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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic	Details
Topic 1	Agentforce Concepts: This section assesses the skills of AI Engineers and covers how Agentforce works, including its reasoning engine, standard and custom topics, agent actions, and user security management. It also includes testing and deploying agents from sandbox to production environments.
Topic 2	Prompt Engineering: This section measures the skills of AI Developers and focuses on prompt engineering techniques. It covers identifying when to use Prompt Builder, managing prompt templates, selecting appropriate grounding techniques, and explaining the process for creating and executing prompt templates.
Topic 3	Agentforce and Data Cloud: This section measures the skills of AI Developers and addresses how Agentforce integrates with Data Cloud to improve response accuracy and personalize answers. It involves grounding with retrievers in Data Cloud to enhance agent performance.
Topic 4	Agentforce and Service Cloud: This section measures the skills of AI Engineers and focuses on building agents that answer questions based on Knowledge articles and connecting them to digital channels. It also covers identifying the correct generative AI features in Agentforce for Service Cloud scenarios.
Topic 5	Agentforce and Sales Cloud: This section assesses the skills of AI Developers and covers identifying the correct generative AI features in Agentforce for Sales Cloud scenarios. It also includes determining when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches.

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Salesforce Certified Agentforce Specialist Sample Questions (Q66-Q71):

NEW QUESTION # 66
A Universal Containers administrator is setting up Einstein Data Libraries. After creating a new library, the administrator notices that only the file upload option is available; there is no option to configure the library using a Salesforce Knowledge base.
What is the most likely cause of this Issue?

A. The administrator is not using Lightning Experience, which is required to display all data source options, Including the Knowledge base option, when configuring Einstein Data Libraries.
B. Salesforce Knowledge is not enabled in the organization; without Salesforce Knowledge enabled, the Knowledge-based data source option will not be available in Einstein Data Libraries.
C. The current Salesforce org lacks the necessary Einstein for Service permissions that support the Knowledge-based Data Library option, so only the file upload option is presented.

Answer: B

Explanation:
Why is "Salesforce Knowledge is not enabled" the correct answer?
If an administrator only sees the file upload option in Einstein Data Libraries and cannot configure a Salesforce Knowledge base, the most likely reason is that Salesforce Knowledge is not enabled in the organization.
Key Considerations for Einstein Data Libraries:
* Salesforce Knowledge Integration is Optional
* Einstein Data Libraries can pull knowledge data only if Salesforce Knowledge is enabled.
* If Knowledge is not activated, the system will default to file uploads as the only available option.
* How to Fix This Issue?
* The administrator should enable Salesforce Knowledge in Setup # Knowledge Settings.
* Once enabled, the option to configure Knowledge-based Data Libraries will become available.
Why Not the Other Options?
# A. The current Salesforce org lacks the necessary Einstein for Service permissions
* Incorrect because even without certain permissions, the Knowledge option would still be visible but greyed out.
# C. The administrator is not using Lightning Experience
* Incorrect because Einstein Data Libraries are accessible in both Classic and Lightning, and Lightning does not control Knowledge base visibility.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that Salesforce Knowledge must be enabled for Data Libraries to use Knowledge as a data source.
* Salesforce Certification Guide explicitly states that file uploads are the default option if Knowledge is not available.

NEW QUESTION # 67
Universal Containers has a custom Agent action calling a flow to retrieve the real-time status of an order from the order fulfillment system.
For the given flow, what should theAgentforce Specialistconsider about the running user's data access?

A. The custom action adheres to the permissions, held-level security, and sharing settings configured in the flow.
. The Agent will always run flows in system mode so the running user's data access will not affect the data returned.
B. The flow must have the "with sharing" permission selected m the advanced settings for the permissions, field-level security, and sharing settings to be respected.

