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Runloop AI

Run agents in sandboxes and keep them in the loop on GitHub PRs

Runloop AI provides sandboxed devboxes for agent workflows, including turn-based interaction through GitHub pull requests. It’s aimed at developers building coding agents that need to execute commands, keep state across turns, and respond to reviewer comments.

iOS
API
Integrations
B2B
For Developers
CLI
Copilot (Human-in-Loop)
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About

What It Is

Runloop AI is an agent infrastructure and developer tooling platform for running AI agents inside sandboxes/devboxes. The documentation shown here focuses on a turn-based workflow where an agent monitors a GitHub pull request, posts progress updates, and acts on PR comments as new tasks.

What to Know

This is a practical pattern for human-in-the-loop coding agents: reviewers can guide the agent through PR comments, and the agent can keep context across multiple comments. The docs also note a production-friendly approach using GitHub webhooks instead of polling.

Key Features
Runs agents inside sandboxed devboxes
Maintains shell state with named shells
Posts status updates to GitHub pull requests
Reads PR comments as agent tasks
Resumes the latest Claude Code conversation with the `-r` flag
Use Cases
Build a coding agent that updates a GitHub PR as it works
Let reviewers assign follow-up tasks by commenting on a pull request
Run code-changing workflows in an isolated sandbox
Agenticness: Adaptive Collaborator

Proposes and executes multi-step plans with your approval.

High evidence
Last evaluated: Apr 26, 2026
This tool has strong action capabilities but limited safety controls. Use with appropriate oversight.

Dimension Breakdown

Action Capability
Autonomy
Adaptation
State & Memory
Safety

Categories

Pricing

Pricing not publicly available

Details
AddedApril 26, 2026
RefreshedApril 26, 2026
Quick Facts
DeploymentCloud-hosted
AutonomySemi-autonomous
Model supportSingle model
Team supportSmall team
Pricing modelSubscription
Interfaceapi, cli
Sources
Last updated April 26, 2026
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