Claude Code Harness & Graph Engineering: Advanced Claude Code CLI Harness Engineering in Practice

Claude Code can be fun in a GUI.

However, Claude Code pays off in CLI harness design.

This course does not introduce Claude Code CLI as merely an AI coding tool. Instead, it covers how to integrate Claude Code into real-world backend and DevOps workflows through the lenses of Context, Permission, Verification, Tool, Subagent, and Debugging Harness. By connecting log analysis, bug fixes, test recovery, CLAUDE.md design, session management, and parallel worktree operations, you will learn how to design a work system that enables Claude to work safely on real projects.

Recommended for people who…

After completing the course,

After taking this course, you will no longer see Claude Code as merely a tool for “entering good prompts.” Instead, you will be able to determine what Claude should see, how far it can act, how to verify its results, when to clear/compact/restart if a session becomes polluted, and how to manage worktrees and parallel sessions.

Specifically, you can structurally codify project rules and prohibitions in CLAUDE.md, organize logs, environment variables, and configuration scope issues in a form that Claude can solve, and review Claude’s proposed changes through testing, diffing, and counterexample verification loops. In other words, you will take Claude Code beyond being a GUI-based assistant and bring it to a level where it can be integrated into actual backend and DevOps workflows.

Features of This Course

1. Rather than simply explaining features, this course teaches from the perspective of “harness engineering” based on research papers.

This course does not list Claude Code’s features like official documentation. Instead, it explains how to design Context, Permission, Verification, Tool, Subagent, and Debugging Harnesses so that Claude Code can work safely on real projects. As a result, you are less affected by rapidly changing version information and are left with principles that can be applied to actual projects.

2. It focuses on large codebases and real-world work problems

Rather than simply building demo apps, this course covers how to keep Claude from getting lost in large codebases, reduce session contamination, safely manage worktrees and parallel sessions, and connect the GitHub Issue → PR workflow with Claude. It starts with the points where people actually get stuck in real-world work.

What you’ll learn

Getting Started with Claude Code CLI in Practice /

Architecture / Memory / CLAUDE.md / Plan Mode / Skills

In the first section, we clearly organize the differences between GUI-based Claude and the CLI, starting with the basics. Rather than simply comparing interface differences, we explain why GUI usage tends to remain at the level of “asking questions and receiving answers,” while the CLI can connect to actual logs, tests, Git, and deployment preparation. We then use the Claude Code architecture to understand why the harness is more important than the model, and explore the role of memory across sessions and CLAUDE.md, as well as the differences between Plan/Thinking Mode and Subagents, and between Skills and Tool use.

A harness configuration file you can copy and use right away

The harness configuration you create directly in the course is provided in full as completed files.
After taking the course, you can copy it into your own project and apply it right away without having to rewrite it from scratch.

The provided configuration is as follows.

• CLAUDE.md
  Defines the work rules Claude must follow in the project.

• codecraft-harness/SKILL.md
  Transforms a short, ambiguous, one-sentence request into a detailed design and implementation plan.

• solid-review/SKILL.md
  Before starting implementation, check whether responsibilities are properly separated and whether the design is unnecessarily complex.

• block-sensitive-paths.sh
  .env, SSH keys, and sensitive files and paths such as parent project folders are blocked from access.

• run-tests-after-edit.sh
  Automatically runs the relevant tests every time Claude modifies a file.

• block-stop-without-tests.sh
  It prevents Claude from reporting a task as complete when tests have not been run or have failed.

• guard.sh
  It even blocks unauthorized external network requests, creating a safe execution environment.

The Hooks included in the course are not merely example code.
We ran them all in real-world environments and verified that they work.

Once the configuration file is registered, tests run automatically every time Claude modifies the code, and when a test fails, it cannot arbitrarily terminate by saying, “I’ve completed the task.”

In other words, you will learn how to go beyond asking Claude to verify its work through prompts and make the system forcibly execute the verification process.

3. Model-Specific Prompt Playbook

Even when using the same harness, each model differs in which instructions it follows well and which it is likely to miss.

In this course, instead of using the same prompt for every model, we provide five copy-ready prompt blocks that outline which instructions to remove and which to add based on each model’s characteristics.

• Opus 5
  Reduce verification instructions that the model performs on its own to prevent unnecessary redundant work.

• Opus 4.8
  Clearly specify the tool execution conditions so that the necessary tools are used at the right time.

