SALESFORCE AGENTFORCE-SPECIALIST PDF VERSION, NEW AGENTFORCE-SPECIALIST TEST PATTERN

Salesforce Agentforce-Specialist Pdf Version, New Agentforce-Specialist Test Pattern

Salesforce Agentforce-Specialist Pdf Version, New Agentforce-Specialist Test Pattern

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Tags: Agentforce-Specialist Pdf Version, New Agentforce-Specialist Test Pattern, Agentforce-Specialist Valid Exam Test, Latest Agentforce-Specialist Dumps Ebook, Test Agentforce-Specialist Practice

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Salesforce Certified Agentforce Specialist Sample Questions (Q111-Q116):

NEW QUESTION # 111
An Al Specialist is tasked with creating a prompt template for a sales team. The template needs to generate a summary of all related opportunities for a given Account.
Which grounding technique should the Al Specialist use to include data from the related list of opportunities in the prompt template?

  • A. Use the merge fields to reference a custom related list of opportunities.
  • B. Use formula fields to reference the Einstein related list of opportunities.
  • C. Use merge fields to reference the default related list of opportunities.

Answer: C

Explanation:
In Salesforce, when creating a prompt template for the sales team, you can include data from related objects such as Opportunities that are linked to an Account. The best method to ground the AI model and provide relevant information from related records, like Opportunities, is by usingmerge fields.
Merge fields in Salesforce allow you to dynamically reference data from a record or related records, like Opportunities for a given Account. In this scenario, theAgentforce Specialistneeds to pull data from the default related list of Opportunitiesassociated with the Account. This is achieved by using merge fields, which pull in data from the standard relationship Salesforce creates between Accounts and Opportunities.
Option A (referencing a custom related list) and Option C (using formula fields with Einstein-related lists) do not align with the standard, practical grounding method for this task. Custom lists would require additional configurations not typically necessary for a basic use case, and formula fields are typically not used to directly fetch related list data for prompt generation in templates.The standard and straightforward method is using merge fields tied to the default related list of opportunities.
Salesforce References:
* Merge Fields in Templates:https://help.salesforce.com/s/articleView?id=000387601&type=1
* Grounding Data in Prompts:https://developer.salesforce.com/docs/atlas.en-us.salesforce_ai.meta
/salesforce_ai/grounding_data_prompts


NEW QUESTION # 112
An Agentforce Specialist wants to troubleshoot their Agent's performance. Where should the Agentforce Specialist go to access all user interactions with the Agent, including Agent errors, incorrectly triggered actions, and incomplete plans?

  • A. Plan Canvas
  • B. Agent Settings
  • C. Event Logs

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:The Agentforce Specialist needs a comprehensive view of user interactions, errors, and action issues for troubleshooting. Let's evaluate the options.
* Option A: Plan CanvasPlan Canvas in Agent Builder visualizes an agent's execution plan for a single interaction, useful for design but not for aggregated troubleshooting data like errors or all interactions, making it incorrect.
* Option B: Agent SettingsAgent Settings configure the agent (e.g., topics, channels), not provide interaction logs or error details. This is for setup, not analysis, making it incorrect.
* Option C: Event LogsEvent Logs in Agentforce (accessible via Setup or Agent Analytics) record all user interactions, including errors, incorrectly triggered actions, and incomplete plans. They provide detailed telemetry (e.g., timestamps, action outcomes) for troubleshooting performance issues, making this the correct answer.
Why Option C is Correct:Event Logs offer the full scope of interaction data needed for troubleshooting, as per Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Agent Analytics > Event Logs- Details interaction and error logging.
* Trailhead: Monitor and Optimize Agentforce Agents- Recommends Event Logs for troubleshooting.
* Salesforce Help: Agentforce Performance- Confirms logs for diagnostics.


NEW QUESTION # 113
Universal Containers (UC) wants to ensure the effectiveness, reliability, and trust of its agents prior to deploying them in production. UC would like to efficiently test a large and repeatable number of utterances.
What should the Agentforce Specialist recommend?

