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Salesforce Agentforce-Specialist Exam Sample Questions

Question # 1

Universal Containers needs to provide insights on the usability of Agents to drive adoption in the organization. What should the Agentforce Specialist recommend?

A. Agent Analytics

B. Agentforce Analytics

C. Agent Studio Analytics

Answer

Explanation:

Agent Analytics: This tool is specifically designed to provide usability insights for Salesforce agents. It tracks metrics like adoption rates, task completion times, and efficiency levels, helping organizations identify areas where agents excel or need additional support.

Agentforce Analytics: This term does not correspond to a recognized Salesforce feature.

Agent Studio Analytics: This is unrelated to analyzing agent usability, as it primarily supports customization or development features rather than providing analytics for adoption.
Thus, Agent Analytics is the correct recommendation as it offers actionable insights to drive agent adoption and productivity.

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Question # 2

An Agentforce at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time. UC wants to help prep the sales team for the calls by summarizing past purchases, interests in products shown by the Contact captured via Data Cloud, and a recap of past email and phone conversations for which there are transcripts. Which approach should the Agentforce Specialist recommend to achieve this use case?

A. Use a prompt template grounded on CRH and Data Cloud data using standard foundation model.

B. Fine-Tune the standard foundational model due to the complexity of the data

C. Deploy UC's own custom foundational model on this data first.

Answer

A. Use a prompt template grounded on CRH and Data Cloud data using standard foundation model.

Explanation

For no-code implementations, Prompt Builder allows Agentforce Specialists to create prompt templates that dynamically ground responses in Salesforce CRM data (e.g., past purchases) and Data Cloud insights (e.g., product interests) without custom coding. The standard foundation model (e.g., Einstein GPT) can synthesize this data into summaries, leveraging structured and unstructured sources (e.g., email/phone transcripts). Fine- tuning (B) or custom models (C) require code and are unnecessary here, as the use case does not involve unique data patterns requiring model retraining.

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Question # 3

After configuring and saving a Salesforce Agentforce Data Library (regardless of the data source), which components are automatically created and available in Data Cloud?

A. A data pipeline, an indexing engine, and a query processor

B. A data connector, an analytics dashboard, and a workflow rule

C. A data stream, a search index, and a retriever

Answer

C. A data stream, a search index, and a retriever

Explanation

Why is "A data stream, a search index, and a retriever" the correct answer?
When a Salesforce Agentforce Data Library is configured and saved, it automatically creates three essential components in Data Cloud to facilitate AI-driven search and retrieval.

Key Components Created in Data Cloud: Data Stream
This acts as the pipeline that brings data into Data Cloud. It enables real-time data ingestion from sources such as Salesforce records, PDFs, or external databases.

Search Index
After ingestion, data is indexed for efficient search and retrieval. This allows AI models to perform structured queries and retrieve relevant data faster.

Retriever
The retriever is an AI-powered search mechanism that uses the search index to fetch the most relevant data. It ensures that AI-generated responses are grounded in structured, reliable data.

Why Not the Other Options?

# A. A data pipeline, an indexing engine, and a query processor Incorrect because Data Cloud does not use a query processor in the same way as traditional databases. Instead, retrievers handle AI-powered data searches.

# B. A data connector, an analytics dashboard, and a workflow rule Incorrect because these components are not automatically created when setting up a Data Library. Analytics dashboards and workflow rules are separate tools used for reporting and automation.

Agentforce Specialist References
Salesforce AI Specialist Material confirms that a Data Stream, Search Index, and Retriever are created automatically in Data Cloud when configuring a Data Library.

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Question # 4

Universal Containers (UC) wants to use Flow to bring data from unified Data Cloud objects to prompt templates. Which type of flow should UC use?

A. Data Cloud-triggered flow

B. Template-triggered prompt flow

C. Unified-object linking flow

Answer

B. Template-triggered prompt flow

Explanation

In this scenario, Universal Containers wants to bring data from unified Data Cloud objects into prompt templates, and the best way to do that is through a Data Cloud-triggered flow. This type of flow is specifically designed to trigger actions based on data changes within Salesforce Data Cloud objects.

Data Cloud-triggered flows can listen for changes in the unified data model and automatically bring relevant data into the system, making it available for prompt templates. This ensures that the data is both real-time and up-to-date when used in generative AI contexts.

For more detailed guidance, refer to Salesforce documentation on Data Cloud-triggered flows and Data Cloud integrations with generative AI solutions.

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Question # 5

Which business requirement presents a good use case for leveraging Einstein Prompt Builder?

A. Forecast future sales trends based on historical data.

B. Identify potential high-value leads for targeted marketing campaigns.

C. Send reply to a request for proposal via a personalized email.

Answer

C. Send reply to a request for proposal via a personalized email.

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