What you'll learn
Deciding whether to index or not
Understand the tradeoffs and decision framework for when indexing makes sense in your RAG system
Building knowledge graphs for retrieval
Learn the technical approach and measurable customer impact from building graph-based retrieval systems
Solving MCP tool sprawl
Discover how super retrieval tools and codegen consolidate multiple tools into streamlined, functional systems
Why this topic matters
Production RAG requires architectural decisions most tutorials skip: whether to index, how to structure knowledge for complex retrieval, when prompt optimization compounds value, and solving tool sprawl before it kills performance. This session shows you the tradeoffs and implementations that separate demos from systems handling real user queries at scale.
You'll learn from
Jason Liu
Consultant at the intersection of Information Retrieval and AI
Jason has built search and recommendation systems for the past 6 years. He has consulted and advised a dozens startups in the last year to improve their RAG systems. He is the creator of the Instructor Python library.
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Josh Clemm
VP of Engineering, Dropbox
Currently VP of Engineering at Dropbox, focused on building Dropbox Dash - an AI-powered search and knowledge management experience. I believe in a people-first approach to engineering leadership, creating environments where teams can grow, ship fast, and find joy in building the future together.