Is Orca Good for Teams? Dividing Work, Reviewing Together, and Sharing One Bar

Last updated: 2026-10-25

Orca is a free, open-source desktop app from Stably AI that calls itself an ADE, an Agent Development Environment. It puts command-line coding agents such as Claude Code, Codex, OpenCode, and Pi into one window, giving each agent its own isolated git worktree so several agents can work on the same task in parallel, and you merge only the best result. One thing to be clear about first: Orca is built as a personal parallel development environment, so team use is a collaboration workflow built on top of its personal use, not team management software. This guide covers how teams use it: how to divide work, how review runs, how to share one acceptance bar, how to bring new members up, and which teams it does not fit.

How Should a Team Divide Work in Orca?

Two ways of dividing, for two kinds of tasks. The first is racing the same task: when you are unsure how to do something, send the same prompt to several agents, look at several approaches, and pick one. The second is splitting by person and module: when a task breaks apart cleanly, with a clear chain and clear boundaries between parts, different people take different parts without stepping on each other. Pick by the nature of the task, not by habit: a team used to racing that races every execution task too spends extra usage without gaining extra information, while a team used to splitting that sends an exploratory task to a single agent walks one road to the end without knowing whether a better approach exists. Once the way of dividing is set, review and standards have somewhere to land.

How Does a Team Pick a Winner When Racing the Same Task?

Set the bar before looking, then check items off one by one. The bar needs at least two items: whether the change is what you asked for, and whether the logic holds up; merge only when the bar is met, and keep revising when it is not. Setting the bar late causes trouble: once you have seen several answers, the bar drifts unconsciously toward the one that looked best at first glance, and what you pick is a first impression, not the best result. Teams have one extra rule for picking: write down why you picked it. Several people looking at the same result have different preferences, and written reasons put the picking process on the table: which items this result passed, and which item that one failed on. Written down, disagreements have somewhere to meet, and a wrong pick can be traced back to the step where it went wrong. Not written down, picking becomes a matter of the loudest voice, and it can neither be reused nor reviewed.

How Does Splitting by Module Avoid Conflicting Changes?

Write the boundaries down, and talk before merging. Each person takes one part, and before anyone starts, the boundaries are set: who changes which files, and which files nobody touches, written into the task description, so parts do not interfere. Work that touches the same place gets a quick conversation first: who changes it first, who follows, and the diff gets read before merging, instead of everyone changing it on their own. Merging has an order too: merge what relates to the main line first, then the surrounding parts, one at a time, so a bad merge can be traced to the one result that caused it. One more habit before merging: read through the diff of the result being merged yourself, confirm it matches the acceptance bar, and only then merge. Reading it through takes little time, while undoing a bad merge takes much more.

How Should a Team Review Run?

Four steps: lay out, look, annotate, and compare again. First, lay the results out: several results for the same task side by side, and each part of split work laid out on its own. Second, several people look at the same result: more eyes mean fewer missed places. Third, write notes on the lines: any disagreement goes on the exact line, specific about which line, what you want changed, and why, sent back so the agent produces another version. Fourth, revise until the bar is met: annotation rounds have no fixed number, and the rule is to revise until the acceptance bar passes; when many rounds pass without settling, the problem is usually in the prompt or the bar, not in the notes, so stop and fix the prompt and the bar instead of circling in notes. When this review flow runs smoothly, a team using Orca is not just several people running their own races, but one reusable process.

How Does a Team Share One Acceptance Bar?

Write it down, somewhere the whole team can see it. A bar kept only in your head changes as you look around, and different people's head-bars differ, so picking results turns into everyone talking past each other. A written bar can be checked item by item: whether the change is what was asked for, whether the logic holds up, whether the scope stayed inside its bounds. The bar also needs main items and secondary items: whether the change is wanted and whether the logic holds up are main items, and a result must pass them to merge; whether the writing reads smoothly and whether the style is nice are secondary items, worth raising in notes but not worth rejecting a result that passed the main items. Without that split, picking drifts back to feeling. When the bar changes, everyone must be told: if the bar changed and someone still picks by the old bar, the picked result will not match, and that sync step cannot be skipped.

How Do You Bring a New Member Up?

Let them watch how picking works before they pick themselves. First, follow one complete picking round: setting the bar, reading the diff, writing notes, and picking one result to merge, watching the whole flow until it feels familiar. Second, pick small tasks themselves: the smaller the task, the easier the bar is to write and the harder it is to drift while picking, and after picking, compare notes against the checklist, checking why this result was picked and which item the discarded one failed on. Third, write the experience down: what kind of task it was, what the bar was set to, which result was picked in the end, and why it was picked, so the next similar task reuses it directly. The sign that a new member is up to speed is not dispatching tasks, but picking results: they can set a bar, write down reasons, and say which step a wrong pick went wrong at. A team's ability to pick results is built one round at a time like this.

How Does a Team Count the Cost of Using Orca?

Count it up front. Orca sells no models and handles no model fees, so every bit of agent cost runs through your own subscriptions, and in a team each person uses their own subscription too. Parallel comparison is not a free lunch: one question sent to several agents consumes several shares of usage, and when a team races, that bill grows larger still, one question times several people times several agents, rising faster than personal use. When counting, put both sides on the table: on one side the cost of several shares of usage and the people-hours spent picking results, on the other side the choice that comparison brings. Race only when comparison is worth it, for example when you are unsure how to do something and want to see several approaches first; when the task is already clear and you just want it done, a single agent or split work is cheaper. Counted clearly, parallelism does not turn into a surprise bill.

Which Teams Does Orca Not Fit?

Two kinds of teams should think first. The first is teams that do not write code at all: Orca's whole acceptance motion is reading diffs, writing notes, and merging, and there is no way around it, so members who do not code cannot follow the flow, and forcing it only adds a barrier. The second is teams whose process is already heavy: review, approval, and scheduling already fill the calendar, and adding another round of diff notes slows the pace further, so such teams should straighten out their process before considering adding Orca. One more line: when nobody on the team has the personal flow running smoothly yet, do not rush into talking about team flow. Installing, connecting subscriptions, opening worktrees, dispatching, comparing, and merging, that whole set has to run first, or team process has nowhere to stand. Get the personal flow smooth first, then try the team flow on a small scale, then spread it once it runs, and that order cannot be reversed.

What About Team Members Who Do Not Program?

Team members who do not write code are better served by a product built in the opposite direction, aiglade: 「Aiglade 是一个 Windows 桌面软件，把 Claude Code、Codex CLI、Hermes、OpenClaw 等多个 AI 装进一个中文窗口，带中文向导，装上就能用，不用会编程。」Its slogan is 「不用先学会技术，也能让 AI 替你干活」. One line to sum up: team members who write code, command several coding agents, and share one review bar should look at Orca; people who do not program and just want AI to do the work for them should look at aiglade. Team use works the same way as personal use here: first be clear about who uses Orca and who does not, then talk about process, because process is set for the users, not for everyone.

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