دانلود کتاب توسعه مبتنی بر مشخصات، از مشخصات تا کد با عوامل هوش مصنوعی

AI Unified Process builds on ideas that are not new. Use cases, introduced by Ivar Jacobson and refined by Alistair Cockburn, have helped teams capture behavior for a long time. What is new is how we connect these ideas to AI tools and to a working test suite, so the whole thing stays honest and stays in sync. The result is a process that works for new projects and for large existing systems, where most of us spend most of our time. This book is about a way to work that keeps the intent at the center. It is called the AI Unified Process. The idea is simple. We describe the behavior we want as clear specifications, we tie those specifications to tests, and we let AI do the heavy lifting of writing the code. The specification stays the source of truth. The code follows from it, and we can always check one against the other. AI coding tools have changed how fast we can write code. They have not changed this hard part. In fact, they make it harder. When a tool can produce hundreds of lines in seconds, the risk is no longer slow typing. The risk is building the wrong thing quickly, with no clear record of what was intended or why. For more than thirty years I have built business software. I started with COBOL and moved to Java, and along the way, I learned one thing again and again: the hard part of software is rarely the code. The hard part is knowing what to build, writing it down clearly, and keeping that shared understanding alive as the system grows.