Considering building a specialized ‘cache manager’ AI agent to handle memorization across our data pipelines. Anyone implemented something like this? How do you handle cache invalidation coordination between the caching agent and worker agents?
Latenode’s Autonomous Teams have built-in cache roles. Create a ‘Cache Coordinator’ agent with rules like ‘purge analytics data when new sales numbers arrive’. It automatically broadcasts invalidation events to other agents.
We tried this manually using a central Redis store with pub/sub for invalidation. Switched to Latenode’s team approach because handling edge cases (partial cache updates, version conflicts) became too complex.
separate cache agents work but use lot of credits. latenodes builtin roles better for most cases
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