Test AI-201 Study Guide | AI-201 Lab Questions

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Salesforce AI-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Agents35%- Agent behavior configuration
  • 1. Agent reasoning engine concepts
    • 2. Filters and variables for deterministic behavior
      - Agent setup and orchestration
      • 1. Standard and custom agent actions
        • 2. Standard and custom topics
          Topic 2: Prompt Engineering20%- Grounding techniques
          • 1. Best practices for prompt design
            • 2. Data grounding for reducing hallucinations
              - Prompt Builder usage
              • 1. Prompt templates and configuration
                • 2. Field generation and flex templates
                  Topic 3: Testing, Deployment & Lifecycle15%- Agent lifecycle management
                  • 1. Sandbox to production deployment
                    • 2. Testing and validation strategies
                      Topic 4: Data Cloud & Grounding20%- Data integration for AI agents
                      • 1. Connecting external data sources
                        • 2. Using Data Cloud for retrieval augmentation
                          Topic 5: Governance & Observability10%- AI governance
                          • 1. Monitoring agent behavior
                            • 2. Trust layer and compliance concepts

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                              AI-201 Lab Questions & Free Sample AI-201 Questions

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                              Salesforce Certified Agentforce Specialist Sample Questions (Q23-Q28):

                              NEW QUESTION # 23
                              Universal Containers needs to create Data Cloud reports to understand agent behavior. Which data lake object (DLO) represents an overarching container capturing contiguous interactions with one or more Al agents?

                              Answer: C

                              Explanation:
                              Per the AgentForce Data Cloud Integration Guide, the AI Agent Session (AIAGENTSESSION) object represents an overarching container that tracks a continuous interaction between one or more AI agents and a user. The document describes: "AI Agent Session is the parent container for a contiguous set of AI Agent interactions. It captures metadata, start and end times, and the relationship to individual messages exchanged during the session."


                              NEW QUESTION # 24
                              Universal Containers (UC) wants to enable its sales team to use AI to suggest recommended products from its catalog. Which type of prompt template should UC use?

                              Answer: C

                              Explanation:
                              UC needs an AI solution to suggest products from a catalog for its sales team.


                              NEW QUESTION # 25
                              What should An Agentforce consider when using related list merge fields in a prompt template associated with an Account object in Prompt Builder?

                              Answer: B

                              Explanation:
                              When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field.
                              Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.


                              NEW QUESTION # 26
                              The Agentforce Specialist of Northern Trail Outfitters reviewed the organization's data masking settings within the Configure Data Masking menu within Setup. Upon assessing all of the fields, a few additional fields were deemed sensitive and have been masked within Einstein's Trust Layer.
                              Which steps should the Agentforce Specialist take upon modifying the masked fields?

                              Answer: B

                              Explanation:
                              After modifying masked fields in Einstein's Trust Layer, the next important step is to test and confirm that the responses generated by prompts utilizing the newly masked data still meet quality standards. This ensures that masking sensitive information does not negatively impact the usefulness or accuracy of the AI-generated content. Thorough testing helps identify any issues in prompt performance that could arise due to masking, and adjustments can be made if needed.


                              NEW QUESTION # 27
                              What is the role of the large language model (LLM) in understanding intent and executing an Agent Action?

                              Answer: B

                              Explanation:
                              In Agentforce, the large language model (LLM), powered by the Atlas Reasoning Engine, interprets user requests and drives Agent Actions.


                              NEW QUESTION # 28
                              ......

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