매달, 우리는 1000명 이상의 사람들이 시험 준비를 잘하고 시험을 잘 통과할 수 있도록 도와줍니다.
Salesforce Agentforce Specialist 온라인 연습
최종 업데이트 시간: 2025년11월17일
당신은 온라인 연습 문제를 통해 Salesforce Salesforce Agentforce Specialist 시험지식에 대해 자신이 어떻게 알고 있는지 파악한 후 시험 참가 신청 여부를 결정할 수 있다.
시험을 100% 합격하고 시험 준비 시간을 35% 절약하기를 바라며 Salesforce Agentforce Specialist 덤프 (최신 실제 시험 문제)를 사용 선택하여 현재 최신 182개의 시험 문제와 답을 포함하십시오.
정답:
Explanation:
To begin validating that the correct fields are being masked in Einstein Trust Layer, the Agentforce Specialist should request the Einstein Generative AI Audit Data from the Security section of the Salesforce Setup menu. This audit data allows the Agentforce Specialist to see how data is being processed, including which fields are being masked, providing transparency and validation that the configuration is working as expected.
Option B is correct because it allows for the retrieval of audit data that can be used to validate data masking.
Option A (Flow Debugger) and Option C (Einstein Feedback) do not relate to validating field masking in the context of the Einstein Trust Layer.
Reference: Salesforce Einstein Trust Layer Documentation:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm
정답:
Explanation:
Agent implementation would be most advantageous in Salesforce Service Cloud when the goal is to streamline customer support processes and improve response times. Agent can assist agents by providing real-time suggestions, automating repetitive tasks, and generating contextual responses, thus enhancing service efficiency.
Option B (data security) is not the primary focus of Agent, which is more about improving operational efficiency.
Option C (marketing campaigns) falls outside the scope of Service Cloud and Agent’s primary benefits, which are aimed at improving customer service and case management.
For further reading, refer to Salesforce documentation on Agent for Service Cloud and how it improves support processes.
정답:
Explanation:
When Universal Containers creates 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, the Agentforce Specialist should manually add the necessary hyperparameters to the new template.
Hyperparameters like Temperature, Frequency Penalty, and Presence Penalty directly 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 to Prompt Builder documentation on configuring hyperparameters in custom templates.
정답:
Explanation:
To ground a sales email on Opportunity Products, Events near the customer, and Tone and voice examples, the Agentforce Specialist should use a prompt-initiated flow. This flow can dynamically fetch the necessary data from related records in Salesforce and ground the generative AI output with contextually accurate information.
Option B (flex template) does not provide the ability to fetch dynamic data from Salesforce records automatically.
Option C (manual insertion) would not allow for the dynamic and automated grounding of data required for custom prompts.
Refer to Salesforce documentation on flows and grounding for more details on integrating data into custom prompt templates.
정답:
Explanation:
For Universal Containers (UC) to refine its Generative AI prompt design strategy and improve the accuracy of the generated summaries for the custom object Guest, the best practice is to focus on crafting concise, clear, and consistent prompt templates.
This includes:
Effective grounding: Ensuring the prompt pulls data from the correct sources.
Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.
Clear instructions: Giving unambiguous directions on what to include in the response.
Iterative feedback: Regularly testing and adjusting prompts based on user feedback.
Option B is correct because it follows industry best practices for refining prompt design.
Option A (prompt test mode) is useful but less relevant for refining prompt design itself.
Option C (prompt review case with Salesforce) would be more appropriate for technical issues or complex prompt errors, not general design refinement.
Reference: Salesforce Prompt Design Best Practices:
https://help.salesforce.com/s/articleView?id=sf.prompt_design_best_practices.htm
정답:
Explanation:
When Universal Containers uses the Draft with Einstein feature in Sales Cloud to create a personalized email, the predefined adjustment to Make Less Formal is the correct option to revise the draft with a more casual tone. This option adjusts the wording of the draft to sound less formal, making the communication more approachable while still maintaining professionalism.
Enhance Friendliness would make the tone more positive, but not necessarily more casual.
Optimize for Clarity focuses on making the draft clearer but doesn't adjust the tone.
For more details, see Salesforce documentation on Einstein-generated email drafts and tone adjustments.
정답:
Explanation:
When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field. Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.
Option B is incorrect because person accounts do not limit the availability of merge fields for the Account object.
Option C is irrelevant since even if no related lists are available at runtime, the prompt can still generate based on other available data fields.
For more information, refer to Salesforce documentation on supported fields and limitations in Prompt Builder.
정답:
Explanation:
Since security and data privacy are critical, the best option for the Agentforce Specialist is to integrate the fine-tuned LLM (Large Language Model) into Salesforce by adding it to Einstein Studio Model Builder. Einstein Studio allows organizations to bring their own AI models (BYOM), ensuring the model is securely managed within Salesforce’s environment, adhering to data privacy standards.
Option A (embedding via iFrame) is less secure and doesn’t integrate deeply with Salesforce's data and security models.
Option C (making callouts to OpenAI) raises concerns about data privacy, as sensitive Salesforce data would be sent to an external system.
Einstein Studio provides the most secure and seamless way to integrate custom AI models while maintaining control over data privacy and compliance. More details can be found in Salesforce's Einstein Studio documentation on integrating external models.
정답:
Explanation:
To create a digest of account action plans using the generative API feature, Universal Containers should use the REST API. The REST API is ideal for integrating Salesforce with external systems and enabling interaction with Salesforce data, including generative capabilities like creating summaries or digests. It supports modern web standards and is suitable for flexible, lightweight interactions between Salesforce and legacy systems.
