Running Claude Code on multiple tasks at once gets messy fast. Files overwrite each other, branches get tangled, and you spend more time fixing the env than shipping code. mitshe gives every agent its own isolated Docker container — separate terminal, browser, git state. Switch between sessions like browser tabs. No more git stash chaos, no branch juggling. Self-hosted, bring your own API keys. Built for devs who run AI agents in parallel and want their sanity back.

Wispr Flow: Dictation That Works Everywhere — Stop typing. Start speaking. 4x faster.

Stop typing. Start speaking. 4x faster.

I built mitshe because I kept losing my mind running Claude Code on multiple tasks at the same time. You'd start one agent on a refactor, another on a bug fix, and within 10 minutes they'd be overwriting each other's files, switching branches mid-edit, and leaving git in a state that took longer to untangle than the original work would have taken. The "fix" was a pile of bash scripts, tmux panes, and git worktrees. It worked, but I spent more time managing the env than actually shipping. mitshe is what I wish existed: every task gets its own isolated container with a dedicated terminal and browser. Switch between agents like tabs. Snapshot environments when you want to reuse a setup. Define your Claude Code instructions once as Skills and apply them anywhere. It's self-hosted and you bring your own API keys your code never leaves your machine. Would love feedback, especially from anyone who's tried to scale parallel AI agents and hit the same wall. What's been your workaround?

Wispr Flow: Dictation That Works Everywhere — Stop typing. Start speaking. 4x faster.

Stop typing. Start speaking. 4x faster.

Mitshe

Run multiple Claude Code agents in parallel, without chaos

Run multiple Claude Code agents in parallel, without chaos