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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Governance & Observability | 10% | - AI governance
|
| Topic 2: Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Topic 3: AI Agents | 35% | - Agent behavior configuration
|
| Topic 4: Prompt Engineering | 20% | - Grounding techniques
|
| Topic 5: Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
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NEW QUESTION # 77
Universal Containers (UC) is expanding its Agentforce for Service capabilities to include case management. For security purposes, UC wants the agent to verify a customer's identity before providing any case-related information. The verification must be deterministic-ensuring that no case details are shared unless identity verification has been successfully completed. Which approach best meets this requirement?
Answer: A
Explanation:
The AgentForce for Service Implementation Guide clearly outlines that when an agent must verify identity before performing any case-related operations, the correct method is to use a variable- based control flow. The documentation specifies: "To maintain deterministic and secure behavior, define a variable (for example, `isVerified') that stores the result of an identity verification step.
Use this variable as a conditional filter in the topic flow to ensure that case-related actions execute only when the variable equals `true'." This ensures that no sensitive or case-specific data is shared unless verification is explicitly confirmed. It provides a deterministic safeguard, as the system only proceeds with case data actions after the verification variable confirms completion.
NEW QUESTION # 78
Universal Containers (UC) has configured a data library and wants to restrict indexing of knowledge articles to articles which are only publicly available in their knowledge base, UC also wants the agent to link sources that the large language model (LLM) grounded its response on.
Which settings should help UC with this?
Answer: C
Explanation:
According to the AgentForce Data Library Configuration Guide, administrators can restrict indexing and retrieval of Knowledge articles to publicly available ones and enable source visibility for LLM-grounded responses. The documentation states:
"Within the data library settings, under Knowledge Settings, enable `Use Public Knowledge Articles' to ensure only publicly visible content is indexed. To display citations, enable `Show Sources' so the agent links the specific articles or data records used to ground its response."
NEW QUESTION # 79
In the context of retriever and search indexes, what best describes the data preparation process in Data Cloud?
Answer: B
Explanation:
Why is "Loading, Chunking, Vectorizing, and Storing" the correct answer?
Agentforce AI-powered search and retriever indexing requires data to be structured and optimized for retrieval. The Data Cloud preparation process involves:
Key Steps in the Data Preparation Process for Agentforce:
Loading Data
Raw text from documents, emails, chat transcripts, and Knowledge articles is loaded into Data Cloud.
Chunking (Breaking Text into Small Parts)
AI divides long-form text into retrievable chunks to improve response accuracy.
Example: A 1000-word article might be split into multiple indexed paragraphs.
Vectorization (Transforming Text for AI Retrieval)
Each text chunk is converted into numerical vector embeddings.
This enables faster AI-powered searches based on semantic meaning, not just keywords.
Storing in a Vector Database
The processed data is stored in a search-optimized vector format.
Agentforce AI retrievers use this data to find relevant responses quickly.
NEW QUESTION # 80
A company wants an Agentforce agent to update Case records and execute Flows on behalf of support agents. Which security model ensures the agent does NOT exceed the user's data access?
Answer: A
Explanation:
Running the agent in user context ensures it respects the user's permissions, sharing rules, and field-level security.
NEW QUESTION # 81
Universal Containers (UC) would like to implement the Sales Development Representative (SDR) Agent. Which channel consideration should UC be aware of while implementing it?
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.
NEW QUESTION # 82
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