Course Description

Fix Broken Projects Fast by Letting AI Refactor Your Entire Codebase at Once

Sometimes AI doesn’t just introduce small bugs — it builds the entire app wrong. When that happens, incremental fixes and implementation plans aren’t enough. You need a way to step back, give AI full project context, and rewrite everything cleanly in one go.

In this lesson, you’ll learn how to use Shotgun Code, an open-source tool that ingests your entire codebase, generates a massive structured prompt, and lets powerful models like Gemini 2.5 Pro produce a complete, accurate diff for your project. Instead of fixing files one by one, you apply one patch and transform your app instantly.

This workflow is ideal when:

• Your app was built incorrectly by AI

• You lack proper documentation or specs

• You want a full architectural refactor without rewriting everything manually

What You’ll Learn

• How Shotgun Code captures and compresses your entire codebase context

• How to generate massive, LLM-friendly refactor prompts automatically

• How to safely exclude unnecessary files (build artifacts, deps, docs)

• How to convert a full app from one UI system to another (e.g. custom → shadcn / Aceternity)

• How to use Gemini 2.5 Pro for deterministic, low-creativity code refactors

• How to apply large diffs cleanly in Cursor or Windsurf

• When this approach beats traditional implementation plans

Core Workflow Explained

1. Prepare Full Project Context

• Select only relevant folders

• Exclude build outputs and dependencies

• Generate a clean, scoped project snapshot

2. Define a High-Level Refactor Task

• Example: “Convert entire UI system to Aceternity UI and improve performance”

• Optional: add Cursor rules or project constraints

3. Generate a Massive AI Prompt

• Shotgun structures everything for LLMs

• Includes file tree, dependencies, and task instructions

4. Execute with Gemini 2.5 Pro

• Use low temperature (0.1) for precise, deterministic output

• Generate a full diff covering all affected files

5. Apply Changes in Cursor

• Paste diff into Cursor

• Apply in one request

• Switch models if needed (Claude Sonnet works great for execution)

Real Results Demonstrated

• Massive performance improvements (smooth scrolling, no jitter)

• Complete UI overhaul with minimal manual work

• Improved user flow and interaction logic

• Cleaner architecture with fewer fragmented fixes

• No need for prior documentation or specs

When to Use Shotgun Code

✅ Large refactors
✅ AI-built projects gone wrong
✅ UI framework migrations
✅ Performance overhauls
❌ Small isolated fixes (overkill)