title: "Why agents need sandboxes, not larger context windows"

Relying on ever-larger context windows for AI agents introduces significant challenges, including high costs, increased latency, and the "lost in the middle" problem where models struggle to recall information. A more scalable solution is the use of sandboxes, which are secure, isolated environments where agents can operate. These sandboxes provide agents with tools like code interpreters, file systems, and web browsers to execute complex, multi-step tasks. This approach allows agents to process and analyze vast amounts of data that would be impossible to fit into a context window, overcoming the inherent limitations of context-based reasoning for complex workflows.