Michal Zalewski — the security researcher behind “lcamtuf’s thing” — got tired of Hacker News feeling like an AI echo chamber, so he measured it. Twice: a full-month sample of the daily top-5 stories in February 2026, then an updated pass in June.
The numbers:
- In February, AI stories took four of the five top slots on multiple days; only three days had no LLM news in the top 5.
- By June, roughly 60% of the daily front page was AI-related or AI-generated early in the month, settling to ~50% by month’s end — up from 40% in February.
- To spot AI-written stories he ran Pangram, an LLM-text detector, then manually reviewed every flag. He found the results plausible — if anything, a few false negatives.
His defense of text detectors is the best part. AI writing doesn’t need to be “inhuman” to be detectable: today’s models have a quasi-deterministic default voice. Ask for the same essay twice and you get stylistically similar output. The individual mannerisms look human, but the exact combination is unlikely in real writing.
It’s a measured, numbers-backed take on how thoroughly AI now saturates the most important geek aggregator on the internet — stories and comments alike.