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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic	Details
Topic 1	Agentforce Concepts: This section assesses the skills of AI Engineers and covers how Agentforce works, including its reasoning engine, standard and custom topics, agent actions, and user security management. It also includes testing and deploying agents from sandbox to production environments.
Topic 2	Agentforce and Data Cloud: This section measures the skills of AI Developers and addresses how Agentforce integrates with Data Cloud to improve response accuracy and personalize answers. It involves grounding with retrievers in Data Cloud to enhance agent performance.
Topic 3	Prompt Engineering: This section measures the skills of AI Developers and focuses on prompt engineering techniques. It covers identifying when to use Prompt Builder, managing prompt templates, selecting appropriate grounding techniques, and explaining the process for creating and executing prompt templates.
Topic 4	Agentforce and Sales Cloud: This section assesses the skills of AI Developers and covers identifying the correct generative AI features in Agentforce for Sales Cloud scenarios. It also includes determining when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches.
Topic 5	Agentforce and Service Cloud: This section measures the skills of AI Engineers and focuses on building agents that answer questions based on Knowledge articles and connecting them to digital channels. It also covers identifying the correct generative AI features in Agentforce for Service Cloud scenarios.

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Salesforce Certified Agentforce Specialist Sample Questions (Q45-Q50):

NEW QUESTION # 45
An Agentforce Specialist wants to troubleshoot their Agent's performance. Where should the Agentforce Specialist go to access all user interactions with the Agent, including Agent errors, incorrectly triggered actions, and incomplete plans?

A. Agent Settings
B. Event Logs
C. Plan Canvas

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:
The Agentforce Specialist needs a comprehensive view of user interactions, errors, and action issues for troubleshooting. Let's evaluate the options.
* Option A: Plan CanvasPlan Canvas in Agent Builder visualizes an agent's execution plan for a single interaction, useful for design but not for aggregated troubleshooting data like errors or all interactions, making it incorrect.
* Option B: Agent SettingsAgent Settings configure the agent (e.g., topics, channels), not provide interaction logs or error details. This is for setup, not analysis, making it incorrect.
* Option C: Event LogsEvent Logs in Agentforce (accessible via Setup or Agent Analytics) record all user interactions, including errors, incorrectly triggered actions, and incomplete plans. They provide detailed telemetry (e.g., timestamps, action outcomes) for troubleshooting performance issues, making this the correct answer.
Why Option C is Correct:
Event Logs offer the full scope of interaction data needed for troubleshooting, as per Salesforce documentation.
References:
Salesforce Agentforce Documentation: Agent Analytics > Event Logs- Details interaction and error logging.
Trailhead: Monitor and Optimize Agentforce Agents- Recommends Event Logs for troubleshooting.
Salesforce Help: Agentforce Performance- Confirms logs for diagnostics.

NEW QUESTION # 46
An Agentforce Specialist at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time, UC wants to help prep the sales team for calls by:
* Summarizing past purchases
* Displaying products the contact has shown interest in (with data captured via Data Cloud)
* Providing a recap of past email and phone conversations that have transcripts Which approach should the Agentforce Specialist recommend to achieve this goal?

A. Use a prompt template grounded on CRM and Data Cloud data using standard foundation models.
B. Fine-tune the standard foundational model due to the complexity of the data.
C. Deploy UC's own custom foundational model on this data first.

Answer: A

Explanation:
The AgentForce No-Code Builder and Prompt Template Guide specifies that when using Salesforce's standard foundation models, users can ground prompts on CRM and Data Cloud data without requiring fine-tuning or model deployment. The documentation notes: "No-code users can leverage standard foundation models with prompt templates grounded in Salesforce data, including CRM and Data Cloud, to summarize records, highlight insights, and prepare agents for customer engagements." This approach allows the sales operations team to automatically summarize customer data (purchases, interests, and communications) without needing model customization.
Option A (deploying a custom foundational model) requires data science expertise, not available in a no-code setup. Option B (fine-tuning) is unnecessary because standard models with grounding are optimized for contextual data use.
Thus, Option C aligns with Salesforce's recommended low-code/no-code configuration for contextual AI assistance.
References (AgentForce Documents / Study Guide):
* AgentForce Builder Guide: "No-Code Prompt Templates Grounded in CRM and Data Cloud"
* Salesforce Einstein Studio Overview: "Standard vs. Fine-Tuned Models"
* AgentForce Study Guide: "Empowering Sales Teams with Grounded Prompts"

NEW QUESTION # 47
An Agentforce Specialist is tasked with analyzing Agent interactions, looking into user inputs, requests, and queries to identify patterns and trends. What functionality allows the Agentforce Specialist to achieve this?

