# Prompt Driven Development with Claude Code: Building a Complete TUI Framework for the Ring Programming Language

arXiv: https://arxiv.org/abs/2601.17584 · HTML: https://mlsanity.com/paper/2601.17584/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 28 references that are in the map.
- First posted on arXiv 24 Jan 2026.

## Builds on (most cited first, 11 of 11)

- [Large Language Models for Software Engineering: A Systematic Literature Review](https://mlsanity.com/paper/2308.10620/) (2023)
- [Software Testing with Large Language Models: Survey, Landscape, and Vision](https://mlsanity.com/paper/2307.07221/) (2023)
- [A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages](https://mlsanity.com/paper/2410.03981/) (2024)
- [Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI](https://mlsanity.com/paper/2505.19443/) (2025)
- [Automatic Programming: Large Language Models and Beyond](https://mlsanity.com/paper/2405.02213/) (2024)
- [Adaptable Logical Control for Large Language Models](https://mlsanity.com/paper/2406.13892/) (2024)
- [Is Programming by Example solved by LLMs?](https://mlsanity.com/paper/2406.08316/) (2024)
- [A Survey of Vibe Coding with Large Language Models](https://mlsanity.com/paper/2510.12399/) (2025)
- [EVOR: Evolving Retrieval for Code Generation](https://mlsanity.com/paper/2402.12317/) (2024)
- [General-Purpose Visual Language and Information System with Case-Studies in Developing Business Applications](https://mlsanity.com/paper/1712.10281/) (2017)
- [The Shift from Writing to Pruning Software: A Bonsai-Inspired IDE for Reshaping AI Generated Code](https://mlsanity.com/paper/2503.02833/) (2025)

## Abstract (arXiv)

Large language models 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 framework for the Ring programming language, completed in roughly ten hours of active work spread across three days using a purely prompt driven workflow with Claude Code, Opus 4.5. 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, followed by complex UI systems and controls expansion. 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 short, reflecting a highly iterative workflow in which the human role was limited to specifying requirements, validating behaviour, and issuing corrective prompts without writing any code manually. The resulting framework includes a complete 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 behaviour, this study provides empirical evidence that modern LLMs can sustain architectural coherence and support the construction of production grade tooling for emerging programming languages, highlighting prompt driven development as a viable methodology within software engineering practice.