Build a Stock Tracking App in 10 minutes with AI (Replit Agents, No-Code)

I want to build a stock dashboard. Boom. In just a few minutes, I told our AI agent to go build it for us. It deployed it for us. Now, it's live on the internet. I did this in what, 10 minutes. By the end of this video, you

will have your own stock tracking dashboard that you built and deployed on the internet by yourself. No coding required. I'm going to do it all with a brand new powerful AI tool called Replet Agents. It is by far the most powerful AI tool I've ever used. With a single prompt, you will have an entire application built out and put on the internet. If your mind isn't blown by the end of this video, you don't have a mind to be blown. Let's get into it. Boom. I'm over here now. Let's get right into it. What you're looking at is replet. com. So, this is Replet agents. This is their newest functionality. And this is really mind-blowing stuff. What's incredible here is you have an AI agent that does all the work for you when you're building applications.

Typically with other AI tools such as cursor, you have to write an AI prompt every time you want to make a change in your application. Now with Replet agents, you just enter a prompt and an agent which is basically an AI that can think for itself and make different decisions and do many different things without prompts goes out and builds an application for you. But on top of that, it actually deploys the application too. So, not only are you building it, you're getting it on the internet and you're launching it all with one sentence. So, for this example, what we're going to do is we're going to build a stock tracking dashboard. I personally invest in a lot of different stocks. I would love to have my own personal dashboard. I don't want to pay for other dashboards on the internet. So, let's go right into replet agent and actually build out that stock dashboard. So let's say I want to build a stock dashboard and deploy it on the internet. I want to be able to enter the ticker of stocks I invest in. And then for each ticker, a

chart shows up on my screen showing the performance. I can then see the performance of my entire portfolio. So I gave it a pretty simple prompt, right? Hey, this is the application I want to build. This is what I want it to do. I'm going to hit enter. And what you're about to see is the AI agent go out, figure out what technology is appropriate. That's a big advantage right there. With cursor and other AI tools, you have to kind of figure out for yourself what technology you want to use, React, whatever it is. This is going to figure out the best technologies to use. This is going to install those technologies. Then, it's going to start writing the code. deploy it to the internet. And all I did was write this one sentence. Along the way, it is going to ask me questions. Hey, do you mind if I do this? this just to make sure it's perfect? But it's going to do all the hard work for us. So, let's start building this. And so, now what it's going to do is start configuring the coding environment for us. Make sure it sets up the previews for the application so we can watch it get built. So, here we go. It's taking my prompt. It's going to start thinking about what technologies to use, what it wants to install. It's going to present a blueprint to us to make sure we like the direction it's going in. It's going to start asking us some questions. I've created a plan for a streamlit based stock portfolio dashboard that allows you to enter stock tickers and view performance charts for individual stocks. The app will be deployable on there. Would you like to review the details of plans? Would you like any of these additional features? So now it's going to ask, okay, that sounds like a good idea. Do you like

these other ideas too? I'll implement it in the app for you too. So we can add portfolio performance ROI alpha beta. Uh, you know what? That actually sounds good. Let's do that. Implement user authentication for personalized portfolio. So now users will be able to log in, sign up, all that. Let's do that. Add alerts for significant price. We'll pause that for now. I don't need alerts right away. Include new sentiment analysis for each stock. That's kind of cool. Let's do that. Let's approve that plan and go. I wanted to keep this simple and just have a pure stock portfolio, but I kind of like these other ideas it came up with. So, here we go. It determined we're going to use Python. You can see that it's using uh it's building Python files for us. It's starting to build each individual file. We're already a couple seconds in and we have five individual code files built out for us. It's figuring out where to get the live stock information from. You can see everything being built out here on the lefth hand side, all our different coding files. And in obviously in the middle, you can see the code actually being built and deployed. It's installing all the different technologies we need. And again, if this was cursor, if this was other AI technologies that allow you to build or code, you know, you're going to have to figure out all these things on your own, right? you think, "Okay, I got to install this. Hey, please install this. " And it kind of does each individual job for you. But with Replet agents, it makes the decisions for you. You don't have to make as many decisions. It's deciding what the best technologies are, installing them for you, and then getting it up and running. It's a lot less decision-m. knowledge you need to build. It just makes it 10 times easier to go from idea to actually deploying your application, which that's incredible. Now you can have people with absolutely zero coding knowledge go out and start building applications on their own right they get an idea they go oh I want to build that they go on replet they give the idea and it's good to go so let's see what it's doing now configured start streamlet app to run okay here we go so now it's going to start building the application is the stock portfolio dashboard working correctly can you see the title stock portfolio dashboard and a text input field for entering stock tickers wow so we entered basically one sentence and look what we got so far. Stock portfolio dashboard. Enter the stock tickers and then look, you can see the stocks already and you got your charts already set up. This is pretty amazing. Like I didn't edit anything out. I put in the couple sentences and we already

