AI researcher and educator
Andrej Karpathy
Andrej Karpathy is an AI researcher and educator, a founding member of OpenAI, and a former director of AI at Tesla working on computer vision.
About Andrej Karpathy
Andrej Karpathy is an AI researcher and educator whose public teaching covers neural networks and large language models. His educational videos include both technical lessons on building models and introductions for a general audience.
He was a founding member and research scientist at OpenAI, led Tesla's AI and computer vision work from 2017 to 2022, and returned to OpenAI in 2023 to work on midtraining and synthetic data. During his PhD at Stanford, he designed and taught the CS231n course on deep learning for visual recognition.
Mentioned in our coverage
105 articles name Andrej Karpathy, excluding author credits.
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- Managed Deep Agents 0.8 Adds User Memory for Personalized AI Agents →
Managed Deep Agents 0.8 ships a second durable memory layer scoped to the authenticated caller. Here is what user memory stores, how to enable it in memory.py, the default Slack and HTTP access rules, and how it relates to schedules.
- Ponytail: The 152K-Star Skill That Makes AI Agents Write Less Code (Tested Claims, Install Guide) →
Ponytail turns your AI coding agent into the laziest senior developer in the room: before writing code it climbs a ladder from do not build it, to reuse it, to the standard library, to a native feature. Its own agentic benchmark reports 54 percent less code and 100 percent safety. Here is how it works, what the numbers do and do not show, and how to try it without regret.
- Karpathy: Ask for Discardable Software Artifacts Now That Code Is Abundant →
On October 2, 2026, Andrej Karpathy argued that as intelligence and code become abundant, you can ask for large, custom, discardable software artifacts, such as web apps and video explainers, that would never have made sense to build before. The shift is economic, not a new model capability.
- Karpathy: Stop Reading LLM Output as Plain Text — Ask for a Video Instead →
On October 2, 2026, Andrej Karpathy posted a short ladder for understanding what language models write: controlled-language text, then diagrams, then HTML pages, then bespoke explainer videos. Here is what each rung means, the exact prompts to try, and where the advice breaks down.
- MicroLLM Lab: Tiny WebGPU Models in the Browser →
A Hacker News front-page demo lets you load Q4 small language models in Chrome, Safari, or Edge, cache them in IndexedDB, and chat with no server after the download. explainx.ai covers what 100M-class models are actually for, the vibe-coded UI fight, Firefox WebGPU failures, and how this lab differs from transformers.js and in-browser fine-tuning.