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真実的-更新するSalesforce-AI-Specialist学習教材試験-試験の準備方法Salesforce-AI-Specialist合格記
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Salesforce Salesforce-AI-Specialist 認定試験の出題範囲:
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>> Salesforce-AI-Specialist学習教材 <<
Salesforce-AI-Specialist試験の準備方法|権威のあるSalesforce-AI-Specialist学習教材試験|最高のSalesforce Certified AI Specialist Exam合格記
IT業界の中でたくさんの野心的な専門家がいって、IT業界の中でより一層頂上まで一歩更に近く立ちたくてSalesforceのSalesforce-AI-Specialist試験に参加して認可を得たくて、Salesforce のSalesforce-AI-Specialist試験が難度の高いので合格率も比較的低いです。SalesforceのSalesforce-AI-Specialist試験を申し込むのは賢明な選択で今のは競争の激しいIT業界では、絶えず自分を高めるべきです。しかし多くの選択肢があるので君はきっと悩んでいましょう。
Salesforce Certified AI Specialist Exam 認定 Salesforce-AI-Specialist 試験問題 (Q73-Q78):
質問 # 73
An AI Specialist created a custom Agent action, but it is not being picked up by the planner service in the correct order.
Which adjustment should the Al Specialist make in the custom Agent action instructions for the planner service to work as expected?
- A. Specify the profiles or custom permissions allowed to invoke the action.
- B. Specify the LLM model provider and version to be used to invoke the action.
- C. Specify the dependent actions with the reference to the action API name.
正解:C
解説:
When a custom Agent action is not being prioritized correctly by the planner service, the root cause is often missing or improperly defined action dependencies. The planner service determines the execution order of actions based on dependencies defined in the action instructions. To resolve this, the AISpecialist must explicitly specify dependent actions using their API names in the custom action's configuration. This ensures the planner understands the sequence in which actions must be executed to meet business logic requirements.
Salesforce documentation highlights that dependencies are critical for orchestrating workflows in Einstein Bots and Agentforce. For example, if Action B requires data from Action A, Action A's API name must be listed as a dependency in Action B's instructions. The Einstein Bot Developer Guide states that failing to define dependencies can lead to race conditions or incorrect execution order.
In contrast:
* Profiles or custom permissions (B) control access to the action but do not influence execution order.
* LLM model provider and version (C) determine the AI model used for processing but are unrelated to the planner's sequencing logic.
質問 # 74
Universal Containers (UC) is Implementing Service AI Grounding to enhance its customer service operations.
UC wants to ensure that its AI- generated responses are grounded in the most relevant data sources. The team needs to configure the system to include all supported objects for grounding.
Which objects should UC select to configure Service AI Grounding?
- A. Case, Case Emails, and Knowledge
- B. Case and Knowledge
- C. Case, Knowledge, and Case Notes
正解:B
解説:
Universal Containers (UC) is implementing Service AI Grounding to enhance its customer service operations.
They aim to ensure that AI-generated responses are grounded in the most relevant data sources and need to configure the system to include all supported objects for grounding.
Supported Objects for Service AI Grounding:
* Case
* Knowledge
* Case Object:
* Role in Grounding:Provides contextual data about customer inquiries, including case details, status, and history.
* Benefit:Grounding AI responses in case data ensures that the information provided is relevant to the specific customer issue being addressed.
* Knowledge Object:
* Role in Grounding:Contains articles and documentation that offer solutions and information related to common issues.
* Benefit:Utilizing Knowledge articles helps the AI provide accurate and helpful responses based on verified information.
* Exclusion of Other Objects:
* Case Notes and Case Emails:
* Not Supported for Grounding:While useful for internal reference, these objects are not included in the supported objects for Service AI Grounding.
* Reason:They may contain sensitive or unstructured data that is not suitable for AI grounding purposes.
Why Options A and C are Incorrect:
* Option A (Case, Knowledge, and Case Notes):
* Case Notes Not Supported:Case Notes are not among the supported objects for grounding in Service AI.
* Option C (Case, Case Emails, and Knowledge):
* Case Emails Not Supported:Case Emails are also not included in the list of supported objects for grounding.
References:
* Salesforce AI Specialist Documentation -Service AI Grounding Configuration:Details the objects supported for grounding AI responses in Service Cloud.
* Salesforce Help -Implementing Service AI Grounding:Provides guidance on setting up grounding with Case and Knowledge objects.
* Salesforce Trailhead -Enhance Service with AI Grounding:Offers an interactive learning path on using AI grounding in service scenarios.
質問 # 75
An account manager is preparing for an upcoming customer call and wishes to get a snapshot of key data points from accounts, contacts, leads, and opportunities in Salesforce.
Which feature provides this?
- A. Sales Insight Summary
- B. Work Summaries
- C. Sales Summaries
正解:A
解説:
Sales Insight Summary aggregates key data points from multiple Salesforce objects (accounts, contacts, leads, opportunities) into a consolidated view, enabling account managers to quickly access relevant information for customer calls.
* Option A (Sales Summaries): Typically refers to Einstein-generated summaries of specific interactions (e.g., emails, calls), not multi-object snapshots.
* Option C (Work Summaries): Focuses on summarizing customer service interactions (e.g., chat transcripts), not sales data.
* Option B (Sales Insight Summary): Directly provides a holistic snapshot of sales-related objects, aligning with the scenario.
References:
* Salesforce Help: Sales Insight Overview
* Describes Sales Insight Summary as "a unified view of account, contact, and opportunity data for sales readiness."
質問 # 76
Universal Containers plans to implement prompt templates that utilize the standard foundation models.
What should the AI Specialist consider when building prompt templates in Prompt Builder?
- A. Include multiple-choice questions within the prompt to test the LLM's understanding of the context.
- B. Ask it to role-play as a character in the prompt template to provide more context to the LLM.
- C. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.
正解:C
解説:
When buildingprompt templates in Prompt Builder, it is essential to consider how the Large Language Model (LLM) processes and generates outputs. Training the LLM with variouswriting styles, such as different word choices, intensifiers, emojis, and punctuation, helps the model better understand diverse writing patterns and produce more contextually appropriate responses.
This approach enhances the flexibility and accuracy of the LLM when generating outputs for different use cases, as it is trained to recognize various writing conventions and styles. The prompt template should focus on providing rich context, and this stylistic variety helps improve the model's adaptability.
Options A and B are less relevant because adding multiple-choice questions or role-playing scenarios doesn't contribute significantly to improving the AI's output generation quality within standard business contexts.
For more details, refer to Salesforce'sPrompt Builder documentationand LLM tuning strategies.
質問 # 77
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 Al-generated time-to close estimation to opportunities
- B. Populate an Al generated lead score for new leads.
- C. Populate an AI generated summary field for sales contracts.
正解:C
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.
質問 # 78
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