have a working stock dashboard. So, is this working? And the text input for entering stock tickers. Yep, it's there. Yep, all those are there. So, it's just checking in with us along the way. Does this look like what you want it to look like? Is this working properly? We just say yes and it keeps building for us. This is pretty amazing. And it's got the about here. The dash will allow you to track multiple stocks and view overall portfolio. Enter stock ticker separated. I mean, for the first time since using AI, this is the first time I feel like I have a human being doing something for me. With before with AI, you always felt like, okay, I have to tell it what to do. It still felt like a computer program. This is the first time where I feel like I have a human being on the other side of the screen doing stuff for me, working, building stuff, and going, "Hey, by the way, Alex, does this live up to your expectations? Do you want me to change anything here? " So, let's see what we got going on here. We built the initial prototype. Now, it's adding portfolio performance metrics. Okay, so now it's adding all the kind of the overall metrics for us. So, these are the extra features. It's like, you want these extra features? Now, it's building out the extra features for us. It's editing the code in the background here. So, it's editing all our different files for us. It is installing new technologies it needs. So it is getting the web server up and running here. In a second it'll probably refresh and have our application going. But now it's working on all the background stuff, all the background data we need to give us the advanced metrics. So here we go. Now it looks better. They improve the looks for us automatically. Wow, look at that. So now we can see volume. It's adding more metrics for our stock portfolio. We can see the performance over time. And now we can see our overall portfolio performance. So we can see all our stocks on one screen. Looks like it has some errors. I'm sure it's going to fix that on its own in a second. That's one of the coolest parts about AI. Even when it messes up and go, "Okay, let me see what I did to mess up. " And it goes back, sees what it did, figures out what it wants to fix. It can really do reasoning and think for itself, which is before software was very dumb, right? If you put in something in the software, it messes up, it's on you. You have to figure out where it messed up. But for the first time with AI and with Replet agents, what we're doing here, it can be like, "Oh, I messed up. Sorry about that. let me figure out what I did and debug it and do it on its own. It can reason. It can look back at what it did, figure out what it did wrong and fix it, which is pretty mind-blowing. So, it's going back, fixing it, restarting the app. Let's see what we got here. Restarted our server. Uh, and now it's presenting results to us. It's taking screenshots for us. Boom. It fixed the performance. So, it had the error at the bottom like we just saw before. It goes, "Okay, let me fix that error. " And now it fixed the error. You can see our tickers, the latest price, the change, the ROI. Pretty amazing performance metrics. explanation. It's explaining the metrics to us so we know what we're looking at here, which is pretty incredible. And it's still thinking. It's like, "Okay, what should we do next? What should we improve? What should we build out now? " It's resetting our application, and it's probably going to start improving some of the graphics, the UI for us. Again, you've seen my intervention so far here by all I've done was give the original command and say, "Yep, that looks good. " That's it. That's all I've done so far. And it's just keeps going. It keeps building the application. We can see, okay, what has it improved? It's adding more D. Okay, now the alpha and the beta are working. We can see the ROI. I'm just watching. I'm just watching and the AI agents going out and improving stuff. All I'm doing is sitting here drinking my coffee and the application is just improving as we go. Did I need any coding experience at all to build this? whatsoever for it to figure out what technologies to use? Like I didn't need to know what Python was for it to decide, okay, I'm going to use Python. It's pulling in live data from the internet. Okay, so it has APIs it's using. I didn't need to know anything about APIs. All I needed to know was what I wanted to build and then it goes out and figures out all the technical stuff for me which is pretty amazing in comparison to cursor right or in comparison to just using claude or chat GPT to build out applications like when you use that you kind of still have to do a lot of the decision-m for yourself right it makes the coding easier but you still have to decide I have to use this technology or I want to do this here it takes all that decision-m out for you which is pretty incredible so it's still thinking it's still figuring out what it needs to do next, which is totally fine cuz I could be going off now, going off doing other things, getting other work done while this is building in the background. Another difference here is this is more of a passive building experience. If you're using cursor or chat GPT or whatever, you have to be actively engaged to build applications. I can't be going working on other things, building other things, and it does work for me. So, let's see what we got here. Looks like there's an error. There has an error calculating the alpha and the beta of stocks. Is the portfolio summary table all right visible on the page? If so, describe what you see in the table. Nope. Currently, I see an error that says, and then we'll just

