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​AI agents are only as good as the data they can access, yet legacy architectures often fail to provide the real-time context agents require. This session explores context engineering: the foundation for ensuring data freshness and quality. We will demonstrate how to unify streaming and low-latency serving on Google Cloud using the Model Context Protocol (MCP) and Vertex AI.

​Learn how combining Confluent’s real-time data with Google Cloud enables agents to take accurate, autonomous action without the lag of traditional data stacks.

Speaker#1: Dr. Sean Falconer is Confluent’s AI Entrepreneur in Residence, driving AI strategy and thought leadership. Sean has built and launched products that have impacted millions. As the founder of [Proven.com](https://proven.com/), he led engineering, product development, and go-to-market strategies, successfully guiding the company to acquisition. At Google, Sean worked on enhancing developer experience and advancing conversational AI technologies.

​He holds a Postdoc in Bioinformatics at Stanford University, where he collaborated with the World Health Organization to modernize the International Classification of Diseases.

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Related topics

AI Algorithms
Artificial Intelligence
Machine Learning
Data Science
Software Engineering

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