AI Agents - Advanced Engineering

Build AI Agents You Can Trust With Real Responsibility

What happens when an AI agent is no longer running for a few seconds or minutes, but for days? What happens when it makes hundreds of decisions without human supervision, interacts with real systems, affects real people, and operates at institutional scale?

AI Agents: Advanced Engineering tackles the hardest engineering problems that emerge when AI agents become genuinely autonomous.

As the final volume in the AI Agents in Practice series, this book takes the NexaCore platform through the deployment of a fully autonomous migration agent and examines the engineering discipline required to make such systems verifiable, resilient, aligned, secure, and trustworthy.

Inside the Book

• Engineer long-running autonomous agents
• Evaluate agent behaviour at scale
• Design failure recovery and self-correction mechanisms
• Define capability boundaries and appropriate refusal behaviour
• Red-team autonomous agent systems
• Apply preference learning from human feedback
• Detect reward hacking and specification gaming
• Implement constitutional constraints in production
• Explore domain fine-tuning and model distillation
• Build advanced RAG systems with provenance validation
• Design multimodal agents
• Optimise latency and operational cost
• Develop institutional governance for autonomous systems
• Approach engineering ethics as a practical discipline

The central question is not simply “Can the agent do it?” It is “Can we verify that it did it correctly, understand when it is failing, and trust it to operate within the boundaries we have defined?”

Through a demanding production scenario, the book explores the difference between an agent that is merely capable and one that can be confidently deployed at scale. It brings together autonomous execution, evaluation, alignment engineering, security, governance, verification, and ethics into a single engineering discipline.

For engineers who are ready to move beyond building capable agents—and toward building trustworthy autonomous systems—this is the final step.

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