copy over the error. Put that Let's copy the whole error over. Why not copy that over, put it in, hit enter. My guess would be it will figure out what is wrong and fix it for us without having us having to do any sort of decision making whatsoever. Keep in mind too, this is just in beta and it's still able to do all these things. So, there's going to be hiccups along the way. I've identified the issue causing the error in the dashboard. It's related to fetching benchmark data for calculating alpha and beta. I'm working on a fix that will make the dashboard more robust even when benchmark data isn't available. This will ensure you can still view your portfolio performance metrics. That's pretty amazing. So, what it did is it figured out the error itself. It figured out what it did wrong and then came up with alternative methods to handle this error moving forward if it happens again so that we never have to view another error message. So it reasoned with itself what it did wrong and then it figured out a bunch of solutions, chose the best solution. Now it's implementing the solution which is pretty amazing. So now it's doing some more thinking. It's going to probably implement the solution in a second. It'll probably refresh the dashboard. Yep, it's implementing its solution by editing the code and it's going to refresh the dashboard so we can see uh what it built. So, restarting our app and here we go. My guess would be is this is working and it's going to have some sort of catch error. So, if there is an error with the data coming in, it has some sort of screen that says error coming or uh data coming soon or data will be filled in a second. Here we go. Running the application. I take another sip of my coffee. performance metrics explain. Now it says default values are being used when there's an error fetching the data. So it explains why there would be zeros in there. Amazing. So it looks like it fixed the issue. It's taken a screenshot so it can validate what it did. Stocks coming in are still real-time data. And also just as a side note here, I'm not a good designer. This is a good-look website, right? It figured out the design on its own. I didn't have to sit here like if it was up to me and I had to figure out the design. This would be really ugly. All right, so here we go. Completed the performance metrics. Implement user authent. Okay, so now it's going to go to user authentication. Next, let's go back to the web view so we can see our application in action here. Looks good. The alpha and the beta stuff have been removed. And next, it's going to do user authentication so that people can log in, which is pretty

amazing. you know, if I wanted to turn this into a product and sell it on the internet, you're going to want user authentication. And so, this is a pretty critical step. If your plans include building products, putting it online, making money, being an entrepreneur, making extra income next to your 9to-5, having the authentication is going to be important. So, boom, log in. Please log in to view your personalized portfolio. This is a really important step for anyone that's going to be deploying apps. I didn't have to do any decision-making. Can you verify the login function is working? Please try logging in with a username user one and password one. That's amazing. So it made a user for us. User one, password one. Login successful. Okay, login was successful. But I get this error on the main screen. And then I just copy paste. I don't even know anything about this. Doesn't matter. My AI developer employee will figure it out for itself. I put in the error. It's thinking and it's going to just debug it. It's going to do the reasoning. It's like, "Oh, that's interesting. Let me figure out what's wrong here. I apologize for the error you encountered. It seems there's a small issue with the outdated Streamlit function. I'm working on fixing this right away, which should resolve the error you're seeing. I'll update you once the change has been made and the app is running smoothly. You know, if I wanted to have multiple of these agents up building 10 applications at once, I could do that, which is pretty incredible. Think about the productivity changes we can have now. If I have 10 ideas for apps, I can just sit here, have my 10 AI agents up building those applications. I go for a run. I come back. I have 10 deployed applications on the internet. That's pretty incredible. Can you verify login functionality? All right, let's try this again. Hopefully, this will work. And it's pretty amazing. It's got all the little details, right? You can click to see your password. Logged in. It works. It works now. figured out its issue, right? Fixed it for us. When you see little things like that, it kind of makes you smile because it makes you realize you're viewing revolutionary technology in real time. Like this app, Replet Agents, came out like 3 days ago. And this is not sponsored, by the way. This is not sponsored by Although Replet, if you do want to sponsor, holler at your boy. I'm just witnessing technology that's kind of mind-blowing in real time. It's pretty incredible. So, now it's going to be putting in new sentiment for each stock, which that's amazing. That's incredible. There's going to be new sentiment for every stock. By the way, I'm going to be deploying this application and putting it live. So, in future videos, I'll be including the link for this if you want to use it as well. Probably be improving this. I love

