Salesforce-AI-Specialist Exam Dumps - Salesforce Certified AI Specialist Exam

For no-code implementations, Prompt Builder allows AI 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.

When creating acustom prompt templateto populate a field with generated output, the most appropriate template type isField Generation. This template is specifically designed for generating field-specific outputs using generative AI.

Additionally, the AI Specialist must ensure thatDynamic Fieldsare enabled.Dynamic Fieldsallow the system to use real-time data inputs from related records or fields when generating content, ensuring that the AI output is contextually accurate and relevant. This is crucial when populating specific fields with AI-generated content, as it ensures the data source remains dynamic and up-to-date.

TheEinstein Trust Layerwill track and audit the interactions to ensure the organization can monitor AI adoption and make necessary enhancements based on AI usage patterns.

For further reading, refer to Salesforce’s guidelines onField Generation templatesand theEinstein Trust Layer.

When acustomer chat is initiated,Einstein Service Repliesprovidesgenerative AI replies or draft emailsbased on recommendedKnowledge articles. This feature uses the information from theSalesforce Knowledge baseto generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.

Option Bis correct becauseEinstein Service Repliesis responsible for generating AI-driven responses based on knowledge articles.

Option A(Einstein Reply Recommendations) is focused on recommending replies but does not generate them.

Option C(Einstein Grounding) refers to grounding responses in data but is not directly related to drafting replies.

References:

Einstein Service Replies Overview:https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.htm

The use case that necessitates the use ofPrompt Builderiscreating a draft of a support bulletin postfor new product patches.Prompt Builderallows the AI Specialist to create and refine prompts that generate specific, relevant outputs, such as drafting support communication based on product information and patch details.

Option B(agent performance score) would likely involve predictive modeling, not prompt generation.

Option C(estimating support ticket volume) would require data analysis and predictive tools, not prompt building.

For more details, refer toSalesforce’s Prompt Builder documentationfor generative AI content creation.

Instructions:This is a core component of Custom Copilot Actions. Instructions tell the AI model what the action should do and how it should be executed. Clear and concise instructions are crucial for the action to function correctly and provide the expected outcome.

Let's look at why the other options are not the primary core component:

Output Types:While important for defining the kind of data the action produces, it's not the core defining element of the action itself.

Action Triggers:These determine when the action is initiated, but they don't define the core functionality of the action.

The sales team at a hotel resort wants to generate a guest summary about guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They require the summary to be availableonly on the contact record page.

Solution:

UsePrompt Builderto create a prompt template that generates the desired summary and displays it on the contact record page.

Prompt Builder:

Purpose:Allows the creation of custom prompt templates that leverage AI to generate content based on Salesforce data.

Functionality:

Field Generation Templates:Can be used to populate fields on records with AI-generated summaries.

Customization:Enables the AI Specialist to design prompts that utilize data from the guest profiles to produce personalized summaries and recommendations.

Relevance to the Use Case:

The sales team wants the summary to be available on the contact record page, which aligns with the capabilities of Prompt Builder to generate and display content on specific record pages.

Implementation Steps:

Create a Field Generation Prompt Template:

Use Prompt Builder to create a new prompt template of typeField Generation.

Design the prompt to instruct the AI to generate a summary based on the guest's interests and activity preferences.

Include Relevant Data:

Use merge fields to include data from the guest profile in the prompt.

Ensure that the prompt accesses the necessary fields to generate accurate recommendations.

Configure the Contact Page Layout:

Add the field that will display the AI-generated summary to the contact record page layout.

Ensure that the field is only visible where appropriate, adhering to the requirement of availability only on the contact record page.

Why Not Einstein Copilot or Model Builder:

Option A (Einstein Copilot):

Purpose:Einstein Copilot is a conversational AI assistant designed to interact with users through natural language.

Mismatch with Requirements:

The team wants a static summary displayed on the contact record page, not an interactive conversational experience.

Option C (Model Builder):

Purpose:Model Builder is used to create custom AI models for predictions and classifications.

Inapplicability:

Building a custom model is unnecessary for generating text summaries based on existing data.

Model Builder does not directly provide functionality to generate and display summaries on record pages.

References:

Salesforce AI Specialist Documentation -Prompt Builder Overview:

Provides an introduction to Prompt Builder and its capabilities.

Salesforce Help -Creating Field Generation Prompt Templates:

Guides on creating prompt templates that generate content for fields on records.

Salesforce Trailhead -Customize AI Content with Prompt Builder:

Offers hands-on experience in building and customizing prompt templates.

Conclusion:

By utilizing Prompt Builder, the sales team can create a customized prompt template that generates personalized guest summaries and recommendations based on activity preferences. This solution meets the requirement of displaying the summary only on the contact record page, enhancing the team's ability to engage with guests effectively.

The reason behind the token limit errors lies in the dynamic nature of the prompt template used in Field Generation. In Salesforce's AI generative models, each prompt and its corresponding output are subject to a token limit, which encompasses both the input and output of the large language model (LLM). Since the prompt template dynamically adjusts based on the specific data of each record, the number of tokens varies per record. Some records may generate longer outputs based on their data attributes, pushing the token count beyond the allowable limit for the LLM, resulting in token limit errors.

This behavior explains why users experience random failures—it is dependent on the specific data used in each case. For certain records, the combined input and output may fall within the token limit, while for others, it may exceed it. This variation is intrinsic to how dynamic templates interact with large language models.

Salesforce provides guidance in their documentation, stating that prompt template design should take into account token limits and suggests testing with varied records to avoid such random errors. It does not mention switching to Flex template type as a solution, nor does it suggest that token limits fluctuate with user demand. Token limits are a constant defined by the model itself, independent of external user load.

References:

Salesforce Developer Documentation onToken Limits for Generative AI Models

Salesforce AI Best Practices on Prompt Design (Trailhead or Salesforce blog resources)

To enableUniversal Containersservice agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is tocreate a custom copilot action that calls the flow. This action will allowEinstein Copilotto interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.

Option Bis correct because it enables integration betweenEinstein Copilotand the flow that connects to Oracle ERP.

Option A(Flex prompt template) is more suited for static responses and not for invoking flows.

Option C(Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.

References:

Salesforce Einstein Copilot Actions:https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm