So this is about running LLM prompts as part of an existing streaming data processing setup.

I guess you could call a trigger-based SQL query an "agent", since that term is wide open to being defined however you want to use it!

If you read through the whole thing, they don't manage to build an AI Agent, they make LLM API calls using Flink's SQL.

They admit making it agentic, with choice over tool selection and with agent-like memory, requires workarounds.

Annoying workarounds, imo.

The post mentions work is in progress to build agents that use Flink without using Flink SQL.

Thereby invalidating it's own title.

SQL is a great language to express “choose something from a priority queue and do something with it” but if you try to think about predefining your entire computation DAG as a single query rather than many queries over time, you lose the loose asynchronous iteration that gives an agent the same grace you’d give to a real-life task assignment. And that grace is what makes agentic workflows powerful.