dmux-workflows

Coordinate parallel AI agent sessions across different harnesses by using dmux, a tmux pane manager that enforces pane-based orchestration and cross-harness coordination through predefined patterns. It allows you to run research, implementation, and testing workflows simultaneously.

Yes, you can run Claude Code, Codex, OpenCode, Cline, Gemini, and Qwen agents in the same terminal session. dmux creates independent panes within a single coordinated tmux session to manage these multiple agent harnesses concurrently.

The best way to split research, implementation, and testing workflows is by applying pattern-based workflows. dmux uses predefined patterns to enforce independent task boundaries, ensuring each AI agent pane operates within its specific workflow scope.

To start a dmux session for parallel agent orchestration, initiate dmux in your terminal and create independent panes. You then run separate agent prompts in these panes to execute coordinated workflows across your chosen harnesses.

Parallel agent orchestration utilizes git worktrees as a best practice for isolation. dmux enforces independent task boundaries across panes, and combining this with git worktrees ensures that concurrent implementation and testing workflows do not conflict.

Using tmux pane management for AI agent workflows provides structured cross-harness coordination within a single terminal. Unlike separate terminals, dmux enforces pane-based orchestration and predefined patterns to maintain independent task boundaries across concurrent sessions.