One thing I've noticed while using AI coding tools is that the bottleneck isn't usually the model anymore — it's coordination. As projects grow, you end up juggling multiple agents, multiple branches, multiple terminals, and multiple experiments at the same time. Running one agent per task sounds great in theory, but in practice it quickly turns into a mess of windows, context switching, and forgotten worktrees. That's the problem Orca was built to solve. Rather than acting as another AI coding assistant, Orca serves as a workspace for managing entire fleets of coding agents. Each task runs in its own isolated git worktree with its own environment, terminal, and context, making it possible to run Claude Code, Codex, Gemini, Cursor CLI, OpenCode, and other agent frameworks side by side without interfering with each other. A lot of effort has gone into making multi-agent development feel natural instead of chaotic. Diff reviews, worktree management, agent monitoring, markdown workflows, browser integration, and cross-platform support all live inside the same environment. The goal isn't replacing developers — it's giving developers better leverage by allowing multiple agents to explore, build, test, and iterate in parallel while keeping everything organized. Visit us onorca.dev/ What makes the approach particularly interesting is that Orca doesn't lock developers into a specific model provider. Bring your own subscriptions, use the agents you already trust, and orchestrate them from a single control center designed around real development workflows rather than isolated chat windows. Still shipping fast and expanding the platform, but the project is already open source and available for anyone interested in exploring what parallel AI-native software development looks like.

Every CLI Agent Claude Code, Codex, Cursor CLI, Gemini, Copilot, OpenCode, Pi — preconfigured. Any other CLI agent drops right in.