Ai-Assisted Programming: Better Planning, Coding, Testing, and Deployment
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Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, and design; coding; and debugging, testing, and documentation. With this practical book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Bard, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer).
You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation.
Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another.
This book examines:
- The core capabilities of AI-based development tools
- Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer
- Ways to use ChatGPT, Bard, Claude, and other generic LLMs for coding
- Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing
- Prompt engineering for development
- Using AI-assisted programming for tedious tasks like creating regular expressions making chron jobs and GitHub Actions
- How to use AI-based low-code and no-code tools
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