't. This changes work. It does. I gave you an example of how this is changing my work.
Jordan Wilson [01:01:52]:
I invited you into my position, into my shoes, right, kind of, you know, giving you some secrets on how we can plan great episodes. Right? I've been doing these exact things, just in other ways using other AI tools, using, you know, different AI search. Right? Stringing you a lot of tools together. This just makes it so much easier. But I want you to think about what you do. The time you waste searching. Right? I've I've talked about it way too many times about how using the Internet is this terrible black hole. It's too hard to use the Internet.
Jordan Wilson [01:02:31]:
The Internet is made to distract you. Think of how much time you waste on the Internet. Right? All of a sudden, whoops, you're on social media. Whoops, you're on, I don't know, ESPN. Right? I'm calling myself out there. Right? Using deep research, obviously, there's huge gains right off the bat by just being able to research way more, way better. But now take some of these new features that they just announced. So being able to have images in your responses, super helpful.
Jordan Wilson [01:03:00]:
But I think the biggest thing is just Deep Research's, increased ability to better use and understand files. Right? So think of my example. You have to have a mountain of data that you don't wanna go through, find trends, and go research those trends. I'm guessing at least half of the audience, you probably have access to some data. In that data, there's probably trends. In those trends, there's probably research that should be done. Period. Go do what I just did.
Jordan Wilson [01:03:34]:
Right? If you are a ChatGPT plus user, you have 10 queries a month. Go use them wisely. Just use my example. Apply it to exactly what you do. Or if you wanna start off with something simpler something simpler, research industry trends, but go into great depth. You know, first, type out everything you know, everything you wanna know, questions you have. Right? Use it as an actual thought partner. One of the biggest mistakes that I think people make is taking demos at face value.
Jordan Wilson [01:04:14]:
Not trying to be mean here. I don't think most tech companies no. Let me just say it how I wanna say it. Tech companies stink at doing demos. Right? As an example, when OpenAI did a demo of operator, right, their their agentic AI, they had it, like, buy tickets, which I thought was a terrible idea for a demo. Right? I think the last thing people wanna do is click and, you know, click approve 20 times for an agent to buy a ticket. That's a terrible idea for a demo for operator. Right? The same thing.
Jordan Wilson [01:04:55]:
I think what most people have talked about in in what OpenAI demoed, for deep research was more just, like, doing, like, a super advanced, super personalized Google search. Right? Like, oh, I need to buy some skis. I'm going on a trip. Here's the type of skis I want. Okay. Well, a a a human can probably do okay on that search, especially a human that knows what they're doing and knows what they're looking for. That's probably a couple good Google searches, you know, maybe ten to fifteen minutes and you're there. Push yourself.
Jordan Wilson [01:05:33]:
Combine the best elements of a large language model. Combine what you already know. Challenge OpenAI to find things that you don't know, but share with it what you know exactly what I did. I said, here's all the data. Here's what I think. Here's what I'm trying to do. Go go research everything. Yo.
Jordan Wilson [01:05:52]:
Go find everything I can't find. I don't have time to go dive into these thousands of pieces of data and to drown in this and then go research and research and research and research and research more. You go do it. Be smart with how you use these tools. Don't just blindly follow what other people online or the big tech companies are telling you to do with it. This is not a glorified search engine. This is the future of work. Use it accordingly.
Jordan Wilson [01:06:23]:
I hope this is helpful. That is what's new in OpenAI's deep research. Use it. My gosh. Use it. But first, you might wanna share this episode. Alright? If you're still listening, share this on LinkedIn. Alright? And I'm gonna send you if if you didn't share our last deep research episode, it's it's the same guide, but I put together 10 business use cases, for deep research that I think are gonna be extremely helpful.
Jordan Wilson [01:06:50]:
So if you want access to those now, like I said, tens of millions of people now have access, but you only have on that $20 a month plan, you only have 10 searches. You gotta use them wisely. Right? Go look at my use cases. Also, another benefit to sharing this, is I'm going to choose, one winner for a ninety minute consult. Maybe you need some help. Right? I think one of the biggest gains you can get is rerunning, a deep research query multiple times and looking at the results. Hey. I'll spend ninety minutes with you walking through.
Jordan Wilson [01:07:32]:
Alright? But you have to repost this on LinkedIn. Also, I'm going to announce the winner in the newsletter. Alright? I'm not gonna reach out and email you. I'm gonna announce it in the newsletter like we did last week for our winner, last week, and I'm gonna say, hey. You gotta reply. So you gotta repost this, and you gotta keep an eye on the newsletter. We're gonna announce the winner. Alright? I like to make this fun.
Jordan Wilson [01:07:55]:
I get tired. I like to do little contests. Alright? It just gives me energy. Makes me smile. Alright. So if you haven't already, go to youreverydayai.com. Sign up for the free daily newsletter y'all. I am busting my butt so you can be the smartest person in AI at your company.
Jordan Wilson [01:08:14]:
Share the love. Right? Sometimes people are like, oh, Jordan, this is so helpful. You know, you help me get a new job. You help me get a promotion. Everyone thinks I'm a, yeah, I'm I'm an AI savant. Alright. We'll share this, please. You know, if if you're speaking at a conference, throw throw the podcast up on a slide.
Jordan Wilson [01:08:32]:
I'd love it. Email your colleagues. I'd love it. If you're listening on the podcast, click that little share button on the podcast, share it to a friend, subscribe to the channel, leave us a rating. There's so many ways that you can help us. I want to continue to do helpful deep dives. I wanna bring on even more and better guests, but this thing only works if you tell someone about it. Alright? Don't keep everyday AI a secret.
Jordan Wilson [01:08:57]:
I'm not keeping any secrets from you. I'm giving you everything to get you ahead, to grow your company and your career with generative AI. Thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.