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How “Nano Banana” and AI-Driven App-Building Are Reshaping Everyday Business Workflows
Today’s AI advancements are making productivity tools more than just “smart”—they’re approachable, deeply practical, and increasingly within reach for business teams outside IT. Directly from behind Google’s latest AI releases, here’s an up-close look at how features like “Nano Banana” and intuitive AI app-building can immediately support business leaders’ goals.
Nano Banana in Practice: Streamlining Image Tasks in Real-World Workflows
Nano Banana, an image-focused AI model integrated within Google’s Gemini platform, demonstrates tangible capabilities that have been rapidly adopted—five billion images created within a single month is direct testament to its ease of use and effectiveness.
Rather than simply automating generic processes, Nano Banana enables nuanced tasks previously reserved for specialists: background removal, historical photo colorization and upscaling, Pinterest mood-board visualization using actual home environments, hyper-grounded portrait creation, and passport photo generation. This makes it possible for business teams to self-serve standard graphics and visual content tasks—frequently a bottleneck for marketing, HR, presentations, and customer communications.
Crucially, Nano Banana allows these actions directly with natural language. What would once require Photoshop or skilled design knowledge can now be executed by describing the desired outcome in plain English. This precise toolset can instantly enrich a company’s communications and documentation by enabling staff to create on-brand, high-quality visuals at speed and scale.
No-Code App Development with Gemini and Nano Banana: From Idea to Working Tool in Minutes
AI’s leap forward isn’t limited to image generation. Using Gemini’s “Build” tool, anyone can now describe an app in natural language—and have a fully functional web application, complete with a unique shareable URL, available in just a couple of minutes. This is not theoretical: full-stack deployment, cloud project setup, storage, logging, and error-handling (with AI-driven “self-healing” if code problems are detected) are completely handled behind the scenes.
Crucially, this no-code approach has seen non-technical professionals—product managers, sales teams, service experts—become prime contributors at recent Bay Area hackathons. Winners and future founders now emerge from those with deep customer understanding and analytical mindset, even if they’ve written zero code before. This is a rare moment when existing domain expertise is as valuable, if not more, than traditional software development skills.
Examples demonstrated include a Dungeons & Dragons character generator that transforms webcam selfies into themed portraits with Nano Banana, generating unique backstories and character stats—all from a single prompt and deployed in moments via Google Cloud, prepared for viral or large-scale use.
Applied AI in Sheets: Unlocking Hours of Productivity From Familiar Tools
AI isn’t just bringing new platforms; it’s transforming well-trodden ground such as spreadsheets. With Gemini’s direct integration into Google Sheets, AI-enhanced workflows are available to anyone familiar with basic spreadsheet logic.
In practical demonstration, business data—such as sports teams, stadium names, and locations—can be instantly enriched by typing an “=AI()” function. For example, automatically pulling and populating real-world addresses for a column of stadiums takes just seconds, eliminating manual lookups that previously could eat hours per task. Data preprocessing, cleaning up misspelled names, or conducting real-time sentiment analysis on customer feedback also become instantaneous: describe the requirement in the formula, reference the column, and columns populate with results (classification as positive, negative, or neutral, etc.). These integrations neutralize the traditional gap between business teams and data experts.
Innovative Use Cases From Nano Banana and Gemini
The direct business applications extend far beyond demos. Nano Banana is already seeing adoption for generating professional headshots (boosting consistency in LinkedIn or intranet profiles), colorizing and restoring old family or company photos, or transforming satellite images into isometric building illustrations for pitch decks or presentations.
Standalone web apps like “Past Forward” showcase another high-engagement application: upload a photo and generate AI-augmented visuals decade-by-decade—enabling marketing, HR, or team-building campaigns that stand out.
Each of these uses demonstrates how business-oriented teams—marketing, customer service, HR, product management—can move swiftly on new ideas, automate manual work, and realize creative concepts with only a basic prompt, without the need for costly software procurement or lengthy tech onboarding.
Key Takeaways for Decision Makers
- Immediate Accessibility: All described AI tools—Nano Banana, Gemini Build, Sheet integrations—are directly available and frequently free to explore via Google Gemini app, AI Studio, or NotebookLM, reducing friction for pilot projects or experimentation.
