Universal Containers implements three custom actions to get three distinct types of sales summaries for its users. Users are complaining that they are not getting the right summary based on their utterances. What should the Agentforce Specialist investigate as the root cause?

1. A. Review that the custom action Is assigned to an Agent.
2. B. Review the action Instructions to ensure they are unique.
3. C. Ensure the input and output types are correctly chosen.

Correct Answer: B
The root cause of users receiving incorrect sales summaries lies in non- unique action instructions (Option B). In Einstein Bots, custom actions are triggered
based on how well user utterances align with the action instructions defined for each action. If the instructions for the three custom actions overlap or lack specificity, the bot??s natural language processing (NLP) cannot reliably distinguish between them, leading to mismatched responses.
Steps to Investigate:
✑ Review Action Instructions: Ensure each custom action has distinct, context- specific instructions. For example:
✑ Test Utterance Matching: Use Einstein Bot??s training tools to validate if user utterances map to the correct action. Overlap indicates instruction ambiguity.
✑ Refine Instructions: Incorporate keywords or phrases unique to each sales summary type to improve intent detection.
Why Other Options Are Incorrect:
✑ A. Assigning actions to an agent is irrelevant, as custom actions are automated bot components.
✑ C. Input/output types relate to data formatting, not intent routing. While important for execution, they don??t resolve utterance mismatches.
References:
✑ Einstein Bot Developer Guide: Stresses the need for unique action instructions to avoid intent conflicts.
✑ Trailhead Module: "Build AI-Powered Bots with Einstein" highlights instruction specificity for accurate action triggering.
✑ Salesforce Help Documentation: Recommends testing and refining action instructions to ensure clarity in utterance mapping.

Universal Containers (UC) wants to enable its sales team to get insights into product and competitor names mentioned during calls. How should UC meet this requirement?

1. A. Enable Einstein Conversation Insights, connect a recording provider, assign permission sets, and customize insights with up to 25 products.
2. B. Enable Einstein Conversation Insights, assign permission sets, define recording managers, and customize insights with up to 50 competitor names.
3. C. Enable Einstein Conversation Insights, enable sales recording, assign permission sets, and customize insights with up to 50 products.

Correct Answer: A
Comprehensive and Detailed In-Depth Explanation:UC wants insights into product and competitor mentions during sales calls, leveraging Einstein Conversation Insights. Let??s evaluate the options.
✑ Option A: Enable Einstein Conversation Insights, connect a recording provider, assign permission sets, and customize insights with up to 25 products.Einstein Conversation Insights analyzes call recordings to identify keywords like product and competitor names. Setup requires enabling the feature, connecting an external recording provider (e.g., Zoom, Gong), assigning permission sets (e.g., Einstein Conversation Insights User), and customizing insights by defining up to 25 products or competitors to track. Salesforce documentation confirms the 25-item limit for custom keywords, making this the correct, precise answer aligning with UC??s needs.
✑ Option B: Enable Einstein Conversation Insights, assign permission sets, define recording managers, and customize insights with up to 50 competitor names.There??s no "recording managers" role in Einstein Conversation Insights setup—integration is with a provider, not a manager designation. The limit is 25 keywords (not 50), and the option omits the critical step of connecting a provider, making it incorrect.
✑ Option C: Enable Einstein Conversation Insights, enable sales recording, assign permission sets, and customize insights with up to 50 products."Enable sales recording" is vague—Conversation Insights relies on external providers, not a native Salesforce recording feature. The keyword limit is 25, not 50, making this incorrect despite being closer than B.
Why Option A is Correct:Option A accurately reflects the setup process and limits for Einstein Conversation Insights, meeting UC??s requirement per Salesforce documentation.
References:
✑ Salesforce Help: Set Up Einstein Conversation Insights – Details provider connection and 25-keyword limit.
✑ Trailhead: Einstein Conversation Insights Basics – Covers permissions and customization.
✑ Salesforce Agentforce Documentation: Sales Features – Confirms integration steps.

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?

1. A. Create a prompt template for product tutorials and guides.
2. B. Add an Answer Questions custom field in the product object for tutorial instructions.
3. C. Publish product tutorials and guides as Knowledge articles.

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.

A Salesforce Administrator wants to generate personalized, targeted emails that incorporate customer interaction data. The admin wants to leverage large language models (LLMs) to write the emails, and wants to reuse templates for different products and customers.
Which solution approach should the admin leverage?

1. A. Use sales Email standard templates
2. B. Create a t field Generation prompt template type
3. C. Create a Sales Email prompt template type.

Correct Answer: C
To generate personalized emails using LLMs while reusing templates:
✑ Sales Email Prompt Template Type (Option C): Designed specifically for generating dynamic email content by combining LLMs with structured templates. It allows admins to define placeholders (e.g., customer name, product details) and reuse templates across scenarios.
✑ Option A: Standard email templates lack LLM integration and dynamic personalization.
✑ Option B: "t field Generation" is not a valid Salesforce prompt template type.
References:
✑ Salesforce Help: Sales Email Prompt Templates
✑ Describes using Sales Email prompt templates to "generate targeted emails using
dynamic data and LLMs."

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?

1. A. Use Model Playground to create a model configuration with the specified parameters.
2. B. Manually add the hyperparameters to the new template.
3. C. Revert to using the standard template without modifications.

Correct Answer: B
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.
✑ Option A (Model Playground) is not necessary here, as it focuses on fine-tuning
models, not adjusting templates directly.
✑ Option C (Reverting to the standard template) does not solve the issue of customizing the prompt template.
For more information, refer to Prompt Builder documentation on configuring hyperparameters in custom templates.