Descriptions:
Substack just shipped AI detection, and I sat down with co-founder and CEO Chris Best to talk about what a detector can and cannot see in your writing.
Full post:
https://natesnewsletter.substack.com/p/ai-detection-ideas-not-words?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
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What’s really happening inside AI detection on Substack?
The common story is that a detector tells you whether writing is real, but the real question is whether anyone meant what they published.
In this video, I share the inside scoop on AI slop, detection, and what still counts as thinking:
– Why over 40% of LinkedIn long-form posts scan as fully AI-generated
– How Substack’s new Pangram scan works, and what it misses
– What a denial of service attack on the public square looks like
– Where human attention still holds value as language gets cheap
Detection gives readers a real signal about how text was made, but it cannot tell you whether anyone thought about it, and that is still the part only a person can supply.
Chapters:
00:00 What AI slop is, and the Pangram numbers
02:43 The same problem inside companies
05:01 A denial of service attack on the public square
07:56 What Substack shipped
11:27 How I actually write with AI
17:41 Proof of work is dead
20:01 Why models pull toward the same ideas
22:35 A Pangram for ideas
26:09 The Odyssey and what lasts
34:46 Anti-slop is a pro-AI stance
41:41 Claude-fishing and the new norms
43:57 Human attention, the last scarce resource
Listen to this video as a podcast.
Spotify: https://open.spotify.com/show/0gkFdjd1wptEKJKLu9LbZ4
Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-news-strategy-daily-with-nate-b-jones/id1877109372
