ちなみに、CertShiken Agentforce-Specialistの一部をクラウドストレージからダウンロードできます：https://drive.google.com/open?id=1084IOW1ujYB5GrjfpYx6NPe4Ml-1OpZs
Salesforce Agentforce-Specialist「Salesforce Certified Agentforce Specialist (AI-201)」認証試験に合格することが簡単ではなくて、Salesforce Agentforce-Specialist証明書は君にとってはIT業界に入るの一つの手づるになるかもしれません。しかし必ずしも大量の時間とエネルギーで復習しなくて、弊社が丹精にできあがった問題集を使って、試験なんて問題ではありません。
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>> Salesforce Agentforce-Specialist関連問題資料 <<
Agentforce-Specialistの実際のテストは、さまざまな分野の多くの専門家によって設計され、顧客のさまざまな状況を考慮し、顧客が時間を節約できるように実用的なAgentforce-Specialist学習教材を設計しました。 学生であろうとオフィスワーカーであろうと、Agentforce-Specialist試験の準備にすべての時間を費やすことはないと思います。専門知識の勉強、家事、子供の世話などに取り組んでいます。 簡素化された情報により、効率的に学習することができます。 そして、あなたは事前に本当の試験を感じたいですか？ Agentforce-Specialist試験問題を購入するだけです！
質問 # 363
What should Universal Containers consider when deploying an Agentforce Service Agent with multiple topics and Agent Actions to production?
正解：B
解説：
Comprehensive and Detailed In-Depth Explanation:
UC is deploying an Agentforce Service Agent with multiple topics and actions to production. Let's assess deployment considerations.
* Option A: Deploy agent components without a test run in staging, relying on production data for reliable results. Sandbox configuration alone ensures seamless production deployment.Skipping staging tests is risky and against best practices. Sandbox configuration doesn't guarantee production success without validation, making this incorrect.
* Option B: Ensure all dependencies are included, Apex classes meet 75% test coverage, and configuration settings are aligned with production. Plan for version management and post- deployment activation.This is a comprehensive approach: dependencies (e.g., flows, Apex) must be deployed, Apex requires 75% coverage, and production settings (e.g., permissions, channels) must align. Version management tracks changes, and post-deployment activation ensures controlled rollout.
This aligns with Salesforce deployment best practices for Agentforce, making it the correct answer.
* Option C: Deploy flows or Apex after agents, topics, and Agent Actions to avoid deployment failures and potential production agent issues requiring complete redeployment.Deploying components separately risks failures (e.g., actions needing flows failing). All components should deploy together for consistency, making this incorrect.
Why Option B is Correct:
Option B covers all critical deployment considerations for a robust Agentforce rollout, as per Salesforce guidelines.
References:
Salesforce Agentforce Documentation: Deploy Agents to Production- Lists dependencies and coverage.
Trailhead: Deploy Agentforce Agents- Emphasizes testing and activation planning.
Salesforce Help: Agentforce Deployment Best Practices- Confirms comprehensive approach.
質問 # 364
Universal Containers plans to enhance the customer support team's productivity using AI.
Which specific use case necessitates the use of Prompt Builder?
正解：B
解説：
The use case that necessitates the use ofPrompt Builderiscreating a draft of a support bulletin postfor new product patches.Prompt Builderallows theAgentforce Specialistto create and refine prompts that generate specific, relevant outputs, such as drafting support communication based on product information and patch details.
* Option B(agent performance score) would likely involve predictive modeling, not prompt generation.
* Option C(estimating support ticket volume) would require data analysis and predictive tools, not prompt building.
For more details, refer toSalesforce's Prompt Builder documentationfor generative AI content creation.
質問 # 365
Universal Containers wants to create a prompt template that consistently extracts a customer's specific product model number and quantity from an email inquiry to draft a response back to the customer.
Which best practice should UC implement to achieve this goal?
正解：A
解説：
The correct answer is B because the requirement is structured extraction, not creative generation. To reliably extract a product model number and quantity, the prompt should give clear instructions that describe exactly what to identify, how to format the extracted values, and how to behave when information is missing. Few-shot examples improve consistency by showing the model representative input-and-output patterns. Option A is wrong because open-ended questions increase variability and are better for exploratory responses, not precise extraction. Option C is wrong because higher temperature increases creativity and randomness, which is the opposite of what UC needs. Salesforce Prompt Builder guidance emphasizes clear prompt instructions, CRM grounding, and managing prompt templates for trusted generative AI outputs.
質問 # 366
Choose 1 option.
What does it mean when a prompt template version is described as immutable?
正解：C
解説：
According to the AgentForce Prompt Template Versioning Guide, when a prompt template version is marked as immutable, it means that no edits or modifications can be made to that version after it has been activated.
This ensures that the logic, wording, and grounding parameters tied to that version remain locked and consistent for auditing, reproducibility, and compliance purposes.
If further changes are required, the system automatically creates a new draft version of the template. The old version remains immutable and preserved for traceability.
Option B is incorrect because multiple versions can exist, and older versions can remain active under specific testing or rollback scenarios. Option C is partially true but incomplete-the immutability refers to the frozen nature of an active version, not just version creation.
Thus, the correct explanation is Option A - Once a prompt template version is activated, it becomes immutable and cannot be changed.
Reference: AgentForce Prompt Management Documentation - "Immutable Version Control in Prompt Templates."
質問 # 367
Universal Containers (UC) is using standard Service AI Grounding. UC created a custom rich text field to be used with Service AI Grounding.
What should UC consider when using standard Service AI Grounding?
正解：B
解説：
Service AI Grounding retrieves data from Salesforce objects to ground AI-generated responses. Key considerations:
* Field Types: Standard Service AI Grounding supports String and Text Area fields. Custom rich text fields (e.g., RichTextArea) are not supported, making Option B correct.
* Objects: While Service AI Grounding primarily uses Case and Knowledge objects (Option A), the limitation here is the field type, not the object.
* Visibility: Service AI Grounding respects user permissions and sharing settings unless overridden (Option C is incorrect).
References:
* Salesforce Help: Service AI Grounding Requirements
* Explicitly states support for "Text Area and String fields" only.
質問 # 368
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