AgentKit vs Pydantic AI

AgentKit is a developer toolkit by Inngest designed to simplify the creation of AI agents that interact with APIs and event-driven workflows.

It provides lightweight abstractions for integrating large language models into structured processes, enabling agents to handle real-world tasks such as scheduling, notifications, or workflow automation.

AgentKit emphasizes event-driven design, allowing developers to build agents that respond to triggers from apps, systems, or users.

Its framework supports modularity, making it easy to extend functionality or connect with other services.

Pydantic AI is a framework built on the popular Python library Pydantic, designed to improve reliability and safety when working with large language models.

It provides structured data validation for LLM outputs, ensuring responses conform to predefined schemas and reducing errors in production environments.

Pydantic AI enables developers to build applications where LLMs produce consistent, machine-usable outputs rather than unstructured text. This is particularly useful for workflows like API responses, database inputs, or structured reporting.