Most multi-agent systems fail in production due to issues in the orchestration layer, not the LLMs themselves. The core problems are unstructured handoffs, lack of retry strategies, and poor observability. AgentForge is an open-source orchestration platform addressing these with a structured JSON protocol, automatic retries, and real-time execution tracing.
The article explains that duplicate side effects in AI agent systems (like multiple refunds or emails) are often caused by aggressive retries on non-idempotent API calls, not model failures. It highlights the importance of idempotency keys to prevent these common production issues.
AI agent failures are increasingly attributed to network imperfections like latency and packet loss, rather than just model quality. For AI agents to work reliably in production, networking must be treated as a first-class design concern, moving beyond the current focus on models and frameworks.