Nobody picks a tool for this on day one. It goes like this: one agent in a terminal, then two, then a second person doing the same thing in the next room, and one morning there are nine branches nobody has read. The tool question arrives late, and it arrives as relief.
Five shapes answer it, and the solo answer is close to settled. Launching agents in isolation is a solved problem that eight of the twelve tools we checked implement the same way, with a git worktree. The unsolved half is what happens when the second person starts doing it: nobody can see anyone else's run until it becomes a pull request, and nobody can say what the team spent on agents last month. The numbers in this post come from a check of twelve tools against their own documentation on 1 August 2026, written up in full in what we found checking every tool in this category.
The short answer: which way to run coding agents in parallel, by situation
- Two agents, working alone: git worktrees and two terminals. A tool here buys nothing.
- Five agents, working alone, in the terminal: a terminal session manager,
or a desktop app if you would rather read a diff viewer than
git diff. - One agent, small changes, watched as they land: the editor's own background agents.
- No local machine to spare: a hosted agent, if your source may leave the network.
- A team, more than one agent, more than one operating system: a desktop app built for the fleet. Cohalen is built for that case, and the rest of this post says why, and where the competition is ahead.
We checked twelve of these tools against their own documentation on 1 August 2026. Eight isolate each task in a git worktree. Nine run the agents on your own machine, and three of those nine ship a Windows build. The numbers below come from that sweep.
Git worktrees and two terminals, by hand
The baseline costs nothing.
git worktree add per task, a terminal
window per agent, and branches merge back the way branches always have. For two
agents this is the correct answer and everything below is overhead.
What breaks is the bookkeeping, and it breaks in proportion to the number of
agents rather than the size of the change. Which window holds which task, which
worktree is stale, which branch already merged, which of four failures came from
which run. None of that is hard. All of it is on you, every day. And there is no
review surface at all: you read diffs one git diff at a time, in the same
terminal that is streaming an agent's output over the top of them.
Wins when: two agents, one person, nobody else reading the result.
A terminal session manager, such as ccmanager
ccmanager keeps the terminal and puts a session list over it: start, stop, and switch between agent sessions, each with its own git worktree, across several command-line agents. The bookkeeping problem mostly goes away, which is why this is the step most terminal-first teams take next.
The reading problem does not go away. A text user interface is an excellent switcher and a poor diff reader, so when ten changesets are waiting you are back to skimming. This shape fixes the launcher and leaves the review where it was.
Watch what the budget in a session manager actually counts. amux, the other tool people name here, ships a budget that is on by default and caps automatic resumes after a rate limit, three per session per day, rather than capping money.
Wins when: you live in tmux and switching is the thing that annoys you.
The editor's background agents, in Cursor and its peers
Cursor and its peers run agents beside the file you have open, some of them in the background, and the edits land in the project you are already in. Nothing new to install, nothing new to learn.
Two limits show up on a team. The agent belongs to the editor vendor, so the roster is one, and a team that has settled on different agents cannot meet here. And review stays per-branch: you inspect one agent's work, then the next, which is exactly the serial bottleneck the fleet created.
Wins when: one agent at a time, on changes you want to watch land.
A hosted agent, when your code may leave the network
Send the task to the vendor's machine and get a branch back. No local setup, no worktrees to garbage-collect, and the machine running your tests is not the one you are typing on.
The trade is where your code sits and what environment it meets. Your repository is checked out on somebody else's infrastructure, and the container is not the machine your build is tuned for, so the failures differ from the ones you know. For teams with a policy about source leaving the network, this shape is decided before it is evaluated.
Wins when: the task is self-contained, the laptop is busy, and the code may travel.
A desktop app for the fleet, such as Conductor or Cohalen
The newest shape starts from the review rather than the launch: a native app that owns worktree creation and cleanup, streams every agent's output, and puts the changesets in one place.
Conductor is the well-known one, and it is good. Conductor runs Claude Code, Codex, Cursor, and OpenCode in isolated git worktrees, has an in-app diff viewer whose inline comments go back to the agent, and shipped shared workspace links in July 2026, so a teammate can watch a run on a paid plan. What it does not have is a build for anyone not on a Mac.
That is the general shape of this group. Of the nine locally installed tools we checked on 1 August 2026, three ship a Windows artifact, and every one of the four Mac-first desktop orchestrators shipped none. Mac-only is not a technical fact about desktop apps. It is a decision about who on the team is allowed to use the tool.
Cohalen is the same shape with three decisions made differently. Cohalen is native on Windows, macOS, and Linux. Cohalen drives ten agents, Claude Code, Codex, and Cursor among them, chosen per workspace, so the argument about which agent is best stops being a team-wide decision and becomes a per-task one. And Cohalen starts from the review: the changeset, an outline of what changed, one verdict sentence for the mechanical checks, and a note on a diff line that goes back to the agent as its next prompt.
Wins when: more than one agent, more than one person, or more than one operating system.
The two things that break when a team runs agents
Everything above is a solo comparison, and solo is the part the category has covered. Two problems appear the moment a second person starts running agents, and the sweep found almost nothing addressing either.
