agent-orchestrator vs codeg

Coding-agent workspaces compared

agent-orchestrator and codeg both help developers coordinate multiple coding agents and work across Git worktrees. agent-orchestrator centers on task planning and supervision through pull requests, CI, and review, while codeg brings agent conversations, histories, files, and tools into a shared workspace with several deployment options.

agent-orchestratorcodeg
LanguageGoRust
LicenseApache-2.0Apache-2.0
Stars13.3k4k
Forks1.8k518
Last analyzedOct 19, 2026Oct 19, 2026

Key differences

  • agent-orchestrator uses a project orchestrator to plan and delegate tasks to workers; codeg emphasizes shared conversations, session search, resumption, and handoffs across agents.
  • agent-orchestrator tracks worker activity alongside pull requests, CI, and review on a live Kanban board; codeg combines conversations with files, terminals, notes, and Git changes on a workspace canvas.
  • agent-orchestrator is written in Go, while codeg is written in Rust.
  • Both projects use the Apache-2.0 license.
  • agent-orchestrator is a desktop application with a local daemon; codeg can run as a desktop app, self-hosted server, or Docker container, with mobile clients described in its documentation.
  • The supplied repository figures list 12.7k stars and 746 open issues for agent-orchestrator, versus 3.8k stars and 286 open issues for codeg.

Choose agent-orchestrator if you…

  • want a project-level agent to break goals into delegated worker tasks.
  • need a live view of workers, pull requests, CI, and reviews through merge.
  • prefer isolated Git-backed worker worktrees with the option to use an agent's native terminal interface.
Read the agent-orchestrator analysis →

Choose codeg if you…

  • want to search, import, and resume sessions across agents.
  • need conversations, files, terminals, notes, and Git changes together in one workspace.
  • want desktop, self-hosted server, or Docker deployment options.
Read the codeg analysis →

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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.