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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompt Engineering | 20% | - Prompt template creation: field generation, flex types - Prompt management and user roles - Grounding techniques and best practices - Prompt Builder usage and use cases |
| Topic 2: AI Agents | 35% | - Agent architecture and reasoning engine - Agent types: Service, Sales, Employee - Deterministic controls: filters and variables - Channel integration: digital experience, email, Slack - Topics and actions configuration - Agent User security and permissions |
| Topic 3: Development Lifecycle | 15% | - Version control and maintenance - Deployment: sandbox to production - Monitoring, adoption and optimization - Testing agents in Testing Center |
| Topic 4: Data Cloud for Agentforce | 20% | - Agentforce Data Library types - Improving response accuracy with data grounding - Unstructured data processing: chunking, indexing - Retrievers and search types: keyword, vector, hybrid |
| Topic 5: Multi-Agent Interoperability | 5% | - Model Context Protocol (MCP) - Agent API usage scenarios - Agent-to-agent communication |
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NEW QUESTION # 280
When a verified customer in a help center says, "I want to upgrade my service plan," an AI agent needs to complete the following tasks:
- Verify identity and entitlement.
- Create a new quote.
- Calculate a prorated upgrade amount.
- Escalate to an Account Executive (AE) only if the reorder exceeds USD
25,000.
Which type of agent should an AgentForce Specialist build to support this use case?
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
According to the AgentForce Specialist Implementation Guide and Agent Type Configuration Reference, this scenario represents a revenue-generating interaction where the AI agent is directly handling an upsell process. The tasks include verifying the customer's entitlement, generating a new quote, and calculating a prorated amount -- all of which align with the Sales Agent configuration type in AgentForce.
The Sales Agent is specifically designed to manage lead conversion, quoting, upselling, renewals, and escalation logic for higher-value opportunities. AgentForce documentation emphasizes that when an interaction involves quote generation, pricing calculations, or escalations to an Account Executive for large deal handling, the correct design is a Sales Agent.
NEW QUESTION # 281
Where should the Agentforce Specialist go to add/update actions assigned to a copilot?
Answer: A
Explanation:
To add or update actions assigned to a copilot, An Agentforce can manage this through several areas:
Copilot Actions Page: This is the central location where copilot actions are managed and configured.
Record Page for the Copilot Action: From the record page, individual copilot actions can be updated or modified.
Copilot Action Library Tab: This tab serves as a repository where predefined or custom actions for Copilot can be accessed and modified.
These areas provide flexibility in managing and updating the actions assigned to Copilot, ensuring that the AI assistant remains aligned with business requirements and processes.
NEW QUESTION # 282
An Agentforce at Universal Containers is trying to set up a new Field Generation prompt template. They take the following steps.
1. Create a new Field Generation prompt template.
2. Choose Case as the object type.
3. Select the custom field AI_Analysis_c as the target field.
After creating the prompt template, the Agentforce Specialist saves, tests, and activates it.
Howsoever, when they go to a case record, the AI Analysis field does not show the (Sparkle) icon on the Edit pencil. When the Agentforce Specialist was editing the field, it was behaving as a normal field.
Which critical step did the Agentforce Specialist miss?
Answer: B
Explanation:
For Field Generation prompt templates to display the Sparkle icon (indicating AI-generated content), the target field must be explicitly associated with the prompt template on the Lightning page layout. Even if the prompt template is activated, failing to add the field to the page layout and link it to the template will result in the field behaving as a standard field. Salesforce documentation emphasizes that page layout configuration is mandatory to enable AI-driven field interactions.
NEW QUESTION # 283
An Agentforce needs to enable the use of Sales Email prompt templates for the sales team. The Agentforce Specialist has already created the templates in Prompt Builder. According to best practices, which steps should the Agentforce Specialist take to ensure the sales team can use these templates?
Answer: A
Explanation:
To enable Sales Email prompt templates:
Permission Set: Assign the Prompt Template User permission set to the sales team to grant access to use pre-built templates.
Feature Activation: Enable Sales Emails in Salesforce Setup to activate the integration between prompt templates and email workflows.
NEW QUESTION # 284
Universal Containers wants its AI agent to answer customer questions with precise and up-to- date information. How does an Agentforce Data Library simplify and enable this?
Answer: A
Explanation:
Why is "Automates Ingestion, Indexing, and Default Retriever Creation" the correct answer?
An Agentforce Data Library is a key component in ensuring that an AI agent provides precise and up-to-date responses by:
Automating data ingestion -> Brings in data from various sources.
Indexing the data -> Organizes it efficiently for AI retrieval.
Creating a default retriever -> Enables the AI to fetch relevant data dynamically when answering customer queries.
Key Features of an Agentforce Data Library:
Automates Data Ingestion
Integrates real-time and historical data into Salesforce Data Cloud.
Ensures that relevant updates are continuously fed into the AI system.
Indexes Data for Efficient Retrieval
Enhances searchability for quick, context-aware responses.
Enables fast AI response times while maintaining accuracy.
Creates a Default Retriever
AI agents use the retriever to fetch the most relevant and current information.
The retriever grounds AI-generated responses using structured and indexed data.
NEW QUESTION # 285
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