AI Augmented Engineering: Reimagining the Software Development Lifecycle with Agentic AI
Format:
Paperback
En stock
0.31 kg
Sí
Nuevo
Amazon
USA
- AI-Augmented Engineering is a comprehensive, enterprise-ready guide to redesigning the Software Development Lifecycle (SDLC) with Agentic and multi-agent AI systems.Rather than positioning AI as a coding assistant, this book demonstrates how governed, structured intelligence can participate across the entire lifecycle from requirements, architecture, and design through development, intelligent testing, release readiness, operations, and continuous quality engineering.It introduces the foundations of Agentic AI, clarifies the distinction between Generative AI, AI Agents, and multi-agent systems, and explains how planning, reasoning, and execution operate within explicit human authority. Readers will learn how to embed lifecycle intelligence using context-aware prompting, structured outputs, regression optimization, architectural drift detection, production feedback loops, and enterprise-safe integration using Model Context Protocol (MCP).The book goes further by detailing multi-agent orchestration architecture, model routing strategies (LLMs, SLMs, LRMs), governance guardrails, operating models, ROI measurement, cost discipline, and enterprise scaling patterns — transforming isolated AI experiments into disciplined, auditable, organization-wide capability.Written for engineering leaders, architects, quality professionals, platform teams, and senior practitioners, this book avoids short-lived tooling trends. Instead, it provides durable architectural principles, coordination models, and governance structures required to build intelligent, accountable, and scalable software systems.If you are responsible for delivery confidence, quality at scale, digital transformation, or enterprise platform modernization, this book provides the blueprint for moving from fragmented AI usage to coordinated, governed, multi-agent SDLC intelligence.
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