  Large language models are redefining software engineering by implementing
AI-powered techniques throughout the whole software development process,
including requirement gathering, software architecture, code generation,
testing, and deployment. However, it is still difficult to develop a cohesive
platform that consistently produces the best outcomes across all stages. The
objective of this study is to develop a unified platform that utilizes multiple
artificial intelligence agents to automate the process of transforming user
requirements into well-organized deliverables. These deliverables include user
stories, prioritization, and UML sequence diagrams, along with the modular
approach to APIs, unit tests, and end-to-end tests. Additionally, the platform
will organize tasks, perform security and compliance, and suggest design
patterns and improvements for non-functional requirements. We allow users to
control and manage each phase according to their preferences. In addition, the
platform provides security and compliance checks following European standards
and proposes design optimizations. We use multiple models, such as GPT-3.5,
GPT-4, and Llama3 to enable to generation of modular code as per user choice.
The research also highlights the limitations and future research discussions to
overall improve the software development life cycle. The source code for our
uniform platform is hosted on GitHub, enabling additional experimentation and
supporting both research and practical uses. \end
