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AI models are advancing rapidly, yet the systems around them remain fragile. Each backend change risks breaking an AI client, while on the web, servers evolve seamlessly without requiring users to download a new browser. What if AI systems worked the same way? In this session, Michael Carducci introduces the architecture of 3rd Generation Agentic AI, building on the principles explored in Data Architecture for AI. He demonstrates how technologies such as JSON-LD, Hydra, and semantic integration enable evolvable, interoperable AI ecosystems that operate reliably at web scale.
Through live demos and real-world examples, Carducci shows how these web-native standards allow APIs to describe themselves, adapt to change, and support safe, autonomous discovery by AI agents, all without brittle coupling. The session highlights why the true frontier of AI lies not in smarter models, but in shared meaning, and how architecture holds the key to achieving it.
What You Will Learn
The principles of 3rd Generation Agentic AI and how it differs from current AI architectures
How JSON-LD, Hydra, and semantic standards create evolvable, interoperable AI systems
Practical examples of building adaptive APIs that enable safe, autonomous agent interaction
Who Should Attend
AI engineers, software architects, and developers designing AI-driven systems who want to build scalable, flexible, and semantically interoperable agentic architectures.
