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Salesforce Agentforce-Specialist Exam Syllabus Topics:| Topic | Details | | Topic 1 | - 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 2 | - 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 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 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 5 | - 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.
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Salesforce Certified Agentforce Specialist Sample Questions (Q195-Q200):NEW QUESTION # 195
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. Generate a Knowledge article based off the prompts that the agent enters to create steps to cancel flights.
- B. Invoke a flow which makes a call to external data to create a Knowledge article.
- C. Execute tasks based on available actions, answering questions using information from accessible Knowledge articles.
Answer: A
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 # 196
Universal Containers (UC) plans to implement prompt templates that utilize the standard foundation models.
What should UC consider when building prompt templates in Prompt Builder?
- A. Include multiple-choice questions within the prompt to test the LLM's understanding of the context.
- B. Ask it to role-play as a character in the prompt template to provide more context to the LLM.
- C. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.
Answer: B
Explanation:
UC is using Prompt Builder with standard foundation models (e.g., via Atlas Reasoning Engine). Let's assess best practices for prompt design.
Option A: Include multiple-choice questions within the prompt to test the LLM's understanding of the context.
Prompt templates are designed to generate responses, not to test the LLM with multiple-choice questions.
This approach is impractical and not supported by Prompt Builder's purpose, making it incorrect.
Option B: Ask it to role-play as a character in the prompt template to provide more context to the LLM.A key consideration in Prompt Builder is crafting clear, context-rich prompts. Instructing the LLM to adopt a role (e.
g., "Act as a sales expert") enhances context and tailors responses to UC's needs, especially with standard models. This is a documented best practice for improving output relevance, making it the correct answer.
Option C: Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.Standard foundation models in Agentforce are pretrained and not user-trainable. Prompt Builder users refine prompts, not the LLM itself, making this incorrect.
Why Option B is Correct:
Role-playing enhances context for standard models, a recommended technique in Prompt Builder for effective outputs, as per Salesforce guidelines.
References:
Salesforce Agentforce Documentation: Prompt Builder > Best Practices - Recommends role-based context.
Trailhead: Build Prompt Templates in Agentforce - Highlights role-playing for clarity.
Salesforce Help: Prompt Design Tips - Suggests contextual roles.
NEW QUESTION # 197
Universal Containers (UC) is looking to improve its sales team's productivity by providing real-time insights and recommendations during customer interactions.
Why should UC consider using Agentforce Sales Agent?
- A. To automate the entire sales process for maximum efficiency
- B. To track customer interactions for future analysis
- C. To streamline the sales process and increase conversion rates
Answer: C
Explanation:
Agentforce Sales Agent provides real-time insights and AI-powered recommendations, which are designed to streamline the sales processand help sales representatives focus on key tasks toincrease conversion rates. It offers features like lead scoring, opportunity prioritization, and proactive recommendations, ensuring that sales teams can interact with customers efficiently and close deals faster.
* Option A: While tracking customer interactions is beneficial, it is only part of the broader capabilities offered by Agentforce Sales Agent and is not the primary objective for improving real-time productivity.
* Option B: Agentforce Sales Agent does not automate the entire sales process but provides actionable recommendations to assist the sales team.
* Option C: This aligns with the tool's core purpose of enhancing productivity and driving sales success.
NEW QUESTION # 198
How should an organization use the Einstein Trust layer to audit, track, and view masked data?
- A. Access the audit trail in Setup and export all user-generated prompts.
- B. In Setup, use Prompt Builder to send a prompt to the LLM requesting for the masked data.
- C. Utilize the audit trail that captures and stores all LLM submitted prompts in Data Cloud.
Answer: C
Explanation:
TheEinstein Trust Layeris designed to ensure transparency, compliance, and security for organizations leveraging Salesforce's AI and generative AI capabilities. Specifically, for auditing, tracking, and viewing masked data, organizations can utilize:
* Audit Trail in Data Cloud: Theaudit trailcaptures and stores all prompts submitted to large language models (LLMs), ensuring that sensitive or masked data interactions are logged. This allows organizations to monitor and audit all AI-generated outputs, ensuring that data handling complies with internal and regulatory guidelines. TheData Cloudprovides the infrastructure for managing and accessing this audit data.
* Why not B?UsingPrompt Builderin Setup to send prompts to the LLM is for creating and managing prompts, not for auditing or tracking data. It does not interact directly with the audit trail functionality.
* Why not C?Although the audit trail can be accessed in Setup, the user-generated prompts are primarily tracked in the Data Cloud for broader control, auditing, and analysis. Setup is not the primary tool for exporting or managing these audit logs.
More information on auditing AI interactions can be found in theSalesforce AI Trust Layerdocumentation, which outlines how organizations can manage and track generative AI interactions securely.
NEW QUESTION # 199
Universal Containers (UC) is using Einstein Generative AI to generate an account summary. UC aims to ensure the content is safe and inclusive, utilizing the Einstein Trust Layer's toxicity scoring to assess the content's safety level.
In the score of 1 indicate?
- A. The response is the most toxic.
- B. The response is the least toxic Einstein Generative AI Toxicity Scoring system, what does a toxicity category.
- C. The response is not toxic.
Answer: A
Explanation:
Einstein Trust Layer's Toxicity Scoring categorizes content on a scale of 0 to 1, where 1 indicates the highest level of toxicity (e.g., harmful, biased, or inappropriate language). This scoring helps organizations filter unsafe AI-generated content. A score of 1 triggers mitigation actions, such as blocking the response or alerting administrators.
* A score of 0 would indicate no toxicity (B is incorrect).
* The scoring system does not use "least toxic" as a category (A is misleading).
Reference:
Salesforce Help Article: Einstein Trust Layer - Toxicity Scoring ("Interpreting Toxicity Scores" section).
Einstein GPT Safety Overview: "Mitigating Harmful Content with Toxicity Detection."
NEW QUESTION # 200
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