PS3 Emulator Devs Politely Ask That People Stop Flooding It with AI PRs

Original Article ↗ Hacker News Discussion ↗

AI-generated PRs and maintainer burden

  • Many commenters say AI-assisted pull requests often increase work for maintainers rather than reduce it.
  • Reviewing large, partially incorrect AI diffs is harder than writing the fix manually.
  • Maintainers describe AI PRs as “slop” when authors can’t explain or test the changes but still expect review and merge.
  • Some see this as a new “endless September” of people unfamiliar with open-source norms overwhelming projects.

LLM limitations in complex or niche codebases

  • Several people report LLMs failing badly on PS3 homebrew, console graphics, or classic Mac APIs due to sparse or subtle training data.
  • The tools sound confident and “blog-smart” but often produce subtly wrong or overcomplicated code.
  • A minority report good results when they first supply detailed docs and tooling (linters, parsers), treating the model as an assistant within a well-defined environment.

What good contributions should look like

  • Strong consensus: anyone submitting code should understand it, test it, and be willing to iterate. Motivation alone is not enough.
  • Suggestions for non-coders: help with documentation, issue triage, reproduction, design, or donate resources instead of code.
  • Forking for personal use is framed as perfectly fine, and often the right place for “works for me” AI modifications.

Gatekeeping, reputation, and process changes

  • Ideas floated: invite-only PRs, reputation systems, web-of-trust–style graphs, auto-closing issues/PRs by default with whitelisting for proven contributors.
  • Some propose repo-level CLAUDE.md/AGENTS.md to set explicit rules for AI use; others argue existing CONTRIBUTING/README already suffice.
  • A few advocate simply banning unsolicited or AI-generated PRs for small and medium projects.

Responsibility, ethics, and copyright

  • One camp emphasizes personal responsibility: if you submit it, you own it, regardless of tooling.
  • Others argue the tools themselves are at fault for confidently misleading non-experts.
  • There is concern that AI-generated code may be uncopyrightable or legally murky, making some maintainers unwilling to accept it.