Leveraging AI

224 | One AI to Rule Them All? I Tested Gemini vs. ChatGPT Across Real Business Use Cases

• Isar Meitis • Episode 224

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Can your AI tool actually do what it promises or is it just fancy fluff?

When it comes to running your business, choosing the right AI platform isn't just about features—it's about real-world performance under pressure. In this episode, I share my experience which AI platform is actually better for things like custom workflows, client-specific automation, data dashboards, deep research, or image generation, this episode is your ultimate field guide.

In this session, you'll discover:
- Why ChatGPT crushed Gemini in memory, personalization, and multi-step automations
- How Gemini unexpectedly won in dashboard building and deep market research
- Real use cases comparing Gems vs. Custom GPTs and the key limitation that still plagues Gemini
- A real-world test of building data-rich dashboards in Gemini vs. ChatGPT (with shocking results)
- How both tools struggled to pull business travel info across emails, proposals, and calendars and why that matters
- A step-by-step visual branding test using AI image generation and who came out on top
- The one killer feature ChatGPT offers that Gemini just doesn’t match (yet)

💼 Want to work smarter with AI? Follow Isar on LinkedIn: https://www.linkedin.com/in/isarmeitis

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Hello and welcome to the Leveraging AI Podcast, the podcast that shares practical and ethical ways to leverage AI to improve efficiency, grow your business, and advance your career. This is Isar Metis, your host, and we've got a very interesting episode for you today. The reason it's interesting is it is based on my own personal experience that is tied to a workshop I have delivered two weeks ago. So two weeks ago, I was invited to provide a several hour workshop at a very large really known tech company in San Francisco. The company that invited me uses Google as their office infrastructure enhanced the request was to focus most of the workshop on Gemini as well as other Google AI tools, and that's what I did. But to do that, I had to take a lot of the workshops that I've been teaching to many other companies and customize it and test it on the Gemini environment, which gives me a very unique insight to how it is compared to other tools, especially ChatGPT. Now I've learned a lot in the process and I thought it's gonna be highly valuable to you too, to learn from my experience from what I've learned from trying to convert use cases from Claude and ChatGPT, mostly ChatGPT into the Gemini universe. And so this episode is not going to be structured in a very specific flow because these are unique specific use cases. We're just gonna go use case by use case and compare what the results were and what were the pros and cons of each and every one of these platforms. There is a winner, which we're gonna get to in the end, but let's get started with the comparison. The first thing that I want to talk about is a concept that is critical for the success of anything you do with ai, and that is the concept of context. These tools lack context, right? They don't know you, they don't know your company, they don't know your industry, they don't know your unique expertise, and because of that, a lot of the answers you're going to get are generic. So the more the tools. Know about you, the more information you provide them in order to learn about your universe, the more specific, the more accurate, the more relevant answers that you're going to get. That is true for all these tools, which means that if you want to get accurate answers, you need to write very long prompts every single time, unless you can teach the model stuff about you that it will remember for the long run. And that is a very big difference right now between ChatGPT and. All the other models, but in this particular case, Gemini as well. So let's look at what I'm referring to. So what I did here is I basically asked ChatGPT, what do you know about me? A very simple and straightforward question. You can do that yourself to test it yourself. You can try it with different models. But let's see what ChatGPT knows about me. And this is just a question that's, there's nothing else in this prompt. And it says, here's a structured overview of what I know about you based on our past conversations and context. You've shared background, former F 16 pilot in the Israeli Air Force. Later on, instructor in the Air Force Academy transitioned to business and technology with 15 plus years as a CEO experience in startups. People post and large corporations last minute travel, hotel beds group,, moved to the US about 20 years ago, professional journey built and scaled multiple companies, including taking one public and selling another. Founded Multiplai in 2023, focused on AI education and consulting. Provides, and so on and so forth. Then it has, content education, which are the things that I'm focusing on right now. It talks about this podcast, the Leveraging AI podcast, about our newsletter, about the hangouts we do every single Friday, and about my collaboration with the Crummer School of Business, which is the business school I did my executive MBA at, and now I've been collaborating with them for the past year and a half in delivering AI education to their audience. And then our other initiative that I'm involved in, market and audience, where it is, who am I'm catering to, personal notes about myself, about my family, what I'm passionate about, what my family does, and so on. And some key takeaways. All of that, it knows about me, which means when I'm asking it anything, it uses that reference information in order to provide more relevant answers to me. I've done the same exact thing with Gemini and asked Gemini what it knows about me. So same question. What do you know about me? And the answer is, based on our current interaction, here's what I know, just as important, what I do not know. What I know, our current conversation, and then it says what we talked about in that particular conversation, time and location. Based