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Rars: a Rust RAR implementation, mostly written by LLMs

bitplane.net

May 13, 2026

9 min read

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49/100

Summary

A RAR compressor for every version of RAR was developed using OpenAI Codex 5.5 and Claude Opus 4.7 in approximately five weeks, costing around £40 in tokens. The resulting code consists of 55,000 lines and is not optimized for speed.

Key Takeaways

A RAR compressor was developed in 5 weeks using OpenAI Codex 5.5 and Claude Opus 4.7, costing approximately £40 in tokens.
The project involved extensive reverse engineering, utilizing various free decompressor sources and tools like Ghidra and DOSBox-x to document the RAR file format.
The author faced challenges with AI models generating incorrect code and had to implement manual interventions to maintain code quality and prevent issues.
The development process highlighted the importance of monitoring AI outputs to avoid propagation of errors and the need for frequent refactoring.

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Community Sentiment

Mixed

Positives

The project represents an ambitious use of AI in software development, showcasing the potential for LLMs to assist in creating functional tools.
The open-source nature of the implementation allows for community-driven improvements and transparency in the development process.

Concerns

Concerns about copyright and the legality of using machine-generated code highlight significant ethical implications in AI-generated software.
The implementation is criticized for being slow and of lower quality compared to established tools like WinRAR, raising doubts about its practical utility.
There is skepticism about the accuracy and correctness of the generated code, which could undermine trust in AI-assisted development.