Taming LLMs with Pydantic - Parsing, Validating, and Guarding Output

Learn how to transform unpredictable LLM outputs into reliable, typed Python objects using Pydantic in this 12-minute conference talk from PyBay 2025. Discover practical techniques for defining schemas that coerce LLM responses into structured formats, implementing validation guardrails to ensure data integrity, and using structured prompting to guide model outputs. Explore real-world strategies for making large language models more predictable and scalable in production environments, with hands-on examples of parsing, validating, and guarding against unreliable AI-generated content through Pydantic's powerful type system and validation framework.