EP 593: Google Opal: The Simplest Vibe Coding Ever? How to Use It

Topics Covered in This Episode:

1. Google Opal Vibe Coding Tool Overview
2. How to Use Google Opal: Step-by-Step
3. Opal vs. Cursor, Replit, Copilot Comparison
4. Building No-Code AI Apps with Opal
5. Google Opal Natural Language Workflow Creation
6. Opal for Task-Based AI App Development
7. Google Opal Beta Features and Limitations
8. Prebuilt Google Opal Apps and Templates
9. Visual Editor and App Sharing in Opal
10. Opal’s Integration with Gemini AI Models

Keywords:

Google Opal, Opal vibe coding, vibe coding tool, no code AI, Google AI, Google Labs, natural language app builder, AI app generator, AI workflow automation, task apps, visual app builder, Google Gemini, Gemini app, AI chaining, Google AI models, Gemini 2.5, Gemini Pro, Gemini Flash, imagine 4, AI image generation, Vo3, audio LM, Lyria 2, multimodal AI, deep research, interactive web application, app editor, Opal gallery, prebuilt AI apps, app remixing, AI output customization, Google account required, beta access, AI for nontechnical users, AI chaining tools, Google Jules, Cursor, GitHub Copilot, Replit, Lovable, full stack AI app builder, knowledge workers, coding automation, AI task automation, Google Imagine, AI video generation, app theme customization, AI image art, Google Drive integration, workflow editor, AI-powered productivity, Edge AI, small language models, app sharing, AI for business, AI problem solving, Google AI Studio, experimental AI apps.

Podcast Transcript

Jordan Wilson [00:00:47]:
I still think that vibe coding has barely caught on. Yes. It's one of the trendier, words in AI in 2025 so far yet. I think there's literally hundreds of millions of people that would probably vibe code a lot more if there was a simpler entry point. Sure. There's software like cursor and get hub copilot and so many others that are actually very easy to build full stack apps. But what if you just need something simple or a way to dip your toe into the vibe coding waters? That's exactly what we're gonna be going over today in Google's newly released Opal tool and what I think is the simplest vibe coding tool ever. I mean, talk about no code.

Jordan Wilson [00:01:41]:
There's literally no code. So in today's show, we're gonna go over, different ways that you can use it, and I'm gonna show you live how to do just that. So on today's show, we're gonna go over the basics of Google's free Opal vibe coding tool. We're gonna compare it to other vibe coding platforms like Cursor, GitHub Copilot, and Replit, and show you live how it works. Alright. I'm excited for today's show. I hope you are too. What's going on y'all? Welcome to Everyday AI.

Jordan Wilson [00:02:10]:
My name is Jordan Wilson, and Everyday AI, it's for you. This is your daily livestream podcast and free daily newsletter helping everyday business leaders like you and me not just learn what's happening in the world of AI, but how we can leverage all of this to grow our companies and our careers. So if that sounds like you, what you're trying to do in it starts here with the unedited, unscripted live streaming podcast. But if you wanna take it to the next level, make sure you go to our website at youreverydayai.com. There, you can sign up for our free daily newsletter. We're gonna be recapping the highlights from today's show. So if there's something maybe you're listening in the car, out on the treadmill, maybe there's something you hear and you're like, wait, what was that? You can always check-in our newsletter as well as we keep you up to date with all the other news happening in the world of AI. So this is gonna be one of those that's a little bit better for our live stream audience watching the video.

Jordan Wilson [00:03:01]:
But if you're on the podcast, you can always go to our YouTube channel or our website. Like I said, youreverydayai.com and watch the video of this. This is gonna be a little bit more visual, but I'm gonna do my best to describe this to our podcast audience. And speaking of audience, when I say your everyday AI, it's yours. This is, you know, we've started this new AI at work Wednesdays showing you ways that, you know, we're using AI internally. And I said, what do you all want? And you voted for Google's new Opal tool. It was actually, pretty close between a couple different tools there. But let's get straight into it.

