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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Agent API usage scenarios - Model Context Protocol (MCP) |
| Topic 2: 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 3: Prompt Engineering | 20% | - Grounding techniques and best practices - Prompt Builder usage and use cases - Prompt template creation: field generation, flex types - Prompt management and user roles |
| Topic 4: Development Lifecycle | 15% | - Testing agents in Testing Center - Deployment: sandbox to production - Monitoring, adoption and optimization - Version control and maintenance |
| Topic 5: AI Agents | 35% | - Agent architecture and reasoning engine - Topics and actions configuration - Agent types: Service, Sales, Employee - Channel integration: digital experience, email, Slack - Deterministic controls: filters and variables - Agent User security and permissions |
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NEW QUESTION # 64
Universal Containers wants to assign agents to improve department efficiency. Which configuration ensures the right tasks are handled by the right agents?
Answer: A
Explanation:
According to the AgentForce Product Overview and Deployment Guide, Salesforce recommends using purpose-built agents to maximize efficiency across departments. The documentation states:
"Each AgentForce agent type is optimized for a specific function - SDR Agent for sales development and lead nurturing, Service Agent for customer service and support cases, and Employee Agent for internal HR, IT, and productivity tasks." This separation ensures that each team benefits from a domain-specific agent equipped with the correct data access and actions.
NEW QUESTION # 65
Universal Containers aims to streamline the sales team's daily tasks by using AI. When considering these new workflows, which improvement requires the use of Prompt Builder?
Answer: A
Explanation:
Prompt Builder is explicitly required to create AI-generated summary fields via prompt templates.
These fields use natural language instructions to extract or synthesize information (e.g., summarizing contract terms). Time-to-close estimations (A) and lead scores (C) are typically handled by predictive AI (e.g., Einstein Opportunity Scoring) or analytics tools, which do not require Prompt Builder.
NEW QUESTION # 66
What is an appropriate use case for leveraging Agentforce Sales Agent in a sales context?
Answer: A
Explanation:
Agentforce Sales Agent is designed to let sales teams perform tasks via natural language commands, leveraging Salesforce data while adhering to policies. For example, agents can ask the AI to "update the opportunity stage to Closed Won" or "generate a quote," with the system enforcing validations and data security. This use case aligns with Salesforce's vision of conversational AI streamlining workflows without compromising compliance.
NEW QUESTION # 67
Universal Containers wants to utilize Agentforce for Sales to help sales reps reach their sales quotas by providing AI-generated plans containing guidance and steps for closing deals. Which feature meets this requirement?
Answer: C
Explanation:
Universal Containers (UC) aims to leverage Agentforce for Sales to assist sales reps with AI- generated plans that provide guidance and steps for closing deals.
NEW QUESTION # 68
At Universal Containers, a sales manager is tackling a tough challenge as several new junior sales reps struggle with objection handling and price negotiations for complex deals. The manager lacks the time to personally guide each sales rep through their specific customer scenarios before their critical meetings. The junior sales reps have asked for a tool that would allow them to practice their pitches by simulating tough conversations and receive personalized feedback that is specific to the commerce opportunity they are working on. Which Salesforce solution should an Agentforce Specialist recommend?
Answer: A
Explanation:
The AgentForce for Sales Overview defines Sales Coach as the AI-powered solution designed to help sales professionals practice and improve selling skills. The guide describes: "Sales Coach simulates customer interactions, allows reps to role-play objection handling, and provides personalized feedback based on real opportunity data." This directly matches the scenario where sales reps want to practice negotiation and objection handling with scenario-specific feedback.
NEW QUESTION # 69
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