How to Run Claude Code Agents in Parallel

One Claude Code agent is productive. Three, running at once on different features, is a different kind of productive — if you can keep them from stepping on each other and still review what they produce. Here’s how parallel agent work actually gets done, and where each approach fits.

First: make sure the work is actually parallel

Before spinning anything up, split the work into independent tasks. If Task B depends on Task A’s output, running them “in parallel” just means merge conflicts with extra steps. The unit that parallelizes well is a scoped feature: clear goal, its own files, definition of done. (This is why user stories map so cleanly to agent runs.)

Practitioners consistently land on the same sweet spot: 2–3 agents at once. Beyond that, the bottleneck isn’t the agents — it’s your ability to review their output.

The three mechanisms

Git worktrees — parallel branches, zero collisions. Worktrees let you check out multiple branches of the same repo into separate directories, one agent per directory. Claude Code supports the pattern natively, and it’s the foundation most parallel setups build on. Full isolation; the cost is managing N checkouts and merging N branches.

Subagents — parallelism inside one session. A single Claude Code session can fan work out to subagents that inherit the parent’s context. Great for divide-and-conquer within one task (research three approaches, refactor four modules); not for independent features, since everything still lives in one session and one working tree.

Agent teams — shared task list, coordinated files. Multiple specialized agents work the same project against a live shared task list, watching each other’s progress to avoid editing the same files. The most “team-like” mode, and the most coordination-sensitive.

The part everyone underestimates: visibility

Running parallel agents is a solved problem. Knowing what’s happening is the hard part: which agent is running, what’s queued, what finished while you were reviewing something else, and what each run actually changed. A terminal per agent doesn’t answer any of that at a glance — and glancing is the whole job once you’re supervising instead of typing.

This is where a board earns its keep. In Instify, each parallel unit is a story card: select the stories you want to ship, hit Run, and the board shows every agent’s status live — Backlog, In Progress, Done — with per-story history of what was built. Quota hit mid-run? The work queues and auto-resumes. Parallelism without a dashboard is how features get shipped twice or not at all.

The short version

Split work into independent, scoped features before parallelizing anything.
2–3 concurrent agents is the practical ceiling — review capacity, not compute, is the limit.
Worktrees for independent features; subagents for fan-out within a task; teams for coordinated multi-agent work.
Whatever mechanism you pick, run it behind something that shows all agents at a glance.

Run Claude Code and Codex in parallel — on a board, not in five terminals. Download for Mac → · See the kanban board for Claude Code →