Scaling LLMs with Go - Production Patterns for Handling Millions of AI Requests

Learn production-ready patterns for scaling Large Language Model (LLM) infrastructure using Go in this conference talk from GopherCon 2025. Discover how Assembled successfully serves tens of millions of LLM requests for major companies like Canva, Etsy, and Patreon by leveraging Go instead of the more common Python approach. Explore concrete implementation strategies that take advantage of Go's type system, concurrency features, and interfaces to solve production challenges more elegantly. Gain practical insights into handling structured outputs, building parallel RAG (Retrieval-Augmented Generation) pipelines, and creating performant, reliable AI applications at scale. Master the specific advantages Go offers for LLM infrastructure and learn battle-tested patterns from real-world deployment experience in high-volume customer support AI systems.