Low Technical Barrier: Natural language interfaces mean that expertise in business context, not coding, is the primary requirement. This enables wider participation and faster prototyping within any organization.
Rapid Deployment: New solutions—from customer sentiment dashboards to creative content generators—can be conceived and launched internally in minutes, with built-in error-handling, cloud resources, and real-time output.
Productivity and Cost Gains: Workflow bottlenecks, such as manual research, repetitive data enrichment, and small imagery or analytics tasks, can be eliminated, saving substantial time and reducing the need for specialized outside services.
Final Thought
Staying current with these AI-powered capabilities isn’t just about future-proofing; it’s already unlocking new efficiencies and creative opportunities for those willing to experiment. Today, transferable business issues—from image creation to data analysis—can be addressed faster, with less technical learning curve, and with greater ownership by every team within the company. Now is the time to reassess what business teams can self-serve and where those latent creative or analytical projects might finally get the green light.
Podcast Transcript
Jordan Wilson [00:00:45]:
If you don't know anything about nano banana, seriously, where have you been? Let me drop a number here. 5,000,000,000. That's how many images have been made with, inside the Gemini app with Nano Banana in less than a month. And maybe you're thinking, oh, okay, Jordan, like, you know, I'm not like a creative person. I'm not a technical person. Why would I use Nano Banana? Well, you're gonna wanna listen to today's show and stick around. Trust me because we're gonna be, uncovering some of the secrets and real power behind Nano Banana and how you can even, in natural language, create an app in a couple of minutes that is actually using Nano Banana. It's gonna be wild.
Jordan Wilson [00:01:29]:
I'm excited for today's conversation. I hope you are too. What's going on y'all? Welcome to Everyday AI. My name is Jordan Wilson, and this is your daily livestream podcast and free daily newsletter helping everyday business leaders like you and me not just keep up with AI, but how we can make sense of it, get ahead, and leverage it to grow our companies and our careers. That's what you're trying to do. Starts right here with the livestream podcast. But if you've missed something or if you need more information, it's all gonna be in our daily newsletter. We're gonna be recapping today's show as well as all the other AI news you need to know to get ahead.
Jordan Wilson [00:02:00]:
So I'm excited for today's show. Have you not used Nano Banana? Don't worry if you haven't. Make sure if you're listening on the podcast, this is one of those more visual ones. So you might wanna go to our website and watch the video, if if if you're not gonna catch it, you know, catch it on the YouTube, stream or anything like that. But, let's just get into it. I'm excited, for today's guest. So please help me welcome to the show. We have Paige Bailey, the AI developer relations lead for Google DeepMind.
Jordan Wilson [00:02:27]:
Paige, thank you so much for joining the Everyday AI Show.
Paige Bailey [00:02:30]:
Thank you so much for having me, and I can't wait to share more about what we've been building, especially for Nano Banana. It's the other AI features that we've been incorporating into Google Workspace and our other Google products.
Jordan Wilson [00:02:43]:
Yeah. It's it's it's been great. And, you know, as someone that's been covering generative AI every day for, like, three years, there's been very few moments where I'm like, oh my gosh. There's been, like, five. And Nano Banana has been one of them. But before we get into it, Paige, can you just tell me a little bit, and our audience a little bit about, you know, what your role is at Google DeepMind and what it is that, you know, you're kind of working on on a day to day?
Paige Bailey [00:03:05]:
Yeah. So I am the area tech lead for developer experience at Google DeepMind. You might have kind of been familiar with developer relations before. We've kind of expanded this out to include more around creator experience. You know, obviously, people are starting to to be able to build apps and to build digital artifacts, with things that aren't so much code centric. So so being able to, kind of help people be successful there to work with the product teams and the engineering teams as well as modeling teams to make sure that we're getting the right data into pretraining, that we have the right evals for the models, and really just trying to make sure that as you're building with Gemini, as you're building with PO three, that you're able to do everything that you need to do. Prior to this, I, started as kind of a machine learning engineer back in 02/2009, building models mostly in, kind of the earth sciences, new background, geophysics, and applied math. And then, the world has certainly changed quite a bit, since then.
