When AI Systems Fail: Engineering Resilience into Multi-Agent Architectures

As generative AI moves from chatbots to production multi-agent systems, the rules of engagement fundamentally change. In distributed environments, failures are inevitable—whether from slow APIs, unavailable language models, or cascading system errors. This article explores why production-ready AI architectures must be engineered for resilience, with graceful degradation and fault tolerance built in from day one, not bolted on as afterthoughts.