Retrieve Feedback From Prompt Engineering

Oct 13, 2025 by orovajewels.com 3 views

PBI 4 - Task 2: Validation Causes BE (Retrieve Feedback From Prompt Engineering)

Overview

In the pursuit of automating the validation process for potential root causes, it is essential to retrieve feedback that can help us understand why a given cause is deemed incorrect. This is where the Retrieve Feedback From Prompt Engineering feature comes into play, enabling us to identify the reasons behind incorrect causes and construct a tailored approach to address them.

Problem Statement

The current process of validating potential root causes is often manual and time-consuming, relying heavily on human judgment and expertise. This can lead to inconsistencies and inaccuracies in the validation process, ultimately affecting the overall quality of the solution. Moreover, the lack of automation in this process makes it challenging to scale and maintain, particularly in complex systems with multiple interacting components.

Solution Overview

To address the limitations of the current process, we propose the implementation of a Retrieve Feedback From Prompt Engineering feature, which will automate the retrieval of feedback to understand why a potential root cause is deemed incorrect. This feature will be built on top of the existing api_call function, which will be used to send a tailored prompt to an AI model. The AI model will then respond with a numerical value, which will be interpreted to assign a specific, descriptive feedback message to the cause object.

Key Components

The Retrieve Feedback From Prompt Engineering feature will consist of the following key components:

retrieve_feedback function: This function will be responsible for identifying the reason a given cause is a cause for a problem, considering any previous causes. It will construct a tailored prompt based on the input parameters and send it to the AI model using the api_call function.
api_call function: This function will be used to send the tailored prompt to the AI model and retrieve the numerical response.
Feedback Interpretation: The numerical response from the AI model will be interpreted to assign a specific, descriptive feedback message to the cause object.

Benefits

The implementation of the Retrieve Feedback From Prompt Engineering feature will have several benefits, including:

Improved Accuracy: By automating the retrieval of feedback, we can reduce the likelihood of human error and improve the accuracy of the validation process.
Increased Efficiency: The feature will enable us to scale and maintain the validation process more efficiently, particularly in complex systems with multiple interacting components.
Enhanced Collaboration: The feature will provide a common language and framework for collaboration among stakeholders, enabling them to work together more effectively to identify and address potential root causes.

Technical Requirements

The implementation of the Retrieve Feedback From Prompt Engineering feature will require the following technical requirements:

API Integration: The feature will require integration with the existing API to send and receive data from the AI model.
Data Storage: The feature will require a data storage solution to store the feedback messages and other relevant data.
Security: The feature will require robust security measures to ensure the confidentiality, integrity, and availability of the data.

Implementation Plan

The implementation of the Retrieve Feedback From Prompt Engineering feature will be carried out in the following phases:

Phase 1: Requirements Gathering: This phase will involve gathering requirements from stakeholders and defining the scope of the project.
Phase 2: Design: This phase will involve designing the architecture and components of the feature.
Phase 3: Development: This phase will involve developing the feature, including the retrieve_feedback function, api_call function, and feedback interpretation.
Phase 4: Testing: This phase will involve testing the feature to ensure it meets the requirements and is free from defects.
Phase 5: Deployment: This phase will involve deploying the feature to production and ensuring it is properly maintained and updated.

Conclusion

The Retrieve Feedback From Prompt Engineering feature will play a critical role in automating the validation process for potential root causes, enabling us to identify the reasons behind incorrect causes and construct a tailored approach to address them. By implementing this feature, we can improve the accuracy and efficiency of the validation process, enhance collaboration among stakeholders, and ultimately deliver better solutions to our customers.
PBI 4 - Task 2: Validation Causes BE (Retrieve Feedback From Prompt Engineering) - Q&A

Frequently Asked Questions

In this section, we will address some of the most frequently asked questions related to the Retrieve Feedback From Prompt Engineering feature.

Q: What is the purpose of the Retrieve Feedback From Prompt Engineering feature?

A: The purpose of the Retrieve Feedback From Prompt Engineering feature is to automate the retrieval of feedback to understand why a potential root cause is deemed incorrect. This feature will enable us to identify the reasons behind incorrect causes and construct a tailored approach to address them.

Q: How will the retrieve_feedback function work?

A: The retrieve_feedback function will be responsible for identifying the reason a given cause is a cause for a problem, considering any previous causes. It will construct a tailored prompt based on the input parameters and send it to the AI model using the api_call function.

Q: What is the role of the api_call function in the Retrieve Feedback From Prompt Engineering feature?

A: The api_call function will be used to send the tailored prompt to the AI model and retrieve the numerical response. This response will be interpreted to assign a specific, descriptive feedback message to the cause object.

Q: How will the feedback be interpreted?

A: The numerical response from the AI model will be interpreted to assign a specific, descriptive feedback message to the cause object. This will be done using a combination of natural language processing (NLP) and machine learning algorithms.

Q: What are the benefits of implementing the Retrieve Feedback From Prompt Engineering feature?

A: The implementation of the Retrieve Feedback From Prompt Engineering feature will have several benefits, including:

Improved accuracy
Increased efficiency
Enhanced collaboration among stakeholders

Q: What are the technical requirements for implementing the Retrieve Feedback From Prompt Engineering feature?

A: The implementation of the Retrieve Feedback From Prompt Engineering feature will require the following technical requirements:

API integration
Data storage
Security measures

Q: What is the implementation plan for the Retrieve Feedback From Prompt Engineering feature?

A: The implementation of the Retrieve Feedback From Prompt Engineering feature will be carried out in the following phases:

Phase 1: Requirements gathering
Phase 2: Design
Phase 3: Development
Phase 4: Testing
Phase 5: Deployment

Q: What is the timeline for implementing the Retrieve Feedback From Prompt Engineering feature?

A: The timeline for implementing the Retrieve Feedback From Prompt Engineering feature will depend on the complexity of the feature and the resources available. However, we anticipate that the feature will be implemented within the next 6-12 months.

Q: Who will be responsible for implementing the Retrieve Feedback From Prompt Engineering feature?

A: The implementation of the Retrieve Feedback From Prompt Engineering feature will be carried out by a team of developers, designers, and testers who will work together to ensure that the feature meets the requirements and is delivered on time.

Additional Resources

For more information on the Retrieve Feedback From Prompt Engineering feature, please refer to the following resources:

Requirements Document: This document outlines the requirements for the Retrieve Feedback From Prompt Engineering feature.
Design Document: This document outlines the design of the Retrieve Feedback From Prompt Engineering feature.
Development Plan: This document outlines the development plan for the Retrieve Feedback From Prompt Engineering feature.

Conclusion

The Retrieve Feedback From Prompt Engineering feature is a critical component of our validation process, enabling us to identify the reasons behind incorrect causes and construct a tailored approach to address them. By implementing this feature, we can improve the accuracy and efficiency of our validation process, enhance collaboration among stakeholders, and ultimately deliver better solutions to our customers.