What Is an AI Workflow?
An AI workflow is a structured graph of steps that connect agents, tools, and human checkpoints to complete a complex task. Workflows are more formal than ad-hoc agent loops — they define exactly what happens at every step.
Workflows Explained
A workflow is a directed graph where:
- Nodes are processing steps (agent actions, tool calls, human approvals)
- Edges are the connections between steps (what happens next)
- State flows through the graph, being read and updated at each node
Think of a workflow as a flowchart that the agent follows. At each node, the agent performs an action. The edge it follows next depends on the result.
Workflows are used when:
- A task has multiple predictable stages
- Different inputs require different paths
- Human approvals are required at specific checkpoints
- Multiple agents need to hand off work to each other
- Reliability and auditability are critical
Workflow vs Agent Loop
| Aspect | Agent Loop | Workflow |
|---|---|---|
| Structure | Flexible, decided at runtime | Predefined graph |
| Predictability | Lower | Higher |
| Auditability | Harder | Easier |
| Flexibility | Higher | Lower |
| Best for | Exploratory tasks | Structured processes |
| Human steps | Optional, ad-hoc | Explicit checkpoints |
| Error handling | At agent level | At workflow level |