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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Agent Development Lifecycle | 15% | - Monitoring, adoption and governance - Testing and debugging in Testing Center - Sandbox to production deployment |
| Topic 2: AI Agents and Agentforce Concepts | 35% | - Agent security and user management - Channel integration and deployment - Topics, actions, and reasoning engine - Agent types: Employee, Service, Sales |
| Topic 3: Multi-Agent Interoperability | 10% | - Agent API usage and integration - Agent-to-agent communication - Model Context Protocol (MCP) |
| Topic 4: Prompt Engineering | 20% | - Grounding techniques and context management - Prompt Builder and template creation - Prompt best practices and optimization |
| Topic 5: Data Cloud for Agentforce | 20% | - Data Library and unstructured data processing - Chunking, indexing and retrieval methods - Vector, keyword and hybrid search |
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NEW QUESTION # 116
An Agentforce Specialist at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time, UC wants to help prep the sales team for calls by:
* Summarizing past purchases
* Displaying products the contact has shown interest in (with data captured via Data Cloud)
* Providing a recap of past email and phone conversations that have transcripts Which approach should the Agentforce Specialist recommend to achieve this goal?
Answer: A
Explanation:
The AgentForce No-Code Builder and Prompt Template Guide specifies that when using Salesforce's standard foundation models, users can ground prompts on CRM and Data Cloud data without requiring fine- tuning or model deployment. The documentation notes: "No-code users can leverage standard foundation models with prompt templates grounded in Salesforce data, including CRM and Data Cloud, to summarize records, highlight insights, and prepare agents for customer engagements." This approach allows the sales operations team to automatically summarize customer data (purchases, interests, and communications) without needing model customization.
Option A (deploying a custom foundational model) requires data science expertise, not available in a no-code setup. Option B (fine-tuning) is unnecessary because standard models with grounding are optimized for contextual data use.
Thus, Option C aligns with Salesforce's recommended low-code/no-code configuration for contextual AI assistance.
References (AgentForce Documents / Study Guide):
AgentForce Builder Guide: "No-Code Prompt Templates Grounded in CRM and Data Cloud" Salesforce Einstein Studio Overview: "Standard vs. Fine-Tuned Models" AgentForce Study Guide: "Empowering Sales Teams with Grounded Prompts"
NEW QUESTION # 117
Universal Containers (UC) wants to build an Agentforce Service Agent that provides the latest, active, and relevant policy and compliance information to customers. The agent must:
* Semantically search HR policies, compliance guidelines, and company procedures.
* Ensure responses are grounded on published Knowledge.
* Allow Knowledge updates to be reflected immediately without manual reconfiguration.What should UC do to ensure the agent retrieves the right information?
Answer: C
Explanation:
Comprehensive and Detailed In-Depth Explanation:
UC requires an Agentforce Service Agent to deliver accurate, up-to-date policy and compliance info with specific criteria. Let's evaluate.
* Option A: Enable the agent to search all internal records and past customer inquiries.Searching all records and inquiries risks irrelevant or outdated responses, conflicting with the need for published Knowledge grounding and immediate updates. This lacks specificity, making it incorrect.
* Option B: Set up an Agentforce Data Library to store and index policy documents for AI retrieval.The Agentforce Data Library integrates with Salesforce Knowledge, indexing HR policies, compliance guidelines, and procedures for semantic search. It ensures grounding in published Knowledge articles, and updates (e.g., new article versions) are reflected instantly without reconfiguration, as the library syncs with Knowledge automatically. This meets all UC requirements, making it the correct answer.
* Option C: Manually add policy responses into the AI model to prevent hallucinations.Manually embedding responses into the model isn't feasible-Agentforce uses pretrained LLMs, not custom training. It also doesn't support real-time updates, making this incorrect.
Why Option B is Correct:
The Data Library meets all criteria-semantic search, Knowledge grounding, and instant updates-per Salesforce's recommended approach.
