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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic	Details
Topic 1	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 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	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 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 5	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.

Salesforce Certified Agentforce Specialist Sample Questions (Q84-Q89):

NEW QUESTION # 84
Which scenario best demonstrates when an Agentforce Data Library is most useful for improving an AI agent' s response accuracy?

A. When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.
B. When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.
C. When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:
The Agentforce Data Library enhances AI accuracy by grounding responses in curated, indexed data. Let's assess the scenarios.
* Option A: When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.The Data Library is designed to store and index structured content (e.g., Knowledge articles, policy documents) for semantic search and grounding. It excels when an agent needs accurate, up-to-date responses from a managed corpus, like policy documents, ensuring relevance and reducing hallucinations. This is a prime use case per Salesforce documentation, making it the correct answer.
* Option B: When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.Combining disparate sources is more suited to Data Cloud's ingestion and harmonization capabilities, not the Data Library, which focuses on indexed content retrieval. This scenario is less aligned, making it incorrect.
* Option C: When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.Zero-copy integration with Snowflake is a Data Cloud feature, but the Data Library isn't specifically tied to this process-it's about indexed libraries, not direct external retrieval. This is a different context, making it incorrect.
Why Option A is Correct:
The Data Library shines in curated, indexed content scenarios like policy documents, improving agent accuracy, as per Salesforce guidelines.
References:
Salesforce Agentforce Documentation: Data Library > Use Cases- Highlights curated content grounding.
Trailhead: Ground Your Agentforce Prompts- Describes Data Library accuracy benefits.
Salesforce Help: Agentforce Data Library- Confirms policy document scenario.

NEW QUESTION # 85
Universal Containers, dealing with a high volume of chat inquiries, implements Einstein Work Summaries to boost productivity.
After an agent-customer conversation, which additional information does Einstein generate and fill, apart from the "summary"'

A. Draft Survey Request Email
B. Sentiment Analysis and Emotion Detection
C. Issue and Revolution

Answer: C

Explanation:
Einstein Work Summaries automatically generate concise summaries of customer interactions (e.g., chat transcripts). Beyond the "summary" field, it extracts and populates Issue (key problem discussed) and Resolution (action taken to resolve the issue). These fields help agents and supervisors quickly grasp the conversation's context without reviewing the full transcript.
* Sentiment Analysis and Emotion Detection (Option A): While Einstein Conversation Insights provides sentiment scores and emotion detection, these are separate from Work Summaries.Work Summaries focus on factual summaries, not sentiment.
* Draft Survey Request Email (Option B): Not part of Work Summaries. This would require automation tools like Flow or Email Studio.
* Issue and Resolution (Option C): Directly referenced in Salesforce documentation as fields populated by Einstein Work Summaries.
References:
* Salesforce Help Article: Einstein Work Summaries
* Einstein Work Summaries focus on "key details like Issue and Resolution" alongside summaries.
* Contrast with Einstein Conversation Insights for sentiment/emotion analysis.

NEW QUESTION # 86
What is true of Agentforce Testing Center?

A. Running tests risks modifying CRM data in a production environment.
B. Running tests does not consume Einstein Requests.
C. Agentforce Testing Center can only be used in a production environment.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:The Agentforce Testing Center is a tool in Agentforce Studio for validating agent performance. Let's evaluate the statements.
* Option A: Running tests risks modifying CRM data in a production environment.Agentforce Testing Center runs synthetic interactions in a controlled environment (e.g., sandbox or isolated test space) and doesn't modify live CRM data. It's designed for safe pre-deployment testing, making this incorrect.
* Option B: Running tests does not consume Einstein Requests.Einstein Requests are part of the usage quota for Einstein Generative AI features (e.g., prompt executions in production). Testing Center uses synthetic data to simulate interactions without invoking live AI calls that count against this quota.
Salesforce documentation confirms tests don't consume requests, making this the correct answer.
* Option C: Agentforce Testing Center can only be used in a production environment.Testing Center is available in both sandbox and production orgs, but it's primarily used pre-deployment (e.g., in sandboxes) to validate agents safely. This restriction is false, making it incorrect.
Why Option B is Correct:Not consuming Einstein Requests is a key feature of Testing Center, allowing extensive testingwithout impacting quotas, as per Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Testing Center > Overview- Confirms no request consumption.
* Trailhead: Test Your Agentforce Agents- Notes quota-free testing.
* Salesforce Help: Agentforce Testing- Details safe, isolated testing.

NEW QUESTION # 87
An Agentforce turned on Einstein Generative AI in Setup. Now, theAgentforce Specialistwould like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu.
What is causing the problem?

A. The Prompt Template Manager permission set was not assigned correctly.
B. The Prompt Template User permission set was not assigned correctly.
C. The large language model (LLM) was not configured correctly in Data Cloud.

Answer: A

Explanation:
In order to access and create custom prompt templates inPrompt Builder, theAgentforce Specialistmust have thePrompt Template Managerpermission set assigned. Without this permission, they will not be able to accessPrompt Builderin the Setup menu, even thoughEinstein Generative AIis enabled.
* Option Bis correct because thePrompt Template Managerpermission set is required to usePrompt Builder.
* Option A(Prompt Template User permission set) is incorrect because this permission allows users to use prompts, but not create or manage them.
* Option C(LLM configuration in Data Cloud) is unrelated to the ability to accessPrompt Builder.
References:
* Salesforce Prompt Builder Permissions:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder_permissions.htm

NEW QUESTION # 88
An Agentforce implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads based on their interactions and data stored in Salesforce. The Agentforce Specialist needs to configure the system to use the most accurate and up-to-date information for email generation.
Which grounding technique should the Agentforce Specialist use?

A. Ground with Apex Merge Fields
B. Ground with Record Merge Fields
C. Automatic grounding using Draft with Einstein feature

Answer: C

Explanation:
ForEinstein Sales Emailsto generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real- time data. The most appropriate technique in this case isGround with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
* Record Merge Fieldsensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
* Apex Merge Fieldsare typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
* Automatic grounding using Draft with Einsteinis a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data likeRecord Merge Fields.
:
Salesforce Einstein Sales Emails Documentation:https://help.salesforce.com/s/articleView?id=release-notes.
rn_einstein_sales_emails.htm

NEW QUESTION # 89
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Exam Agentforce-Specialist Bible & Agentforce-Specialist Latest Exam Notes

Agentforce-Specialist Latest Exam Notes - Guide Agentforce-Specialist Torrent

Salesforce Agentforce-Specialist Exam Syllabus Topics:

Salesforce Certified Agentforce Specialist Sample Questions (Q84-Q89):

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