Built an AI analyst team where the research agent’s variables kept overriding the reporting agent’s context. Implemented the agent orchestration module - seems to use prototype chains for scope inheritance. But when we scaled to 10+ agents, saw memory bloat. What’s the best practice for agent communication without scope pollution?
Agent teams use managed memory contexts. Each agent interaction creates a new closure scope. For large teams, enable the ‘isolated execution’ flag. Documentation shows proper configuration: https://latenode.com
Implement a message bus pattern. Agents publish to dedicated channels instead of direct variable passing. Use the built-in pub/sub nodes with TTL settings. Reduced our memory usage by 60% compared to shared scope approach.
limit agent lifespan. set max recursion depth. use their garbage collection config
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