Software engineering's third transformation is here. Are you ready? The shift from waterfall to agile changed how teams worked. The move to cloud-native changed how systems were built. Now, AI agents are changing the nature of the work itself — and most organizations aren't prepared. While 62% of enterprises are experimenting with AI coding agents, fewer than 10% have achieved production-scale deployment. The gap between early adopters and everyone else is widening with each passing quarter. AI-Native Software Architecture bridges that gap. This isn't another book about prompt engineering or which AI assistant to license. It's a comprehensive guide to redesigning your systems, teams, and development processes so that AI agents operate as first-class participants in your software delivery lifecycle — not tools bolted onto the side. What you'll learn: The difference between AI-assisted (adding tools to existing processes) and AI-native (redesigning processes around AI capabilities) — and why only the latter delivers lasting competitive advantage - A five-stage AI-Native Maturity Model to assess where your organization stands today and chart a path forward - Five architectural patterns for AI-native systems: Orchestrator, Tool-Use, Human-in-the-Loop, Reflection, and Multi-Agent Collaboration - How to evolve team structures, define new engineering roles like the AI Conductor , and adopt Specification-Driven Development — the methodology replacing code-first approaches - Production-grade quality gates, security frameworks, cost management, and observability for AI-generated code - A detailed 90-day transformation playbook with week-by-week milestones - Four new pricing models — outcome-based, capacity-based, platform, and value-share — for capturing the economics of AI-native delivery Who this book is for: Engineering leaders and CTOs planning an AI-native transformation - Senior engineers and architects designing systems where AI agents and humans collaborate - IT services leaders confronting the existential disruption to the labor-based delivery model What makes this book different: Every framework is grounded in evidence — from published research by McKinsey, Deloitte, and Gartner, from real organizational case studies, and from the author's direct experience helping engineering teams navigate the shift. Where the evidence is strong, it says so clearly. Where it's preliminary, it notes the uncertainty. No hype. No hand-waving. Just actionable architecture. About the author: Luis Soares is the founder of ShipWithAgents.ai, where he helps organizations implement AI-native engineering practices. His background spans blockchain systems, distributed architecture, and low-level systems programming in Rust — domains where rigorous verification, trust boundaries, and human-AI collaboration aren't theoretical concepts but daily engineering requirements.