Chris Olah Portfolio
Co-founder of Anthropic, where he leads interpretability research; his blog and the "Circuits" paper series present original findings on reverse-engineering what individual neurons and features compute inside trained networks, built on a decade-long archive going back to posts like "Understanding LSTM Networks."
What makes it work
A breakdown of the choices that make this portfolio stand out.
Original research, not secondhand explanation
The Circuits series doesn't summarize other people's papers — it publishes original findings about which internal features and circuits deep networks compute, the kind of ground-up empirical work that defines actual research rather than research communication.
Diagrams built to carry the technical argument
Custom visualizations of activation space and feature interactions are not decoration — they are the proof itself, since interpretability claims are hard to state convincingly in words alone.
A research agenda visible across a decade of posts
Read start to finish, the archive traces one throughline — from "Neural Networks, Manifolds, and Topology" (2014) to circuits and transformer interpretability — showing a sustained research program, not scattered topical posts.
What AI Researchers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Publish original findings, not just summaries of others' papers — a genuine research contribution is what separates a researcher's site from a technical-writing site.
When a claim is hard to state in words, build a custom diagram that carries the argument instead of describing it in prose.
Let your archive read as a single throughline over years, not a set of disconnected topics — it shows a sustained research agenda.
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