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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

Introducing OpenAI API

The OpenAI platform offers a variety of natural language processing (NLP) services, powering many AI applications. At its core, the platform leverages large language models (LLMs) that are trained on a massive amount of data, with a complex architecture and billions of learnable parameters to produce AI-generated responses. Developers can interact with the platform through its API with text-based requests that are often called prompts. The prompts are processed, enriched, and transformed before being passed into the LLM model. The model’s output is further refined and delivered as a response to the API request.

The Chat service by OpenAI is designed for conversational interactions with the LLM where the conversation uses three types of prompt roles – user, system, and assistant:

  • User prompts represent an end user of the system such as a ChatGPT user, and resemble prompts we feed into ChatGPT, such as Tell me about the Fibonacci sequence...
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Supercharged Coding with GenAI
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