2.2 Standard and Custom Topics (Subagents)

Salesforce Certified Agentforce Specialist Exam

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1 Chapter 1: Exam Overview & How Agentforce Agents Work

1.1 Agentforce Specialist (AI-201) Exam Facts & Spring '26 Blueprint 1.2 How an Agent Works & the Building Blocks of Agent Script 1.3 Hybrid Reasoning: Agent Script in Canvas View and Script View

2 Chapter 2: Deterministic Control, Topics (Subagents) & Actions

2.1 Deterministic Behavior: Filters, Variables & Template Expressions 2.2 Standard and Custom Topics (Subagents) 2.3 Standard and Custom Agent Actions

3 Chapter 3: Agent Types, Security Context, Channels & Agent API

3.1 When to Use an Employee Agent or a Service Agent 3.2 Security Context: Who the Agent Runs As and How It Affects Actions 3.3 Connecting Agents to Channels: Digital Experiences, Email, Voice & Slack 3.4 When to Use the Agent API

4 Chapter 4: Prompt Builder Fundamentals

4.1 When to Use Prompt Builder 4.2 Access Controls Governing Prompt Templates 4.3 Prompt Template Types: Field Generation, Flex & More 4.4 Creating, Activating & Executing Prompt Templates

5 Chapter 5: Grounding, Prompt Best Practices, Trust Layer & Model Access

5.1 Choosing the Right Grounding Technique 5.2 Best Practices for Writing Effective Prompts 5.3 Einstein Trust Layer Security and Privacy Features 5.4 Managing and Preventing Access to Specific Models

6 Chapter 6: Data 360 Fundamentals for Agentforce

6.1 Agentforce Data Library: Types and Concepts 6.2 Chunking: Breaking Content Into Retrievable Units 6.3 Indexing and Search Types: Vector, Hybrid & Keyword 6.4 Retrievers: Individual, Ensemble & Filtered Retrieval

7 Chapter 7: Testing Agents with Testing Center

7.1 Testing an Agent with Testing Center 7.2 How Testing Center Evaluations Work

8 Chapter 8: Deploying Agents and Prompt Templates

8.1 Deploying an Agent from Sandbox to Production 8.2 Deploying Prompt Templates from Sandbox to Production

9 Chapter 9: Governance and Observability

9.1 Managing and Monitoring Agents 9.2 Agent Analytics and Agent Optimization

10 Chapter 10: Multi-Agent Orchestration, MCP & A2A

10.1 When a Multi-Agent Architecture Is Appropriate 10.2 Open Multi-Agent Protocols: MCP and A2A

2.2 Standard and Custom Topics (Subagents)

Key Takeaways Explain This Topic AI

Beginning in April 2026, Salesforce calls agent topics subagents, with no change in functionality.

A subagent includes a name, a 1-3 sentence description, reasoning instructions, reasoning actions, and action definitions.

The Agent Router compares recent conversation history with subagent names and descriptions to choose the best subagent.

Adding a subagent from the asset library adds an editable copy; later edits in the asset library don't sync to that copy.

A custom subagent created inside an agent in Agentforce Builder is available only to that agent version.

Last updated: September 2026

2.2 Standard and Custom Topics (Subagents)

Quick Answer: A subagent (called a topic in the Spring '26 exam guide and in older docs) is one job the agent can do . It has a name and description that drive classification, reasoning instructions that control logic and guide the LLM, and actions that are its tools. Use standard subagents from the asset library for common jobs such as escalation, off-topic handling, and customer verification. Create custom subagents for jobs specific to your business.

Anatomy of a Subagent

Part What it contains How it's used

Name Usually 2-3 plain-language words, such as Order Management Classification and references ( @subagent.Order_Management )

Description 1-3 sentences describing the job and the requests that should trigger it The Agent Router compares it with the conversation to pick the best match

Reasoning instructions Agent Script logic plus natural-language prompts Resolved into the prompt sent to the LLM

Actions available for reasoning References to agent actions and utilities (transition, set variables, escalate), with optional filters and follow-up actions Tools the LLM may choose during reasoning

Action definitions Names, descriptions, inputs, outputs, and targets of all actions assigned to the subagent Make actions available to reference. Visible in Script view, not Canvas view

Subagents keep the agent focused. The LLM sees only the current subagent's resolved instructions and reasoning actions, not every tool in the org.

