Evidence-first authority page
AI Agents vs Workflows: What's the Difference?
A clear distinction between a fixed automation workflow and a genuine AI agent, since the two terms are often used interchangeably but describe different levels of autonomy.
Direct answer
A workflow follows a fixed, predetermined sequence of steps regardless of what happens along the way; an agent dynamically decides its next action based on the current state and can deviate from any predetermined path — the practical distinction matters because a workflow is more predictable and easier to debug, while an agent is more flexible but less predictable, and many production systems deliberately use a hybrid of both.
Last reviewed 2026-08-29
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Why the distinction is practical, not just terminology
A fixed workflow is the right choice when a task's steps are well-known and don't vary — it's predictable, testable, and cheap to run. An agent is the right choice when the steps genuinely depend on information only available at runtime. Using an agent where a workflow would do adds unpredictability without benefit; using a rigid workflow where genuine judgment is needed produces brittle failures on edge cases.