dmux Workflows
Orchestrate parallel AI agent sessions using dmux, a tmux pane manager for agent harnesses.
When to Activate
- Running multiple agent sessions in parallel
- Coordinating work across Claude Code, Codex, and other harnesses
- Complex tasks that benefit from divide-and-conquer parallelism
- User says "run in parallel", "split this work", "use dmux", or "multi-agent"
What is dmux
dmux is a tmux-based orchestration tool that manages AI agent panes:
- Press
nto create a new pane with a prompt - Press
mto merge pane output back to the main session - Supports: Claude Code, Codex, OpenCode, Cline, Gemini, Qwen
Install: npm install -g dmux or see github.com/standardagents/dmux
Quick Start
Workflow Patterns
Pattern 1: Research + Implement
Split research and implementation into parallel tracks:
Pattern 2: Multi-File Feature
Parallelize work across independent files:
Pattern 3: Test + Fix Loop
Run tests in one pane, fix in another:
Pattern 4: Cross-Harness
Use different AI tools for different tasks:
Pattern 5: Code Review Pipeline
Parallel review perspectives:
Best Practices
- Independent tasks only. Don't parallelize tasks that depend on each other's output.
- Clear boundaries. Each pane should work on distinct files or concerns.
- Merge strategically. Review pane output before merging to avoid conflicts.
- Use git worktrees. For file-conflict-prone work, use separate worktrees per pane.
- Resource awareness. Each pane uses API tokens — keep total panes under 5-6.
Git Worktree Integration
For tasks that touch overlapping files:
Complementary Tools
Troubleshooting
- Pane not responding: Check if the agent session is waiting for input. Use
mto read output. - Merge conflicts: Use git worktrees to isolate file changes per pane.
- High token usage: Reduce number of parallel panes. Each pane is a full agent session.
- tmux not found: Install with
brew install tmux(macOS) orapt install tmux(Linux).


