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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompt Engineering | 25% | - Prompt Builder
|
| Topic 2: AI Agents | 35% | - Topics and Actions
|
| Topic 3: Data and AI Governance | 20% | - Data grounding
|
| Topic 4: Testing, Deployment, and Operations | 20% | - Monitoring
|
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NEW QUESTION # 147
At Horizon Insurance, the customer service team is reporting that the agent consistently routes claims intake conversations to the Policy Inquiry subagent, even though user intent clearly indicates a claims-related issue.
This misrouting persists despite the user clearly expressing the intent to discuss a claim. The Agentforce Specialist added guard conditions, but the problem persists.
What is most likely causing this incorrect routing in Horizon Insurance's agent?
Answer: B
Explanation:
The correct answer is C because persistent routing to the wrong subagent usually indicates semantic overlap in subagent purpose, description, or entry conditions. Agentforce uses subagent descriptions and instructions to determine which capability is relevant to the user's intent. If "Claims Intake" and
"Policy Inquiry" both describe insurance policy details, claims eligibility, or coverage questions too broadly, the reasoning engine can classify claims requests into the wrong subagent. Procedural instructions and Flows are not the normal root cause of intent classification failure. Global instructions can influence overall behavior, but they should not be used as the primary routing definition for competing subagents. Salesforce Agent Script guidance emphasizes that topic or subagent descriptions help the model understand when a topic is relevant during classification.
NEW QUESTION # 148
What is a key benefit of the Agent-to-Agent (A2A) protocol?
Answer: A
Explanation:
The Agent-to-Agent (A2A) Protocol Overview describes A2A as a standardized framework for cross- vendor agent discovery and communication. The documentation specifies:
"A2A enables secure, interoperable communication between AI agents across vendors, platforms, and ecosystems, using standardized APIs and schemas for message exchange and capability discovery." This allows AgentForce agents to interact with external AI systems or partner agents while maintaining data governance and identity controls.
Option B is incorrect because auto-onboarding without contracts or trust verification is not supported.
Option C confuses A2A with the internal reasoning runtime used by AgentForce; A2A operates across systems, not within a single platform.
Therefore, Option A correctly defines the key benefit of the Agent-to-Agent protocol.
References (AgentForce Documents / Study Guide):
* AgentForce Architecture Guide: "Understanding the Agent-to-Agent (A2A) Protocol"
* AgentForce Interoperability Handbook: "Cross-Vendor Agent Communication Framework"
* AgentForce Study Guide: "A2A Integration Standards and Benefits"
NEW QUESTION # 149
An Agentforce at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time. UC wants to help prep the sales team for the calls by summarizing past purchases, interests in products shown by the Contact captured via Data Cloud, and a recap of past email and phone conversations for which there are transcripts.
Which approach should the Agentforce Specialist recommend to achieve this use case?
Answer: A
Explanation:
For no-code implementations, Prompt Builder allows Agentforce Specialists to create prompt templates that dynamically ground responses in Salesforce CRM data (e.g., past purchases) and Data Cloud insights (e.g., product interests) without custom coding. The standard foundation model (e.g., Einstein GPT) can synthesize this data into summaries, leveraging structured and unstructured sources (e.g., email/phone transcripts). Fine- tuning (B) or custom models (C) require code and are unnecessary here, as the use case does not involve unique data patterns requiring model retraining.
Reference:
Salesforce Help Article: Prompt Builder for No-Code AI ("Grounding in CRM and Data Cloud" section).
Einstein GPT Implementation Guide: "Generating Summaries with Pre-Built Models."
NEW QUESTION # 150
Universal Containers aims to streamline the sales team's daily tasks by using AI.
When considering these new workflows, which improvement requires the use of Prompt Builder?
Answer: B
Explanation:
Prompt Builder is explicitly required to create AI-generated summary fields via prompt templates. These fields use natural language instructions to extract or synthesize information (e.g., summarizing contract terms). Time-to-close estimations (A) and lead scores (C) are typically handled by predictive AI (e.g., Einstein Opportunity Scoring) or analytics tools, which do not require Prompt Builder.
Reference:
Salesforce Help Article: Create AI-Generated Fields with Prompt Builder ("Summary Field Generation" example).
Einstein GPT for Sales Guide: "Automating Contract Summaries."
NEW QUESTION # 151
An Agentforce at Universal Containers is trying to set up a new Field Generation prompt template. They take the following steps.
1. Create a new Field Generation prompt template.
2. Choose Case as the object type.
3. Select the custom field AI_Analysis_c as the target field.
After creating the prompt template, the Agentforce Specialist saves, tests, and activates it. Howsoever, when they go to a case record, the AI Analysis field does not show the (Sparkle) icon on the Edit pencil. When the Agentforce Specialist was editing the field, it was behaving as a normal field.
Which critical step did the Agentforce Specialist miss?
Answer: B
Explanation:
For Field Generation prompt templates to display the Sparkle icon (indicating AI-generated content), the target field must be explicitly associated with the prompt template on the Lightning page layout. Even if the prompt template is activated, failing to add the field to the page layout and link it to the template will result in the field behaving as a standard field. Salesforce documentation emphasizes that page layout configuration is mandatory to enable AI-driven field interactions.
* Reactivating the layout (A) is unnecessary unless the layout itself was modified after activation.
* Case objects are supported for Field Generation (B is incorrect).
Reference:
Salesforce Help Article: Configure Field Generation Prompt Templates ("Associating Fields with Page Layouts" section).
Einstein GPT Implementation Guide: "Enabling AI-Generated Fields in Lightning Pages."
NEW QUESTION # 152
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