Jordan Wilson [00:04:10]:
It's it's it's changed a ton. Right? So I even remember, you know, I was at, you know, Google Cloud Next and, you know, you and and, you know, Logan took the stage there. And I'm like I'm like remembering now, like, and and just seeing the difference between, you you know, what? That was, like, April or May and where we are today. What's possible for both developers and non developers has completely changed. So, just describe for our audience, you know, what are you you know, how capable, you know, are people now to build something that maybe if they didn't have the skills before, how has it changed?
Paige Bailey [00:04:48]:
Yeah. It's I I think there's it's truly remarkable what you can do with Man O Banana in particular. So so you can think of it as kind of a natural language interface, for for images, that allows you to do most of what you would be doing in Photoshop. So you can remove backgrounds. You can, colorize images that might be historic images of your family. You can make them higher resolution. You can kind of take your Pinterest mood boards and turn them into actual, like, visualizations using your own home as kind of the background scaffolding. You can create really, really beautiful, and, hyper grounded new, kind of portrait photos.
Paige Bailey [00:05:31]:
You can generate your own passport photos, like, all sorts of things. And it's been really remarkable to see what what people have been doing there. And then another product that we're really excited about is called Build, which allows you to just describe an app in natural language, create it, and even deploy it with a unique URL without having to ever write a single line of code yourself. Mhmm. So, like, the there's even a feature with Gemini that if the if in the process of writing the code for the app, the model encounters any errors, it will take the error, feed it back to Gemini, and then, kind of self heal the code and self heal the app, to to get the right outcome for what you've described.
Jordan Wilson [00:06:13]:
So so, obviously, you you have a technical background. Right? I don't. And what's, like, what's weird is, like, everything that you just said there, it all made sense to me. Whereas maybe three to five years ago, some of that would have went over my head. Let me ask you this. Is is everyone or can everyone be a developer now at least, like, you know, go in and and get their feet wet? Right? I've I've used Jules. I've used Opal. I've used, you know, AI Studio to to build apps, Canvas and and Gemini.
Jordan Wilson [00:06:42]:
Right? Can anyone do this, or do you still need some level of expertise?
Paige Bailey [00:06:46]:
Absolutely. Anybody can do this. And I I think it's so exciting in the sense that we have hackathons every weekend in the Bay Area. It feels like we do. And it's been really magical to see that the the attendees for hackathons have moved away from just being engineers to being product managers, to being, you know, folks for maybe a sales background, a business development background who are really excited about solving problems, and who are able to describe really articulately, like, the kinds of questions that need to be solved. And now there's no hurdle. Like, there's no big chasm of, you know, software engineering ability that needs to stand between them and getting the work done of building an app that can really meet their customers' needs. So a lot of the time in hackathons, the the teams that we see winning, and the teams that we see, you know, kind of potentially even building out companies aren't really necessarily the ones with all engineers on staff.
Paige Bailey [00:07:43]:
It's kind of like the singleton PMs who have a hobby project or the the salespeople who have spent, you know, ten thousand hours with customers and who deeply know what they need and who just want to, like, build a tool that they can help address those concerns. So I am very jazzed. Like, I and I can't wait to see, things like build and things like these models be adopted more and more in the science community as well because I I think we have, you know, a ton of hyper talented people across so many different domains who haven't had the time to spend ten years learning how to be a software engineer, but who know precisely what needs to be built. And now they finally have AI democratized in a way such that they can just be let loose and create all of the things that they've dreamed about.
Jordan Wilson [00:08:29]:
Alright. Well well, let's let's do this. Let's let's let loose a little bit. So for our podcast audience, I'm gonna have, Paige share her screen here, and we're gonna walk through a couple of different use cases. One, I think is great for for nontechnical people, beginners. If if you spend a ton of time in Google Sheets like me, I think this first example, will be really, really good. This is something that, I love using. But, Paige, why don't you just kind of, walk and talk us through kind of what we can do here, inside of, Google Sheets.
