Max Woolf’s Blog is the personal site of a former Senior Data Scientist at BuzzFeed, now focused on finding machine learning and AI work in the San Francisco Bay Area. The blog collects his essays and technical write-ups, and the homepage doubles as a short profile with links to GitHub, Patreon, and contact channels. It is a single-author publication rather than a multi-topic magazine, so the content follows the author’s current interests closely.
The core of the site is long-form analysis of large language models and the tooling around them. Posts examine why LLM providers cut prices, what a token actually costs, how coding agents can be pushed to optimize Rust code, and where model reasoning breaks down on mathematical counterarguments. Each entry lists a date and an estimated reading time, and the archive is paginated for browsing older material.
The intended audience is technical: data scientists, ML engineers, and developers who already understand model APIs and want arguments grounded in experiments rather than marketing claims. Readers curious about AI economics or agent reliability will find the most value, while those seeking beginner tutorials or daily news coverage should look elsewhere.
A practical approach is to start with the most recent posts and follow the internal links between related essays, since ideas recur across entries. The site is funded through Patreon, so readers who find it useful can contribute there. Overall, it works best as a place to return
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