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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic
Details

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.

Topic 2

Development Lifecycle: This area addresses testing agents in Testing Center, deploying from sandbox to production, and managing agent adoption and monitoring.

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.

Topic 4

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.

Topic 5

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.

Salesforce Certified Agentforce Specialist (AI-201) Sample Questions (Q343-Q348):

NEW QUESTION # 343
Universal Containers (UC) currently tracks Leads with a custom object. UC is preparing to implement the Sales Development Representative (SDR) Agent. Which consideration should UC keep in mind?

A. Agentforce SDR only supports custom objects associated with Accounts.
B. Agentforce SDR only works on Opportunities.
C. Agentforce SDR only works with the standard Lead object.

Answer: C

Explanation:
Universal Containers (UC) uses a custom object for Leads and plans to implement the Agentforce Sales Development Representative (SDR) Agent. The SDR Agent is a prebuilt, configurable AI agent designed to assist sales teams by qualifying leads and scheduling meetings. Let's evaluate the options based on its functionality and limitations.
* Option A: Agentforce SDR only works with the standard Lead object.Per Salesforce documentation, the Agentforce SDR Agent is specifically designed to interact with the standard Lead object in Salesforce. It includes preconfigured logic to qualify leads, update lead statuses, and schedule meetings, all of which rely on standard Lead fields (e.g., Lead Status, Email, Phone). Since UC tracks leads in a custom object, this is a critical consideration-they would need to migrate data to the standard Lead object or create a workaround (e.g., mapping custom object data to Leads) to leverage the SDR Agent effectively. This limitation is accurate and aligns with the SDR Agent's out-of-the-box capabilities.
* Option B: Agentforce SDR only works on Opportunities.The SDR Agent's primary focus is lead qualification and initial engagement, not opportunity management. Opportunities are handled by other roles (e.g., Account Executives) and potentially other Agentforce agents (e.g., Sales Agent), not the SDR Agent. This option is incorrect, as it misaligns with the SDR Agent's purpose.
* Option C: Agentforce SDR only supports custom objects associated with Accounts.There's no evidence in Salesforce documentation that the SDR Agent supports custom objects, even those related to Accounts. The SDR Agent is tightly coupled with the standard Lead object and does not natively extend to custom objects, regardless of their relationships. This option is incorrect.
Why Option A is Correct:
The Agentforce SDR Agent's reliance on the standard Lead object is a documented constraint. UC must consider this when planning implementation, potentially requiring data migration or process adjustments to align their custom object with the SDR Agent's capabilities. This ensures the agent can perform its intended functions, such as lead qualification and meeting scheduling.
References:
Salesforce Agentforce Documentation: SDR Agent Setup - Specifies the SDR Agent's dependency on the standard Lead object.
Trailhead: Explore Agentforce Sales Agents - Describes SDR Agent functionality tied to Leads.
Salesforce Help: Agentforce Prebuilt Agents - Confirms Lead object requirement for SDR Agent.

NEW QUESTION # 344
What is the main purpose of Prompt Builder?

A. A tool for developers to use in Visual Studio Code that creates prompts for Apex programming, assisting developers in writing code more efficiently.
B. A tool that enables companies to create reusable prompts for large language models (LLMs), bringing generative AI responses to their flow of work
C. A tool within Salesforce offering real-time Al-powered suggestions and guidance to users, Improving productivity and decision-making.

Answer: B

Explanation:
Prompt Builder is designed to help organizations create and configure reusable prompts for large language models (LLMs). By integrating generative AI responses into workflows, Prompt Builder enables customization of AI prompts that interact with Salesforce data and automate complex processes. This tool is especially useful for creating tailored and consistent AI-generated content in various business contexts, including customer service and sales.
It is not a tool for Apex programming (as in option A).
It is also not limited to real-time suggestions as mentioned in option C. Instead, it provides a flexible way for companies to manage and customize how AI-driven responses are generated and used in their workflows.
Salesforce Prompt Builder Overview: https://help.salesforce.com/s/articleView?id=sf.prompt_builder.htm

NEW QUESTION # 345
Cloud Kicks uses a third-party agent for research and an Agentforce agent for customer service.
Which purpose-built protocol allows cross-vendor agents to communicate?

A. Model Context Protocol (MCP)
B. Agent-to-Agent (A2A)
C. Application Programming Interface (API)

Answer: B

Explanation:
The correct answer is C because Agent-to-Agent, or A2A, is the purpose-built protocol for communication and collaboration between AI agents across different vendors and platforms. In this scenario, Cloud Kicks has a third-party research agent and an Agentforce customer service agent. The requirement is direct cross-vendor agent communication, not just access to a tool or external endpoint. MCP is mainly used to connect agents with tools, resources, and external context. A generic API can integrate systems, but it is not the agent- interoperability protocol being tested here. Salesforce describes A2A as an open standard that allows AI agents from different platforms to securely communicate, collaborate, share context, and coordinate work.

NEW QUESTION # 346
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process.
How should An Agentforce apply the power of conversational AI to this use case?

A. Configure the Integration Flow Standard Action in Agent.
B. Create a custom copilot action which calls a flow.
C. Create a Flex prompt template in Prompt Builder.

Answer: B

Explanation:
To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Agent to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
* Option B is correct because it enables integration between Agent and the flow that connects to Oracle ERP.
* Option A (Flex prompt template) is more suited for static responses and not for invoking flows.
* Option C (Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.
References:
* Salesforce Agent Actions: https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm

NEW QUESTION # 347
An Agentforce at Universal Containers is trying to set up a new Field Generation prompt template. They take the following steps.
1. Create a new Field Generation prompt template.
2. Choose Case as the object type.
3. Select the custom field AI_Analysis_c as the target field.
After creating the prompt template, the Agentforce Specialist saves, tests, and activates it. Howsoever, when they go to a case record, the AI Analysis field does not show the (Sparkle) icon on the Edit pencil. When the Agentforce Specialist was editing the field, it was behaving as a normal field.
Which critical step did the Agentforce Specialist miss?

A. They forgot that the Case Object is not supported for Add generation as Feinstein Service Replies should be used instead.
B. They forgot to reactivate the Lightning page layout for the Case object after activating their Field Generation prompt template.
C. They forgot to edit the Lightning page layout and associate the field to a prompt template

Answer: C

Explanation:
For Field Generation prompt templates to display the Sparkle icon (indicating AI-generated content), the target field must be explicitly associated with the prompt template on the Lightning page layout. Even if the prompt template is activated, failing to add the field to the page layout and link it to the template will result in the field behaving as a standard field. Salesforce documentation emphasizes that page layout configuration is mandatory to enable AI-driven field interactions.
* Reactivating the layout (A) is unnecessary unless the layout itself was modified after activation.
* Case objects are supported for Field Generation (B is incorrect).
Reference:
Salesforce Help Article: Configure Field Generation Prompt Templates ("Associating Fields with Page Layouts" section).
Einstein GPT Implementation Guide: "Enabling AI-Generated Fields in Lightning Pages."

NEW QUESTION # 348
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