Orca

Most developers running AI coding agents discover the problem the hard way: agents clobber each other’s changes, or you lose track of which branch is running what task while you chase down a terminal. Orca treats this as the core problem. It provisions each agent its own git worktree and terminal session, runs them in parallel, and gives you a single task board showing every agent’s status, elapsed time, and last action — the vendor’s own demo shows five agents running concurrent checkout regression tests on the same repo without conflict.

The differentiating feature is the worktree-first architecture. Where other tools put agents in a shared working directory or queue them serially, Orca creates genuinely isolated environments per task. The built-in file editor and git tracking sit alongside the terminals, so you can inspect what an agent changed, review the diff, and commit — or revert — without leaving the environment. The vendor describes this as ‘bring your own agent’: you plug in whichever CLI agent subscription you already hold, so you are not locked into a proprietary model.

Orca fits teams doing rapid iteration across multiple feature branches — the mobile companion app means a developer can kick off agents before leaving the office and check status from a phone. The self-hosted Enterprise option makes it viable for teams with data residency requirements. Where it breaks: Orca is not a general IDE. Teams that need a rich extension ecosystem, language server integrations beyond what the built-in editor provides, or deep debugger support will find themselves running Orca alongside their existing editor — at which point context-switching returns in a different form.

Orca is available on macOS, Windows, and Linux. The vendor states an Enterprise tier with self-hosted deployment. The project carries 46,000 GitHub stars at the time of listing, which community signals suggest reflects adoption among developers already running agent-heavy workflows rather than casual use.