Build a structured extractor
A lot of AI work has nothing to do with conversation: "take this unstructured input and give me back something my code can use." A support ticket → a queue. A contract → its key terms. A review → a sentiment and a set of themes. For that, skip the agent and use a flow whose output shape is guaranteed. Two patterns cover it.
Classifier — one of N categories
When the answer is a single label from a fixed set, use the Classifier pattern.
- New flow → Classifier
Define your categories — say
{billing, technical, account, urgent}— with a short description of what belongs in each. The descriptions are what make it accurate; be specific about the boundaries. - Test and publish
Run real inputs through the test pane, tighten the category descriptions where it gets confused, and publish a version.
- Call it
Run it (form shape) and the output is one of your categories — a value you can
switchon directly, no parsing.
Structurer — typed JSON against a schema
When you need multiple fields out, use the Structurer pattern. You give it a JSON Schema and it returns an object matching it.
- New flow → Structurer
Describe the shape you want — the fields, their types, which are required. A contract extractor might return
{ parties: string[], effectiveDate: string, autoRenews: boolean }. - Test and publish
Feed it representative inputs, confirm the fields come back right, and publish.
- Call it
The run returns an object matching your schema — drop it straight into your code, no free-text parsing, no "sometimes it wraps it in prose."
Compose them
A structurer or classifier can be attached to an agent as a tool, or imported into a bigger flow as a step. Build the reliable piece once, reuse it everywhere.