# How to Build an AI Agent Harness With Claude Opus 5.5

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How to Build an AI Agent Harness With Claude Opus 5.5

Build the control system that gives your Claude agent tools, state, permissions, progress tracking, recovery, and human approval

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Sep 29

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Your AI agent completes three useful steps, calls a tool, and then fails. When you restart it, the agent no longer knows what worked, repeats the same search, and confidently says the task is finished.

The model did not suddenly become less capable. The system around it was never designed to preserve progress, constrain tools, recover from failure, or prove that “done” really means done.

This is the hidden difference between an impressive agent demo and a dependable agent system.

Claude Opus 5.5 can reason, plan, and use tools across long tasks. But the model is only the reasoning engine. A harness manages everything around it: the task, tool loop, state, checkpoints, permissions, retries, approvals, logs, and completion tests.

For an everyday builder, that means fewer repeated steps, fewer silent failures, and a clear place to regain control when the agent reaches a decision it should not make alone.

The key is not maximum autonomy. It is visible progress with safe recovery.

Inside: a complete local harness, working mock mode, Claude API configuration, tool permissions, checkpoints, approval gates, eight failure tests, and a downloadable starter kit...

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