• Sonnet 5
  This section covers how to describe exactly, in literal terms, the files to modify and the scope of the changes.

• Haiku 4.5
  We lay out the execution procedure step by step so you can work reliably even with models that do not have the effort option.

• Fable 5
  We provide, for reference, an approach that avoids giving the model excessive instructions and retains only the necessary guidance.

Each playbook also includes the following content.

• Parameter combinations that cause a 400 Error when requested

• Default parameters and behavioral differences by model

• A record sheet comparing the results while changing the effort value

• Lab 04 exercise comparing results by running the same prompt on multiple models

Rather than simply explaining “which model is better,” you will learn how to find the optimal settings for each model yourself by repeatedly running the same task and recording the results.

Graph Engineering Hands-on Materials — Lab 05

You will directly compare the approach of handling complex tasks sequentially in one go with the Graph Engineering approach of dividing and handling multiple tasks according to their dependencies.

Interactive Learning Sheet

You can use it by opening the HTML file in a browser, without any separate installation or server launch.

You can play back step by step how the same request is processed differently in the following two approaches.

• Repeating a single flow with loop-based execution

• Graph-based execution that divides a task into multiple nodes and dependencies

When you select each step, you can also view the configuration file that created that action, allowing you to immediately understand the relationship between the execution result and the configuration.

Step-by-Step Learning Guide

We provide a learning guide comprising a total of 645 lines.

Instead of explaining the theory at length from the beginning, it is structured in the following order.

Check the conclusion → 30-minute practice → key concepts → advanced theory

There are separate learning paths for non-majors and for students with development experience.

Even those using Claude Code for the first time through vibe coding can start with hands-on practice, while developers can delve deeper into its internal workings and design principles.

Three demo projects you can run directly

Rather than just reading the configuration files, you will run claude in an actual project folder and see firsthand how Hooks block and validate tasks.

Each project intentionally includes the following issues.

• Type error

• Test failure

• A logic bug that appears normal on the surface

Learners will directly experience the following flow.

Detect the issue → Block the task → Fix the code → Run the tests → Pass validation

Loop-based and graph-based projects use the same code, with only the harness configuration set up differently.

Therefore, you can accurately compare how results differ due not to code differences, but to differences in how the work is organized.

Reference documents

We also provide practical documentation that you can refer to when setting up projects or solving problems even after completing the course.

• Environment Setup Guide
  A summary of how to prepare the execution environment, register Hooks, and resolve common errors.

• Distinguishing the Roles of Skills, Hooks, CLAUDE.md, and Tests
  Explains what each component is responsible for and which tool to use for which problem.

• Harness Inspection Checklist
  Verify that nothing is missing from the prompt, design, implementation, testing, and completion criteria.

• Question and test cards
  Provides questions to use when requirements are unclear, test design criteria, and verification table templates.

• Model-specific playbook documents
  Parameter settings, behavioral characteristics, and prompt-writing guidelines for each model are organized in one place.

• Model evaluation log
  You can run the same task with multiple models and configurations, then compare and record the results.

These materials are not merely course supplements; they are structured as a Claude Code harness operations manual that you can reuse repeatedly in real-world projects.

The person who created this course

• Silicon Valley Survivor | American Snail 

  Based on experience and know-how gained at the forefront of the Global Tech Scene, this course shows non-majors how to overcome technical barriers and become the owners of their businesses.

  • Current) Founder of a Silicon Valley AI coding agent startup

    • Operating the self-developed AI tool 'Snailer CLI' (20K+ downloads)

    • Selected for the Google for Startups Program

  • Formerly an engineer at major U.S. tech companies and promising startups

    • Gave up the final stage at Amazon to start a company

    • Silicon Valley AI fintech startup engineer

    • OpenAI / Meta / Apple / Adobe / Amazon Full-Stack Fellowship

    • Domestic search engine portal, fintech development

    • AI startup AR/B2B/SDK development

  • Proven educational expertise

    • Double major in Computer Science and Business Administration at a four-year university in Seoul, with extensive startup experience

    • Produced 2,100+ students cumulatively; 4.5K+ followers on the social media platform Threads / 500+ Substack followers

    • Threads: https://www.threads.com/@rich_l_2024?igshid=NTc4MTIwNjQ2YQ==

    • Substack: https://open.substack.com/pub/1234373801

Do you have any questions?

Notes Before Enrolling