Agentforce-Specialist試験感想 & Agentforce-Specialist問題例

P.S.JPTestKingがGoogle Driveで共有している無料の2025 Salesforce Agentforce-Specialistダンプ：https://drive.google.com/open?id=1BjQTJ4ENs3yBWCr_W5PSUMKy9GfMFRBc

多くの人は自分の能力を向上させる方法を模索しています。では、どうしたらいいですか？一番よい方法はAgentforce-Specialist試験参考書を買うことです。Agentforce-Specialist試験参考書を３０時間ぐらい勉強したら、Agentforce-Specialist試験に参加できます。そして、彼らは無事にAgentforce-Specialist試験に合格しました。本当に驚きました！

Agentforce-Specialistテスト資料を購入したすべてのお客様を大切にしています。お客様との協力を継続したいと考えています。 Agentforce-Specialistテストの質問は常に更新および改善されているため、必要な情報を入手してより良い体験を得ることができます。 Agentforce-Specialistのテストの質問は、デジタル化のペースに従い、絶えず改装し、新しいものを追加しています。 Agentforce-Specialist試験準備がお客様に誠実に役立つことを実感していただければ幸いです。また、Agentforce-Specialistトレーニングガイドの合格率は99％から100％であり、Agentforce-Specialist試験に高いスコアで合格することができます。

>> Agentforce-Specialist試験感想 <<

試験の準備方法-真実的なAgentforce-Specialist試験感想試験-100％合格率のAgentforce-Specialist問題例

電子デバイスでの学習は、実際の研究に触れることに反します。 Agentforce-Specialist試験ダンプは、Agentforce-Specialist試験教材の世界有数のプロバイダーの1つとして知られています。便宜上、今後の参考のためにいくつかのデモを提供しており、それらのダウンロードに対して料金を請求しないことをお約束します。したがって、ダウンロードしてAgentforce-Specialist試験をお試しください。その後、Agentforce-Specialistテストの質問を使用することが適切かどうかがわかります。ダウンロードに問題がある場合は、必ずサービスにアクセスしてください。

Salesforce Agentforce-Specialist 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Agentforce and Data Cloud: This section measures the skills of AI Developers and addresses how Agentforce integrates with Data Cloud to improve response accuracy and personalize answers. It involves grounding with retrievers in Data Cloud to enhance agent performance.
トピック 2	Agentforce and Sales Cloud: This section assesses the skills of AI Developers and covers identifying the correct generative AI features in Agentforce for Sales Cloud scenarios. It also includes determining when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches.
トピック 3	Agentforce and Service Cloud: This section measures the skills of AI Engineers and focuses on building agents that answer questions based on Knowledge articles and connecting them to digital channels. It also covers identifying the correct generative AI features in Agentforce for Service Cloud scenarios.
トピック 4	Agentforce Concepts: This section assesses the skills of AI Engineers and covers how Agentforce works, including its reasoning engine, standard and custom topics, agent actions, and user security management. It also includes testing and deploying agents from sandbox to production environments.
トピック 5	Prompt Engineering: This section measures the skills of AI Developers and focuses on prompt engineering techniques. It covers identifying when to use Prompt Builder, managing prompt templates, selecting appropriate grounding techniques, and explaining the process for creating and executing prompt templates.

Salesforce Certified Agentforce Specialist 認定 Agentforce-Specialist 試験問題 (Q101-Q106):

質問 # 101
A Salesforce Agentforce Specialist is reviewing the feedback from a customer about the ineffectiveness of the prompt template.
What should the Agentforce Specialist do to ensure the prompt template's effectiveness?

A. Periodically change the templates grounding object.
B. Use the Prompt Builder Scorecard to help monitor.
C. Monitor and refine the template based on user feedback.

正解：B

解説：
To address the ineffectiveness of a prompt template reported by a customer, the Salesforce Agentforce Specialist should use the Prompt Builder Scorecard (Option B). This tool is explicitly designed to evaluate and monitor prompt templates against key criteria such as relevance, accuracy, safety, and grounding. By leveraging the scorecard, the specialist can systematically identify weaknesses in the template and make data- driven refinements. While monitoring and refining based on user feedback (Option A) is a general best practice, the Prompt Builder Scorecard is Salesforce's recommended tool for structured evaluation, aligning with documented processes for maintaining prompt effectiveness. Changing the grounding object (Option C) without proper evaluation is reactive and does not address the root cause.
:
Salesforce Einstein Agentforce Specialist Certification Guide: Emphasizes using the Prompt Builder Scorecard to evaluate prompts and iterate based on results.
Trailhead Module: "Einstein for Developers" highlights the scorecard as a critical tool for assessing prompt performance.
Salesforce Help Documentation: Details the Scorecard's role in evaluating prompts against predefined criteria.

質問 # 102
Universal Containers (UC) uses Salesforce Service Cloud to support its customers and agents handling cases.
UC is considering implementing Agent and extending Service Cloud to mobile users.
When would Agent implementation be most advantageous?

