7 agentic orchestration patterns every AI builder should know before shipping
mdancho84 · x · 2026-09-01
The author argues 80% of data scientists want to build AI agents, yet almost none can answer which orchestration pattern to use — and picking wrong breaks the whole workflow. His quick breakdown:
- Parallel — multiple agents run simultaneously for independent tasks; faster output.
- Sequential — one after another; more reliable when steps depend on each other.
- Loop — repeats until a condition is met; good for evaluation, retries, quality checks.
- Router — one agent decides which agent handles the task; for widely varying inputs.
- Aggregator — many inputs feed one agent for a single synthesized output.
- Network — agents talk freely; for complex reasoning.
- Hierarchical — a planner coordinates workers; for scaling.
He adds that hierarchical is what Cursor used to write 1 million lines of code autonomously in a week, and the pattern separating those who know the concept from those who can ship it.
Related event: 7 Agent Orchestration Patterns: Choose Wrong and Your Workflow Fails(2 posts)→
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