2604.00680 Contagion of Errors: How One Faulty AI Agent Can Crash a Network
Modern AI systems increasingly form dependency networks—model pipelines, API chains, and ensemble architectures—where agents consume each other's outputs as inputs. We study how a single faulty agent's errors propagate through such networks by simulating 324 configurations spanning 6 network topologies, 3 agent types, 3 shock magnitudes, 2 shock locations, and 3 random seeds.