MLOps.community The Future of AI Agents is Sandboxed
11 snips
Dec 19, 2025 Jonathan Wall, CEO of Runloop.ai and a former Google engineer, dives into the future of AI agents and the importance of sandboxed environments. He reveals how sandboxes create safe spaces for agents to operate while preventing security risks. Wall discusses building efficient agent infrastructures, the advantages of isolated compute environments, and the significance of creating Git-like workflows for enterprises. He also explores how refining agent performance through failed runs can drive iterative advancements, revolutionizing how agents interact with data and each other.
AI Snips
Chapters
Transcript
Episode notes
Give Agents Their Own Computer
- Giving an agent its own isolated computer unlocks far more capabilities than exposing limited APIs.
- Isolation reduces blast radius while enabling tools like compilers, shells, and file systems for agentic workflows.
Build Sandbox Images With Blueprints
- Configure sandbox images to match the agent's workload using blueprints or dynamic mounts.
- Start with a dev box, iterate with dynamic mounts, then bake the working recipe into a blueprint.
Isolation Prevents Catastrophic Risks
- Running agents next to production servers is risky because they can execute arbitrary shell commands and consume unpredictable resources.
- Sandboxes limit resource usage and reduce the risk of catastrophic actions like rm -rf on shared servers.