agentsop-map-reduce-fanout

Implement parallel LLM calls using a map-reduce dynamic fan-out protocol that processes N independent items concurrently and merges them into one result. It enforces bounded concurrency, explicit failure policies, and per-call timeouts.

Prevent 429 and TPM storms in concurrent LLM pipelines by enforcing bounded concurrency levels using semaphores or max concurrency limits. The protocol designs concurrency-by-design to safely manage parallel request throughput.

The best way to merge parallel LLM agent branches is selecting a reducer that matches your downstream consumer’s input shape, such as concatenate, summarize, vote, rank-top-K, or tree-reduce, ensuring coherent reduction across parallel outputs.

LangGraph supports dynamic fan-out for parallel retrieval via its Send mechanics. The protocol provides cross-framework SOPs covering LangGraph Send, asyncio, and CrewAI parallelism for multi-query retrieval and per-item processing.

Use map-reduce fan-out instead of batching when you process N independent items in parallel and need to reduce them into one result. The protocol provides activation guidance to determine when dynamic fan-out is appropriate versus chaining or sequential DAG workflows.

Use failure policies like abort-all, best-effort, retry-then-skip, or quorum for parallel LLM pipelines. The protocol requires explicit failure strategies alongside per-call and total wall-clock timeouts to handle dynamic fan-out safely.