How Do You Agent - Running 5-8 Claude Code Agents in tmux
Most developers run one AI agent at a time. But the real productivity unlock is running five to eight Claude Code agents simultaneously in tmux, all working on the same codebase. Here is how to actually make that work.
The tmux Setup
Each agent gets its own tmux window with a descriptive name. tmux new-window -n "auth-refactor" beats "window-3" every time. When you have eight windows open, you need to know what each agent is doing at a glance.
Split your terminal into a grid with tmux split-window so you can monitor multiple agents. A 2x2 grid showing four agents simultaneously is the sweet spot for visibility without squinting.
Task Decomposition Is Everything
The hard part is not the tmux config - it is breaking work into independent chunks. Each agent needs a task that does not conflict with what the others are doing. Frontend components, backend endpoints, database migrations, and test files are natural boundaries.
If two agents touch the same file, you will spend more time resolving conflicts than you saved by parallelizing. Plan your task boundaries before spinning up agents.
Practical Limits
Five agents is productive. Eight agents is possible but requires more coordination overhead. Beyond eight, the merge conflicts and context management eat into your gains. The bottleneck shifts from coding speed to your ability to review and merge the output.
Monitoring and Recovery
Check on each agent every few minutes. They sometimes get stuck in loops or go down a wrong path. A quick redirect early saves twenty minutes of wasted tokens later. Use tmux select-window -t "auth-refactor" to jump between agents quickly.
The key insight is that parallel agents are not about doing things faster - they are about doing more things at once while you orchestrate.
Fazm is an open source macOS AI agent. Open source on GitHub.