Harness Engineering for AI Coding Agents: Build Reliable Claude Code, Codex, and Python Agent Workflows with Guardrails, Tests, CI Gates, and Production Controls (AI Agents & MCP Series)
Language: English
Published by Independently published, 2026
- Softcover
- New

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- Title
- Harness Engineering for AI Coding Agents: Build Reliable Claude Code, Codex, and Python Agent Workflows with Guardrails, Tests, CI Gates, and Production Controls (AI Agents & MCP Series)
- Author
- Calado, Leandro
- Publisher
- Independently published
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798196736506
- Series
- Book 20 of 21: AI Agents & MCP Series
Vibe coding is easy. Shipping reliable AI-generated code is the hard part.
Harness Engineering for AI Coding Agents is a practical guide for developers, tech leads, and technical founders who want to turn AI coding agents into reliable software delivery systems.
Instead of teaching another generic AI coding tutorial, this book focuses on the missing layer: the harness around the agent.
You will learn how to structure repositories, write AGENTS.md files, create task specs, build context packs, define safe boundaries, enforce tests, add CI gates, validate AI-generated code, and create production-ready workflows for Claude Code, Codex-style agents, and Python projects.
Inside, you will build:
• An AGENTS.md generator
• A repo context pack builder
• An AI task spec generator
• An agent output validator
• A Python test harness for AI changes
• A CI gate for AI-generated code
• A security scan gate
• A PR review automation harness
• A Claude Code workflow template
• A production AI coding agent starter kit
This is not a hype book about replacing developers. It is a practical engineering guide for making AI coding agents safer, more testable, more reliable, and more useful in real software projects.
Harness Engineering for AI Coding Agents is a practical guide for developers, tech leads, and technical founders who want to turn AI coding agents into reliable software delivery systems.
Instead of teaching another generic AI coding tutorial, this book focuses on the missing layer: the harness around the agent.
You will learn how to structure repositories, write AGENTS.md files, create task specs, build context packs, define safe boundaries, enforce tests, add CI gates, validate AI-generated code, and create production-ready workflows for Claude Code, Codex-style agents, and Python projects.
Inside, you will build:
• An AGENTS.md generator
• A repo context pack builder
• An AI task spec generator
• An agent output validator
• A Python test harness for AI changes
• A CI gate for AI-generated code
• A security scan gate
• A PR review automation harness
• A Claude Code workflow template
• A production AI coding agent starter kit
This is not a hype book about replacing developers. It is a practical engineering guide for making AI coding agents safer, more testable, more reliable, and more useful in real software projects.
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California Books
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