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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Agent API usage scenarios - Model Context Protocol (MCP) |
| Topic 2: Prompt Engineering | 20% | - Prompt Builder usage and use cases - Prompt management and user roles - Prompt template creation: field generation, flex types - Grounding techniques and best practices |
| Topic 3: AI Agents | 35% | - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack - Agent User security and permissions - Agent types: Service, Sales, Employee - Deterministic controls: filters and variables - Topics and actions configuration |
| Topic 4: Data Cloud for Agentforce | 20% | - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing - Agentforce Data Library types - Improving response accuracy with data grounding |
| Topic 5: Development Lifecycle | 15% | - Deployment: sandbox to production - Testing agents in Testing Center - Monitoring, adoption and optimization - Version control and maintenance |
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問題 #102
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?
答案：A
解題說明：
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.
問題 #103
What is automatically created when a custom search index is created in Data Cloud?
答案：A
解題說明：
In Salesforce Data Cloud, a custom search index is created to enable efficient retrieval of data (e.g., documents, records) for AI-driven processes, such as grounding Agentforce responses.
問題 #104
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. What does a safety category score of 1 indicate in the Einstein Generative Toxicity Score?
答案：C
解題說明：
In the Einstein Trust Layer, the toxicity scoring system is used to evaluate the safety level of content generated by AI, particularly to ensure that it is non-toxic, inclusive, and appropriate for business contexts. A toxicity score of 1 indicates that the content is deemed safe.
The scoring system ranges from 0 (unsafe) to 1 (safe), with intermediate values indicating varying degrees of safety. In this case, a score of 1 means that the generated content is fully safe and meets the trust and compliance guidelines set by the Einstein Trust Layer.
For further reference, check Salesforce's official Einstein Trust Layer documentation regarding toxicity scoring for AI-generated content.
問題 #105
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 Agent capability helps the agent accomplish this?
答案：A
解題說明：
In this scenario, the Agent capability that best helps the agent is its ability to execute tasks based on available actions and answer questions using data from Knowledge articles. Agent 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.
問題 #106
Before activating a custom copilot action, An Agentforce would like is to understand multiple real- world user utterances to ensure the action being selected appropriately. Which tool should the Agentforce Specialist recommend?
答案：C
解題說明：
Model Playground (specifically within the context of Generative AI and Copilot in Salesforce) allows you to test and refine the behavior of your AI models and, by extension, how your copilot actions interpret and respond to different user inputs (utterances). It's a sandbox environment where you can:
Input various user utterances.
See how the underlying Large Language Model (LLM) and the copilot's reasoning engine classify those utterances.
Observe which actions are triggered by those utterances.
Adjust the action instructions and examples to improve the copilot's understanding and ensure the correct action is chosen for specific user requests. This iterative testing is crucial for ensuring the action performs as expected in real-world scenarios.
問題 #107
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