Can't have been much, as the Chrome project is 20+ years old and LLMs have only recently become a thing; they did not slacken their code review and testing practices with the advent of LLM code generators. And I doubt they do much development on the affected areas at the moment, they mention a 13 year old issue for example.

But it's an open source project, you can go and figure out whether your assertion is correct.

If people are handing off the coding to AI more and more then they'll be less skilled at spotting potential bugs in the first place. AI, course of, could be run to find potential bugs in the AI-coded features before commit. But then you're getting further and further towards a world where code, and code that runs infrastructure, is incomprehensible. We'll have to start sacrificing the first-born to the silicon in the hopes of a good build for code that controls your electrical sub-station.

Look at the git stats for the project. Lines of code submitted haven't changed dramatically. Not everyone is just merging slop into the codebase. There are many ways to use AI, and most established players are not merging vibe coded nonsense.

That is a stat you invented out of thin air, based upon nothing but pejorative hope, against all logic or rational consideration of the timeline or the scale of the project, and you declare it the "elephant in the room"?

HN is so weird on the topic of AI, and so many desperately are trying to contrive a reality. Odd stuff.

If you assume that AI can produce code with less bugs, your 100 times increase in fresh bugs means you also increased your speed for new functionality by more than 100 times.

If models can spot 13 years old critical bugs, I think they can also produce fresh code without those bugs. The skillset is the same.