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| Section | Weight | Objectives |
|---|---|---|
| AI Agents | 35% | - Security and governance
|
| Data and AI Governance | 20% | - Ethics and compliance
|
| Testing, Deployment, and Operations | 20% | - Monitoring
|
| Prompt Engineering | 25% | - Grounding and best practices
|
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질문 # 23
Universal Containers would like to route SMS text messages to a service rep from an Agentforce Service Agent. Which Service Channel should the company use in the flow to ensure it's routed properly?
정답：A
설명：
UC wants to route SMS text messages from an Agentforce Service Agent to a service rep using a flow. Let's identify the correct Service Channel.
Option A: MessagingIn Salesforce, the "Messaging" Service Channel (part of Messaging for In-App and Web or SMS) handles text-based interactions, including SMS. When integrated with Omni-Channel Flow, the
"Route Work" action uses this channel to route SMS messages to agents. This aligns with UC's requirement for SMS routing, making it the correct answer.
Option B: Route Work Action"Route Work" is an action in Omni-Channel Flow, not a Service Channel. It uses a channel (e.g., Messaging) to route work, so this is a component, not the channel itself, making it incorrect.
Option C: Live Agent"Live Agent" refers to an older chat feature, not the current Messaging framework for SMS. It's outdated and unrelated to SMS routing, making it incorrect.
Option D: SMS ChannelThere's no standalone "SMS Channel" in Salesforce Service Channels-SMS is encompassed within the "Messaging" channel. This is a misnomer, making it incorrect.
Why Option A is Correct:
The "Messaging" Service Channel supports SMS routing in Omni-Channel Flow, ensuring proper handoff from the Agentforce Service Agent to a rep, per Salesforce documentation.
References:
Salesforce Agentforce Documentation: Omni-Channel Integration > Messaging - Details SMS in Messaging channel.
Trailhead: Omni-Channel Flow Basics - Confirms Messaging for SMS.
Salesforce Help: Service Channels - Lists Messaging for text-based routing.
질문 # 24
Universal Containers (UC) needs to capture and store detailed interaction data for all agents.
Which feature should help UC get a full view of the agent's behavior from start to finish, including reasoning engine executions, actions, prompt and gateway inputs/outputs, error messages, and final responses?
정답：B
설명：
The AgentForce Observability and Diagnostics Guide details that AgentForce Session Tracing provides the most comprehensive visibility into agent operations. The documentation explains: "Session Tracing captures the entire execution flow for each agent session - including reasoning engine decisions, executed actions, prompts, gateway inputs and outputs, error logs, and final agent responses - to provide an end-to-end view of agent behavior." Agentforce Analytics (Option A) focuses on aggregated performance metrics like usage, engagement, and accuracy trends rather than deep operational data.
Utterance Analysis (Option B) evaluates specific interactions or conversation snippets but does not include reasoning engine or system-level traces.
Hence, Option C - AgentForce Session Tracing - is correct as it provides detailed, end-to-end diagnostic insight across all agent executions.
References (AgentForce Documents / Study Guide):
AgentForce Observability Guide: "Using Session Tracing for End-to-End Agent Visibility" AgentForce Implementation Handbook: "Tracing Reasoning and Action Flows" AgentForce Study Guide: "Monitoring and Debugging with Session Tracing"
질문 # 25
An Agentforce Agent has been developed with multiple topics and Agent Actions that use flows and Apex.
Which options are available for deploying these to production?
정답：C
설명：
Why is "Deploy flows, Apex, and all agent-related items using either change sets or the Salesforce CLI
/Metadata API" the correct answer?
When deploying an Agentforce Agent with multiple topics and Agent Actions that use flows and Apex, a complete deployment solution is required. Change sets and the Salesforce CLI/Metadata API support the deployment of flows, Apex code, and agent-related metadata.
Key Considerations for Agentforce Deployments:
* Supports Deployment of All Required Components
* Agentforce Agents include flows, Apex classes, topics, and agent actions.
* Change sets and Salesforce CLI/Metadata API allow deployment of all these components together, ensuring a smooth transition to production.
* Agentforce Metadata Can Be Deployed Using Standard Tools
* Change Sets: Allows admins to move configurations, custom objects, and metadata between Salesforce environments.
* Salesforce CLI/Metadata API: Enables scripted deployments, automating the transfer of Agentforce configurations.
* Ensures a Complete Migration Without Manual Configuration
* Deploying all components together reduces the risk of misconfiguration.
* Automating deployments using the Metadata API ensures consistency across environments.
Why Not the Other Options?
