The Complete Engineering Blueprint to Build, Govern, and Scale LLM-Powered Agents That Work in Production

Agentic AI is no longer hype -- it's the new operating layer of software. Yet most teams are still trapped in the same cycle: endless pilots that never scale, fragile prototypes stitched together with brittle tools, and zero governance around risk, cost, or ROI.

The Agentic AI Systems Blueprint is the handbook that breaks this cycle.
Designed for CTOs, AI engineers, product leaders, and ambitious professionals, it delivers an engineering-grade, end-to-end roadmap for building goal-driven, LLM-powered agents that don't just demo -- they perform at scale in production.

Here's what makes this book different:

• Architectural Blueprint: Master the PRAL cycle (Perceive-Reason-Act-Learn) and modular design with Planner, Executor, Memory, and Tools.

• Advanced Behaviors: Implement recursive reasoning, adaptive goal reprioritization, multi-agent orchestration, and self-healing loops.

• AgentOps in Practice: CI/CD for agents, versioning of prompts and policies, canary rollouts, shadow testing, and rollback strategies.

• Governance Kit: RBAC and IAM, sandboxing, usage quotas, audit logging, HITL oversight, and risk scoring models for safe adoption.

• FinOps for Agents: Token budgeting, cost forecasting, and accountability frameworks -- because uncontrolled cost is the fastest way to fail.

• Evaluation Pipelines: Benchmarks, red-teaming, regression tests, and automated evaluation loops, with ready-to-use scorecards.

• Vertical Playbooks with KPIs: Customer Support (AHT, FCR, CSAT), Finance (compliance, risk), Retail/Marketing (conversion, CPA), DevOps (MTTR).

• Toolbox Included: Checklists, templates, prompt packs, and framework diagrams -- ready to apply immediately, saving weeks of trial and error.

• Future-Proofing: Standards for the agentic web, A2A protocols, and ecosystem interoperability.



While other books skim the surface or drown in theory, this blueprint delivers the entire lifecycle -- from design and orchestration to deployment, governance, risk, ROI, and scale.

Every chapter is outcome-driven, equipped with field-tested frameworks, evaluation pipelines, and ready-to-use toolkits.

The result? Agentic AI systems engineered for trust, resilience, and measurable impact in production.

If you're ready to move beyond fragile demos and start building systems that truly perform at scale, this is the comprehensive blueprint you've been looking for.

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• Print Length: 294 Pages
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