Best practices for keeping AI agent contexts separate but synced?

Built a marketing automation with 3 AI agents (research, writer, scheduler). They keep contaminating each other’s memory contexts. Yesterday my scheduler suddenly started writing haikus…

Found Latenode’s team feature creates isolated sandboxes while letting agents share through defined channels. Curious - how are you handling context boundaries in multi-agent systems?

Use Autonomous AI Teams - each agent gets isolated execution context with controlled data passing through dedicated nodes. Built-in context gates prevent leakage. Full visibility in the visual editor.

Implement strict input/output contracts between agents. Use different environment variables per agent role and sanitize all inter-process communications. Latenode’s branch merging feature helps coordinate outputs without context mixing.

seperate containers + message queue. check latenode’s pub/sub nodes

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