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| Topic | Details |
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| Topic 1 | - Multi-Agent Interoperability: This domain explains Model Context Protocol (MCP), agent-to-agent communication, and when to use Agent API for system interactions.
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| Topic 2 | - AI Agents: This domain covers configuring agent behavior, understanding the reasoning engine, selecting topics and actions for agent types, managing Agent User security, choosing appropriate agent types, and connecting agents to various channels.
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| Topic 3 | - Prompt Engineering: This section focuses on using Prompt Builder, managing user roles, creating prompt templates with field generation and flex types, selecting grounding techniques, and applying best practices for effective prompts.
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| Topic 4 | - Data Cloud for Agentforce: This domain covers Agentforce Data Library types, improving responses with unstructured data through chunking and indexing, understanding retrievers, and selecting keyword, vector, or hybrid search types.
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| Topic 5 | - Development Lifecycle: This area addresses testing agents in Testing Center, deploying from sandbox to production, and managing agent adoption and monitoring.
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Salesforce Certified Agentforce Specialist (AI-201) Sample Questions (Q33-Q38):
NEW QUESTION # 33
Universal Containers (UC) has a new AI project.
What should UC consider when adding a related list on the Account page to be used in the prompt template?
- A. After selecting a related list from the Account, use the field picker to choose merge fields in Prompt Builder.
- B. Prompt Builder must be used to assign the fields from the related list as a JSON format.
- C. The fields for the related list are based on the default page layout of the Account for the current user.
Answer: C
Explanation:
The correct answer is C. Salesforce documentation states that when a prompt template is grounded with a related list, the fields available for that related list are based on the page layout of the parent object for the current user. That means the Account page layout controls which related-list fields are exposed for prompt grounding. Option A is wrong because Prompt Builder does not require assigning related-list fields in JSON format. Option B sounds plausible because field selection is involved in Prompt Builder workflows, but it misses the key limitation being tested: related-list field availability is driven by the current user's parent- object page layout. For exam purposes, the controlling consideration is the page layout dependency, not manual JSON formatting or generic field-picker behavior.
NEW QUESTION # 34
An Agentforce Specialist is creating a prompt template to assist support reps in drafting responses to customer complaints.
To ensure the responses are empathetic and helpful, what is a key element to include in the prompt template?
- A. A direct instruction to the large language model (LLM) to role-play as a character
- B. A list of keywords related to customer complaints
- C. The entire history of the customer's previous interactions with the company
Answer: A
Explanation:
The Prompt Builder Best Practices Guide emphasizes including a role instruction in prompts to set tone and communication style. The document explains: "Role-playing instructions (e.g., 'You are an empathetic customer support agent') are a best practice for ensuring the LLM adopts the desired persona, tone, and style in responses." Option A directly reflects this principle by instructing the LLM to role-play as a character, resulting in empathetic, customer-centric responses.
Option B (listing keywords) provides no tone or intent guidance.
Option C (including full interaction history) risks token overload and redundancy, which can degrade prompt performance.
Thus, Option A aligns with Salesforce's prompt design best practices for tone and empathy.
References (AgentForce Documents / Study Guide):
Salesforce Prompt Builder Design Guide: "Using Role Instructions for Empathy and Tone" AgentForce Prompt Engineering Handbook: "Persona and Context in Prompts" AgentForce Study Guide: "Creating Effective Prompts for Customer-Facing Use Cases"
NEW QUESTION # 35
Universal Containers (UC) uses a file upload-based data library and custom prompt to support AI-driven training content. However, users report that the AI frequently returns outdated documents. Which corrective action should UC implement to improve content relevancy?
- A. Configure a custom retriever that includes a filter condition limiting retrieval to documents updated within a defined recent period, ensuring that only current content is used for AI responses.
- B. Switch the data library source from file uploads to a Knowledge-based data library, because Salesforce Knowledge bases automatically manage document recency, ensuring current documents are returned.
- C. Continue using the default retriever without filters, because periodic re-uploads will eventually phase out outdated documents without further configuration or the need for custom retrievers.