Jordan Wilson [00:09:02]:
Let's go ahead and, bring it up there. So there we go. So we have, your Google Sheet showing. Just walk us through what's going on here.
Paige Bailey [00:09:10]:
Yeah. So so I have a couple of tabs that I've created in this Google Sheets document to help showcase some of the new, capabilities of our AI function, which is taking Gemini directly into Google Sheets. This first one is kind of near and dear to my heart. I am a super soccer fan. I I used to play it, used to play it back in school, and so we have a lot of teams from, teams from The UK, specifically from England, their stadium names, and their locations. And what I'm going to do is in this fourth column, I'm just going to type in equals AI. So that's the function name. I'm going to open parenthesis, and then I'm going to describe in natural language something that I would like to have as kind of a supplement to this data.
Paige Bailey [00:09:58]:
So I'm going to take this stadium names column. I'm going to say something like, return the address or the location. I'm going to add a comma. I'm going to add, the the kind of link to that, that cell. So this is all very familiar. If you've ever used Sheets before, if you've ever used Excel before, I'm going to hit enter. And immediately behind the scenes, Gemini kind of returns, the the location of the stadium name, in The United Kingdom. And then even better, kind of similar, for user experience to all of those, all of those other functions that have you United used before.
Paige Bailey [00:10:42]:
It kind of fills in and populates each one of the each one of the cells in the column, based on, based on that stadium name and location. So it's it's pretty cool to to be able to see this happen in real time, and to be able to understand that, you know, you can start generating data, analyzing data, doing things like sentiment analysis, just via natural language and the the AI function.
Jordan Wilson [00:11:09]:
Like, let me be honest. Like, where, like, where was this, like, ten years ago? Right? Because this one simple thing so, you know, Paige walked us through. There's team name, column a, stadium name, column b, location, you you know, column c. And then in column b, she just automatically pulled the address live for these 20, top England soccer teams. This would have taken, I don't know, at least for me, two hours because I woulda got distracted. I woulda went on the team's Twitter. Right? Like like, that is such a time saver. So even sometimes when you're thinking of, like, oh, what would I use, you know, Gemini and sheets for? There you go.
Jordan Wilson [00:11:44]:
Save a ton of time.
Paige Bailey [00:11:46]:
Exactly. And and it's also really useful. Like, I'm sure if anybody has ever done data preprocessing or data cleaning before, you've experienced the pain that that is, you know, people's names spelled slightly differently or capitalized slightly differently in the same column. State names, city names, slightly misspelled. Like, with this function, what you can do is you can kind of go through. And for those fuzzy problems that didn't even have, like, exact functions to help you tackle, this AI feature can kind of go through and make data preprocessing so much easier. I have been using it all the time, honestly. And, and I I think it unlocks kind of these more complicated data analysis, workflows for people who previously would have had to learn something like Python or r to do those automations.
Jordan Wilson [00:12:37]:
Yeah. Such such such like a great, I think, use case for anyone out there, you know, whether you don't wanna have to go through and manually do it or just enrich your spreadsheet. So alright. What are you showing us here, with Yeah. We're still coming.
Paige Bailey [00:12:49]:
So so this is a surprise for you, or at least you you've probably done it before. So it's, but I haven't shown you this tab. I I just grabbed, some comments from different social media platforms. So, full disclosure, some of the comments might be a little bit spicy because they they come from social media. But one of the cool things that you can do with Gemini as well is you can ask for sentiment analysis. So we have some gems that are baked in. You can also just ask in natural language to classify based on whatever categories that you would like. But it, but you can kind of give, you can kind of give the, the kind of table views for customer sentiment.
Paige Bailey [00:13:30]:
You can summarize the customer sentiment of the support tickets. You can, kind of analyze at scale how customers feel about a product, or kind of similar to what we just did before. You could say, like, classify the sentiment, for the statements, into positive, negative, or neutral. And, and then just say, like, alright. Well, b two, and then it will go through and kind of do the the classification for you.
