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Title: Agentforce-Specialist受験内容、Agentforce-Specialist合格資料 [Print This Page]
Author: samgree385    Time: 4 hour before
Title: Agentforce-Specialist受験内容、Agentforce-Specialist合格資料
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チャンスは常に準備ができあがった者に属します。しかし、我々に属する成功の機会が来たとき、それをつかむことができましたか。SalesforceのAgentforce-Specialist認定試験を受験するために準備をしているあなたは、CertShikenという成功できるチャンスを掴みましたか。CertShikenのAgentforce-Specialist問題集はあなたが楽に試験に合格する保障です。この問題集は大量な時間を節約させ、効率的に試験に準備させることができます。CertShikenの練習資料を利用すれば、あなたはこの資料の特別と素晴らしさをはっきり感じることができます。この問題集は間違いなくあなたの成功への近道で、あなたが十分にAgentforce-Specialist試験を準備させます。
煩わしいSalesforceのAgentforce-Specialist試験問題で、悩んでいますか？悩むことはありません。CertShikenが提供した問題と解答はIT領域のエリートたちが研究して、実践して開発されたものです。それは十年過ぎのIT認証経験を持っています。CertShikenのSalesforceのAgentforce-Specialistの試験問題と解答は当面の市場で最も徹底的な正確的な最新的な模擬テストです。
>> Agentforce-Specialist受験内容 <<
Agentforce-Specialist合格資料 & Agentforce-Specialist最新資料「成功っていうのはどちらですか。」このように質問した人がいます。私は答えてあげますよ。CertShikenを選んだら成功を選ぶということです。CertShikenのSalesforceのAgentforce-Specialist試験トレーニング資料はIT認証試験を受ける全ての受験生が試験に合格することを助けるものです。この資料はSalesforceのAgentforce-Specialist試験のために特別に研究されたもので、受験生からの良い評価をたくさんもらいました。CertShikenのSalesforceのAgentforce-Specialist試験トレーニング資料を選んだらぜひ成功するということを証明しました。
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
  • プロンプトエンジニアリング：このセクションでは、AI開発者のスキルを測定し、プロンプトエンジニアリングの手法に焦点を当てます。プロンプトビルダーを使用するタイミングの特定、プロンプトテンプレートの管理、適切なグラウンディング手法の選択、プロンプトテンプレートの作成と実行のプロセスの説明などを網羅します。
トピック 2
  • Agentforceの概念：このセクションでは、AIエンジニアのスキルを評価し、Agentforceの仕組み（推論エンジン、標準トピックとカスタムトピック、エージェントアクション、ユーザーセキュリティ管理など）について説明します。また、サンドボックスから本番環境へのエージェントのテストとデプロイについても説明します。
トピック 3
  • AgentforceとData Cloud：このセクションでは、AI開発者のスキルを評価し、AgentforceとData Cloudの連携によって応答精度を向上させ、回答をパーソナライズする方法を説明します。また、Data Cloudのリトリーバーを活用したグラウンディングによって、エージェントのパフォーマンスを向上させます。
トピック 4
  • AgentforceとService Cloud：このセクションでは、AIエンジニアのスキルを測定し、ナレッジ記事に基づいて質問に答え、それらをデジタルチャネルに接続するエージェントの構築に焦点を当てます。また、Service CloudシナリオにおけるAgentforceの適切な生成AI機能の特定についても取り上げます。
トピック 5
  • AgentforceとSales Cloud：このセクションでは、AI開発者のスキルを評価し、Sales Cloudシナリオに適したAgentforceのAI生成機能の特定について説明します。また、営業開発担当者（SDR）や営業コーチなど、Agentforceの営業エージェントをいつ活用すべきかを判断することも含みます。

