Python’s prominence in data science and backend engineering has made it the go-to language for AI infrastructure. However, as AI applications grow, developers seek tools that mix Python’s flexibility with the reliability of production-ready systems.
Pydantic started as a library for type-safe data validation in Python and has become one of its most popular projects. Recently, the Pydantic team introduced Pydantic AI, a type-safe agent framework for creating trustworthy AI systems in Python.
Samuel Colvin, the creator of Pydantic and Pydantic AI, joins a podcast episode with Gregor Vand to discuss Pydantic’s beginnings, the design principles of type safety in AI applications, the development of Pydantic AI, the LogFire observability platform, and the impact of open-source sustainability and engineering discipline on future AI tooling.
Gregor Vand is a technologist focused on security, with experience as a CTO in cybersecurity, cyber insurance, and software engineering companies. He is based in Singapore and is accessible via his profile at vand.hk or LinkedIn.
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