Jordan Wilson [00:14:04]:
I've I've spent again, all these things, I'm, like, like, laughing and and, like, face palming the just hours I've spent and the money I've spent in years past to pay for tools that would monitor sentiment analysis on social media, and Paige just showed us, oh, you can just click a button now in in Gemini and Sheets. So alright. I wanna get into the second use case. But before we do, a quick very quick word, you know, from our sponsors. Great timing. Google, NotebookLM.
Jordan Wilson [00:15:45]:
Alright. Let's get I I like, I actually literally forgot until just now. If any of you are listening to this and you're like, wait. I've I've I've heard this page sounds so so familiar. I think it's, you know, a a previous partnership we had with with Google. I think we had page, you you know, talking about Gemini 2.5 Flash. So, great great timing.
Paige Bailey [00:16:04]:
Amazing. And I also like, I have to say, like, NotebookLM and Steven Johnson. Like, he's just such a sweetheart too. Like, they they have been, rolling out features like gangbusters. It's been so awesome to use audio overviews and all of the analysis features in as well.
Jordan Wilson [00:16:20]:
Oh, it's been yeah. And and I do have to shout out, like, Josh. Like, Josh Woodward, I'll, like, you know, DM him something. I'll be like, hey. This isn't working. And then, like, a day later, he's, like, fixed it. I'm like, this is crazy.
Paige Bailey [00:16:33]:
I don't think he sleeps. Like, he is he is and he he does that for all of the products, but within labs, within DeepMind, is just kind of, like, the most helpful person I have worked with in my entire career. So, like, if y'all don't follow Josh Woodward on all of the social media, I strongly, strongly recommend it.
Jordan Wilson [00:16:51]:
Alright. So, Paige, let's let's get into the next one. Let's show people how you can literally build an app in natural language with Nano Banana, with the viral AI image generator and editor. Let's see it. Walk us through it.
Paige Bailey [00:17:06]:
Absolutely. So so, right now, I'm in AI Studio. AI Studio is kind of the first place to go to get access to DeepMind's models as soon as they're released. You can select different models here off to the right, including Nano Banana and see kind of information about them behind the scenes. You can also use many of these models in our products like the Gemini app, but this just kind of gives you an under the hood kind of view for a lot of the models and their capabilities. But the feature that we're talking about today is this thing called built. It's this little puzzle piece guide that you might see here off to the left. And when you click on it, you're kind of put into this gallery of a whole bunch of apps that, that the team has created to kind of inspire you, or you can just describe an app that you would like to create in natural language, and have it generated for you.
Paige Bailey [00:17:55]:
So today, I, I am going to, you know, we we talked a little bit about Dungeons and Dragons before. So I'm going to just, you know, create, an app that allows all of my friends to generate, like, hyper personalized characters using Nando Banana. Does that sound good?
Jordan Wilson [00:18:15]:
Or Yeah. Let's let's let's do it. And literally, like, y'all, she's there's there's no editing. You know, if you're listening to the podcast, she's doing this live. She's typing this out inside of AI studio in the build feature. So anyone can go do this in natural language. But, yeah, maybe why don't you kind of, literally just dictate even what you're typing to your page just so our audience can, can can imagine it with you.
Paige Bailey [00:18:37]:
Yeah. Absolutely. So I'm just going to type create an app that uses the webcam to take an image of the user. The app should then use nano banana, to, to, modify the image of the user into a Dungeons and Dragons character, unique Dungeons and Dragons character. Make sure that the app also includes character stats, so, like, strength and dexterity and all that good stuff, and that the app is well designed. So let's do control enter, and see what we get. That was obviously, like, a very simple prompt. I'm not the best at prompting.
Paige Bailey [00:19:22]:
I should have probably used Gemini two dot five pro to help me, like, rewrite my prompts behind the scenes.
Jordan Wilson [00:19:27]:
It's it's it's better. It's it's better just to go with, you you know, your gut, something simple. So, like, as this is building, so it's telling us exactly what it's doing. Right?
