Session
Feeding and Fencing AI Agents: Engineering Governed Agentic Systems on Real-Time Data
This session explores how to make autonomous AI agents trustworthy at scale.
Using a fraud investigation scenario built on Apache Kafka, the Model Context Protocol (MCP), and an LLM-based reasoning agent, the talk shows how governance can be engineered into both the real-time data layer and the tool boundary that controls agent actions.
Attendees will learn
Why the trust boundary in an agentic system belongs in the server, not only in the prompt
How MCP can be used as a typed, auditable governance contract
Engineering patterns behind shadow mode, approval-gated tools, and multi-model routing
How these concepts come together in a working open-source reference implementation they can explore afterward
This session is designed for engineers, architects, product leaders, researchers, students, and anyone interested in building trustworthy AI-agent systems.
Gajendra Babu Thokala
Senior Engineering Leader
Seattle, Washington, United States
Links
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