on the information provided to my system. I know it is Thursday, August 7th at 10:49 AM technical information, very little. And what it doesn't know, it doesn't know my name, it doesn't know my age. It doesn't know where I live. It doesn't know my email address. It doesn't know my browsing history. It's a lot of other stuff it doesn't know. So basically it doesn't know anything about me, which is good from maybe a security perspective. It's bad from a context perspective to. Any conversations I'm going to have. So I actually take the time for a very long time now, investing in teaching Chachi piti about me, about my business, about my tone, about my customers, about the proposals that I write, about the services that I deliver. It knows a lot more than it actually shared in that one summary, and because of that can provide me much better information. The other thing that I use for context in chat g PT that does not exist in the Gemini universe is I use projects. Projects are on the left side, right under,, the custom GPT segment just above your. Chats. And in there you can create these folders. And in these folders you will have different conversations, but each conversation can have its own unique context universe. So you can see in this particular case, this is a sample client project. It's not a real client, but I have one for each and every one of my clients. In there you will see that I have different kinds of information. I have proposals, for that particular client that I've sent this client I have. Different files that I've created. So the culture of the company based on my experience and based on their website, what proposals I've sent them. So you can see what that is. The consulting agreement I have with them, the people in the company that I engage with and their profiles from LinkedIn, the workshop proposal that I sent them, the about US PDF from their website. So more context about that particular client. So then when I have conversations in this folder, it has a lot more context about this particular which again is not something you can do in Gemini. So that's on context, which is definitely a huge win on the chat GPT side. So let's move on to the next use case. The next use case is using custom GPTs versus using gems. So the concept is very similar. I'll explain in one sentence what it is. So custom gpt and gems allow you to write instructions that you wanna repeat time and time again. So every time you have a repetitive thing you want to do with ai, whether it's writing a proposal, analyzing a specific document, comparing two Excel files, uh, creating content, et cetera, et cetera, every one of those can become either a custom GPT on the chat, GPT Universe or GEMS on the Gemini universe. I recorded an entire episode about it. And if you want to dive into the topic of custom gpt, you can go back to episode 1 75. It is called Stop Wasting Time, automate repetitive Tasks with Custom gpt so you can go back and listen more about that topic. But there is a similar concept that is more or less the same in the Gemini universe called gems, where you can provide information and so on. So the way I create and the way I teach how to create both custom GPTs and gems is not by writing the instructions on your own, but rather by having a conversation with cha GPT or in Gemini and then asking ChatGPT at the end of the conversation. Once you explain to it everything that you want, once you ask it questions, once you work inside the conversation. On the actual output and you achieve the correct output, then I would go and say, I would like you to now turn everything that we've done, including the final successful outcome. So ignore the stuff that didn't work into highly detailed instructions for a custom GPT or a gem, because it creates better instructions than I can, especially after we've done the entire exercise and we're getting to the outcome that we want. I've done this in chat GPT multiple times, and then I've tried it in Gemini and it doesn't work as good. So let's look at an example from each and every one of those. So in this particular case, this is from a presentation I've done for the Israeli parliament and I've started the prompt with you are an expert data researcher in the Israeli Parliament tset. We are planning to use a custom GPT to help us in the research and summarization of data. We would like to build a team of separate personalities that will participate in this process, et cetera, et cetera, et cetera. I'm writing in this prompt, and then we're going back and forth and it gives me suggestions of what these people can be and what they will do and what are going to be the responsibilities and the roles of each and every one of them, and what's gonna be the research process and what's gonna be the focus on different things. And then I ask it for a list of responsibilities for each and every one of these people. So it went ahead and did that. So now I have a long list of responsibilities. And then in the end, after going through the entire process, I said, please create a detailed instructions for our custom GPT that will create all these personas. The GPT should receive an input that would be a topic for the Nset team would like to research. The team should first discuss the topic debate. And agree on the way forward, et cetera, et cetera, et cetera. And he wrote these amazing instructions. So you can see there's system description. This is the first thing that it created. Then it created a team overview. It gave names to each and every one of the people. What's their role, what's their style? So they can have different personalities that will support the team. Then a step-by-step workflow. Step one, topic intake and group discussion. What are the actions that they should follow? Step two, data collection. Step three. Domain analysis, what each people, which, and it even has a breakdown of who's leading what aspect of the process based on the personas and the roles and the actions that they need to take and the responses that they need to provide. Step four, political and public lens. Step five, quantitative analysis. Step six, synthesis and drafting. Step seven, risk