Paige Bailey [00:19:36]:
Yeah. It absolutely is. If you've ever played SimCity 2,000 and you've seen, like, the loading screen Yeah. For, like, reticulating splines, it looks very, very similar. It's, basically defining everything that it would need to do in order to build out this app with all of the, kind of the the stack associated with building, a really nice web application. If it needs to generate prompts behind the scenes for any of these models, it's, it's kind of defining those prompts as well. We're kind of put into this thing that looks a little bit like a a development environment. So you can see the code getting generated off to the right.
Paige Bailey [00:20:13]:
This really nice directory structure in the center. If you're a developer, you can kind of one button click save this as a public or a private GitHub repo. And if Gemini encounters any errors along the way as it's building this app, what it will do is it will take that error. It will put it back into the model, and then it will use all of that to kind of, to kind of self heal and, like, fix itself before, before the app exists. But it looks like we've already got the app. It's done. Yeah. It's done.
Paige Bailey [00:20:44]:
So let's test it out. I'm going to begin this quest. It says d and d character forge, which sounds very, which sounds very, very cool. I'm going to take a picture. I'm going to forge my character. I used the webcam to take a picture, so that looks like it was, pulled up correctly. It's consulting the elder scrolls and forging arcane artifacts. This is very cute.
Paige Bailey [00:21:10]:
So it's got my before image. It's got my after image. That's super cool. I am a for anybody, I'm a wood elf ranger, and I'm chaotic good. And it's got, like, the the same, it's got kind of, like, the same peace sign. It's got the same facial structure. My hair is a little bit purple, so maybe that's inspiration that I should make a a lifestyle choice change, for, like, dying
Jordan Wilson [00:21:34]:
Predicting the future, it seems as well.
Paige Bailey [00:21:36]:
Exactly. And then, and then it's got strength, dexterity, wisdom, charisma, all that good stuff, as well as a backstory. So Lyra grew up in a secluded elven forest, learning the ways of nature and the bow from an early age. This is awesome. I love it.
Jordan Wilson [00:21:53]:
This is nuts. This is and and and, yes, she literally did this live in real time. Just said nano banana and obviously knew to use Gemini 2.5 Flash, and she used her webcam right there, like, just vibe coding in the airport. So now how can you actually use this and share this? Walk us
Paige Bailey [00:22:10]:
through. Well, of course, I want you to join my Dungeons and Dragons campaign. So so, like, and all of the folks who are listening today. So I'm going to go ahead and click this little rocket symbol that we have on the right that allows us to deploy the app automatically to Google Cloud. I'm going to select the cloud project. I'm going to click to deploy the app, and then it will kind of generate a unique URL behind the scenes. So this URL, you can share with friends, family, coworkers, and it will also hook up everything else that you need from a cloud project perspective. So storage, logging, Cloud Run, like, it hooks up all of the all of the infrastructure so you don't have to worry about any of it.
Paige Bailey [00:22:51]:
It's doing it in a secure way because it's using Google Cloud. And then if I click, this kind of cloud project, it will also give me insight into logs, so all of the things that were required to to build this app, and then also billing. So if this happens to go viral, I can kind of see, and also no judgment. This is my personal, my personal GCP account. It shows me all of the services and all of the costs associated for the different products, that have been used. So it's it's really, really nice to have all of this handy, and we were able like, this is effectively a hackathon project using Nano Banana deployed with a unique ROI that, took us less than, like, two minutes to build. It's kinda bonkers.
Jordan Wilson [00:23:40]:
Amazing. Yeah. Amazing. Like, I even as, you know, Paige Paige was talking there, I I I already used it. I already have my own character. Not as much strength and dexterity as as Paige, but, you know, I gotta start somewhere. I gotta start somewhere. Alright.
Jordan Wilson [00:23:55]:
So so Paige, you gave us a a a great, you know, Gemini use case for nontechnical people. We dove into and talked about some different nano banana use cases. You built something literally live in in, like, a minute. So I wanna ask you this as as a third thing. What's been your personal, you know, favorite either either use case of Nano Banana, your favorite project you've seen maybe someone else build? What's kind of that that one thing that you always go to? You're like, this is such a great use case. Because I feel there's, like, unlimited use cases.