Jordan Wilson [00:03:38]:
And, also, I did put together a list of 20 ready to go Opal apps. So, maybe after today's show, you're like, wait. That sounds interesting, but what are some ways I could use it? So, go repost this show, on LinkedIn, and I will send you access to those. Alright. So let's get into the basics. What the heck is Opal? Well, it's a free vibe coding tool released from Google, and it's much different than these other, kind of vibe coding tools out there. Technically, Google has, like, five different ways, you can vibe code, and I'm gonna be comparing, Opal with some of the other more popular ones, mainly, Jules and some other, very much more, fully featured vibe coding tools like Cursor and Replit and others. But for the most part, it is a completely new way to build apps.

Jordan Wilson [00:04:34]:
Okay? So the way that Google says it, it says you can build, edit, and share multi sorry. Build, edit, and share many AI apps using natural language. So, you know, a lot of these vibe coding tools, when people look at them, right, like Lovable and Bolt and Cursor and, all these other ones, And it can be a little daunting because you're like, wait. I thought this was like a no code thing. Like, why do I have this entire repo, and I'm having to, you know, make these MD files and, like like, what the heck is going on? If if you've ever felt that and you just wanna, like, experience something for the first time, I think Opal is great for that. It is free. If you have a Google account, that's all you need to get going and you can literally and I'm not exaggerating this. You can build a fully functioning app that you can share with others and it works in, like, less than a minute.

Jordan Wilson [00:05:27]:
So I'm gonna do something a little more complex, but let's dive into a little bit more an overview of exactly what Opal is and how it works. So like I said, right now, it is free, but it is experimental inside Google Labs. So, I believe the last I read, it's only open, in the beta only, so you can opt into it on Google Labs. And right now, it's only available for The US. I will double check that because Google is literally shipping things, like, daily. So I will make sure to double check that before we put out today's newsletter. And, essentially, natural language. You just tell Google what you want it to build, and it's gonna build a visual multi step workflow that you can go in and edit later.

Jordan Wilson [00:06:11]:
And it changed together different prompts, model calls, and Google Gemini tools. That's the great thing. Essentially, anything that Google Gemini has released, you can use that inside of Google Opal. So if you've ever seen maybe, you know, the v o3 video generator, or the imagine four or just any of Google's models. Right? They have the, top end Gemini 2.5 models, and you're like, wow. I wish I could build something on that while you can. And it takes literally less than a minute to build something extremely basic, or you can spend a little bit more time modifying it. So users can edit workflows via a conversational command, or a visual editor, then you can test and refine your apps.

Jordan Wilson [00:06:54]:
And finished apps, can be shared with others who also have an Opal account. So, yeah, you can't just, you you know, share it publicly. You do have to share it, with anyone that has also signed up for Opal. But like I said, all you need is a Google account right now in The US. Takes less than a minute to get up and running. So my biggest takeaways, I've been using it since it came out on some of my different accounts. If you think that you're gonna build your next SaaS or your next iPhone app with this, that's not what it's for. I like to say this is great and the best for task apps.

Jordan Wilson [00:07:33]:
Right? So I think a lot of times when people think about vibe coding something, they're running into an issue and then they think, okay, I need to build a fully functioning web app for this, or, oh, this could be an iPhone app. Right? Whereas, maybe first, you need to validate it just quickly. Like, can it be done? Is there a market for it? Or even maybe you're just like, let me just build this for myself. Maybe it doesn't need to be a full stack with a back end, login, pricing, users, a dashboard. Right? Maybe you don't need all that. Maybe you just need to build yourself something that's gonna solve one of your problems immediately. And I think that's what Opal is great for. If you go back and listen to my 2025 AI prediction and roadmap series, I said nontechnical people are gonna be building themselves apps just to solve their daily issues.

Jordan Wilson [00:08:18]:
And I think Opal is the one for that because it is dead simple. Right? In the same way that I think NotebookLM has changed the way a lot of people work even nontechnical people. I think Opal might be that tool that does it for nontechnical people that you can just code task apps. That's what I call. These aren't full stack, fully customizable, right, where you can, you know, change every pixel. It's not like that. These are more task apps. They're not highly customizable, but I think if you just reframe your brain into, like, okay.