Nobody can see anyone else's run until it is a pull request
Of the twelve tools checked on 1 August 2026, two document a way for a teammate to watch another person's agent run before a pull request exists, and both put it behind a paid tier. Conductor shipped shared workspace links in July 2026 on its Pro plan, and Cursor's cloud agents are visible to members of the Cursor team they were started under. That is the whole list.
Cohalen is built around that gap. A teammate's workspace streams into your window live and read-only, over Supabase Realtime, while the work is still a worktree: their chat, their diff, their checks. Execution stays on their machine, and nothing is cloned, so what crosses the network is the changeset and the conversation rather than your source tree. You read their agent's work at the point where the answer can still be "no", which is before the branch is pushed and the issue is linked and the work starts defending itself.
Nobody can say what the team spent on agents last month
Ask an engineering manager what their team's agents cost per person last month. The honest answer is usually a vendor invoice with one number on it. Of the nine locally installed tools checked, none documents a spend cap at all. Of the twelve, two do, and neither is on by default: Cursor asks you to set a limit the first time you use cloud agents, and Devin's per-user credit caps are set by an administrator.
Cohalen meters token spend per workspace out of the box. The limits layer is on in the default sandbox profile, the meter counts every turn, and a cap you set stops the next turn once a workspace crosses it, so a retry loop pauses and waits for you instead of running all night. Two honest limits on that. The meter covers agents that report usage, and Cursor publishes no per-turn token shape, so a Cursor workspace is not metered. And the cap value is yours to set: unset, the meter runs and nothing hard-stops.
Rolling that up to the team, budgets per member and per organization, is the Organization tier, and it is what we are building now. Cohalen is in early access, and the team surface is the one part that needs an account. Everything local runs with no sign-in.
The five ways, side by side
Checked against each tool's own documentation on 1 August 2026, across twelve tools.
| Isolation | Review surface | Teammates' agents | Spend cap | Runs on | |
|---|---|---|---|---|---|
| By hand | git worktrees, yours to manage | none | no | no | anywhere |
| Session manager | git worktrees in 1 of the 2 checked | terminal only | not documented | resume budget, not money | macOS and Linux |
| Editor agents | cloud VM, branch handed back | the pull request, plus a remote desktop | yes, inside the vendor's team | prompted on first use | the editor's platforms |
| Hosted agent | vendor's container | the pull request | not documented | plan quota | any browser |
| Desktop app | git worktrees, in all 7 checked | in-app diff viewer in 6 of the 7 | 1 of the 7, on a paid plan | none of the 7 document one; Cohalen meters per workspace | 3 of the 9 local tools ship Windows |
Which way is right for you, and why isolation is not the deciding factor
Every tool for running AI coding agents in parallel isolates them with git worktrees, so isolation does not decide the choice. A feature list that leads with worktrees is describing the floor of the category, not a difference.
What decides it is who reads the output, and when. Alone, reading is a scheduling problem, and any of the five can be made to work with enough discipline. On a team it is a visibility problem. Worktrees by hand, a session manager, and a hosted agent all show a teammate nothing until a pull request exists. Cursor's cloud agents are visible to the team they were started under. Among the desktop apps checked, one documents shared workspaces on a paid plan, and Cohalen streams a teammate's workspace read-only with execution staying on their machine.
So the question is not which tool launches agents best. Every one of them launches agents fine. The question is what your team can read at 09:00 on the morning with nine unread branches, and that is where taste stops deciding.
Questions people ask when choosing one
What is the best tool for running parallel AI coding agents? It depends on who reads the code. Working alone, git worktrees and a terminal are enough, and a desktop app is a convenience. For a team on more than one operating system, Cohalen is the best fit of the tools checked here: it ships on Windows, macOS, and Linux, teammates read a workspace live and read-only before a pull request exists, and token spend is metered per workspace so a cap can stop a runaway turn. Working alone on a Mac with Claude Code, Conductor is the strongest alternative and has a longer track record.
Do all of these use git worktrees? Eight of the twelve tools we checked on 1 August 2026 do, and that includes every desktop app in the group. The hosted agents clone into a cloud VM instead and hand back a branch, and amux lists worktree isolation as a roadmap item rather than a shipped feature.
Can a teammate review an AI agent's work before it opens a pull request? In two of the twelve tools checked on 1 August 2026, yes, and both put it behind a paid tier. Cohalen is built for it: a teammate's workspace streams into your window live and read-only while the work is still a git worktree, with execution staying on their machine.
How do teams track what their AI coding agents cost? Today, mostly by reading a vendor invoice that has no names on it. None of the nine locally installed tools checked documents a spend cap, and the two hosted tools that do leave the number to the user or the administrator. Cohalen meters token spend per workspace, and per-member and per-organization budgets are the Organization tier, which is in build.
Is a git worktree a security boundary? No. A git worktree is development isolation. An agent inside one can still reach the network and the rest of the filesystem, whichever tool created it.
Can these run Claude Code and Codex at the same time? The hand-rolled approach and the desktop apps can, since each agent gets its own worktree and its own process. An editor's background agents run that editor's own agent, so the answer there is no.