Features of Salesforce AI-201 Desktop and Web-based Practice Exams
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Salesforce Certified Agentforce Specialist Sample Questions (Q109-Q114):
NEW QUESTION # 109
An Agentforce configured Data Masking within the Einstein Trust Layer. How should the Agentforce Specialist begin validating that the correct fields are being masked?
- A. Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger.
- B. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.
- C. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
Answer: B
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.
NEW QUESTION # 110
Universal Containers (UC) recently rolled out Einstein Generative AI capabilities and has created a custom prompt to summarize case records. Users have reported that the case summaries generated are not returning the appropriate information. What is a possible explanation for the poor prompt performance?
- A. The data being used for grounding is incorrect or incomplete.
- B. The Einstein Trust Layer is incorrectly configured.
- C. The prompt template version is incompatible with the chosen LLM.
Answer: A
Explanation:
UC's custom prompt for summarizing case records is underperforming, and we need to identify a likely cause.
NEW QUESTION # 111
Universal Containers built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors. What is the cause of the random nature of this error?
- A. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.
- B. The number of tokens that can be processed by the LLM varies with total user demand.
- C. The number of tokens generated by the dynamic nature of the prompt template will vary by record.
Answer: C
Explanation:
In Salesforce Agentforce, prompt templates are used to generate dynamic responses or field values by leveraging an LLM, often with grounding data from Salesforce records or external sources. The scenario describes a Field Generation prompt template that fails intermittently with token limit errors, indicating that the issue is tied to exceeding the LLM's token capacity (e.g., input + output tokens). The random nature of these failures suggests variability in the token count across different records, which is directly addressed by Option B.
Prompt templates in Agentforce can be dynamic, meaning they pull in record-specific data (e.g., customer names, descriptions, or other fields) to generate output. Since the data varies by record-some records might have short text fields while others have lengthy ones-the total number of tokens (words, characters, or subword units processed by the LLM) fluctuates. When the token count exceeds the LLM's limit (e.g., 4,096 tokens for some models), the process fails, but this only happens for records with higher token-generating data, explaining the randomness.
NEW QUESTION # 112
Universal Containers (UC) is creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements. Which prompt template type should UC use and which consideration should UC review?
- A. Flex, and that Dynamic Fields is enabled
- B. Field Generation, and that Dynamic Forms is enabled
- C. Field Generation, and that Dynamic Fields is enabled
Answer: C
Explanation:
Salesforce Agentforce provides various prompt template types to support AI-driven tasks, such as generating text or populating fields. In this case, UC needs a custom prompt template to populate a field with generated output, which directly aligns with the Field Generation prompt template type. This type is designed to use generative AI to create field values (e.g., summaries, descriptions) based on input data or prompts, making it the ideal choice for UC's requirement.
Additionally, UC has enabled the Einstein Trust Layer, a governance framework that ensures AI outputs are safe, explainable, and auditable, capturing AI Audit data for monitoring adoption and identifying improvement areas.
The consideration UC should review is whether Dynamic Fields is enabled. Dynamic Fields allow the prompt template to incorporate variable data from Salesforce records (e.g., case details, customer info) into the prompt, ensuring the generated output is contextually relevant to each record. This is critical for field population tasks, as static prompts wouldn't adapt to record-specific needs. The Einstein Trust Layer further benefits from this, as it can track how dynamic inputs influence outputs for audit purposes.
NEW QUESTION # 113
Universal Containers has a new AI project. What should An Agentforce consider when adding a related list on the Account object to be used in the prompt template?
- A. The fields for the related list are based on the default page layout of the Account for the current user.
- B. Prompt Builder must be used to assign the fields from the related list as a JSON format.
- C. After selecting a related list from the Account, use the field picker to choose merge fields in Prompt Builder.
Answer: C
Explanation:
Universal Containers (UC) wants to include details from a related list on the Account object in a prompt template. This is typically done via Prompt Builder in Salesforce's generative AI setup.
Prompt Builder Behavior
Selecting a Related List: Within Prompt Builder, you can navigate to the object (Account) and choose which related list (e.g., Contacts, Opportunities) you want to reference.
Field Picker: Once a related list is chosen, Prompt Builder provides a field picker interface, allowing you to select specific fields from that related list. These fields then become available for merge fields or dynamic insertion within your prompt.
NEW QUESTION # 114
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