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{ "item_title" : "Domain-Driven Design with AI Agents", "item_author" : [" Lucan Verid "], "item_description" : "AI CAN GENERATE CODE IN SECONDS. BUT CAN IT BUILD SOFTWARE THAT LASTS?Writing code is becoming easier. Building reliable, maintainable enterprise applications is not.AI coding assistants and autonomous agents can accelerate development, but they can also introduce fragile architectures, inconsistent business logic, security vulnerabilities, and technical debt. Without clearly defined boundaries and engineering discipline, faster development can create bigger problems.What if you could combine the speed of AI with the architectural precision of Domain-Driven Design?Domain-Driven Design with AI Agents shows you how to combine Domain-Driven Design (DDD), TypeScript, Python, Clean Architecture, and AI agents for software engineering to design maintainable enterprise applications while keeping business logic, security, and architectural decisions under control.Through practical examples and an evolving Enterprise Commerce and Operations Platform (ECOP), you'll discover how to transform complex business requirements into structured domain models, apply enterprise backend architecture principles, and introduce AI-assisted coding workflows without sacrificing engineering quality.INSIDE THIS BOOK, YOU'LL DISCOVER HOW TO: Master Domain-Driven Design with TypeScript: Apply strategic and tactical DDD, bounded contexts, aggregates, entities, value objects, domain events, and business invariants to model complex business operations.Build maintainable enterprise backend systems: Combine Clean Architecture and TypeScript with Node.js, Fastify, REST APIs, PostgreSQL repositories, and application services.Develop Python-powered AI coding agents: Explore structured requirements analysis, specification validation, architecture-aware code generation, and controlled engineering automation.Orchestrate LangGraph multi-agent workflows: Coordinate specialized agents for requirements analysis, domain modeling, architecture planning, coding, testing, security review, and evaluation.Protect your software architecture: Establish architectural guardrails, dependency boundaries, automated verification, and human approval processes to reduce risks from AI-generated code.Apply event-driven architecture patterns: Understand transactional outbox design, domain events, idempotency, retries, and compensating actions for more reliable enterprise workflows.Strengthen testing and security: Explore unit, integration, contract, and end-to-end testing alongside authentication, authorization, agent permissions, and secure execution practices.Prepare applications for production environments: Learn deployment and operational practices involving Docker, Docker Compose, GitHub Actions CI/CD, observability, database migrations, and reliability engineering.Evolve software systems with confidence: Discover how to manage changing domain requirements, evaluate AI-assisted changes, and preserve architectural consistency as applications grow.GO BEYOND AI-GENERATED CODE. LEARN TO ENGINEER SYSTEMS THAT CAN EVOLVE.Whether you're a backend developer, full-stack engineer, software architect, or technical lead, this book provides a practical foundation for Domain-Driven Design, enterprise software architecture, and AI-assisted software development.Move beyond isolated code generation and develop the architectural judgment to design, evaluate, and improve complex applications with confidence.Stop treating AI as a shortcut to more code. Start using it as a disciplined engineering advantage.Get your copy today and build the skills to design reliable, maintainable, AI-assisted enterprise software.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/816/475/9798164751111_b.jpg", "price_data" : { "retail_price" : "18.99", "online_price" : "18.99", "our_price" : "18.99", "club_price" : "18.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Domain-Driven Design with AI Agents|Lucan Verid

Domain-Driven Design with AI Agents : Build Production-Ready Enterprise Applications with TypeScript, Python, Multi-Agent Workflows, Software Architect

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Overview

AI CAN GENERATE CODE IN SECONDS. BUT CAN IT BUILD SOFTWARE THAT LASTS?

Writing code is becoming easier. Building reliable, maintainable enterprise applications is not.

AI coding assistants and autonomous agents can accelerate development, but they can also introduce fragile architectures, inconsistent business logic, security vulnerabilities, and technical debt. Without clearly defined boundaries and engineering discipline, faster development can create bigger problems.

What if you could combine the speed of AI with the architectural precision of Domain-Driven Design?

Domain-Driven Design with AI Agents shows you how to combine Domain-Driven Design (DDD), TypeScript, Python, Clean Architecture, and AI agents for software engineering to design maintainable enterprise applications while keeping business logic, security, and architectural decisions under control.

Through practical examples and an evolving Enterprise Commerce and Operations Platform (ECOP), you'll discover how to transform complex business requirements into structured domain models, apply enterprise backend architecture principles, and introduce AI-assisted coding workflows without sacrificing engineering quality.

INSIDE THIS BOOK, YOU'LL DISCOVER HOW TO:

  • Master Domain-Driven Design with TypeScript: Apply strategic and tactical DDD, bounded contexts, aggregates, entities, value objects, domain events, and business invariants to model complex business operations.

  • Build maintainable enterprise backend systems: Combine Clean Architecture and TypeScript with Node.js, Fastify, REST APIs, PostgreSQL repositories, and application services.

  • Develop Python-powered AI coding agents: Explore structured requirements analysis, specification validation, architecture-aware code generation, and controlled engineering automation.

  • Orchestrate LangGraph multi-agent workflows: Coordinate specialized agents for requirements analysis, domain modeling, architecture planning, coding, testing, security review, and evaluation.

  • Protect your software architecture: Establish architectural guardrails, dependency boundaries, automated verification, and human approval processes to reduce risks from AI-generated code.

  • Apply event-driven architecture patterns: Understand transactional outbox design, domain events, idempotency, retries, and compensating actions for more reliable enterprise workflows.

  • Strengthen testing and security: Explore unit, integration, contract, and end-to-end testing alongside authentication, authorization, agent permissions, and secure execution practices.

  • Prepare applications for production environments: Learn deployment and operational practices involving Docker, Docker Compose, GitHub Actions CI/CD, observability, database migrations, and reliability engineering.

  • Evolve software systems with confidence: Discover how to manage changing domain requirements, evaluate AI-assisted changes, and preserve architectural consistency as applications grow.


GO BEYOND AI-GENERATED CODE. LEARN TO ENGINEER SYSTEMS THAT CAN EVOLVE.

Whether you're a backend developer, full-stack engineer, software architect, or technical lead, this book provides a practical foundation for Domain-Driven Design, enterprise software architecture, and AI-assisted software development.

Move beyond isolated code generation and develop the architectural judgment to design, evaluate, and improve complex applications with confidence.

Stop treating AI as a shortcut to more code. Start using it as a disciplined engineering advantage.

Get your copy today and build the skills to design reliable, maintainable, AI-assisted enterprise software.

This item is Non-Returnable

Details

  • ISBN-13: 9798164751111
  • ISBN-10: 9798164751111
  • Publisher: Independently Published
  • Publish Date: October 2026
  • Dimensions: 11 x 8.5 x 0.35 inches
  • Shipping Weight: 0.88 pounds
  • Page Count: 166

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