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| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering | 20% | - Prompt Builder usage and use cases - Prompt management and user roles - Grounding techniques and best practices - Prompt template creation: field generation, flex types |
| AI Agents | 35% | - Agent User security and permissions - Deterministic controls: filters and variables - Topics and actions configuration - Agent types: Service, Sales, Employee - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack |
| Development Lifecycle | 15% | - Deployment: sandbox to production - Monitoring, adoption and optimization - Version control and maintenance - Testing agents in Testing Center |
| Data Cloud for Agentforce | 20% | - Improving response accuracy with data grounding - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing - Agentforce Data Library types |
| Multi-Agent Interoperability | 5% | - Agent API usage scenarios - Model Context Protocol (MCP) - Agent-to-agent communication |
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NEW QUESTION # 108
An Agentforce Specialist is assisting Universal Containers with troubleshooting an agent. The Agentforce Specialist notices that the agent is not using topic actions in the desired sequence, causing inconsistent outcomes. Which technique should the Agentforce Specialist recommend to ensure deterministic control over the order in which actions are executed?
Answer: C
Explanation:
The AgentForce Action Sequencing and Deterministic Flow Guide explains that to ensure actions are executed in a specific and predictable order, administrators must explicitly define the order of actions in the topic setup. The documentation states:
"To achieve deterministic control, sequence the topic's actions in the desired order of execution.
This ensures that dependent actions, such as data retrieval followed by record creation, execute consistently and predictably."
NEW QUESTION # 109
For an Agentforce Data Library that contains uploaded files, what occurs once it is created and configured?
Answer: B
Explanation:
In Salesforce Agentforce, a Data Library is a feature that allows organizations to upload files (e.g., PDFs, documents) to be used as grounding data for AI-driven agents. Once the Data Library is created and configured, the uploaded files are indexed to make their content searchable and usable by the AI (e.g., for retrieval-augmented generation or prompt enhancement). The key question is where this indexing occurs. Salesforce Agentforce integrates tightly with Data Cloud, a unified data platform that includes a vector database optimized for storing and indexing unstructured data like uploaded files. When a Data Library is set up, the files are ingested and indexed into Data Cloud's vector database, enabling the AI to efficiently retrieve relevant information from them during conversations or actions.
NEW QUESTION # 110
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: A
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 # 111
What is the primary function of the planner service in the Agent system?
Answer: B
Explanation:
The primary function of the planner service in the Agent system is to identify copilot actions that should be taken in response to user utterances. This service is responsible for analyzing the conversation and determining the appropriate actions (such as querying records, generating a response, or taking another action) that the Agent should perform based on user input.
NEW QUESTION # 112
Universal Containers (UC) configured a new PDF file ingestion in Data Cloud with all the required fields, and also created the mapping and the search Index. UC Is now setting up the retriever and notices a required fleld is missing. How should UC resolve this?
Answer: A
Explanation:
Why is "Update the search index to include the desired field" the correct answer?
When configuring a retriever in Data Cloud for PDF file ingestion, all necessary fields must be included in the search index. If a required field is missing, the correct action is to update the search index to ensure it is available for retrieval.
Key Considerations for Fixing Missing Fields in Data Cloud Retrievers:
Search Index Controls Which Fields Are Searchable
The search index defines which fields are indexed and accessible to the retriever.
If a field is missing, it must be added to the index before it can be queried.
Ensures Complete and Accurate Data Retrieval
Without indexing, the retriever cannot reference the missing field in AI responses.
Updating the index makes the field available for AI-powered retrieval.
Supports AI-Grounded Responses
Agentforce relies on Retriever-Augmented Generation (RAG) to ground AI responses in searchable Data Cloud content.
Ensuring all relevant fields are indexed improves AI-generated answer accuracy.
NEW QUESTION # 113
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