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| Section | Weight | Objectives |
|---|---|---|
| Development Lifecycle | 15% | - Deployment: sandbox to production - Monitoring, adoption and optimization - Testing agents in Testing Center - Version control and maintenance |
| Prompt Engineering | 20% | - Grounding techniques and best practices - Prompt Builder usage and use cases - Prompt management and user roles - Prompt template creation: field generation, flex types |
| Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Model Context Protocol (MCP) - Agent API usage scenarios |
| Data Cloud for Agentforce | 20% | - Agentforce Data Library types - Retrievers and search types: keyword, vector, hybrid - Improving response accuracy with data grounding - Unstructured data processing: chunking, indexing |
| AI Agents | 35% | - Agent architecture and reasoning engine - Deterministic controls: filters and variables - Agent User security and permissions - Channel integration: digital experience, email, Slack - Topics and actions configuration - Agent types: Service, Sales, Employee |
>> Actual AI-201 Test Answers <<
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NEW QUESTION # 303
Universal Containers (UC) currently tracks Leads with a custom object. UC is preparing to implement the Sales Development Representative (SDR) Agent. Which consideration should UC keep in mind?
Answer: B
Explanation:
Universal Containers (UC) uses a custom object for Leads and plans to implement the Agentforce Sales Development Representative (SDR) Agent. The SDR Agent is a prebuilt, configurable AI agent designed to assist sales teams by qualifying leads and scheduling meetings. Let's evaluate the options based on its functionality and limitations.
NEW QUESTION # 304
Universal Containers (UC) needs to create a prompt template that provides a detailed product description based on the latest product data. The description will be used in marketing materials to ensure consistency and accuracy. Which prompt template type should UC use?
Answer: A
NEW QUESTION # 305
Universal Containers (UC) plans to answer questions based on similar cases that have been successfully resolved in the past. What should UC consider when implementing this approach?
Answer: B
Explanation:
According to the AgentForce Data Configuration and Retrieval Guide, when an organization like Universal Containers wants to enable its AI agent to answer questions using historical case data, the correct implementation is to create an Unstructured Data Model Object (UDMO) based on the Case object, then index that data for retrieval.
The documentation clearly explains:
"When using previous case records to power AI-driven Q&A or similarity-based retrieval, create a UDMO mapped to the Case object. UDMOs allow the system to process and semantically index unstructured text fields such as Case Description, Resolution, and Comments, enabling the LLM to surface contextually similar resolved cases." This allows the AgentForce retrieval engine to perform semantic searches across historical support data, returning cases that are most contextually relevant to the user's query.
NEW QUESTION # 306
Universal Containers (UC) plans to automatically populate the Description field on the Account object. Which type of prompt template should UC use?
Answer: B
Explanation:
Universal Containers (UC) wants to automatically populate the Description field on the Account object. The AI-driven solution must generate textual data and write it directly into a field.
Field Generation Prompt Template
Primary Use Case: A Field Generation prompt template is specifically designed to create or fill in fields on a record with AI-generated text.
Auto-population: By configuring a Field Generation prompt template, admins can define the instructions, data inputs, and desired output for the AI. The resulting text then populates the specified field, such as the Account Description.
NEW QUESTION # 307
Universal Containers (UC) wants to ensure its compliance team can retrieve exact matches of policy clause numbers from a structured legal document library. Which search type should UC implement?
Answer: B
Explanation:
According to the AgentForce Search Optimization Guide, when the use case requires retrieving exact matches (such as policy clause numbers, legal identifiers, or invoice IDs) from structured data, the recommended approach is to use keyword search. The documentation specifies:
"Keyword search ensures deterministic retrieval of exact term matches from structured fields, preserving precision for identifiers, numeric values, and code references."
NEW QUESTION # 308
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