and ethic. Review, and then who is the lead on that and the actions for all of that Step eight final review. And then there's a communication format on how they should communicate with one another. And then what is the output structure of the report that they should generate and additional capabilities. So, this is an incredible set of instructions that, again, there is no way I could have written this as accurate and as detailed. And then I did a similar process in Gemini asking it to create instructions for a specific business process, not exactly the same. And when I did that, it actually gave me. Instructions that were okay. They weren't horrible, but they definitely weren't great. And it was weird because it was kind of like relating it in third person, and I'll explain what I mean. So my prompt was, I would like you to create instructions for a gem that I can run inside of Google Slides that will ask the user this set of questions and topic, blah, blah, blah, blah, blah. And then it created a set of instructions that should be able to work, but it invented things that just don't exist. So as an example, it said this Gem will open in the sidebar in Google Slides. It will guide the user through a series of five steps, asking questions and so on and so forth. But the reality is it cannot open on the sidebar. So I wrote back, I said, I don't believe the sidebar can have a next button. I believe it is a simple chat interface. Am I wrong? but then it said you are right to question the specifics as the interface isn't free foreign canvas. However, it's more powerful than a simple interface, and you can absolutely have a next button, which by the way is not true. At least I wasn't able to see it true, but it gave me instructions that just don't work. So, instead of just giving me instructions for a gem, it's referring to what needs to be the instructions in the gem, which is not horrible. And in many cases it actually worked okay, but it's definitely not as good as the solution that I got from chat GPT. Then I tested something else. I tested a very complex multi-step custom GPT that I've created a while back for a client, and I was trying to recreate it with the same exact instructions on Gemini. So let's look at that. So before we dive into this, let's talk about what this multi-step process does, and it's actually gonna blow your mind just by itself. Because what it does is it takes a inventory file that is completely fake. I made it up. All the numbers are made up, but it's an inventory file from multiple sources showing inventory of different SKUs in different locations for the company. And it is using it to create a sales brief for the salespeople to explain to them what inventory we have, what inventory was were out of, in which regions of the world and so on. So this is something that many companies struggle with, right? So the ability to take information and compare the inventory from yesterday to inventory from today, the inventory from last week to the inventory from this week, and based on that update sales information that they can be sent to salespeople. This is a process that many companies do completely manually today, and I've developed a custom GPT that does the entire process, but it's a five step process, so all I have to do right now is upload the old inventory file, the new inventory file, and the old sales file to the custom GPT, and then it follows all the different steps. It does step one, step two, step three, step four compares different things, uh, where it is, what are the sizes, what are the SKUs, it's the same package type, uh, and so on and so forth to verify all that information. And then when it's done with that step, it goes to step three, and then it removes all the roles that. Do not have the relevant rows in the other file anymore. So basically we have it in the sales files, but they don't exist in the inventory file anymore. So it compares three different files back and forth. It updates all the quantity and the numbers and the SKUs and everything to provide me a new updated file, and then it provides it to me. As a CSV file that I can download to either upload to whatever CRM system that I'm running or to email to my team. Again, the CSV file can then be converted to anything that I want. So this is an extremely powerful multi-step process that I have tested consistently multiple times and provides. Accurate and amazing results every time that I run it. You can imagine similar processes across multiple aspects of businesses where you have multiple data sources that you need to align, compare, and provide some kind of an output based on all of them, and it works flawlessly inside of ChatGPT. However, when I try to run it on Gemini with the same exact instructions it literally gets stuck. It doesn't do anything. It says, of course, I will process the files, uh, according to the steps provided. Please provide a moment while I perform the data comparison, filtering, merging, and updating. I'll provide you with a final updated file for download shortly. That sounds very promising. Only nothing happens, and so. I tried several different ways. I changed the instructions a little bit. Again, the instructions were copied and pasted, uh, and yet it does not work. The inputs are the same exact files that I gave ChatGPT. So in this particular case, again, a huge win for ChatGPT compared to Gemini when it comes to actually running a multi-step complex process, with the same exec instructions on both platforms. Now in addition, one more thing that you can do in custom GPT is that you cannot do. In gems is add code to them to connect them to more advanced capabilities and connect them to API of third party tools, connect them to MCP servers, et cetera. So if we look at this particular GPT is connected down here to the API of data for SEO. Which is a company that provides data for SEO, like the name suggests, but that means that I can ask questions about keywords and their availability and competitors and their density and so on across any domain that I want, within this custom GPT, and get information about myself, my competitors, and so on, and Build my future blog post