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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
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Part 3: From Code to Production with GenAI
21
Index

Basics to Advanced LLM Prompting for GenAI Coding

In Part 2 of this book, we explore how LLMs can be applied to consistently generate quality code. It begins with a high-level guide on how LLMs work and then applies them to different tasks. By the end of this part, you will understand which tools (ChatGPT, OpenAI API, and GitHub Copilot) can be best applied for a given task.

This part expands into prompt engineering, including advanced topics such as few-shot learning, Chain-of-Thought reasoning, iterative prompting, and chaining to better understand and refactor code. It concludes with an exploration of fine-tuning methods.

This part contains the following chapters:

  • Chapter 6, Behind the Scenes: How ChatGPT, GitHub Copilot, and Other LLMs Work
  • Chapter 7, Reading and Understanding Code Bases with GenAI
  • Chapter 8, An Introduction to Prompt Engineering
  • Chapter 9, Advanced Prompt Engineering for Coding-Related Tasks
  • Chapter 10, Refactoring Code...
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Supercharged Coding with GenAI
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