Just a few high level points about how this works. It works in multiple stages:

  1. I apply a domain and keyword filter to the feed
  2. The content of the remaining articles are run twice daily through a Modern Bert-based classifier fine-tuned to detect AI-related content (~8000 training examples)[0]. 

  - Commit messages for agent attribution
  - The contributor graph for agents
  - Repo files for instructions/configs

HN Frontpage minus AI: https://hcker.news/?view=frontpage&ai=exclude

You may also like Small Web HN: https://hcker.news/?view=frontpage&smallweb=include

0: The original workflow for this was a little different. For the better part of the past year, I had an AI agent detect AI-related stories and raise ~20 stories to me to make a judgement call on. After a while, a workflow like this just doesn't make sense when small models can do it equally as well. The training data is based on the machine and my labeling.

Funny how it uses AI