⚡ دستیارهای کدنویسی مبتنی بر هوش مصنوعی (AI Coding Assistants) به تیم‌ها کمک می‌کنند سریع‌تر از همیشه نرم‌افزار بسازند. اما برای تبدیل این سرعت به نوآوری واقعی، سازمان‌ها باید فراتر از صرفاً نوشتن کد عمل کرده و نرم‌افزار را سریع، امن و قابل‌اعتماد ارائه دهند.

🤖 در حالی که کدنویسی با کمک هوش مصنوعی به جریان اصلی (Mainstream) تبدیل شده، آنچه پس از نوشتن کد رخ می‌دهد هنوز جای کار دارد. کتاب AI-Native Software Delivery یک راهنمای عملی برای به‌کارگیری هوش مصنوعی در کل چرخه تحویل نرم‌افزار — از Commit تا Production و فراتر از آن — است.

👨‍💻 این کتاب برای مهندسان نرم‌افزار، رهبران DevOps و مدیران فناوری نوشته شده و نشان می‌دهد تیم‌های پیشرو چگونه با کمک AI فرایندهای CI/CD را بهینه می‌کنند، هزینه‌های ابری را مدیریت می‌کنند، امنیت را تقویت می‌کنند و کارهای عملیاتی تکراری (Operational Toil) را حذف می‌کنند. همچنین ریسک‌های اتوماسیون شکننده را آشکار کرده و راهکارهایی برای جلوگیری از ساخت سیستم‌های غیرقابل‌گسترش ارائه می‌دهد.

📘 در این کتاب می‌آموزید که چگونه:

⚡ یکپارچه‌سازی AI در جریان‌های کاری تحویل برای کاهش زمان رسیدن به ارزش (Time to Value)

🧩 اجتناب از خطاهای رایج در استراتژی‌های اتوماسیون پراکنده

🔐 پیاده‌سازی اصول DevSecOps متناسب با مقیاس تیم

🛠️ به‌کارگیری عملی AIOps، Chaos Engineering و SRE

🔄 آینده‌نگری در تحویل نرم‌افزار با Pipelineهای هوشمند و حلقه‌های بازخورد

🚀 چه در حال تکامل‌بخشیدن به فرایند تحویل قدیمی باشید، چه در حال طراحی یک پلتفرم جدید، این کتاب راهنمایی استراتژیک برای هدایت سازمان شما به‌سوی آینده‌ی AI-Native Software Delivery خواهد بود.

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.

Table of Contents

Chapter 1. The Road to AI-Native DevOps

Chapter 2. Source Control Management

Chapter 3. The Build and Pre-Deployment Testing Steps of Continuous Integration

Chapter 4. Deploying to Test Environments

Chapter 5. Securing Applications and the Software Supply Chain

Chapter 6. Chaos Engineering and Service Reliability

Chapter 7. Deploying to Production

Chapter 8. Feature Management and Experimentation

Chapter 9. AI and Automation for Cloud Cost Management

Chapter 10. A Platform Engineering Approach to Modern DevOps

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 Product Marketing 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 blends deep 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.