Local-First AI Workspace

Local-First AI Workspace

Start from the desktop, keep work close to your repos and files, and extend the same setup to remote environments when needed.

What the workspace model enables

Agents live inside folders, conversations are saved as files, workspace state stays inspectable, and the same setup can travel to remote machines when work moves there.

Why local-first matters

Strong agents need access to real projects, real files, and real tools. A local-first workspace keeps that environment close to the developer and team instead of hiding it behind hosted abstractions.

What teams gain

Desktop-first workflow for daily work
Project files and agent state stay visible
Local and remote workspace continuity
Reusable skills and tools per workspace
Diff-based review of agent changes
A better fit for repo-based teams than browser-only tools

FAQ

What does local-first mean here?

It means the workspace begins on the desktop near the team’s repos, files, and tools rather than inside a hosted browser sandbox.

Can the same setup run remotely?

Yes. OpAgent already shows one agent environment for local and remote workspaces.

Is this only for developers?

No. The model is developer-friendly, but the core value is that teams can work with files, tools, and reusable agent capabilities in one place.

Why not just use a web workflow builder?

Workflow builders are useful, but they are not a substitute for a general workspace where agents can operate on real project context.

Start with a workspace your team already understands

Download the desktop app and run agents where your files, repos, and team context already live.