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A tweet claims that Graph Engineering, developed by two Anthropic seniors, has made Karpathy's loop 1000x better by wiring agents into a graph, resulting in significantly improved Claude responses. It also notes that Andrej Karpathy joined Anthropic five weeks ago.
Andrej Karpathy says he's never felt more behind as a programmer, explaining that Software 3.0 shifts programming from writing code to prompting within a context window, redefining the job rather than making it easier.
Andrej Karpathy removed his affiliation with Anthropic from his online biography, suggesting a potential change in his professional association.
Andrej Karpathy may have left Anthropic, according to reports. The AI researcher previously worked at OpenAI and Tesla.
A vlog about Andrej Karpathy's journey from Google intern to founder of AI-defining projects like Tesla Autopilot, OpenAI, and Claude, emphasizing the value of working on things you don't yet understand.
Andrej Karpathy gives a 15-minute talk on the challenges of multi-task learning, covering architecture tradeoffs, loss balancing, data engines, and team workflow, highlighting often-overlooked team coordination issues.
Andrej Karpathy shared his years of experience with AI Agents at a Silicon Valley tech meetup, including that early OpenAI attempts were premature, the language model path was the right approach, agents are easy to demo but hard to productize, and that human cognitive structures should be leveraged as inspiration.
Andrej Karpathy's LLM Wiki pattern enables building a persistent, structured knowledge base that compounds over time, unlike stateless RAG systems. The tutorial shows how to create one in under 30 minutes using LLMs to compile and link markdown pages.
A Twitter thread discusses the irony of Andrej Karpathy's teaching philosophy—learning by building from scratch—while he now uses AI to code, and shares a 3-week learning journey using Claude Opus 4.8 to master deep learning the old way.
Andrej Karpathy emphasizes that true AI understanding comes from building, not collecting prompts, in a 2-hour interview.
Andrej Karpathy commented that Claude Tag represents the third paradigm shift in LLM interaction: from website, app to a persistent, asynchronous team member, and emphasized that this shift is effective and powerful.
Andrej Karpathy and Geoffrey Huntley advocate using loops for AI prompts—giving the AI a goal, letting it plan, act, and check its own work—instead of manual single-request interactions.
Andrej Karpathy shares his simple approach to using AI in a workshop: just tell the machine what you want in plain words, no complex prompts or frameworks. The video reveals his actual workflow.
The release of Fable 5 has sparked widespread discussion. Andrej Karpathy calls it a major version leap, some consider it their "singularity moment," while others worry about the future of software engineering. This article summarizes 10 most noteworthy reactions.
Jeremy Howard expresses strong dismay over an event that he believes is a dark day with potentially irreversible damage, likely in the AI industry.
Andrej Karpathy discusses how AI-generated software is increasing demand for software, referencing Jevon's paradox.
Andrej Karpathy, co-founder of OpenAI and former AI lead at Tesla, demonstrated his practical AI workflow over two hours, emphasizing simple natural language instructions and incremental nudges rather than complex engineering.
Curatube is a distraction-free interface for YouTube playlists, designed to help focus on learning. It currently features the Neural Networks: Zero to Hero course by Andrej Karpathy.
The article argues that using LLMs for research requires a closed-loop system like Karpathy's LLM Wiki or the Recall AI knowledge base to prevent hallucinations, ensuring all outputs are grounded in trusted source documents.
Andrej Karpathy's lecture reveals an 'LLM Wiki' pattern to transform past content into a self-updating knowledge base, helping creators discover patterns in their writing.