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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
21
Index

Best Practices for Prompting with ChatGPT

GenAI applications excel in certain aspects of coding and often achieve high scores in coding assignment tests. Ongoing improvements to these models continue to push the boundaries, as they begin to master a wide range of coding-related tasks and supercharge the way we develop and refine code.

To achieve good results from GenAI applications, we will focus on three pillars: model mastery of the specific task at hand, evaluation metrics to critically assess the output, and crafting precise prompts to clearly achieve the desired outcome.

This chapter focuses on best practices for crafting prompts in coding-related tasks, guided by the five S’s: structured prompt, including surrounding context, focusing on a single task, providing specific instructions, and keeping the prompt as short as possible. Later in the book, we will delve into advanced prompt engineering techniques, methods to construct manual and automatic evaluation metrics...

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