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| Section | Weight | Objectives |
|---|---|---|
| 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 |
| Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Agent API usage scenarios - Model Context Protocol (MCP) |
| Development Lifecycle | 15% | - Monitoring, adoption and optimization - Testing agents in Testing Center - Deployment: sandbox to production - Version control and maintenance |
| Prompt Engineering | 20% | - Prompt management and user roles - Prompt Builder usage and use cases - Prompt template creation: field generation, flex types - Grounding techniques and best practices |
| AI Agents | 35% | - Topics and actions configuration - Agent architecture and reasoning engine - Agent types: Service, Sales, Employee - Agent User security and permissions - Channel integration: digital experience, email, Slack - Deterministic controls: filters and variables |
우선 우리ExamPassdump 사이트에서Salesforce AI-201관련자료의 일부 문제와 답 등 샘플을 제공함으로 여러분은 무료로 다운받아 체험해보실 수 있습니다.체험 후 우리의ExamPassdump에 신뢰감을 느끼게 됩니다. ExamPassdump에서 제공하는Salesforce AI-201덤프로 시험 준비하시면 편안하게 시험을 패스하실 수 있습니다.
질문 # 204
For an Agentforce Data Library that contains uploaded files, what occurs once it is created and configured?
정답：C
설명：
In Salesforce Agentforce, a Data Library is a feature that allows organizations to upload files (e.g., PDFs, documents) to be used as grounding data for AI-driven agents. Once the Data Library is created and configured, the uploaded files are indexed to make their content searchable and usable by the AI (e.g., for retrieval-augmented generation or prompt enhancement). The key question is where this indexing occurs. Salesforce Agentforce integrates tightly with Data Cloud, a unified data platform that includes a vector database optimized for storing and indexing unstructured data like uploaded files. When a Data Library is set up, the files are ingested and indexed into Data Cloud's vector database, enabling the AI to efficiently retrieve relevant information from them during conversations or actions.
질문 # 205
Coral Cloud Resorts (CCR) wants to configure its agent so that booking actions are only available when a customer's membership tier is "Premium" or "Elite". This business rule must be enforced deterministically. What should CCR implement?
정답：A
설명：
Per the AgentForce Configuration and Control Flow Guide, enforcing deterministic business rules
- such as restricting certain actions based on a data condition-requires using context variables with conditional filters. The guide specifies: "Use context variables mapped to relevant Salesforce fields to store state information. Then apply conditional filters to ensure actions execute only when specific conditions (e.g., membership tier) are met." This ensures the rule is deterministic, meaning the action cannot trigger if the condition is not satisfied.
질문 # 206
An Agentforce implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads based on their interactions and data stored in Salesforce.
The Agentforce Specialist needs to configure the system to use the most accurate and up-to-date information for email generation. Which grounding technique should the Agentforce Specialist use?
정답：B
설명：
For Einstein Sales Emails to generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real-time data. The most appropriate technique in this case is Ground with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
Record Merge Fields ensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
Apex Merge Fields are typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
Automatic grounding using Draft with Einstein is a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data like Record Merge Fields.
질문 # 207
An Agentforce is tasked to optimize a business process flow by assigning actions to agents within the Salesforce Agentforce Platform. What is the correct method for the Agentforce Specialist to assign actions to an Agent?
정답：A
설명：
In the Salesforce Agentforce Platform, assigning actions to Agents requires mapping them through Topics in Agent Builder. Topics act as the container that links an Agent's conversational intent with the specific actions it can perform. By first assigning an action to a Topic in Agent Builder, the Agentforce Specialist ensures that the Agent knows when and how to trigger the action during the business process flow.
질문 # 208
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?
정답：C
설명：
The Agentforce Specialist needs a comprehensive view of user interactions, errors, and action issues for troubleshooting.
질문 # 209
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