Shared caching between specialized AI agents - best approach?

Building a team of AI agents where one agent’s output feeds into another’s process. Right now, each agent makes independent API calls even for identical data. Tried setting up a shared database, but consistency issues arise when agents update cached values.

How are people handling coordinated caching across Latenode’s Autonomous AI Teams? Any patterns for version-stamped results or read-through caching that works across agents?

Autonomous Teams have shared memory layers. Create agent-specific namespaces in workflow variables. Use their built-in version control - agents automatically reference latest approved data. Game changer for multi-stage processing.

Implement a publish-subscribe model. Agents write to a central cache with execution timestamps. Consumer agents check timestamp validity before using. Added a JavaScript node to handle conflict resolution logic.