At LlamaIndex we see a lot of agents built every day, and we've got a sense of what works and what doesn't. We've distilled those learnings down into a series of patterns and best practices for building real-world, production agents, and we're here to share them. You'll learn patterns for applying structure and guidance to famously nondeterministic LLMs and get concrete instruction on how to implement them.

About Laurie Voss
Laurie has been a web developer for 27 years, and along the way he co-founded npm, Inc.. He cares passionately about making technology accessible to everyone by demystifying complex technology topics.

Recorded at the AI Engineer World's Fair in San Francisco. Stay up to date on our upcoming events and content by joining our newsletter here: https://www.ai.engineer/newsletter

AI Engineer

LlamaIndex VP of Developer Relations presents key agent design patterns for production systems. The talk covers LlamaIndex as a framework for building generative AI applications, explains why agents are useful for handling unstructured data, and demonstrates five core design patterns: chaining, routing, parallelization, orchestrator-workers, and evaluator-optimizers. The presentation emphasizes how agents improve RAG performance through introspection and self-correction capabilities, and shows practical implementation using LlamaIndex workflows with Python functions and type annotations.

Effective agent design patterns in production — Laurie Voss, LlamaIndex