Article teaches how to build AI agents in Python using Pydantic AI with structured outputs and type validation.

Pydantic AI is a Python framework that brings strong typing and validation to AI agent development, allowing agents to return validated Python objects instead of raw strings by defining output models using Pydantic BaseModel.

Agents can register plain Python functions as tools by using type hints and docstrings, enabling the LLM to understand what each tool does and when to invoke it during multi-step reasoning.

The framework provides dependency injection via a typed RunContext pattern, allowing agents to access database connections and API clients at runtime without relying on global state, making tests easier to write.

Pydantic AI supports multiple model providers (OpenAI, Anthropic Claude, Google Gemini) by changing only the model string, and includes built-in capabilities like web search and extended reasoning.