Harness Engineering for Agentic AI: Design Production-Ready AI Agent Systems with Security, Runtime Control, Observability, and Failure Recovery - Tapa blanda

Sinopsis

Harness Engineering for Agentic AI: Design Production-Ready AI Agent Systems with Security, Runtime Control, Observability, and Failure Recovery

What happens after your AI agent works perfectly in a demo, but fails when real users, real tools, real data, and real consequences enter the picture?
Building an AI agent is one challenge. Building an agent you can confidently run in production is another. Models can make unexpected decisions, tools can fail, workflows can stop halfway through, APIs can time out, permissions can be misused, and a simple retry can accidentally repeat a payment, message, or other critical action.
Harness Engineering for Agentic AI shows developers and AI engineers how to build the engineering layer that keeps autonomous agents controlled, observable, secure, and recoverable. Instead of focusing only on prompts and model intelligence, this practical guide explains the infrastructure and runtime controls needed to move from a working agent prototype to a dependable production system.
Inside, you will learn how to:

• Design a production-ready AI agent harness architecture
• Control agent loops, tasks, state transitions, timeouts, and concurrency
• Build reliable tool interfaces, validation, permissions, and approval gates
• Manage state, checkpoints, resumable execution, and long-running workflows
• Protect agents with authentication, authorization, least privilege, and prompt-injection defenses
• Implement logging, tracing, monitoring, and cost visibility
• Handle failures with retries, backoff, circuit breakers, fallbacks, and idempotency
• Recover safely from partial failures, interrupted workflows, and uncertain tool outcomes
• Keep humans in control with approvals, escalation, intervention, and kill switches
• Test and evaluate the complete harness before production deployment

Rather than treating failures as unusual events, this book teaches you to design for them from the beginning. Practical explanations, architecture patterns, code examples, testing approaches, and production checklists help you understand not only what to build, but why each control matters.
Whether you are developing AI assistants, autonomous agents, tool-using LLM applications, multi-step workflows, or production agent platforms, this book will help you bridge the gap between an agent that can act and an agent system you can actually operate with confidence.
AI agents are becoming more capable. The engineering systems around them must become stronger too.

Build beyond the prototype. Engineer the harness that keeps your AI agents secure, controlled, observable, and ready for production. Get your copy of Harness Engineering for Agentic AI today and start building agent systems designed for what happens after the demo.

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