👋 Hey everyone! If you’ve been itching to build a full-stack AI application with real-world impact, this is the tutorial you’ve been waiting for. In my latest video, you’ll learn how to create an app that connects directly to CrewAI Enterprise, the platform that makes deploying and monitoring your crews incredibly easy. 🔥 Who Is This For? - Beginner-to-intermediate developers. - Anyone looking to turn their Crews into a SaaS app. 🛠️ What You’ll Use: - 🖥️ NextJS, Drizzle, Neon, and TypeScript for full-stack development. - 🤖 CrewAI Enterprise for AI-powered decision-making and automation. 🎯 What You’ll Build: A full-stack AI app that helps creators figure out their next video ideas: - 📝 Data Scraping: Pull videos and comments from a YouTube channel. - 🎥 AI Processing: Use CrewAI to generate video ideas, titles, descriptions, research trends, and score ideas. - ⚙️ Crew Integration: Seamlessly deploy and monitor AI workflows with CrewAI Enterprise. 📚 What You’ll Learn (3 Phases): 1️⃣ Phase 1: Project Setup - Lay the foundation with modern web technologies. 2️⃣ Phase 2: Code and Deploy the NextJS App - Build the app and take it live. 3️⃣ Phase 3: Build and Deploy Your Crew - Harness the power of CrewAI to handle AI-driven tasks. 💡 Why Watch This? - 🛠️ Get hands-on experience building a full-stack AI app. - 🚀 Learn how to integrate and optimize workflows with CrewAI Enterprise. - 📈 Add modern tools to your developer toolkit. ✨ Bonus: I’m giving away the source code for free so you can follow along and experiment with your own projects! 💪 Want to Level Up Even Further? If you’re interested in turning this app into a SaaS product, check out the AI Developer Accelerator Pro. 👉 I’ve included a mini-module on scaling this project to automate weekly YouTube scraping and idea generation. 🔗 Learn more here: https://www.skool.com/ai-developer-accelerator-pro/about

Hey team! I'm thrilled to announce that I've just released a brand-new crash course on creating a free vector store with Superbase! This tutorial is your ultimate guide to mastering data storage and retrieval augmented generation (RAG) to chat with your data like never before. By the end of this video, you'll have built a mini full-stack application that lets you save emails to a vector store and chat with your previous emails. I can't wait for you to dive in! Here's what you can expect in this crash course: 1. Superbase Setup: Learn how to set up a Superbase project, create tables, and store data and embeddings efficiently. 2. Email Storage and Embedding: Discover how to save emails, break them into sections, and embed them for easy retrieval. 3. RAG Implementation: Master the art of querying your vector store to pull relevant information and chat with your data using OpenAI. Why This Tutorial is a Game-Changer: - Step-by-Step Guidance: From setting up Superbase to implementing RAG, I walk you through every step. - Real-World Application: Build a functional app that lets you interact with your data in innovative ways. - Free Source Code: I'm giving away all the source code for free, so you can follow along and customize your project. If you have any questions, feel free to drop a comment below! Cheers, Brandon Hancock 🧑‍💻🥂 P.S. Here's a link to the source code: https://github.com/bhancockio/supabase-postgres-vector-store-yt

🚀 Exciting Course Updates Just Landed! Hey everyone! 👋 I’ve got some awesome news to share with you. Let's jump right in! 1️⃣ New Optional Sidebar Module I’ve added a refactored sidebar module to the course that simplifies logic using Tailwind CSS. This version replaces the old TypeScript-heavy approach, improving consistency across mobile and desktop. Plus, it's broken into bite-sized videos to make it super easy to follow. P.S. If the original version gave you trouble, this update should make things a lot smoother! https://www.skool.com/ai-developer-accelerator/classroom/f4101dd0?md=470aae3fad4041be8eceed7da414c8b7 2️⃣ Scale Resource Now Available The new scale resource is live in the resource section at the end of the course. It covers managing storage limits, scaling your app efficiently, and monitoring behavior using tools like PostHog, DataDog, and Sentry. https://www.skool.com/ai-developer-accelerator/classroom/f4101dd0?md=8794fc6eaa4846b2bacfc392ce38cf7e 🔧 Coming Next: Dev to Production Module I’m currently working on a new module that will walk you through taking your project from development to production. This will include updating integrations with Clerk and Stripe, swapping out databases, and handling all the important steps to make sure your launch goes smoothly. 💬 Got ideas for what else you'd like to see in the course? Drop a comment below and let me know! Cheers, Brandon 🧑‍💻🥂

Hey everyone! 👋 Today, I’m super excited to share a sneak peek of my latest video, where I walk you through the ultimate AI tech stack for building MVPs (Minimum Viable Products) lightning fast. If you’ve been trying to get your AI projects off the ground or want to quickly showcase proof-of-concepts to your clients, you’re in for a treat. 🚀 Why This Stack? In the upcoming video, I break down a powerful combination of Claude, V0 and Cursor. These tools, when used together, help you build beautiful and functional Next.js MVPs in record time. The Stack Breakdown: - Claude – Acts as the brains of the operation, helping you brainstorm ideas, outline, and strategize. Imagine Claude as your project’s foundation, setting the direction before you even write a line of code. - V0 – This tool is your MVP powerhouse. It can crank out Next.js components like a pro and streamline server-side logic. Perfect for getting the main chunk of your app up and running fast. - Cursor – Finally, when it comes to the fine-tuning, Cursor jumps in to polish the details, handle data cleanup, and make those last-minute tweaks that turn a good MVP into a great one. ✨ Real-World Use Case: Real Estate Offer Letter Generator Let me give you a sneak peek of a real-world example. In the video, I walk through how I built a Real Estate Offer Letter Generator in just a couple of hours. Here’s what the app does: 1. Allows real estate agents to input client details and upload documents like client conversations and property specs. 2. Automatically generates offer letters based on the uploaded information. 3. Provides agents with an interface to tweak values like the offer price, export the final document, and send it off to clients with just a few clicks. The coolest part? What usually takes hours of manual work was done in minutes using this AI tech stack! 😲 👷‍♂️ Building the Pyramid: From Concept to MVP in No Time When building out MVPs, I like to think of it as constructing a pyramid:

Hey everyone! Welcome to the official support thread for all your questions related to the AI Marketing Platform course! If something isn’t clear or you’re stuck on a particular topic, feel free to ask away! Chances are, if you’ve got a question, someone else is wondering the same thing. I’ll be doing my best to respond as quickly as possible. This is also a fantastic space for you to connect with fellow course members—so if you know the answer to someone’s question, don’t hesitate to jump in and help out! We’re building a community where everyone can learn from each other, so let’s make the most of it! Looking forward to your questions and the discussions ahead!