the idea of this application now that I'm building it. I have a thousand different ideas for improvements I'm going to make. So, that'll be coming soon. Here we go. To enable new sentiment analysis for the stocks, we need an API key from news API. Please provide your news API key. You can obtain a free API key at here. Okay, I'm going to go do that. get this API key. Okay, got my API key. I'm going to put it in here. Add the secret. Here we go. And it is implementing it. So, we should have a live news stream into our stock tracking portfolio. Let's do this. It's probably going to make us log in again. What's amazing here is I've been a programmer now for 15 years. When I wanted to build applications like this, I needed to do research on what the best APIs were, right? what the best sources for data were that I could pull into my application and that was a whole process in itself. This went around just figured out what the best API was. Is the new sentiment analysis being displayed correctly for each stock in the portfolio? Well, let's log in again. User one, password one, login. Here we go. And now let's see if we got new sent new sentiment. Amazing. Okay. And it's actually rating the sentiment for us. That's incredible. That's amazing. Please check if there's new center score in each stock with overall sentiment. Yep, I'm seeing all of that. Now we got the news for each stock. We can stay on top of our stocks here. This is pretty incredible. And it made it work. Just did it for us. Here we go. Now we're going to deploy it. I've completed planes. The following steps are executed. Good. Very good. All right. So, let's deploy it to production. Deploy a stable public version unaffected by the changes you make in the workspace. Recommended reserve VM. Set up your deployment. Let's do it. And then let us Here we go. It's got the databases. It's got everything figured out we need. Let's deploy it. It's going to put it on the internet. Couple clicks. Again, I needed zero technical knowledge to do all this. You saw everything. There was nothing edited out here, right? You saw every step I did. You saw the deployment. How much coding did I have to do? Zero. Right? How much technical knowledge did I need? Zero. Anyone now can go from idea for an application to building it out with very little in between those two steps. What I built here would have took me months before. Months. This took me a few minutes. This is pretty amazing. So, it's deploying everything. It's putting everything online. It's hosting it on the web servers. It's deploying the databases. So, you can have multiple users logging in. And once this is done and it's promoted to production, it'll be good to go and it'll be live. This is going to be awesome. And again, I could have gone out, you know, I could have said, "Hey, start this job. Go out, do whatever. Come back. I have a working application for me, right? And I could even had multiple of these windows up building 10 different applications at once for me. " It's pretty incredible. Really for the first time feels like I have an employee working for me just building stuff out, just building stuff out for me, right? If I wanted to go now after this build out more features for this, I could deploy it to production. I can just keep improving this. I did this in what, 10 minutes. Imagine what this would look like if I spent a full 12 hours on this or a full eight hour workday. I would probably have a full enterprise scale application. If I spent eight hours, this took me 10 minutes. What you just saw here, imagine what would happen if I spent 8 hours building this out. I would have like a full intense incredible application probably with a ton of features and functionality. Probably could be able to monetize it, right? $10 a month come in, you can use all the functionality. That's pretty incredible. So, this is pushing it live. By the end of this, I will have a URL I can put in, see my application live on the internet, test it out, give it to my friends. That's always the most fun part when you first start building applications. You put it online, you send it to your friend Lee. Lee sees it. Goes, "Holy I didn't know you could do this. This is incredible. " Yeah, I'm that smart, dude. Now you can be that smart. Now you can build out your own stuff. Send it to your friends. Your mom goes, "Oh my god, I didn't know my son was that smart. daughter was that smart. This is amazing. I love you so much more now. Some of the benefits of this. Everyone around you thinks you're smarter now. So, we're going to let this run here. Very shortly, it'll be good to go. All right. Deployed to production. Here we go. Deployed 5 minutes ago. Also, one last thing before I click this link and we see the application. Make sure to hit subscribe down below if you want to see more videos like this. All I do is make videos showing you how to build cool things with zero programming knowledge necessary. Make sure to hit like and reply what you want me to build next. Let's open up the domain. Let's see our application working. Here we go. The big moment, the moment of truth. Let's see our application live on the internet. Did Replet agent not only build the application but deploy it so anyone can see it? Let's see here. It is running. It is loading. I can't wait to see it. Here it is live. Boom. All

right. Let's do user one. Log in. And there it is. There's our app. Incredible. There you have it. In just a few minutes, I came up with the idea for an application. I told our AI agent to go build it for us. It deployed it for us. Now, it's live on the internet. There it is. You can go to this URL right now and use it. Now, if I wanted to, I can put this on a normal domain. I can monetize it. I can start selling it. Start making money as a side hustle. Replet agents. Replet. com is where I got this. It is probably up to this point in time the most powerful AI tool I've ever used. Unbelievable. If you enjoyed this video, let me know in the reply section what else you want me to build as well. Everything I build, I get from the reply section. It's everything is user feedback driven. So, let me know. I appreciate you and I'll see you in the next