P.S. VCESoft在Google Drive上分享了免費的2026 Salesforce Agentforce-Specialist考試題庫：https://drive.google.com/open?id=1vTFuGDAGLFx18XIGsjClX57_HAySaCjQ
Salesforce Agentforce-Specialist認證證書可以加強你的就業前景，可以開發很多好的就業機會。VCESoft是一個很適合參加Salesforce Agentforce-Specialist認證考試考生的網站，不僅能為考生提供Salesforce Agentforce-Specialist認證考試相關的所有資訊，而且還為你提供一次不錯的學習機會。VCESoft能夠幫你簡單地通過Salesforce Agentforce-Specialist認證考試。
| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Agentforce Specialist (AI-201) |
| Exam Number: | AI-201 |
| Exam Format: | Multiple Select, Scenario-Based, Multiple Choice |
| Certificate Validity Period: | 1 year (requires annual maintenance) |
| Passing Score: | 73% |
| Real Exam Qty: | 60-65 |
| Available Languages: | English |
| Related Certifications: | Salesforce Certified AI Specialist |
| Exam Price: | $200 USD |
| Exam Duration: | 105 minutes |
| Recommended Training: | Trailhead Agentforce Specialist Certification Prep |
| Exam Registration: | Salesforce Certification Registration Pearson VUE Scheduling |
| Sample Questions: | Salesforce Agentforce-Specialist Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended: 6 months experience with Agentforce or Salesforce AI features |
| Official Syllabus URL: | https://trailhead.salesforce.com/credentials/certification-detail-print/?certificationId=286 |
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問題 #50
An Agentforce Specialist deployed a Service Agent to an Experience Cloud site and enabled Credential-Based User Verification. The specialist notices that all Data Manipulation Language (DML) record updates are showing the "Last Modified By" user as the authenticated Community User instead of the Agent User.
What should the specialist explain to the business about the effect on audit fields?
答案：A
解題說明：
The correct answer is A. Credential-Based User Verification ties the service interaction to the authenticated Experience Cloud user, so record access and record changes are evaluated through that verified user's security context. That explains why audit fields such as Last Modified By show the Community User rather than the generic Agent User. This is not an error; it is the expected governance outcome when the agent is operating with verified user identity. Option B is incorrect because system- context flow execution would explain bypassed sharing behavior, not why the authenticated user appears in audit fields. Option C is incorrect because the scenario explicitly states Credential-Based User Verification, not token-based verification. For regulated environments, this behavior is valuable because audit trails show which verified customer identity caused the record update.
問題 #51
Universal Containers implemented Agentforce for its users. One user complains that an Agent is not deleting activities from the past 7 days. What is the reason for this issue?
答案：A
解題說明：
Context of the QuestionUniversal Containers (UC) uses Agentforce, a specialized AI-driven assistant for Salesforce. A user reports that an Agent is unable to delete recent activities.
Why Agentforce Cannot Delete Records
Agentforce's Standard Actions: Agentforce typically has predefined or "standard" actions like Create, Update, or Summarize records. However, a standard Delete Record action is not part of the default set of Agentforce actions.
Implication: If Agentforce has no built-in delete functionality, it cannot remove activities-even if the user has permission to delete them in the Salesforce UI.
Why Other Options Are Incorrect
Option A - Permission to Delete the User's Records: Standard Salesforce user permissions do not automatically extend to Agentforce's capabilities. Even if the user can delete records, that doesn't grant Agentforce a new action.
Option B - Agentforce Delete Record Action Permission: There is no separate "Delete Record Action permission" for Agentforce to be toggled. The relevant issue is that the standard Delete Record action does not exist within Agentforce out of the box.
ConclusionThe core reason for the issue is that Agentforce does not support a standard Delete Record action (Choice C).
Salesforce Agentforce Specialist References & Documents
Salesforce Official Documentation - Agentforce(Note: Agentforce may be a pilot or specialized feature; check pilot release notes or official docs for standard actions.) Salesforce Agentforce Specialist Study GuideCovers the limitations of certain AI-enabled features regarding record operations.
問題 #52
When using a prompt template, what should an Agentforce Specialist consider with their grounding data and chosen model?
答案：A
解題說明：
The most critical technical consideration when pairing a prompt template's grounding data with a chosen Large Language Model (LLM) is the relationship between the two. The correct action is to review the model limitation in Prompt Builder versus the grounding data size (C).
Every LLM has a fixed context window limit, typically expressed in tokens (the model's units for processing text). This token limit defines the maximum amount of input data (the prompt template text + all the dynamic grounding data) and output data the model can handle in a single request.