Answer: A
Explanation:
UC's issue is that their file upload-based Data Library (where PDFs or documents are uploaded and indexed into Data Cloud's vector database) is returning outdated training content in AI responses. To improve relevancy by ensuring only current documents are retrieved, the most effective solution is to configure a custom retriever with a filter (Option B). In Agentforce, a custom retriever allows UC to define specific conditions-such as a filter on a "Last Modified Date" or similar timestamp field-to limit retrieval to documents updated within a recent period (e.g., last 6 months). This ensures the AI grounds its responses in the most current content, directly addressing the problem of outdated documents without requiring a complete overhaul of the data source.
Option A: Switching to a Knowledge-based Data Library (using Salesforce Knowledge articles) could work, as Knowledge articles have versioning and expiration features to manage recency. However, this assumes UC' s training content is already in Knowledge articles (not PDFs) and requires migrating all uploaded files, which is a significant shift not justified by the question's context. File-based libraries are still viable with proper filtering.
Option B: This is the best corrective action. A custom retriever with a date filter leverages the existing file- based library, refining retrieval without changing the data source, making it practical and targeted.
Option C: Relying on periodic re-uploads with the default retriever is passive and inefficient. It doesn't guarantee recency (old files remain indexed until manually removed) and requires ongoing manual effort, failing to proactively solve the issue.
Option B provides a precise, scalable solution to ensure content relevancy in UC's AI-driven training system.
Salesforce Agentforce Documentation: "Custom Retrievers for Data Libraries" (Salesforce Help: https://help.
salesforce.com/s/articleView?id=sf.agentforce_custom_retrievers.htm&type=5) Salesforce Data Cloud Documentation: "Filter Retrieval for AI" (https://help.salesforce.com/s/articleView?
id=sf.data_cloud_retrieval_filters.htm&type=5)
Trailhead: "Manage Data Libraries in Agentforce" (https://trailhead.salesforce.com/content/learn/modules
/agentforce-data-libraries)
NEW QUESTION # 36
Universal Containers (UC) has configured a data library and wants to restrict indexing of knowledge articles to articles which are only publicly available in their knowledge base, UC also wants the agent to link sources that the large language model (LLM) grounded its response on.
Which settings should help UC with this?
- A. In the data library setting window, under Knowledge Settings, enable Use Public Knowledge Article and select Show sources,
- B. Use Data Categories to categorize publicly available articles to index. Sources are automatically displayed when knowledge articles are categorized as Public.
- C. In the data library setting window, under Knowledge Settings, enable Use Public Knowledge Article. It is not possible to display articles that the LLM grounded its response in.
Answer: A
Explanation:
According to the AgentForce Data Library Configuration Guide, administrators can restrict indexing and retrieval of Knowledge articles to publicly available ones and enable source visibility for LLM-grounded responses. The documentation states:
"Within the data library settings, under Knowledge Settings, enable 'Use Public Knowledge Articles' to ensure only publicly visible content is indexed. To display citations, enable 'Show Sources' so the agent links the specific articles or data records used to ground its response." Option A correctly reflects these two documented configuration steps.
Option B is incorrect because Salesforce explicitly supports source display for transparency through the
"Show Sources" setting.
Option C incorrectly assumes that Data Categories control indexing visibility and source linking, which is handled by explicit Knowledge Settings, not categorization.
References (AgentForce Documents / Study Guide):
* AgentForce Data Library Configuration Guide: "Knowledge Settings for Public Article Indexing"
* AgentForce Transparency and Source Attribution Notes: "Show Sources Option"
* AgentForce Study Guide: "Configuring Knowledge Visibility and Source Display"
NEW QUESTION # 37
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?
- A. Turn on Einstein Copilot.
- B. Turn on Einstein Generative AI.
- C. Turn on Prompt Builder.
Answer: B
Explanation:
For Northern Trail Outfitters (NTO) to configure theEinstein Trust Layer, theEinstein 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 Einstein Copilot) 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.
SalesforceAgentforce SpecialistReferences:For more details on the Einstein Trust Layer and setup steps:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_overview.htm
NEW QUESTION # 38
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