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| Section | Weight | Objectives |
|---|---|---|
| AI Agents | 35% | - Agent User security and permissions - Channel integration: digital experience, email, Slack - Agent architecture and reasoning engine - Topics and actions configuration - Agent types: Service, Sales, Employee - Deterministic controls: filters and variables |
| Data Cloud for Agentforce | 20% | - Improving response accuracy with data grounding - Agentforce Data Library types - Unstructured data processing: chunking, indexing - Retrievers and search types: keyword, vector, hybrid |
| Prompt Engineering | 20% | - Prompt management and user roles - Grounding techniques and best practices - Prompt Builder usage and use cases - Prompt template creation: field generation, flex types |
| Multi-Agent Interoperability | 5% | - Model Context Protocol (MCP) - Agent API usage scenarios - Agent-to-agent communication |
| Development Lifecycle | 15% | - Monitoring, adoption and optimization - Testing agents in Testing Center - Deployment: sandbox to production - Version control and maintenance |
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問題 #97
Once a data source is chosen for an Agentforce Data Library, what is true about changing that data source later?
答案：B
解題說明：
Why is "The data source cannot be changed after it is selected" the correct answer?
When configuring an Agentforce Data Library, the data source selection is permanent. Once a data source is set, it cannot be modified or replaced. This design ensures data consistency, security, and reliability within Salesforce's AI-driven environment.
Key Considerations in Agentforce Data Library
Data Source Lock-In
The chosen data source remains fixed to maintain data integrity and avoid inconsistencies.
Any updates or modifications require creating a new Data Library instead of modifying the existing one.
Why Can't the Data Source Be Changed?
The data source defines the foundation of AI-driven workflows, and any modification would disrupt processing logic.
Agentforce tools rely on structured datasets to enable AI-powered recommendations, and changing data sources could lead to inconsistencies in grounding techniques.
Workarounds for Changing Data Sources
If an organization needs to use a different data source, a new Agentforce Data Library must be created and configured from scratch.
Old data can be manually migrated into the new data source for continuity.
問題 #98
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?
答案：C
解題說明：
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.
問題 #99
Universal Containers deploys a new Agentforce Service Agent into the company's website but is getting feedback that the Service Agent is not providing answers to customer questions that are found in the company's Salesforce Knowledge articles. What is the likely issue?
答案：C
解題說明：
According to the AgentForce Knowledge Integration and Access Configuration Guide, a Service Agent retrieves and grounds its responses using data from Salesforce Knowledge when the correct permissions are assigned. If customers report that the agent cannot access or provide answers from Knowledge articles, the most common root cause is that the AgentForce Service Agent user lacks the "Allow View Knowledge" permission.
This permission enables the agent to retrieve and read published articles from Salesforce Knowledge for grounding responses. Without it, the agent cannot access the content repository, resulting in incomplete or generic answers.
問題 #100
Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests. What should An Agentforce recommend to generate this email?
答案：C
解題說明：
To generate an email about products that closely match a customer's expressed interests, An Agentforce should recommend using a custom sales email template that is grounded with interest and product information. This ensures that the email content is personalized based on the customer's preferences, increasing the relevance of the marketing message.
Using grounding ensures that the generative AI pulls the correct data related to customer interests and product matches, making the email more effective.
問題 #101
An Agentforce is creating a custom action for Agentforce. Which setting should the a ensure the action performs as expected?
答案：A
解題說明：
When creating a custom action for Einstein Bots in Salesforce (including Agentforce), Action Instructions are critical for defining how the bot processes and executes the action. These instructions guide the bot on the logic to follow, such as API calls, data transformations, or conditional steps. Testing and iterating on the instructions ensures the bot understands how to handle dynamic inputs, external integrations, and decision-making.
Salesforce documentation emphasizes that Action Instructions directly impact the bot's ability to execute workflows accurately. For example, poorly defined instructions may lead to incorrect API payloads or failure to parse responses. The Einstein Bot Developer Guide highlights that refining instructions is essential for aligning the bot's behavior with business requirements.
問題 #102
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