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Beyond Code Generation
AI Across the Modern SDLC
This book is 100% completeLast updated on 2026-07-29
AI in software development is about much more than generating code.
Beyond Code Generation explores how AI can support the entire software development lifecycle—from understanding requirements and designing systems to development, testing, code review, deployment, and operations.
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About
About the Book
AI in software development is often discussed as a coding story. But the bigger opportunity extends across the entire software development lifecycle.
Beyond Code Generation is a practical guide to understanding how AI can support software engineering from requirements and architecture through development, testing, code review, deployment, and operations.
Written for developers, tech leads, engineering managers, architects, and technology leaders, the book looks at where AI is genuinely useful, where human judgment still matters, and how teams can introduce AI into existing engineering workflows responsibly.
Along the way, you'll explore AI-assisted development, testing and quality engineering, AI-powered code review, AI agents, human-AI workflows, governance and guardrails, organizational adoption, and ways to measure the impact of AI on engineering.
The focus is practical rather than theoretical: how AI fits into the work software teams already do, how that work may change, and what organizations should consider as AI becomes more capable.
The goal is simple: move the conversation beyond generating more code and toward building better software with less friction across the entire lifecycle.
Author
About the Author
pankaj bisht
Pankaj Bisht is a technology leader and solution architect with more than a decade of experience building software products and leading engineering teams.
His work spans full-stack engineering, software architecture, and Generative AI, with hands-on experience building LLM applications, multi-agent systems, AI guardrails, and production-focused AI solutions.
He is particularly interested in how AI is changing everyday software engineering—from coding assistants and agents to testing, architecture, governance, and engineering workflows.
His writing focuses on practical AI adoption: understanding what works, where human judgment remains essential, and how engineering teams can use AI responsibly.
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