Agentic AI Engineering 2026
English | 4 Jun. 2026 | ASIN: B0H483SMKZ | 134 pages | EPUB (True) | 115.08 KB
The era of passive chatbots is over. The systems that matter now don't just respond-they pursue goals, execute tasks, and adapt to reality. Welcome to the era of Agentic AI.In Agentic AI Engineering 2026, veteran systems practitioner Harvey Webber moves past temporary hype and superficial product demos to deliver a definitive, code-agnostic masterclass in building production-ready autonomous systems. Written specifically for software engineers, ML practitioners, and technical architects, this practical book isolates the durable design patterns that allow AI agents to plan, reason, and safely act in the real world.Frameworks will shift and APIs will change, but the engineering principles established in this book are designed to last. Webber breaks down the architectural anatomy of successful agents, providing a step-by-step scaffold around the unique strengths and stark limitations of modern Large Language Models (LLMs).Inside this comprehensive guide, you will master:The Beating Heart of Agency: A deep dive into the perception-decision-action cycle and the foundational ReAct (Reasoning and Acting) pattern.Core Building Blocks: How to architect precise tool schemas, implement multi-layered memory (short-term, long-term, episodic, and semantic), and deploy robust Retrieval-Augmented Generation (RAG).Advanced Orchestration & Planning: Designing deterministic chains, adaptive graphs, and multi-agent hierarchies utilizing supervisor-worker, delegation, handoff, and debate collaboration models.Production-Grade Guardrails: Critical engineering strategies for input/output validation, least-privilege permissions, sandboxed execution, and mitigating the persistent threat of prompt injection.Operations & Scaling: Practical math for token cost reduction, model routing, latency mitigation, asynchronous concurrency, and state persistence over long-running tasks.Real-World Deep Dives: Architectural blueprints for building state-of-the-art coding assistants, research synthesis engines, customer-facing agents, and workflow automation systems.Complete with production checklists, evaluation datasets guidelines, and a comprehensive glossary of agentic terminology, this text bridges the gap between clever prototypes and resilient, auditable enterprise software.Stop prompting. Start engineering. Build AI systems you can actually trust with real users and real money.
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