AI Agents - Advanced Engineering : Autonomous agents, alignment engineering, and institutional governance at scale (AI Agents in Practice Book 4)
English | October 8, 2026 | ASIN: B0HMBQCT2W | 540 pages | Epub | 608.59 KB
AI AGENTS: ADVANCED ENGINEERINGAutonomous agents, alignment engineering, and institutional governance at scale.A capable AI agent can perform a task.A trustworthy AI agent must be able to perform that task autonomously, verify its own outcomes, recognise uncertainty, respect boundaries, recover from failure, and remain accountable when operating at scale.AI Agents: Advanced Engineering is the fourth and final volume in the AI Agents in Practice series. It addresses the engineering problems that emerge when production agents become highly capable, autonomous, long-running, and consequential.The book continues the NexaCore story with the deployment of an autonomous migration agent responsible for complex work that can run for days without direct human supervision. That scenario exposes a new class of engineering challenges: silent failures, compounding errors, verification gaps, alignment problems, specification gaming, governance conflicts, and unintended impacts.You will learn how to:* Engineer long-running autonomous agents that can operate across extended execution windows* Design durable state, checkpoints, context management, and independent outcome verification* Evaluate agent behaviour at scale* Build failure recovery and self-correction mechanisms* Establish capability boundaries and principled refusal behaviour* Red-team agent systems and uncover weaknesses before deployment* Explore preference learning and feedback-driven improvement* Detect reward hacking and specification gaming* Implement constitutional constraints in production systems* Apply domain fine-tuning and distillation strategies* Build advanced RAG systems with provenance validation and source verification* Design multimodal agents capable of working with visual information* Optimise latency, token consumption, and operating costs at demanding scale* Establish institutional governance for large agent deployments* Treat engineering ethics as an operational discipline rather than an afterthoughtThe book is organised around the central distinction between capability and trustworthiness.Increasing what an agent can do does not automatically make it safe to deploy. As systems become more autonomous, engineers need new infrastructure for evaluation, verification, constraints, monitoring, governance, and accountability.The book therefore goes beyond individual techniques. It examines how these mechanisms fit together into an engineering discipline for advanced autonomous systems.You will work with Python and the production agent architecture developed throughout the series, building on concepts from the earlier volumes while introducing advanced verification, evaluation, alignment, governance, multimodal, and operational patterns.This book is intended for engineers who have built and operated production AI agents, or readers who have completed Books 1 through 3. Python 3.11+, asyncio familiarity, and working knowledge of LLM APIs are expected.AI Agents: Advanced Engineering is Book 4 and the final volume of the AI Agents in Practice series.The journey began with building an agent.It continued with deploying and scaling it.Then came federation and coordination.Now comes the hardest engineering problem of all:How do you build an autonomous agent that can be trusted to operate at scale?
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