Fastest Way to Turn Your AI App Idea into an MVP (11 minutes)

Today I'm building an AI powered language coach app [music] called Lingo Coach from scratch in under 15 minutes. This is hands down the fastest way to go from idea to MVP. And this is not just your average vibe coding platform. This is a gentic vibe coding. We're going to be building with AI agents that scaffold the app, catch bugs, suggest [music] fixes, and literally help you ship faster than ever by using Emergent. Now look, I built a couple apps in my day back in 2015 when I launched my very first app. Getting it off the ground used to take [music] forever, months. I built my previous app, Puff Count, to 44K per month in monthly recurring revenue before exiting the business. And I'm now working on a web and mobile app marketplace called Posted that has just crossed over [music] 150K per month in revenue. I've done it all. I've coded from scratch. I've hired [music] massive dev teams. I vibe coded. But with the tools we have today and platforms like this one I'm about to show you, you can go from idea to [music] MVP faster than ever before. And look, shipping fast is the most important part of being in the [music] app business. You need to get your MVP into the market as soon as possible. Do not polish. Do not make sure it's perfect before you launch. You need to start marketing, start getting users, start generating revenue so that [music] you can use that information and that data and that customer feedback to iterate and build [music] further. All you need is one feature with an onboarding and a hard pay wall. That's it. So, in this video, I'm going to be walking you through [music] the entire process to go from idea to MVP. We're going to find an idea. We're going to validate it and then we're going to use emergent to get this idea off the ground into an [music] MVP state. Beginning to end, building a real functional voice enabled AI app that runs on Open AI or Claude speaks via 11 Labs and gives [music] real feedback live. Let's ride. Okay, here we have it. Our entire document, our brain dump here, if you will, explaining the full project and what we are going to be building. Again, the name of it is Lingo Coach, a language learning practice app where you speak with an AI coach. It will listen your responses. You'll have a live dictionary and translations with lookups and some citations if we decide to add that in. And we're going to integrate 11 Labs so that the app can speak back to us. And we're going to be doing all that using this beautiful platform called Emergent. Shout out to them. They just raised their series B. So, this company is not just your average vibe cutting platform, but they are seriously taking this all to the next level. You can build full stack apps, mobile apps, landing pages, etc. You can swap between different LLMs to build. You can push to GitHub. You can upload files. It's got some pre-made templates here for you. It's got everything. Okay. So, why language learning? Why is that the idea we're going to go after? Language learning is one of the most broadly applicable niches on the planet, especially English. There is mass market appeal, which makes for easy advertising, and there is a serious pain point that we are solving. And just look at the competitors. Of course, we have the big kahuna Dolingo doing $50 million in annual recurring revenue. We have Lerna doing 3 mil in annual recurring revenue. We have Elsa doing 400K. Laura doing 500K. Practica doing a million dollars in revenue every single month. There are so many apps crushing it in the space. And guess what? They're all also running an absurd amount of paid ads. Practica alone running 560 unique paid ads right now on Meta. And guess what? If all these companies are running paid ads, it means they are profitable. They're not spending money on paid ads because they're not profitable. I promise you that. So this is a very very good sign right here alone we know this idea is validated. And you might be thinking okay well there's a lot of competitors. Why would I build an app where there's a ton of competition who are already crushing it. It does not matter. Our target market everybody who wants to learn a language especially English which we're going to emphasize. Your target market is everyone with one of these billions and billions of people. At some point everybody has a dream to learn a different language. So all we have to do is market a little bit different than any one of these apps. And even if we can get to 20K, 30K MR, a fraction of what some of these companies are doing, that is going to be life-changing money because building mobile apps, you're building real enterprise value. You can take your month or your current revenue, multiply that by 12, and you have your ARR. If you build a successful mobile app, you can sell that mobile app for a multiple of your ARR. Okay, hopefully that makes sense. We do not need to capture this entire market, but we can definitely learn from the competitors and we can use them to validate our idea because they're making a ton of money. I also have their pay walls and onboardings uh pulled up here so we can get an idea of what we should be charging and how we should build out the payw wall or how we should build out the onboarding rather. Always always a very good idea to look at the competition before you begin to build your mobile app. Okay, so let's get into the build. And again, we're going to be building this using emergence. So of course it is going to be a mobile app and we are going to be using clawed opus to get the initial scaffolding done for the app. Now, all we have to do is tell it what we would like to build. And if you already have some sketches or some designs done, you can also attach those as images here to give the platform more context on what you're looking to build, but we're just going to do it straight from the jump here. So, let's go. Now, it is going to start to cook and we will let it build. And you'll see already here the Agentic Vibe Coding come in. It's asking questions actively while building, making sure that it has all the context it needs before it actually compiles everything. So, it's asking us here a few questions to ensure I build exactly what you need. Authentication