Single-agent systems have a ceiling. For complex, multi-step tasks — software development pipelines, research automation, enterprise workflows — multi-agent systems (MAS) are where the real power is. This guide covers the four leading frameworks, key architectural patterns, and the production best practices that actually matter. Why Multi-Agent? Single agents hit three fundamental limits: Limit Symptom Multi-Agent Solution Context length Forgets instructions mid-task Split subtasks; each agent stays focused Specialization Generalist quality drops Role-specialized agents in combination Parallelism Sequential = slow Run independent tasks concurrently Concrete example : A software development task split into Requirements Agent → Design Agent → Implementation Agent → Test Agent yields measurably better quality than one "do everything" agent. The 4 Core Architectural Patterns 1.…