Contribute.
We publish articles, case studies, primers, and tools from engineers and researchers working on ML systems. If you've learned something hard the hard way, you should write about it here.
The process
Share an idea
Start a GitHub Discussion, drop into Discord, or open a PR. A few sentences is enough.
Shape it
We'll help you narrow the idea, find the useful angle, and decide what form it should take.
Draft
Write in markdown, in your own voice. Add code, figures, equations, or links if they help.
Review
We'll review for clarity, correctness, and readability. Nothing fancy, just make the work easier to learn from.
Publish
Once it is ready, we publish it and credit you as a contributor. Comments happen in GitHub Discussions.
What we publish
- Articles — opinionated, well-argued takes on a real problem (~1,500–3,000 words).
- Case studies — what happened when you actually shipped the thing.
- Primers — careful explainers of techniques that deserve more careful treatment.
- Tools — working calculators or visualizers, with a writeup.
- Reading lists — annotated bibliographies on narrow topics.
What we don't publish
- Promotional content for products.
- Recycled paper summaries.
- "X is dead, long live Y" hot takes without evidence.
- Listicles. Especially listicles.
Style
Concrete over abstract. Numbers over adjectives. One idea per paragraph. Show your work, including the parts that didn't.
We're trying to make a publication that you'd want to send to your future self. Write accordingly.