A. When the focus is on optimizing marketing campaigns and strategies
B. When the main objective is to enhance data security and compliance measures
C. When the goal is to streamline customer support processes and improve response times

正解：C

解説：
Agent implementation would be most advantageous in Salesforce Service Cloud when the goal is to streamline customer support processes and improve response times. Agent can assist agents by providing real-time suggestions, automating repetitive tasks, and generating contextual responses, thus enhancing service efficiency.
* Option B (data security) is not the primary focus of Agent, which is more about improving operational efficiency.
* Option C (marketing campaigns) falls outside the scope of Service Cloud and Agent's primary benefits, which are aimed at improving customer service and case management.
For further reading, refer to Salesforce documentation on Agent for Service Cloud and how it improves support processes.

質問 # 103
What is a valid use case for Data Cloud retrievers?

A. Modifying and updating data within the source systems connected to Data Cloud.
B. Grounding data from external websites to augment a prompt with RAG.
C. Returning relevant data from the vector database to augment a prompt.

正解：C

解説：
Salesforce Data Cloud integrates with Agentforce to provide real-time, unified data access for AI-driven applications. Data Cloud retrievers are specialized components that fetch relevant data from Data Cloud's vector database-a storage system optimized for semantic search and retrieval-to enhance agent responses or actions. A valid use case, as described in Option A, is using these retrievers to return pertinent data (e.g., customer purchase history, support tickets) from the vector database to augment a prompt. This process, often part of Retrieval-Augmented Generation (RAG), allows the LLM to generate more accurate, context-aware responses by grounding its output in structured, searchable data stored in Data Cloud.
* Option B: Grounding data from external websites is not a primary function of Data Cloud retrievers.
While RAG can incorporate external data, Data Cloud retrievers specifically work with data within Salesforce's ecosystem (e.g., the vector database or harmonized data lakes), not arbitrary external websites. This makes B incorrect.
* Option C: Data Cloud retrievers are read-only mechanisms designed for data retrieval, not for modifying or updating source systems. Updates to source systems are handled by other Salesforce tools (e.g., Flows or Apex), not retrievers.
Option A is correct because it aligns with the core purpose of Data Cloud retrievers: enhancing prompts with relevant, vectorized data from within Salesforce Data Cloud.
:
Salesforce Data Cloud Documentation: "Data Cloud for Agentforce" (Salesforce Help: https://help.salesforce.
com/s/articleView?id=sf.data_cloud_agentforce.htm&type=5)
Trailhead: "Data Cloud Basics" module (https://trailhead.salesforce.com/content/learn/modules/data-cloud- basics)

質問 # 104
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?

A. Populate an AI generated summary field for sales contracts.
B. Populate an Al generated lead score for new leads.
C. Populate an Al-generated time-to close estimation to opportunities

正解：A

解説：
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.
Reference:
Salesforce Help Article: Create AI-Generated Fields with Prompt Builder ("Summary Field Generation" example).
Einstein GPT for Sales Guide: "Automating Contract Summaries."

質問 # 105
Universal Containers (UC) plans to implement prompt templates that utilize the standard foundation models.
What should UC consider when building prompt templates in Prompt Builder?

A. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.
B. Ask it to role-play as a character in the prompt template to provide more context to the LLM.
C. Include multiple-choice questions within the prompt to test the LLM's understanding of the context.

正解：B

解説：
UC is using Prompt Builder with standard foundation models (e.g., via Atlas Reasoning Engine). Let's assess best practices for prompt design.
* Option A: Include multiple-choice questions within the prompt to test the LLM's understanding of the context.Prompt templates are designed to generate responses, not to test the LLM with multiple- choice questions. This approach is impractical and not supported by Prompt Builder's purpose, making it incorrect.
* Option B: Ask it to role-play as a character in the prompt template to provide more context to the LLM.A key consideration in Prompt Builder is crafting clear, context-rich prompts. Instructing the LLM to adopt a role (e.g., "Act as a sales expert") enhances context and tailors responses to UC's needs, especially with standard models. This is a documented best practice for improving output relevance, making it the correct answer.
* Option C: Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.Standard foundation models in Agentforce are pretrained and not user- trainable. Prompt Builder users refine prompts, not the LLM itself, making this incorrect.
Why Option B is Correct:
Role-playing enhances context for standard models, a recommended technique in Prompt Builder for effective outputs, as per Salesforce guidelines.
References:
Salesforce Agentforce Documentation: Prompt Builder > Best Practices - Recommends role-based context.
Trailhead: Build Prompt Templates in Agentforce - Highlights role-playing for clarity.
Salesforce Help: Prompt Design Tips - Suggests contextual roles.

質問 # 106
......

ユーザーエクスペリエンスの向上を常に目指しています。 Agentforce-Specialistテストガイドを購入する前にPDFバージョンのデモをダウンロードして、その内容を簡単に見て、Agentforce-Specialist試験を理解してください。 Agentforce-Specialistの実際の質問を知ったら、購入するかどうかを決めることができます。プロセスは静かでシンプルです。あなたがする必要があるのは、当社のウェブサイトにアクセスして無料のデモをダウンロードすることです。これにより多くの時間を節約でき、Agentforce-Specialist試験問題の合格率は98％以上なので、Agentforce-Specialistテストガイドで満足する可能性が高くなります。

Agentforce-Specialist問題例: https://www.jptestking.com/Agentforce-Specialist-exam.html

P.S. JPTestKingがGoogle Driveで共有している無料かつ新しいAgentforce-Specialistダンプ：https://drive.google.com/open?id=1BjQTJ4ENs3yBWCr_W5PSUMKy9GfMFRBc