The grounding data, which is pulled dynamically from Salesforce records (e.g., related lists, long text fields, Flow outputs), varies significantly in size from one record to the next. If the combined size of the prompt and the dynamic data for a specific record exceeds the LLM's token limit, the generative AI request will fail with a "token limit exceeded" error. The Agentforce Specialist must proactively design the template to limit the amount of data retrieved (e.g., using Flow to summarize related lists or querying only essential fields) to ensure it stays within the chosen model's capacity.
Option A is incorrect because the Einstein Trust Layer's token limit primarily relates to PII masking and is a security-related capacity, not the fundamental model's context window. Option B is incorrect because OFFSET is a SOQL query function used for pagination, which is irrelevant to ensuring the total size of the final assembled prompt (template + data) fits within the model's token limit.
Simulated Exact Extract of AgentForce documents (Conceptual Reference):
"A major challenge in prompt template design is managing the Large Language Model (LLM) token limit against the volume of grounding data. The specialist must always Review the model limitation in Prompt Builder versus the grounding data size before activation. LLM context windows (token limits) are fixed per model, but dynamic prompt components-such as merge fields from related lists or long text area fields-can cause the total size of the prompt to vary significantly by record. To prevent random token limit failures, the prompt instructions and grounding logic (Flow/Apex) must be explicitly constrained to retrieve only the essential data required to answer the query, ensuring the combined input stays well below the LLM's defined capacity." Simulated Reference: AgentForce Prompt Builder Best Practices Guide, Section 4: Performance and Scalability, p. 92.
問題 #53
Universal Containers (UC) wants to make a sales proposal and directly use data from multiple unrelated objects (standard and custom) in a prompt template. How should UC accomplish this?
答案：D
解題說明：
Comprehensive and Detailed In-Depth Explanation:UC needs to incorporate data from multiple unrelated objects (standard and custom) into a prompt template for a sales proposal. Let's evaluate the options based on Agentforce capabilities.
* Option A: Create a prompt template passing in a special custom object that connects the records temporarily.While a custom object could theoretically act as a junction to link unrelated records, this approach requires additional setup (e.g., creating the object, populating it with data via automation), and there's no direct mechanism in Prompt Builder to "pass in" such an object to a prompt template without grounding or flow support. This is inefficient and not a native feature, making it incorrect.
* Option B: Create a prompt template-triggered flow to access the data from standardand custom objects.There's no such thing as a "prompt template-triggered flow" in Salesforce. Flows can invoke prompt templates (e.g., via the "Prompt Template" action), but the reverse-triggering a flow from a prompt template-is not a standard construct. While a flow could gather data from unrelated objects and pass it to a prompt, this option's terminology is inaccurate, and it's not the most direct solution, making it incorrect.
* Option C: Create a Flex template to add resources with standard and custom objects as inputs.In Agentforce's Prompt Builder, aFlex template(short for Flexible Prompt Template) allows users to define dynamic inputs, including data from multiple Salesforce objects (standard or custom), even if they're unrelated. Resources can be added to the template (e.g., via merge fields or Data Cloud queries), enabling the prompt to pull data directly from specified objects without requiring a junction object or complex flows. This is ideal for generating a sales proposal using disparate data sources and aligns with Salesforce's documentation on Flex templates, making it the correct answer.
Why Option C is Correct:Flex templates are designed for scenarios requiring flexible data inputs, allowing UC to directly reference multiple unrelated objects in the prompt template. This simplifies the process and leverages Prompt Builder's native capabilities, as outlined in Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Prompt Builder > Flex Templates- Describes adding multiple object resources as inputs.
* Trailhead: Build Prompt Templates in Agentforce- Highlights Flex templates for dynamic data scenarios.
* Salesforce Help: Create Flexible Prompts- Confirms support for standard and custom object data.
問題 #54
A customer is authenticated and identified as being either bronze, silver, or gold membership level. Those levels define which subagents or actions are available to the agent to perform specific tasks as per the level- based entitlements.
What is the best way to ensure the agent responds appropriately?
答案：A
解題說明：
The correct answer is A. Entitlement data must be available before the reasoning engine decides which subagents or actions are eligible. Setting custom variables in before reasoning ensures the membership tier is hydrated early enough to drive deterministic filters, available when rules, and flow inputs.
Option B is wrong because after reasoning occurs too late for initial action visibility and routing decisions in the current reasoning cycle. Option C is wrong because the Agent Router is for routing
/classification logic, not the best place to establish reusable entitlement state for action filters and downstream flow logic. The key Agentforce design principle is to make access conditions deterministic before the LLM sees tools. That prevents the agent from offering bronze, silver, or gold actions outside the customer's actual entitlement level.
問題 #55
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Agentforce-Specialist證照資訊: https://www.vcesoft.com/Agentforce-Specialist-pdf.html
P.S. VCESoft在Google Drive上分享了免費的2026 Salesforce Agentforce-Specialist考試題庫：https://drive.google.com/open?id=1vTFuGDAGLFx18XIGsjClX57_HAySaCjQ