Multi-Project
Keep several projects active inside one AI-native workstation. Move between them, run work across them, and manage changing priorities without rebuilding your setup.
Instead of treating every repo as a separate setup, keep your projects visible, coordinate active work, and decide what needs you next from one workspace.
Keep every repo in one sidebar and move between them without closing the work in progress or rebuilding the environment around it.
Every chat shows whether it is running, waiting on your answer or done, across all your projects. Go where you are needed.
The terminal, browser and files a chat opened stay with that chat. Come back to it and they are where you left them.
Give a branch its own worktree and its own chat. Two features in one project, both running, neither in the other's way.
Review active projects and coordinate upcoming development tasks from the same workspace instead of planning each one in isolation.
Once your projects are in PandaOS, the workspace becomes the place you return to throughout the day. Open what each project needs, start the work, then shift your focus as priorities change.
Bring the repos and projects you actively work on into PandaOS.
Open the tools and sessions each project needs.
Focus on whichever project needs attention next.
Working across several projects can create a second job: remembering where every session, task and piece of active work lives.
You manage the projects and the setup around them.
See what's happening and go where you're needed.
Every project gets the same agents, the same connected apps and the same memory. Pick up where this page leaves off.
Keep the repos you're building, debugging, and managing accessible alongside the agents and development tools that move them forward.
It's particularly useful for developers handling multiple repositories, freelancers working across client projects, and agencies managing several development environments.
PandaOS agents can analyze repositories, modify or create files, execute terminal commands, and interact with the development environment as part of a task.
Yes. PandaOS includes a Limited mode that keeps agents inside the project folder. On Mac it is enforced by the system sandbox, and scheduled automations always run in it.
Yes. PandaOS supports a bring-your-own-model architecture, including API-key connections and different model engines, so you can choose how AI is powered inside your workspace.
PandaOS's built-in browser can browse websites, inspect web applications, take screenshots, and send those screenshots directly into chat for analysis.
Yes. PandaOS agents can perform multi-step workflows across connected services, including working with repositories, databases, deployment tools, and external applications.