Multi-Agent Architecture Patterns for Claude Code
Multi-agent architectures distribute work across multiple agent invocations, each with its own focused context. When designed well, this distribution enables capabilities beyond single-agent limits. When designed poorly, it introduces coordination overhead that negates benefits. The critical insight is that sub-agents exist primarily to isolate context, not to anthropomorphize role division.
Core Concepts
Multi-agent systems address single-agent context limitations through distribution. Three dominant patterns exist: supervisor/orchestrator for centralized control, peer-to-peer/swarm for flexible handoffs, and hierarchical for layered abstraction. The critical design principle is context isolation—sub-agents exist primarily to partition context rather than to simulate organizational roles.
Effective multi-agent systems require explicit coordination protocols, consensus mechanisms that avoid sycophancy, and careful attention to failure modes including bottlenecks, divergence, and error propagation.
Why Multi-Agent Architectures
The Context Bottleneck
Single agents face inherent ceilings in reasoning capability, context management, and tool coordination. Multi-agent architectures address these limitations by partitioning work across multiple context windows.
The Parallelization Argument
Many tasks contain parallelizable subtasks that a single agent must execute sequentially. Multi-agent architectures assign each subtask to a dedicated agent with a fresh context.
The Specialization Argument
Different tasks benefit from different agent configurations. Multi-agent architectures enable specialization without combinatorial explosion.
Progressive Loading
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- •See: references/patterns.md
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