  • A. Leverage the Agent Large Language Model (LLM) UI and test UC's agents with different utterances prior to activating the agent.
  • B. Deploy the agent in a QA sandbox environment and review the Utterance Analysis reports to review effectiveness.
  • C. Create a CSV file with UC's test cases in Agentforce Testing Center using the testing template.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:The goal of Universal Containers (UC) is to test its Agentforce agents for effectiveness, reliability, and trust before production deployment, with a focus on efficiently handling alarge and repeatable number of utterances. Let's evaluate each option against this requirement and Salesforce's official Agentforce tools and best practices.
* Option A: Leverage the Agent Large Language Model (LLM) UI and test UC's agents with different utterances prior to activating the agent.While Agentforce leverages advanced reasoning capabilities (powered by the Atlas Reasoning Engine), there's no specific "Agent Large Language Model (LLM) UI" referenced in Salesforce documentation for testing agents. Testing utterances directly within an LLM interface might imply manual experimentation, but this approach lacks scalability and repeatability for a large number of utterances. It's better suited for ad-hoc testing of individual responses rather than systematic evaluation, making it inefficient for UC's needs.
* Option B: Deploy the agent in a QA sandbox environment and review the UtteranceAnalysis reports to review effectiveness.Deploying an agent in a QA sandbox is a valid step in the development lifecycle, as sandboxes allow testing in a production-like environment without affecting live data.
However, "Utterance Analysis reports" is not a standard term in Agentforce documentation. Salesforce provides tools like Agent Analytics or User Utterances dashboards for post-deployment analysis, but these are more about monitoring live performance than pre-deployment testing. This option doesn't explicitly address how to efficiently test alarge and repeatable number of utterancesbefore deployment, making it less precise for UC's requirement.
* Option C: Create a CSV file with UC's test cases in Agentforce Testing Center using the testing template.The Agentforce Testing Center is a dedicated tool within Agentforce Studio designed specifically for testing autonomous AI agents. According to Salesforce documentation, Testing Center allows users to upload a CSV file containing test cases (e.g., utterances and expected outcomes) using a provided template. This enables the generation and execution of hundreds of synthetic interactions in parallel, simulating real-world scenarios. The tool evaluates how the agent interprets utterances, selects topics, and executes actions, providing detailed results for iteration. This aligns perfectly with UC's need for efficiency (bulk testing via CSV), repeatability (standardized test cases), and reliability (systematic validation), ensuring the agent is production-ready. This is the recommended approach per official guidelines.
Why Option C is Correct:The Agentforce Testing Center is explicitly built for pre-deployment validation of agents. It supports bulk testing by allowing users to upload a CSV with utterances, which is then processed by the Atlas Reasoning Engine to assess accuracy and reliability. This method ensures UC can systematically test a large dataset, refine agent instructions or topics based on results, and build trust in the agent's performance- all before production deployment. This aligns with Salesforce's emphasis on testing non-deterministic AI systems efficiently, as noted in Agentforce setup documentation and Trailhead modules.
References:
* Salesforce Trailhead: Get Started with Salesforce Agentforce Specialist Certification Prep- Details the use of Agentforce Testing Center for testing agents with synthetic interactions.
* Salesforce Agentforce Documentation: Agentforce Studio > Testing Center- Explains how to upload CSV files with test cases for parallel testing.
* Salesforce Help: Agentforce Setup > Testing Autonomous AI Agents- Recommends Testing Center for pre-deployment validation of agent effectiveness and reliability.


NEW QUESTION # 114
Universal Containers wants to implement a solution in Salesforce with a custom UX that allows users to enter a sales order number. Subsequently, the system will invoke a custom prompt template to create and display a summary of the sales order header and sales order details. Which solution should an Agentforce Specialist implement to meet this requirement?