Jordan Wilson [00:08:49]:
Do I just need, you know, an AI tool that can do something for me that's repetitive and I don't really care about how it looks, but I do have some customizable, the ability to customize how it functions. That's what Opal's for. And by far, I think this is the easiest way to vibe code away, nagging problems for everyday people. And I'm gonna give you an example of something that I've started to use it for, and I'm gonna continue to refine it for myself as well. So like I said, Opal is free. You don't need to pay for API usage or hosting. That's the other thing. A lot of times if you're trying to build an AI app, you have to connect it and pay for that AI usage.

Jordan Wilson [00:09:28]:
Right? So if you're using OpenAI's API or Claude's API, right, you have to actually pay for it. You're not paying for it, inside Google Gemini. Right? I've been saying this since AI Google's AI studio came out. It's like I feel like I'm robbing Google, whenever I use it. Same thing with Opal. The fact that I can create an app that has Gemini embedded, I can use anything Google essentially, anything that Google Gemini has released, and it's free. Of course, it is in beta. It's experimental.

Jordan Wilson [00:10:00]:
Right? So that doesn't mean it's gonna be around in five years. It might get folded into other products. But right now, I mean, I've been talking for eight minutes. You could have already built multiple AI apps that solve it. And this is the most no code vibe coder there is Mainly because there's literally no code. Alright. So let's start live, shall we? Alright. Live stream audience.

Jordan Wilson [00:10:27]:
Do me a favor as always. Let me know if you can see the screen. So this is, I started on one of my other accounts, so, not, littering your screen with a thousand things. So here's what we're gonna do. When you go on to Opal, you'll see it's an experiment. You have to be logged in. So, please follow along live for our livestream audience or, you know, if you're in the podcast, you're in your car, hit pause, jump back in in front of your computer. Let's vibe code some stuff together.

Jordan Wilson [00:10:57]:
So when I log in, all I'm gonna do is go click create new. Alright. And there's different ways that you can create a new app inside Opal. I'm gonna show you one way, and then I'm gonna show you the other. And I'm not gonna fully build the app out the first way. I'm just gonna show you how it functions. So, for our livestream audience, you'll see and hopefully, podcast audience, I can explain this easy enough. So right now, there's two different panes.

Jordan Wilson [00:11:25]:
So the main pane, it's kind of like a canvas, and I can also chat with Opal, in this canvas view as well. And then on the right side, I can actually preview the app. It's going to build it and render it as we go, which is really cool. So if you're used to using, you know, canvas mode in Gemini or ChatGPT or artifacts in, Claude, it's the same thing. You kinda chat on the left side and then you can see things rendered on the right side. So a very familiar interface. However, the big difference here is now there's essentially, like, a canvas, a whiteboard that you can actually drag things in and build. So, essentially, you have user inputs.

Jordan Wilson [00:12:05]:
You have generate, which is the Google Gemini capabilities, and then you have an output. So, then you can also add different assets. You can upload files connected to your Google Drive, YouTube, text drawing, etcetera. Right? So we're not gonna get into assets. I just wanna show you the two different ways that you can build an app. So one is you can do it more manually by just clicking these assets and dragging them around the board. So as an example, I can click user input, and our live stream audience will see. Now there's a bright yellow box, and it just says user input.

Jordan Wilson [00:12:40]:
Right? And then I can go in and select it in the editor. So then on the right side, I can click the at key, and then I have different options. Right. I wouldn't do these for the user inputs because for the most part, user input is gonna be a text command from me, the user. So keep that in mind when I'm building this. The user input is what the person using it, which is probably gonna be you or your team, is ultimately gonna put in. So I can type in different commands there. I'm gonna leave this blank.

Jordan Wilson [00:13:06]:
I'm just showing everyone an example of how this works. Alright. And then I have generate. So here's where the magic happens. Alright. So this is all the different capabilities inside Google Gemini. So I have different models here. So I can choose different models.

