AI-Native Software Delivery: Proven Practices to Produce High-Quality Software Faster

AI coding assistants are helping teams create software faster than ever. But to turn that speed into real innovation, organizations must go beyond writing code and deliver software quickly, securely, and reliably.

While AI-assisted coding is now mainstream, what happens after the code is written is still catching up. AI-Native Software Delivery is your practical guide to applying AI across the entire delivery lifecycle, from commit to production and beyond.

Written for software engineers, DevOps leaders, and tech executives, this book explores how leading teams are using AI to streamline CI/CD, manage cloud costs, strengthen security, and eliminate operational toil. The book also uncovers the risks of brittle automation and shows you how to avoid building systems that don't scale.

You'll learn how to:

  • Integrate AI across delivery workflows to accelerate time to value
  • Avoid common pitfalls of fragmented automation strategies
  • Adopt DevSecOps principles that scale with your team
  • Apply real-world practices in AIOps, chaos engineering, and SRE
  • Future-proof your delivery with intelligent pipelines and feedback loops

Whether you're evolving a legacy delivery process or designing a new platform, this guide will help you lead your organization into the AI-native future of software delivery.

1146900574
AI-Native Software Delivery: Proven Practices to Produce High-Quality Software Faster

AI coding assistants are helping teams create software faster than ever. But to turn that speed into real innovation, organizations must go beyond writing code and deliver software quickly, securely, and reliably.

While AI-assisted coding is now mainstream, what happens after the code is written is still catching up. AI-Native Software Delivery is your practical guide to applying AI across the entire delivery lifecycle, from commit to production and beyond.

Written for software engineers, DevOps leaders, and tech executives, this book explores how leading teams are using AI to streamline CI/CD, manage cloud costs, strengthen security, and eliminate operational toil. The book also uncovers the risks of brittle automation and shows you how to avoid building systems that don't scale.

You'll learn how to:

  • Integrate AI across delivery workflows to accelerate time to value
  • Avoid common pitfalls of fragmented automation strategies
  • Adopt DevSecOps principles that scale with your team
  • Apply real-world practices in AIOps, chaos engineering, and SRE
  • Future-proof your delivery with intelligent pipelines and feedback loops

Whether you're evolving a legacy delivery process or designing a new platform, this guide will help you lead your organization into the AI-native future of software delivery.

59.99 In Stock
AI-Native Software Delivery: Proven Practices to Produce High-Quality Software Faster

AI-Native Software Delivery: Proven Practices to Produce High-Quality Software Faster

AI-Native Software Delivery: Proven Practices to Produce High-Quality Software Faster

AI-Native Software Delivery: Proven Practices to Produce High-Quality Software Faster

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$59.99 

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Overview

AI coding assistants are helping teams create software faster than ever. But to turn that speed into real innovation, organizations must go beyond writing code and deliver software quickly, securely, and reliably.

While AI-assisted coding is now mainstream, what happens after the code is written is still catching up. AI-Native Software Delivery is your practical guide to applying AI across the entire delivery lifecycle, from commit to production and beyond.

Written for software engineers, DevOps leaders, and tech executives, this book explores how leading teams are using AI to streamline CI/CD, manage cloud costs, strengthen security, and eliminate operational toil. The book also uncovers the risks of brittle automation and shows you how to avoid building systems that don't scale.

You'll learn how to:

  • Integrate AI across delivery workflows to accelerate time to value
  • Avoid common pitfalls of fragmented automation strategies
  • Adopt DevSecOps principles that scale with your team
  • Apply real-world practices in AIOps, chaos engineering, and SRE
  • Future-proof your delivery with intelligent pipelines and feedback loops

Whether you're evolving a legacy delivery process or designing a new platform, this guide will help you lead your organization into the AI-native future of software delivery.


Product Details

ISBN-13: 9781098171957
Publisher: O'Reilly Media, Incorporated
Publication date: 07/25/2025
Sold by: Barnes & Noble
Format: eBook
Pages: 212
File size: 4 MB

About the Author

Nick Durkin is Field CTO for Harness, with responsibility for the organization's worldwide field engineering team, post-sales engineering team, and a portion of the platform.

He previously held technical and executive roles at OverOps, DataTorrent, and Zelle (Early Warning), where he ran critical infrastructure for the United States government. He also served as lead architect on the Department of Homeland Security's Financial Institution—Verifying Identity Credential Service (FIVICS) initiative where he developed several patents for anti-fraud technologies, which are currently in use not only by the federal government but also by some of the world's largest financial institutions.
Eric Minick is Senior Director of DevOps Solutions at Harness, with a focus on enabling AI-native pipelines, and developer experience.

For over two decades, he has helped global enterprises, including IBM and UrbanCode, adopt DevOps practices at scale. He regularly contributes to the DevOps community through writing, speaking, and consulting.
Chinmay Gaikwad is Director of Product Marketing at Harness, where he combines deep AI-native DevOps and AppSec expertise with strategic marketing leadership.

He is a software engineer by training and is recognized for his expertise in application security, DevOps practices, and developer experience, with a proven track record in both technical and marketing roles across early-stage and late-stage startups as well as public companies.
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