100% Pass 2025 The Best Agentforce-Specialist: Practical Salesforce Certified Agentforce Specialist Information

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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 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 3	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 4	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.
Topic 5	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.

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Salesforce Certified Agentforce Specialist Sample Questions (Q173-Q178):

NEW QUESTION # 173
What is the primary function of the planner service in the Agent system?

A. Offering real-time language translation during conversations
B. Generating record queries based on conversation history
C. Identifying copilot actions to respond to user utterances

Answer: C

Explanation:
The primary function of the planner service in the Agent system is to identify copilot actions that should be taken in response to user utterances. This service is responsible for analyzing the conversation and determining the appropriate actions (such as querying records, generating a response, or taking another action) that the Agent should perform based on user input.

NEW QUESTION # 174
In addition to Recipient and Sender, which object should An Agentforce utilize for inserting merge fields into a Sales email template prompt?

A. Recipient Account
B. User Organization
C. Recipient Opportunities

Answer: A

Explanation:
* Sales Email Template Use Case:When creating a Sales email template (especially for outreach or follow-up), you often need to reference relevant details about the Account linked to the recipient.
* Standard Merge Fields in Salesforce Email Templates:
* Recipient(Contact, Lead, or Person receiving the email)
* Sender(User sending the email)
* Recipient Account(the Account related to that Contact, providing company-level details and other relevant data)
* Why Recipient Account?
* For Sales communications, referencing theAccountdata (e.g., Account name, industry, or other custom fields) in an email is very common.
* This is especially important for B2B scenarios where the Contact is tied to an Account.
* "Recipient Opportunities" could be multiple, so it's less direct for standard email merges. The
"User Organization" is more generic internal information, not typically inserted for personalization to the recipient.
* References and Study Resources:
* Salesforce Help & Training#Email Templates: Merge Fields
* Salesforce Trailhead#"Create and Customize Email Templates in Sales Cloud"
* SalesforceAgentforce SpecialistStudy Resources(covers recommended best practices for leveraging standard objects like Account in AI-powered or prompt-based communications)

NEW QUESTION # 175
An Agentforce is creating a custom action for Agentforce.
Which setting should theAgentforce Specialisttest and iterate on to ensure the action performs as expected?

A. Action Name
B. Action Input
C. Action Instructions

Answer: C

Explanation:
When creating a custom action for Einstein Bots in Salesforce (including Agentforce), ActionInstructions are critical for defining how the bot processes and executes the action. These instructions guide the bot on the logic to follow, such as API calls, data transformations, or conditional steps. Testing and iterating on the instructions ensures the bot understands how to handle dynamic inputs, external integrations, and decision- making.
Salesforce documentation emphasizes that Action Instructions directly impact the bot's ability to execute workflows accurately. For example, poorly defined instructions may lead to incorrect API payloads or failure to parse responses. The Einstein Bot Developer Guide highlights that refining instructions is essential for aligning the bot's behavior with business requirements.
In contrast:
* Action Name (A) is a static identifier and does not affect functionality.
* Action Input (B) defines parameters passed to the action but does not dictate execution logic.
Thus, iterating on Action Instructions (C) ensures the action performs as expected.

NEW QUESTION # 176
Universal Containers built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors. What is the cause of the random nature of this error?

A. The number of tokens generated by the dynamic nature of the prompt template will vary by record.
B. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.
C. The number of tokens that can be processed by the LLM varies with total user demand.

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:In Salesforce Agentforce, prompt templates are used to generate dynamic responses or field values by leveraging an LLM, often with grounding data from Salesforce records or external sources. The scenario describes a Field Generation prompt template that fails intermittently with token limit errors, indicating that the issue is tied to exceeding the LLM's token capacity (e.g., input + output tokens). Therandom natureof these failures suggests variability in the token count across different records, which is directly addressed by Option B.
Prompt templates in Agentforce can be dynamic, meaning they pull in record-specific data (e.g., customer names, descriptions, or other fields) to generate output. Since the data varies by record-some records might have short text fields while others have lengthy ones-the total number of tokens (words, characters, or subword units processed by the LLM) fluctuates. When the token count exceeds the LLM's limit (e.g., 4,096 tokens for some models), the process fails, but this only happens for records with higher token-generating data, explaining the randomness.
* Option A: Switching to a "Flex" template type might sound plausible, but Salesforce documentation does not define "Flex" as a specific template type for handling token variability in this context (there are Flow-based templates, but they're unrelated to token limits). This option is a distractor and not a verified solution.
* Option C: The LLM's token processing capacity is fixed per model (e.g., a set limit like 128,000 tokens for advanced models) and does not vary with user demand. Demand might affect performance or availability, but not the token limit itself.
Option B is the correct answer because it accurately identifies the dynamic nature of the prompt template as the root cause of variable token counts leading to random failures.
References:
* Salesforce Agentforce Documentation: "Prompt Templates" (Salesforce Help:https://help.salesforce.com
/s/articleView?id=sf.agentforce_prompt_templates.htm&type=5)
* Trailhead: "Build Prompt Templates for Agentforce"(https://trailhead.salesforce.com/content/learn
/modules/build-prompt-templates-for-agentforce)

NEW QUESTION # 177
A service agent is looking at a custom object that stores travel information. They recently received a weather alert and now need to cancel flights for the customers that are related with this itinerary. The service agent needs to review the Knowledge articles about canceling and rebooking the customer flights.
Which Einstein Copilot capability helps the agent accomplish this?

A. Invoke a flow which makes a call to external data to create a Knowledge article.
B. Generate a Knowledge article based off the prompts that the agent enters to create steps to cancel flights.
C. Execute tasks based on available actions, answering questions using information from accessible Knowledge articles.

Answer: B

Explanation:
In this scenario, theEinstein Copilotcapability that best helps the agent is its ability toexecute tasks based on available actionsandanswer questionsusing data from Knowledge articles. Einstein Copilot can assist the service agent by providing relevant Knowledge articles on canceling and rebooking flights, ensuring that the agent has access to the correct steps and procedures directly within the workflow.
This feature leverages the agent's existing context (the travel itinerary) and provides actionable insights or next steps from the relevant Knowledge articles to help the agent quickly resolve the customer's needs.
The other options are incorrect:
* Brefers to invoking a flow to create a Knowledge article, which is unrelated to the task of retrieving existing Knowledge articles.
* Cfocuses on generating Knowledge articles, which is not the immediate need for this situation where the agent requires guidance on existing procedures.
References:
* Salesforce Documentation onEinstein Copilot
* Trailhead Module onEinstein for Service

NEW QUESTION # 178
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