This pull request updates the README.md to introduce and explain Project CodeGuard, an open-source security framework for AI coding agents. The changes focus on describing the purpose, benefits, and multi-stage methodology of Project CodeGuard in embedding security best practices into AI workflows.

Project CodeGuard overview and benefits:

• Added a description of Project CodeGuard as a model-agnostic security framework for AI coding agents, emphasizing its role in embedding secure-by-default practices and providing comprehensive security rules.
• Explained common security vulnerabilities that can be introduced by AI coding agents, such as skipping input validation, hardcoding secrets, and using weak cryptography.
• Detailed how Project CodeGuard integrates security checks before, during, and after code generation, ensuring security is addressed throughout the development lifecycle.
• Provided examples of how specific rules (e.g., input validation and secret management) operate at multiple stages of code generation and review.
• Highlighted the multi-stage methodology and its benefits for maintaining both security and productivity in AI-driven development.