Artificial intelligence (AI) has become the most defining technology of our era, increasingly integrated into diverse professional domains. Yet, the fast pace of technological evolution has rendered many recently developed applications outdated, raising challenges in maintenance and modernization. With over 49% of global internet traffic generated by bots or APIs (G4Media, 2024), adapting existing systems to AI-driven solutions is no longer optional but essential.

This paper explores the automatic transformation of legacy applications into APIs, proposing a system where uploading a file enables conversion within seconds. The study combines theoretical and practical perspectives. The literature review defines AI, outlines its applications, and highlights the role of ChatGPT Plus in education and programming. It further examines API concepts, application refactoring, and the use of Large Language Models (LLMs) in API generation and testing.

The practical component demonstrates how ChatGPT converted a calculator and a Tetris game, both originally coded by the author, into functional APIs on the first attempt. Enhancements included automated testing for the calculator and multi-modal controls for Tetris (buttons, gesture recognition, and voice commands). Additionally, the system successfully generated API descriptions from uploaded .html files.

The conclusion reflects on implementation challenges and achievements, while proposing directions for further development. This work emphasizes the potential of AI to streamline software modernization and API-based integration, bridging theoretical insights with practical innovation.

Keywords: API, Automatic application enhancement, user experience, LLM, AI programming.