based on actual real SEO data right here within chat GPT, without having to go to other tools and bring information and so on. This is a very powerful capability. This is called Actions, and it's available on the bottom of custom gpt. Uh, if you, if I'll open this, you'll see this is just code that connects it to their MCP server. I didn't write the code. That's a code that they provide to anybody. So you can go and grab the code and attach it in here, and you can then have this kind of capability. The ability to out code into a gem just doesn't exist. So that's another benefit of custom GPEs versus Gemini Gems. The next topic that we're going to talk about is dashboards. So I actually think that the best tool to create dashboards right now is Claude. Every time I need to create dashboards, I actually go to Claude, and Claude does an amazing job in creating visually pleasing and also very effective dashboards. However, I wanted to test Gemini on that topic, but before I even wanted to test it, something very interesting happened. I was actually working on a financial analysis, and so the financial analysis, just as an example, took, information of a publicly traded company. In this particular case, I believe it was Salesforce, and then it grabbed the information from the internet and it gave me their information, and I asked it to create a report about it. So this was a great example on how you can take raw data off the internet and create graphs like you can see here, like fiscal results per quarter, or then compare that year over year and just get information just by asking simple questions or even creating complete reports like you can see here inside of Gemini. So it created this detailed report on the financial success of Salesforce. In the past X number of quarters based on the prompting that I provided in the beginning. I could have done this obviously on any company in the world. So a very solid solution from Gemini in this particular case, however, it then suggested on its own to create an interactive dashboard, and all I have to do is say, yes, I'm interested in that. And it created this amazing dashboard from the data that it has collected based on my prompt. So you can see it says Salesforce financial dashboard. It has key matrix, revenue analysis, profitability and efficiency. Each and every one of them is a link that if I click, it will scroll down to that particular section. Then there's the key findings in big, bold statuses, and if I click on each and every one of them, it opens another segment with some more details about this particular topic. So you can see if I click different things, it goes to that. And then it has revenue and seasonal patterns. And then it has year over year comparison and it created. All of this on its own. Based on the conversation that I had with it, I did not define any of the components in this dashboard. It just asked me if I would like to create one. And when I said yes, it created this, which is really, really cool. So from that perspective, huge win. On the Gemini side, both taking the initiative and suggesting it, but also without me defining what exactly I want to see in the dashboard. It was able to create this amazing dashboard, but then I did something else and I went the next step. I said, I have these amazing dashboards that I've created in Claude. Can I just replicate them in ChatGPT and in Gemini and see which one does a better job? So I started with ChatGPT. And all I did is I provided it the same exact information that I provided to Claude, and I provided it a screenshot of the dashboard, so it got the input file that I'm going to upload, basically the same exact file that I'm using on the cloud side, and you've got a screenshot. Of the entire page. So a full page screenshot, not just the top of it, of the dashboard and all the components that are in it. And then I ask it and I said, you're an expert in dashboard application creation. I'm going to provide you the following, basically what I explained to you. And I ask it to create the dashboard. And it did, and it never works. So when I click preview. The first step is correct. It actually asked me to upload the file and start the analysis, but every time I do this, there's some kind of a bug and the actual dashboard doesn't run despite the fact it's the same exact file. I, I gave it as the sample data in order to build the initial dashboard. So that was my experience with ChatGPT. I tried it several times and I got the same issue every single time. Gemini, on the other hand, got the same exact instructions. I literally copied and pasted the instruction. I also copied and pasted, uh, the same screenshot from the Claude Dashboard, and instead of course, I will create the dashboard and it went ahead and created an amazing dashboard. It's working, it's fully functional. I can upload the file, so let's play the game. I will click here and I will go and find the file. Here we go. Click open. Click start analysis and boom, I have a working dashboard and you can see that it has, uh, the monthly sales trend and it has year over year growth and it has the top 20 clients and their trend in the past month compared to the trailing 12 months. And it has the distribution between the top leading clients and there's the filters on top. And I didn't have to explain any of this. I literally just showed it a screenshot of the other dashboard. So if I click now, uh, channel one. You can see that it changes the numbers. I can click and say, oh, I just wanna look at Q1, uh, for that. So it will change that as well. And you can see that it changes only to Q1 across the different years, uh, and so on and so forth. So all of this is working. I can go to clients and I can select the different clients across different regions and everything. We'll move and update accordingly across all the different aspects of the dashboard, really fantastic and without almost any effort. So on this particular example, definitely a huge win for Gemini, for creating the right code, for understanding the need, and for creating a very useful and functioning dashboard. With very few steps. Uh, the only thing I had to actually correct