GrapheneOS defends use of AI for coding

GrapheneOS is currently defending its use of AI coding tools on Mastodon against complaints by various accounts claiming to be users.

We do not understand where you’re coming from or why you’re so incredibly angry with us. It’s not justified and does not make sense.

grapheneos.social/@GrapheneOS/117243573090596184

I haven’t dug into the code, but blanket hate for AI in code is extremely frustrating. There’s a difference between vibe coding and the hundred other ways to “use AI” on a project.

It’s funny because anyone seeing this as black and white clearly hasn’t ever opened an IDE.

Ssshh…Most of those having a knee-jerk “AI BAD! YOU BAD!” reaction don’t have any clue WTF an IDE is, how code completion works, nor the fact that by most metrics 95%+ of code now has “AI” in the chain…and has had that for YEARS.

github.blog/…/survey-ai-wave-grows/

survey.stackoverflow.co/2025/ai

OMGWTFBBQ!

Here’s a crazy idea…how about instead of “AI BAD! ME HATE AI” how about some nuance? Assume ALL software in 2026 has had AI assistance, and review it on its merits.

As for the devs at GrapheneOS directly…why were you (the general you) trusting them before? Humans can be plenty dicey in ways that affect code all on their own.

reddit.com/…/why_i_deleted_grapheneos_louis_rossm…

factually.co/…/louis-grossman-grapheneos-drama-c1…

Supposedly wonderful “human artisanal code” has plenty of fuckery.

en.wikipedia.org/wiki/XZ_Utils_backdoor

thehackernews.com/…/urgent-secret-backdoor-found-…

simonwillison.net/…/supply-chain-attack-on-axios/

hivepro.com/…/axios-npm-supply-chain-attack-what-…

Supposedly wonderful “human artisanal code” has plenty of fuckery.

These are supply chain attacks and in the case of xz utils, the attacker had gone to extreme lenghts to hide the attack from a well-meaning, good-hearthed but overworked and burnt out solo maintainer.

To compare this to bugs that people unwittingly introduce in normal human-written code is not sincere.

Deleted

Okay, but they still happen with orders of magnitude less frequency than bugs in AI code. Consider that the time between when rsync first adopted LLM-generated code and users en masse reporting rsync internal protocol errors during a backup was on the order of months.