Metadata API is used for retrieving and deploying metadata, not for data operations like generating summaries.
SOAP API is an older API used for integration but is less flexible compared to REST for this specific use case.
For more details, refer to Salesforce REST API documentation regarding using REST for data integration and generating content.
정답:
Explanation:
An Agentforce wants to include data from the response of an external service invocation (REST API callout) into a prompt template. The goal is to incorporate dynamic data retrieved from an external API into the AI-generated content.
Solution:
Use External Service Record Merge Fields
External Service Integration:
Definition: External Services in Salesforce allow the integration of external REST APIs into Salesforce without custom code.
Registration: The external service must be registered in Salesforce, defining the API's schema and methods.
External Service Record Merge Fields:
Purpose: Enables the inclusion of data from external service responses directly into prompt templates using merge fields.
Functionality:
Dynamic Data Inclusion: Allows prompt templates to access and use data returned from REST API callouts.
Merge Fields Syntax: Use merge fields in the prompt template to reference specific data points from the API response.
Implementation Steps:
Register the External Service:
Use External Services to register the REST API in Salesforce.
Define the API's schema, including methods and data structures.
Create a Named Credential:
Configure authentication and endpoint details for the external API.
Use External Service in Flow:
Build a Flow that invokes the external service and captures the response. Ensure the flow outputs the necessary data for use in the prompt template. Configure the Prompt Template:
Use External Service Record merge fields in the prompt template to reference data from the flow's output.
Syntax Example: {{flowOutputVariable.fieldName}}
Why Other Options are Less Suitable:
Option A (Convert the JSON to an XML merge field):
Irrelevance: Converting JSON to XML merge fields is unnecessary and complicates the process.
Unsupported Method: Salesforce prompt templates do not support direct inclusion of XML merge fields from JSON conversion.
Option C (Use “Add Prompt Instructions” flow element):
Purpose of Add Prompt Instructions:
Allows adding instructions to the prompt within a flow but does not facilitate including external data.
Limitation: Does not directly help in incorporating external service responses into the prompt template.
Reference: Salesforce Agentforce Specialist Documentation - Integrating External Services with Prompt Templates:
Explains how to use External Services and merge fields in prompt templates.
Salesforce Help - Using Merge Fields with External Data:
Provides guidance on referencing external data in templates using merge fields.
Salesforce Trailhead - External Services and Flow:
Offers a practical understanding of integrating external APIs using External Services and Flow.
Conclusion:
By using External Service Record merge fields, the Agentforce Specialist can effectively include data from external REST API responses into prompt templates, ensuring that the AI-generated content is enriched with up-to-date and relevant external data.
정답:
Explanation:
When using Prompt Builder in a Salesforce org, the correct process involves several important steps:
Select the appropriate prompt template type based on the use case.
Develop the prompt within the prompt workspace, where the template is created and customized.
Select CRM-derived grounding data to be dynamically inserted into the prompt, ensuring that the AI-generated responses are based on accurate and relevant data.
Pick the model to use for generating responses, either using Salesforce's built-in models or custom ones.
Test and validate the generated responses to ensure accuracy and effectiveness.
Option B is correct as it follows the proper steps for using Prompt Builder.
Option A and Option C do not capture the full process correctly.
Reference: Salesforce Prompt Builder Documentation:
https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm
정답:
Explanation:
Universal Containers (UC) has concerns about data privacy when using Salesforce's generative AI features, particularly around preventing third-party LLMs from accessing or retaining their data. The Zero-Data Retention Policy in the Einstein Trust Layer is designed to address these concerns by ensuring that:
No data is used for training or product improvements by third-party LLMs.
No data is retained outside of the customer's Salesforce organization.
The LLM provider cannot access any customer data.
This policy aligns perfectly with UC’s requirements for keeping their data safe while leveraging generative AI capabilities.
Prompt Defense and Data Masking are also security features, but they do not directly address the concerns related to third-party data access and retention.
Reference: Salesforce Einstein Trust Layer Documentation:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer.htm
정답:
Explanation:
When creating a custom action in Agent, one of the available options is to use Flows. Flows are a powerful automation tool in Salesforce, allowing the Agentforce Specialist to define custom logic and actions within the Copilot system. This makes it easy to extend Copilot's functionality without needing custom code.
While Apex triggers and SOQL are important Salesforce tools, Flows are the recommended method for creating custom actions within Agent because they are declarative and highly adaptable.
For further guidance, refer to Salesforce Flow documentation and Agent customization resources.
정답:
Explanation:
To generate an email about products that closely match a customer’s expressed interests, An Agentforce should recommend using a custom sales email template that is grounded with interest and product information. This ensures that the email content is personalized based on the customer's preferences, increasing the relevance of the marketing message.
Using grounding ensures that the generative AI pulls the correct data related to customer interests and product matches, making the email more effective.
For more information, refer to Salesforce documentation on grounding AI-generated content and email personalization strategies.
정답:
Explanation:
Universal Containers can achieve the request to explore similar opportunities by using the standard Copilot action. Agent has built-in actions to handle natural language queries, such as “Show me other opportunities like this one.” The standard action will process the query and return results based on predefined matching criteria like opportunity details and past Closed Won deals.
This approach avoids the need to create custom flows or Apex classes, leveraging out-of-the-box functionality.
For further details, refer to Agent for Sales documentation regarding standard actions and natural language processing.