Thread

1. boutell · 1790944763 · focus · HN ↗

   I head a much, much smaller open source project. Since the November Singularity we've been seeing at least six responsibly reported security advisories a month. However, this last month we had 22 unique security advisories. Our project has been built with adherence to the OWASP Top Ten Guidelines and other best practices from the beginning. But software is hard and AI is thorough.

   Each month, we fix them all in our monthly maintenance release and disclose at that time. We fight AI fire with fire, and hand-review, of course.

   So far, we can keep up. One hopes this is possible at the scale of the Linux project, which assuredly has more humans and more AI to throw at the problem. But team size does not scale linearly with interested audience, and potential bugs do scale with codebase size (and other extremely important factors, like code quality, at which the Linux team is assuredly much better than we are).

   ("November Singularity" is a cheeky reference to the arrival of Opus 4.5 and "good enough" coding models and harnesses generally.)

   1. sparklingmango · 1790945577 · focus · HN ↗

      I too use November 2025 as a true turning point.

      1. soulofmischief · 1790955388 · focus · HN ↗

         It was. That's when I stopped coding most things by hand. The difference in what I could reliably get AI to do for me in February 2025 vs February 2026 is just massive. I immediately became a huge advocate amongst my peers for going all-in on automated engineering because this curve is about to get very steep and if you're not staying ahead, you might get left behind.

         1. gamerdonkey · 1790956672 · focus · HN ↗

            I'm genuinely curious: if the trend is toward "AI accomplishes my goals more easily than in the past", what curve are you "staying ahead" of?

            Why isn't even easier for an AI noob to jump in at the next step with less friction than the current one?

            1. becquerel · 1790957520 · focus · HN ↗

               AI is becoming a more and more powerful lever that lets you move greater loads per application; it is in a real sense giving you more leverage. But the lever is difficult to use effectively, and the methods for using the level change every week or so.

               1. sysguest · 1790958287 · focus · HN ↗

                  > methods for using the level change every week or so

                  hmm doesn't mean noob will become better? if what I'm "learning" about AI is going to get deprecated every week... then it doesn't make sense to "keep up"

                  1. andybak · 1790960019 · focus · HN ↗

                     Here's how I think about it. There's two different things "knowing how to use AI effectively" and "knowing how to leverage effective AI to improve your project".

                     1. Both are multipliers on skills you already have. A "noob" will be at a disadvantage.

                     2. The second one is a complex blend of technical skill, domain knowledge and human factors (knowing your user-base, knowing your product/project, understanding UX/DX/whatever) that you probably will always have an edge on.

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