How we built our multi-agent research system Anthropic

Anthropic's multi-agent Research system uses a lead agent (Claude Opus 4) that coordinates parallel subagents (Claude Sonnet 4) to explore complex research queries simultaneously, achieving 90.2% better performance than single-agent systems by distributing token budgets across independent search trajectories. The system's effectiveness stems from token efficiency—token usage alone explains 80% of performance variance—combined with parallelization that enables breadth-first exploration unsuitable for sequential pipelines, allowing dynamic path adjustments as investigations unfold.

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