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Salesforce Certified Agentforce Specialist Sample Questions (Q33-Q38):
NEW QUESTION # 33
Universal Containers (UC) wants to offer personalized service experiences and reduce agent handling time with Al-generated email responses, grounded in Knowledge base.
Which AI capability should UC use?
- A. Einstein Service Replies for Email
- B. Einstein Email Replies
- C. Einstein Generative Service Replies for Email
Answer: A
Explanation:
ForUniversal Containers (UC)to offer personalized service experiences and reduce agent handling time using AI-generated responses grounded in theKnowledge base, the best solution isEinstein Service Replies for Email. This capability leverages AI to automatically generate responses to service-related emails based on historical data and theKnowledge base, ensuring accuracy and relevance while saving time for service agents.
* Einstein Email Replies(option A) is more suited for sales use cases.
* Einstein Generative Service Replies for Email(option C) could be a future offering, but as of now, Einstein Service Replies for Emailis the correct choice for grounded, knowledge-based responses.
:
Einstein Service Replies Overview:
NEW QUESTION # 34
When configuring a prompt template, an Agentforce Specialist previews the results of the prompt template they've written. They see two distinct text outputs: Resolution and Response. Which information does the Resolution text provide?
- A. It shows which sensitive data is masked before it is sent to the LLM.
- B. It shows the full text that is sent to the Trust Layer.
- C. It shows the response from the LLM based on the sample record.
Answer: C
Explanation:
Comprehensive and Detailed In-Depth Explanation:
In Salesforce Agentforce, when previewing a prompt template, the interface displays two outputs:Resolution andResponse. These terms relate to how the prompt is processed and evaluated, particularly in the context of theEinstein Trust Layer, which ensures AI safety, compliance, and auditability. TheResolution text specifically refers to the full text that is sent to the Trust Layer for processing, monitoring, and governance (Option A). This includes the constructed prompt (with grounding data, instructions, and variables) as it's submitted to the large language model (LLM), along with any Trust Layer interventions (e.g., masking, filtering) applied before or after LLM processing. It's a comprehensive view of the input/output flow that the Trust Layer captures for auditing and compliance purposes.
* Option B: The "Response" output in the preview shows the LLM's generated text based on the sample record, not the Resolution. Resolution encompasses more than just the LLM response-it includes the entire payload sent to the Trust Layer.
* Option C: While the Trust Layer does mask sensitive data (e.g., PII) as part of its guardrails, the Resolution text doesn't specifically isolate "which sensitive data is masked." Instead, it shows the full text, including any masked portions, as processed by the Trust Layer-not a separate masking log.
* Option A: This is correct, as Resolution provides a holistic view of the text sent to the Trust Layer, aligning with its role in monitoring and auditing the AI interaction.
Thus, Option A accurately describes the purpose of the Resolution text in the prompt template preview.
:
Salesforce Agentforce Documentation: "Preview Prompt Templates" (Salesforce Help:https://help.salesforce.
com/s/articleView?id=sf.agentforce_prompt_preview.htm&type=5)
Salesforce Einstein Trust Layer Documentation: "Trust Layer Outputs" (https://help.salesforce.com/s
/articleView?id=sf.einstein_trust_layer.htm&type=5)
NEW QUESTION # 35
Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology.
However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses.
Which solution should UC consider?
- A. Build Al model with Einstein discovery and deploy to sales users.
- B. fine-tune the Einstein AI model with CBM data.
- C. Enable Agentforce and deploy to sales users.
Answer: B
Explanation:
* Context of the Question: Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses.
* Why Fine-Tune an Einstein AI Model with CRM Data?
* Company-Specific Relevance: By fine-tuning Einstein AI with UC's CRM data (accounts, opportunities, products, and historical interactions), the model learns the enterprise-specific context. This ensures that the generative outputs are accurate and tailored to UC's sales scenarios.
* Security and Compliance: Using Salesforce Einstein within the Salesforce ecosystem keeps data under UC's control, aligning with trust, security, and compliance requirements.
* Better Predictions: Einstein AI can produce more relevant insights (e.g., recommended next steps, content suggestions, or AI-generated email responses) when it has been trained on real, high-quality internal data.
* Why Not Build an AI Model with Einstein Discovery (Option B)?
* Einstein Discovery Use Case: Einstein Discovery is best suited for predictive and prescriptive analytics (e.g., analyzing large data sets for patterns, scoring leads, or predicting churn). While it provides advanced analytics, it is not primarily designed for generative text-based interactions for end-user consumption in a conversational format.
