Open source projects are closing their gates as a result of AI. A flood of low-quality code
Open source projects such as curl, ghostty and tldraw are fed up with ubiquitous code-generating AI tools. Curl shuts down bounty programmes for vulnerability reports, ghostty bans outsiders from using AI, and tldraw goes one step further - blocking all PRs (change proposals) from external users. What was not long ago portrayed as a revolution to increase developer productivity has today become a source of frustration, extra work and a deterioration in the quality of collaboration for many repository maintainers.
The common denominator of the problem is so-called 'vibe coding' - automatically generated patches, features and submissions that often look plausible, but in practice contain incorrect assumptions, non-existent vulnerabilities, or cosmetic changes with no real value. Instead of speeding up development, artificial intelligence is increasingly slowing down project maintainers, forcing them to manually filter through hundreds of pointless proposals. As a result, some developers are coming to the conclusion that the only effective strategy is to set hard boundaries.
This is well illustrated by Mitchell Hashimoto's statement on X (formerly Twitter), who speaks directly about the drastic decline in the quality of PRs.
Hacker News (https://news.ycombinator.com/item?id=46641042) users are also sceptical about AI tools. Some point out that LLMs-based systems are not bad in themselves, rather the problem is the way they are used - especially the mass sending of low-quality pull requests without understanding the code and context of the project. AI is not a substitute for knowledge and does not make anyone a good programmer; on the contrary, AI creates a flood of 'weak programmers', working against the open source scene.
Examples of submissions:
https://github.com/ghostty-org/ghostty/pull/10316
https://github.com/ghostty-org/ghostty/pull/10270
https://github.com/ghostty-org/ghostty/pull/10205
Sources:
curl:
https://arstechnica.com/security/2026/01/over...-bug-bounties-to-ensure-intact-mental-health/
tldraw:
https://github.com/tldraw/tldraw/issues/7695
https://news.ycombinator.com/item?id=46641042
https://tldraw.dev/blog/stay-away-from-my-trash
ghosts:
https://github.com/ghostty-org/ghostty/pull/10412
Have you encountered the "ai slop" problem in a programming context? I've already encountered it and it's in my project - a nonsense PR meant to add rotary encoder support was created contrary to the basic logic and organisation of my project....
The common denominator of the problem is so-called 'vibe coding' - automatically generated patches, features and submissions that often look plausible, but in practice contain incorrect assumptions, non-existent vulnerabilities, or cosmetic changes with no real value. Instead of speeding up development, artificial intelligence is increasingly slowing down project maintainers, forcing them to manually filter through hundreds of pointless proposals. As a result, some developers are coming to the conclusion that the only effective strategy is to set hard boundaries.
This is well illustrated by Mitchell Hashimoto's statement on X (formerly Twitter), who speaks directly about the drastic decline in the quality of PRs.
Hacker News (https://news.ycombinator.com/item?id=46641042) users are also sceptical about AI tools. Some point out that LLMs-based systems are not bad in themselves, rather the problem is the way they are used - especially the mass sending of low-quality pull requests without understanding the code and context of the project. AI is not a substitute for knowledge and does not make anyone a good programmer; on the contrary, AI creates a flood of 'weak programmers', working against the open source scene.
Examples of submissions:
https://github.com/ghostty-org/ghostty/pull/10316
https://github.com/ghostty-org/ghostty/pull/10270
https://github.com/ghostty-org/ghostty/pull/10205
Sources:
curl:
https://arstechnica.com/security/2026/01/over...-bug-bounties-to-ensure-intact-mental-health/
tldraw:
https://github.com/tldraw/tldraw/issues/7695
https://news.ycombinator.com/item?id=46641042
https://tldraw.dev/blog/stay-away-from-my-trash
ghosts:
https://github.com/ghostty-org/ghostty/pull/10412
Have you encountered the "ai slop" problem in a programming context? I've already encountered it and it's in my project - a nonsense PR meant to add rotary encoder support was created contrary to the basic logic and organisation of my project....
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