001_Promt Engineering

Promt Engineering

1. Persona (Who should AI act as?)

Tell AI what kind of expert it should be.

Example

  Act as a senior Java architect with 15 years of experience.

2. Identity (Specific expertise)

Define the exact specialization.

Example

 You specialize in Spring Boot, Microservices, Kafka, and AWS.

3. Context (Background information)

Explain the situation.

Example

   I am upgrading a Java 8 monolithic application to Java 17 microservices using Spring Boot 3.

Without context, AI may give generic answers.

4. Format (How should output look?)

Tell AI how to present the answer.

Example

Give the answer in:

   Step-by-step format
   Architecture diagram
   Sample code
   Best practices

5. Audience (Who will read it?)

Different audiences need different explanations.

Example

   Audience: Junior developers

   AI will simplify the explanation.

Another example:

  Audience: Solution Architects

  AI will provide deeper technical details.

6. Tone (Writing style)

Specify the communication style.

Example

     Professional
     Friendly
     Formal
     Technical
     Executive Summary

Example:

     Use a professional and technical tone.

7. Data (Information provided)

Give actual data, requirements, examples, documents, or code.

Example

    @RestController
    public class UserController {
    }

Prompt:

    Analyze this code and suggest improvements.

The more data you provide, the better the response.

Complete PICFATD Example

Bad Prompt

Explain Microservices.

Result: Generic answer.

Good PICFATD Prompt

Persona: Senior Solution Architect

Identity: Expert in Java, Spring Boot, Kubernetes, AWS

Context: I have 10 microservices running on AWS EKS. Traffic is increasing from 1,000 to 100,000 users per day.

Format: Provide architecture diagram, scaling strategy, and implementation steps.

Audience: Engineering managers and senior developers.

Tone: Professional and technical.

Data: Current stack: Java 17, Spring Boot 3.5, Kafka, PostgreSQL, Redis.

Prompt:

Act as a Senior Solution Architect specialized in Java, Spring Boot, Kubernetes, and AWS. I have 10 microservices running on AWS EKS and traffic is expected to grow from 1,000 to 100,000 users per day. Provide a scalable architecture design, capacity planning, Kubernetes configuration, monitoring strategy, and cost optimization recommendations. Present the answer with diagrams, tables, and implementation steps. The audience is engineering managers and senior developers. Use a professional and technical tone.