was the graph on the bottom that had all the companies, uh, if there are no filters are applied. So if I do this, it had like a gazillion companies, which made no sense. It was too crowded and all I had to do is ask it to only include the top 20 companies, uh, in the graph and everything else just worked out of the box with almost no instructions. So big win. To Gemini on this particular creation of the dashboard compared to Chad G. Pt that despite all my attempts, was never able to make this work And now our next topic is deep research. Both tools have deep research creating capabilities. Both tools are the two leading tools from a deep research perspective right now. From my perspective and my experience, and I use both of them all the time, I also try the other tools. Very regularly. So about about once every other week, I will try one of the other tools or some of the other tools as well just to see how they're doing. So whether that's, perplexity or Deep seek or Claude and I will try their deep se, deep research as well. Still, ChatGPT and Gemini have a very big lead when it comes to deep research, but let's compare the two. And so in this particular example, what I was looking for is I was looking for AI software solutions that can help architects, interior designers, smart home integrators and builders, and other people who work with floor plans and stuff like that. Because I have multiple clients in that universe and I wanted to see what it will find. So I wrote along in detailed. Prompt. I copied the same exact prompt to both tools and I let it run. So you can see the prompt is about a page and a half long explaining exactly what I need. The way it works with Gemini, it tells you what it's going to do, and then you can say that you approve the plan or not. If you don't, it will ask you to clarify what else do you want or what do you want different? It's a little different on the ChatGPT universe. It always asks you questions so. After you write the prompt again, it's the same exact prompt I copied and pasted it. it said, to get started, could you please clarify the following? Are you focused only on AI powered software, or should I include any advanced software, even if not AI based that supports automation, rules, logic, blah, blah, blah. So it asked me all these questions that I gotta answer in order to clarify exactly what I'm looking for. Then both started the research. Uh, usually Gemini takes a lot longer when he does the process, but both tools will work on it for a while. And then this is the result I got from ChatGPT. So you can see it starts with a table that shows the different tools and what functionality they have. But what you'll see is that already here there's issues where it's not showing, uh, some of the table. And if you scroll down, then you'll see many of these aspects instead of being a part of the table as they should, are just written in text with the vertical line in between them. So it didn't really create it correctly. So I have some of the functionality here compared, but then all the other ones are in this weird format that I cannot do anything with. So I messed that up. But overall, then it started with generative. Design tools for architects, uh, and gave me several different options. Then it gave me, uh, AI tools for interior designer and space planning, and then it gave me a few options here, uh, and so on and so forth. So overall, a detailed, helpful report that is aligned with what I requested or kind of aligned with what I requested, and I explained why. What I mean by kind of aligned, if you go back to the prompt, what I ask it to start with, I ask it to start with doing a research. On what kind of positions, what kind of roles exist in these companies, and what are the use cases of each and every one of those people? And only then go and start the research on the actual tools to be able to check if they can do these functions that these different roles have to do. So, if we go to the Gemini version of the deep research, you will see that it followed the instructions. Perfectly said part one, the professional landscape of floor plan utilization, and then it has objectives, and then it has chapter one, core design and planning professions. And then it has architectural designers and drafters, and it has what their needs are and what they need to do and so on and so forth. And it went to interior designer, floor plan related tasks, space planning. So it literally followed. In detail exactly what I requested. So it started with a much better understanding of what these people need before it started the actual research on the people. Now maybe ChatGPT did the same thing, but it not expose that in its report. So it's very hard for me to know. So you can see all of this, like I'm still scrolling and scrolling and scrolling. For those of you who're not watching this. All of this, like pages and pages are just analysis of what are the roles and what key functions they need that these software will do for them. And then comes part to of the AI software market, floor plan, automation landscape. And then it has the objectives and then it has all the different tools, very similar to way cha PT did it, divided to the different segments and what are the benefits and the pros and cons of each and every one of the software and the pricing and so on. Very detailed report. It also created a table in the end, like I requested, which G PT put in the beginning. But in this particular case, the table is full and complete. So all of it is in the table. And it included all the different companies and tools that it found necessary. The other very cool thing that exists if you use Gemini, is that almost every output that it has, you have a one click export to the relevant Google platform. In this particular case, it's Google Sheets, so if I click on export to Google Sheets, it will build a Google Sheet file for me with this table in it, and I don't have to copy paste, realign and so on. It's the same thing with opening reports as documents and so on. So it's a very helpful, useful tool, uh, for Gemini. So in general, and again, I use deep research several times a week, every