Themata.AI
Themata.AI

Popular tags:

#developer-tools#ai-agents#discussion#trending#llms#ai-ethics#claude#code-generation#ai-safety#openai

AI is changing the world. Don't stay behind. Clear summaries, community insight, delivered without the noise. Subscribe to never miss a beat.

© 2026 Themata.AI • All Rights Reserved

Archive

|

Topics

|

Privacy

|

Cookies

|

Contact
← All stories

Story

Rars: a Rust RAR implementation, mostly written by LLMs

1 report

1 website

1 discussion

Latest report

Overview

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.

Summary from bitplane.net.

Reports

One report so far. Additional coverage will appear here when it is linked to this story.

  1. bitplane.net

    Rars: a Rust RAR implementation, mostly written by LLMs

    Read report →

Community reactions

Each reaction summarizes sampled comments from the linked discussion.

Hacker News · bitplane.net

Rars: a Rust RAR implementation, mostly written by LLMs ↗
Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Read this discussion’s reaction

Based on 5 sampled comments from this thread. Analyzed 2026-05-14.

  • Praise: The project represents an ambitious use of AI in software development, showcasing the potential for LLMs to assist in creating functional tools.
  • Praise: The open-source nature of the implementation allows for community-driven improvements and transparency in the development process.
  • Concern: Concerns about copyright and the legality of using machine-generated code highlight significant ethical implications in AI-generated software.
  • Concern: The implementation is criticized for being slow and of lower quality compared to established tools like WinRAR, raising doubts about its practical utility.
  • Concern: There is skepticism about the accuracy and correctness of the generated code, which could undermine trust in AI-assisted development.