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@ray_fu

2026-06-20

How to build a Claude Agent team that runs in Loops #ai #tech

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Most people don't realize that your AI coding agent only runs once and hands whatever comes out, even if it has bugs. This is how I built a Claude Agent Dev team that loops automatically building, testing, and fixing until everything's perfect. Create two specialists in Claude Code.

The first is a builder agent. All it does is fix and write code. The second is the checker agent.

All it does is run your test type checks, and linting. It reports exactly what failed each time. You keep these two agents separate because of the same agent that writes the code is checking its own code, it won't catch its own blind spots.

Create an orchestrator command that chains them into a loop. The builder implements the feature and the checker runs all the tests. The checker says all green, then the loop stops.

However, if a checker says something failed and it sends the failure back to the builder agent, the builder agent then reads the failure and fixes it. The checker then runs everything again, and this runs automatically in a loop until everything is perfect. This is the part that you need to know because it's a feature that prevents the loop from burning all of your tokens.

You need to add stop rules with five maximum cycles after this. If everything's not fixed, that means a human needs to come in and figure out what's broken. The second stop rule is that if a fix breaks Something that was previously passing, the loop also stops immediately because that means something is being broken to fix something else.

Without these rules, the loop continues forever where the agents start weakening tests in order to fake a pass. I created a step by step guide with the exact agent and orchestration commands in order to build this out just like the video and comment loop and I'll send it to you.

by step guide with the exact agent and orchestration commands in order to build this out just like the video and comment loop and I'll send it to you. Follow for more advice on making money and running your business with tech and AI.

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AI visibility work depends on matching the right model, search surface, or answer format to the business outcome being optimized.

AI visibility and answer readiness · asserts

  • Map each AI/search surface to a task: answer extraction, public copy, citation mining, checkout readiness, media generation, or customer-intent capture.

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What is this source mainly about?

AI visibility work depends on matching the right model, search surface, or answer format to the business outcome being optimized.

What should an operator take from it?

Map each AI/search surface to a task: answer extraction, public copy, citation mining, checkout readiness, media generation, or customer-intent capture.

Which topics does it connect to?

This source is connected to AI visibility and answer readiness.

What public evidence supports the record?

Most people don't realize that your AI coding agent only runs once and hands whatever comes out, even if it has bugs.