Paige Bailey [00:24:26]:
There's there's so many use cases. One of my, one of my favorites has really been because often, I don't have time for professional, like, you know, the the kind of professional headshots that you might put on LinkedIn for for myself, and I know that my coworkers don't either. You can ask for Nano Banana to create professional headshots. I've been using it to colorize old family photos, which has been, like, really exciting for my mom and for all of my, like, family members to see. There's also a really great use case where you can give it an aerial satellite image of a place and then have it turn into an isometric building, that you could use for a game. So it looks like, kind of a pixelated a pixelated scene from a, from a video game. You can have it imagine what a street view like it looks like for a given place that you might have on satellite images, but one that everybody on the call can try out today, that's that's part of our, kind of Gemini app showcase, is actually called Past Forward. It was created by my colleague, Amar.
Paige Bailey [00:25:36]:
And what you can do is you can generate yourself through the decades, which is quite cool. So if I was to, kind of upload a photo, so I'm just going to, to select an old photo that I have kinda hanging out on my, hanging out on my, my laptop. I'm going to click generate. And then this app behind the scenes, and I'm gonna zoom out a little bit so folks can see, it creates different images from the nineteen seventies, from the February, and kind of allows you to to kind of see yourself, in all of those different, age I love the aviator glasses from the seventies. Like, holy moly. But it and also the big pair from the nineteen eighties, like, I would absolutely rock that. Like, this is, this is really, really cool, and is something that you could do today, with your friends, your family, and kind of have, have displayed along the way as well.
Jordan Wilson [00:26:39]:
The the possibilities are are literally mind boggling. Right? Like, like, hey, Paige, I could have you show us hundreds of demos every day, and I still don't think we could honestly scratch the surface of what's possible, in in Nano Banana. But, you know, as we as we wrap up today's show, Paige, what would you say is is your one, you know, most, you know, practical or tactical, you know, piece of advice that you have for people to start going in and maybe either using Nano Banana on the front end in AI Studio or building with it? What's that one piece?
Paige Bailey [00:27:14]:
Yeah. So so I would strongly, strongly recommend like, I I know there's a lot coming out. Like, at DeepMind, it feels like we're releasing new models and new features every four or five days. So it's it's been a it's been a hard thing to keep up even further, all all of the folks working on the team. But, really, the best way to to kind of understand what these models are capable of, is to test them out yourself. So roll up your sleeves. Like, Google's made a lot of these models available to use for free via the Gemini app, via NovocLM, via AI Studio. So if you have something that you've been curious about, if you have, like, a workflow that's really frustrating that you would love to automate, just go in, ask Gemini, like, to to help you, to help you write a prompt if you don't know how to prompt yourself or if you're just getting started, and just test it out.
Paige Bailey [00:28:07]:
Like and I guarantee you, if you try it, if you, keep iterating, if it doesn't work the first time, I I think that you will be surprised to see how far these models have come over the last six months. And given that this is a new space, given that this is a complete reimagining of everything, machine learning and AI, over this past couple of years, like, you're getting started at pretty much the same place that everybody else is getting started. So, really, there's still time. There's still room to get in on the Ground Floor. Don't be afraid. Like, just test things out.
Jordan Wilson [00:28:41]:
I don't I don't know what's more impressive, you know, what we've seen in Nano Banana or what Paige Bailey just delivered in twenty seven minutes in terms of value. My gosh. So if you miss anything, if you're listening, make sure you go check out our newsletter. We're gonna be recapping it all. But, Paige, thank you so much for taking time out of your day to join the Everyday AI Show. We really appreciate it.
Paige Bailey [00:29:01]:
Thank you. Thank you for everything that you're doing to kind of bring AI to everyone and make it approachable and accessible. We appreciate you and, can't wait to listen to your next podcast.
Jordan Wilson [00:29:11]:
Alright. Well, hey. Every day. So you can't it's it's hard to miss it. It's hard to miss it. Alright. So thank you everyone for tuning in. Like I said, if you haven't already, please go to youreverydayai.com.
Jordan Wilson [00:29:20]:
Sign up for that free online newsletter. We'll see you back later for more everyday AI. Thanks, y'all. Awesome.