The Shift to Dynamic Multi Agent Autonomous Systems

The paradigm of Artificial Intelligence has shifted from monolithic, prompt-response models to dynamic, multi-agent autonomous systems. This "Agentic Transition" introduces a non-linear, geometric risk profile where errors cascade and amplify through interconnected agent workflows. Landmark research from Google and MIT reveals critical limitations to naive scaling: a "45% Threshold" where adding more agents to a task degrades performance if the baseline agent is already moderately competent, ...