# Interpreting Pangram

DevFeed: [Interpreting Pangram](<https://devfeed.tech/articles/interpreting-pangram-30736.md>)

Original publisher: [Read original article](<https://lucumr.pocoo.org/2026/9/14/interpreting-pangram/>)

Author: Armin Ronacher

Published: 2026-09-14T00:00:00Z

Content type: opinion

Language: en

Sources: [Armin Ronacher](<https://devfeed.tech/sources/armin-ronacher.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [Training AI Models](<https://devfeed.tech/topics/training-ai-models.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [llm](<https://devfeed.tech/tags/llm.md>), [model](<https://devfeed.tech/tags/model.md>), [openai](<https://devfeed.tech/tags/openai.md>), [training](<https://devfeed.tech/tags/training.md>), [training-data](<https://devfeed.tech/tags/training-data.md>)

## AI overview

The article discusses Pangram, an AI-text detector that classifies passages as human-written, AI-generated, or mixed. It explains that Pangram manufactures training data from human-authored text and LLM-generated rewrites and edits, then describes an experiment using Opus 5 to generate text intended to read as entirely AI-generated.

## Source excerpt

Yesterday David Sacks wrote a tweet and within a few minutes people did, what they usually do, and they asked Pangram if it was AI. And Pangram said it's entirely AI generated. To which David replied that these AI detectors are bogus. Now Pangram has a pretty low false positive rate, but if you have ever used an LLM as a writing assitant, you will have probably noticed that it claims your posts 100% AI, even though you don't feel like they are. Pangram itself is a trained model, that attempts to detect segments of text as being definitely human, definitely AI and a mixture of the two. If you want to know how it works, they published a paper. The short summary is that they are manufacturing its own training data by starting from collections of known human authored text. An LLM is then tasked to understand the text and write a fresh new text on the same topic. They also let the LLM perform partial edits on that original human text and through that they can pick up on these co-authored details. Pangram claims their model to have rates of 0.0041% false AI accusations and 0.34% missed AI text. So now that we know this I figured it might be fun to have an LLM re-create David's tweet. I first came up with a prompt. And when I say I came up with that prompt I in fact used an LLM to propose to me from that tweet what I might want to say for the structure. I'm sure if you ask Pangram about if the above text is AI, it will probably say so, but that's not really the point. The point is that I then used Opus 5 to generate a text which reads entirely AI generated. If you are curious, this is the prompt I used: Original prompt to generate a David Sacks like tweet Please write an 8 paragraph tweet about "Pacing the Frontier", not longer than 350 words. Context of this tweet is this post by Dario: https://darioamodei.com/post/we-must-pace-the-frontier And this tweet by Sam Altman: "I agree with Dario that we need to pace the frontier. This has been a primary topic of discussions we'