Updated 2026년 4월
Best Multi-Agent Framework for Sequential workflows
Sequential workflows chain agents in a fixed pipeline — each step finishes before the next begins. Pick this pattern when the work decomposes cleanly into stages with clear ownership and predictable handoffs. CrewAI, LangGraph, and Haystack all implement sequential pipelines as a first-class primitive; LangGraph wins when you need typed state and replayable checkpoints.
Top 3 picks for sequential workflows
Best fit inputs
Roles 2-5, latency tolerance under 10 seconds, observability moderate or higher, team experience basic or above.
Typical use cases
- →Document ingest → enrichment → classification pipelines.
- →Customer email triage where intent extraction precedes routing.
- →Multi-step data validation with a final approval gate.
Pitfalls
- !Sequential pipelines are brittle to upstream failures — invest in retry and dead-letter handling early.
- !Token cost grows linearly with pipeline length; prune intermediate steps before launch.
- !Pure sequential is the wrong fit when intermediate state must influence which step runs next — see adaptive.
FAQ
When is sequential the wrong choice?
When agents need to react to intermediate state or call each other dynamically. Adaptive or hierarchical patterns will fit better.
Does sequential mean single-threaded?
Within a single trace, yes — but you can parallelise across traces. Concurrency belongs to the runtime, not the workflow.
Is sequential cheaper than parallel?
Usually yes per task, because there is no fan-out token amplification. It is also slower per task by definition.
How long should a sequential pipeline be?
Five steps is the comfortable ceiling before observability becomes painful and token costs balloon. Beyond that, refactor into hierarchical.
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