Jordan Wilson [00:13:22]:
I can do Gemini 2.5 Flash Pro. You can, you can do in-depth research. You can plan and execute different tasks. Here's imagine for Google's state of the art, AI image generating model. There's audio l m. You could generate speech from text. There's a VO. I don't I'm not actually sure if this is Vo3 or two.

Jordan Wilson [00:13:44]:
I will have to reach out, to my friends at Google and double check that. And then you have Lyria two, which can create instrumentals from text. So talk about a literal creative sandbox here. Right? So think. If you've ever been using a large language model and you're like, man, I wish when I type something in, I could get video out or an image out or, you know, an instrumental out. Right? Now you can, and it's literally just on a drop down. Alright? And then essentially, what you would do to connect these things is you drag an arrow from your user input to your generate. Right? I have to actually, connect that.

Jordan Wilson [00:14:23]:
There we go. Alright. And there we go. Sorry. Didn't get a little little backwards there. Okay. So we have our user input that sends the user inputs to the generate tab. I choose what I want it to do.

Jordan Wilson [00:14:36]:
Alright? And then I can, you know, type in instructions. Right? So, you know, I can say, you know, take the, take the user input, and that's a selectable item, and use, you know, Gemini 2.5 Flash to blah blah blah blah blah. Right? And then all I have to do is click output. Alright? And then I drag the generate to the output. So it's simple. Podcast audience, think I have three little things up on a whiteboard, user input, it gets sent over to generate, inside generate. I could choose what Google, capabilities I want, and that gets sent over to an output. And so I essentially have in the app, not none of this would work yet.

Jordan Wilson [00:15:17]:
I'm just showing you the two different ways that you can build it. So that's way one, but I say do it the other way. It's way easier. You just type something, and describe what you want to build. Okay. So I actually have a little prompt here, and I'm gonna put it in, and we're gonna get it going. So here's what I said. And we're gonna watch because it's going to be built live.

Jordan Wilson [00:15:47]:
Right? So now I'm telling Google how I want this to be built. And actually, it might take a minute or two. Actually, no. I lied. It's done. My gosh. That was fast. Alright.

Jordan Wilson [00:16:00]:
So it's very it's very impressive. Alright. I couldn't even explain what I wanted to be built, because it's already built. So you'll see now I have a user input. I have a multiple step, generation process, and I'll explain exactly what's going on. So there's some some simple conditional logic here. Alright. There's four different processes, four different generates, and then it gives me an outcome.

Jordan Wilson [00:16:28]:
And I literally have an app ready. Alright. So now in the right hand side, it built an app. Like I said, these aren't, apps that you're gonna be building and and, you know, moving things around pixel for pixel. For the most part, I mean, you have a little bit cussed like, a little bit, customization options. Right? You can go in and create a a certain theme again with AI. Right. So I'm just gonna go in and alright.

Jordan Wilson [00:16:56]:
Let's see here. All right. I'm running into an issue. I think it's because when I was clicking around. All right. So actually what I'm going to do, when I was clicking around, I accidentally disconnected one of the nodes. So I'm just going to, redo that app. Bam.

Jordan Wilson [00:17:15]:
And it's gonna cook here in a second, but in the second, let me actually take quick pause halftime break, thirty second halftime break word for word from our sponsors.

Google Gemini [00:17:28]:
This podcast is supported by Google. Hey, everyone. David here, one of the product leads for Google Gemini. If you dream it and describe it, v o3 in Gemini can help you bring it to life as a video. Now with incredible sound effects, background noise, and even dialogue. Try it with a Google AI Pro plan or get the highest access with the Ultra plan. Sign up at Gemini dot Google to get started and show us what you create. This podcast is supported by Google.

Google Gemini [00:18:04]:
Hey, everyone. David here, one of the product leads for Google Gemini. If you dream it and describe it, v o3 in Gemini can help you bring it to life as a video, now with incredible sound effects, background noise, and even dialogue. Try it with a Google AI Pro plan or get the highest access with the Ultra plan. Sign up at gemini.google to get started and show us what you create.

