Neel Nanda Portfolio
Mechanistic interpretability researcher who ran DeepMind's mech interp team and now leads the interpretability track at MATS; his site archives 50+ numbered technical posts reverse-engineering transformer internals, alongside open recruiting and mentorship for new interpretability researchers.
What makes it work
A breakdown of the choices that make this portfolio stand out.
A numbered post series that functions as a running research log
Sequentially numbered posts (past 50) read like a lab notebook made public — readers can trace how his understanding of transformer circuits evolved rather than seeing only polished conclusions.
Mentorship infrastructure built into the site itself
Recruiting and supervising MATS applicants directly from the homepage turns a personal blog into a functioning pipeline for training new interpretability researchers, not just a publishing outlet.
Research strategy writing alongside technical writing
"Good Research Takes are Not Sufficient for Good Strategic Takes" addresses how to choose problems, not just how to solve them — a rarer and higher-leverage kind of writing for a field this young.
What AI Researchers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Number your posts and let them read as a running log, not a disconnected greatest-hits feed.
If your field is young, build a visible path (a program, a set of starter problems) for newcomers directly into your site.
Write occasionally about how you pick research problems, not only about your solutions — it signals judgment, not just execution.
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