How Classification Uses Descriptions

When you create an agent, a special subagent called the Agent Router becomes the starting subagent. Transitions to every subagent are added to its reasoning actions. The agent compares the recent conversation, including the latest message, with the names and descriptions of those subagents and selects the best match.

You can customize routing:

Add logic, actions, and variables to the Agent Router to drive classification.

Exclude a subagent from classification with a filter.

Remove a subagent's reference from the Agent Router so it's reachable only by transitions from other subagents. For example, a "Refund Approval" subagent could be reachable only from "Order Management."

Define a different starting subagent, or remove the Agent Router entirely if you control routing another way.

Writing a strong description

Weak description Strong description

"Handles customer questions." "Answers questions about order status, delivery dates, tracking numbers, and changes to shipping addresses for existing orders."

"Billing." "Explains invoice charges, payment due dates, and payment methods, and helps customers update a saved card. Doesn't handle refunds."

Overlapping descriptions cause inconsistent routing. If two subagents both claim "payment problems," the classifier may flip between them.

Standard Subagents

Standard subagents come from the asset library (Setup → Agentforce Assets) and from agent templates. They're prebuilt examples for common business use cases. Ones that appear in Salesforce documentation and default templates include:

Standard subagent Job
Agent Router Special starting subagent that classifies and routes each message
Off Topic Politely redirects requests outside the agent's purpose without answering them
Ambiguous Question Asks the user to clarify requests that are too vague to route
Escalation Transfers the conversation to a human through the connection's outbound Omni-Channel flow

Customer Verification / Service Customer Verification Verifies identity and stores the verified ID in VerifiedCustomerId

General FAQ Answers general questions, typically with the Answer Questions with Knowledge action and a Data Library

Case Management Creates and manages cases, for example when escalation isn't possible

Key behaviors of the asset library:

Adding a subagent from the asset library adds a copy to your agent. You edit the copy, and changes apply only to that agent version.

Changes to the asset library version don't sync to copies already in agents. Add the updated subagent again to pick up changes.

You can't delete a standard subagent from the asset library. You can delete custom ones.

After adding a standard subagent, review and customize its instructions, reasoning actions, and underlying flows or prompt templates.

Custom Subagents

Create a custom subagent when no standard subagent covers the job, such as warranty registration on a custom object or a return process with company-specific rules.

Where you create it Availability Best for

Inside an agent in Agentforce Builder (Canvas view, Script view, or with the Agentforce assistant) Only that agent version A job unique to one agent

In the asset library (Setup → Agentforce Assets → Subagents → New Subagent) Can be added to many agents and versions Reusable jobs shared across agents

Subagents created in the asset library currently follow the legacy builder style (classification description, scope, instructions), but they can be added to agents in either builder and customized afterward. If you rename a custom subagent in an agent, update any references to it in the Agent Router or other subagents.

Loading diagram... Choosing standard vs. custom subagents

Best Practices for Subagent Instructions

Salesforce's instruction guidance for agents emphasizes:

Put sensitive or deterministic business rules into logic or actions. Instead of "Don't refund an order unless it was within 30 business days," build that check into a flow-based action or Agent Script logic.

Keep instructions minimal. Start with the fewest needed, add one at a time while testing, and remove overlap or contradictions. Salesforce notes that each legacy instruction field supports up to 131,072 characters, but shorter usually performs better.

Give business context. Define terms in plain language, such as "Promo codes apply discounts at checkout; registration codes register products for warranty."

Provide decision criteria between similar actions. "If the customer can access their email, use Email Password Reset; otherwise use Security Question Verification."

Be explicit about sequence. In the legacy builder, agents don't follow separate instruction fields in order, so use one instruction with "First… Then… Finally…". In the new builder, use logic when order truly matters.

Use absolutes deliberately and language consistently. Say "customer" everywhere rather than mixing "client" and "customer," and name actions explicitly.

Scenario Guide

Scenario Best answer
Customers ask about the weather on a retail support agent Rely on the Off Topic subagent to redirect
"I need help" with no detail Ambiguous Question asks for specifics
A job only one agent performs, using a custom object Custom subagent created in that agent

Five business-unit agents all need the same "Loyalty Balance" job Custom subagent in the asset library , added to each agent

A refund subagent should never be chosen directly by classification Remove it from the Agent Router's actions and transition to it from Order Management