An Agentforce wants to include data from the response of external service invocation (REST API callout) into the prompt template.
How should the Agentforce Specialist meet this requirement?
Correct Answer:B
An Agentforce wants to include data from the response of an external service invocation (REST API callout) into a prompt template. The goal is to incorporate dynamic data retrieved from an external API into the AI-generated content.
Solution:
✑ Use External Service Record Merge Fields
✑ External Service Integration:
✑ External Service Record Merge Fields:
Implementation Steps:
✑ Register the External Service:
✑ Create a Named Credential:
✑ Use External Service in Flow:
✑ Configure the Prompt Template:
Why Other Options are Less Suitable:
✑ Option A (Convert the JSON to an XML merge field):
✑ Option C (Use ??Add Prompt Instructions?? flow element):
References:
✑ Salesforce Agentforce Specialist Documentation - Integrating External Services with Prompt Templates:
✑ Salesforce Help - Using Merge Fields with External Data:
✑ Salesforce Trailhead - External Services and Flow:
Conclusion:
By using External Service Record merge fields, the Agentforce Specialist can effectively include data from external REST API responses into prompt templates, ensuring that the AI-generated content is enriched with up-to-date and relevant external data.
Universal Containers wants support agents to use Agentforce to ask questions about its product tutorials and product guides.
What should the Agentforce Specialist do to meet this requirement?
Correct Answer:C
✑ Context of the QuestionUniversal Containers (UC) wants its support agents to use Agentforce to ask questions about product tutorials and product guides. Agentforce typically references knowledge sources to provide accurate and
contextual responses.
✑ Why Knowledge Articles?
✑ Why Not the Other Options?
✑ ConclusionTo ensure Agentforce can effectively retrieve and deliver accurate information about products, publishing product tutorials and guides as Knowledge articles is the recommended approach.
Salesforce Agentforce Specialist References & Documents
✑ Salesforce Documentation: Set Up Salesforce KnowledgeDiscusses how to publish articles for easy access
✑ by AI-driven assistants and support teams.
✑ Salesforce Agentforce Specialist Study GuideExplains best practices for feeding knowledge sources to generative AI and Agentforce.
After configuring and saving a Salesforce Agentforce Data Library (regardless of the data source), which components are automatically created and available in Data Cloud?
Correct Answer:C
Why is "A data stream, a search index, and a retriever" the correct answer? When a Salesforce Agentforce Data Library is configured and saved, it automatically creates three essential components in Data Cloud to facilitate AI-driven search and retrieval.
Key Components Created in Data Cloud:
✑ Data Stream
✑ Search Index
✑ Retriever
Why Not the Other Options?
* A. A data pipeline, an indexing engine, and a query processor
✑ Incorrect because Data Cloud does not use a query processor in the same way as traditional databases.
✑ Instead, retrievers handle AI-powered data searches.
* B. A data connector, an analytics dashboard, and a workflow rule
✑ Incorrect because these components are not automatically created when setting up a Data Library.
✑ Analytics dashboards and workflow rules are separate tools used for reporting and automation.
Agentforce Specialist References
✑ Salesforce AI Specialist Material confirms that a Data Stream, Search Index, and Retriever are created automatically in Data Cloud when configuring a Data Library.
In Model Playground, which hyperparameters of an existing Salesforce-enabled foundational model can An Agentforce change?
Correct Answer:A
In Model Playground, An Agentforce working with a Salesforce-enabled foundational model has control over specific hyperparameters that can directly affect the behavior of the generative model:
✑ Temperature: Controls the randomness of predictions. A higher temperature leads
to more diverse outputs, while a lower temperature makes the model's responses more focused and deterministic.
✑ Frequency Penalty: Reduces the likelihood of the model repeating the same
phrases or outputs frequently.
✑ Presence Penalty: Encourages the model to introduce new topics in its responses, rather than sticking with familiar, previously mentioned content.
These hyperparameters are adjustable to fine-tune the model??s responses, ensuring that it meets the desired behavior and use case requirements. Salesforce documentation confirms that these three are the key tunable hyperparameters in the Model Playground. For more details, refer to Salesforce AI Model Playground guidance from Salesforce??s official documentation on foundational model adjustments.
Universal Containers, dealing with a high volume of chat inquiries, implements Einstein Work Summaries to boost productivity.
After an agent-customer conversation, which additional information does Einstein generate and fill, apart from the "summary"'
Correct Answer:C
Einstein Work Summaries automatically generate concise summaries of customer interactions (e.g., chat transcripts). Beyond the "summary" field, it extracts and populates Issue (key problem discussed) andResolution (action taken to resolve the issue). These fields help agents and supervisors quickly grasp the conversation's context
without reviewing the full transcript.
✑ Sentiment Analysis and Emotion Detection (Option A): While Einstein Conversation Insights provides sentiment scores and emotion detection, these are separate from Work Summaries. Work Summaries focus on factual summaries, not sentiment.
✑ Draft Survey Request Email (Option B): Not part of Work Summaries. This would require automation tools like Flow or Email Studio.
✑ Issue and Resolution (Option C): Directly referenced in Salesforce documentation as fields populated by Einstein Work Summaries.
References:
✑ Salesforce Help Article: Einstein Work Summaries
✑ Einstein Work Summaries focus on "key details like Issue and Resolution" alongside summaries.
✑ Contrast with Einstein Conversation Insights for sentiment/emotion analysis.