International Journal of Science, Engineering and TechnologyAuthors: Prof. Nikhil Agrawal, Anushka Patil, Nikhil Kurkure, Dheesh Medekar, Renesh Sharma, Kuntal Thakur
Abstract: – For decades, the command-line interface has been fundamental to system administration, software development, and automation, supporting both professionals and advanced users.Its usability however has been restricted and intimidating to say the very least as a user is required to memorize the commands and syntax. With recent breakthroughs in NLP and LLM based architectures in quite literally everything the traditional CLIs are being integrated with them these as well. This survey brings together the latest research and practical system developments in natural language powered command line assistants and automated shell systems. We start by looking at how CLIs have evolved historically and examining early automation technologies, tracing the journey from manually crafted scripts to neural network approaches that harness the capabilities of modern transformer models. The paper presents a systematic way to classify intelligent shell systems based on their underlying model architecture, how they decide whether to execute commands, their safety measures, and their strategies for handling errors. We evaluate several representative systems including ShellGPT, Warp AI, Copilot CLI, and our own hybrid assistant that combines both local and cloud-based language models using detailed comparison matrices and real world use case analysis. We dive deep into the major challenges these systems face: hallucinations where the AI generates incorrect commands, ambiguous error messages that are hard to interpret, limited training data, and serious security concerns. Finally, we explore where future research should head, imagining the next wave of autonomous system administration agents, secure on-device AI inference, and voice controlled CLI automation. This survey contributes a unified classification system, an extensive literature review, empirically grounded comparisons between systems, and practical recommendations for researchers and developers who want to build robust, intelligent command line automation tools, to say the very least the final target is to help create something at the kernel level which will be an assisted mechanism for the entire os and all applications within it.
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