Prompt Engineering for Developers

Design, structure, and debug advanced prompts for Generative AI development.

Pillar

Technology – Platforms, Tools, Infrastructure & Productivity

Overview

This course equips developers with the skills to craft, optimize, and troubleshoot prompts that drive effective and reliable outputs from Generative AI models. Participants will explore techniques to create clear, context-aware prompts that enhance model performance in diverse applications.

Learning Objectives

Participants will be able to:

• Understand the principles and best practices of prompt engineering

• Design complex, multi-turn prompts for robust AI interactions

• Debug and refine prompts to improve response accuracy and relevance

• Leverage prompt templates and chaining for scalable AI workflows

• Integrate prompt engineering within AI development pipelines

Target Audience

• AI developers and machine learning engineers

• NLP specialists and data scientists

• AI product managers and technical leads

• Software engineers working with GenAI APIs

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Interactive coding labs and real-time prompt testing

• Collaborative workshops on prompt design challenges

• Case studies and best practice discussions

Materials Provided

• Prompt engineering guidelines and templates

• Sample prompt libraries and code snippets

• Access to sandbox environments for hands-on practice

• Certificate of completion

Outcomes

• Create advanced prompts tailored to specific use cases

• Troubleshoot and optimize prompts for higher quality outputs

• Develop reusable prompt patterns for efficiency and consistency

• Integrate prompt engineering into AI-powered applications

Outline / Content

Day 1: Foundations of Prompt Engineering

• Introduction to prompt design principles

• Understanding AI model behavior and response patterns

• Simple prompt creation and testing

Day 2: Advanced Prompt Design Techniques

• Multi-turn conversations and context management

• Prompt chaining and conditional prompting

• Using system messages and role definitions

Day 3: Debugging and Optimizing Prompts

• Identifying common prompt pitfalls

• Techniques for refining prompts based on output analysis

• Automated prompt testing and evaluation

Day 4: Scaling and Integrating Prompt Engineering

• Building prompt libraries and templates

• Integrating prompts into development workflows and APIs

• Workshop: Design and deploy a prompt-driven GenAI feature

• Group review and feedback session