# A. Deploy the flows and Apex using normal deployment tools and manually create the agent-related items in production.
* Incorrect because manually creating agent-related items in production introduces risk and inconsistency.
* This approach is error-prone and time-consuming, especially for large Agentforce deployments.
# B. Use only change sets because the Salesforce CLI does not currently support the deployment of agent-related metadata.
* Incorrect because Salesforce CLI and Metadata API fully support Agentforce deployments.
* Change sets are useful but limited in large-scale, automated deployments.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that Agentforce metadata (flows, actions, and topics) can be deployed using Change Sets or the Metadata API.
질문 # 26
Universal Containers (UC) wants to implement an AI-powered customer service agent that can:
* Retrieve proprietary policy documents that are stored as PDFs.
* Ensure responses are grounded in approved company data, not generic LLM knowledge.What should UC do first?
정답：B
설명：
Comprehensive and Detailed In-Depth Explanation:To implement an AI-powered customer service agent that retrieves proprietary policy documents (stored as PDFs) and ensures responses are grounded in approved company data, UC must first establish a foundation for the AI to access and use this data. TheAgentforce Data Library(Option A) is the correct starting point. A Data Library allows UC to upload PDFs containing policy documents, index them into Salesforce Data Cloud's vector database, and make them available for AI retrieval. This setup ensures the agent can perform Retrieval-Augmented Generation (RAG), grounding its responses in the specific, approved content from the PDFs rather than relying on generic LLM knowledge, directly meeting UC's requirements.
* Option B: Expanding the AI agent's scope to search all Salesforce records is too broad and unnecessary at this stage. The requirement focuses on PDFs with policy documents, not all Salesforce data (e.g., cases, accounts), making this premature and irrelevant as a first step.
* Option C: "Add the files to the content, and then select the data library option" is vague and not a precise process in Agentforce. While uploading files is part of setting up a Data Library, the phrasing suggests adding files to Salesforce Content (e.g., ContentDocument) without indexing, which doesn't enable AI retrieval. Setting up the Data Library (A) encompasses the full process correctly.
* Option A: This is the foundational step-creating a Data Library ensures the PDFs are uploaded, indexed, and retrievable by the agent, fulfilling both retrieval and grounding needs.
Option A is the correct first step for UC to achieve its goals.
References:
* Salesforce Agentforce Documentation: "Set Up a Data Library" (Salesforce Help:https://help.salesforce.
com/s/articleView?id=sf.agentforce_data_library.htm&type=5)
* Salesforce Data Cloud Documentation: "Ground AI Responses with Data Cloud" (https://help.
salesforce.com/s/articleView?id=sf.data_cloud_agentforce.htm&type=5)
질문 # 27
Coral Cloud Resorts wants visibility into credit usage associated with testing.
Which feature supports this?
정답：C
설명：
The AgentForce Testing Center Guide specifies that all testing activity-including prompt tests, structured batch runs, and evaluation sessions-consumes AI credits, which can be monitored directly through the Testing Center interface. The documentation states: "Testing Center provides visibility into testing performance, outcomes, and credit usage. Administrators can view test credit consumption metrics to understand resource utilization across agents and environments." Agentforce Analytics (Option A) provides insights into performance, engagement, and operational metrics but does not directly track credit consumption tied to testing. Digital Wallet (Option B) manages AI credit balances across orgs but does not offer test-specific tracking. Therefore, Testing Center is the correct answer since it explicitly supports monitoring credit usage during agent testing activities.
References (AgentForce Documents / Study Guide):
* AgentForce Testing Center Guide: "Monitoring Credit Consumption During Testing"
* AgentForce Admin Handbook: "Tracking Usage and Test Costs"
* AgentForce Study Guide: "Testing Resource Visibility and Credit Management"
질문 # 28
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우리 Itcertkr 에는 최신의Salesforce Agentforce-Specialist학습가이드가 있습니다. Itcertkr의 부지런한 IT전문가들이 자기만의 지식과 끊임없는 노력과 경험으로 최고의Salesforce Agentforce-Specialist합습자료로Salesforce Agentforce-Specialist인증시험을 응시하실 수 있습니다.Salesforce Agentforce-Specialist인증시험은 IT업계에서의 비중은 아주 큽니다. 시험신청하시는분들도 많아지고 또 많은 분들이 우리Itcertkr의Salesforce Agentforce-Specialist자료로 시험을 패스했습니다. 이미 패스한 분들의 리뷰로 우리Itcertkr의 제품의 중요함과 정확함을 증명하였습니다.
Agentforce-Specialist최신 업데이트버전 시험자료: https://www.itcertkr.com/Agentforce-Specialist_exam.html
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