Overview

Your AI agent is only as good as the environment you build around it. Prompt engineering got us started. Context engineering leveled us up. But as AI agents become autonomous - writing code, running tests, and deploying changes - a new discipline has emerged: Harness Engineering. Harness Engineering for Web Developers is a practical guide that walks you through the three-stage evolution of working with AI, from crafting single prompts to designing full autonomous agent environments. What you will learn: Prompt engineering fundamentals - role prompting, chain of thought, few-shot patterns Context engineering - context windows, RAG, tool use, MCP, and memory systems Harness engineering - architecture constraints, garbage collection, and reliability math CLAUDE.md and AGENTS.md - writing effective agent document maps The Generator/Evaluator pattern - separating work and verification for reliable output Building a harness step by step - linters, pre-commit hooks, ArchUnit, CI/CD gates Production harness operations - monitoring, cost management, and self-improving systems Includes code recipes for Claude Code, Cursor, GitHub Copilot, and OpenAI Codex. Every concept is illustrated with real-world examples using Spring Boot, FastAPI, React, and TypeScript. Why 95% accuracy is not enough: A 20-step agent pipeline at 95% per step succeeds only 36% of the time. This book shows you how to build the harness that turns that 36% into 95%+. Written for developers who want to move from talking to AI to building systems where AI works autonomously and reliably.

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