Intro To Prompt Chaining in FormWise

Build multi-step SmartForms by passing outputs between prompt steps.

Overview

Prompt chaining lets you build multi-step SmartForms. Each step runs its own AI generation. Later steps can reuse earlier outputs (for example, “generate an avatar” → “write emails for that avatar”).

Use prompt chaining when you need:

• A workflow with clear stages (draft → refine → format)

• Higher output consistency (each step has a narrow job)

• Background reasoning steps that users don’t need to see

Each prompt chain step is a separate AI call. More steps increases token usage and timeout risk.

Prerequisites

• A SmartForm (prompt chaining is not available on Toolsets).

• At least two prompt chain steps (to pass output forward).

Build your first prompt chain

1

Create a SmartForm

Create a new SmartForm in FormWise.

2

Add a “Prompt Chain” step

Inside your SmartForm, add a new step and choose Prompt Chain.

3

Add at least one more step

Create Step 2 (and Step 3, Step 4, etc.). Each step can build on earlier outputs.

Map output between steps (@step_x)

In any step after Step 1, press @ in the prompt editor. You’ll see earlier outputs like @step_1.

Always add context before a mapped step

Bad (unclear):

• ❌ “Use @step_1 to generate the email copy.”

Good (explicit):

Using the customer avatar below, write a targeted email that addresses their pain points.

Customer Avatar:
@step_1

Treat @step_1 like a variable. Name it in plain English first.

Customize each step

Each prompt chain step is its own “module.” You can tune it independently:

• Instructions: keep them narrow and unambiguous.

• AI engine: choose a stronger model for complex steps.

• Datasets: add datasets when you need stable, domain-specific facts.

Show or hide steps from end users

Use the eye icon on each step:

• Visible: the user sees the step run and its output.

• Hidden: the step runs in the background. The user only sees what you expose later.

Hidden steps are useful for “prep work” like extraction, cleanup, or summarization.

Common issues

• You don’t see @step_1 in the menu: you’re editing Step 1, or you only have one step.

• Outputs get cut off: reduce output length, switch to a larger-context model, or split into more focused steps.

Next steps

• Go deeper on strategy, tokens, and structure in the Advanced Prompt Chaining Guide.

• Use the broader prompt checklist in Prompt Engineering.