International Journal of Science, Engineering and TechnologyAuthors: Archana Banait, Yash Khalkar, Soham Gaikwad, Kanhaiya Sharma, Vivek Sanandiya
Abstract: AutoDevOS is an AI-driven autonomous software development orchestrator designed to revolutionize the way soft- ware projects are built and managed. It allows users to provide high-level natural language prompts, which are decomposed by a central meta-agent into specialized sub-tasks. These tasks are then handled by distinct intelligent agents (frontend, backend, DevOps, testing, and documentation). These agents collaborate seamlessly to generate, integrate, and deploy production-ready applications with minimal human intervention. The system leverages large language models (LLMs) alongside the Model Context Protocol (MCP) for dynamic context management and tool execution. Key observations from our prototype demonstrate a 40% reduction in boilerplate generation time and an 85% task completion rate for standard multi-file operations. By combining modular task handling, automated loop detection, and DevOps integration, AutoDevOS significantly improves code quality and prevents context degradation—paving the way for the future of intelligent, autonomous software engineering
