3 Prompt Engineering and Problem Formulation

In this chapter, we turn our focus to the fundamental skills of prompt engineering and problem formulation, key elements for anyone interacting with AI. It’s about finding the right words and structure to make our interactions as productive as possible. This skill is less about complex language and more about precision and understanding the AI’s capabilities.

Prompt engineering, much like selecting the right tool for a specific job, requires an understanding of which type of prompt best suits the task at hand. As AI models become more intuitive and sophisticated, simpler tasks may require less detailed prompting, similar to tools becoming more automated. However, the art of problem formulation, like understanding the blueprint before construction, remains indispensable. Problem formulation is envisioning the end goal and guiding the AI to achieve it effectively.

3.1 Prompt engineering

3.2 The spectrum of AI prompting

3.2.1 Zero-shot prompting

3.2.2 Single-shot prompting

3.2.3 Few-shot prompting

3.2.4 Many-shot prompting

3.2.5 The future of prompt engineering

3.3 The mechanics of a good prompt

3.3.1 Key principles in prompt construction

3.4 Introductory prompts for IT roles

3.4.1 Awesome Prompts Lab

3.5 Advanced techniques

3.6 Best practices and common mistakes

3.6.1 Learning from success

3.6.2 Pitfalls to avoid

3.6.3 Meta-prompts and hints

3.7 Problem formulation

3.7.1 Incorporating problem formulation

3.8 Prompts used to write this chapter

3.9 Summary