Orca — Run Multiple AI Coding Agents in Parallel in One App (Desktop + Mobile + Remote)

On a Friday afternoon, you hand Claude Code a forty-minute refactor. The terminal is occupied, and nothing else can happen in that repo. You want to try Codex on the same task, but a second terminal turns chaotic: two agents edit the same branch, diffs overlap, and you lose track of who is doing what. Then you leave for a meeting, and everything stops. The problem is not a weak agent — it is the missing control panel: one place to run many agents at once, each in its own space, where you can track progress, review each diff, and keep working away from your desk.

What Is Orca? An AI Orchestrator for Parallel AI Coding Agents

Orca Is Not Another Coding Agent

Orca is a control panel for AI coding agents, also called an Agent Development Environment or fleet console. The project is stablyai/orca, MIT-licensed, written in TypeScript on Electron by Stably AI (YC W22), created 2026-03-17. Latest release: v1.4.251, 2026-11-06. As of 2026-11-07, the repo has 117,864 stars and 7,476 forks.

To be clear: Orca ships no model or agent of its own. It runs the CLI agents you already have — Claude Code, Codex, Grok, Cursor, GitHub Copilot, Muse, DeepSeek Harness, OpenCode, Pi, Hermes Agent, Devin, and 20+ others — each on your own subscription and account. Project repo: https://github.com/stablyai/orca — not the separate repo Chaoyi-Z/orca.

The project’s principle: anything that runs in a terminal runs in Orca.

What Problem Does Orca Solve?

First, parallel instead of sequential: several agents handle several tasks at once, or try several approaches to one task. Second, each agent gets its own git worktree, so they never collide at branch or file level. Third, one place to view, chat, review diffs, and merge, instead of N scattered terminals. Fourth, work continues away from your desk: a mobile companion and remote runtime keep agents running on a server.

Who Should Use Orca — and Who Does Not Need It Yet?

Orca fits developers who already use at least one paid CLI agent, run long tasks, want to try several solutions in parallel, or work across many repos. DevOps, SREs, and homelab users comfortable with SSH and VMs also fit.

Conversely, a single agent for short tasks with no waiting means Orca adds little. And with no CLI agent subscription at all, Orca cannot replace that cost.

Orca Architecture and How a Parallel AI Agent Fleet Works

Main Components of Orca

• Orca Desktop: Electron app for macOS, Windows, Linux — workspace, chat, terminal, diff review, built-in browser, mobile emulator.
• Coordinator: the orchestrating agent — splits a large task, assigns it to workers, collects the results.
• Worker agent: a real CLI agent session — Claude Code, Codex, or OpenCode — in its own workspace, with its own context.
• Git worktree: the isolation unit — each worker gets its own worktree and branch of the same repo.
• Remote Orca Server, SSH host, cloud VM: remote runtimes — agents run on when the laptop sleeps.
• Mobile companion: iOS via App Store, Android via APK — pings you when an agent needs a reply; answer in chat.
• GitHub and Linear integration: tasks in one place, a workspace per task, commit and PR drafts from diffs, failing checks sent back to the agent.
• Orca CLI, Plugins, Automations, Computer Use: create worktrees and start workers from the CLI; one-click plugin installs; scheduled-prompt automations; Computer Use lets agents control desktop apps and browsers.

Data and Control Flow — the Article’s Only Diagram

flowchart LR
    User["User<br/>prompt + merge decision"]
    Coord["Orca Desktop / Coordinator<br/>chat UI, terminal, diff review"]
    WA["Worker A: Claude Code<br/>worktree-A / branch-A"]
    WB["Worker B: Codex<br/>worktree-B / branch-B"]
    WC["Worker C: OpenCode<br/>worktree-C / branch-C"]
    Review["Diff Review<br/>line-by-line review, notes, feedback"]
    Merge["Merge Winner<br/>only one version into main"]
    GH["GitHub / Linear<br/>incoming tasks"]
    PR["Commit / PR Draft<br/>from the selected diff"]
    Desk["Desktop App"]
    Mob["Mobile Companion<br/>iOS / Android"]
    Rem["Remote Server / SSH / Cloud VM<br/>agents running in background"]
    GH --> Coord
    User --> Coord
    Desk --> Coord
    Mob --> Coord
    Rem --> Coord
    Coord --> WA
    Coord --> WB
    Coord --> WC
    WA --> Review
    WB --> Review
    WC --> Review
    Review --> Merge
    Merge --> PR
    Review -. "feedback" .-> Coord

Send a prompt to the coordinator, or open a workspace from a GitHub or Linear task. The coordinator splits the task across workers, each running independently in its own worktree. You review each diff line by line, annotate specific lines, and send feedback for fixes.