single week for multiple topics. Gemini is number one right now when it comes to doing deep research, and ChatGPT is good. But it's definitely in a second place, and this was just one example. It's a very clear example of why Gemini is better overall. By the way, Gemini also found and researched more tools than ChatGPT. ChatGPT researched 18 different tools that it reviewed, and Gemini did 23 different tools that it reviewed. Part of it might be because it did the first part of the research as I requested. The next topic that is a lot of fun is creating images. So if you remember X number of months ago, I think it was May Cha, GPT came out with its amazing image generation capabilities. The world was going crazy with creating Ghibli images of themselves, their family, their coworkers, and so on. And then two weeks ago, Gemini came out with Nano Banana, which is also known as Gemini 2.5 flash image, which creates amazing images and knows how to keep consistency and so on. And I wanted to try an experiment that I did just after Chet PT came out and tried to replicate it with Gemini. And so the experiment was to take a relatively low resolution image of a product of the internet and create an ad with it. In this particular case, it is a Neutrogena sunscreen 70 SPF. And again, those of you're watching this, this is an image of the internet. It has a white background and a relatively low quality image of the sunscreen in its tube without any kind of background, and what I did is I first asked it, please provide a line by line text of what is written on this product. This helps you afterwards get consistent results when it's recreating it. So it gave me the exact thing that was on it, and then I said, now I'd like you to create a closeup professional product, photography of a female hand holding the product. The background is the ocean and the beach, but it is blurry as the focus is on the hand. And the product. Nikon Z seven 50 millimeter lens aperture 2.8. And then the product should say, and then I pasted what he told me that's written on the product and it's created an amazing image. It looks exactly like the prompt. Suggest professional photography off the beach with the right lighting, with a female hand holding the product. It looks perfect. But if we zoom in. If we zoom in on the text, you see the text says, dermatologist recommended brand. It says Beach defense, water and sun, sunscreen, lotion, broad spectrum, all the stuff that it says. But here on the bottom, where it's where the original one said, water resistance, this one says, which is not exactly the same, and instead of 80 minutes it says zero eight minutes. So it missed one small aspect. Again, if you don't zoom into the fine print, you will not know the difference. But then I went on and I asked it to change the SPF 70 to 50 just for fun. And it did that, and it actually captured both places that it's written. Then I went ahead and asked it to change, the SPF from 70 to 50, just to see if you will do it. So you can see in the original image it says broad spectrum SPF 70, and then it says 70 in a big font beneath that. And then in the new image it does says 50, but where it says broad spectrum, it doesn't have a number anymore. Just as broad spectrum, SPF. And then I ask it, please redo the image and change the girl's nail polish to the USA flag pattern. And it did amazing. It actually did that and it kept the 50 SPF, but now you can see that the broad spectrum says SPF three, and you can see that the water resistant is now all gibberish of what it said before. It doesn't even say water resistant. It says something else and it says 50 minutes. So things are starting to drift away from the original image, but the quality is still very good. And if you don't dive into the very close details, it looks. Perfect, and it looks professional. Then I went further and said, extend the image on the bottom to make it a nine by 16 image and write in a fun summary font. 4th of July sale, Neutrogena, bogo, and it did exactly what I asked. It extended the picture to a portrait format, and then it added in two different fonts, the sale. Then the bottom font wasn't clear enough, so I asked it to change that to the same font, and I got to something that I can definitely use as a professional ad. The only problem, as we've seen before is if we dive in, you will see that now even the stuff that was written on the bottom is a little bit messed up and it invented new words, that are supposed to be written there and it invented the amount of time that it protects you from that. So again, from as an ad, it still looks great. From the very fine details, it's still not perfect. I try to mimic the same exact process with Gemini 2.5 flash image, also known as nano banana. I first of all started the same exact way I started in ChatGPT. I pasted the same exact image and I asked it to create the line by line text. And then I used the same exact font that says, I would like you to create the closeup professional product photography of a female hand holding the product. And they gave me something that looks like a female hand holding the product, but it was something completely different than what I had before. It still looks like a tube of sunscreen lotion, but it doesn't look anything like the original one. And then it caught my attention that I forgot to turn on the image generation tool, which means it's still using, in this particular case, it's old Imagine four engine instead of the image generation capability, which is hidden down in the tools. So in the prompt menu where you write your prompt, there are tools and if you click on that, there's an option to create images and there's a little banana. Icon next to it, and that's what you wanna select. So then I started from the beginning with the correct tool, and you can see here that it says image and it has the banana next to it. And I pasted the same stuff. And this time it created a perfect image. It actually has all the text correct. Including the water resistant in the 80 minutes. The quality of the image from a pixelation perspective is slightly lesser than what it was on the ChatGPT side. But, uh, both