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Agentforce-Specialist Test Discount Voucher, Valid Agentforce-Specialist Practic

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Agentforce-Specialist Test Discount Voucher, Valid Agentforce-Specialist Practic

Posted at yesterday 09:14      View：4 | Replies：1        Print      Only Author   [Copy Link] 1#
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Salesforce Agentforce-Specialist Exam Syllabus Topics:
TopicDetails
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 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 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 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
  • 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 (Q299-Q304):NEW QUESTION # 299
Which feature in the Einstein Trust Layer helps to minimize the risks of jailbreaking and prompt injection attacks?
  • A. Data Masking
  • B. Prompt Defense
  • C. Secure Data Retrieval and Grounding
Answer: B
Explanation:
The Einstein Trust Layer is designed to ensure responsible and compliant AI usage. Data Masking (B) is the mechanism that directly addresses compliance with data protection regulations like GDPR by obscuring or anonymizing sensitive personal data (e.g., names, emails, phone numbers) before it is processed by AI models. This prevents unauthorized exposure of personally identifiable information (PII) and ensures adherence to privacy laws.
Salesforce documentation explicitly states that Data Masking is a core component of the Einstein Trust Layer, enabling organizations to meet GDPR requirements by automatically redacting sensitive fields during AI interactions. For example, masked data ensures that PII is not stored or used in AI model training or inference without explicit consent.
In contrast:
* Toxicity Scoring (A) identifies harmful or inappropriate content in outputs but does not address data privacy.
* Prompt Defense (C) guards against malicious prompts or injection attacks but focuses on security rather than data protection compliance.
Reference:
Salesforce Help Article: Einstein Trust Layer ("Data Masking" section).
Einstein Trust Layer Overview: "Data Protection and Compliance Features" (GDPR alignment via Data Masking).

NEW QUESTION # 300
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. User Utterances dashboard.
  • B. Agent Event Logs dashboard.
  • C. AI Audit and Feedback Data dashboard.
Answer: A
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 # 301
Universal Containers (UC) would like to implement the Sales Development Representative (SDR) Agent.
Which channel consideration should UC be aware of while implementing it?
  • A. SDR Agent only works in the Email channel.
  • B. SDR Agent must be deployed in the Messaging channel.
  • C. SDR Agent must also be deployed on the company website.
Answer: B
Explanation:
Universal Containers (UC) is implementing the Agentforce Sales Development Representative (SDR) Agent, a prebuilt AI agent designed to qualify leads and schedule meetings. Channel considerations are critical for deployment. Let's evaluate the options based on official Salesforce documentation.
Option A: SDR Agent must be deployed in the Messaging channel.The Agentforce SDR Agent is designed to engage prospects in real-time conversations, primarily through the Messaging channel (e.g., Salesforce Messaging for in-app or web chat). This aligns with its purpose of qualifying leads interactively and scheduling meetings, as outlined in Agentforce for Sales documentation. While it may leverage email for follow-ups, its core deployment and interaction occur via Messaging, making this a key consideration UC must be aware of. This is the correct answer.
Option B: SDR Agent only works in the Email channel.The SDR Agent is not limited to email. While it can send emails (e.g., follow-ups after lead qualification), its primary function-real-time lead engagement- relies on Messaging. Stating it "only works in the Email channel" is inaccurate and contradicts its documented capabilities, making this incorrect.
Option C: SDR Agent must also be deployed on the company website.While the SDR Agent can be embedded on a company website via Messaging (e.g., as a chat widget), this is an implementation choice, not a mandatory requirement. The agent's deployment is channel-specific (Messaging), and website integration is optional, not a "must." This option overstates the requirement, making it incorrect.
Why Option A is Correct:
The SDR Agent's primary deployment in the Messaging channel is a documented consideration for its real- time lead qualification capabilities. UC must plan for this channel to ensure effective implementation, as per Salesforce guidelines.
References:
Salesforce Agentforce Documentation: SDR Agent Setup > Channels - Specifies Messaging as the primary channel.
Trailhead: Explore Agentforce Sales Agents - Notes SDR Agent's Messaging focus for lead engagement.
Salesforce Help: Agentforce for Sales > SDR Agent - Confirms Messaging deployment requirement.

NEW QUESTION # 302
Universal Containers is rolling out a new generative AI initiative.
Which Prompt Builder limitations should the Agentforce Specialist be aware of?
  • A. Creations or updates to the prompt templates are not recorded in the Setup Audit Trail.
  • B. Rich text area fields are only supported in Flex template types.
  • C. Custom objects are supported only for Flex template types.
Answer: A
Explanation:
When rolling out a new Generative AI initiative in Salesforce using Prompt Builder, it's important to understand its current limitations. One key limitation is that changes to prompt templates (creation, edits, or deletions) are not logged in the Setup Audit Trail, which means admins won't have a historical record of modifications for compliance or troubleshooting.
Reference:
"Prompt Builder Limitations | Salesforce Documentation" .

NEW QUESTION # 303
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 Record Merge Fields
  • B. Automatic grounding using Draft with Einstein feature
  • C. Ground with Apex Merge Fields
Answer: B
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 # 304
......
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Posted at yesterday 23:30        Only Author  2#
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