TLDR Tech / Practical
Lessons from Kafka and Flink for building robust AI agents
To create dependable AI agent workflows, the author suggests applying architectural principles from stream processing systems such as Kafka and Flink. These include utilizing durable external state, employing append-only event logs, and enabling recovery through replays. An example is given of how agent systems can avoid state loss and duplicate notifications during restarts by treating them like stream processing jobs, using concepts like keyed state, checkpoints, and idempotency keys.
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