What happens when an AI system can do more than generate a function?
It can inspect a repository, understand a development task, create a plan, modify multiple files, run commands, execute tests, analyze failures, and continue working until it reaches a solution.
Agentic Coding with LLMs: Build Autonomous Software with Generative AI and Advanced Prompt Engineering explores the technologies and engineering principles behind this new generation of autonomous software development systems.
This book takes readers beyond traditional AI coding assistants and into the architecture of coding agents. You will learn how LLM-powered agents reason about development tasks, break complex goals into smaller actions, use external tools, manage memory, retrieve relevant information, and evaluate their own results.
A major focus is placed on advanced prompt engineering and context design. Readers will discover how system instructions, task decomposition, structured outputs, retrieval, feedback loops, and verification strategies can dramatically improve the reliability of autonomous coding systems.
From single-agent workflows to collaborative multi-agent architectures, the book provides a practical framework for building AI systems capable of performing meaningful software engineering tasks.
You will also explore testing, security, observability, failure recovery, and human oversight critical components for moving agentic coding from impressive demonstrations to dependable engineering tools.
For developers, AI engineers, and builders preparing for the next era of software development, this book provides the knowledge needed to design, build, and control autonomous coding systems powered by Large Language Models
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Paperback. Etat : new. Paperback. What happens when an AI system can do more than generate a function?It can inspect a repository, understand a development task, create a plan, modify multiple files, run commands, execute tests, analyze failures, and continue working until it reaches a solution.Agentic Coding with LLMs: Build Autonomous Software with Generative AI and Advanced Prompt Engineering explores the technologies and engineering principles behind this new generation of autonomous software development systems.This book takes readers beyond traditional AI coding assistants and into the architecture of coding agents. You will learn how LLM-powered agents reason about development tasks, break complex goals into smaller actions, use external tools, manage memory, retrieve relevant information, and evaluate their own results.A major focus is placed on advanced prompt engineering and context design. Readers will discover how system instructions, task decomposition, structured outputs, retrieval, feedback loops, and verification strategies can dramatically improve the reliability of autonomous coding systems.From single-agent workflows to collaborative multi-agent architectures, the book provides a practical framework for building AI systems capable of performing meaningful software engineering tasks.You will also explore testing, security, observability, failure recovery, and human oversight critical components for moving agentic coding from impressive demonstrations to dependable engineering tools.For developers, AI engineers, and builders preparing for the next era of software development, this book provides the knowledge needed to design, build, and control autonomous coding systems powered by Large Language Models This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798172476297
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. What happens when an AI system can do more than generate a function?It can inspect a repository, understand a development task, create a plan, modify multiple files, run commands, execute tests, analyze failures, and continue working until it reaches a solution.Agentic Coding with LLMs: Build Autonomous Software with Generative AI and Advanced Prompt Engineering explores the technologies and engineering principles behind this new generation of autonomous software development systems.This book takes readers beyond traditional AI coding assistants and into the architecture of coding agents. You will learn how LLM-powered agents reason about development tasks, break complex goals into smaller actions, use external tools, manage memory, retrieve relevant information, and evaluate their own results.A major focus is placed on advanced prompt engineering and context design. Readers will discover how system instructions, task decomposition, structured outputs, retrieval, feedback loops, and verification strategies can dramatically improve the reliability of autonomous coding systems.From single-agent workflows to collaborative multi-agent architectures, the book provides a practical framework for building AI systems capable of performing meaningful software engineering tasks.You will also explore testing, security, observability, failure recovery, and human oversight critical components for moving agentic coding from impressive demonstrations to dependable engineering tools.For developers, AI engineers, and builders preparing for the next era of software development, this book provides the knowledge needed to design, build, and control autonomous coding systems powered by Large Language Models This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798172476297
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Taschenbuch. Etat : Neu. Neuware - What happens when an AI system can do more than generate a function It can inspect a repository, understand a development task, create a plan, modify multiple files, run commands, execute tests, analyze failures, and continue working until it reaches a solution.Agentic Coding with LLMs: Build Autonomous Software with Generative AI and Advanced Prompt Engineering explores the technologies and engineering principles behind this new generation of autonomous software development systems.This book takes readers beyond traditional AI coding assistants and into the architecture of coding agents. You will learn how LLM-powered agents reason about development tasks, break complex goals into smaller actions, use external tools, manage memory, retrieve relevant information, and evaluate their own results.A major focus is placed on advanced prompt engineering and context design. Readers will discover how system instructions, task decomposition, structured outputs, retrieval, feedback loops, and verification strategies can dramatically improve the reliability of autonomous coding systems.From single-agent workflows to collaborative multi-agent architectures, the book provides a practical framework for building AI systems capable of performing meaningful software engineering tasks.You will also explore testing, security, observability, failure recovery, and human oversight critical components for moving agentic coding from impressive demonstrations to dependable engineering tools.For developers, AI engineers, and builders preparing for the next era of software development, this book provides the knowledge needed to design, build, and control autonomous coding systems powered by Large Language Models. N° de réf. du vendeur 9798172476297
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