Answer: A

Explanation:
When a flow is invoked via a custom Agent action, its data access depends on the flow's runtime configuration, not system mode by default. Salesforce flows can be configured to respect the running user's permissions and sharing settings:
* If the flow is set to "Run as the User Who Launched the Flow" (enabled in Flow Settings), it adheres to the user's permissions, field-level security (FLS), and sharing rules.
* Option C is incorrect because flows do not always run in system mode unless explicitly configured to do so.
* Option A is misleading because "with sharing" is an Apex concept, not a flow setting.Flows use runtime settings like FLS and sharing enforcement.
References:
* Salesforce Help: Flow Runtime and Security Context
* Flow Settings: "Run with User Permission and Field-Level Security" ensures data access aligns with the user's permissions.

NEW QUESTION # 68
What is best practice when refining Einstein Copilot custom action instructions?

A. Provide examples of user messages that are expected to trigger the action.
B. Use consistent introductory phrases and verbs across multiple action instructions.
C. Specify the persona who will request the action.

Answer: A

Explanation:
When refiningEinstein Copilot custom action instructions, it is considered best practice toprovide examples of user messagesthat are expected to trigger the action. This helps ensure that the custom action understands a variety of user inputs and can effectively respond to the intent behind the messages.
* Option B(consistent phrases) can improve clarity but does not directly refine the triggering logic.
* Option C(specifying a persona) is not as crucial as giving examples that illustrate how users will interact with the custom action.
For more details, refer toSalesforce's Einstein Copilot documentationon building and refining custom actions.

NEW QUESTION # 69
Universal Containers (UC) plans to send one of three different emails to its customers based on the customer's lifetime value score and their market segment.
Considering that UC are required to explain why an e-mail was selected, which AI model should UC use to achieve this?

A. Predictive model
B. Generative model
C. Predictive model and generative model

Answer: A

Explanation:
Universal Containers should use a Predictive model to decide which of the three emails to send based on the customer's lifetime value score and market segment. Predictive models analyze data to forecast outcomes, and in this case, it would predict the most appropriate email to send based on customer attributes.
Additionally, predictive models can provide explainability to show why a certain email was chosen, which is crucial for UC's requirement to explain the decision-making process.
* Generative models are typically used for content creation, not decision-making, and thus wouldn't be suitable for this requirement.
* Predictive models offer the ability to explain why a particular decision was made, which aligns with UC's needs.
Refer to Salesforce's Predictive AI model documentation for more insights on how predictive models are used for segmentation and decision making.

NEW QUESTION # 70
Universal Containers (UC) has a mature Salesforce org with a lot of data in cases and Knowledge articles. UC is concerned that there are many legacy fields, with data that might not be applicable for Einstein AI to draft accurate email responses.
Which solution should UC use to ensure Einstein AI can draft responses from a defined data source?

A. Work Summaries
B. Service AI Grounding
C. Service Replies

Answer: B

Explanation:
Service AI Groundingis the solution thatUniversal Containersshould use to ensureEinstein AIdrafts responses based on a well-defined data source. Service AI Grounding allows the AI model to be anchored in specific, relevant data sources, ensuring that any AI-generated responses (e.g., email replies) are accurate, relevant, and drawn from up-to-date information, such asKnowledge articlesorcases.
Given that UC has legacy fields and outdated data, Service AI Grounding ensures that only the valid and applicable data is used by Einstein AI to craft responses. This helps improve the relevance of responses and avoids inaccuracies caused by outdated or irrelevant fields.
Work SummariesandService Repliesare useful features but do not address the need for grounding AI outputs in specific, current data sources likeService AI Groundingdoes.
For more details, you can refer to Salesforce'sService AI Grounding documentationfor managing AI- generated content based on accurate data sources.

NEW QUESTION # 71
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Get latest Agentforce-Specialist Prepare Questions Pass the Agentforce-Specialist Exam in the First Attempt

Salesforce Agentforce-Specialist Exam Syllabus Topics:

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Salesforce Certified Agentforce Specialist Sample Questions (Q66-Q71):

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