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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompt Engineering | 20% | - Grounding techniques
|
| Topic 2: Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
| Topic 3: AI Agents | 35% | - Agent setup and orchestration
|
| Topic 4: Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Topic 5: Governance & Observability | 10% | - AI governance
|
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NEW QUESTION # 277
Universal Containers implements three custom actions to get three distinct types of sales summaries for its users. Users are complaining that they are not getting the right summary based on their utterances. What should the Agentforce Specialist investigate as the root cause?
Answer: C
Explanation:
The root cause of users receiving incorrect sales summaries lies in non-unique action instructions (Option B). In Einstein Bots, custom actions are triggered based on how well user utterances align with the action instructions defined for each action. If the instructions for the three custom actions overlap or lack specificity, the bot's natural language processing (NLP) cannot reliably distinguish between them, leading to mismatched responses.
Steps to Investigate:
Review Action Instructions: Ensure each custom action has distinct, context-specific instructions.
For example:
Action 1: "Summarize quarterly sales by region."
Action 2: "Generate a product-wise sales breakdown for the current fiscal year." Action 3: "Provide a comparison of sales performance between online and in-store channels." Ambiguous or overlapping instructions (e.g., "Get sales summary") cause confusion.
Test Utterance Matching: Use Einstein Bot's training tools to validate if user utterances map to the correct action. Overlap indicates instruction ambiguity.
Refine Instructions: Incorporate keywords or phrases unique to each sales summary type to improve intent detection.
NEW QUESTION # 278
Universal Containers needs to create Data Cloud reports to understand agent behavior. Which data lake object (DLO) represents an overarching container capturing contiguous interactions with one or more Al agents?
Answer: A
Explanation:
Per the AgentForce Data Cloud Integration Guide, the AI Agent Session (AIAGENTSESSION) object represents an overarching container that tracks a continuous interaction between one or more AI agents and a user. The document describes: "AI Agent Session is the parent container for a contiguous set of AI Agent interactions. It captures metadata, start and end times, and the relationship to individual messages exchanged during the session."
NEW QUESTION # 279
A Salesforce Agentforce Specialist is reviewing the feedback from a customer about the ineffectiveness of the prompt template. What should the Agentforce Specialist do to ensure the prompt template's effectiveness?
Answer: B
Explanation:
To address the ineffectiveness of a prompt template reported by a customer, the Salesforce Agentforce Specialist should use the Prompt Builder Scorecard (Option B). This tool is explicitly designed to evaluate and monitor prompt templates against key criteria such as relevance, accuracy, safety, and grounding. By leveraging the scorecard, the specialist can systematically identify weaknesses in the template and make data-driven refinements. While monitoring and refining based on user feedback (Option A) is a general best practice, the Prompt Builder Scorecard is Salesforce's recommended tool for structured evaluation, aligning with documented processes for maintaining prompt effectiveness. Changing the grounding object (Option C) without proper evaluation is reactive and does not address the root cause.
NEW QUESTION # 280
Universal Containers implemented Agentforce for its users. One user complains that an Agent is not deleting activities from the past 7 days. What is the reason for this issue?
Answer: B
Explanation:
Universal Containers (UC) uses Agentforce, a specialized AI-driven assistant for Salesforce. A user reports that an Agent is unable to delete recent activities.
Why Agentforce Cannot Delete Records
Agentforce's Standard Actions: Agentforce typically has predefined or "standard" actions like Create, Update, or Summarize records. However, a standard Delete Record action is not part of the default set of Agentforce actions.
Implication: If Agentforce has no built-in delete functionality, it cannot remove activities-even if the user has permission to delete them in the Salesforce UI.
NEW QUESTION # 281
A company wants to retrieve patient history details to augment the Al agent response. [he company wants to leverage the Data Cloud search index feature. What is best practice when considering retrieval-augrmented generation (RAG) for information that may contain personally identifiable information (PII)?
Answer: A
Explanation:
According to the AgentForce Data Governance and RAG Security Guidelines, when implementing retrieval-augmented generation (RAG) using Data Cloud search indexes, best practice is to ensure that personally identifiable information (PII) and other sensitive data are never indexed or embedded in the retrieval system.
The documented recommendation is to mask or exclude sensitive fields before creating embeddings or indexing content. This prevents the large language model (LLM) from accessing or generating responses that could inadvertently expose confidential information. Masking can include redacting names, IDs, contact details, or any regulated medical information.
NEW QUESTION # 282
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