What Is an Agentic Workflow?
A structured, multi-step process where an AI agent plans, acts, checks results, and adjusts — as opposed to a single prompt-and-response exchange.
More than one step
An agentic workflow is a structured sequence where an agent breaks a task into steps, takes an action for each step (often via a tool call), evaluates the result, and decides what to do next — repeating until the overall task is complete, rather than producing one single response to one single prompt.
Why structure the steps at all
A well-defined workflow — plan, then act, then check, then decide the next step — makes an agent's behavior more predictable and easier to debug than an unstructured "figure it out" loop, and it gives natural points to insert validation or a human check before the agent proceeds further.
Common patterns
Recurring agentic workflow patterns include a reasoning-then-acting loop (think, act, observe the result, repeat), a planner that breaks a large task into subtasks up front, and a reviewer step that checks another step's output before the workflow is allowed to continue — all aimed at making multi-step automation more reliable.
Frequently Asked Questions
What is an agentic workflow?
A structured, multi-step process where an AI agent plans, takes an action, evaluates the result, and decides what to do next — repeating until a task is complete, rather than a single prompt-and-response exchange.
Why not just let an agent freely decide everything?
A structured workflow makes behavior more predictable and easier to debug, and creates natural points to insert validation or human review before the agent proceeds — an unstructured loop is harder to reason about or trust.