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Agentforce Specialist Certification Maintenance (Summer '25)

  Agentforce Specialist Certification Maintenance (Summer '25)

Control Agent Access to Topics and Actions with Filters

As of March 2025, you can now create filters for topics and actions in Agentforce, ensuring agents can access them only when specific conditions are met. Previously, agents had access to all added topics and actions without restriction. Now, agents’ access to topics and actions can be controlled using filter and context variables.

Filters help you securely manage agent access to sensitive or conditional workflows.

This is especially useful for Service agents on customer channels. Once you’ve configured and customized the Customer Verification topic to align with your security requirements, you can create filters to control access to topics and actions that perform tasks on a user’s behalf. For example, you might unlock a Case Management topic only when the user’s case status is Escalated, or allow an agent to initiate a return only if the user’s order was received within the past 30 days.

To get started with using filters:

  1. Add the variables to your agent via the Context panel. These serve as conditions in your filters.
  2. Go to the Filters tab and create a filter.

Once you’ve created your filter, here’s how you can apply it to a topic or action.

  1. In the Topics panel, open the Details page for the topic or action you want to control. Apply the filter. Once you do, it’s active for that topic or action within this specific agent only.
  2. Once the filter conditions are met, the agent can access and use the filtered topic or action.

This update applies to Lightning Experience in Enterprise, Performance, Unlimited, and Developer editions.

Secure Agents with Customer Verification

In Agentforce, security isn’t just about authentication. It’s about controlling access to actions within the agent experience. That’s where Customer Verification topics play a key role, ensuring that only verified users can initiate sensitive conversations or perform high-risk actions through the agent.

You can define which topics and actions require verification, tailoring access based on your organization’s specific security policies. For example, if your company offers booking services through a self-service channel, you might want to verify a user’s identity before allowing them to do things like change a reservation, access payment details, or request a refund.

Here’s how it works. If an unverified user attempts to access a protected topic or action, the agent automatically launches the Customer Verification topic. From there, the agent:

  1. Requests the user’s email or username.
  2. Sends a one-time passcode (OTP) to the user via email.
  3. Verifies the user when they successfully enter the OTP.

By adding this step, you greatly reduce the risk of unauthorized access or fraudulent changes.

Test an Agent Using Testing Center

Before launching your generative AI-powered agent into the world, you need confidence that it works correctly in every situation. That’s where Agentforce Testing Center comes in, a new feature that allows you to evaluate agent accuracy and reliability at scale by:

  • Running batch tests using a simple CSV template
  • Using generative AI to create test scenarios
  • Testing up to 1,000 cases per test
  • Running up to 10 test jobs in a 10-hour window

This results in faster development cycles and more reliable agents that are ready to meet customer needs from day one.

Create and Run a Test

When creating your own test scenarios, start with the provided CSV testing template. Make sure to include values in the Utterances column and at least one additional column. For expected values, use the API names—not the labels—of topics and actions. You can find these API names in Agentforce Builder. Keep in mind that any empty fields in your test file are treated as failures.

  1. From Setup, in the Quick Find box, search for and select Testing Center. Or from Agent Builder, click Batch Test.
  2. Click New Test.
  3. Give your test a name.
  4. Select the agent and add a description.
  5. Click Next.
  6. (Optional) Choose to include context variables (like user profile, location, or channel) to simulate different user environments. You can also choose to include conversation history.
  7. Click Next.
  8. You can generate test cases using AI or use your own scenarios. For AI-generated test cases, you can create test cases based on relevant topics and actions or based on the data available to that agent in Agentforce Data Library. Select one of the following:
  • Topics and Actions: Generate up to 1,000 test cases by selecting topics to test. Add a description to guide the AI on purpose and scope, then click Next.
  • Agentforce Data Library: With a data library assigned, generate up to 100 test cases based on the agent’s knowledge. Add a description and select topics, then click Next.
  • Upload CSV: Use the testing template to upload up to 1,000 custom test cases. Include data in the Utterances column and at least one other. Use API names (not labels) for topics and actions—find these in Agentforce Builder.
  1. Click Generate Test Cases to finalize and create your test set.
  2. To re-run a test, locate it in the test list and select Run Again from the dropdown menu.

Q/A:

1. What’s one way Agentforce helps protect access to sensitive topics and actions within an agent experience?

Ans: Using filters and Customer Verification to control access based on conditions

2. Which of the following is true about using the Agentforce Testing Center?

Ans: You can test agents using CSV templates or have tests automatically created using gen AI.

3. What’s a required step when deploying an AI agent from a sandbox to production using change sets?

Ans: Ensure the orgs are connected via a deployment connection.

4. When creating a test in Agentforce Testing Center, what must be included in the CSV file?

Ans: At least one utterance and the API name of the expected topic

Which two types of data sources can be used in the Agentforce Data Library to improve response accuracy?
Ans: Custom retrievers with filters, web search data libraries

What is the purpose of adding a custom retriever to a Field Generation prompt template in Prompt Builder?
Ans: To ground prompts with real-time data for more accurate responses

What must users do to allow an AI agent to answer questions using knowledge articles?
Ans: Create a data library using knowledge articles as the source.

What are the required steps to connect an Agentforce Service agent to a digital channel like WhatsApp or Facebook Messenger?
Ans: Configure Omni-Channel, create a service deployment, and build an Omni-Channel Flow.




How do Agentforce SDR and Agentforce Sales Coach differ in their purpose?
Ans: SDR automates outreach; Sales Coach provides rep coaching and feedback.

When would someone use an Agentforce Sales Coach instead of an Agentforce SDR?
Ans: When your goal is to improve rep performance with personalized coaching.



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