Today I'm making a contribution to the AI-agent-focused open source community: git-viewspace, a way for multiple agents to share the same git repository cheaply. (Link in comments) When several AI agents work on the same codebase, giving each one a separate clone is straightforward—but it duplicates data and leaves you coordinating branches, commits, and integration yourself. Git Viewspace takes a different approach: independent lightweight working directories (views) backed by one shared Git repository. Each agent gets its own view of a specific commit, using virtual file system drivers, one of which creates a private writable layer for its changes. Unchanged files are read directly from Git through a shared filesystem backend, rather than copied into every workspace. A coordinating daemon manages view lifecycles and serializes publication operations, so agents don’t race against the same Git index. A view takes under 0.5 seconds to create, and uses up minimal disk space even for large repositories. You can have literally hundreds of these with minimal overhead. The result is a foundation for parallel agent workflows with explicit boundaries: - Independent edits and branches for each agent. - Shared repository storage and decoded-content caching. - Explicit commit, merge, and snapshot-update operations. - Machine-readable status and command results. - Recovery handling for interrupted filesystem operations. - Support for explicitly prepared, pinned submodules. Git Viewspace is not an agent framework, task scheduler, or security sandbox. It doesn’t decide which agent should do what, and it doesn’t make conflicting changes disappear. It provides the filesystem and Git coordination layer underneath those decisions. The implementation uses Python, Linux FUSE, and OverlayFS. Version 0.1.0 ships as one installable package, with documentation, regression tests, and real-mount lifecycle and recovery checks. Licensed under Apache-2.0 through Adapt Framework Solutions. If you’re building systems where multiple agents collaborate on a repository, I’d welcome feedback—particularly on integration workflows, operational simplicity, and what you’d need before adopting it yourself.