Prompt-Driven Development with Claude Code: Developing a TUI Framework for the Ring Programming Language

Large language models (LLMs) are increasingly used in software development, yet their ability to generate and maintain large, multi-module systems through natural language interaction remains insufficiently characterized. This study presents an empirical analysis of developing a 7420-line Terminal User Interface (TUI) framework for the Ring programming language using a prompt-driven workflow with Claude Code (Opus 4.5), employing an iterative testing and corrective feedback. The system was produced through 107 prompts: 21 feature requests, 72 bug fix prompts, 9 prompts sharing information from Ring documentation, 4 prompts providing architectural guidance, and 1 prompt dedicated to generating documentation. Development progressed across five phases, with the Window Manager phase requiring the most interaction (35 prompts), followed by complex UI systems (25 prompts) and control expansion (20 prompts). Bug-related prompts covered redraw issues, event-handling faults, runtime errors, and layout inconsistencies, while feature requests focused primarily on new widgets, window-manager capabilities, and advanced UI components. Most prompts were brief (mean ≈ 258 characters; median = 207 characters), reflecting a highly iterative workflow in which the human role was limited to specifying requirements, validating behavior, and issuing corrective prompts—without writing any code manually. The resulting framework contains 28 classes, 334 methods and includes a windowing subsystem, event-driven architecture, interactive widgets, hierarchical menus, grid and tree components, tab controls, and a multi-window desktop environment. By combining quantitative prompt analysis with qualitative assessment of model behavior, this study provides empirical evidence that modern LLMs can preserve architectural coherence across iterations and support the construction of new libraries and tools for emerging programming languages, highlighting prompt-driven development as a viable methodology within software-engineering practice.