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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Agentforce Specialist (AI-201) |
| Exam Number: | AI-201 |
| Exam Format: | Multiple Select, Scenario-based Questions, Multiple Choice |
| Real Exam Qty: | 60 multiple-choice questions + up to 5 unscored questions |
| Available Languages: | Japanese, English, French |
| Related Certifications: | Salesforce Platform Administrator Salesforce AI Associate (retired) Salesforce Platform App Builder Salesforce AI Specialist (retired) |
| Passing Score: | 72%-73% |
| Exam Duration: | 105 minutes |
| Exam Price: | USD 200 |
| Recommended Training: | Salesforce Trailhead Agentforce Learning Paths Agentforce Specialist Exam Prep |
| Exam Registration: | Salesforce Certification Registration Certification Exam Guide |
| Sample Questions: | Salesforce Agentforce-Specialist Sample Questions |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | None |
| Official Syllabus URL: | https://help.salesforce.com/s/articleView?id=005298924&type=1 |
>> Agentforce-Specialist資格講座 <<
Agentforce-Specialistテスト資料は、学習プラットフォームの科学的性質を強化するために、特に製品の高いIQチームで構成される多数の資格試験専門家を雇い、これらの専門家はAgentforce-Specialistクイズの長年の教育経験を組み合わせて試験の分野での成果を導き、研究するために、普及はSalesforce Certified Agentforce Specialist (AI-201)試験ダンプの非常に複雑な内容でした。エキスパートチームは、Agentforce-Specialist試験に合格するためのAgentforce-Specialistクイズガイドコンサルティングに高品質を提供できます。
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質問 # 40
Universal Containers (UC) has built a custom retriever in AI Models, formerly Einstein Studio, to ground AI responses with technical documentation. UC now requires that a summary field from the search index be included in the output to provide a brief overview of each retrieved document.
What is the recommended course of action for UC?
正解：B
解説：
The correct answer is B. A custom retriever controls which indexed data is searched and what fields are returned to the prompt or agent. If UC needs a summary field returned, the correct action is to update the retriever configuration, save the revised retriever version, and activate that version so the prompt template uses it. Option A is excessive and technically wrong because retriever versioning supports controlled updates rather than forcing a complete rebuild and deletion. Option C is wrong because default retrievers do not automatically return every useful field in the exact structure a business requires. For grounded AI, returned fields must be intentionally configured so the model receives the right concise context without unnecessary noise. Salesforce documents retriever customization and activation of retriever versions.
質問 # 41
Universal Containers (UC) implements a custom retriever to improve the accuracy of AI-generated responses.
UC notices that the retriever is returning too many irrelevant results, making the responses less useful. What should UC do to ensure only relevant data is retrieved?
正解：A
解説：
Comprehensive and Detailed In-Depth Explanation:In Salesforce Agentforce, acustom retrieveris used to fetch relevant data (e.g., from Data Cloud's vector database or Salesforce records) to ground AI responses.
UC's issue is that their retriever returns too many irrelevant results, reducing response accuracy. The best solution is todefine filters(Option A) to refine the retriever's search criteria. Filters allow UC to specify conditions (e.g., "only retrieve documents from the 'Policy' category" or "records created after a certain date") that narrow the dataset, ensuring the retriever returns only relevant results. This directly improves the precision of AI-generated responses by excluding extraneous data, addressing UC's problem effectively.
* Option B: Changing the search index to a different data model object (DMO) might be relevant if the retriever is querying the wrong object entirely (e.g., Accounts instead of Policies). However, the question implies the retriever is functional but unrefined, so adjusting the existing setup with filters is more appropriate than switching DMOs.
* Option C: Increasing the maximum number of results would worsen the issue by returning even more data, including more irrelevant entries, contrary to UC's goal of improving relevance.
* Option A: Filters are a standard feature in custom retrievers, allowing precise control over retrieved data, making this the correct action.
Option A is the most effective step to ensure relevance in retrieved data.
References:
* Salesforce Agentforce Documentation: "Create Custom Retrievers" (Salesforce Help:https://help.
salesforce.com/s/articleView?id=sf.agentforce_custom_retrievers.htm&type=5)
* Salesforce Data Cloud Documentation: "Filter Data for AI Retrieval" (https://help.salesforce.com/s
/articleView?id=sf.data_cloud_retrieval_filters.htm&type=5)
質問 # 42
Universal Containers (UC) is experimenting with using public Generative AI models and is familiar with the language required to get the information it needs. However, it can be time-consuming for both UC's sales and service reps to type in the prompt to get the information they need, and ensure prompt consistency. Which Salesforce feature should the company use to address these concerns?
正解：B
解説：
UC wants to streamline the use of Generative AI by reducing the time reps spend typing prompts and ensuring consistency, leveraging their existing prompt knowledge. Let's evaluate the options.
* Option A: Agent Builder and Action: Query Records.Agent Builder in Agentforce Studio creates autonomous AI agents with actions like "Query Records" to fetch data. While this could retrieve information, it's designed for agent-driven workflows, not for simplifying manual prompt entry or ensuring consistency across user inputs. This doesn't directly address UC's concerns and is incorrect.
* Option B: Einstein Prompt Builder and Prompt Templates.Einstein Prompt Builder, part of Agentforce Studio, allows users to create reusable prompt templates that encapsulate specific instructions and grounding for Generative AI (e.g., using public models via the Atlas Reasoning Engine). UC can predefine prompts based on their known language, saving time for reps by eliminating repetitive typing and ensuring consistency across sales and service teams. Templates can be embedded in flows, Lightning pages, or agent interactions, perfectly addressing UC's needs. This is the correct answer.
* Option C: Einstein Recommendation Builder.Einstein Recommendation Builder generates personalized recommendations (e.g., products, next best actions) using predictive AI, not Generative AI for freeform prompts. It doesn't support custom prompt creation or address time/consistency issues for reps, making it incorrect.
Why Option B is Correct:
Einstein Prompt Builder's prompt templates directly tackle UC's challenges by standardizing prompts and reducing manual effort, leveraging their familiarity with Generative AI language. This is a core feature for such use cases, as per Salesforce documentation.
References:
Salesforce Agentforce Documentation: Einstein Prompt Builder - Details prompt templates for consistency and efficiency.
Trailhead: Build Prompt Templates in Agentforce - Explains time-saving benefits of templates.
Salesforce Help: Generative AI with Prompt Builder - Confirms use for streamlining rep interactions.
質問 # 43
Before activating a custom Agent action, an Agentforce Specialist would like to understand multiple real- world user utterances to ensure the action is being selected appropriately.
Which tool should the Specialist recommend?
正解：C
解説：
The Model Playground allows an Agentforce Specialist to test and simulate real-world user utterances against the configured actions, ensuring the custom Agent action is triggered appropriately based on intent matching and natural language understanding-without needing a full deployment.
質問 # 44
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：B
解説：
Comprehensive and Detailed In-Depth Explanation:
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 # 45
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