When one version satisfies you, merge it into main and discard the rest. Orca picks no winner and reconciles no divergent versions — the human decides at review and merge. Sessions move between Chat and Terminal without losing context.

Dependencies and Technical Limits, Stated Plainly

Orca needs Git, a repo with worktrees, one logged-in CLI agent with an active subscription, a GitHub or Linear account for native integrations, and the Electron runtime.

First limit: isolation is at git level, not a sandbox. Worktrees separate branches and files, but workers share the machine — OS, env vars, credentials, network, ports, local databases, caches. Two agents can still clash outside the repo, e.g. over a port. A worktree is not a container or VM.

Second limit: cost multiplies with the number of agents. Each worker is a full session with its own context and tokens; N parallel agents means N times the token cost and usage limits. No independently verified performance figures exist, so this article cites no benchmark.

Third limit: mobile pairing outside the LAN is unconfirmed — the docs place the pairing relay in the repo under cloud/, while a secondary review says the iOS companion only works on the same Wi-Fi. I have not tested this; I only compared the docs.

Fourth limit: the project ships daily (release v1.4.251 on 2026-11-06, 8,084 open issues) — check the docs at https://www.onorca.dev/docs before following them.

How to Install Orca and Run Agents in Parallel

Prerequisites Before Installing Orca

You need macOS, Windows, or Linux, Git, at least one CLI agent — e.g. Claude Code or Codex — logged in with an active subscription, and a git repo to try worktrees in. A GitHub or Linear account is optional. Use the full name in Homebrew: the bare orca cask is an unrelated Plotly cask.

Install Orca on macOS, Windows, Linux, and Mobile

On macOS via Homebrew, the command copied verbatim from the project docs:

brew install --cask stablyai/orca/orca

Upgrade later with brew upgrade --cask stablyai/orca/orca.

You can also download directly from https://onorca.dev/download or https://github.com/stablyai/orca/releases/latest — .dmg for Apple Silicon and Intel, .exe for Windows, AppImage for Linux.

On Arch Linux, via AUR: yay -S stably-orca-bin (stably-orca-git to build from source). On mobile, iOS via the App Store, Android via the APK at onorca.dev/download/android. Checked against the official docs, but not run by me.

Run Your First Agent and Verify Orca Works

Step 1: open Orca and a repo, create a workspace and a first worktree for a small task, and pick a logged-in CLI agent. Step 2: run the agent in Chat, then move the session to Terminal to confirm context is preserved. Step 3: add a parallel worktree for the same task with a different agent. Step 4: review each diff, annotate lines, send feedback, then merge the chosen version.

Expected result: two separate worktrees and branches, each agent with its own chat and terminal, diff review per worker, and a merge applying only the chosen version.

Common Errors and How to Fix Them

Agent missing: check the CLI agent is installed and logged in — Orca installs neither Claude Code nor Codex for you. Wrong software: you typed brew install --cask orca instead of stablyai/orca/orca — remove the wrong cask and reinstall. Branch already exists: check git worktree list, remove the extra worktree or rename the branch. Remote/mobile not connecting: check pairing, the SSH host, and the network.

Uninstall Orca and Clean Up Worktrees — Rollback

Removing Orca cleans up neither worktrees and branches nor granted agent permissions. Before calling it removed, delete extra worktrees with git worktree remove, delete unused branches, check git status, revoke tokens or SSH keys given to the remote host, and turn off scheduled automations. If an agent ever read a .env file or credentials, rotate them.

Technical Review of Orca — Pros, Cons, Security, and Operations

Pros of Orca

Orca reuses subscriptions you already pay for, with no extra model or agent to buy, and supports 30+ CLI agents. Parallelisation is real at worktree level, plus coordinator/worker orchestration — not just more terminals. Line-by-line diff review, focused feedback, commit/PR drafting from diffs, and sending failing checks back to the agent form a closed loop. It is MIT open source, with 117,864 stars.

Cons and Points to Consider

Orca is an Electron app, heavier than a plain CLI — machine resources traded for a fleet interface. More workers means more tokens and review time, since each worker produces a full diff to accept or discard. Features change daily, docs can lag the changelog, and 8,084 open issues show many bugs still open. No independently verified performance figures exist.

Security and Privacy When Running Orca

Agents run with your user privileges on the machine or SSH host. Credentials, tokens, .env files, and SSH keys an agent can read are a real risk — run agents only on repos and machines where you have weighed the access scope, and review permissions and secrets first.

