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Salesforce Certified Agentforce Specialist Sample Questions (Q48-Q53):

NEW QUESTION # 48
Where should theAgentforce Specialistgo to add/update actions assigned to a copilot?

A. Copilot Detail page, Global Actions, or the record page for the copilot action
B. Copilot Actions page, the record page for the copilot action, or the Copilot Action Library tab
C. Copilot Actions page or Global Actions

Answer: B

Explanation:
To add or update actions assigned to a copilot, An Agentforce can manage this through several areas:
* Copilot Actions Page: This is the central location where copilot actions are managed and configured.
* Record Page for the Copilot Action: From the record page, individual copilot actions can be updated or modified.
* Copilot Action Library Tab: This tab serves as a repository where predefined or custom actions for Copilot can be accessed and modified.
These areas provide flexibility in managing and updating the actions assigned to Copilot, ensuring that the AI assistant remains aligned with business requirements and processes.
The other options are incorrect:
* Bmisses the Copilot Action Library, which is crucial for managing actions.
* Cincludes the Copilot Detail page, which isn't the primary place for action management.
References:
* Salesforce Documentation onManaging Copilot Actions
* SalesforceAgentforce SpecialistGuide onCopilot Action Management

NEW QUESTION # 49
When creating a custom retriever in Einstein Studio, which step is considered essential?

A. Configure the search index, choose vector or hybrid search, choose the fields for filtering, the data space and model, then define the ranking method.
B. Define the output configuration by specifying the maximum number of results to return, and map the output fields that will ground the prompt.
C. Select the search index, specify the associated data model object (DMO) and data space, and optionally define filters to narrow search results.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:In Salesforce's Einstein Studio (part of the Agentforce ecosystem), creating acustom retrieverinvolves setting up a mechanism to fetch data for AI prompts or responses. Theessential stepis defining the foundation of the retriever: selecting thesearch index, specifying thedata model object (DMO), and identifying thedata space(Option A). These elements establish where and what the retriever searches:
* Search Index: Determines the indexed dataset (e.g., a vector database in Data Cloud) the retriever queries.
* Data Model Object (DMO): Specifies the object (e.g., Knowledge Articles, Custom Objects) containing the data to retrieve.
* Data Space: Defines the scope or environment (e.g., a specific Data Cloud instance) for the data.
Filters are noted as optional in Option A, which is accurate-they enhance precision but aren't mandatory for the retriever to function. This step is foundational because without it, the retriever lacks a target dataset, rendering it unusable.
* Option B: Defining output configuration (e.g., max results, field mapping) is important for shaping the retriever's output, but it's a secondary step. The retriever must first know where to search (A) before output can be configured.
* Option C: This option includes advanced configurations (vector/hybrid search, filtering fields, ranking method), which are valuable but not essential. A basic retriever can operate without specifying search type or ranking, as defaults apply, but it cannot function without a search index, DMO, and data space.
* Option A: This is the minimum required step to create a functional retriever, making it essential.
Option A is the correct answer as it captures the core, mandatory components of retriever setup in Einstein Studio.
References:
* Salesforce Agentforce Documentation: "Custom Retrievers in Einstein Studio" (Salesforce Help:
https://help.salesforce.com/s/articleView?id=sf.einstein_studio_retrievers.htm&type=5)
* Trailhead: "Einstein Studio for Agentforce" (https://trailhead.salesforce.com/content/learn/modules
/einstein-studio-for-agentforce)

NEW QUESTION # 50
Universal Containers (UC) wants to create a new Sales Email prompt template in Prompt Builder using the
"Save As" function. However, UC notices that the new template produces different results compared to the standard Sales Email prompt due to missing hyperparameters.
What should UC do to ensure the new prompt template produces results comparable to the standard Sales Email prompts?

A. Use Model Playground to create a model configuration with the specified parameters.
B. Manually add the hyperparameters to the new template.
C. Revert to using the standard template without modifications.

Answer: B

Explanation:
WhenUniversal Containerscreates a new Sales Email prompt template using the"Save As"function, missing hyperparameters can result in different outputs. To ensure the new prompt produces comparable results to the standard Sales Email prompt, theAgentforce Specialistshouldmanually add the necessary hyperparameters to the new template.
* Hyperparameters likeTemperature,Frequency Penalty, andPresence Penaltydirectly affect how the AI generates responses. Ensuring that these are consistent with the standard template will result in similar outputs.
* Option A (Model Playground)is not necessary here, as it focuses on fine-tuning models, not adjusting templates directly.
* Option C (Reverting to the standard template)does not solve the issue of customizing the prompt template.
For more information, refer toPrompt Builder documentationon configuring hyperparameters in custom templates.

NEW QUESTION # 51
Universal Containers (UC) users are complaining that agent answers are not satisfactory. The agent is using PDF files as a knowledge source.
How should UC troubleshoot this issue?

A. Verify the retriever's filter criteria and data source connection.
B. Analyze the data mapping between source fields and Data Cloud object fields.
C. Check that the agent has the PDF file field permission access for the data library.

Answer: A

Explanation:
Why is "Verify the retriever's filter criteria and data source connection" the correct answer?
If agent answers are not satisfactory when using PDF files as a knowledge source, the issue is likely caused by:
* Retriever misconfiguration
* If filters are too broad or too restrictive, AI may fail to find relevant information.
* Checking filter logic and retrieval scope helps improve accuracy.
* Incorrect data source connection
* If the retriever is not properly linked to the PDF storage location, it may fail to retrieve relevant information.
* Ensuring a stable connection between Salesforce Data Cloud and the retriever prevents retrieval failures.
* Parsing Issues with PDF Files
* If PDFs are not properly indexed, AI may struggle to extract relevant content.
* Ensuring structured document formatting improves AI comprehension.
Why Not the Other Options?
# A. Analyze the data mapping between source fields and Data Cloud object fields.
* Incorrect because data mapping issues primarily affect structured CRM data, not PDF-based knowledge sources.
* The issue likely stems from retrieval settings, not field mapping.
# B. Check that the agent has the PDF file field permission access for the data library.
* Incorrect because permission access issues would prevent AI from accessing PDFs entirely rather than causing poor response quality.
* AI can still generate responses, even if they are inaccurate, which means the issue lies in retriever settings, not permissions.
Agentforce Specialist References
* Salesforce AI Specialist Material details how retriever filters and data sources impact AI- generated answers.
* Salesforce Certification Guide mentions the importance of verifying retriever configurations for accurate knowledge retrieval.

NEW QUESTION # 52
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process.
How should An Agentforce apply the power of conversational AI to this use case?

A. Create a custom copilot action which calls a flow.
B. Create a Flex prompt template in Prompt Builder.
C. Configure the Integration Flow Standard Action in Agent.

Answer: A

Explanation:
To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Agent to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
* Option B is correct because it enables integration between Agent and the flow that connects to Oracle ERP.
* Option A (Flex prompt template) is more suited for static responses and not for invoking flows.
* Option C (Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.
References:
* Salesforce Agent Actions: https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm

NEW QUESTION # 53
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100% PASS QUIZ 2025 PASS-SURE SALESFORCE AGENTFORCE-SPECIALIST BEST PREPARATION MATERIALS

100% Pass Quiz 2025 Pass-Sure Salesforce Agentforce-Specialist Best Preparation Materials