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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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1
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

Explaining non-project files

The /explain command is not limited to .py files or core business logic. For instance, in our Manhattan distance code base, we can use Copilot to interpret an entire non-project file or a specific section of it.

Explaining an entire file

There are times when we may want a summary of a complete non-project file. For example, consider the requirements.txt file in our project:

pandas==2.2.3
flask==3.1.0

To get a general explanation, we can highlight the entire content with the cursor, then open the inline chat or chat window and enter /explain. Figure 7.7 shows an example of this using the chat window in VS Code:

Figure 7.7: Chat window explanation of a full file highlighted content

Figure 7.7: Chat window explanation of a full file highlighted content

In this case, Copilot accurately recognized that requirements.txt lists the dependencies needed for the code base to run properly. For common non-project files, we can generally expect reliable explanations since LLMs have encountered many similar...

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Supercharged Coding with GenAI
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