of these can then use different kind of upscales to solve the problem. So I don't see that as a big issue. Uh, but overall a great image. Definitely as good as the one Chachi created as the first step. It even did something very cool and it added little water droplets on the actual tube to make it look as if somebody's at the beach actually holding it, which I found really cool. It makes it look a lot more realistic and there's shading on it. It's just perfect from an image perspective. Then I went the same exact step that I did with ChatGPT. I said, I would like you to recreate the image with SPF of 50 instead of 70. And in this particular case, it actually changed the 50 SPF part on the fine print where it says broad spectrum SPF. It missed that and it kept that as 70. So I would say that in this particular case, it is equal to what chat GPT did because Cha GPT didn't write the SPF at all on the five print, and it actually did, Gemini did better by preserving the font of the 50 over 70 when ChatGPT changed it a little bit. Then I followed the same process. Please redo the image and change the girl's name polish to the US flag. And he did that and it kept everything else intact. And in this particular case, it is also maintaining everything that was written on the packaging. So you can see that the dermatologist recommended, uh, brand is still okay, and you see that the fine print here still says. Water resistant 80 minutes, so better than ChatGPT did on keeping the actual product, but then is where it starts failing and I asked it to extend the bottom of the image to make it a nine by 16 image and write the font on the bottom and it just doesn't change the aspect ratio. That's something I found with nano banana that it just doesn't do. Does not agree to change the aspect ratio of images. So it created the font. It was very hard to read because it created the colors of the flag within inside the text, which is actually very cool, but it makes it hard to actually read, ask it to remove it. And in the second attempt it actually did. So the final output is very similar to what we had with GPT, but with several different, but with several major differences. One is that it did not extend the bottom of the image, so the text actually hides a little bit of the actual product, which is not what I wanted, and it is not what I had with ChatGPT two is in the very final image. You can see that there's a lot more pixelation around the text on the actual tube and it's not as clear, and it's starting to have these weird artifacts so it drifts further and further away from the original image as you keep redoing the product, that's something you just should be aware of. So what is the verdict here? I would say this is a tie because ChatGPT did a better job in the aspect ratio and placing the font in the correct place, and Gemini did a better job in maintaining the exact text and the accuracy on the product, at least in the first few steps. But then I said, okay, this deviation from the. Original text in Gemini only happened after multiple steps of making different corrections in the image. What if I try to one shot it? What if I allow it to create the image with a more detailed prompt, with just one step. So in this particular case, I basically took all the prompts and combined them together. I gave it the same original image and I said, make it nine by 16. The background needs to be the ocean blurry, blah, blah, blah. Changed the SPF from 50 to 70. The girl's name Polish needs to be the pattern of the US flag, and then exactly what it needs to say, and it actually created it with one go other than the aspect ratio. So I got. Something very similar to the final ad with keeping the accuracy of the text on the product. So this is great because I don't have to then fix it in Photoshop and so on, but it did not extend the aspect ratio, so I was able to find a solution to part of the problem, but not for the entire problem. The expect ratio is just something that Gemini will not do at this point. And then the final thing that I tested was how good are these tools in actually reading my information across multiple of my tools that it is connected to? So Gemini is a Google product. It has access to Google Calendar, Google Drive, and Gmail. And ChatGPT, if you connect it through its connectors, also has access to your calendar and your Gmail account. So I have lots and lots of business travel coming in. The next two months, I'm doing multiple in-person workshops to companies. I'm speaking at several different conventions and events, and so I'm going to be traveling a lot. So what I did is I started in ChatGPT and I said I would like to check my calendar and my emails and all the proposals that I've sent in the past six months, and look for any engagements between now and the end of November that requires me to travel. I would like you to create a table with the following columns, starting date, ending date, destination activity, and details, and then I explain what do I want in the details. And the way you do this in chat, GPT is when you click on the plus button, in the prompt section of chat GPT, there is a button that says Use connectors. And if you click on that. There's a dropdown menu where you can connect different connectors like Canva and Dropbox and so on, and there's a lot of other connectors that you can go and choose from. But what I connected is Gmail and Google Calendar, and I asked you to find, uh, information and then it only found two pieces of information for my travel. It only found two travel things that I need to do in the next two months, which I wish that was the case. It's more like, seven or eight, but it did a very good job on those too. So it gave me the dates, uh, the starting date and the ending date, and the location and the activity, and a very well detailed plan on exactly what am I doing and what, who am I meeting and where I'm supposed to go. And if there was hotel information or stuff like that, all it is is in there, including the booking reference of the, uh, hotel that I'm staying in and so on. So. Not great, but not horrible either. It found a few of the events, uh, and gave