The core idea is smart - instead of dumping corrections into a log nobody rereads, it turns them into behavior the agent actually reuses next time. What I like most is that it's not a black box: learnings are visible on a dashboard, testable, and reversible, so you're not just trusting a vector store to quietly change your agent's behavior. The token savings angle is a nice bonus on top of the reliability pitch, not the main selling point.