Orca: the ADE for orchestrating a fleet of coding agents in parallel
Ramón Chancay 👨🏻💻DEV Community
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What do you do when Claude Code proposes one solution, Codex a different one, and Gemini a third? The usual move is to pick an agent up front and take whatever it produces. Orca changes that dynamic: it runs all three at once, each isolated in its own git worktree, and lets you compare the results and merge the one that won. It's an open-source ADE (Agent Development Environment)—MIT, by Stably AI—an environment built for coding agents to work in parallel, not for one person writing line by line. I tried it to orchestrate a fleet of agents, and this is what it does today, on the build they shipped this same week.
TL;DR
Orca runs any CLI agent (Claude Code, Codex, Gemini, Grok, Cursor CLI, OpenCode and 25+ more) in parallel, each in its own isolated worktree, on your own subscription.
It has a CLI (orca worktree, orca terminal) and an orchestration layer with tasks, dispatches and decision gates to coordinate the fleet from a coordinator agent.
It runs on macOS, Windows and Linux, plus iOS and Android apps to monitor and steer agents from your phone. Install via brew or AUR. They ship daily.
What Orca is and what an ADE means
An IDE is designed for a person to read, write and debug code. An ADE changes the primary user: the one operating the environment is the agent, and the person moves to coordinating, reviewing and deciding. Orca describes itself as "the ADE for working with a fleet of parallel agents," and that phrase captures what sets it apart from an editor with a chat panel bolted onto the side.
The practical difference is that Orca doesn't assume one agent, but several running at once. Instead of opening a terminal, launching an agent and waiting, you set up several agents in parallel, each with its own terminal, browser and context, and you see them all in one place. It's open source (MIT license), written almost entirely in TypeScript, and it runs on your own subscription for each agent: there's no billing layer in the middle, you use your Claude account, your Codex account, or whichever you have.
One misconception is worth clearing up before going further: Orca doesn't compete with Claude Code or Codex, it runs them. The useful comparison isn't Orca against an agent, but Orca against the other ways of working with agents. The axis that matters is one: is the tool built for one agent or for several in parallel?
Tool
What it is
Several in parallel
Isolated worktree per task
Orchestration
Claude Code / Codex
CLI agent
Manual, across terminals
Not native
No
Cursor
AI IDE
Background agents
No
No
OpenHands
Autonomous agent
Not native
No
No
Orca
ADE
Yes, native
Yes
Yes
Put another way: the first three are designed around one agent solving a task, and running several in parallel is something you rig up by hand if at all. Orca flips the starting point: the unit isn't the agent, it's the fleet. And because it wraps them instead of replacing them, inside Orca you still use Claude Code or whichever agent you prefer. (The landscape moves fast and several of these tools are adding parallel-agent features; the table is today's snapshot, not a verdict.)
Keep reading
That is the first half. The full walkthrough — with the rest of the implementation, the trade-offs and the things that only show up in production — is on my blog:
Read the full post on ramonchancay.me →
Originally published at www.ramonchancay.me/blog/orca-parallel-coding-agent-fleet.
Disclosure: I maintain Lantunnel. It is Apache-2.0 and the source is linked at the end.
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