Desktop orchestrator for coding agents and worktrees

A workspace for agent-driven development

One coding agent can handle a task. Running several across a project creates a different job: deciding what matters, splitting work cleanly, giving each agent the right context, preventing branch collisions, and following every change through review and merge.

AO is a local desktop workspace built for that job. Add a repository and create a worker session with the coding agent, model, and interface that fit the task. For Git-backed work, AO gives the worker its own branch and worktree. The task, conversation, terminal, changed files, browser preview, pull request, CI, and review state stay attached to that session from start to finish.

Behind the desktop app, AO's local daemon watches agent activity and source-control state. The result is a shared, live view of the project instead of a collection of disconnected terminals, branches, and browser tabs.

Install

Download the latest AO desktop app for your platform. AO checks for updates automatically.

Platform	Download
macOS (Apple silicon)	Download
macOS (Intel)	Download
Windows	Download
Linux (AppImage)	Download
Linux (Debian/Ubuntu)	Download
Linux (Fedora/RHEL)	Download

Open Agent Orchestrator and point it at the repository you want AO to manage. The desktop app runs the daemon for you, so no CLI is required. See the installation guide for agent CLI setup and troubleshooting.

Workers execute focused tasks

A worker is AO's unit of execution: one task, one coding agent, and one isolated workspace. Use New task when the work is already clear. Describe the outcome, choose an agent and model, attach relevant files, and work with the agent in structured Chat or its native terminal UI.

Open a worker at any time to continue the conversation, attach to its terminal, inspect its changes, use its isolated browser, review its pull request, or send CI and review feedback back to the same agent. This makes each task independently understandable and keeps parallel work from collapsing into one shared context.

The orchestrator plans across the project

The project orchestrator is AO's persistent planning and coordination agent. It works at the level above individual tasks: the product direction, technical strategy, priorities, and sequence of work across the repository.

Use the orchestrator to explore an idea before implementation, brainstorm product and technical approaches, reason through tradeoffs, identify high-impact work, and turn an ambiguous outcome into a concrete plan. Its project-scoped conversation preserves goals, decisions, constraints, and earlier reasoning. It combines that planning history with repository context and live AO state, including active workers, ownership, pull requests, CI, and reviews. This keeps planning grounded in both the project and the work already underway.

When a plan becomes actionable, the orchestrator can break it into focused tasks, spawn or redirect workers, pass each worker the relevant context, follow their progress, and coordinate follow-up work. The orchestrator owns planning and delegation; workers own implementation, tests, commits, and pull requests.

The Kanban keeps the system legible

Every worker appears on the same live board, whether you started it from New task or the orchestrator delegated it. AO derives each card's position from session, pull request, CI, and review facts, turning the Kanban into an operational view of the project:

• Working: workers that are actively implementing or ready for another instruction
• Needs you: blocked sessions, missing input, failed CI, requested changes, or lost signals
• In review: open and draft pull requests waiting on checks or review
• Ready to merge: approved or mergeable work, with merged sessions kept visible until they are archived

Each card keeps the task, agent, branch, activity, pull request, and status together. Open it to inspect the conversation or terminal, changed files, PR summary, reviews, and preview. The board shows what is moving, what is blocked, and where your attention will have the most impact.

One workflow, from idea to merge

1. Start at the right level. Give a clear task directly to a worker, or develop a larger outcome with the project orchestrator and let it shape the plan.
2. Delegate focused work. Start workers yourself or have the orchestrator create them with the context and ownership they need.
3. Build in isolation. Every Git-backed worker gets its own branch and worktree; Scratch workers get AO-managed branchless directories.
4. Supervise live state. AO follows agent activity, pull requests, CI, review feedback, and merge conflicts, then reflects those facts on the Kanban.
5. Close the feedback loop. Inspect any worker directly, make project-level decisions with the orchestrator, and return actionable failures or review comments to the agent that owns the work.

AO works with the coding agents and source-control workflow you already use. Agents keep their native strengths; AO supplies the project context, isolated execution, coordination, and operational view that make them work as a system.

Product highlights

Pull requests and agent reviews Keep CI, mergeability, reviewer state, and interactive agent reviews beside the worker, then return requested changes to the same owner.
Agent-controllable browser Preview and inspect a worker's local app beside its interface. Browser profiles are isolated per worker so parallel UI tasks do not share state.
Native interfaces, one supervisor Use structured Chat or the agent's native terminal UI while AO keeps task context, workspace state, and feedback in one place.

Supported agents

27 coding agents supported through one supervised workflow.

Claude Code	Codex	Cursor
opencode	Aider	GitHub Copilot
Grok	Kimi	Pi
Amp	Auggie	Droid
Crush	Cline	Goose
Qwen	Continue	Devin
Kiro	Kilo Code	Vibe
Muse	Agy	Autohand
Kimchi	Prime Agent	OMP

Browse agent setup guides →

Use the interface that fits the moment: structured Chat or the agent's native terminal UI.

Report a bug

Open a bug report from your own GitHub account. A few sentences in your own words about what you did and what went wrong are enough. Add what you expected, reproduction steps, your AO version and OS, or a screenshot if you have them; these are helpful, not prerequisites.

A local coding agent can help you clarify the report and gather evidence using the bug-triage skill. Keep the issue body focused on your observations, with agent-collected logs, database excerpts, and investigation notes in separate attachments. Review any draft before submitting it under your own account. Please don't ask AO Bot to file issues on your behalf; reporter attribution matters.

For help describing a problem, join the bug-triaging channel on Discord. See contribution guidance for more detail.

Develop and contribute

Contributions are welcome across code, docs, triage, examples, and tests.

git clone https://github.com/Untrivial-ai/agent-orchestrator.git
cd agent-orchestrator

Start with the development guide for prerequisites, local setup, and test commands. Read CONTRIBUTING.md before opening a pull request, and use GitHub Issues for bugs and feature requests.

Documentation

Document	Start here when you need
Product documentation	Installation, agent setup, and day-to-day product usage.
docs/architecture.md	Backend mental model, lifecycle, persistence, CDC, status derivation, and daemon boundaries.
docs/backend-code-structure.md	Package ownership and where each backend concern belongs.
docs/cli/README.md	CLI behavior and daemon route mapping.
docs/development.md	Prerequisites, build steps, running tests, and troubleshooting for local development.
docs/STATUS.md	What currently ships on main and what remains in flight.

Follow the journey

Community

Join Discord for help and contributor discussion, follow @ao_build for updates, or start a conversation in GitHub Issues.

Anonymous telemetry

AO uses privacy-preserving product usage and reliability metrics designed to exclude PII and project content. These metrics help us understand adoption and improve the product. To understand which teams and developers get the most value from AO, we also record the GitHub organization or account that owns a project (the owner segment only, never the repository, path, or URL); for a personal repository this is the owner's own username, so that single field is not anonymous. We use it to prioritize improvements and reach out for feedback. Learn more about telemetry and privacy.

License

Agent Orchestrator is available under the Apache License 2.0.