Salesforce Certified Agentforce Specialist 認定 Agentforce-Specialist 試験問題 (Q74-Q79):質問 # 74
Universal Containers (UC) is creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements. Which prompt template type should UC use and which consideration should UC review?
正解：A
解説：
Salesforce Agentforce provides various prompt template types to support AI-driven tasks, such as generating text or populating fields. In this case, UC needs a custom prompt template to populate a field with generated output, which directly aligns with the Field Generation prompt template type. This type is designed to use generative AI to create field values (e.g., summaries, descriptions) based on input data or prompts, making it the ideal choice for UC's requirement. Additionally, UC has enabled the Einstein Trust Layer, a governance framework that ensures AI outputs are safe, explainable, and auditable, capturing AI Audit data for monitoring adoption and identifying improvement areas.
The consideration UC should review is whether Dynamic Fields is enabled. Dynamic Fields allow the prompt template to incorporate variable data from Salesforce records (e.g., case details, customer info) into the prompt, ensuring the generated output is contextually relevant to each record. This is critical for field population tasks, as static prompts wouldn't adapt to record-specific needs. The Einstein Trust Layer further benefits from this, as it can track how dynamic inputs influence outputs for audit purposes.
* Option A: Correct. "Field Generation" matches the use case, and "Dynamic Fields" is a key consideration to ensure flexibility and auditability with the Trust Layer.
* Option B: "Field Generation" is correct, but "Dynamic Forms" is unrelated. Dynamic Forms is a UI feature for customizing page layouts, not a prompt template setting, making this option incorrect.
* Option C: "Flex" templates are more general-purpose and not specifically tailored for field population tasks. While Dynamic Fields could apply, Field Generation is the better fit for UC's stated goal.
Option A is the best choice, as it pairs the appropriate template type (Field Generation) with a relevant consideration (Dynamic Fields) for UC's scenario with the Einstein Trust Layer.
:
Salesforce Agentforce Documentation: "Prompt Template Types" (Salesforce Help: https://help.salesforce.
com/s/articleView?id=sf.agentforce_prompt_templates.htm&type=5)
Salesforce Einstein Trust Layer Documentation: "Monitor AI with Trust Layer" (https://help.salesforce.com/s
/articleView?id=sf.einstein_trust_layer.htm&type=5)
Trailhead: "Build Prompt Templates for Agentforce" (https://trailhead.salesforce.com/content/learn/modules
/build-prompt-templates-for-agentforce)

質問 # 75
Universal Containers (UC) recently rolled out Einstein Generative AI capabilities and has created a custom prompt to summarize case records. Users have reported that the case summaries generated are not returning the appropriate information. What is a possible explanation for the poor prompt performance?
正解：B
解説：
Comprehensive and Detailed In-Depth Explanation:UC's custom prompt for summarizing case records is underperforming, and we need to identify a likely cause. Let's evaluate the options based on Agentforce and Einstein Generative AI mechanics.
* Option A: The prompt template version is incompatible with the chosen LLM.Prompt templates in Agentforce are designed to work with the Atlas Reasoning Engine, which abstracts the underlying large language model (LLM). Salesforce manages compatibility between prompt templates and LLMs, and there's no user-facing versioning that directly ties to LLM compatibility. This option is unlikely and not a common issue per documentation.
* Option B: The data being used for grounding is incorrect or incomplete.Grounding is the process of providing context (e.g., case record data) to the AI via prompt templates. If the grounding data- sourced from Record Snapshots, Data Cloud, or other integrations-is incorrect (e.g., wrong fields mapped) or incomplete (e.g., missing key case details), the summaries will be inaccurate. For example, if the prompt relies on Case.Subject but the field is empty or not included, the output will miss critical information. This is a frequent cause of poor performance in generative AI and aligns with Salesforce troubleshooting guidance, making it the correct answer.
* Option C: The Einstein Trust Layer is incorrectly configured.The Einstein Trust Layer enforces guardrails (e.g., toxicity filtering, data masking) to ensure safe and compliant AI outputs.
Misconfiguration might block content or alter tone, but it's unlikely to cause summaries to lack appropriate informationunless specific fields are masked unnecessarily. This is less probable than grounding issues and not a primary explanation here.
Why Option B is Correct:Incorrect or incomplete grounding data is a well-documented reason for subpar AI outputs in Agentforce. It directly affects the quality of case summaries, and specialists are advised to verify grounding sources (e.g., field mappings, Data Cloud queries) when troubleshooting, as per official guidelines.
References:
* Salesforce Agentforce Documentation: Prompt Templates > Grounding- Links poor outputs to grounding issues.
* Trailhead: Troubleshoot Agentforce Prompts- Lists incomplete data as a common problem.
* Salesforce Help: Einstein Generative AI > Debugging Prompts- Recommends checking grounding data first.

質問 # 76
Universal Containers' data science team is hosting a generative large language model (LLM) on Amazon Web Services (AWS).
What should the team use to access externally-hosted models in the Salesforce Platform?
正解：C
解説：
To accessexternally-hosted models, such as a large language model (LLM) hosted on AWS, theModel Builderin Salesforce is the appropriate tool.Model Builderallows teams to integrate and deploy external AI models into the Salesforce platform, making it possible to leverage models hosted outside of Salesforce infrastructure while still benefiting from the platform's native AI capabilities.
* Option B, App Builder, is primarily used to build and configure applications in Salesforce, not to integrate AI models.
* Option C, Copilot Builder, focuses on building assistant-like tools rather than integrating external AI models.
Model Builder enables seamless integration with external systems and models, allowing Salesforce users to use external LLMs for generating AI-driven insights and automation.
SalesforceAgentforce SpecialistReferences:For more details, check the Model Builder guide here:
https://help.salesforce.com/s/ar ... external_models.htm

