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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Cloud & Grounding	20%	- Data integration for AI agents 1. Using Data Cloud for retrieval augmentation 2. Connecting external data sources
Topic 2: Testing, Deployment & Lifecycle	15%	- Agent lifecycle management 1. Sandbox to production deployment 2. Testing and validation strategies
Topic 3: AI Agents	35%	- Agent behavior configuration 1. Agent reasoning engine concepts 2. Filters and variables for deterministic behavior - Agent setup and orchestration 1. Standard and custom topics 2. Standard and custom agent actions
Topic 4: Prompt Engineering	20%	- Grounding techniques 1. Best practices for prompt design 2. Data grounding for reducing hallucinations - Prompt Builder usage 1. Field generation and flex templates 2. Prompt templates and configuration
Topic 5: Governance & Observability	10%	- AI governance 1. Trust layer and compliance concepts 2. Monitoring agent behavior

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Salesforce Certified Agentforce Specialist AI-201 Prüfungsfragen mit Lösungen (Q202-Q207):

202. Frage
Universal Containers built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors. What is the cause of the random nature of this error?

A. The number of tokens generated by the dynamic nature of the prompt template will vary by record.
B. The number of tokens that can be processed by the LLM varies with total user demand.
C. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.

Antwort: A

Begründung:
In Salesforce Agentforce, prompt templates are used to generate dynamic responses or field values by leveraging an LLM, often with grounding data from Salesforce records or external sources. The scenario describes a Field Generation prompt template that fails intermittently with token limit errors, indicating that the issue is tied to exceeding the LLM's token capacity (e.g., input + output tokens). The random nature of these failures suggests variability in the token count across different records, which is directly addressed by Option B.
Prompt templates in Agentforce can be dynamic, meaning they pull in record-specific data (e.g., customer names, descriptions, or other fields) to generate output. Since the data varies by record-some records might have short text fields while others have lengthy ones-the total number of tokens (words, characters, or subword units processed by the LLM) fluctuates. When the token count exceeds the LLM's limit (e.g., 4,096 tokens for some models), the process fails, but this only happens for records with higher token-generating data, explaining the randomness.

203. Frage
A company wants to retrieve patient history details to augment the Al agent response. [he company wants to leverage the Data Cloud search index feature. What is best practice when considering retrieval-augrmented generation (RAG) for information that may contain personally identifiable information (PII)?

A. Mask sensitive fields and index only non-PII data.
B. Encrypt embeddings, but still index PII records.
C. Depend on the agent's prompt to avoid exposing PII.

Antwort: A

Begründung:
According to the AgentForce Data Governance and RAG Security Guidelines, when implementing retrieval-augmented generation (RAG) using Data Cloud search indexes, best practice is to ensure that personally identifiable information (PII) and other sensitive data are never indexed or embedded in the retrieval system.
The documented recommendation is to mask or exclude sensitive fields before creating embeddings or indexing content. This prevents the large language model (LLM) from accessing or generating responses that could inadvertently expose confidential information. Masking can include redacting names, IDs, contact details, or any regulated medical information.

204. Frage
Universal Containers (UC) wants to create a new Sales Email prompt template in Prompt Builder using the "Save As" function. However, UC notices that the new template produces different results compared to the standard Sales Email prompt due to missing hyperparameters. What should UC do to ensure the new prompt template produces results comparable to the standard Sales Email prompts?

A. Revert to using the standard template without modifications.
B. Manually add the hyperparameters to the new template.
C. Use Model Playground to create a model configuration with the specified parameters.

Antwort: B

Begründung:
When Universal Containers creates a new Sales Email prompt template using the "Save As" function, missing hyperparameters can result in different outputs. To ensure the new prompt produces comparable results to the standard Sales Email prompt, the Agentforce Specialist should manually add the necessary hyperparameters to the new template.
Hyperparameters like Temperature, Frequency Penalty, and Presence Penalty directly affect how the AI generates responses. Ensuring that these are consistent with the standard template will result in similar outputs.

205. Frage
Northern Trail Outfitters (NTO) wants to configure Einstein Trust Layer in its production org but is unable to see the option on the Setup page. After provisioning Data Cloud, which step must an Al Specialist take to make this option available to NTO?

A. Turn on Prompt Builder.
B. Turn on Agent.
C. Turn on Einstein Generative AI.

Antwort: C

Begründung:
For Northern Trail Outfitters (NTO) to configure the Einstein Trust Layer, the Einstein Generative AI feature must be enabled. The Einstein Trust Layer is closely tied to generative AI capabilities, ensuring that AI-generated content complies with data privacy, security, and trust standards.

206. Frage
Universal Containers would like to route SMS text messages to a service rep from an Agentforce Service Agent. Which Service Channel should the company use in the flow to ensure it's routed properly?

A. Live Agent
B. Route Work Action
C. Messaging

Antwort: C

Begründung:
UC wants to route SMS text messages from an Agentforce Service Agent to a service rep using a flow.

207. Frage
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