Pydantic AI uses Pydantic models to encapsulate AI agent definitions, enforcing type-safe inputs and outputs. Developers declare prompt templates as model fields, automatically validating user data and agent responses. The framework offers built-in error handling, retry logic, and function‐calling support. It integrates with popular LLMs (OpenAI, Azure, Anthropic, etc.), supports asynchronous workflows, and enables modular agent composition. With clear schemas and validation layers, Pydantic AI reduces runtime errors, simplifies prompt management, and accelerates the creation of robust, maintainable AI agents.