Centralized orchestrators in multi-agent systems create a single point of failure. Here’s why you need a distributed coordinator—and how to build one using event sourcing and a lightweight
Most multi-agent orchestrators are built like a central brain that routes every decision. That's a single point of failure. Here's why you need a distributed coordinator pattern, and how we
When 200 AI agents hit the same API endpoint simultaneously, everything breaks. Here's how we solved the thundering herd problem with a distributed semaphore and a team in Can Tho.
Static agent chains fail in production. We built a lightweight, event-driven router that cut pipeline failures by 60% and eliminated bottlenecks. Here's the exact architecture and code.
Stop treating your agent orchestration like a simple retry loop. Here's why you need a circuit breaker pattern to prevent cascading failures in production multi-agent systems.
State management is the silent killer of multi-agent systems. Here's how we used event sourcing with a Vietnamese team to eliminate race conditions, reduce debugging time by 70%, and build
Retries aren't enough for production multi-agent systems. Here's why you need a real circuit breaker pattern to stop cascading failures, and how we implemented one using the ECOA AI Platform
Most multi-agent systems fail because of data starvation, not bad prompts. Here's why your orchestration layer is the real problem—and how to fix it with event-driven scheduling and a priority
When two AI agents try to write to the same Redis key, you don't get a bug. You get a war. Here's how we fixed it with a proper state
Shared state is the silent killer of multi-agent systems. After a production nightmare with competing Redis keys, here's exactly how we designed a conflict-free orchestration layer that actually works.
Local development is the missing link in multi-agent systems. Here's how to set up a real local environment, test agent interactions, and catch failures before they hit production — using