دانلود کتاب طراحی دامنه-محورِ تقویت‌شده با هوش مصنوعی: طراحی دامنه‌های بهتر با استفاده از مدل‌های زبانی بزرگ (LLM)، پرامپت‌های ساختاریافته و جریان‌های کاری چندعاملی

Modern software systems are more complex than ever. Distributed architectures, regulatory pressure, integration sprawl, and sociotechnical fragmentation place enormous cognitive demands on developers, architects, and technical leaders. Domain-Driven Design remains one of the most effective ways to master that complexity, but it depends on sustained reasoning, precise language, and a shared understanding of the business domain.
Large language models introduce a new kind of support for this work. Used only as code generators, they can produce fluent and plausible artifacts without preserving the decision sthat make a domain model coherent. This book treats AI as a structured reasoning partner that can amplify human thinking, reduce cognitive overload, and help teams expose ambiguity while people retain decision authority.
The book begins by building an operational mental model of how modern AI and LLMs work. You’ll examine tokenization, statistical prediction, context windows, emergent reasoning, and the limits behind apparently intelligent behavior. This foundation explains why precision in language matters and why architectural constraints are essential when an AI systemparticipates in domain reasoning.
From there, you’ll apply AI to domain discovery and modeling. Event Storming becomes abridge between human exploration and structured AI collaboration, while reusable rules and prompt patterns establish vocabulary, output structure, and semantic boundaries. Through iterative feedback and the Brew Up case study, you’ll refine events, commands, aggregates, policies, and bounded contexts without hiding unresolved domain questions.