Build Fully Autonomous AI Dev Teams with Claude Code
Course Description
Build Fully Autonomous AI Dev Teams with Claude Code + tmux Orchestration
Claude Code is already one of the best AI coding agents out there — but most people still use it like a single assistant, one task at a time. In this course, you’ll learn a workflow that turns Claude Code into a truly autonomous multi-agent system: it spins up a full team, runs tasks in parallel, schedules check-ins automatically, and keeps development moving without constant monitoring.
You’ll use tmux (terminal multiplexer) to manage multiple Claude Code instances inside one terminal session and terminal scheduling to run a timed, self-driving development loop. By the end, you’ll be able to launch a spec-driven project where front-end and back-end teams work simultaneously, commit progress automatically, and report status on a schedule.
What You’ll Learn
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How to turn Claude Code into a parallel, autonomous development team
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How tmux enables one agent to control multiple Claude Code instances
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How scheduling eliminates the need to constantly monitor progress
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How to run a full-stack build using a spec-driven workflow
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How to structure specs so agents build the right app, on a timeline
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How to add version control checkpoints and restore points automatically
Key Concepts Explained
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tmux (Terminal Multiplexer)
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Create multiple terminal windows inside one session
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Spawn multiple Claude Code instances controlled by a main agent
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Persist sessions in memory so you can resume exactly where you left off
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Terminal Scheduling
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Assign tasks with time-based execution rules
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Automate phase transitions and check-ins
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Run a closed-loop workflow that progresses without manual supervision
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Tools & Framework Used
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Tmux Orchestrator (GitHub repository workflow)
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Clone and set up the orchestrator project
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Run setup scripts to enable the agentic workflow
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Use a tmux session as the runtime environment for the agent team
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Claude Code
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Initialize the main orchestrator agent
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Run system checks (tmux control + scheduling verification)
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Deploy and manage multiple sub-agents/windows
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Optional: Cursor
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View and edit the repository structure visually
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Inspect specs, task folders, and generated output
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Setup Workflow You’ll Follow
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Clone the Tmux Orchestrator repository into your target directory
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Run setup commands to make scripts executable
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Start a fresh tmux session for orchestration
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Initialize Claude Code inside the tmux session
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Run a verification prompt to confirm:
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tmux window control is working
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scheduling is functioning correctly
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Required Fixes for the Current Repo Version
Because the project is still evolving, you’ll learn how to apply two practical fixes:
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Fix 1: Hard-coded paths
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The repo may contain paths tied to the author’s username
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Claude detects and updates them automatically for your environment
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Fix 2: Fully autonomous command execution
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Replace standard Claude commands with the version using:
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--dangerously-skip-permissions
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Ensures all terminal agents run commands without waiting for approvals
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Prevents the workflow from freezing at phase one
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Spec-Driven App Building System
You’ll set up a simple but powerful spec structure:
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Spec folder (the blueprint)
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Main spec with timed development phases
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Integration spec
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Separate frontend and backend specs
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Optional UI reference folder for design replication
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Task Manager folder (execution workspace)
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Where the app is actually built
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Where agents implement features and run servers/tests
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Multi-Team Parallel Development
You’ll learn how to define and deploy teams inside your prompt:
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Frontend team
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Project manager window
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Developer window
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Server/test window
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Backend team
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Project manager window
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Developer window
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Server/test window
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Extending teams (optional)
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Add an auth team, payments team, etc., using the same pattern
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Automated Checkpoints & Progress Control
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Scheduled check-ins every 15 minutes
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Status reports on what each team is doing
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Timed phases with completion targets
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Automatic commits as restore points
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Option to proceed fully automatically or step-by-step (your choice)
Getting Clean, Copy-Pastable Commands
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Why GitHub repos can be hard to follow in video form
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Using GitIngest to convert a GitHub repo into AI-readable text
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Feeding that summary into Claude/ChatGPT to generate:
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Installation steps
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Commands
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Workflow explanations
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Troubleshooting guidance
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Minasaty AI
E learning Plateforme Organization
4.5Instructor Rating