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So far, when data streaming and AI are mentioned together, it typically describes the problem of maintaining a fresh, relevant context: e.g. use stream-processing to join/aggregate/enrich data streams, and pass them to an agent as context for inference. And honestly, I'm sold.

But is there anything else? E.g. using Kafka for agent-to-agent communication? Streaming long agent sessions? Workflow orchestration?