Essential AI Coding Fundamentals I wish I knew sooner (ChatGPT, Cursor AI, v0)
Essential AI Coding Fundamentals I wish I knew sooner (ChatGPT, Cursor AI, v0)
In this episode, I am joined byJason Zhou, product manager & YouTuber, where we dive deep into AI coding fundamentals. Jason shares his unique insights into how to use and set up AI to streamline to the process of building you next app. Learn how to use AI like a pro!
Timestamps:
00:00 Intro
00:20 Preview of Jason’s Workflow
07:27 Case Study: Building a Reddit Analytics Platform
08:56 Writing detailed specs upfront
11:40 Core Functionality Breakdown
12:51 Researching Packages for Implementation
16:13 Debugging and Iteration Process
19:04 Demonstrating the Reddit Post Fetching
19:59 Categorizing Reddit Posts with OpenAI
24:29 Debugging Continued
29:13 Using Step-by-Step Debugging Techniques
32:15 Setting Up the Project Structure
35:22 Generating Detailed Documentation
38:55 Building the Application with Cursor
46:01 Transitioning to UI Improvements
50:00 Exploring Startup Ideas
51:58 Implementing Reusable Authentication Prompts
56:04 Conclusion: Structuring AI Coding for Success
57:53 Where to Find More Resources and Tutorials
1) The problem: Large language model coding is unpredictable. Tutorials make it look easy, but reality is different. Jason's solution? A structured workflow for more consistent results.
2) Step 1: Write detailed specs upfront
- Simulate how product teams work in reality
- Uncover uncertainties early
- Include project overview, core functionality, and implementation docs
- Cursor for functionality
- V0 for UI touchups
- This order leads to more success than trying everything at once
- Create a collection of standard functionalities (e.g., user auth, payment)
- Share these prompts within the community
- Speeds up development process significantly
- Build functionality first
- Use V0 for UI improvements later
- Provide style examples (e.g., "similar to Vercel") for better results
- Example: Auth setup prompt that works across projects
- Saves time and ensures consistency
- Aggregators for modular prompts
- New ways to integrate prompts into developer tools
- More streamlined workflows (like Bolt) to automate manual steps
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