Local command center for parallel AI coding agents

Run several AI coding projects side by side without tangling branches or context

Problem

Developers report that when they experiment with multiple AI models on personal projects, the best approach is cloning the repo and letting each agent work in parallel. But in practice, multiple agents, branches, and repos easily cross-contaminate context, and local worktrees become messy. Others mention manually moving results back into the main workspace is slow and error-prone.

Solution

A local-first desktop command center that puts each AI coding task in its own clone or worktree, isolating workspace, branch, and session state. Users assign tasks, inspect diffs, compare approaches, and merge validated changes back into the main repo with one click. No cloud backend required; it uses the user's own model keys.

Users

Indie hackers juggling multiple side projects, small-team tech leads, and engineers using AI agents for prototyping or refactoring.

MVP

Auto-create and clean up Git worktrees; keep per-task agent sessions and context; side-by-side diff view with human approval; one-click merge or discard; run locally with bring-your-own API key.

Revenue

One-time desktop license at $29–$49; optional annual subscription for team templates and priority support.

Why now

Coding agents are shifting from single chats to long-running, multi-branch execution, while most tools remain session-centric. Worktrees and local inference are mature enough for an indie developer to build the coordination layer without owning models or cloud infra.