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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Agents | 35% | - Agent behavior configuration
|
| Topic 2: Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| 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 # 198
Universal Containers (UC) wants to enable its sales reps to explore opportunities that are similar to previously won opportunities by entering the utterance, "Show me other opportunities like this one." How should UC achieve this with Agents?
Answer: B
Explanation:
Universal Containers can achieve the request to explore similar opportunities by using the standard Copilot action. Agent has built-in actions to handle natural language queries, such as
"Show me other opportunities like this one." The standard action will process the query and return results based on predefined matching criteria like opportunity details and past Closed Won deals.
This approach avoids the need to create custom flows or Apex classes, leveraging out-of-the-box functionality.
NEW QUESTION # 199
After an agent selects a topic, what is an important factor the reasoning engine uses to select the action?
Answer: C
Explanation:
The most crucial factor a reasoning engine uses to select an action after a topic is chosen is the priority given to each action (A). In advanced agent frameworks like AgentForce (simulated context), actions within a topic are typically not executed simply in an explicit, fixed order () unless there's no conditional logic. Instead, the reasoning engine evaluates all available actions and their associated pre-conditions (or triggers) and priorities. A priority score is often a numerical value assigned to an action that dictates its relative importance when multiple actions could potentially be executed simultaneously or when the agent must choose the 'best' action to address the current topic state. This prioritization ensures the agent handles the most critical or relevant tasks first, which is essential for efficient and goal-oriented behavior. The action's name and instructions () are descriptive for the developer but are not the primary selection criteria used by the runtime reasoning engine itself; it's the logic and priority that govern execution.
NEW QUESTION # 200
Universal Containers has grounded a prompt template with a related list. During user acceptance testing (UAT), users are not getting the correct responses. What is causing this issue?
Answer: A
Explanation:
UC has grounded a prompt template with a related list, but the responses are incorrect during UAT. Grounding with related lists in Agentforce allows the AI to access data from child records linked to a parent object.
NEW QUESTION # 201
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?
Answer: A
Explanation:
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.
NEW QUESTION # 202
Universal Containers (UC) has configured a data library and wants to restrict indexing of knowledge articles to articles which are only publicly available in their knowledge base, UC also wants the agent to link sources that the large language model (LLM) grounded its response on.
Which settings should help UC with this?
Answer: A
Explanation:
According to the AgentForce Data Library Configuration Guide, administrators can restrict indexing and retrieval of Knowledge articles to publicly available ones and enable source visibility for LLM-grounded responses. The documentation states:
"Within the data library settings, under Knowledge Settings, enable `Use Public Knowledge Articles' to ensure only publicly visible content is indexed. To display citations, enable `Show Sources' so the agent links the specific articles or data records used to ground its response."
NEW QUESTION # 203
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