I built a desktop app for managing multiple AI coding agents at the same time

I've been experimenting a lot with coding agents, and I kept running into the same problem.

The more agents I used, the harder they became to manage.

I'd have one agent working on a feature, another fixing something else, several terminals open, separate Git worktrees, and then I'd have to keep track of which agent changed what.

So I started building CrewCode.

The idea is basically to treat AI agents like a development crew while you remain the lead developer.

Each agent can work in its own isolated Git worktree, while CrewCode gives you one place to see what they're doing, manage their sessions, review their changes, and eventually bring the work back together.

I'm also trying to keep it provider-independent instead of building around one AI company. I want developers to be able to use different coding agents together depending on what they're good at.

It's open source and I've gotten it to the point where other developers can actually start using it.

I'm curious how other developers handling multiple coding agents are managing this right now.

Are you using worktrees + terminals manually, or have you found a better workflow?

u/Ok_Capital2235 — 16 hours ago
▲ 6 r/coding_agents+3 crossposts

I built a free, open-source desktop app to run a crew of AI coding agents in parallel.

Sharing a tool I've been working on. CrewCode is a free, open-source (Apache-2.0) Electron desktop app that lets you run, supervise, and review multiple AI coding agents across git worktrees from one place.

Instead of juggling terminals, worktrees, PR pages, and separate agent UIs, it keeps the full workflow together:

- Multiple agents, one app — CrewCoder, Claude Code, Codex, OpenCode, pi, Ollama, Hermes, OpenRouter, Grok Build. Structured bridges *and* real terminal panes.

- Worktree-native git — create/switch/merge/remove worktrees in-app; parallel work stays isolated.

- Crew orchestration — launch agents in parallel with different roles/models/effort, a supervisor loop, and save/reuse crew templates.

- Delegated threads — an agent can spawn real, persistent chat sessions and report back.

- Provider switch mid-chat — generates a hand-off summary so the new agent keeps going with context.

- Local plugin platform — sandboxed panels, MCP servers, custom agent providers.

and way More..

I learned alot from this experience with electron apps, on how to optimize multiple agents and keep low memory

Curious what people think of the approach. Let me know in the comments.

Repo: [CrewCode](https://github.com/OnPoint-Dev-Tools/crewcode)

u/Ok_Capital2235 — 11 days ago