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By: Heena T Shaikh and Kazi Kutubuddin Sayyad Liyakat
1,2 Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur (MS), India.
The contemporary software development lifecycle (SDLC) is burdened by significant cognitive friction, characterized by high demands for syntax recall, boilerplate management, and painstaking manual debugging. This paper proposes and examines a novel programming model built upon deeply embedded AI, moving beyond simple code completion tools to establish a truly intent-based, declarative development environment. The proposed model leverages specialized Large Language Models (LLMs) and domain-specific generative agents (Cognitive Programming Assistants, or CPAs) capable of real-time translation of high-level human intent (expressed in natural language and architectural diagrams) into verifiable, executable code modules. Key features include semantic debugging, where the AI proactively identifies logical flaws based on declared requirements rather than just runtime errors, and automatic cross- platform adaptation. Initial findings of study suggest that this AI-centric model dramatically reduces the time spent on low-level implementation details, decreasing boilerplate code generation by up to 80% and allowing human developers to prioritize architectural integrity, system validation, and security auditing. This transition redefines the programmer’s role from a code translator to a system architect and verifier, paving the way for exponentially faster development cycles and the effective management of increasingly complex systems.
AI-driven programming, Intent-based coding, Generative agents, Cognitive load reduction, Future of SDLC, Semantic debugging, Declarative Programming.
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