Erscheint: Februar 2027
Buch (Softcover): Fachbuch
AI Meets Domain-Driven Design
Building Correct, Scalable Software Through Better Specifications
Produkt bewerten
Verlag:
Springer EN Unsere-Artikel-Nr.: P35279225
EAN: 9798868832031
Erscheint: Februar 2027
Versand: Kostenlos
-8.4 %
CHF 83.–
CHF 76.–
Beschreibung
Most development teams have experimented with AI-generated code, only to encounter a familiar pattern and outputs that appear correct at first glance but fail to hold up under real-world scrutiny. These systems often miss domain nuances, overlook critical business rules, and produce APIs that unravel under expert review. The issue isn’t the model or the prompt—it’s the lack of strong, well-defined specifications. This book addresses this gap by combining artificial intelligence with Domain-Driven Design, showing how AI can enhance, not replace, rigorous design process. Through the Synergetic Blueprint, a structured approach that guides teams from business. intent to fully functioning, tested, and documented software, the book positions AI as a collaborator that improves speed, consistency, and quality. Grounded in real research, the book follows a running example, such as Larder, a recipe-sharing platform that developed across multiple iterations, to demonstrate how richer domain artefacts lead to better AI outcomes. Across seventeen chapters, readers are taken through the complete software lifecycle, including North Star definition, Wardley Mapping, Domain Storytelling, EventStorming, Context Mapping, and Domain Modeling, culminating in EXACT Coding—a practical, test-driven workflow for AI-assisted implementation. With contributions from industry practitioners and a strong emphasis on real-world application, this book equips readers with a proven, end-to-end methodology for building reliable, domain-driven systems while keeping human expertise firmly at the center. You Will:. Learn to use the Synergetic Blueprint, a 12-step process from North Star to running software, as the structured context that makes AI output domain-coherent rather than generically plausible. Critize first-draft Wardley Maps and Capability Maps, seeding EventStorming sessions, proposing Context Map integration patterns, and deriving OpenAPI and AsyncAPI contracts from domain artefacts. Build and maintain a living Ubiquitous Language with AI as a consistency guardian — detecting drift, flagging ambiguity, and keeping every artefact from Domain Story to API contract aligned.
Spezifikationen
Sprache
- Englisch
Autor
- Annegret Junker
Zielgruppe
- Professional/practitioner
Erscheinungsjahr
- 2027
Format
- Buch (Softcover)