NaSh: Guardrails for an LLM-Powered Natural Language Shell

Bimal Raj Gyawali, Saikrishna Achalla, Konstantinos Kallas, Sam Kumar

2025-06-16

Abstract

We explore how a shell that uses an LLM to accept natural language input might be designed differently from the shells of today. As LLMs may produce unintended or unexplainable outputs, we argue that a natural language shell should provide guardrails that empower users to recover from such errors. We concretize some ideas for doing so by designing a new shell called NaSh, identify remaining open problems in this space, and discuss research directions to address them.