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Salesforce Agentforce-Specialist Exam Syllabus Topics:
Topic
Details
Topic 1
- 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 2
- 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 3
- 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.
Topic 4
- 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 5
- 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.
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Salesforce Certified Agentforce Specialist Sample Questions (Q142-Q147):
NEW QUESTION # 142
Universal Containers (UC) wants to enable its sales team with automatic post-call visibility into mention of competitors, products, and other custom phrases.
Which feature should theAgentforce Specialistset up to enable UC's sales team?
- A. Call Insights
- B. Call Summaries
- C. Call Explorer
Answer: A
Explanation:
To enable Universal Containers' sales team with automatic post-call visibility into mentions ofcompetitors, products, and custom phrases, theAgentforce Specialistshould set upCall Insights.Call Insightsanalyzes voice and video calls for key phrases, topics, and mentions, providing insights into critical aspects of the conversation. This feature automatically surfaces key details such as competitor mentions, product discussions, and custom phrases specified by the sales team.
* Call Summariesprovide a general overview of the call but do not specifically highlight keywords or topics.
* Call Exploreris a tool for navigating through call data but does not focus on automatic insights.
For more information, refer toSalesforce's Call Insights documentationregarding the analysis of call content and extracting actionable information.
NEW QUESTION # 143
Amid their busy schedules, sales reps at Universal Containers dedicate time to follow up with prospects and existing clients via email regarding renewals or new deals. They spend many hours throughout the week reviewing past communications and details about their customers before performing their outreach. Which standard Agent action helps sales reps draft personalized emails to prospects by generating text based on previous successful communications?
- A. Agent Action: Summarize Record
- B. Agent Action: Find Similar Opportunities
- C. Agent Action: Draft or Revise Sales Email
Answer: C
Explanation:
Comprehensive and Detailed In-Depth Explanation:UC's sales reps need an AI action to draft personalized emails based on past successful communications, reducing manual review time. Let's evaluate the standard Agent actions.
* Option A: Agent Action: Summarize Record"Summarize Record" generates a summary of a record (e.g., Opportunity, Contact), useful for overviews but not for drafting emails or leveraging past communications. This doesn't meet the requirement, making it incorrect.
* Option B: Agent Action: Find Similar Opportunities"Find Similar Opportunities" identifies past deals to inform strategy, not to draft emails. It provides data, not text generation, making it incorrect.
* Option C: Agent Action: Draft or Revise Sales EmailThe "Draft or Revise Sales Email" action in Agentforce for Sales (sometimes styled as "Draft Sales Email") uses the Atlas Reasoning Engine to generate personalized email content. It can analyze past successful communications (e.g., via Opportunity or Contact history) to tailor emails for renewals or deals, saving reps time. This directly addresses UC's need, making it the correct answer.
Why Option C is Correct:"Draft or Revise Sales Email" is a standard action designed for personalized email generation based on historical data, aligning with UC's productivity goal per Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Agentforce for Sales > Draft Sales Email- Details email generation.
* Trailhead: Explore Agentforce Sales Agents- Covers email drafting with past data.
* Salesforce Help: Sales Features in Agentforce- Confirms personalization capabilities.
NEW QUESTION # 144
A support team handles a high volume of chat interactions and needs a solution to provide quick, relevant responses to customer inquiries.
Responses must be grounded in the organization's knowledge base to maintain consistency and accuracy.
Which feature in Einstein for Service should the support team use?
- A. Einstein Knowledge Recommendations
- B. Einstein Service Replies
- C. Einstein Reply Recommendations
Answer: B
Explanation:
Einstein Service Replies:This feature is designed to generate contextual, AI-powered response suggestions for agents during chat and email interactions. Crucially, these replies can be grounded in your organization's knowledge base, ensuring consistency and accuracy. This aligns perfectly with the requirement for quick, relevant, and consistent responses.
NEW QUESTION # 145
What is automatically created when a custom search index is created in Data Cloud?
- A. A retriever that shares the name of the custom search index.
- B. A predefined Apex retriever class that can be edited by a developer to meet specific needs.
- C. A dynamic retriever to allow runtime selection of retriever parameters without manual configuration.
Answer: A
Explanation:
Comprehensive and Detailed In-Depth Explanation:
In Salesforce Data Cloud, a custom search index is created to enable efficient retrieval of data (e.g., documents, records) for AI-driven processes, such as grounding Agentforce responses. Let's evaluate the options based on Data Cloud's functionality.
* Option A: A retriever that shares the name of the custom search index.When a custom search index is created in Data Cloud, a correspondingretrieveris automatically generated with the same name as the index. This retriever leverages the index to perform contextual searches (e.g., vector-based lookups) and fetch relevant data for AI applications, such as Agentforce prompt templates. The retriever is tied to the indexed data and is ready to use without additional configuration, aligning with Data Cloud's streamlined approach to AI integration. This is explicitly documented in Salesforce resources and is the correct answer.
* Option B: A dynamic retriever to allow runtime selection of retriever parameters without manual configuration.While dynamic behavior sounds appealing, there's no concept of a "dynamic retriever" in Data Cloud that adjusts parameters at runtime without configuration. Retrievers are tied to specific indexes and operate based on predefined settings established during index creation. This option is not supported by official documentation and is incorrect.
* Option C: A predefined Apex retriever class that can be edited by a developer to meet specific needs.Data Cloud does not generate Apex classes for retrievers. Retrievers are managed within the Data Cloud platform as part of its native AI retrieval system, not as customizable Apex code. While developers can extend functionality via Apex for other purposes, this is not an automatic outcome of creating a search index, making this option incorrect.
Why Option A is Correct:
The automatic creation of a retriever named after the custom search index is a core feature of Data Cloud's search and retrieval system. It ensures seamless integration with AI tools like Agentforce by providing a ready-to-use mechanism for data retrieval, as confirmed in official documentation.
References:
Salesforce Data Cloud Documentation: Custom Search Indexes- States that a retriever is auto-created with the same name as the index.
Trailhead: Data Cloud for Agentforce- Explains retriever creation in the context of search indexes.
Salesforce Help: Set Up Search Indexes in Data Cloud- Confirms the retriever-index relationship.
NEW QUESTION # 146
Universal Containers needs to provide insights on the usability of Agents to drive adoption in the organization.
What should the Agentforce Specialist recommend?
- A. Agentforce Analytics
- B. Agent Studio Analytics
- C. Agent Analytics
Answer: C
Explanation:
* Agent Analytics: This tool is specifically designed to provide usability insights for Salesforce agents. It tracks metrics like adoption rates, task completion times, and efficiency levels, helping organizations identify areas where agents excel or need additional support.
* Agentforce Analytics: This term does not correspond to a recognized Salesforce feature.
* Agent Studio Analytics: This is unrelated to analyzing agent usability, as it primarily supports customization or development features rather than providing analytics for adoption.
Thus,Agent Analyticsis the correct recommendation as it offers actionable insights to drive agent adoption and productivity.
Reference:
"Boost Adoption with Analytics Tools | Salesforce" .
NEW QUESTION # 147
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