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Want to build your own apps but don't know how to code? In this video, I show you how I built a fully functional AI powered YouTube comments app using only AI tools in just 3 days! This is a step by step guide that covers everything from brainstorming app ideas and creating a roadmap, to generating code and designing a beautiful user interface. 🧞 Sign up for the Comment Genie Beta: https://mrc.fm/cgbeta ✨ Weekly AI Newsletter: https://mrc.fm/creatormagic You can get $100 free credit for Linode to host your no code app. Use the link here for Linode here: https://mrc.fm/linode We'll be using these awesome AI tools: ● ChatGPT: https://mrc.fm/chatgpt For brainstorming ideas, creating a development roadmap and generating code. ● Cursor: https://mrc.fm/cursor This AI powered code generator will do the heavy lifting and write most of the code for us. ● Replit: https://mrc.fm/replit We'll use Replit to host our code in the cloud and quickly test our app online. ● v0: https://mrc.fm/v0 This AI powered design tool helps you create beautiful and responsive user interfaces without any coding. ● Midjourney: https://mrc.fm/midjourney We'll use Midjourney (or your favourite AI art generator) to quickly create a stunning logo for our app. I also share some bonus tips and tricks to help you get the most out of AI powered app development. Let me know in the comments what you're building with AI! Here are the time-stamped chapters in the requested format: 0:00 Introduction 0:25 Brainstorming with AI using ChatGPT 1:49 OpenAI ChatGPT o1 Preview for tech stack 2:55 Using Replit for cloud based coding 3:18 Introducing Cursor Composer for AI assisted coding 5:50 Testing out our AI developed app 6:48 Using v0 for frontend graphic design 8:35 Creating a logo with Midjourney 9:14 List of no code AI tools for developing apps 9:58 Tips for optimal AI assisted coding 11:49 Deploying the app with Linode 12:46 Demo of the Comment Genie app 13:12 Responding to feedback from beta testers 14:12 Conclusion 12:35 Demonstrating the Comment Genie app 13:24 Implementing user feedback 14:44 Conclusion and call for viewer feedback