VI · Multi-AgentMature★★

Lead Researcher

also known as Research Orchestrator, Lead-and-Subagents

A lead agent writes a research plan and dispatches parallel sub-agents that fan out for breadth-first information gathering, then merges results.

This pattern helps complete certain larger patterns —

  • specialisesOrchestrator-Workers★★— An orchestrator dynamically breaks a task into subtasks at runtime and delegates each to a worker LLM, then synthesises results.
  • specialisesSupervisor★★— Place a coordinating agent above a set of specialised agents and route work to them.

Context

A team is using an agent to handle open-ended research tasks — write a market brief on a niche industry, gather competitive intelligence, prepare a literature review. The work benefits from breadth-first exploration across many sources rather than depth-first reasoning along one thread, and there is a deadline measured in hours, not days.

Problem

A single agent doing the research serially is bottlenecked on its own token generation: it can only search and read one source at a time, and by the time it has visited ten sources the deadline has passed or its context window is exhausted. A generic orchestrator-workers pattern handles parallel sub-tasks but does not say anything about how to plan research questions, how to keep sub-agents from overlapping, or how to synthesise findings into a coherent answer. The team needs a structure shaped specifically for research, not a generic dispatcher.

Forces

  • Sub-agent count vs cost.
  • Synthesis quality bounded by lead agent's reasoning over fragmented results.
  • Information overlap across sub-agents is wasted compute.

Example

An investment research firm asks an agent to write a brief on a niche industrial-equipment market by Friday. A single agent takes hours and misses half the relevant sources. They restructure as lead-researcher: the lead reads the brief, plans five parallel research questions (market size, top vendors, regulatory landscape, recent M&A, customer reviews), and dispatches each to a sub-agent that searches independently. Findings come back as structured records; the lead synthesises them and dispatches a follow-up sub-agent for one gap it spots. Wall-clock time drops from hours to twenty minutes.

Diagram

Solution

Therefore:

Lead agent receives the user query, plans a set of parallel research questions, and dispatches each to a sub-agent. Each sub-agent searches independently and returns structured findings to the lead. The lead reads the returned findings and synthesises the answer; if synthesis reveals gaps, the lead spawns additional sub-agents.

What this pattern forbids. Sub-agents return findings only to the lead; peer-to-peer communication is forbidden.

The smaller patterns that complete this one —

And the patterns that stand alongside it, or against it —

  • alternative-toClone Fan-Out Research·— Spawn 100 or more identical, full-capability agent instances in parallel — each a complete general agent rather than a role-specialised worker — and aggregate their independent outputs into a single answer.
  • alternative-toRumination Agent★— Run a single agent through a protracted think-search-verify-revise-act loop spanning hundreds of tool calls, autonomously re-formulating hypotheses across the run.

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References

Provenance