Harness Engineering: Building, Evaluating, and Operating Reliable AI Agents (Paperback) (ISBN-13: 9798998018206)

An AI model can propose an action, but the software around it determines what happens next. Harness Engineering explains how to build that surrounding system: the execution loop, tool interfaces, context management, permission boundaries, evaluation, and operational controls that make agent behavior inspectable and manageable.

Written for experienced software engineers, the book develops these ideas through a coding-agent running example and focused Python companions. It begins with a small execution loop and an independent evaluator, then introduces controlled edits, repository navigation, checkpoints, retries, and recovery. Dedicated security chapters examine prompt injection, exact-action approval, defense testing, and containment. Later chapters cover tracing, comparative evaluation, resource management, multi-agent coordination, protocol integration, durable service operation, and state evolution.

Code examples, diagrams, failure scenarios, exercises, and solutions explain how the mechanisms work and where their guarantees end. A free companion repository provides runnable code, tests, and retained example results. The emphasis is on understanding engineering decisions well enough to build and evaluate your own harness.