A. Agent Event Logs dashboard.
B. AI Audit and Feedback Data dashboard.
C. User Utterances dashboard.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:
The task requires analyzinguser inputs, requests, and queriesto identify patterns and trends in Agentforce interactions. Let's assess the options based on Agentforce's analytics capabilities.
* Option A: Agent Event Logs dashboard.Agent Event Logs capture detailed technical events (e.g., API calls, errors, or system-level actions) related to agent operations. While useful for troubleshooting or monitoring system performance, they are not designed to analyze user inputs or conversational trends. This option does not meet the requirement and is incorrect.
* Option B: AI Audit and Feedback Data dashboard.There's no specific "AI Audit and Feedback Data dashboard" in Agentforce documentation. Feedback mechanisms exist (e.g., user feedback on responses), and audit trails may track changes, but no single dashboard combines these for analyzing user queries and trends. This option appears to be a misnomer and is incorrect.
* Option C: User Utterances dashboard.The User Utterances dashboard in Agentforce Analytics is specifically designed to analyze user inputs, requests, and queries. It aggregates and visualizes what users are asking the agent, identifying patterns (e.g., common topics) and trends (e.g., rising query types). Specialists can use this to refine agent instructions or topics, making it the perfect tool for this task. This is the correct answer per Salesforce documentation.
Why Option C is Correct:
The User Utterances dashboard is tailored for conversational analysis, offering insights into user interactions that align with the specialist's goal of identifying patterns and trends. It's a documented feature of Agentforce Analytics for post-deployment optimization.
References:
Salesforce Agentforce Documentation: Agent Analytics > User Utterances Dashboard- Describes its use for analyzing user queries.
Trailhead: Monitor and Optimize Agentforce Agents- Highlights the dashboard's role in trend identification.
Salesforce Help: Agentforce Dashboards- Confirms User Utterances as a key tool for interaction analysis.

NEW QUESTION # 48
Universal Containers wants to reduce overall customer support handling time by minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields. Which combination of Agentforce for Service features enables this effort?

A. Einstein Reply Recommendations and Case Summaries
B. Einstein Service Replies and Work Summaries
C. Einstein Reply Recommendations and Case Classification

Answer: A

Explanation:
Universal Containers (UC) aims to streamline customer support by addressing two goals: reducing in-chat typing time for routine answers and minimizing post-chat analysis by auto-suggesting case field values. In Salesforce Agentforce for Service, Einstein Reply Recommendations and Case Classification (Option A) are the ideal combination to achieve this.
Einstein Reply Recommendations: This feature uses AI to suggest pre-formulated responses based on chat context, historical data, and Knowledge articles. By providing agents with ready-to-use replies for common questions, it significantly reduces the time spent typing routine answers, directly addressing UC's first goal.
Case Classification: This capability leverages AI to analyze case details (e.g., chat transcripts) and suggest values for case fields (e.g., Subject, Priority, Resolution) during or after the interaction. By automating field population, it reduces post-chat analysis time, fulfilling UC's second goal.
Option B: While "Einstein Reply Recommendations" is correct for the first part, "Case Summaries" generates a summary of the case rather than suggesting specific field values. Summaries are useful for documentation but don't directly reduce post-chat field entry time.
Option C: "Einstein Service Replies" is not a distinct, documented feature in Agentforce (possibly a distractor for Reply Recommendations), and "Work Summaries" applies more to summarizing work orders or broader tasks, not case field suggestions in a chat context.
Option A: This combination precisely targets both in-chat efficiency (Reply Recommendations) and post-chat automation (Case Classification).
Thus, Option A is the correct answer for UC's needs.
Salesforce Agentforce Documentation: "Einstein Reply Recommendations" (Salesforce Help: https://help.
salesforce.com/s/articleView?id=sf.einstein_reply_recommendations.htm&type=5) Salesforce Agentforce Documentation: "Case Classification" (Salesforce Help: https://help.salesforce.com/s
/articleView?id=sf.case_classification.htm&type=5)
Trailhead: "Agentforce for Service" (https://trailhead.salesforce.com/content/learn/modules/agentforce-for- service)

NEW QUESTION # 49
Universal Containers has implemented an agent that answers questions based on Knowledge articles. Which topic and Agent Action will be shown in the Agent Builder?

A. General Q&A topic and Knowledge Article Answers action.
B. General FAQ topic and Answers Questions with Knowledge Action.
C. General CRM topic and Answers Questions with LLM Action.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:
UC's agent answers questions using Knowledge articles, configured in Agent Builder. Let's identify the topic and action.
* Option A: General Q&A topic and Knowledge Article Answers action."General Q&A" is not a standard topic name in Agentforce, and "Knowledge Article Answers" isn't a predefined action. This lacks specificity and doesn't match documentation, making it incorrect.
* Option B: General CRM topic and Answers Questions with LLM Action."General CRM" isn't a default topic, and "Answers Questions with LLM" suggests raw LLM responses, not Knowledge- grounded ones. This doesn't align with the Knowledge focus, making it incorrect.
* Option C: General FAQ topic and Answers Questions with Knowledge Action.In Agent Builder, the "General FAQ" topic is a common default or starting point for question-answering agents. The
"Answers Questions with Knowledge" action (sometimes styled as "Answer with Knowledge") is a prebuilt action that retrieves and grounds responses with Knowledge articles. This matches UC's implementation and is explicitly supported in documentation, making it the correct answer.
Why Option C is Correct:
"General FAQ" and "Answers Questions with Knowledge" are the standard topic-action pair for Knowledge- based question answering in Agentforce, per Salesforce resources.
References:
Salesforce Agentforce Documentation: Agent Builder > Actions- Lists "Answers Questions with Knowledge." Trailhead: Build Agents with Agentforce- Describes FAQ topics with Knowledge actions.
Salesforce Help: Knowledge in Agentforce- Confirms this configuration.

NEW QUESTION # 50
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