Opensourcing Multiplayer AI in Discord

Bunny is open-sourcing a multiplayer AI development platform that turns a VM or Docker container into a shared workspace with collaborative shells, live previews, and chat-native workflows. The platform adds a semantic layer on top of Git, integrates a validation agent for continuous testing, and enforces governance policies across human and AI agents. This aims to solve context fragmentation and coordination challenges in AI-assisted software development.

Shared remote environment A VPS or container becomes the team's persistent workspace: terminals, live previews, streamed browsers, and a unified timeline where code, feedback, and experiments converge. Collaborative development for the AI era Turn a VM or Docker container into a shared dev station with shared shells, live previews, and chat-native workflows. Self-hosted by default. Discuss in chat. Execute in shared context. Shipping in a single thread Same moment, one source of truth Without bunny With bunny Governed gateway, shared context Without bunny With bunny Current version No shared context Shared context Proposal: 2 devs and silos Broken context Relevant context Instead of each developer working locally and synchronizing through GitHub, teams collaborate directly around a common remote environment, with chat, roles, and permissions intact. A VPS or container becomes the team's persistent workspace: terminals, live previews, streamed browsers, and a unified timeline where code, feedback, and experiments converge. Work from a channel with the same context, the same coding agent, and distinct rights for every contributor, whether engineers, designers, operators, or non-technical members. Install the tools you already use shell, CLIs, scripts, Codex, Claude through prompts and shared workflows in an environment your team controls. The Git commit is often the only durable artifact explaining a project's evolution. But in modern workflows, meaning lives elsewhere: chat threads, agent prompts, collective decisions, tests run, errors encountered, and trade-offs accepted. bunny adds a semantic layer on top of code versioning, connecting each important change to the discussions, goals, and interactions that led to it. Enriched metadata is ingested into a GraphRAG, enabling questions that Git alone cannot answer. Why was this commit made? Which discussion led to this implementation? What objective did this change serve? Which agents or contributors influenced this decision? Current workflows are poorly suited to AI-assisted development. Teams iterate faster, rely more on agents, yet CI arrives too late, takes too long, and sometimes gets bypassed entirely. bunny integrates a validation agent that works in parallel with development: continuously testing changes, detecting regressions, analyzing errors, and suggesting fixes directly in chat. On a shared VM, many contributors work at once: engineers in their shells, multiple AI agents in parallel. A single checkout would mean constant collisions, with one session stomping another's files mid-edit. bunny provisions a git worktree for every agent and every user shell. Each session gets its own working directory and branch on the same repository, locally on the machine for isolated edits, safe parallelism, and merge when ready. bunny sits between your team and every connected tool with a verification and enforcement layer. Before any teammate or AI agent runs a command, opens a PR, or touches an integration, bunny checks authorizations against your policies and RBAC rules. The same governance applies whether the request comes from a human in chat or an autonomous agent, with no backdoors or shadow access. Policies travel with context across GitHub, shells, browsers, and every MCP-connected service. Software development as a living process where humans, AI agents, environments, discussions, tests, and decisions stay connected in one flow.