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| Section | Weight | Objectives |
|---|
| Topic 1: Einstein Trust Layer & Security | | - Trust Layer & Security Features
- 1. Enterprise-grade deployment
- Data Masking
- 1. Configuration of privacy data entities
|
| Topic 2: Reasoning Engine & AI Actions | | - Workflow mastery
- 1. Standard Agent actions
- 2. Custom Agent actions (Flows)
- 3. Custom Agent actions (Apex)
|
| Topic 3: Agent Force Concepts | 30% | - Einstein GPT Integration
- 1. Advanced implementation strategies
- Data Cloud & Grounding Techniques
- 1. Real-world applications
|
| Topic 4: Prompt Engineering | 30% | - Agentforce AI Setup & Configuration
- 1. Advanced implementation strategies
- Prompt Builder & Template Creation
|
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100% Pass 2026 Salesforce AI-201: Salesforce Certified Agentforce Specialist โProfessional Valid Exam Question
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Salesforce Certified Agentforce Specialist Sample Questions (Q239-Q244):
NEW QUESTION # 239
A Salesforce Administrator wants to generate personalized, targeted emails that incorporate customer interaction data. The admin wants to leverage large language models (LLMs) to write the emails, and wants to reuse templates for different products and customers. Which solution approach should the admin leverage?
- A. Create a Sales Email prompt template type.
- B. Use sales Email standard templates
- C. Create a t field Generation prompt template type
Answer: A
Explanation:
To generate personalized emails using LLMs while reusing templates:
Sales Email Prompt Template Type (Option C): Designed specifically for generating dynamic email content by combining LLMs with structured templates. It allows admins to define placeholders (e.g., customer name, product details) and reuse templates across scenarios.
NEW QUESTION # 240
An Agentforce Specialist needs to create a prompt template to fill a custom field named Latest Opportunities Summary on the Account object with information from the three most recently opened opportunities. How should the Agentforce Specialist gather the necessary data for the prompt template?
- A. Select the latest Opportunities related list as a merge field.
- B. Create a flow to retrieve the opportunity information.
- C. Select the Account Opportunity object as a resource when creating the prompt template.
Answer: B
Explanation:
In Salesforce Agentforce, a prompt template designed to populate a custom field (like "Latest Opportunities Summary" on the Account object) requires dynamic data to be fed into the template for AI to generate meaningful output. Here, the task is to gather data from the three most recently opened opportunities related to an account. The most robust and flexible way to achieve this is by using a Flow (Option B). Salesforce Flows allow the Agentforce Specialist to define logic to query the Opportunity object, filter for the three most recent opportunities (e.g., using a Get Records element with a sort by CreatedDate descending and a limit of 3), and pass this data as variables into the prompt template. This approach ensures precise control over the data retrieval process and can handle complex filtering or sorting requirements.
NEW QUESTION # 241
In a Knowledge-based data library configuration, what is the primary difference between the identifying fields and the content fields?
- A. Identifying fields highlight key terms for relevance scoring, while content fields store the full text of the article for retrieval.
- B. Identifying fields help locate the correct Knowledge article, while content fields enrich AI responses with detailed information.
- C. Identifying fields categorize articles for indexing purposes, while content fields provide a brief summary for display.
Answer: B
Explanation:
In Agentforce, a Knowledge-based data library (e.g., via Salesforce Knowledge or Data Cloud grounding) uses identifying fields and content fields to support AI responses.
NEW QUESTION # 242
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?
- A. The Einstein Trust Layer is incorrectly configured.
- B. The prompt template version is incompatible with the chosen LLM.
- C. The data being used for grounding is incorrect or incomplete.
Answer: C
Explanation:
UC's custom prompt for summarizing case records is underperforming, and we need to identify a likely cause.
NEW QUESTION # 243
An Agentforce Specialist wants to ensure their custom agent action performs as expected in conversations. What should the Agentforce Specialist focus on when creating action instructions?
- A. Include comprehensive detailed descriptions and perform smoke testing.
- B. Write concise agent action instructions and test in Agentforce Builder.
- C. Ensure the agent action label matches the utterance's intent.
Answer: B
Explanation:
The AgentForce Action Design Guide emphasizes that concise and clear action instructions are essential for predictable and reliable agent behavior. The documentation states: "Action instructions should be concise, clearly define the purpose of the action, and specify its expected inputs and outputs. Each action must be validated through testing in AgentForce Builder to confirm the LLM interprets and executes it as intended."
NEW QUESTION # 244
......
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