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The state of AI writing on Hacker News · Updated 24 May 2026 · 21:13 UTC

10% of Hacker News’ front page is now AI-written.

We’ve checked 2,976 articles from the Hacker News front page over the last 38 days. Every linked story gets run through an AI detector and logged. The number keeps going up.

— The headline figure

10%

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

Apr '26: 6% Change ↑ +67%
2,976 articles scored 1,595 distinct domains 38 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
+67%
change in the AI-written share since tracking began

The first month we tracked sat at 6%. The latest reads 10%. This counts the front page only, not the web at large.

— 02 of 03
21%
of open source / docs is AI-generated

Open source / docs run the highest AI share of any source type, across 404 articles. Personal blogs and open-source docs sit far lower.

— 03 of 03
94%
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% → 10% (+4pp)
0%
5%
10%
6%
10%
Apr '26May '26

— By source type

Where the AI is coming from.

Publishing platform
33%
33% n = 3
Open source / docs
21%
21% n = 404
Community
10%
10% n = 62
Personal blog
8% n = 2,039
Business / finance press
3% n = 32
Academic preprints
2% n = 86
Tech press
1% n = 135
Mainstream press
1% n = 120
Reference
0% n = 20
Science press
0% n = 63
Games press
0% n = 4
Website
0% n = 8
By HN submission type · AI fraction
Show HN
0%
Ask HN
9%
Standard story
9%

— 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.