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The state of AI writing on Hacker News · Updated 23 Aug 2026 · 03:03 UTC

19% of Hacker News’ front page is now AI-written.

We’ve checked 10,610 articles from the Hacker News front page over the last 128 days. Every linked story gets run through an AI detector and logged. The number keeps going up.

— The headline figure

19%

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

Apr '26: 6% Change ↑ +217%
10,610 articles scored 5,092 distinct domains 128 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
+217%
change in the AI-written share since tracking began

The first month we tracked sat at 6%. The latest reads 19%. This counts the front page only, not the web at large.

— 02 of 03
34%
of open source / docs is AI-generated

Open source / docs run the highest AI share of any source type, across 1,285 articles. Personal blogs and open-source docs sit far lower.

— 03 of 03
96%
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% → 19% (+13pp)
0%
5%
10%
15%
20%
6%
11%
13%
17%
19%
Apr '26May '26Jun '26Jul '26Aug '26

— By source type

Where the AI is coming from.

Open source / docs
34%
34% n = 1,285
Publishing platform
33%
33% n = 24
Personal blog
13%
13% n = 7,510
Community
10%
10% n = 261
Academic preprints
7% n = 361
Tech press
1% n = 367
Mainstream press
1% n = 384
Business / finance press
1% n = 138
Reference
0% n = 73
Science press
0% n = 183
Games press
0% n = 16
Website
0% n = 8
By HN submission type · AI fraction
Show HN
0%
Launch HN
17%
Ask HN
5%
Standard story
14%

— 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.