AI Agent Screen Reference

Appian Designer provides a streamlined screen for creating, managing, and optimizing your AI agents. Use this screen to configure AI agent behavior, test functionality, and monitor performance. This reference explains each interface element and its purpose.

For step-by-step configuration guidance, see Create and Configure an AI Agent. For foundational concepts, see About AI Agents.

Create AI Agent dialog

When you click NEW > AI Agent in the Build view, the Create AI Agent dialog appears. The dialog includes the following fields:

Field	Description
Name	The name of the AI agent.
Description	An optional description to help identify the AI agent's purpose.
Agent Type	The type of AI agent to create. Choose Process Agent to automate routine tasks without interruption within a process model, or Chat Agent to engage users through natural conversation in an interface. Agent type cannot be changed after creation.

After you click CREATE, the AI agent opens in the Build tab where you configure its instructions, tools, inputs, and outputs.

Tabs

The screen includes these main tabs that organize your work.

• Build
• Monitor

Build

The Build tab provides a unified workspace for creating, configuring, and testing AI agents. The interface uses a split-pane layout with the Configure panel on the left and the Test panel on the right. This layout lets you view your AI agent's complete configuration alongside step-by-step test results in a single workspace.

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Configure panel layout

The Configure panel organizes AI agent settings into two main areas:

• Instructions field: This field occupies the top of the Configure panel. The Instructions field includes an internal scrollbar for long text and remains visible at all times, even when you work with tools, inputs, or outputs in the tabbed section below it.
• Tabbed container: This container sits below the Instructions field and holds the Tools, Inputs, and Outputs sections. To define properties, click the + button in each tab to open a modal.

Markdown rendering in the Build tab

The Instructions field supports Markdown formatting to help you structure and style your content. The Instructions field displays raw Markdown syntax by default to allow for immediate editing. To see how the rendered Markdown displays, click the Preview tab.

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Test panel states

The Test panel operates in two states depending on whether a test is running.

Empty/Ready state

The Test panel displays the Empty/Ready state when no test is running and no results are loaded. The Empty/Ready state includes:

• Load Test Case dropdown, prominently displayed at the top of the panel.
• Clear Input Values button to reset all input fields.
• Auto-generated input fields based on the AI agent's configured inputs.
• Run Test button. You cannot run tests while unsaved configuration changes exist.

Running/Result state

The Test panel displays the Running/Result state after you click Run Test. The Running/Result state includes:

• Inputs used (read-only), showing the input values at the time the test started.
• Step-by-step tool calls and the AI agent's thinking process.
• Final outputs with Markdown rendering.
• Stop button for canceling the running AI agent.
• Save as Test Case button to preserve the configuration for reuse.
• New Test button to reset the Test panel back to the Empty/Ready state.

Parallel tool call display in the run stream

When the AI agent executes multiple tool calls in parallel, the run stream groups those calls under a single step. Each parallel step displays:

• Grouped step layout: All concurrent tool calls share the same step ID and appear as a visual group within that step.
• Individual card interaction: Click any tool call card within the group to view its results or error messages.

For parallel execution constraints, see Parallel tool execution.

Configure panel (left)

The Configure panel lets you view, create, and manage AI agent settings including instructions, inputs, outputs, and tools.

Test panel (right)

The Test panel lets you validate your AI agent's behavior by providing input values and observing how your AI agent responds. The Test panel supports simple form fields for basic data types or expressions for complex types like records, CDTs, and maps. The Load Test Case dropdown allows you to quickly reuse saved test configurations. When you save a test case, the expressions are also saved, so you can reuse and modify them in future tests.

If you configure an input as an array using the Array (multiple values) checkbox, you must use constant or expression options to define your test lists. Static values are not available for array inputs.

The side-by-side layout of the Configure and Test panels eliminates the need to switch between separate views, creating a more direct feedback loop for building and refining AI agents. For step-by-step guidance, see Create and Configure an AI Agent and Monitor AI Agents.

Monitor

The Monitor tab lets you track how AI agents are performing over time. The Monitor tab displays key metrics for each AI agent, including the AI agent run status, number of tool calls, successful completions, and average run duration. These metrics help you measure efficiency, spot trends, and identify areas for improvement.

The run history uses a timeline layout that displays each step chronologically, including tool calls, AI agent reasoning, and outputs. The timeline replaces the previous card-based display and provides a clearer view of how the AI agent processed each request.

The run detail view accessed from the Monitor tab also includes a Stop button for canceling active AI agent runs. For monitoring best practices, see Monitor AI Agents.

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Inputs and outputs

Inputs and outputs define the data your AI agent receives and returns. Configure inputs and outputs directly in the Inputs and Outputs sections of the Configure panel on the Build tab. When configuring these variables, specify whether each variable accepts a single value or multiple values.

Array (multiple values)

The Array (multiple values) checkbox lets input or output variables accept or return a list of values instead of a single value. Selecting the Array (multiple values) checkbox changes the variable signature from a single data type to a list of that data type.

For example:

• A Document input without the checkbox accepts one document.
• A Document input with the checkbox accepts a list of documents.

The array capability lets you pass multiple items directly to your AI agent or receive structured lists as outputs without building complex looping logic. The AI agent screen formats list values for better readability.

Tools

Tools are design objects that enable AI agents to access or act on data, processes, and documents.

Tool	Description
Process	Starts a process model in Appian to perform a series of predefined tasks or workflows.
AI Agent	Collaborates with another AI agent to complete a task, providing a way to orchestrate a modular, multi-agent workflow.
MCP Server	Connects to an external MCP server to give the AI agent access to third-party tools. When you select this option, you choose an MCP connected system, then select specific tools from that server.
Document	Provides the AI agent with context from a single document.
Document folder	Gives the AI agent access to multiple documents stored in a folder.
Record	Allows the AI agent to retrieve data from record types.
Rule	Uses expression rules or decisions to provide logic or data.

Developer feedback

Developer feedback allows you to rate AI agent outputs directly within evaluation results. Feedback captures structured quality judgments on the overall AI agent run.

Feedback controls

Developer feedback appears on each test result in the Evaluate tab drill-down view and in the Test panel after a run completes. The feedback includes the following elements:

Element	Description
Thumbs up / Thumbs down	A binary quality judgment on the AI agent run. Required to submit feedback. Positive feedback (thumbs up) marks the run as a strong example for future reference.
What went wrong checkboxes	Optional checkboxes that identify the type of failure. Available options: "Wrong output", "Made up information", "Too many steps", "Got stuck", "Took too long", "Failed to recover from error", "Other". Select up to five. Appears after thumbs-down.
Free-text comment	An optional text field for additional context about the rating.

Feedback targets

Feedback targets the overall outcome of the entire AI agent run, including whether the final output meets expectations.

Strong examples

When you give a thumbs-up rating, the AI agent run is automatically marked as an ideal outcome. Strong examples create a library of reference outputs.

Feedback