質問 # 77
Universal Containers (UC) is building a Flex prompt template. UC needs to use data returned by the flow in the prompt template.
Which flow element should UC use?
正解：B
解説：
* Context of the Question
* Universal Containers (UC) wants to build a Flex prompt template that uses data returned by a Flow.
* "Flex Prompt Templates" allow admins andAgentforce Specialists to incorporate external or dynamic data into generative AI prompts.
* Why "Add Flow Instructions" Is Needed
* Passing Flow Data into Prompt Templates: When configuring the prompt, you must specify how data from the running Flow is passed into the Flex template. The designated element for that is typically "Flow Instructions," which map the Flow outputs to the prompt.
* Other Options:
* Add Flex Instructions: Typically controls how the AI responds or structures the output, not how to bring Flow data into the template.
* Add Prompt Instructions: Usually for static or manual instructions that shape the AI's response, rather than referencing dynamic data from the Flow.
* Outcome
* "Add Flow Instructions" ensures the prompt can dynamically use the data that the Flow returns- makingOption Ccorrect.
SalesforceAgentforce SpecialistReferences & Documents
* Salesforce Help & Training:Using Prompt Templates with FlowExplains how to pass Flow variables into a prompt template via a specialized step (e.g., "Flow Instructions").
* SalesforceAgentforce SpecialistStudy GuideOutlines how to configure generative AI prompts that reference real-time Flow data.

質問 # 78
Universal Containers wants to implement a solution in Salesforce with a custom UX that allows users to enter a sales order number. Subsequently, the system will invoke a custom prompt template to create and display a summary of the sales order header and sales order details. Which solution should an Agentforce Specialist implement to meet this requirement?
正解：B
解説：
Comprehensive and Detailed In-Depth Explanation:
Universal Containers (UC) requires a solution with acustom UXfor users to input a sales order number, followed by invoking a custom prompt template to generate and display a summary. Let's evaluate each option based on this requirement and Salesforce Agentforce capabilities.
* Option A: Create an autolaunched flow and invoke the prompt template using the standard
"Prompt Template" flow action.An autolaunched flow is a background process that runs without user interaction, triggered by events like record updates or platform events. While it can invoke a prompt template using the "Prompt Template" flow action (available in Flow Builder to integrate Agentforce prompts), it lacks a user interface. Since UC explicitly needs acustom UXfor users to enter a sales order number, an autolaunched flow cannot meet this requirement, as it doesn't provide a way for users to input data directly.
* Option B: Create a template-triggered prompt flow and invoke the prompt template using the standard "Prompt Template" flow action.There's no such thing as a "template-triggered prompt flow" in Salesforce terminology. This appears to be a misnomer or typo in the original question. Prompt templates in Agentforce are reusable configurations that define how an AI processes input data, but they are not a type of flow. Flows (like autolaunched or screen flows) can invoke prompt templates, but
"template-triggered" is not a recognized flow type in Salesforce documentation. This option is invalid due to its inaccurate framing.
* Option C: Create a screen flow to collect the sales order number and invoke the prompt template using the standard "Prompt Template" flow action.A screen flow provides a customizable user interface within Salesforce, allowing users to input data (e.g., a sales order number) via input fields.
The "Prompt Template" flow action, available in Flow Builder, enables integration with Agentforce by passing user input (the sales order number) to a custom prompt template. The prompt template can then query related data (e.g., sales order header and details) and generate a summary, which can be displayed back to the user on a subsequent screen. This solution meets UC's need for a custom UX and seamless integration with Agentforce prompts, making it the best fit.
Why Option C is Correct:
Screen flows are ideal for scenarios requiring user interaction and custom interfaces, as outlined in Salesforce Flow documentation. The "Prompt Template" flow action enables Agentforce's AI capabilities within the flow, allowing UC to collect the sales order number, process it via a prompt template, and display the result- all within a single, user-friendly solution. This aligns with Agentforce best practices for integrating AI-driven summaries into user workflows.
References:
Salesforce Help: Flow Builder > Prompt Template Action- Describes how to use the "Prompt Template" action in flows to invoke Agentforce prompts.
Trailhead: Build Flows with Prompt Templates- Highlights screen flows for user-driven AI interactions.
Agentforce Studio Documentation: Prompt Templates- Explains how prompt templates process input data for summaries.

質問 # 79
......
SalesforceのAgentforce-Specialistソフトを使用するすべての人を有効にするために最も快適なレビュープロセスを得ることができ、我々は、SalesforceのAgentforce-Specialistの資料を提供し、PDF、オンラインバージョン、およびソフトバージョンを含んでいます。あなたの愛用する版を利用して、あなたは簡単に最短時間を使用してSalesforceのAgentforce-Specialist試験に合格することができ、あなたのIT機能を最も権威の国際的な認識を得ます！
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