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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Einstein Trust Layer & Security | - Trust Layer & Security Features
| |
| Topic 2: Agent Force Concepts | 30% | - Data Cloud & Grounding Techniques
|
| Topic 3: Prompt Engineering | 30% | - Prompt Builder & Template Creation
|
| Topic 4: Reasoning Engine & AI Actions | - Workflow mastery
|
On a regular basis, we update the PDF version to improve the AI-201 Questions and accurately reflect any changes that have been made to the test content. We know that Salesforce Certified Agentforce Specialist (AI-201) certification exam costs can be high, with registration fees often running between $100 and $1000. We provide a free demo version of our product to ensure you are completely satisfied with our Salesforce Certification Exams preparation material. The purpose of this free demo is to help you make a well-informed decision.
NEW QUESTION # 128
The Agentforce Specialist of Northern Trail Outfitters reviewed the organization's data masking settings within the Configure Data Masking menu within Setup. Upon assessing all of the fields, a few additional fields were deemed sensitive and have been masked within Einstein's Trust Layer.
Which steps should the Agentforce Specialist take upon modifying the masked fields?
Answer: B
Explanation:
After modifying masked fields in Einstein's Trust Layer, the next important step is to test and confirm that the responses generated by prompts utilizing the newly masked data still meet quality standards. This ensures that masking sensitive information does not negatively impact the usefulness or accuracy of the AI-generated content. Thorough testing helps identify any issues in prompt performance that could arise due to masking, and adjustments can be made if needed.
NEW QUESTION # 129
Universal Containers (UC) has configured an Agentforce Data Library using Knowledge articles.
When testing in Agent Builder and the Experience Cloud site, the agent is not responding with grounded Knowledge article information. However, when tested in Prompt Builder, the response returns correctly. What should UC do to troubleshoot the issue?
Answer: A
Explanation:
UC has set up an Agentforce Data Library with Knowledge articles, and while Prompt Builder retrieves the data correctly, the agent fails to do so in Agent Builder and Experience Cloud.
NEW QUESTION # 130
Universal Containers (UC) implements a custom retriever to improve the accuracy of AI- generated responses. UC notices that the retriever is returning too many irrelevant results, making the responses less useful. What should UC do to ensure only relevant data is retrieved?
Answer: C
Explanation:
In Salesforce Agentforce, a custom retriever is used to fetch relevant data (e.g., from Data Cloud's vector database or Salesforce records) to ground AI responses. UC's issue is that their retriever returns too many irrelevant results, reducing response accuracy. The best solution is to define filters (Option A) to refine the retriever's search criteria. Filters allow UC to specify conditions (e.g., "only retrieve documents from the `Policy' category" or "records created after a certain date") that narrow the dataset, ensuring the retriever returns only relevant results. This directly improves the precision of AI-generated responses by excluding extraneous data, addressing UC's problem effectively.
NEW QUESTION # 131
Based on the user utterance, 'Show me all the customers in New York', which standard Agent action will the planner service use?
Answer: B
Explanation:
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
This action fetches Salesforce records that match a set of criteria, such as customers located in New York.
Uses standard or custom object fields (e.g., BillingState = 'New York').
Works with Large Language Models (LLMs) and Copilot Actions
When a user asks for filtered data, Query Records is the default action assigned by the Planner Service.
Optimized for Structured Data Retrieval
Ensures AI retrieves relevant CRM records quickly and accurately.
NEW QUESTION # 132
Universal Containers (UC) has a mature Salesforce org with a lot of data in cases and Knowledge articles. UC is concerned that there are many legacy fields, with data that might not be applicable for Einstein AI to draft accurate email responses. Which solution should UC use to ensure Einstein AI can draft responses from a defined data source?
Answer: A
Explanation:
Service AI Grounding is the solution that Universal Containers should use to ensure Einstein AI drafts responses based on a well-defined data source. Service AI Grounding allows the AI model to be anchored in specific, relevant data sources, ensuring that any AI-generated responses (e.g., email replies) are accurate, relevant, and drawn from up-to-date information, such as Knowledge articles or cases.
Given that UC has legacy fields and outdated data, Service AI Grounding ensures that only the valid and applicable data is used by Einstein AI to craft responses. This helps improve the relevance of responses and avoids inaccuracies caused by outdated or irrelevant fields.
Work Summaries and Service Replies are useful features but do not address the need for grounding AI outputs in specific, current data sources like Service AI Grounding does.
For more details, you can refer to Salesforce's Service AI Grounding documentation for managing AI-generated content based on accurate data sources.
NEW QUESTION # 133
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