At their core, AI agents are microservices with a brain. They're powered by large language models (LLMs) and are independent, specialized, and designed to operate autonomously.

But agents need more than LLMs to scale -- they need real-time data access, context, and the ability to collaborate across tools, services, and even other agents. As timely data becomes crucial for modern AI systems, agents must operate within distributed, event-driven environments. This session focuses on how to bridge the gap between streaming infrastructure and agentic architectures, by enabling developers to build, test, and operate agents natively on Flink. 

Through architecture diagrams, use cases and a demo, we'll show practical steps for getting started with streaming agents to power new automation workflows.