How to build a dev team with 4 AI Agents in Claude

Summary of the video (tech concepts / setup)

The video describes how to automate software feature development using four coordinated AI agents that work like a CI-style dev team—planning, coding, testing, and reviewing—so features can be shipped even while the human is asleep.

Core workflow: 4 specialized agents

1. Planner agent

   • Takes a vague feature request and turns it into a detailed specification.
   • The spec includes exact file paths, function signatures, and edge cases.
   • Uses Opus 4 as the planning “driver” because plan quality determines everything downstream.

2. Coder agent

   • Reads the planner’s spec and implements it exactly as specified.
   • Uses Sonnet 4.6 to save costs, leveraging an “already exact implementation path.”

3. Tester agent

   • Reads the code changes produced by the coder.
   • Writes test cases that cover:
     • Happy paths
     • Edge cases

4. Reviewer agent (read-only gatekeeper)

   • Cannot edit code.
   • Reads:
     • the specs
     • the changes
     • runs a git diff
   • Provides a verdict before anything is merged to the main branch.
   • Emphasized as the most important part for safety/quality control.

Shared context between agents (“dot pipeline” folder)

Each agent writes outputs to a shared folder called dot pipeline, so the next agent can read context from the previous step.

Example paths:

• Planner output: dot pipeline/specs.md
• Coder output: dot pipeline/changes.md

This shared-file approach ensures each agent operates with the correct prior context.

Orchestrating all agents in a loop (“one slash man”)

The video also mentions creating a single command/tool (described as “one slash man”) that chains the agents together into a full loop:

• planner → coder → tester → reviewer

This lets a feature request (example given: “add rate limiting to the login endpoint”) flow through the entire pipeline automatically.

Guides / tutorial references

• The creator claims there is a detailed step-by-step guide to set this system up.
• The workflow is presented as a repeatable tutorial/pipeline for building features with AI agents.

Main speakers / sources

• Primary speaker/source: The video creator speaking in first person (e.g., “I can set up…”, “I created a detailed step-by-step guide…”).
• Technological model sources mentioned:
  • Opus 4 (planning driver)
  • Sonnet 4.6 (coding agent)