Jordan Wilson [00:18:36]:
Alright. And, yeah, in that thirty seconds, obviously, Opal rebuilt the app that I accidentally, screwed up there. Alright. Let me just go ahead and tell everyone exactly what I told Opal to do. This is putting AI to work at Wednesdays. This is something I'm actually using, and I like it. So I said I want to create a simple app called a podcast episode outline generator for my podcast, Everyday AI. Give the app either I want to be able to give the app either a basic or a specific topic, and it will do very specific reef research for me that is timely and relevant.

Jordan Wilson [00:19:13]:
It should first start by searching Google for the topic I want on today's date, then this week, then this month, then prior months. So I'm giving it directions on how I need it to search because if I'm using this to help me plan and research episodes, I need to make sure I'm researching today's news first, then this week because I don't wanna be re researching stuff from months ago. It's very old. Then I say, being fresh and timely with information is paramount. Essentially, I'll give the app a topic, then it will give me three different episode topic ideas and outline what should be covered. The three ideas should be different from each other. The outline should include a suggested title, five major topics to cover in each episode, and factual bullet points of each of these topics. It should also use Google's imagine to create a visual for each suggested episode.

Jordan Wilson [00:20:07]:
The app should be easy to use and interactive. Alright. So it's obviously done. So essentially, now I'm back on, the kind of whiteboard version, and I have my podcast planner on the right side, because I'm in editor mode. But I can click app mode, and that essentially, launches this very basic app full screen. But let's go back into editor mode and explain a little bit of what happened. So it took my prompt and it created this app, in this kind of like whiteboard version. Right? And I can go in here and I can edit things and refine them a little bit as well.

Jordan Wilson [00:20:44]:
But essentially, I can go in. Let's zoom in a little bit here to see exactly what's going on. So on the user, sorry. I'm not used to using this on my, it's it's a scroll thing. I wish I could click and drag, but it's a little different. So essentially, on topic, this is the user input. So, the user in enters the podcast topic, then, it takes that topic and it carries that topic over, to the three different generate tabs. So it's doing multiple steps of research, and it's passing it on, to each of the generate tabs.

Jordan Wilson [00:21:18]:
And then in the end, it's creating an interactive web application. So, again, the input is the podcast topic, the generate using Google Gemini. It does three different steps of researching and passes the information onto each different step. And then last but not least, the output is an interactive web application. Pretty cool. Right? Let's see if it works. Alright. So I have something already typed up.

Jordan Wilson [00:21:46]:
So let's use the app mode, and I'm gonna click start. Okay. So all it is, it now there's no no fancy visuals, no animations. This is straightforward. That's why I call this more of a task app builder, and it's not a traditional fully featured, you know, full stack, you know, agentic coding tool. Alright. So all I'm doing is now I'm putting in a simple prompt. And what it's showing me right now, it's conducting deep research.

Jordan Wilson [00:22:16]:
And I'm actually gonna skip over to editor mode because it's a little more fun to watch here because you can literally watch as it takes my query from step to step. So it's in the first step right now. So the first of those three generate tabs is highlighted, and I can see it says conduct conducting deep research. So, on those different modules, one of them was doing a version of Google's deep research. So this is great. This is the normal process I do. The way I normally research a topic is I will manually start typing out my ideas, my bullet points, you you know, facts from the newsletter, etcetera. And then I'll send those to Google's deep research, open it OpenAI's deep research, Claude's deep research.

Jordan Wilson [00:22:59]:
Right? And then I take all of that information, and then I'll start, organizing it first myself. I'll say, okay. Based on all this, I'll start browsing it, and I'll start outlining it. And then I'll send my, a a a rich, initial outline, and all of this deep research, over to different AI tools to help me start outlining my shows. Right? It's a very collaborative process. I usually ultimately use OpenAI's Canvas or, Gemini Canvas so then I can do a more interactive, element with the, the AI. So now already, it's moving on to the second step. So you'll see right away.

