Improving Nex.js Applications with Shotgun Code and AI Tools

00:00 Introduction

This video focuses on using Shotgun Code to improve a flawed Nex.js application by leveraging AI tools to automate code changes.

01:15 Overview of Shotgun Code

Shotgun Code allows users to submit their entire codebase to generate prompts for large language models (LLMs) like Gemini 2.5 Pro. It helps create patches for code changes by analyzing the codebase and suggesting specific modifications.

03:30 Installation Process

To use Shotgun Code, prerequisites include installing Go, Node.js, and the Wales CLI. The video provides installation commands and guides viewers through setting up the application.

05:45 Preparing the Context

Users need to select only the necessary folders in their project to avoid exceeding size limits. The video shows how to refine the project context and compose a task prompt for the AI.

08:00 Executing the Prompt

Instructions for executing the prompt in Google AI Studio are given, emphasizing setting the model to Gemini 2.5 Pro with a low temperature for precise outputs.

10:15 Applying Changes and Results

After receiving the diff from Gemini, users can apply changes in Cursor. The video showcases the improvements made to the app, including performance enhancements, UI upgrades, and a better user flow.

13:30 Conclusion

The video wraps up by highlighting Shotgun Code as a revolutionary tool for code management and improvement, especially for projects lacking comprehensive documentation.