AVAIL USEFUL LATEST SALESFORCE-AI-SPECIALIST EXAM LABS TO PASS SALESFORCE-AI-SPECIALIST ON THE FIRST ATTEMPT

Avail Useful Latest Salesforce-AI-Specialist Exam Labs to Pass Salesforce-AI-Specialist on the First Attempt

Avail Useful Latest Salesforce-AI-Specialist Exam Labs to Pass Salesforce-AI-Specialist on the First Attempt

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.
Topic 2
  • Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.
Topic 3
  • Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.
Topic 4
  • Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.
Topic 5
  • Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.

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Salesforce Certified AI Specialist Exam Sample Questions (Q98-Q103):

NEW QUESTION # 98
Universal Containers is rolling out a new generative AI initiative.
Which Prompt Builder limitations should the AI Specialist be aware of?

  • A. Creations or updates to the prompt templates are not recorded in the Setup Audit Trail.
  • B. Custom objects are supported only for Flex template types.
  • C. Rich text area fields are only supported in Flex template types.

Answer: B

Explanation:
ThePrompt Builderin Salesforce has some specific limitations, one of which is thatcustom objects aresupportedonly for Flex template types. This means that users must rely on Flex templates to integrate custom objects into their prompts.
* Option A: While rich text area fields have certain restrictions, this does not pertain to the core limitation of integrating custom objects.
* Option B: Updates and creations for prompt templates are indeed recorded in the Setup Audit Trail, so this statement is incorrect.
* Option C: This is the correct answer as it reflects a documented limitation of the Prompt Builder.


NEW QUESTION # 99
Universal Containers implemented Einstein Copilot for its users.
One user complains that Einstein Copilot is not deleting activities from the past 7 days.
What is the reason for this issue?

  • A. Einstein Copilot does not support the Delete Record action.
  • B. Einstein Copilot Delete Record Action permission is not associated to the user.
  • C. Einstein Copilot does not have the permission to delete the user's records.

Answer: A

Explanation:
Einstein Copilot currently supports various actions like creating and updating records but does not support the Delete Recordaction. Therefore, the user's request to delete activities from the past 7 days cannot be fulfilled using Einstein Copilot.
* Unsupported Action:The inability to delete records is due to the current limitations of Einstein Copilot's supported actions. It is designed to assist with tasks like data retrieval, creation, and updates, but for security and data integrity reasons, it does not facilitate the deletion of records.
* User Permissions:Even if the user has the necessary permissions to delete records within Salesforce, Einstein Copilot itself does not have the capability to execute delete operations.
References:
* Salesforce AI Specialist Documentation -Einstein Copilot Supported Actions:
* Lists the actions that Einstein Copilot can perform, noting the absence of delete operations.
* Salesforce Help -Limitations of Einstein Copilot:
* Highlights current limitations, including unsupported actions like deleting records.


NEW QUESTION # 100
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should an AI Specialist recommend to resolve the issue?

  • A. Add new data masking rules in LLM setup.
  • B. Configure data masking in the Einstein Trust Layer setup.
  • C. Enable data masking for sandbox refreshes.

Answer: B

Explanation:
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, the AI Specialist should configure thedata maskingrules within theEinstein Trust Layer. The Einstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
Salesforce AI Specialist References:For more information, refer to:https://help.salesforce.com/s/articleView?
id=sf.einstein_trust_layer_data_masking.htm


NEW QUESTION # 101
An AI Specialist built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors.
What is the cause of the random nature of this error?

  • A. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.
  • B. The number of tokens that can be processed by the LLM varies with total user demand.
  • C. The number of tokens generated by the dynamic nature of the prompt template will vary by record.

Answer: C

Explanation:
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.
Reference:
Salesforce Developer Documentation on Token Limits for Generative AI Models Salesforce AI Best Practices on Prompt Design (Trailhead or Salesforce blog resources)


NEW QUESTION # 102
Universal Containers (UC) has implemented Generative AI within Salesforce to enable summarization of a custom object called Guest. Users have reported mismatches in the generated information.
In refining its prompt design strategy, which key practices should UC prioritize?

  • A. Submit a prompt review case to Salesforce and conduct thorough testing In the playground to refine outputs until they meet user expectations.
  • B. Enable prompt test mode, allocate different prompt variations to a subset of users for evaluation, and standardize the most effective model based on performance feedback.
  • C. Create concise, clear, and consistent prompt templates with effective grounding, contextual role- playing, clear instructions, and iterative feedback.

Answer: C

Explanation:
ForUniversal Containers (UC)to refine itsGenerative AIprompt design strategy and improve the accuracy of the generated summaries for the custom objectGuest, the best practice is to focus on craftingconcise, clear, and consistent prompt templates. This includes:
* Effective grounding: Ensuring the prompt pulls data from the correct sources.
* Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.
* Clear instructions: Giving unambiguous directions on what to include in the response.
* Iterative feedback: Regularly testing and adjusting prompts based on user feedback.
* Option Bis correct because it follows industry best practices for refining prompt design.
* Option A(prompt test mode) is useful but less relevant for refining prompt design itself.
* Option C(prompt review case with Salesforce) would be more appropriate for technical issues or complex prompt errors, not general design refinement.
References:
* Salesforce Prompt Design Best Practices:https://help.salesforce.com/s/articleView?id=sf.
prompt_design_best_practices.htm


NEW QUESTION # 103
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