The Zig project's rationale for their firm anti-AI contribution policy

The Zig project's rationale for their firm anti-AI contribution policy

Zig has one of the most stringent anti-LLM policies of any major open source project: No LLMs for issues. No LLMs for pull requests. No LLMs for comments on the …

"Useful" is not sufficient

So Linus Torvalds, head of the Linux kernel development, put his foot down on the Linux Kernel development mailing list when someone was bringing up criticism of LLMs: “Linux is not one of those anti-AI projects, and if somebody has issueswith that, they can do the open-source thing and fork it. Or just walk away. […]

open-slopware

Free/Open Source Software choosing to use and/or support LLM usage/AI, as well as alternatives and tips to requesting better policies or forking.

Lisp Against the (LL)Machine

Every Lisp, Scheme, and Lisp-adjacent project listed is a non-toy implementation that is at least somewhat active. When I first wrote this article (2026-03-12), most Lisps did not have a policy or even public stance on LLM contributions. In such cases I posted to their bug trackers or discussion lists to ask. Most maintainers kindly responded.

Front page · Saturday, June 6, 2026

On ThinkStack: Linux kernel adopts no-embargo policy as LLMs flood maintainers with CVEs · Evan You ships Vite Plus to unify Rollup, Oxlint, Oxformat, and Vitest into one Rust/Go toolchain · 88% of firms use AI coding tools but only 5.5% see business impact, PlatformCon study fin

LLMs Are Accelerating the Open Source Sustainability Crisis

Adam Wathan, the creator of Tailwind CSS, has been speaking about how LLMs have made his project more popular than ever…while also making it fall apart financially, causing him to fire 75% of his engineers. “I think AI is a huge reason why our business is struggling, even though it’s making Tailwind more popular than ever.” — Adam Wathan (12:03) How is this possible? A major cause is that LLMs are blocking Tailwind’s creators and users from forming a relationship with each other.

Histomat of F/OSS: We should reclaim LLMs, not reject them

A few days ago, I came across a blog post titled On FLOSS and training LLMs that articulates a growing frustration within the free and open source software…

I’m Tired of Talking About AI

I don’t want to talk about LLMs anymore.

If You’re Going To Defend AI And Whine About Its Critics, You Should Probably Be Honest About Its Actual Harms

I think this recent post by AI industry CEO Matt Shumer is worth a read. In it, he basically explains how quickly LLMs (large language models) are evolving to supplant many developers and prog…

The LLM Critics Are Right. I Use LLMs Anyway.

I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.

The LLM Critics Are Right. I Use LLMs Anyway.

I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.

The Arguments Against Open Source AI are Very Bad | Tom Bedor's Blog

The release of Kimi K3 has opened a fresh round of angst and confused discourse. There's a loud cohort of journalists, business leaders, and politicians arguing that open source AI is a dangerous threat. OpenAI's Dean Ball:

We Got Claude to Fine-Tune an Open Source LLM

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Why your local LLM feels dumber than it is

Quick Introduction We have all been on forums, chats, reddit, discord, youtube, or somewhere and heard “Oh! Model XYZ is AMAZEBALLZ!zomgwtfbbq” then downloaded it (or more likely, some quantized form of it) and said “eww… This sucks!” This post is going to be a rather technical series of experiments to demonstrate the impact of implementation-specific hazards with inference. I will be using the term “reference implementation” to describe the lab that published and offers first-party hosting of ...

Dan Shipper 📧 on Twitter / X

this is true and is a big reason why you don’t need to be a highly technical researcher to use LLMs in surprising and novel ways https://t.co/TuxNzXzToU— Dan Shipper 📧 (@danshipper) July 27, 2025