Co-founder of WordPress and founder of Automattic; blogs at ma.tt.
recommended
The easiest way to feel this for yourself is to run one locally tonight: install Ollama or LM Studio, pull a small Qwen model, and talk to an intelligence that lives entirely on your own machine, no cloud required.
Post giving WordPress community members a reading/homework list on AI after a WordCamp keynote
Machine learning engineer working on recommender systems, personalization and information retrieval; previously at Mozilla.ai, Duo, Tumblr and Automattic, and author of the 'What are embeddings?' text.
uses
For my local setup, I'm currently using Pi as the agent harness and LM Studio as the inference server
'Running local models is good now' — the local models and harnesses she runs on an M2 Mac.
Every entry is a verbatim quote and a link to the public post it came from. Nothing is paraphrased. If it is not on record somewhere public, it is not here.
The verdict is what they actually said: loved and liked are explicit; recommended means they told others to get it; uses means they only say they use it; read is a book on their public shelf with no verdict; mixed and disliked are kept too.
A dashed affiliate link, sponsored or their own label means the post disclosed a relationship. It is shown, never hidden.
The shading behind a date shows how dated a recommendation is for its kind of thing.
The shading behind a date shows how dated a recommendation is, for its kind of thing. Fully green is recent. It drains a quarter at a time as the post gets older, and is empty once it reads as dated.
What counts as old depends on the thing. A laptop praised four years ago has been replaced twice; a book loved twenty years ago is probably still loved. The shading is gone after about:
Hardware, services4 years
Software5 years
Podcasts, courses, other8 years
Books25 years
Stripes mean the post carries no date and the date shown is an estimate. No date at all, no shading.