method, Google login, quick setup, secure oath. Yeah, let's use Google social login. A power for the lesson feature. Do you want a powered language tutoring? Yes, we do. Yes, an AI tutor using chat GPT 5.2 database. Yes. Option A, let's use MongoDB. What languages initially? Initially we want to support English. Any specific features you'd like to highlight in the MVP? Nah, let's let it cook. Not even typing on my keyboard. Literally just talking to emergent and this agent to build everything. So boom. After a few short minutes here, we are now done. We can preview and we have the option to deploy directly to Android or iOS. But we're just going to preview it. Right now we have our preview window open and we can even test it out on Expo by scanning this QR code. So, bang. Let's see how she looks. And there we have it. Our app is live. We can test this out now. AI powered conversations, personalized lessons, and we can build our vocabulary. So, we can sign in with Google. Beautiful. That works. Log into chat vocab. Wow, there it is. You can even do it on web. Officially logged in. And now we can start chatting. We can create lessons here. Again, I'm doing the same thing on my phone. I have this on my phone, but just for the sake of the video, I will show you on my computer. English test. Help me learn English. I'd consider myself pretty advanced at English. Create a lesson. Okay, so we don't have the lessons configured or any of the dictionary backend configured, but that's okay. The main thing that we want to finalize here is the chatting to AI. So, what we're going to do is prompt this to integrate 11 Labs and we're going to add a chat bubble into this so that we can have a conversation with the AI and hopefully it can give us feedback on our English. Let's prompt that up. Now, I want you to add an additional chat button onto the homepage. And this button will allow us to talk back and forth with the AI. We want the AI to give us feedback on our conversation with it. Okay. And now you can see that the agent is asking for our 11 Labs API key which we will provide to it. Now here is the API key. Bang. Now we're cooking with fire. We have 11 Labs integrated. And we even have this voice activated text to speech chat. And we can even listen to a voice speaking back to us with the 11 Labs integration. Just to break this down for you, Practica is doing $1 million per month essentially doing the same thing. You chat to an AI and they have these nice visuals and it's a little bit more built. It's put together, but it's essentially the same thing. You're chatting back and forth with an AI and it's giving you language feedback. Again, with our MVP, we keep it very, very simple. This is how all great apps start. They start very basic, just the core features and we can slowly add things on top of this. We can start to build AI avatars that are animated and speak back to us and we could have that at the top of the page. And then essentially we have a competitor to all these apps we showed earlier that are doing millions of dollars per month. Okay, nice. It will even define words for us as well. Candy means a sweet treat usually made with sugar like chocolate bars, gummies, lollipops, or hard sweets. What's your favorite kind of candy? Now, we're going to plug in an MCP to look up certain words and site where they got the definition from. And we're also going to include an image when it decides to show the user what the words are. So, we're going to add that now. Again, we have the agent helping us out here, asking some clarifying questions for looking up definitions of citations, blah blah blah. Let's do it on demand. So, we're going to say add these on demand with a lookup button. And then for the word images, I would love to use Unsplash, but I don't have an API key. And I'm too lazy to get one. So, uh, we're going to go with option C. And for word images, use option C. Just use web search to find relevant images. Send that through. Boom. Now we officially have the MCP pulling in the source of each word that we add into our dictionary. The images aren't showing up yet, which is a bug. And hopefully the agent can catch this. So we are going to see if it can. So upon further investigation, it looks like it is indeed pulling the images when we look up a word and add it to our dictionary. They're just not showing on my browser for some reason, but not to worry. This is a problem that we can tackle together with a team member. Which brings me to the next part of the video where we can push this entire codebase into GitHub and we can dive into the code a little bit deeper. This dictionary is really cool and I think we could do some very cool things with it. We could add vocabulary etc. And of course we also have the voice chat with 11 Labs integrated. So we have some great MVP core features here that we can build on top of. Boom. And now we have created a new repo and we can push all of this to GitHub. Boom. And here we have it. Absolutely everything from our project all in one place beautifully laid out for us. So there you have it. A quick recap of what we got done with immersion. We have a universal LLM key. We use Claude and GPT 3.5 in this project. We integrated 11 Labs voice so that we could hear the AI agent speaking back to us when we're trying to learn a language. There was a realtime chat back and forth with the AI. We added an MCP dictionary with citations and images. We tested the agent bug fixing capabilities. We pushed all of our code to GitHub. And importantly, we saw the options to push this entire project live into production on the iOS or Android app stores. Now, the next thing that I would like to do with this project is implement an onboarding, add a hard payw wall, track those onboarding metrics and the conversion rate, and of course, officially push this live to the app store. Hopefully, you enjoyed the video. If you'll want, I will do that and show that entire process on my next video. If you'all want to try out emergent, the link is going to be in the description. And I also dropped the entire document that we used on this video and a full checklist so that you can build your own MVP with emergent as well. That will also be in the description. Hope you enjoyed the video. I'll catch you on the next one.