Riley Brown demonstrates how to build a complete AI image generation application using Cursor’s Agent feature, showcasing the power of modern AI-assisted development tools. The tutorial covers everything from initial setup to deployment, including integration with Firebase for authentication and storage, and implementation of multiple AI image generation models. The project demonstrates how developers can quickly build full-stack applications with minimal manual coding.
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Episode Timestamps:
00:00 – Intro
00:23 – Why Cursor
03:43 – Setting Up a Project in Cursor
06:48 – YOLO Mode Discussion
09:39 – Deciding what to build
10:25 – Exploring API Integration
12:54 – Building an AI Image Generator
16:44 – Building, testing and debugging AI Image Generator
38:00 – Enhancing User Interface Design
41:59 – Firebase integration
53:00 – Deploying app using Vercel
Link to Mount Cursor image generator: https://rileygregpod4.vercel.app
Clone the repo and start the development server in one command: https://github.com/ansh/template-2
Key Points:
• Demonstration of building an AI image generator using Cursor’s Agent feature
• Integration of multiple AI image models (Flux, Ideagram, Stability AI)
• Implementation of Firebase authentication and storage
• Deployment process using Vercel
• Live coding session showing real-world application development:
1) The Ultimate Stack for 2024:
• Cursor (AI coding assistant)
• Next.js (framework)
• Firebase (database)
• Vercel (deployment)
• Replicate (AI models)
Key insight: Cursor’s Agent mode is INSANELY good now
2) Step-by-Step Build Process:
i) Start with empty folder in Cursor
ii) Clone template repo with one command
iii) Add AI image generation
iv) Connect Firebase
v) Deploy to Vercel
Time needed: Just 75 minutes!
3) Pro Tips for Working with AI Models:
• Use Replicate for easy access to top AI models
• Test in Playground before implementing
• Always save model parameters
• Keep track of API keys
• Start in test mode for databases
4) Firebase Setup Simplified:
a) Create project
b) Enable Authentication
c) Set up Storage
d) Set billing limits ($20 cap recommended)
e) Enable test mode
– Key Learning: Test mode first, production rules later!
5) MAJOR INSIGHT: Building with AI is like Legos
• Start with basic template
• Add features incrementally
• Use examples as building blocks
• Test & iterate quickly
• Learn from failures
6) Deployment Checklist:
• GitHub repo setup
• Vercel project creation
• Environment variables
• API keys configuration
• Domain authorization
7) Most Common Gotchas:
• API key management
• Environment variables
• Authentication domains
• Server restarts
• Aspect ratio handling
8) The Future of AI Dev Tools:
• Templates getting smarter
• Payment integration coming
• More automated deployment
• Better error handling
• Improved documentation
TAKEAWAY: You don’t need to be a senior dev to build cool stuff with AI anymore.
Notable Quotes:
"I think of AI coding like Legos, right? You’re looking for the pieces that you need to put together." – Riley Brown
"I’m never going to claim to be an expert. I am here messing with these tools as are you. I’ve just been told that I’m pretty good at explaining things." – Riley Brown
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