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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Agentforce Specialist (AI-201) |
| Exam Number: | AI-201 |
| Related Certifications: | Salesforce AI Specialist (retired) Salesforce AI Associate (retired) Salesforce Platform Administrator Salesforce Platform App Builder |
| Passing Score: | 72%-73% |
| Exam Format: | Multiple Choice, Scenario-based Questions, Multiple Select |
| Exam Price: | USD 200 |
| Available Languages: | English, French, Japanese |
| Real Exam Qty: | 60 multiple-choice questions + up to 5 unscored questions |
| Exam Duration: | 105 minutes |
| Recommended Training: | Agentforce Specialist Exam Prep Salesforce Trailhead Agentforce Learning Paths |
| 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 |
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NEW QUESTION # 237
Universal Containers is implementing a Retrieval-Augmented Generation (RAG) solution where the knowledge store contains Spanish articles, but users will query the agent in French and English. The Agentforce Specialist needs to ensure the retriever can accurately find relevant articles despite the language differences.
What should the specialist do to meet this requirement?
Answer: B
Explanation:
The correct answer is C. In a multilingual RAG design, the embedding model must support semantic similarity across the languages involved in both the source content and user queries. Since the articles are in Spanish and users may ask questions in French or English, selecting the multilingual-e5-large embedding model broadly for the search index is the correct approach. Option A and Option B are too narrow because each excludes one of the languages in the complete requirement. The retriever does not simply match keywords; it compares vector representations of the query and indexed chunks. A multilingual embedding model improves cross-language retrieval by placing semantically similar text from different languages closer in vector space. Salesforce Data 360 search index guidance identifies multilingual content and embedding-model selection as key retrieval considerations.
NEW QUESTION # 238
The Agentforce Specialist of Northern Trail Outfitters reviewed the organization's data masking settings within the Configure Data Masking menu within Setup. Upon assessing all of the fields, a few additional fields were deemed sensitive and have been masked within Einstein's Trust Layer.
Which steps should the Agentforce Specialist take upon modifying the masked fields?
Answer: A
Explanation:
After modifying masked fields in Einstein's Trust Layer, the next important step is to test and confirm that the responses generated by prompts utilizing the newly masked data still meet quality standards. This ensures that masking sensitive information does not negatively impact the usefulness or accuracy of the AI-generated content. Thorough testing helps identify any issues in prompt performance that could arise due to masking, and adjustments can be made if needed.
* Option B is correct because testing the effects of masking on AI responses is a critical step in ensuring AI continues to function as expected.
* Option A (turning off and on the Einstein Trust Layer) is unnecessary after changing the masked fields.
* Option C (turning on Einstein Feedback) allows for user feedback but is not a direct step following field masking modifications.
:
Salesforce Einstein Trust Layer Overview: https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer.htm
NEW QUESTION # 239
What is one key purpose of action instructions when creating a custom agent action in Agentforce?
Answer: C
Explanation:
According to the AgentForce Action Design and Configuration Guide, action instructions serve as the directive text that informs the Reasoning Engine about when and how to invoke a specific action. The documentation states: "Action instructions guide the reasoning engine by describing the action's purpose, inputs, and when it should be selected. Clear, concise instructions improve the LLM's accuracy in mapping user intent to the correct action." Option A is correct because it reflects this documented purpose - connecting user intent with the appropriate system action.
Option B is incorrect since the temperature parameter for the LLM is defined at the system or configuration level, not within action instructions.
Option C is incorrect because action instructions are meant for the reasoning engine, not for end users.
References (AgentForce Documents / Study Guide):
AgentForce Action Design Guide: "How Action Instructions Support Reasoning" AgentForce Builder Handbook: "Optimizing Action Selection through Clear Instructions" AgentForce Study Guide: "Purpose of Action Instructions in Custom Actions"
NEW QUESTION # 240
During configuration, Universal Containers (UC) forgot to grant Knowledge access to the Agentforce Service Agent.
Which permission must UC add for the agent to interact with Knowledge articles and answer customer questions effectively?
Answer: A
Explanation:
According to the AgentForce for Service Configuration Guide, for an agent to interact with and retrieve Knowledge articles, it must have Knowledge object and field access, along with the "Allow View Knowledge" permission. The documentation explains: "Agents need permission to access Knowledge records and their fields to retrieve and summarize content accurately. Additionally, the Allow View Knowledge setting enables the agent to use the Knowledge object as a retrieval source." Option A is incomplete because "Run Flows" is unrelated to Knowledge article access. Option C refers to custom object permissions and external user management, which are unrelated to Knowledge configuration.
Therefore, Option B provides the correct and required set of permissions for AgentForce Service Agents to access and utilize Knowledge data effectively.
References (AgentForce Documents / Study Guide):
* AgentForce for Service Setup Guide: "Knowledge Article Access and Permissions"
* Salesforce Knowledge Configuration Guide: "Granting View Knowledge Access to Agents"
* AgentForce Study Guide: "Configuring Service Agents for Knowledge Retrieval"
NEW QUESTION # 241
Universal Containers (UC) uses a file upload-based data library and custom prompt to support AI-driven training content. However, users report that the AI frequently returns outdated documents. Which corrective action should UC implement to improve content relevancy?
Answer: C
Explanation:
Comprehensive and Detailed In-Depth Explanation:
UC's issue is that their file upload-based Data Library (where PDFs or documents are uploaded and indexed into Data Cloud's vector database) is returning outdated training content in AI responses. To improve relevancy by ensuring only current documents are retrieved, the most effective solution is to configure a custom retriever with a filter (Option B). In Agentforce, a custom retriever allows UC to define specific conditions-such as a filter on a "Last Modified Date" or similar timestamp field-to limit retrieval to documents updated within a recent period (e.g., last 6 months). This ensures the AI grounds its responses in the most current content, directly addressing the problem of outdated documents without requiring a complete overhaul of the data source.
* Option A: Switching to a Knowledge-based Data Library (using Salesforce Knowledge articles) could work, as Knowledge articles have versioning and expiration features to manage recency.
However, this assumes UC's training content is already in Knowledge articles (not PDFs) and requires migrating all uploaded files, which is a significant shift not justified by the question's context. File- based libraries are still viable with proper filtering.
* Option B: This is the best corrective action. A custom retriever with a date filter leverages the existing file-based library, refining retrieval without changing the data source, making it practical and targeted.
* Option C: Relying on periodic re-uploads with the default retriever is passive and inefficient. It doesn't guarantee recency (old files remain indexed until manually removed) and requires ongoing manual effort, failing to proactively solve the issue.
Option B provides a precise, scalable solution to ensure content relevancy in UC's AI-driven training system.
:
Salesforce Agentforce Documentation: "Custom Retrievers for Data Libraries" (Salesforce Help: https://help.
salesforce.com/s/articleView?id=sf.agentforce_custom_retrievers.htm&type=5) Salesforce Data Cloud Documentation: "Filter Retrieval for AI" (https://help.salesforce.com/s/articleView?
id=sf.data_cloud_retrieval_filters.htm&type=5)
Trailhead: "Manage Data Libraries in Agentforce" (https://trailhead.salesforce.com/content/learn/modules
/agentforce-data-libraries)
NEW QUESTION # 242
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