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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud for Agentforce | 20% | - Unstructured data processing: chunking, indexing - Retrievers and search types: keyword, vector, hybrid - Improving response accuracy with data grounding - Agentforce Data Library types |
| Topic 2: AI Agents | 35% | - Agent types: Service, Sales, Employee - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack - Agent User security and permissions - Topics and actions configuration - Deterministic controls: filters and variables |
| Topic 3: Multi-Agent Interoperability | 5% | - Model Context Protocol (MCP) - Agent-to-agent communication - Agent API usage scenarios |
| Topic 4: Development Lifecycle | 15% | - Version control and maintenance - Deployment: sandbox to production - Monitoring, adoption and optimization - Testing agents in Testing Center |
| Topic 5: Prompt Engineering | 20% | - Prompt template creation: field generation, flex types - Grounding techniques and best practices - Prompt management and user roles - Prompt Builder usage and use cases |
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NEW QUESTION # 158
Universal Containers deploys a new Agentforce Service Agent into the company's website but is getting feedback that the Service Agent is not providing answers to customer questions that are found in the company's Salesforce Knowledge articles. What is the likely issue?
Answer: B
Explanation:
According to the AgentForce Knowledge Integration and Access Configuration Guide, a Service Agent retrieves and grounds its responses using data from Salesforce Knowledge when the correct permissions are assigned. If customers report that the agent cannot access or provide answers from Knowledge articles, the most common root cause is that the AgentForce Service Agent user lacks the "Allow View Knowledge" permission.
This permission enables the agent to retrieve and read published articles from Salesforce Knowledge for grounding responses. Without it, the agent cannot access the content repository, resulting in incomplete or generic answers.
NEW QUESTION # 159
An Agentforce Service Agent, who has been successfully assisting customers with service requests in Salesforce, is now unable to help customers with issues related to a new product replacement process. The company recently implemented a custom Product Replacement object in Salesforce to track and manage these replacements. Which Agentforce Agent User change must be implemented to address this issue?
Answer: C
Explanation:
Why is "Permission Set Read Access" the correct answer?
If an Agentforce Service Agent is unable to assist customers with the new Product Replacement process, it is likely due to missing object permissions.
Key Considerations for Object Access in Agentforce:
Custom Objects Require Permission Set Access
The new Product Replacement object must be explicitly assigned to the agent's permission set.
Without Read access, the agent cannot view or interact with the object.
Ensuring Full Data Access for Agents
In Setup -> Permission Sets, the admin should:
Grant Read access to the Product Replacement object
Ensure that related fields (e.g., status, replacement reason) are also accessible Aligning AI and Agent Workflows If Einstein AI is used to suggest solutions, the agent must have visibility into the Product Replacement object for context-aware responses.
NEW QUESTION # 160
Universal Containers has a custom Agent action calling a flow to retrieve the real-time status of an order from the order fulfillment system. For the given flow, what should the Agentforce Specialist consider about the running user's data access?
Answer: A
Explanation:
When a flow is invoked via a custom Agent action, its data access depends on the flow's runtime configuration, not system mode by default. Salesforce flows can be configured to respect the running user's permissions and sharing settings:
If the flow is set to "Run as the User Who Launched the Flow" (enabled in Flow Settings), it adheres to the user's permissions, field-level security (FLS), and sharing rules.
NEW QUESTION # 161
Universal Containers (UC) is looking to enhance its operational efficiency. UC has recently adopted Salesforce and is considering implementing Agent to improve its processes. What is a key reason for implementing Agent?
Answer: C
Explanation:
The key reason for implementing Agent is its ability to streamline workflows and automate repetitive tasks. By leveraging AI, Agent can assist users in handling mundane, repetitive processes, such as automatically generating insights, completing actions, and guiding users through complex processes, all of which significantly improve operational efficiency.
NEW QUESTION # 162
What is best practice when refining Agent custom action instructions?
Answer: C
Explanation:
When refining Agent custom action instructions, it is considered best practice to provide examples of user messages that are expected to trigger the action. This helps ensure that the custom action understands a variety of user inputs and can effectively respond to the intent behind the messages.
NEW QUESTION # 163
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