Running 24 Concurrent Claude Code Instances
A single AI in a terminal is a useful tool. Twenty-four of them running at once — concurrently, each on its own task, all drawing on the same shared skills, coordinated under one controller — is a different thing entirely. It is the difference between a tool and an operation. And I was running them that way before the tooling was really meant to.
Ahead of the tooling
At the time, coordinating multiple Claude Code instances was something the tooling was supposed to be able to do — a capability on the horizon rather than in your hands. I was not waiting for it. I had already worked out how to run two dozen instances concurrently and keep them productive, by building the structure around them that made it hold together.
From one to twenty-four
The leap is not simply opening more windows. Instances running at once only help if they are not tripping over each other: clear boundaries between what each owns, shared knowledge so they stay consistent, and a controller that hands out work and gathers up the results.
- Isolation by project. Each instance works inside its own boundary, so one piece of work can never bleed into another — essential when the work spans different clients.
- Shared skills and agents. Common capabilities live in one place and every instance draws on them, so improving a skill once improves all twenty-four.
- A single controller. One layer distributes work and coordinates the instances, rather than each running blind.
- Validation built in. Work is checked against real, deployed output before it is accepted — not assumed good because an AI produced it.
The outcome
Two dozen tasks progressing at once instead of queueing behind a single operator — consistently, because they share the same foundation. This is the AI First Principles framework at scale — AI first, human second, with the structure doing the coordinating. The structure is interchangeable too: the same approach is not tied to one AI vendor, which keeps the whole operation free to move.