me a detailed information about each of the events when I did the same thing for Gemini. Which in theory should do a better job because it has native access to all my stuff. It found three different travel out of like the seven or eight that it was supposed to find, and it provided a similar level of information. As far as the details, it doesn't look. As nice and clean as the view inside of Chat pt. But it definitely has the same quality and the same level of details as far as all the things that I need and the information in it. And again, it has the button to export to Google Sheets with one click, which is helpful. So from my perspective on this particular aspect, they both. Failed because they both did not provide even half of the travel that he was supposed to find. And the information is definitely there across the different tools. To be fair, Gemini has access to more information, but it because it can also see my Google Drive and it can find all the proposals that I've written there as well, not just as attachments in Gmail, but the information should be available on both platforms. So both tools had the option to be successful in this and they were not. So what is the bottom line of all of this? We tried multiple different use cases. Some are more basic, some are more advanced capabilities, and we're trying to compare the two different platforms and in some aspects also clawed as well. And the reality is that each and every one of them has pros and cons. Some things Gemini did better, like the dashboards and coding, uh, tools have actually worked better on Gemini than they worked on chat GPT. Also, as far as finding information, it found a little more information in my Google Drive and so on. It definitely did a much better job on deep research. ChatGPT, on the other hand, did a better job with custom GPT compared to gems, actually a much better job across all the different aspects from creating them in a regular conversation through running more complex ones and getting consistent results through the ability to use code. So pros and cons on each side, there is no one clear. Winner because each and every one of them has different capabilities that it's actually good at. And the same is actually true if you expand that to Claude and Grok, which I also use regularly for different aspects. So what does that mean to you and your business? Well, if you have to pick one tool, I would say pick the tool that is best connected to your universe. So if you are a Google user, over time, you will gain more and more benefits by using Gemini. And yes, I know cha. GPT has connectors and Claude has MCP and connectors and so on. But we have to assume that Google will make better, seamless integrations of their universe into their world. And in general, Gemini is a very powerful and capable platform. The only thing, it was definitely not as good at. Is gems. And so that's the only thing that you're giving up on to an extent. You can still create gems, they can still run automations. I built a lot, uh, for myself and I definitely build a few for, different clients, but it, if I had a choice, I will build those in custom GPT because it just runs better and provides, uh, more capabilities. If you're not in the Google universe, you can choose whatever tool you want. Then ChatGPT is definitely an option. However, if you are willing to provide different people access to different tools, depending on the use cases that they have, and you heard me talk about this in this podcast a thousand times. It's all about the use case. Right. You don't start by selecting a tool. You start by finding the use cases in which AI can provide you significant value, and you can define value however you want. It's all okay. This could be time, this could be money, this could be happiness of your employees. This could be anything you define as valuable to you and your business, but. Find something that provides value to your business that AI can help you solve. And then find the best tool that does that in the best way. And this might be doing sub deep research like I did for the architects, uh, and interior designers, right? You may run that and you may find custom specific tools for specific tasks. Or you can just test yourself, the main platforms like Cha pti and Gemini and Rock and Claude and so on, and some of the Chinese models and open source models and see which one does that particular thing better than the other tools. And then in two to three months, you can test it again if new models come out and you wanna make sure you're not staying behind. And as long as you understand the concepts and you understand the risks, and you understand what is working and not is not working and what you need to test for in these tools, then switching the tools should be very easy. You don't have to be married to any of these tools for a very long time. You can switch if you understand the concepts and you've built the right processes around it. That's it for today. I hope you found this, valuable. This is just a current comparison between ChatGPT and Gemini, which are the two leading AI platforms right now in means of usage, and you now kind of know. What each and every one of them does a little better. Your use cases might be different, so you have to test it on your own, but this gives you an idea, maybe on how you can test it. So I hope you found this valuable. If you have, please give us a thumbs up in a five star rating on your favorite podcasting platform, whether it's Apple Podcast or Spotify, which is where most of you listen to the show, share it with other people. This is how you can help other people learn how to use AI properly, is by sharing this podcast. Literally open your phone right now unless you're driving. Click on the share button and type the names of a few people that you know, either on WhatsApp or Instagram or LinkedIn or text messages, however you wanna share it with people or email and just share it with a few people that can benefit from this podcast as well. I will be really grateful if you do that, and until next time, have an awesome rest of your week.

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