Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs
Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability. By…
Cassie Shum, Vice President of Ecosystem and Product Engineering at RelationalAI, discusses the importance of knowledge graphs in building production-ready agentic AI systems. She explains four practical architectural patterns that build upon basic RAG: context bundling, decision provenance, code as truth, and agent visibility. Shum demonstrates a knowledge graph-based harness to improve feedback loops, optimize token usage, and maintain system reliability.
She explains that her talk focuses on lessons learned from her experience building agentic systems and how knowledge graphs serve as a critical foundation for these systems.
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