Event-Driven Architecture Cuts Multi-Agent AI Latency and Boosts Throughput

Scaling multi-agent AI systems with synchronous calls creates deadlocks, timeouts, and cascading failures, as one slow agent can stall an entire pipeline. Event-driven architecture (EDA) addresses this by replacing request-response patterns with a publish-subscribe model, where agents emit and react to events on a shared bus instead of waiting on each other. In tests described by TormentNexus, synchronous coordination among just three agents increased end-to-end latency by 340% compared to an event-driven setup, with the Planner spending 78% of its time idle. Using a Swarm event bus, peak task throughput reportedly jumped from 45 tasks per minute under synchronous coordination to 850 tasks per minute with EDA. The Pub/Sub model allows Planner, Implementer, and Critic agents to stay loosely synchronized through shared event streams without any agent blocking another.