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LLM & Agentic

Hierarchical Delegation

Hierarchical delegation pattern for multi-agent systems: orchestrating specialized agents with a coordinator for complex tasks.

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Staff10 min readFirst readThe Agent LoopPlanner-Executor

After this section you can

  • Write a delegation brief that a worker can execute without the lead’s context, including an output contract
  • Choose a model per role and estimate the token cost of a team against a single agent
  • Tell router, planner and orchestrator apart, and prevent the coordination failures of parallel agents
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Hierarchical Delegation: Multi-Agent Teams

An orchestrator splits a job into briefs and hands each one to a worker agent with its own context window, tools and model. It is the most powerful way to spread a big task across agents, and the most expensive way to be right.

Key idea

Multi-agent is a context-management strategy. Each worker burns its own window on the reading and returns a short report; the orchestrator keeps only decisions. You pay for it in tokens, several times a single agent, so use it for broad, parallel, high-value work.

One lead holds the decisions. Each worker reads a lot in its own window and hands back a little.
1 · Request “audit our auth flow” 2 · Orchestrator claude-opus-5 plan · delegate · verify · synthesise 4 · Answer one voice, sources cited 3 · brief down, report up Research worker claude-haiku-4-5 web_search · web_fetch reads ~40K → returns ~1.5K Code worker claude-sonnet-5 read_repo · run_tests reads ~60K → returns ~2K Review worker claude-sonnet-5 read · grep (read-only) reads ~30K → returns ~1K Each worker: its own context window, only its own tools. A star, never a mesh. Token counts are illustrative.

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