Based on the user utterance, 'Show me all the customers in New York', which standard Agent action will the planner service use?
Correct Answer:
A
Why is Query Records the Correct Answer?
In Agentforce, the Planner Service is responsible for interpreting user requests and selecting the appropriate Copilot Action to fulfill them. When a user issues a command like:"Show me all the customers in New York",the system must retrieve a list of customers filtered by location.
The Query Records action is designed precisely for this purpose.
Key Features of Query Records in Agentforce:
✑ Retrieves Data Based on Specific Field Values
✑ Works with Large Language Models (LLMs) and Copilot Actions
✑ Optimized for Structured Data Retrieval
Why Not the Other Options?
* B. Fetch Records
✑ This is not a standard term in Einstein Copilot or Agentforce.
✑ No defined Agentforce action exists under this name.
* C. Select Records
✑ Select Records is used to pick records from an already presented list, not to retrieve them initially.
✑ If the user had already retrieved records and wanted to refine their selection, Select Records might be appropriate.
✑ However, since the user's request is to retrieve records, Query Records is the correct action.
Agentforce Specialist References
This information is confirmed from the Salesforce AI Specialist Material and Questions Document, where the Query Records action is explicitly defined as the appropriate standard action for retrieving filtered CRM records.
Universal Containers wants to use an external large language model (LLM) in Prompt Builder.
What should An Agentforce recommend?
Correct Answer:
B
Bring Your Own Large Language Model (BYO-LLM) functionality in Einstein Studio allows organizations to integrate and use external large language models (LLMs) within the Salesforce ecosystem. Universal Containers can leverage this feature to connect and ground prompts with external LLMs, allowing for custom AI model use cases and seamless integration with Salesforce data.
✑ Option B is the correct choice as Einstein Studio provides a built-in feature to work
with external models.
✑ Option A suggests using Apex, but BYO-LLM functionality offers a more streamlined solution.
✑ Option C focuses on Flow and External Services, which is more about data
integration and isn't ideal for working with LLMs.
References:
Salesforce Einstein Studio BYO-LLM Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_studio_llm.htm
After configuring and saving a Salesforce Agentforce Data Library (regardless of the data source), which components are automatically created and available in Data Cloud?
Correct Answer:
C
Why is "A data stream, a search index, and a retriever" the correct answer? When a Salesforce Agentforce Data Library is configured and saved, it automatically creates three essential components in Data Cloud to facilitate AI-driven search and retrieval.
Key Components Created in Data Cloud:
✑ Data Stream
✑ Search Index
✑ Retriever
Why Not the Other Options?
* A. A data pipeline, an indexing engine, and a query processor
✑ Incorrect because Data Cloud does not use a query processor in the same way as traditional databases.
✑ Instead, retrievers handle AI-powered data searches.
* B. A data connector, an analytics dashboard, and a workflow rule
✑ Incorrect because these components are not automatically created when setting up a Data Library.
✑ Analytics dashboards and workflow rules are separate tools used for reporting and automation.
Agentforce Specialist References
✑ Salesforce AI Specialist Material confirms that a Data Stream, Search Index, and Retriever are created automatically in Data Cloud when configuring a Data Library.
Northern Trail Outfitters (NTO) wants to configure Einstein Trust Layer in its production org but is unable to see the option on the Setup page.
After provisioning Data Cloud, which step must an Al Specialist take to make this option available to NTO?
Correct Answer:
B
For Northern Trail Outfitters (NTO) to configure the Einstein Trust Layer, the Einstein Generative AI feature must be enabled. The Einstein Trust Layer is closely tied to generative AI capabilities, ensuring that AI-generated content complies with data privacy, security, and trust standards.
✑ Option A (Turning on Agent) is unrelated to the setup of the Einstein Trust Layer,
which focuses more on generative AI interactions and data handling.
✑ Option C (Turning on Prompt Builder) is used for configuring and building AI-driven prompts, but it does not enable the Einstein Trust Layer.
Salesforce Agentforce Specialist References:For more details on the Einstein Trust Layer and setup steps: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_overview.htm
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?
Correct Answer:
C
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
✑ Incorrect data source connection
✑ Parsing Issues with PDF Files
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.
