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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Agents | 35% | - Topics and actions configuration - Deterministic controls: filters and variables - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack - Agent User security and permissions - Agent types: Service, Sales, Employee |
| Topic 2: Prompt Engineering | 20% | - Prompt management and user roles - Prompt Builder usage and use cases - Grounding techniques and best practices - Prompt template creation: field generation, flex types |
| Topic 3: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Model Context Protocol (MCP) - Agent API usage scenarios |
| Topic 4: Development Lifecycle | 15% | - Deployment: sandbox to production - Monitoring, adoption and optimization - Testing agents in Testing Center - Version control and maintenance |
| Topic 5: Data Cloud for Agentforce | 20% | - Improving response accuracy with data grounding - Agentforce Data Library types - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing |
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NEW QUESTION # 78
Universal Containers wants to implement a solution in Salesforce with a custom UX that allows users to enter a sales order number. Subsequently, the system will invoke a custom prompt template to create and display a summary of the sales order header and sales order details.
Which solution should an Agentforce Specialist implement to meet this requirement?
Answer: C
Explanation:
Universal Containers (UC) requires a solution with a custom UX for users to input a sales order number, followed by invoking a custom prompt template to generate and display a summary.
Let's evaluate each option based on this requirement and Salesforce Agentforce capabilities.
NEW QUESTION # 79
Universal Containers (UC) is preparing to use the Agentforce Testing Center to ensure the reliability of a new agent. UC has a CSV file with test cases and is reviewing the documentation to understand best practices and limitations. Which best practice should the company follow to avoid modifying CRM data while running tests in the Testing Center?
Answer: C
Explanation:
According to the AgentForce Testing and Validation Guidelines, all automated or large-scale test runs in Testing Center should be executed in a sandbox environment to prevent any unintended modifications to live CRM data.
Running tests in production can trigger record updates, create cases, or call actions that alter live data, violating best practice standards for safe validation. Testing in a sandbox ensures the environment mirrors production logic while maintaining data isolation.
NEW QUESTION # 80
Before activating a custom agent action, an AgentForce Specialist would like to evaluate multiple real-world user utterances to ensure the action is being selected appropriately. Which tool should the AgentForce Specialist recommend?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
The AgentForce Testing Center is the recommended tool for validating and refining agent behavior before activation. According to the AgentForce Quality Assurance and Testing Framework, the Testing Center enables specialists to simulate and analyze how the reasoning engine classifies user utterances, selects topics, and triggers actions across multiple test cases.
This testing environment provides detailed diagnostics, showing classification confidence, prompt resolution paths, and grounding behavior. It allows for adjustments before production deployment to ensure accuracy and relevance in real-world scenarios.
NEW QUESTION # 81
The marketing team at Universal Containers is looking for a way personalize emails based on customer behavior, preferences, and purchase history. Why should the team use Agent as the solution?
Answer: C
Explanation:
Agent is designed to assist in generating personalized, AI-driven content based on customer data such as behavior, preferences, and purchase history. For the marketing team at Universal Containers, this is the perfect solution to create dynamic and relevant email content. By leveraging Agent, they can ensure that each customer receives tailored communications, improving engagement and conversion rates.
NEW QUESTION # 82
What is An Agentforce able to do when the "Enrich event logs with conversation data" setting in Agent is enabled?
Answer: C
Explanation:
When the "Enrich event logs with conversation data" setting is enabled in Agent, it allows An Agentforce or admin to view session data, including both the user input and copilot responses from interactions over the past 7 days. This data is crucial for monitoring how the copilot is being used, analyzing its performance, and improving future interactions based on past inputs.
This setting enriches the event logs with detailed conversational data for better insights into the interaction history, helping Agentforce Specialists track AI behavior and user engagement.
NEW QUESTION # 83
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