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Supercharged Coding with GenAI

Supercharged Coding with GenAI

By : Hila Paz Herszfang, Peter V. Henstock
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Supercharged Coding with GenAI

Supercharged Coding with GenAI

5 (1)
By: Hila Paz Herszfang, Peter V. Henstock

Overview of this book

Software development is being transformed by GenAI tools, such as ChatGPT, OpenAI API, and GitHub Copilot, redefining how developers work. This book will help you become a power user of GenAI for Python code generation, enabling you to write better software faster. Written by an ML advisor with a thriving tech social media presence and a top AI leader who brings Harvard-level instruction to the table, this book combines practical industry insights with academic expertise. With this book, you'll gain a deep understanding of large language models (LLMs) and develop a systematic approach to solving complex tasks with AI. Through real-world examples and practical exercises, you’ll master best practices for leveraging GenAI, including prompt engineering techniques like few-shot learning and Chain-of-Thought (CoT). Going beyond simple code generation, this book teaches you how to automate debugging, refactoring, performance optimization, testing, and monitoring. By applying reusable prompt frameworks and AI-driven workflows, you’ll streamline your software development lifecycle (SDLC) and produce high-quality, well-structured code. By the end of this book, you'll know how to select the right AI tool for each task, boost efficiency, and anticipate your next coding moves—helping you stay ahead in the AI-powered development era.
Table of Contents (23 chapters)
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Part 1: Foundations for Coding with GenAI
7
Part 2: Basics to Advanced LLM Prompting for GenAI Coding
14
Part 3: From Code to Production with GenAI
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21
Index

From Code to Production with GenAI

In Part 3 of this book, we branch from simple coding to the full software development life cycle (SDLC). We first focus on writing docstrings, followed by testing, since these are almost universally required for production-ready code. The next advanced topic is scaling applications for systems in terms of runtime and memory. The part will also cover logging, monitoring, and error handling.

The techniques for completing these SDLC steps build on both the five S’s framework and advanced prompt engineering techniques discussed in Part 2.

The final chapter examines the current trends, including vibe coding, and suggests what might be next for the field of GenAI.

This part contains the following chapters:

  • Chapter 12, Documenting Code with GenAI
  • Chapter 13, Writing and Maintaining Unit Tests
  • Chapter 14, GenAI for Runtime and Memory Management
  • Chapter 15, Going Live with GenAI: Logging, Monitoring, and Errors...
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