Python’s rise in data science and backend engineering has established it as the go-to language for AI infrastructure development. However, as AI applications expand rapidly, developers are seeking tools that merge Python’s adaptability with the robustness of production-grade systems.
Pydantic started as a library focused on type-safe data validation in Python and has become one of the most widely used projects in the language. Recently, the Pydantic team introduced Pydantic AI, a type-safe agent framework for creating dependable AI systems in Python.
Samuel Colvin, the creator of Pydantic and Pydantic AI, joins the podcast alongside Gregor Vand to explore the beginnings of Pydantic, the principles of type safety in AI applications, the progression of Pydantic AI, the LogFire observability platform, and the role of open-source sustainability and engineering discipline in advancing the future of AI tools.
Gregor Vand, a security-focused technologist, has served as a CTO in sectors like cybersecurity, cyber insurance, and general software engineering. Based in Singapore, he can be found at vand.hk or on LinkedIn.
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