Visual Studio Code, featuring Gwyneth Peña-Siguenza, guides developers through prompt-driven development and AI-powered codebase refactoring using GitHub Copilot with a FastAPI + Cosmos DB project.

Refactor an Existing Codebase Using Prompt-Driven Development with GitHub Copilot

Featuring: Gwyneth Peña-Siguenza (@madebygps)
**Produced by Visual Studio Code **

This session demonstrates how to leverage GitHub Copilot to refactor an e-commerce inventory management app written with FastAPI and Azure Cosmos DB. The walkthrough covers recognizing code smells, building contextually-rich prompts, running Copilot in Agent Mode for refactoring tasks, and reviewing AI-generated improvements step by step. The approach emphasizes best practices for integrating AI assistance into real-world development workflows.

Video Chapters

  • Intro (00:00)
  • Getting Started (00:36)
  • Choosing Directory & file: product_crud_batch.py (02:25)
  • Writing Custom Instructions (03:50)
  • Creating Effective Prompts (05:25)
  • Running Prompts with Copilot Agent Mode (09:58)
  • Testing Changes (19:11)
  • Summary & Key Takeaways (23:39)
  • Wrap Up (24:14)

Key Topics Covered

  • Refactoring real-world Python code for an e-commerce scenario
  • Identifying and addressing code smells in an inventory system
  • Constructing targeted instructions and prompts for Copilot
  • Using Copilot’s Agent Mode for iterative improvements
  • Reviewing, testing, and validating AI-suggested code
  • Best practices for making AI-driven refactoring reliable and maintainable

Demo Project

Best Practices Highlighted

  • Develop focused, stepwise prompts for each refactor target
  • Validate Copilot’s output through tests and code reviews
  • Iterate rapidly, integrating manual and AI changes
  • Leverage Agent Mode for continual improvement and prompt experimentation

Connect with Visual Studio Code

For developers looking to enhance productivity and code quality using Copilot, this video offers actionable insights and hands-on techniques that can be applied to similar Python and Azure-based projects.