This repository provides a self-paced guide for intermediate developers to build a full-stack fitness application using GitHub Copilot's agent mode. It aims to demonstrate how natural language prompts can generate complete applications, reducing development time and effort.

How It Works

The exercise leverages GitHub Copilot's agent mode within a preconfigured development environment. Users will interact with Copilot Chat, selecting agent mode to generate application code based on natural language requirements. The process involves prompting Copilot with specific roles and desired outcomes, allowing exploration of different LLM models like GPT-4o for varied outputs.

Quick Start & Requirements

• Install/Run: Follow instructions to "Copy Exercise" and then click "Start Exercise" within a preconfigured GitHub Codespaces environment.
• Prerequisites: Intermediate development experience, familiarity with GitHub Copilot, basic GitHub, and web development concepts.
• Setup: Estimated completion time is under one hour.
• Links: GitHub Codespaces, GitHub Copilot

Highlighted Details

• Focuses on practical application of AI-powered code generation.
• Guides users through prompt engineering for specific roles (e.g., gym teacher).
• Encourages experimentation with different LLM models for comparative results.
• Designed for rapid, hands-on learning within an hour.

Maintenance & Community

The repository is a GitHub-sponsored educational resource. Further community interaction details are not specified in the README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Permissive license suitable for commercial use and integration with closed-source projects.

Limitations & Caveats

The exercise relies on a preconfigured environment, and users may need to refresh the page for the "Start Exercise" button to activate. The effectiveness of the generated application is dependent on the quality of the prompts provided to Copilot.