Jordan Wilson [00:23:36]:
You might be wondering, okay, why is this taking so long? Well, it's not because it's literally doing, multiple steps of deep research. Alright. We're already now it's creating images. So now I can see the third of the three generate icons is highlighted. So I know I know right now, it already did a bunch of research. It made those, podcast ideas and I assume right now what's happening, because I can see it's highlighted. It's using imagine, four to create visuals as well. And now it's on the last step in the output, and it's creating an interactive, kind of web app just based on the prompt that I sent.

Jordan Wilson [00:24:20]:
And the prompt that I sent, I all I my my topic was quarter three twenty twenty five trends of smaller language models, like Google's Gemma three two seventy m, which just came out, this week, and OpenAI's GPT OSS 20 b and the rise of Edge AI. So I do wanna do an updated show sometime soon on, kind of this rise of the, smaller language models. They're getting much more powerful, much more robust. So I literally just built an app, customize it with natural language, and it went out, did, did a bunch of research, put it together how I wanted to. It it should give me three different episode ideas based on my topic I gave it. It should bullet point factual, information on those different episode ideas, and it should also give me, some some image art. Right? So, it's probably not image art that I would actually use, you know, on a zero shot. I would probably go in after the fact and, use it a little bit.

Jordan Wilson [00:25:21]:
Alright. So it's done. It's done. That was pretty impressive. Alright. So now I'm going to drag I'm actually gonna go in full app mode. So hopefully our live stream audience can see this. This is pretty this is pretty cool.

Jordan Wilson [00:25:38]:
Alright. So I have the three different ideas here that, this this this is really, really cool. I'm just cheesing a podcast audience because, man, I like this this technology is really, really impressive. Okay. So I have the three different episode ideas. So one, it says edge of innovation, how smaller AI models are reshaping quarter three twenty twenty five. The second one, it says Gemma 03/02/1970, Google's tiny titan of on device AI. And then the third one, it says OpenAI goes open.

Jordan Wilson [00:26:13]:
The GPT OSS 20 b and the future of accessible AI. So it looks like I gave it kind of two examples. So it built out episode ideas on the two examples, and then it made more of a general one. So right now, it's I have this kind of interactive, almost like a little miniature website. The three episode ideas, when I hover over them, I can tell there's more information. So when I click on one okay. Let's see if I can click on them all. Okay.

Jordan Wilson [00:26:38]:
Cool. I can't click on them all at the same time, which is pretty nice. So each of these, it should have at least five bullet points. One, two, three, four, five, six. It gave me six, and that's fine. Oh, no. Oh, gosh. Okay.

Jordan Wilson [00:26:51]:
It gave me a ton, a ton more information than I even asked for. So it looks like it gave me different categories. So let's just walk through the edge of innovation. The first one, how smaller AI models are reshaping quarter three twenty twenty five. So give me five different categories, and then in each of those kind of categories, it bullet pointed additional information. So it says, first, the rise of small language models. Second, edge AI. Third, the convergence, small language models, and edge AI synergies.

Jordan Wilson [00:27:23]:
The fourth, industry transformation in real time impact, and then privacy, efficiency, and accessibility. So pretty good. So I'm actually gonna look now at the GPTOS version because this is the only one I've done a dedicated podcast on, and I wanna look at the quality of research here. So it says the GPT OSS 20 b model was released on August 5. That's correct. It's available under the permissive Apache two point o license. Correct. Allowing free building, customizing, and deployment without restrictive copyright.

Jordan Wilson [00:27:54]:
It marks OpenAI's first open way language model released since g b t two. Correct. Signifies a strategic recalibration towards an open source strategy responding to growing open source AI community and competition. Correct. CEO Sam Altman indicated consideration of a different open source strategy. And, yeah, this is all really, really good. So this right here is something I'm gonna be using all the time now because this is something this multi step process is something that I've been doing manually. Right? I would obviously go in and refine this.

