Runloop devboxes are the foundation of building AI coding agents fast. We built devboxes because we were tired of hitting the same common problems and needs when building new agents.

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Devboxes & Your Stack

Your AI agent will need to do more than just chat. Very likely, you are building an agents that will:

  • Query external APIs
  • Pull, build, and execute code from git repositories
  • Run a headless browser to scrape or interact with websites
  • Read and write files on a filesystem
  • Run proprietary code or binaries

In development, it’s easy to do all of these things with a script on your local machine. But in production, you’ll need a better approach. That’s where devboxes come in.

Runloop devboxes are the isolated virtual machine your AI agent does its work on. By building your agent against devbox APIs, your agent can do all of these things without you investing significant time and effort in building infrastructure.

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Key Devbox Features

  • Isolated, ephemeral virtual machines: Devboxes are created on demand, and deleted when they are no longer needed.
  • Super fast boot times: Our base devbox images are optimized to boot in less than 200ms.
  • Stateful or stateless: By default, devboxes are stateless and are destroyed after each run. But devboxes also support snapshot, suspend, and result, each with one simple API call.
  • Customizable sizes and images: You can choose machine size and resources from a range of options, and you can create and customize team-shared images with blueprints.

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Working with Devboxes

Your agent code will interact with devboxes through the Runloop API. We provide client SDKs for Python and Typescript.

You can also use the Runloop CLI and the Runloop Dashboard to view, manage, and monitor your devboxes.

Ready to get started? Read on for quick examples showcasing common devbox uses.