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Learn how ontologies serve as the crucial middle ground between rigid code-orchestrated workflows and chaotic LLM-driven processes in AI agent development. Discover when and how to implement these graph-shaped fragments of actionable knowledge to bring structure, semantics, and reliability to GenAI-powered applications. Explore three key applications through practical examples: guiding knowledge graph construction, adding semantic layers for more efficient and accurate retrieval in GraphRAG systems, and encoding essential domain logic that shouldn't be left to LLM interpretation. Gain insights from Dr. Jesús Barrasa, AI Field CTO at Neo4j and co-author of "Building Knowledge Graphs," as he demonstrates how ontologies can solve critical gaps in agent reasoning and decision-making processes.
