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// FAQs
Everything You Need to Know
We’re a talented team of former Google and Stripe engineers dedicated to solving the complex challenges of productionizing AI for software engineering at scale.
How does pricing work—especially for bursty, idle-heavy workloads?
We offer usage-based pricing and custom VM sizing. Idle Devboxes can be suspended to preserve state to control compute costs. Researchers and OSS contributors can request usage credits, and we provide special tiers for benchmarking and RL training use cases.
What’s the startup latency like compared to traditional VMs or containers?
AS fast as sub-second start including full tool availability. We use seekable images, warm node pools, and other optimizations to ensure rapid devbox availability. Runloop prioritizes “time to agent action”—i.e., how fast an agent can begin doing useful work (e.g., build, test, interact with the codebase).
How is Runloop different from competitors?
Runloop is optimized for AI coding agents, not just developer convenience. Runloop provides stateful, resumable “Devboxes” with micro-VM isolation, fast suspend/resume, and support for multi-turn RL workflows. We minimize “agent blocked time,” not just boot latency.
Can I run arbitrary code and long-running tasks safely?
Yes. Each Devbox is an isolated micro-VM with enforced network policies. That means you can run untrusted LLM-generated code, spawn browsers, or trigger compilers without risking host contamination or tenant bleed. If your agent spawns subprocesses or modifies state mid-run, we preserve it with snapshotting.
Do Devboxes support interactive debugging, browser access, or human-in-the-loop workflows?
Absolutely. Devboxes support port tunneling, SSH, shell access, and browser access, making them ideal for workflows where agents require developer input. Snapshots allow you to pause, fork, or resume agents without resetting state—critical for experimentation and observability.
Can I deploy to VPC?
Yes! Please contact sales@runloop.ai for more information!