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.