* Why Not Enable Agentforce (Option C)?
* Agentforce Overview: "Agentforce" (sometimes referencing a pilot or non-mainstream name) typically focuses on interactive help or workforce collaboration. It does not inherently solve the problem of large-scale generative AI using internal CRM data. Moreover, you still need a robust generative engine fine-tuned on company data.
* Outcome: Fine-tuning the Einstein AI model with UC's CRM data (Answer A) is the most direct, Salesforce-native solution to provide generative AI responses that are aligned with UC's context, driving productivity gains and ensuring data privacy.
SalesforceAgentforce SpecialistReferences & Documents
* Salesforce Official: Einstein GPT Overview
* Discusses how Einstein GPT can be fine-tuned with specific CRM data to deliver contextually relevant, generative AI responses.
* Salesforce Trailhead:Get Started with Salesforce Einstein
* Explains the fundamentals of AI within the Salesforce platform, including training and optimizing Einstein models.
* Salesforce Documentation: Einstein Discovery
* Details how Einstein Discovery is primarily used for advanced analytics and predictions, not direct generative text solutions.
* SalesforceAgentforce SpecialistStudy Guide
* Provides the official outline of Einstein AI capabilities, referencing how to configure and fine- tune models for specialized enterprise use cases.
NEW QUESTION # 36
An Agentforce Service Agent, who has been successfully assisting customers with service requests in Salesforce, is now unable to help customers with issues related to a new product replacement process. The company recently implemented a custom Product Replacement object in Salesforce to track and manage these replacements. Which Agentforce Agent User change must be implemented to address this issue?
- A. The permission set group assigned to the Agent User needs to grant access to the Product Replacement flow.
- B. The profile assigned to the Agentforce Agent User needs AI training permission to the custom Product Replacement object.
- C. The permission set assigned to the Agent User needs Read access to the custom Product Replacement object.
Answer: C
Explanation:
Why is "Permission Set Read Access" the correct answer?
If an Agentforce Service Agent is unable to assist customers with the new Product Replacement process, it is likely due to missing object permissions.
Key Considerations for Object Access in Agentforce:
* Custom Objects Require Permission Set Access
* The new Product Replacement object must be explicitly assigned to the agent's permission set.
* Without Read access, the agent cannot view or interact with the object.
* Ensuring Full Data Access for Agents
* In Setup # Permission Sets, the admin should:# Grant Read access to the Product Replacement object# Ensure that related fields (e.g., status, replacement reason) are also accessible
* Aligning AI and Agent Workflows
* If Einstein AI is used to suggest solutions, the agent must have visibility into the Product Replacement object for context-aware responses.
Why Not the Other Options?
# A. The permission set group assigned to the Agent User needs to grant access to the Product Replacement flow.
* Incorrect because flow permissions only control automation access, not direct object access.
* If an agent cannot view the object, the flow will not be visible or usable.
# C. The profile assigned to the Agentforce Agent User needs AI training permission to the custom Product Replacement object.
* Incorrect because AI training permissions relate to model learning and improvement, not object visibility.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that permission sets control object-level access for Agentforce users.
NEW QUESTION # 37
Universal Containers (UC) wants to improve the efficiency of addressing customer questions and reduce agent handling time with AI- generated responses. The agents should be able to leverage their existing knowledge base and identify whether the responses are coming from the large language model (LLM) or from Salesforce Knowledge.
Which step should UC take to meet this requirement?
- A. Turn on Service AI Grounding and Grounding with Knowledge.
- B. Turn on Service Replies, Service AI Grounding, and Grounding with Knowledge.
- C. Turn on Service AI Grounding, Grounding with Case, and Service Replies.
Answer: A
Explanation:
To meetUniversal Containers'goal of improving efficiency and reducing agent handling time with AI- generated responses, the best approach is to enableService Replies,Service AI Grounding, andGrounding with Knowledge.
* Service Repliesgenerates responses automatically.
* Service AI Groundingensures that the AI is using relevant case data.
* Grounding with Knowledgeensures that responses are backed by Salesforce Knowledge articles, allowing agents to identify whether a response is coming from theLLMorSalesforce Knowledge.
* Option Cdoes not includeService Replies, which is necessary for generating AI responses.
* Option Alacks theGrounding with Knowledge, which is essential for identifying response sources.
For more details, refer toSalesforce Service AI documentationon grounding and service replies.
NEW QUESTION # 38
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