Pydantic AI with Samuel Colvin

Python's popularity in data science and back end engineering has made it the default language for building AI infrastructure. However, with the rapid growth of AI applications, developers are increasingly looking for tools that combine Python's flexibility with the rigor of production ready systems. Pydantic began as a library for type safe data validation in Python and has become one of the language's most widely adopted projects. More recently, the Pydantic team created Pydantic AI, a type safe agent framework for building reliable AI systems in Python. Samuel Colvin is the creator of Pydantic and Pydantic AI. In this episode, he joins the podcast with Gregor Van to discuss the origins of Pydantic, the design principles behind type safety and AI applications, the evolution of Pydantic AI, the LogFire observability platform, and how open source sustainability and engineering discipline are shaping the next generation of AI tooling. Gregor Vand is a security focused technologist, having previously been a CTO across cybersecurity, cyber insurance, and general software engineering companies. He is based in Singapore and can be found via his profile at van.hk or on LinkedIn. Hello, and welcome to Software Engineering Daily. My guest today is Samuel Colvin. We're really excited to have you here today, Samuel. Thanks so much for having me. Yeah. Really excited to be here. Yeah. So, Samuel, you are just to get this completely correct, you are the founder of Pydantic. Is that correct? I am the founder of Pydantic. I have to say since I recently moved to the Bay Area, people have started asking me for the first time, did you also create the library? Which seems like a slightly weird question. I feel like I'd be a fraud if I was created Pydantic, the company running Pydantic, the company, and didn't create the library. But, yeah, I created the original library way back, and now now we're on the run the company by the same name. Good. Yeah. Well, I'm glad we cleared that one up at the start. I'm glad I didn't ask. Did you only found the company? So as we like to do on Software Engineering Daily, just getting a sense of where have you come from from a developer standpoint. I've seen on LinkedIn, you've worked through some interesting companies, and I think it really interesting to understand how Pydantic came about. We're also here to talk about Pydantic AI, but we're gonna just hear about the story to this point in time. Yeah. So I I was a mechanical engineer way back and then been a software engineer for since, like, 2014. Worked in a number of different roles, ran a bootstrapped self funded company before, but then started I don't know. It's really got into open source, like, 2016, 2017. And around then, type ins were just coming to Python in, I guess, 03/2006. And they seem really powerful, but it seemed to me then and seems still to me today, completely ludicrous that they don't …