References:
Salesforce Agentforce Documentation: Data Library > Knowledge Integration- Details indexing and updates.
Trailhead: Build Agents with Agentforce- Covers Data Library for accurate responses.
Salesforce Help: Grounding with Knowledge- Confirms real-time sync.
NEW QUESTION # 118
An Agentforce is setting up a new org and needs to ensure that users can create and execute prompt templates.
TheAgentforce Specialistis unsure which roles are necessary for these tasks.
Which permission sets should theAgentforce Specialistassign to users who need to create and execute prompt templates?
Answer: A
Explanation:
To effectively manage and use prompt templates, two distinct permission sets are required:
* Prompt Template Manager: This permission set allows users to create prompt templates. It provides the necessary access to define templates, which can be shared and utilized across the organization.
* Prompt Template User: This permission set is designed for users who need to execute the templates. It provides the ability to interact with pre-designed prompts and generate outcomes based on these templates.
TheData Cloud Adminpermission set is not directly relevant to creating or executing prompt templates but is more focused on managing the Data Cloud.
NEW QUESTION # 119
Universal Containers implemented Agentforce for its users. One user complains that an Agent is not deleting activities from the past 7 days. What is the reason for this issue?
Answer: A
Explanation:
* Context of the QuestionUniversal Containers (UC) uses Agentforce, a specialized AI-driven assistant for Salesforce. A user reports that an Agent is unable to delete recent activities.
* Why Agentforce Cannot Delete Records
* Agentforce's Standard Actions: Agentforce typically has predefined or "standard" actions like Create, Update, or Summarize records. However, a standard Delete Record action is not part of the default set of Agentforce actions.
* Implication: If Agentforce has no built-in delete functionality, it cannot remove activities-even if the user has permission to delete them in the Salesforce UI.
* Why Other Options Are Incorrect
* Option A - Permission to Delete the User's Records: Standard Salesforce user permissions do not automatically extend to Agentforce's capabilities. Even if the user can delete records, that doesn't grant Agentforce a new action.
* Option B - Agentforce Delete Record Action Permission: There is no separate "Delete Record Action permission" for Agentforce to be toggled. The relevant issue is that the standard Delete Record action does not exist within Agentforce out of the box.
* ConclusionThe core reason for the issue is thatAgentforce does not support a standard Delete Record action(Choice C).
SalesforceAgentforce SpecialistReferences & Documents
* Salesforce Official Documentation - Agentforce(Note: Agentforce may be a pilot or specialized feature; check pilot release notes or official docs for standard actions.)
* SalesforceAgentforce SpecialistStudy GuideCovers the limitations of certain AI-enabled features regarding record operations.
NEW QUESTION # 120
Choose 1 option.
Universal Containers (UC) wants to ensure its compliance team can retrieve exact matches of policy clause numbers from a structured legal document library.
Which search type should UC implement?
Answer: A
Explanation:
According to the AgentForce Search Optimization Guide, when the use case requires retrieving exact matches (such as policy clause numbers, legal identifiers, or invoice IDs) from structured data, the recommended approach is to use keyword search. The documentation specifies: "Keyword search ensures deterministic retrieval of exact term matches from structured fields, preserving precision for identifiers, numeric values, and code references." Semantic search (Option C) uses contextual understanding and synonym expansion, which may yield near matches but not exact ones. Hybrid search (Option B) combines both semantic and keyword results for general knowledge retrieval, but it introduces probabilistic ranking-not suitable for exact legal or compliance queries.
Therefore, for the compliance use case where exact clause number matching is required, keyword search guarantees accuracy, speed, and compliance integrity.
References (AgentForce Documents / Study Guide):
* AgentForce Search and Retrieval Guide: "Choosing Between Keyword, Semantic, and Hybrid Search"
* AgentForce Compliance and Legal Data Search Best Practices
* AgentForce Study Guide: "Optimizing Structured Data Search for Exact Matches"
NEW QUESTION # 121
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