AI agents

workmux is designed with AI agent workflows in mind. Run multiple agents in parallel, each in their own isolated environment.

Agent integration

When you provide a prompt via --prompt, --prompt-file, or --prompt-editor, workmux automatically injects the prompt into panes running the configured agent command (e.g., claude, codex, opencode, gemini, or whatever you've set via the agent config or --agent flag) without requiring any .workmux.yaml changes:

• Panes with a command matching the configured agent are automatically started with the given prompt.
• You can keep your .workmux.yaml pane configuration simple (e.g., panes: [{ command: "<agent>" }]) and let workmux handle prompt injection at runtime.

This means you can launch AI agents with task-specific prompts without modifying your project configuration for each task.

Examples

# Create a worktree with an inline prompt for AI agents
workmux add feature/ai --prompt "Implement user authentication with OAuth"

# Override the default agent for a specific worktree
workmux add feature/testing -a gemini

# Create a worktree with a prompt from a file
workmux add feature/refactor --prompt-file task-description.md

# Open your editor to write a prompt interactively
workmux add feature/new-api --prompt-editor

Parallel workflows

workmux can generate multiple worktrees from a single add command, which is ideal for running parallel experiments or delegating tasks to multiple AI agents.

Multi-agent example

# Create one worktree for claude and one for gemini with a focused prompt
workmux add my-feature -a claude -a gemini -p "Implement the new search API integration"
# Generates worktrees: my-feature-claude, my-feature-gemini

# Create 2 instances of the default agent
workmux add my-feature -n 2 -p "Implement task #{{ num }} in TASKS.md"
# Generates worktrees: my-feature-1, my-feature-2

See the add command reference for all parallel workflow options.