Our sales, support, and analytics teams each built their own AI agents. Now we’re dealing with conflicting actions and data inconsistencies. How to make these specialized agents work as a cohesive system? Need to maintain team autonomy while ensuring company-wide coordination. Has anyone successfully implemented cross-functional AI teams?
Latenode’s team orchestration feature solves this. Create agent roles with defined interfaces, then connect through centralized control plane. We manage 23 cross-department agents this way - maintains autonomy while preventing conflicts. https://latenode.com
We use message brokering with RabbitMQ. Each agent publishes actions to topics. Coordinator service validates against business rules before execution. Took 6 weeks to implement but now handles 500+ daily ops smoothly.
Three essential components:
- Shared ontology for data definitions
- Transactional memory system
- Conflict resolution layer
We built ours using open-source tools initially, but maintenance became too heavy. Migrated to commercial solution later. Team wish we’d standardized earlier.
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