Remote Orca Server and SSH add attack surface: the server always runs, agents run in the background. Use SSH keys, a firewall, and regular updates. Verify the mobile pairing and relay authentication against current docs before use outside a trusted network. Telemetry is anonymous with an opt-out per the docs — disable it if you wish. Computer Use is a very broad permission — enable it only when needed, on a machine without sensitive data.

Operations, Performance, and Scalability

Update Orca via Homebrew or a new release. Scheduled automations help with repetitive work like dependency bumps or triage, but need log and result monitoring. On performance there is no measured data — only qualitative analysis: the bottleneck shifts from “how fast the model runs” to “how many diffs a person can review” and “how many parallel sessions the token budget supports”. That is analysis, not a benchmark.

Orca vs. Similar Tools

Criteria: bundled agent or existing agents; parallel mechanism; coordinator/worker orchestration; diff review and merge; remote and mobile; interface; extra cost; source and licence.

Worktrunk is a CLI for git worktrees for parallel AI agents — lightweight, without Orca’s desktop panel, coordinator, mobile, or remote.

Orkas is a local-first desktop with 16 built-in specialist agents — the opposite of Orca, which uses the agents you already have.

T3 Code controls agents from a phone — mobile is its core, while in Orca mobile is only a companion to the desktop fleet and remote.

Agent Desktop is a computer-use CLI via the accessibility tree — desktop control is its core, while in Orca Computer Use is one feature among many.

Conclusion: there is no absolute “best”. Orca wins as a comprehensive fleet control panel, loses on lightness to Worktrunk, and loses on bundled agents to Orkas.

Orca in Practice — Business, Homelab, DevOps, and IT Administration

A dev team running many tasks in parallel: one coordinator splits a feature into API, UI, and tests across three workers in three worktrees; the dev reviews each diff, merges the winner, discards the rest.

DevOps/SRE and IT administration — agents running in the background on a server: assign agents on a Remote Orca Server, SSH host, or cloud VM to write scripts, update runbooks, and bump dependencies on schedule — only on a locked-down host, never touching production credentials.

Homelab — a fleet of agents on a home server: run Orca remote on a home server, many agents on many self-hosted repos at once, monitored from a phone — keep it updated and permissioned, since home servers are patched less rigorously than cloud.

AI workflow — trying several approaches to the same task: run Claude Code and Codex on the same prompt in two worktrees, compare the diffs, pick one — the user still decides the merge.

Conclusion — Who Should Use Orca, Who Should Not, Next Steps

Three things to remember: Orca is a fleet control panel, not a new agent; its biggest value is parallelisation plus organised review, its biggest cost is multiplied tokens and review time; and a worktree is git isolation, not a sandbox.

Use Orca if you already have a CLI agent subscription, run long tasks, want parallelisation, and work remotely or from mobile. Skip it if you have no CLI agent, only do short tasks, or need strong sandboxing — that needs an extra isolation layer beyond Orca.

Next step: install with the guide above, try a small task with two parallel workers, review the diffs, then expand to remote and mobile. Read the docs at https://www.onorca.dev/docs and the v1.4.251 changelog (2026-11-06) before using new features.

Lessons Learned

1. A worktree only solves branch conflicts — conflicts outside the repo, like ports or shared files, remain; check them before fanning out.
2. Fan-out multiplies cost and review work: only fan out when comparing several approaches is worth the tokens and diff-reading time.
3. The user is the final reconciler: Orca picks no winner, so the review and merge process must exist before you run many workers.
4. Remote and mobile pay off only once pairing and access are locked down; convenience does not replace a security check.
5. The project ships daily, so every instruction here has an expiry date — check the docs and changelog before following it.

Verification Scope

Check date: 2026-11-07. Verified against primary sources: the stablyai/orca repo via the GitHub API at 01:18 UTC on 2026-11-07 (117,864 stars, 7,476 forks, MIT, created 2026-03-17, release v1.4.251 dated 2026-11-06), the README with install commands copied verbatim, and the docs at onorca.dev/docs.

Default vs. opt-in: running existing CLI agents is the default on opening the app; Remote Server, SSH, cloud VM, mobile companion, automation, and Computer Use need configuration or enabling. Anonymous telemetry has an opt-out per the docs.

The numbers here are repo and configuration figures — stars, forks, listed agent count, open issue count — not performance benchmarks. Not verified: Orca was not installed, run, or benchmarked; mobile pairing outside the LAN is unconfirmed; the Orca CLI version-command syntax is unverified.

References

• Official repo: https://github.com/stablyai/orca
• Release v1.4.251: https://github.com/stablyai/orca/releases/tag/v1.4.251
• Homepage and downloads: https://onorca.dev
• Docs: https://www.onorca.dev/docs
• Telemetry docs: https://www.onorca.dev/docs/telemetry