Prompt-Driven Autonomous Enterprise Software Systems: Architecture, Design, and Feasibility Analysis

Prompt-Driven Autonomous Enterprise Software Systems: Architecture, Design, and Feasibility Analysis presents a novel paradigm for building next-generation enterprise applications using artificial intelligence. This research introduces a comprehensive framework where natural language prompts serve as the primary interface for designing, developing, deploying, and evolving software systems. The paper proposes a Prompt-Driven Autonomous Enterprise Software System (PDAESS) architecture that integrates large language models, multi-agent orchestration, automated testing pipelines, and cloud-native deployment strategies. The system enables transformation from high-level business requirements into fully functional software systems, including user interface design, backend services, database schema generation, testing, and deployment, all driven by AI. A key contribution of this work is the introduction of a self-evolution engine, allowing systems to continuously adapt through prompt-based updates. This enables dynamic scaling, automated refactoring, and real-time system optimization without extensive human intervention. The study provides: A detailed layered architecture model for AI-driven software systems A complete end-to-end workflow from prompt to production deployment A structured feasibility analysis distinguishing current capabilities from future possibilities Identification of critical technical, security, and governance challenges Real-world enterprise use cases across industries such as SaaS, banking, healthcare, and e-commerce While acknowledging that fully autonomous enterprise systems are not yet entirely achievable, this paper demonstrates that many foundational components are already feasible with existing technologies. The proposed framework serves as a research roadmap toward AI-native software engineering, where development shifts from manual coding to intelligent system generation. This work is particularly relevant for researchers, software architects, and industry practitioners exploring the intersection of artificial intelligence, DevOps automation, and enterprise system design. Artificial Intelligence Autonomous Software Systems, Generative AI DevOps Automation Software Architecture Cloud Computing Self-Healing Systems