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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Model Context Protocol (MCP) - Agent API usage scenarios |
| Topic 2: Data Cloud for Agentforce | 20% | - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing - Improving response accuracy with data grounding - Agentforce Data Library types |
| Topic 3: Development Lifecycle | 15% | - Testing agents in Testing Center - Deployment: sandbox to production - Version control and maintenance - Monitoring, adoption and optimization |
| Topic 4: Prompt Engineering | 20% | - Prompt management and user roles - Prompt Builder usage and use cases - Prompt template creation: field generation, flex types - Grounding techniques and best practices |
| Topic 5: AI Agents | 35% | - Agent types: Service, Sales, Employee - Topics and actions configuration - Agent User security and permissions - Deterministic controls: filters and variables - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack |
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NEW QUESTION # 145
An Agentforce turned on Einstein Generative AI in Setup. Now, the Agentforce Specialist would like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu. What is causing the problem?
Answer: C
Explanation:
In order to access and create custom prompt templates in Prompt Builder, the Agentforce Specialist must have the Prompt Template Manager permission set assigned. Without this permission, they will not be able to access Prompt Builder in the Setup menu, even though Einstein Generative AI is enabled.
NEW QUESTION # 146
Universal Containers (UC) uses a file upload-based data library and custom prompt to support AI- driven training content. However, users report that the AI frequently returns outdated documents.
Which corrective action should UC implement to improve content relevancy?
Answer: C
Explanation:
UC's issue is that their file upload-based Data Library (where PDFs or documents are uploaded and indexed into Data Cloud's vector database) is returning outdated training content in AI responses. To improve relevancy by ensuring only current documents are retrieved, the most effective solution is to configure a custom retriever with a filter (Option B). In Agentforce, a custom retriever allows UC to define specific conditions-such as a filter on a "Last Modified Date" or similar timestamp field-to limit retrieval to documents updated within a recent period (e.g., last
6 months). This ensures the AI grounds its responses in the most current content, directly addressing the problem of outdated documents without requiring a complete overhaul of the data source.
NEW QUESTION # 147
Universal Containers needs to restrict access to refund processing actions so only customers with Active account status can initiate refunds. How should an Agentforce Specialist apply the restriction deterministically?
Answer: A
Explanation:
According to the AgentForce Action Orchestration and Control Logic Guide, deterministic restrictions on action execution should be implemented using context variables and conditional filters.
By creating a context variable (e.g., AccountStatus) that pulls the customer's current status and applying a conditional filter that limits execution to cases where AccountStatus = "Active", the refund action can be programmatically restricted. This ensures the agent can only trigger the refund flow when conditions are met, providing both consistency and governance over sensitive actions.
NEW QUESTION # 148
Universal Containers (UC) wants to improve the efficiency of addressing customer questions and reduce agent handling time with AI- generated responses. The agents should be able to leverage their existing knowledge base and identify whether the responses are coming from the large language model (LLM) or from Salesforce Knowledge. Which step should UC take to meet this requirement?
Answer: A
Explanation:
To meet Universal Containers' goal of improving efficiency and reducing agent handling time with AI-generated responses, the best approach is to enable Service Replies, Service AI Grounding, and Grounding with Knowledge.
Service Replies generates responses automatically.
Service AI Grounding ensures that the AI is using relevant case data.
Grounding with Knowledge ensures that responses are backed by Salesforce Knowledge articles, allowing agents to identify whether a response is coming from the LLM or Salesforce Knowledge.
NEW QUESTION # 149
Universal Containers has a requirement to provide a sales summary for its sales reps who are using Employee Agents, but they are not happy with the default answer. Which best practice should the AgentForce Specialist recommend?
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
According to the AgentForce Prompt Customization and Template Development Guide, when an organization wants to modify or enhance how structured data (like Salesforce records) is summarized or presented by an agent, the correct approach is to create a Record Summary custom prompt template.
Record Summary templates allow specialists to tailor how the agent interprets and communicates record information - such as opportunities, accounts, or sales summaries - ensuring the output aligns with company-specific terminology, tone, and data needs.
NEW QUESTION # 150
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