Jordan Wilson [00:28:30]:
I essentially just zero shot at this thing, right, or one shot of this thing. I gave it a very simple prompt, no going back and forth, and it did a pretty good job. And then it also gave me these different, visual concepts down here, at the bottom. None of them are breathtaking, right, but it just pulled together some different visuals based on the content. So, nothing that I would probably use for the most part. I mean, there's a couple of these I might use, like, in an infographic or on a blog post. Nothing's blowing me away per se. But, again, all I did is say, make me some images.

Jordan Wilson [00:29:05]:
Right? If I was more descriptive on the type of images, the style, what I would be using it for, I would assume that these visuals would be a lot better. But here you go. I essentially, for each and every podcast idea that I have, I can go get multiple different angles that I can tackle this from. Some of my base research has already done for me. And although these visuals right now might not be great, eventually, they might. Right? I can spend some more time, be a little bit more descriptive, and then I can go in and edit the app as well. So as an example, now I'm going back into the app editor, and I'm looking, at what it built. So again, all I did natural language, but I can go back in, click any of these modules, and edit them as well.

Jordan Wilson [00:29:48]:
So as an example, the generate podcast images, I can go in and see exactly what's happening. So I can go over here on the right hand side, and it looks like it used Gemini two point o flash image generation. But maybe I wanna use imagine four. Alright. So, I can do that, and then I could rerun it. And I'm guessing those images are gonna be much, much better now. Right? So it was using a much older version, and actually underappreciated and underutilized model in Gemini two point o flash because it does text and images in the same model, but the image quality is nothing near what a matching four is. So if I ran this again, I'm guessing it would be much better.

Jordan Wilson [00:30:28]:
Alright? And it saves automatically. Right? So that's really, really cool. So let me show you one or two other things quickly in Opel, and then I'm gonna go over some comparisons against other tools. So one of the things is, Opal has a gallery, which is really cool. So, essentially, there's different prebuilt apps that you can go in and modify. So one is learning with YouTube. Right? So I can click that. Again, the app is already built, and I can click this remix.

Jordan Wilson [00:30:58]:
Okay? So what the remix does is it essentially creates a version or a copy of the app. And now I can go in and, you know, do this for my own purposes. So I can just say, you know, update this, to make it a dedicated learning tool that explains, complex AI topics for everyday nontechnical people. Alright? So in, a couple of seconds, I can take something that was prebuilt by the Google Opal team, go in, put some simple natural language instructions and refine this and use it for my own purposes. So you can edit things in natural language essentially in a chat box, chat box, or I can go up in this more, kind of sticky note whiteboard, layout in these modules, click them and change anything in natural language or with the drop down. So not only can you build something from scratch with the modules, you can, number two, build something with natural language. Or the third way that you can do it is you can go and find, in Google Opal's prebuilt library, go in, remix something, and it's done. Right? So this one is literally already done.

Jordan Wilson [00:32:20]:
So in that thirty seconds, I went in and, kind of fine tuned a version of this web app, for myself. The other thing is, you know, the themes you don't have, like I said, this isn't something where you're gonna build something fully customizable. Oh, I want an app, you know, that's interactive in this way. It's really just for completing basic tasks with anything Google's AI has to offer, which is a ton. Right? But I can, you know, change the theme. Right? So I could just say, you know, basketball themed. Click enter, and it's gonna change the design. So you don't have a ton of customization, but I think that's the whole point.

Jordan Wilson [00:32:56]:
Right? And another thing is you'll see there's not a bunch of code flashing up on my screen. It is literally no code, which I love. Alright. So let's get back. We learned a little bit live. Let's do some comparisons quick. Let me, compare these to some other popular vibe coding platforms, even Google's own. Right? And you're like, wait.

Jordan Wilson [00:33:18]:
Google Opal? What about Google Jules? So, Google Opal, the target audience is general creators and knowledge workers. So these are no code users. And the biggest standout differentiator for Opal is it's no code AI chaining. So the ability to use multiple, Google AI features back to back to back passing the input along without knowing any code. Google Jules is another tool from Google. I would say this is one of their more, popular kind of, AI vibe coding tools. There's actually so many. Google has, I would say, easily five, but Jules is another popular one.

