RLM Orchestrator

Long-context reasoning across massive documents is handled by treating prompts as environments to explore rather than raw inputs. This orchestration approach uses recursive decomposition to break complex prompts into manageable chunks, preventing context rot.

Recursive decomposition for multi-hop synthesis is a method that breaks complex prompts into manageable chunks to avoid context rot. It coordinates distributed sub-queries to connect distant facts and synthesize insights across massive documents.

You orchestrate sub-queries by defining phases of reconnaissance, decomposition, delegation, and aggregation. This role-based prompt structure coordinates sub-agents to execute distributed sub-queries and aggregate findings into coherent answers.

Yes, you can use a role-based prompt structure to coordinate sub-agents for information integration. The orchestration process plans reconnaissance, spawns sub-agents for delegation, and aggregates their results to produce coherent answers.

The best way to avoid context rot in large-context inputs is recursive decomposition. By breaking complex prompts into manageable chunks and coordinating distributed sub-queries, you prevent information loss and maintain synthesis quality.