The use of Generative AI has started changing how software is developed today. Many tools are now available that help developers write code faster or fix errors, but most of them only support specific tasks. They do not handle the complete software development process from In this paper, we propose a system called JellyfishAI ,which aims to automate the full software development lifecycle. The idea is simple — a user can describe their requirements in normal language, and the system will generate a complete, ready-to-use application. It combines different technologies like natural language processing, code generation models, testing, and deployment into one system. Technology is advancing very fast, and modern applications need to be scalable, reliable, and developed quickly. Because of this, traditional development methods are under a lot of pressure. Usually, software development includes many steps like requirement analysis, design, coding, testing, and deployment. These steps often require manual work and skilled developers, which makes the process slow and costly. It can also lead to mistakes and inconsistent results. With the introduction of Generative AI, things have started to improve. These systems can understand user input and generate code, documentation, and even design ideas. They help developers save time by assisting in coding and debugging tasks. However, these tools still have limitations. Most of them only focus on one part of development, like code suggestions or bug fixing, and do not provide a complete solution. Another issue is that developers still need to use multiple tools separately and connect them manually. This makes the workflow complicated and less efficient. Also, the code generated by AI tools often needs to be checked by humans to ensure it is correct, secure, and follows proper standards. Even though CI/CD pipelines help automate deployment, they mostly follow fixed rules and do not have intelligent decision-making capabilities. Similarly, testing tools can find errors but cannot automatically improve the quality of the code. Because of this, there is a need for a system that can intelligently manage all stages of development together. Today's software systems are also becoming more complex, and there is a growing need to build applications quickly. Startups and companies want to turn their ideas into working products as fast as possible. However, depending on skilled developers and manual work often slows things down. This becomes even more difficult when dealing with large systems that require proper coordination and integration. To solve these problems, we introduce JellyfishAI, which is designed to automate the entire development process. Unlike existing tools, this system brings everything together in one place. It can understand user requirements, generate code, test it, check for errors, and deploy the application automatically. The system is built using multiple layers that include language processing, AI-based code generation, validation, and deployment. This ensures that the generated code is not only functional but also tested and ready to use. The system also improves over time using feedback and learning mechanisms. JellyfishAI also focuses on important factors like security, scalability, and maintainability. It includes features to detect vulnerabilities, manage dependencies, and improve performance, so that the final application meets industry standards. This system can change how software development is done. By automating repetitive tasks, developers can focus more on designing and solving problems instead of doing routine work. It also makes it possible for people without strong technical skills to build applications. In conclusion, AI has the potential to improve software development by making it faster, cheaper, and more efficient. However, to achieve full automation, we need systems that combine all stages of development in one place. JellyfishAI is an attempt to do that by providing a complete, end-to-end solution for building software automatically.
Kadam et al. (Thu,) studied this question.