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Test Agentforce-Specialist Dumps Pdf - Free Agentforce-Specialist Exam Dumps

The Agentforce-Specialist study questions included in the different versions of the PDF，Software and APP online which are all complete and cover up the entire syllabus of the exam. And every detail of these three vesions are perfect for you to practice and prapare for the exam. If you want to have a try before you pay for the Agentforce-Specialist Exam Braindumps, you can free download the demos which contain a small part of questions from the Agentforce-Specialist practice materials. And you can test the functions as well.

Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic
Details

Topic 1

Agentforce and Service Cloud: This section measures the skills of AI Engineers and focuses on building agents that answer questions based on Knowledge articles and connecting them to digital channels. It also covers identifying the correct generative AI features in Agentforce for Service Cloud scenarios.

Topic 2

Agentforce Concepts: This section assesses the skills of AI Engineers and covers how Agentforce works, including its reasoning engine, standard and custom topics, agent actions, and user security management. It also includes testing and deploying agents from sandbox to production environments.

Topic 3

Agentforce and Data Cloud: This section measures the skills of AI Developers and addresses how Agentforce integrates with Data Cloud to improve response accuracy and personalize answers. It involves grounding with retrievers in Data Cloud to enhance agent performance.

Topic 4

Prompt Engineering: This section measures the skills of AI Developers and focuses on prompt engineering techniques. It covers identifying when to use Prompt Builder, managing prompt templates, selecting appropriate grounding techniques, and explaining the process for creating and executing prompt templates.

Topic 5

Agentforce and Sales Cloud: This section assesses the skills of AI Developers and covers identifying the correct generative AI features in Agentforce for Sales Cloud scenarios. It also includes determining when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches.

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Quiz Agentforce-Specialist - Salesforce Certified Agentforce Specialist –The Best Test Dumps Pdf

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Salesforce Certified Agentforce Specialist Sample Questions (Q83-Q88):

NEW QUESTION # 83
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?

A. Configure data masking in the Einstein Trust Layer setup.
B. Enable data masking for sandbox refreshes.
C. Add new data masking rules in LLM setup.

Answer: A

Explanation:
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, the Agentforce Specialist should configure thedata maskingrules within theEinstein Trust Layer.
TheEinstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
Salesforce Agentforce Specialist References:
For more information, refer to:https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer_data_masking.htm

NEW QUESTION # 84
In Model Playground, which hyperparameters of an existing
Salesforce-enabled foundational model can An Agentforce change?

A. Temperature, Frequency Penalty, Presence Penalty
B. Temperature, Top-k sampling, Presence Penalty
C. Temperature, Frequency Penalty, Output Tokens

Answer: A

Explanation:
InModel Playground, An Agentforce working with a Salesforce-enabled foundational model has control over specific hyperparameters that can directly affect the behavior of the generative model:
* Temperature: Controls the randomness of predictions. A higher temperature leads to more diverse outputs, while a lower temperature makes the model's responses more focused and deterministic.
* Frequency Penalty: Reduces the likelihood of the model repeating the same phrases or outputs frequently.
* Presence Penalty: Encourages the model to introduce new topics in its responses, rather than sticking with familiar, previously mentioned content.
These hyperparameters are adjustable to fine-tune the model's responses, ensuring that it meets the desired behavior and use case requirements. Salesforce documentation confirms that these three are the key tunable hyperparameters in the Model Playground.
For more details, refer toSalesforce AI Model Playgroundguidance from Salesforce's official documentation on foundational model adjustments.

NEW QUESTION # 85
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process.
How should An Agentforce apply the power of conversational AI to this use case?

A. Configure the Integration Flow Standard Action in Agent.
B. Create a custom copilot action which calls a flow.
C. Create a Flex prompt template in Prompt Builder.

Answer: B

Explanation:
To enableUniversal Containersservice agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is tocreate a custom copilot action that calls the flow. This action will allowAgentto interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
* Option Bis correct because it enables integration betweenAgentand the flow that connects to Oracle ERP.
* Option A(Flex prompt template) is more suited for static responses and not for invoking flows.
* Option C(Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.
:
Salesforce Agent Actions:https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm

NEW QUESTION # 86
Universal Containers wants to use an external large language model (LLM) in Prompt Builder.
What should An Agentforce recommend?

A. Use Flow and External Services to bring data from an external LLM.
B. Use Apex to connect to an external LLM and ground the prompt.
C. Use BYO-LLM functionality in Einstein Studio.

Answer: C

Explanation:
Bring Your Own Large Language Model (BYO-LLM) functionality in Einstein Studio allows organizations to integrate and use external large language models (LLMs) within the Salesforce ecosystem.
Universal Containers can leverage this feature to connect and ground prompts with external LLMs, allowing for custom AI model use cases and seamless integration with Salesforce data.
* Option B is the correct choice as Einstein Studio provides a built-in feature to work with external models.
* Option A suggests using Apex, but BYO-LLM functionality offers a more streamlined solution.
* Option C focuses on Flow and External Services, which is more about data integration and isn't ideal for working with LLMs.
:
Salesforce Einstein Studio BYO-LLM Documentation: https://help.salesforce.com/s/articleView?id=sf.
einstein_studio_llm.htm

NEW QUESTION # 87
What is the importance of Action Instructions when creating a custom Agent action?

A. Action Instructions define the expected user experience of an action.
B. Action Instructions tell the user how to call this action in a conversation.
C. Action Instructions tell the large language model (LLM) which action to use.

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:In Salesforce Agentforce, custom Agent actions are designed to enable AI-driven agents to perform specific tasks within a conversational context.Action Instructionsare a critical component when creating these actions because they define the expected user experience by outlining how the action should behave, what it should accomplish, and how it interacts with the end user. These instructions act as a blueprint for the action's functionality, ensuring that it aligns with the intended outcome and provides a consistent, intuitive experience for users interacting with the agent. For example, if the action is to "schedule a meeting," the Action Instructions might specify the steps (e.g., gather date and time, confirm with the user) and the tone (e.g., professional, concise), shaping the user experience.
* Option B: While Action Instructions might indirectly influence how a user invokes an action (e.g., by making it clear what inputs are needed), they are not primarily about telling the user how to call the action in a conversation. That's more related to user training or interface design, not the instructions themselves.
* Option C: The large language model (LLM) relies on prompts, parameters, and grounding data to determine which action to execute, not the Action Instructions directly. The instructions guide the action's design, not the LLM's decision-making process at runtime.
Thus, Option A is correct as it emphasizes the role of Action Instructions in defining the user experience, which is foundational to creating effective custom Agent actions in Agentforce.
References:
* Salesforce Agentforce Documentation: "Create Custom Agent Actions" (Salesforce Help:https://help.
salesforce.com/s/articleView?id=sf.agentforce_custom_actions.htm&type=5)
* Trailhead: "Agentforce Basics" module (https://trailhead.salesforce.com/content/learn/modules
/agentforce-basics)

NEW QUESTION # 88
......

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