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What Is an Agentic Workflow? Definition and Design Patterns
A definition of agentic workflows and the common design patterns — sequential, router, and orchestrator — used to build them.
Direct answer
An agentic workflow is a process where one or more AI agents autonomously plan, execute, and adapt a sequence of steps toward a goal, as opposed to a fixed pipeline where every step is hard-coded in advance. The term describes the workflow's structure, not a specific product.
Last reviewed 2026-08-29
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Common design patterns
- Sequential — a fixed chain of steps where each agent or tool call feeds directly into the next, with limited branching.
- Router — a controller step classifies the input and routes it to one of several specialized downstream agents or tools.
- Orchestrator-worker — a top-level agent decomposes a goal into subtasks and delegates each to a specialized worker agent, then aggregates results.
- Evaluator-optimizer — one agent produces an output and a second agent critiques it against defined criteria, looping until the output passes.
Single agent vs. multi-agent
Not every agentic workflow requires multiple agents. A single agent with a well-designed tool set and a clear stopping condition often outperforms a multi-agent system for a well-scoped task, because multi-agent coordination adds latency and failure surface (a message passed incorrectly between agents, an aggregation step that drops context).
Multi-agent patterns earn their complexity when a task genuinely benefits from specialization — different agents with different tool access, different prompts, or different models tuned for different subtasks — rather than as a default architecture.
Where this fits in the frameworks landscape
Frameworks like LangGraph, CrewAI, and Microsoft Agent Framework provide the orchestration primitives — state management, agent handoff, tool routing — that these patterns are typically built on, rather than implementing the patterns themselves; the workflow design remains the developer's decision.