# Pangram AI Detection Integrates Into Substack to Show Readers Which Posts Use AI

> Substack is adding AI detection from Pangram, and it puts the estimate right in front of readers rather than hiding it in a moderation dashboard. The tool scans posts and notes of a hundred words or more published after July 21, estimating how much of the text reads as human-written versus AI-assisted, and it works across the web and iOS. Writers can disable the label, scan drafts before publishing, or add a How I make this note explaining where AI fits in their process. Chief executive Chris Best has been blunt about the motivation: he wants to keep Substack from turning into LinkedIn, flooded with generic AI slop. Framing detection as a transparency signal for readers, instead of a punishment for writers, is a notably different bet from platforms that quietly downrank suspected AI content. Detection is imperfect, and false positives on heavily edited human writing are a real risk that could sting creators unfairly. But as AI writing becomes ubiquitous, a widely read platform choosing to surface provenance openly, and letting writers add context, is an experiment worth watching. Neither company says it trains models on publisher content.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: TechCrunch · Published Thursday, September 3, 2026_

## Wortins' read

Substack is adding AI detection from Pangram, and it puts the estimate right in front of readers rather than hiding it in a moderation dashboard. The tool scans posts and notes of a hundred words or more published after July 21, estimating how much of the text reads as human-written versus AI-assisted, and it works across the web and iOS. Writers can disable the label, scan drafts before publishing, or add a How I make this note explaining where AI fits in their process. Chief executive Chris Best has been blunt about the motivation: he wants to keep Substack from turning into LinkedIn, flooded with generic AI slop. Framing detection as a transparency signal for readers, instead of a punishment for writers, is a notably different bet from platforms that quietly downrank suspected AI content. Detection is imperfect, and false positives on heavily edited human writing are a real risk that could sting creators unfairly. But as AI writing becomes ubiquitous, a widely read platform choosing to surface provenance openly, and letting writers add context, is an experiment worth watching. Neither company says it trains models on publisher content.

## Source

[Read the full story at TechCrunch](https://techcrunch.com/2026/07/22/substacks-new-tool-tells-you-whos-been-writing-their-newsletters-with-ai/)

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