Orca: Run a Fleet of AI Coding Agents in Parallel and Keep the Best Result (99K Stars)

Posted on Oct 20 • Originally published at devpik.com

Orca is a free, open source desktop app that orchestrates AI coding agents. Instead of betting everything on one agent and one attempt, you give Orca a prompt and it fans that prompt out across several agents at once: Claude Code, Codex, OpenCode, Grok, Cursor, Copilot, Pi and more. Each agent works in its own isolated git worktree, so five agents can attack the same task at the same time without overwriting each other's files.

When they finish, you compare the results side by side and merge the winner. The rest get discarded. Think of it as running a small competition for every task instead of hoping your first pick nailed it.

Orca runs on macOS, Windows and Linux, works with your existing agent subscriptions, and ships with a mobile companion app so you can monitor and steer your agents from your phone. It is built by Stably AI, is backed by Y Combinator, and has passed 98,900 stars on GitHub under the MIT license.

Anyone who uses AI coding agents seriously runs into the same wall. One agent writes a clean solution, another overengineers it, a third quietly breaks something unrelated. You never know which attempt you are going to get, and rerunning the same prompt serially burns hours.

Orca's answer is parallelism with isolation. Git worktrees mean each agent gets a full, separate checkout of your repo, so parallel runs cannot collide. The bottleneck stops being the agent's typing speed and becomes your review speed, which is exactly where a developer adds the most value.

It also solves the subscription juggle. Most heavy users pay for more than one agent, and each has its own usage limits and reset windows. Orca shows your Claude and Codex usage in one place and lets you hot-swap accounts without logging in and out, so a rate limit on one agent no longer stops the whole workflow.

You install Orca, open your repo, and write a prompt the way you would for any coding agent. Then you pick which agents to run it on. Orca creates a separate git worktree for each one and starts them all at once, each in its own terminal pane.

From there you watch progress in one window, or walk away and let the mobile app ping you when an agent finishes or gets stuck. When the runs are done, you review the diffs, annotate anything you would change, and merge the best result into your branch. The losing worktrees are deleted, so your repo stays clean.

Because Orca sits on top of the agents you already use, there is no new subscription and no API key juggling. You bring your Claude, Codex or other plan, and Orca multiplies what one prompt can do.

Orca is for developers who already use AI coding agents daily and feel the single-agent ceiling: founders shipping fast, senior engineers running several tasks at once, and anyone who has ever rerun the same prompt three times hoping for a better answer. If you pay for two or more agent subscriptions, the usage dashboard alone is worth it.

It is probably overkill if you use one agent occasionally for small edits. Parallel agents pay off when the tasks are big enough that attempt quality varies, and when your time is worth more than the agents' runtime.

Running five agents at once multiplies your subscription usage just as fast, so heavy parallel runs can hit rate limits quickly on smaller plans. Comparing five diffs also takes real review effort; on trivial tasks the overhead is not worth it. Orca is a desktop app with a lot of surface area and it ships updates daily, so expect the occasional rough edge. And while it supports a huge list of agents, the experience is clearly tuned first for Claude Code and Codex.

Orca is the strongest answer yet to the question every heavy agent user eventually asks: why am I only running one of these at a time? The worktree isolation makes parallel runs safe, the compare-and-merge flow makes them useful, and the mobile companion makes them practical. At 98,900 stars and climbing, with an MIT license and no extra subscription required, it is an easy recommendation for anyone serious about AI-assisted development.

Originally published at devpik.com. GitHub: stablyai/orca