Imagine a world where you can build AI agents to complete any task you need.
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A few years ago, that was the plot out of a Marvel movie, but today…
Imagine spinning up AI agents that handle any task on your backlog. Not sci-fi anymore, just solid engineering.
In this session, we’ll dive into the semantic layer — the data modeling and query foundation that powers LLM-based agents. We’ll share key architecture principles, design patterns, and best practices for building scalable, AI-ready semantics.
Discover how to model and query data optimized for agent interaction, enabling systems to talk to your data without complex SQL, saving time and unlocking deeper insights.
Join Lior Ebel, Sari Blumenberg (Budnick), and Roy Benjamin as they unpack the core engineering and architectural shifts shaping the full lifecycle of complex, LLM-native applications.
