A Eulogy for Vim

Original Article ↗ Hacker News Discussion ↗

Forking Vim Over AI Use

  • Several commenters clarify that the fork targets:
    • Alleged use of LLMs to generate core Vim patches, leading to more frequent breakage.
    • Marketing language around Vim9 as “AI ready.”
  • Some see forking 8.2 as reasonable for those wanting a “pre-AI” baseline or who dislike Vim9 script.
  • Others view it as an overreaction to a single contributor’s behavior or to minor AI-adjacent messaging.

LLMs, “Vibe Coding,” and Accessibility

  • One side argues “vibe coding” lowers the barrier to programming:
    • Helps burned-out or time-constrained professionals do side projects.
    • Lets non-programmer domain experts build tools without years of study.
    • Compared to historical shifts: assembly → compilers, low-level → high-level languages, DAWs in music.
  • Skeptics counter:
    • Programming has long been “accessible” to anyone motivated to learn.
    • LLM-heavy workflows may produce users who don’t truly learn to program.
    • Accessibility is limited by subscription cost and hardware centralization.

Quality and Reliability of AI-Generated Code

  • Mixed reports:
    • Some users say LLMs make them dramatically more productive, with projects they’d never complete otherwise.
    • Others report AI-generated changes causing regressions in long-stable tools (e.g., accounting software), raising worries about subtle correctness issues.
  • Many expect AI contributions to be ubiquitous in open source, making “untainted” software unrealistic.

Ethical, Environmental, and Labor Concerns

  • Supporters of the fork emphasize:
    • Rising energy use, hardware demand, and environmental impact of large models.
    • Links to exploitative mining conditions.
    • Fear of job displacement, especially in well-paid tech roles, and increased corporate gatekeeping.
  • Critics respond:
    • These costs are not unique to AI; similar critiques apply to most industrial or IT buildouts.
    • Whether the tradeoff is “worth it” depends on perceived benefits, which some see as substantial.

Community Tone, Gatekeeping, and Culture

  • Some object to framing AI as “obviously awful” and to moralizing that implies dissenters are pretending not to understand harms.
  • Others defend drawing hard moral lines regardless of utility.
  • There is frustration both with “AI evangelists” and with “holier-than-thou” anti-AI stances, plus concern over new users changing established communities.