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This Salesforce Certified Agentforce Specialist (AI-201) certification is a valuable credential that is designed to validate your expertise all over the world. After successfully competition of AI-201 exam you can gain several personal and professional benefits. All these Salesforce Certified Agentforce Specialist (AI-201) certification exam benefits will not only prove your skills but also assist you to put your career on the right track and achieve your career objectives in a short time period.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Agents | 35% | - Agent behavior configuration
|
| Topic 2: Governance & Observability | 10% | - AI governance
|
| Topic 3: Prompt Engineering | 20% | - Grounding techniques
|
| Topic 4: Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Topic 5: Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
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NEW QUESTION # 97
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: A
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 # 98
An Agentforce needs to create a Sales Email with a custom prompt template. They need to ground on the following data.
Opportunity Products Events near the customer Tone and voice examples
How should the Agentforce Specialist obtain related items?
Answer: B
Explanation:
To ground a sales email on Opportunity Products, Events near the customer, and Tone and voice examples, the Agentforce Specialist should use a prompt-initiated flow. This flow can dynamically fetch the necessary data from related records in Salesforce and ground the generative AI output with contextually accurate information.
NEW QUESTION # 99
Universal Containers wants to keep retrieval accurate as product documentation changes frequently. Which approach should the company implement?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
According to the official AgentForce implementation guidelines and RAG (Retrieval-Augmented Generation) architecture within Salesforce, maintaining retrieval accuracy depends on ensuring that embeddings and indexed content remain synchronized with the most recent data. When product documentation or knowledge base content changes, the underlying text used for vector embeddings must also be updated to reflect the new information.
The AgentForce documentation clearly specifies that when content is modified, the recommended practice is to rebuild the search index. This process regenerates the document chunks, re- embeds them using the latest model, and updates the index used by the retrieval system. This ensures that queries return the most current and relevant responses aligned with the updated content.
NEW QUESTION # 100
An Agentforce created a custom Agent action, but it is not being picked up by the planner service in the correct order. Which adjustment should the Al Specialist make in the custom Agent action instructions for the planner service to work as expected?
Answer: A
Explanation:
When a custom Agent action is not being prioritized correctly by the planner service, the root cause is often missing or improperly defined action dependencies. The planner service determines the execution order of actions based on dependencies defined in the action instructions. To resolve this, the Agentforce Specialist must explicitly specify dependent actions using their API names in the custom action's configuration. This ensures the planner understands the sequence in which actions must be executed to meet business logic requirements.
Salesforce documentation highlights that dependencies are critical for orchestrating workflows in Einstein Bots and Agentforce. For example, if Action B requires data from Action A, Action A's API name must be listed as a dependency in Action B's instructions. The Einstein Bot Developer Guide states that failing to define dependencies can lead to race conditions or incorrect execution order.
NEW QUESTION # 101
Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. The goal is to enhance the team's performance by identifying areas for improvement and competitive intelligence. Which feature provides insights about competitor mentions and coaching opportunities?
Answer: A
Explanation:
For analyzing voice and video call records to gain insights into competitor mentions, coaching opportunities, and other key information, Call Explorer is the most suitable feature. Call Explorer, a part of Einstein Conversation Insights, enables sales teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, including competitor mentions and moments for coaching. These insights are vital for improving sales performance by providing a clear understanding of the interactions during calls.
Call Summaries offer a quick overview of a call but do not delve deep into competitor mentions or coaching insights.
Einstein Sales Insights focuses more on pipeline and forecasting insights rather than call-based analysis.
NEW QUESTION # 102
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