  • A. Create an autolaunched flow and invoke the prompt template using the standard "Prompt Template" flow action.
  • B. Create a template-triggered prompt flow and invoke the prompt template using the standard "Prompt Template" flow action.
  • C. Create a screen flow to collect the sales order number and invoke the prompt template using the standard "Prompt Template" flow action.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:Universal Containers (UC) requires a solution with a custom UXfor users to input a sales order number, followed by invoking a custom prompt template to generate and display a summary. Let's evaluate each option based on this requirement and Salesforce Agentforce capabilities.
* Option A: Create an autolaunched flow and invoke the prompt template using the standard
"Prompt Template" flow action.An autolaunched flow is a background process that runs without user interaction, triggered by events like record updates or platform events. While it can invoke a prompt template using the "Prompt Template" flow action (available in Flow Builder to integrate Agentforce prompts), it lacks a user interface. Since UC explicitly needs acustom UXfor users to enter a sales order number, an autolaunched flow cannot meet this requirement, as it doesn't provide a way for users to input data directly.
* Option B: Create a template-triggered prompt flow and invoke the prompt template using the standard "Prompt Template" flow action.There's no such thing as a "template-triggered prompt flow" in Salesforce terminology. This appears to be a misnomer or typo in the original question. Prompt templates in Agentforce are reusable configurations that define how an AI processes input data, but they are not a type of flow. Flows (like autolaunched or screen flows) can invoke prompt templates, but
"template-triggered" is not a recognized flow type in Salesforce documentation. This option is invalid due to its inaccurate framing.
* Option C: Create a screen flow to collect the sales order number and invoke the prompt template using the standard "Prompt Template" flow action.A screen flow provides a customizable user interface within Salesforce, allowing users to input data (e.g., a sales order number) via input fields.
The "Prompt Template" flow action, available in Flow Builder, enables integration with Agentforce by passing user input (the sales order number) to a custom prompt template. The prompt template can then query related data (e.g., sales order header and details) and generate a summary, which can be displayed back to the user on a subsequent screen. This solution meets UC's need for a custom UX and seamless integration with Agentforce prompts, making it the best fit.
Why Option C is Correct:Screen flows are ideal for scenarios requiring user interaction and custom interfaces, as outlined in Salesforce Flow documentation. The "Prompt Template" flow action enables Agentforce's AI capabilities within the flow, allowing UC to collect the sales order number, process it via a prompt template, and display the result-all within a single, user-friendly solution. This aligns with Agentforce best practices for integrating AI-driven summaries into user workflows.
References:
* Salesforce Help: Flow Builder > Prompt Template Action- Describes how to use the "Prompt Template" action in flows to invoke Agentforce prompts.
* Trailhead: Build Flows with Prompt Templates- Highlights screen flows for user-driven AI interactions.
* Agentforce Studio Documentation: Prompt Templates- Explains how prompt templates process input data for summaries.


NEW QUESTION # 115
An Agentforce at Universal Containers is trying to set up a new Field Generation prompt template. They take the following steps.
1. Create a new Field Generation prompt template.
2. Choose Case as the object type.
3. Select the custom field AI_Analysis_c as the target field.
After creating the prompt template, theAgentforce Specialistsaves, tests, and activates it. Howsoever, when they go to a case record, the AI Analysis field does not show the (Sparkle) icon on the Edit pencil. When theAgentforce Specialistwas editing the field, it was behaving as a normal field.
Which critical step did theAgentforce Specialistmiss?

  • A. They forgot that the Case Object is not supported for Add generation as Feinstein Service Replies should be used instead.
  • B. They forgot to edit the Lightning page layout and associate the field to a prompt template
  • C. They forgot to reactivate the Lightning page layout for the Case object after activating their Field Generation prompt template.

Answer: B

Explanation:
For Field Generation prompt templates to display the Sparkle icon (indicating AI-generated content), the target field must be explicitly associated with the prompt template on the Lightning page layout. Even if the prompt template is activated, failing to add the field to the page layout and link it to the template will result in the field behaving as a standard field. Salesforce documentationemphasizes that page layout configuration is mandatory to enable AI-driven field interactions.
* Reactivating the layout (A) is unnecessary unless the layout itself was modified after activation.
* Case objects are supported for Field Generation (B is incorrect).


NEW QUESTION # 116
......

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