Why AI sandboxes suck
Blog post from Freestyle
Sandbox environments, while useful for isolating untrusted or user-submitted code, often limit an agent's capabilities by providing a constrained computing experience, such as a JavaScript isolate or a limited container, making it difficult for agents to perform complex tasks. This limitation arises from the assumption that the agent's needs can be predicted, which is often not the case. In contrast, virtual machines (VMs) offer a more robust solution by providing a full operating system environment with features like memory snapshots, live forking, and integration with various runtimes, allowing agents to perform a wider range of tasks effectively. The use of VMs facilitates a real development environment, as seen in tools like RigKit, enabling agents to operate more like junior engineers with access to the necessary tools and feedback loops for software development. The future of agent infrastructure should focus on better isolation that allows agents to discover task requirements within a controlled boundary, rather than imposing overly restrictive environments that stifle their potential.
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