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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Topic 2: AI Agents | 35% | - Agent setup and orchestration
|
| Topic 3: Governance & Observability | 10% | - AI governance
|
| Topic 4: Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
| Topic 5: Prompt Engineering | 20% | - Prompt Builder usage
|
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NEW QUESTION # 180
Universal Containers (UC) wants to use Generative AI Salesforce functionality to reduce Service Agent handling time by providing recommended replies based on the existing Knowledge articles.
On which AI capability should UC train the service agents?
Answer: B
Explanation:
Service Replies (specifically Einstein Service Replies) is the Salesforce Generative AI functionality designed to automatically draft responses for service agents in real-time, based on contextual information, including existing knowledge articles. This directly addresses Universal Containers' need to reduce handling time by providing recommended replies grounded in their knowledge base
NEW QUESTION # 181
An Agentforce has created a copilot custom action using flow as the reference action type.
However, it is not delivering the expected results to the conversation preview, and therefore needs troubleshooting. What should the Agentforce Specialist do to identify the root cause of the problem?
Answer: C
Explanation:
When troubleshooting a copilot custom action using flow as the reference action type, enabling dynamic debugging within Copilot Builder's Dynamic Panel is the most effective way to identify the root cause. By turning on dynamic debugging, the Agentforce Specialist can see detailed logs showing both the inputs and outputs of the flow, which helps identify where the action might be failing or not delivering the expected results.
NEW QUESTION # 182
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process. How should An Agentforce apply the power of conversational AI to this use case?
Answer: A
Explanation:
To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Agent to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
NEW QUESTION # 183
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?
Answer: B
Explanation:
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.
NEW QUESTION # 184
Coral Cloud Resorts needs consistent pass/fail logic for agent testing. Which Testing Center capability provides that?
Answer: C
Explanation:
According to the AgentForce Testing Center Guide, structured batch testing is the feature that provides consistent, repeatable pass/fail validation for agent testing. The documentation explains:
"Structured batch testing allows specialists to define expected outputs per test utterance and automatically validate the agent's responses, resulting in deterministic pass/fail outcomes."
NEW QUESTION # 185
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