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The state of AI writing on Hacker News · Updated 5 Nov 2026 · 17:08 UTC

18% of Hacker News’ front page is now AI-written.

We’ve checked 16,714 articles from the Hacker News front page over the last 203 days. Every linked story gets run through an AI detector and logged. The number keeps going up.

— The headline figure

18%

of front-page articles in Nov '26 were flagged as AI-generated by Pangram.

Apr '26: 6% Change ↑ +200%
16,714 articles scored 7,563 distinct domains 203 days of tracking Pangram v3.3 classifier

— Key findings

Three things we learned.

You can reproduce all of it from the open data. Pangram, the detector we use, reports 99.98% accuracy on its own benchmarks.

— 01 of 03
+200%
change in the AI-written share since tracking began

The first month we tracked sat at 6%. The latest reads 18%. This counts the front page only, not the web at large.

— 02 of 03
45%
of publishing platform is AI-generated

Publishing platform run the highest AI share of any source type, across 47 articles. Personal blogs and open-source docs sit far lower.

— 03 of 03
97%
of Show HN posts are human-written

Posts written straight to HN stay almost entirely human. The AI turns up in the articles people link to, not in HN itself.

— Month by month

The AI-written share, every month we’ve tracked.

Trajectory 6% → 18% (+12pp)
0%
5%
10%
15%
20%
6%
11%
13%
17%
19%
19%
16%
18%
Apr '26May '26Jun '26Jul '26Aug '26Sep '26Oct '26Nov '26

— By source type

Where the AI is coming from.

Publishing platform
45%
45% n = 47
Open source / docs
41%
41% n = 1,920
Personal blog
14%
14% n = 12,064
Community
9%
9% n = 346
Academic preprints
7% n = 550
Tech press
2% n = 595
Business / finance press
2% n = 195
Science press
1% n = 263
Mainstream press
0% n = 589
Reference
0% n = 113
Games press
0% n = 24
Website
0% n = 8
By HN submission type · AI fraction
Show HN
0%
Launch HN
23%
Ask HN
3%
Standard story
15%

— Methodology

How it works.

A script checks the Hacker News front page every 15 minutes. For each of the top 30 stories it opens the linked page and pulls out the article text. That text goes to Pangram, an AI-content detector. Pangram reports 99.98% accuracy on its own benchmarks.

Pangram rates each article in chunks of about 225 words. We average the chunks into one score, then drop it into a bucket:

HUMAN
< 30%
MIXED
30–70%
AI
> 70%
0%50%100% AI

— Caveats

What this doesn’t tell you.

  • No detector is perfect. Pangram is accurate, but it still gets things wrong. Most misses are false positives on text that’s been heavily edited or translated.
  • A high score means the text reads the way AI models write. It can’t tell you who actually wrote it.
  • The HN front page is whatever its users vote up. This measures that, not the web at large.
  • For each article we store the URL, the score, and Pangram’s chunk-by-chunk breakdown. The breakdown is what powers the segment view.