AI-201試験の準備方法｜完璧なAI-201参考書勉強試験｜権威のあるSalesforce Certified Agentforce Specialist資格専門知識

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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Agents	35%	- Agent behavior configuration 1. Filters and variables for deterministic behavior 2. Agent reasoning engine concepts - Agent setup and orchestration 1. Standard and custom topics 2. Standard and custom agent actions
Topic 2: Testing, Deployment & Lifecycle	15%	- Agent lifecycle management 1. Sandbox to production deployment 2. Testing and validation strategies
Topic 3: Governance & Observability	10%	- AI governance 1. Trust layer and compliance concepts 2. Monitoring agent behavior
Topic 4: Data Cloud & Grounding	20%	- Data integration for AI agents 1. Using Data Cloud for retrieval augmentation 2. Connecting external data sources
Topic 5: Prompt Engineering	20%	- Prompt Builder usage 1. Prompt templates and configuration 2. Field generation and flex templates - Grounding techniques 1. Best practices for prompt design 2. Data grounding for reducing hallucinations

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AI-201試験の準備方法｜ユニークなAI-201参考書勉強試験｜一番優秀なSalesforce Certified Agentforce Specialist資格専門知識

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Salesforce Certified Agentforce Specialist 認定 AI-201 試験問題 (Q59-Q64):

質問 # 59
An administrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM data. UC needs enhanced data protection and up-to-date AI capabilities. UC also needs to include relevant information from a Salesforce record to be merged with the prompt.
Which feature in the Einstein Trust Layer best supports UC's need?

A. Dynamic grounding with secure data retrieval
B. Data masking
C. Zero-data retention policy

正解：A

解説：
Dynamic grounding with secure data retrieval is a key feature in Salesforce's Einstein Trust Layer, which provides enhanced data protection and ensures that AI-generated outputs are both accurate and securely sourced. This feature allows relevant Salesforce data to be merged into the AI-generated responses, ensuring that the AI outputs are contextually aware and aligned with real-time CRM data.
Dynamic grounding means that AI models are dynamically retrieving relevant information from Salesforce records (such as customer records, case data, or custom object data) in a secure manner. This ensures that any sensitive data is protected during AI processing and that the AI model's outputs are trustworthy and reliable for business use.
The other options are less aligned with the requirement:
Data masking refers to obscuring sensitive data for privacy purposes and is not related to merging Salesforce records into prompts.
Zero-data retention policy ensures that AI processes do not store any user data after processing, but this does not address the need to merge Salesforce record information into a prompt.

質問 # 60
Universal Containers needs to restrict access to refund processing actions so only customers with Active account status can initiate refunds. How should an Agentforce Specialist apply the restriction deterministically?

A. Include step-by-step instructions at the topic level and action level explaining the rules and examples.
B. Create a context variable for the account status field and apply a conditional filter AccountStatus equals "Active" to refund actions.
C. Create a Flex Prompt Template that has instructions to check for account status.

正解：B

解説：
According to the AgentForce Action Orchestration and Control Logic Guide, deterministic restrictions on action execution should be implemented using context variables and conditional filters.
By creating a context variable (e.g., AccountStatus) that pulls the customer's current status and applying a conditional filter that limits execution to cases where AccountStatus = "Active", the refund action can be programmatically restricted. This ensures the agent can only trigger the refund flow when conditions are met, providing both consistency and governance over sensitive actions.

質問 # 61
An Agentforce is setting up a new org and needs to ensure that users can create and execute prompt templates. The Agentforce Specialist is unsure which roles are necessary for these tasks.
Which permission sets should the Agentforce Specialist assign to users who need to create and execute prompt templates?

A. Prompt Template Manager for creating templates and Prompt Template User for executing templates
B. Data Cloud Admin for creating templates and Prompt Template User for executing templates
C. Prompt Template Manager for creating templates and Data Cloud Admin for executing templates

正解：A

解説：
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.
The Data Cloud Admin permission set is not directly relevant to creating or executing prompt templates but is more focused on managing the Data Cloud.

質問 # 62
A company wants an Agentforce agent to update Case records and execute Flows on behalf of support agents. Which security model ensures the agent does NOT exceed the user's data access?

A. Einstein Trust Layer only
B. System Mode execution
C. Public API access
D. Running the agent in the user context

正解：D

解説：
Running the agent in user context ensures it respects the user's permissions, sharing rules, and field-level security.

質問 # 63
Universal Containers (UC) wants to implement an AI-powered customer service agent that can:
- Retrieve proprietary policy documents that are stored as PDFs.
- Ensure responses are grounded in approved company data, not generic
LLM knowledge.
What should UC do first?

A. Set up an Agentforce Data Library for AI retrieval of policy documents.
B. Expand the AI agent's scope to search all Salesforce records.
C. Add the files to the content, and then select the data library option.

正解：A

解説：
To implement an AI-powered customer service agent that retrieves proprietary policy documents (stored as PDFs) and ensures responses are grounded in approved company data, UC must first establish a foundation for the AI to access and use this data. The Agentforce Data Library (Option A) is the correct starting point. A Data Library allows UC to upload PDFs containing policy documents, index them into Salesforce Data Cloud's vector database, and make them available for AI retrieval. This setup ensures the agent can perform Retrieval-Augmented Generation (RAG), grounding its responses in the specific, approved content from the PDFs rather than relying on generic LLM knowledge, directly meeting UC's requirements.

質問 # 64
......

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