Jordan Wilson [00:33:53]:
The target audience for this one is more professional developers and teams wanting more autonomous help. And the, standout differentiator here is async autonomy, and it functions more like a coding colleague that works in the background. So, you know, different, you know, vibe coding tools, different pros and cons. Let's look at some other popular ones. Cursor, target audience for Cursor, developers seeking a deeply integrated AI first coding environment. The differentiator for Cursor, it's an AI first IDE, and it's a fork of BS code that's supercharged with AI offering code based aware chat and predictive multiline completion. So that's usually if you're working with a pretty big code base, Cursor's a great tool for that. GitHub GitHub Copilot, this is, the target audience I would be for dedicated software developers all the way up to enterprise.

Jordan Wilson [00:34:46]:
And the standout differentiator would be the ecosystem in the integration. So it's literally everywhere. Developers RDR. So, you know, mainly, GitHub, different command line editors, IDEs, and this is backed, and supported by Microsoft. That's actually their product. Replit. So the target audience there are coders, from learners to pros, educators, and small teams. And Replit is fully featured top to bottom.

Jordan Wilson [00:35:13]:
It is full stack. It is all in one, development hosting. It combines coding, running, debugging, and deploying with a self healing also AI agent in one platform. Very impressive, but a pretty steep learning curve. Lovable. It's been kind of, trending a lot recently, I would say. So for more for developers, startup founders, and product teams. So if you're trying to push an app, you know, maybe a a a startup idea, a software as a service, you know, maybe lovable or replit is something you might be looking at.

Jordan Wilson [00:35:45]:
So this is a standout differentiator. I would say for rapid MVPs generates production grade, full stack code, back end database, etcetera, from a high level conversation. But in terms of Opal, like I said, it is the fastest, easiest to use, literally no code. You don't even see code. And I think to use multiple pieces of Google Gemini AI, string the queries together, share the context, you know, from a deep research, to a Gemini 2.5, to an imagine, four to a v o3 and passing that information all along is a no brainer to start using this immediately to just solve nagging problems. So I also have kind of a core features, showdown here for our livestream audience. I'll probably include this in the newsletter as well, but the by far, the standout feature for Opal is just no code. Literally, no code.

Jordan Wilson [00:36:44]:
There's no code. Right? So if you wanna go in there and write the code, this isn't for you, Opal. It's, the one of the simplest there is. Alright? So that is a wrap y'all. So, I will say this. I hope this was helpful. And I did create a literal starter pack, alright, of 20 different, kind of ready to go apps, that you can go in and modify them for yourself. Alright.

Jordan Wilson [00:37:11]:
So, I'm gonna share them on my screen here. So they're they're ready to go. So, you know, the meeting debrief and action plan, the three sixty degree article analyzer, and these just have placeholders ready. So these have been crafted specifically for Opal. Alright? And I think out of these 20, I I really spend a good amount of time trying to make them for the everyday nontechnical user. Just some of the most common problems that people run into on a day to day basis. So if you've been wanting to, you know, start vibe coding something or you're like, there has to be a different way or you're like, hey. I'm using, you know, different AIs, but I'm always having to copy and paste and use multiple ones.

Jordan Wilson [00:37:53]:
This is a great way to start stringing these together in Opal. And I have some great, different use cases that I've already put together. It's very easy to visually see. You can copy and paste these. There's some placeholders you put in your information. It's a great starting point. So maybe, I mean, maybe one of these is just gonna work for you right away. You copy and paste, and this could take a task that you're spending five, six, seven hours a week on and turn it into five, six, seven minutes a week, literally.

Jordan Wilson [00:38:22]:
So, if you do want access to this, these ready to go Opal apps, just make sure you go share this on LinkedIn. Alright. So, if you're listening on the podcast, we always put the link to the LinkedIn livestream as well as we put that link on our website. So go repost this, and I will send you this full list of Opal apps. I hope this is helpful. If it was, go to youreverydayai.com. Sign up for the free daily newsletter. We're gonna be recapping today's show and a whole lot more.

Jordan Wilson [00:38:51]:
Thanks for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.