Jeremiah Lowin
Jeremiah Lowin is the founder and CEO of Prefect and the author of FastMCP. Prefect develops automation tools used across the data and AI ecosystem, and FastMCP has become the standard framework for working with the Model Context Protocol. Before founding Prefect, he spent over a decade leading risk and data initiatives at major investment firms and was a founding member of the Apache Airflow PMC. He lives in Washington, DC.
Session
Python became the language of data science because it made hard work feel possible. It gave scientists, analysts, engineers, and researchers a shared way to express ideas without forcing them to become software specialists first. The result was a style of software that made powerful systems easier to learn, easier to combine, and easier to trust.
In this keynote, Jeremiah Lowin explores what it means for software to be Pythonic: simple, composable, readable, and easy to reason about. Those qualities helped Python become the default language for data science, and they matter even more now that software is beginning to build software.
The next generation of agentic systems will be judged by whether people can understand them, change them, and trust them. This talk argues that the lesson of PyData is also the challenge for AI: build systems that remain easy to reason about as they become more powerful, and use emerging interfaces like MCP to make data easier to communicate, explore, and act on.