Different Prompting Techniques¶

Overview¶

This document explores various prompting techniques to achieve the same goal using different approaches. Understanding these techniques helps create more effective and versatile prompts.

1. Role-Based Prompting¶

Role-based prompting involves assigning a specific role to the AI to guide its responses based on the expertise of that role.

You are an experienced DevOps engineer with expertise in AWS infrastructure. 
Create a plan for migrating a monolithic application to a microservices architecture on AWS.

2. Step-by-Step Prompting¶

Step-by-step prompting breaks down a task into sequential steps to ensure clarity and completeness in the response.

I need to migrate a monolithic application to a microservices architecture on AWS.
1. First, analyze the current monolithic application structure
2. Then, identify components that can be separated into microservices
3. Next, design the AWS infrastructure using appropriate services
4. Finally, create a migration timeline with minimal downtime

3. Use Case-Context-Task Prompting¶

This technique provides a clear use case, context, and task to guide the AI in generating a focused and relevant response.

Use case: To create a migration plan for a monolithic application to microservices on AWS.

Context: We have a monolithic Java application serving 10,000 users that has become difficult to maintain and scale.

Task: Create a detailed migration plan that includes:
- Application decomposition strategy
- AWS services to utilize
- Migration steps
- Testing approach

4. Input-Output Format Specification¶

Input-output format specification defines the input details and expected output structure to ensure precise and structured responses.

I need a migration plan for converting a monolithic application to microservices on AWS.

Input:
- Monolithic Java application
- Currently hosted on-premises
- 10,000 daily active users
- Needs to maintain 99.9% uptime during migration

Output format:
1. Executive Summary (3-4 sentences)
2. Application Decomposition Strategy (bullet points)
3. AWS Architecture Diagram (text description)
4. Migration Timeline (weeks/phases)
5. Risk Mitigation Steps (bullet points)

5. Few-Shot Prompting¶

Few-shot prompting provides examples to guide the AI in generating similar responses for new tasks.

I need to create migration plans for different applications. Here are two examples:

Example 1:
Application: E-commerce website
Migration plan:
- Separate product catalog, shopping cart, and payment processing into microservices
- Use AWS ECS for containerization
- Implement API Gateway for routing
- Timeline: 3 months with phased approach

Example 2:
Application: CRM system
Migration plan:
- Extract customer management, reporting, and notification components
- Use AWS Lambda for serverless functions
- Implement DynamoDB for flexible schema
- Timeline: 4 months with parallel development

Now, create a similar migration plan for a monolithic Java application with 10,000 users that needs to be migrated to AWS microservices.

6. Chain-of-Thought Prompting¶

Chain-of-thought prompting encourages the AI to think through a problem step by step to arrive at a logical solution.

I need to migrate a monolithic Java application to microservices on AWS. Let's think through this step by step.

First, we need to understand the current architecture. A monolithic Java application typically has tightly coupled components like user management, business logic, and data access layers.

Next, we should identify which components would make good microservices. Components with clear boundaries and independent functionality are good candidates.

Then, we need to choose appropriate AWS services. For Java microservices, we might consider ECS, EKS, or perhaps even Lambda for certain functions.

After that, we need to plan the data migration strategy, as moving from a monolithic database to separate data stores requires careful planning.

Finally, we should develop a phased migration approach to minimize disruption.

Based on this thinking, create a migration plan for this application.

7. Negative Prompting¶

Negative prompting specifies what the AI should avoid doing, helping to refine the response by eliminating undesired outcomes.

Create a migration plan for moving a monolithic Java application to microservices on AWS. 
The plan should NOT:
- Suggest a "big bang" migration approach
- Recommend moving everything to microservices without analysis
- Ignore data migration challenges
- Overlook the need for monitoring and observability

8. Persona-Based Prompting¶

Persona-based prompting tailors the response to a specific audience or persona, ensuring the output is relevant and understandable to them.

I'm a technical project manager with limited AWS knowledge. My team needs to migrate our monolithic Java application to microservices on AWS. 

Explain the migration plan to me as if I need to present it to both technical team members and executive stakeholders. Use analogies where helpful and avoid unnecessary technical jargon.