A Survival Guide to a PhD
Source
- Source kind:
blog-rss-item - URL: http://karpathy.github.io/2016/09/07/phd/
- Discovery source: https://karpathy.github.io/feed.xml
- License:
NOASSERTION - Distribution policy:
public-summary-local-archive-only - Public mirror status:
summary-only - Content hash:
7a26db6dc81e71d3f71a9671e47e25f30412426b8b4d9669327da0695e6760ea - First seen: 2026-05-15
- Last changed: 2026-05-15
Classification
- Primary category: Personal heuristics / AI philosophy / learning advice
- Corpus source note: 2026-05-15-karpathy-public-corpus
- Project taxonomy: karpathy-project-taxonomy
- Idea map: karpathy-idea-map
- Topic hub: karpathy-public-work
Summary
This guide is patterned after my âDoing well in your coursesâ , a post I wrote a long time ago on some of the tips/tricks Iâve developed during my undergrad. Iâve received nice comments about that guide, so in the same spirit, now that my PhD has come to an end I wanted to compile a similar retrospective document in hopes that it might be helpful to some. Unlike the undergraduate guide, this one was much more difficult to write because there is significantly more variation in how one can traverse the PhD experience. Therefore, many things are likely contentious and a good fraction will be specific to what Iâm familiar with (Computer Science / Machine Learning / Computer Vision research). But disclaime…
What This Teaches
- How Karpathy frames technical judgment, learning, research, or AI systems in long-form prose.
- Useful as a high-signal idea source for research taste, project framing, and agent workflow design.
Why It Matters
Karpathy’s posts often crystallize reusable heuristics; this wiki should preserve the ideas without relying on chat memory.
Public Handling Notes
- EXTRACTED: This page records public metadata and a source-grounded summary.
- INFERRED: Full local preservation, when available, is for private/local use unless a license or explicit source policy makes public redistribution safe.
- Do not treat this page as permission to republish unlicensed source text or code wholesale.