AI‑Augmented Domain‑Driven Design Design Better Domains Using LLMs, Structured Prompts, and Multi-agent Workflows [#1041985]

AI‑Augmented Domain‑Driven Design: Design Better Domains Using LLMs, Structured Prompts, and Multi-agent Workflows
English | 2026 | ISBN: 1807421058 | 310 pages | True PDF,EPUB | 30.48 MB
Apply AI to Domain-Driven Design with LLMs, prompt engineering, and multi-agent systems. Build repeatable domain modeling workflows that strengthen software architecture decisions, domain clarity, and consistency.Key FeaturesApply LLMs as structured reasoning partners for Domain-Driven DesignAdvance domain modeling with structured prompts and EventStormingDesign AI agents and multi-agent systems for DDD workflowsStrengthen software architecture decisions with AI-assisted reasoningRefine domain events, aggregates, and bounded contexts with AIBook DescriptionDomain-Driven Design helps software architects and developers manage complexity by creating a shared understanding of business domains and translating that understanding into coherent software architecture. AI-Augmented Domain-Driven Design shows you how to extend that practice with generative AI and LLMs without handing architectural decisions over to AI.You'll learn to use LLMs as structured reasoning partners for domain modeling, applying prompt engineering techniques, rulebooks, EventStorming patterns, and iterative refinement. Through practical case studies, you'll use AI-assisted reasoning to identify and refine domain events, commands, aggregates, and bounded contexts while preserving human judgment and domain clarity.You'll then advance from structured prompting to AI agents for domain discovery, storytelling, and context mapping. By orchestrating these agents into multi-agent systems, you'll build repeatable Domain-Driven Design workflows that support complex software architecture work while reducing cognitive overload.By the end of the book, you'll have a disciplined approach to integrating LLMs and AI agents into your DDD practice, helping you reason about complex domains, strengthen architecture decisions, and maintain conceptual consistency as software systems evolve.What you will learnUnderstand how LLMs reason, where they help, and where they failApply prompt engineering to Domain-Driven Design workflowsUse AI-assisted reasoning to refine domain events and bounded contextsBuild rulebooks that guide and constrain LLM reasoningApply AI to EventStorming and domain modeling activitiesDesign AI agents for domain discovery and DDD workflowsOrchestrate multi-agent systems for domain modelingStrengthen software architecture decisions while preserving domain clarityWho this book is forThis book is for software developers, software architects, and technical leaders working on complex business systems who want to advance their Domain-Driven Design practice with AI. You should be comfortable with software architecture concepts and familiar with DDD fundamentals such as bounded contexts, aggregates, domain events, and domain modeling. No prior AI expertise is required, but an interest in LLMs, prompt engineering, and AI-assisted reasoning will help you get the most from the practical workflows.Table of ContentsWhy AI Matters for Domain-Driven Design TodayHow LLMs Actually Think and Why Precision Unlocks UnderstandingThe Architect's View: Reasoning with AI SystemsFrom Domain Exploration to AI CollaborationDefining Rules: Teaching the Model to Think in DDDIterative Refinement: Building the Bounded ContextPrompt as Domain CarrierFrom Prompts to Agents: Structuring AI CollaborationFrom Guardrails to Specialists: Designing Agents for DDDThe Orchestrator: Building the Coordinating AgentGoverned Autonomy: Balancing Autonomy and Alignment Across Agents
Apply AI to Domain-Driven Design with LLMs, prompt engineering, and multi-agent systems. Build repeatable domain modeling workflows that strengthen software architecture decisions, domain clarity, and consistency.
Apply LLMs as structured reasoning partners for Domain-Driven Design
Advance domain modeling with structured prompts and EventStorming
Design AI agents and multi-agent systems for DDD workflows
Strengthen software architecture decisions with AI-assisted reasoning
Refine domain events, aggregates, and bounded contexts with AI
Domain-Driven Design helps software architects and developers manage complexity by creating a shared understanding of business domains and translating that understanding into coherent software architecture. AI-Augmented Domain-Driven Design shows you how to extend that practice with generative AI and LLMs without handing architectural decisions over to AI.
You'll learn to use LLMs as structured reasoning partners for domain modeling, applying prompt engineering techniques, rulebooks, EventStorming patterns, and iterative refinement. Through practical case studies, you'll use AI-assisted reasoning to identify and refine domain events, commands, aggregates, and bounded contexts while preserving human judgment and domain clarity.
You'll then advance from structured prompting to AI agents for domain discovery, storytelling, and context mapping. By orchestrating these agents into multi-agent systems, you'll build repeatable Domain-Driven Design workflows that support complex software architecture work while reducing cognitive overload.
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