I have a complicated relationship with Hacker News. The site is the most important aggregator of geek news and a major source of traffic to this blog. At the same time, it has a fair number of toxic commenters, making it a dependable source of insults hurled in my general direction; if you want a taste, this article has been called “watered-down” and “slop”.
The site is run by geeks and for geeks, so it’s not immune to tech trends; for example, around 2018, it had a fair number of stories focused on cryptocurrencies and NFTs. That said, the recent shift feels more profound: almost every day, it feels that the lineup is dominated by stories focused on AI, written by AI, or commented on by AI.
That images shows a particularly bad day, so to give a more honest assessment, I also performed a more systematic survey in February 2026, and again in June of the same year.
Original February 2026 investigation
To get a sense of how much of the feed is occupied by AI-related topics, I took a sampling of the daily top #5 for all of February:
AI took four out of five spots on Feb 4 and Feb 12, plus arguably the entire line-up on Feb 5 (story #3 was submarine marketing for an AI vendor). The only days without LLM news in the top 5 were February 1 (with the first AI story at #7, then #9), February 9 (first at #8), and February 25 (with AI at #6, #9, #10).
For the second part of the experiment — figuring out which stories were likely AI-written — I tapped into Pangram. Pangram is a remarkably good, conservative model for detecting LLM-generated text. These detectors have bad rap among techies, but the objections are often based on outdated assumptions or outright misconceptions. For the tools to work, AI writing doesn’t need to be in any way “inhuman”. It’s enough that the default voice of the current crop of LLMs is quasi-deterministic: ask for the same essay twice and you’ll get a stylistically similar result. The individual mannerisms are human-like, but it’s very unlikely that your writing combines the exact same set. I write about it a bit more here.
To validate the results, I also reviewed all the flagged stories and I think the findings make sense; if anything, Pangram had a couple of false negatives. To give you a sense of what was flagged, have a look at the #3 story on February 19 (“AI is not a coworker, it’s an exoskeleton”). It had 500+ upvotes and 500+ comments. In my opinion, it has a wide range of red flags.
Updated data for June 2026
In June, to capture more detail, I used solid black for pure-play AI navel-gazing (vendor announcements, op-eds about the benefits or drawbacks of the technology, etc) and hatched shapes for stories that lean heavily into AI, but have broader ramifications (e.g., the Instagram AI support agent account hack). As before, stories that are only tangentially related to AI (e.g., reports of RAM price hikes) are not flagged.
In the first half of the month, roughly 60% of the daily HN lineup was AI-related or AI-generated, tapering off to ~50% as we approached the end of the month. This is up from 40% in February.
As for the comment side: https://www.marginalia.nu/weird-ai-crap/hn/
Hacker news is easy.
Take a story about a court case, for example.
Just preface every comment with "I have absolutely no experience as a judge or a lawyer, but I am still very smart and so have a strong untethered-from-reality opinion about this that others will surely want to know. Here it is:"
If the comment still makes sense with that preface, discard it, it's useless.
If it *doesn't* make sense with that preface , those are the valuable comments.