This chapter covers
- Engaging with ChatGPT
- Learning the basics of using Copilot
- Learning the basics of using CodeWhisperer
- Exploring prompt engineering patterns
- Contrasting the differences between these three Generative AI offerings
In this chapter, we embark on a practical journey through the landscape of Generative AI, harnessing the power of three groundbreaking tools: ChatGPT, GitHub Copilot, and AWS CodeWhisperer. As we navigate the intricacies of these technologies, we’ll apply them to a series of challenging scenarios modeled after the rigorous interview questions posed by leading tech giants. Whether you’re a seasoned developer or a curious enthusiast, prepare to unlock innovative strategies that could give you the edge in your next technical interview. Get ready to transform abstract concepts into tangible solutions right at the forefront of AI’s evolving role in tech hiring.
We will begin by using two currently available models for ChatGPT: GPT-4 and GPT-3.5. The purpose is twofold: it will allow us to appreciate the engagement model of ChatGPT, and it will also let us establish a baseline against which we can compare and contrast the other two. Using two models will also allow us to appreciate the generational sea change between these model versions. Finally, throughout this chapter, we will use some common patterns in prompt engineering.