Tagged articles

Karpathy

18 articles · Page 1 of 1

Jul 15, 2026 · Artificial Intelligence

Why Karpathy Says Vibe Coding Isn’t Dead and Software 3.0 Is Giving Rise to Agentic Engineering

The article analyzes Karpathy’s evolving view—from naming Vibe Coding in 2025, through his Software 3.0 paradigm, to the 2026 introduction of Agentic Engineering—explaining how these concepts differ, why they matter for AI‑driven software development, and what product teams should adjust as model capabilities mature.

AI programmingAgentic EngineeringKarpathy

0 likes · 16 min read

Why Karpathy Says Vibe Coding Isn’t Dead and Software 3.0 Is Giving Rise to Agentic Engineering

Machine Heart

Jun 27, 2026 · Artificial Intelligence

How Andrej Karpathy Really Uses Claude – The Game-Changing CLAUDE.md Guide

The article explains the CLAUDE.md file attributed to Andrej Karpathy, detailing why large language models need explicit project‑level instructions, presenting concrete rules and best‑practice guidelines for reading code, planning changes, keeping implementations simple, testing, debugging, managing dependencies, and communicating effectively, all aimed at reducing Claude's coding errors.

AI codingClaudeKarpathy

0 likes · 19 min read

How Andrej Karpathy Really Uses Claude – The Game-Changing CLAUDE.md Guide

Machine Heart

Jun 24, 2026 · Industry Insights

Karpathy Backs Engram: AI Memory Startup Aiming for Persistent Enterprise Knowledge

Engram, a newly announced AI memory startup backed by investors such as General Catalyst, Kleiner Perkins, Sequoia and advisors including Andrej Karpathy, aims to move beyond temporary context retrieval by building a continuous‑learning memory layer that lets models absorb and recall enterprise‑specific knowledge, contrasting with typical RAG or long‑context methods.

AI memoryKarpathyLarge Language Models

0 likes · 6 min read

Karpathy Backs Engram: AI Memory Startup Aiming for Persistent Enterprise Knowledge

AI Engineering

Jun 24, 2026 · Artificial Intelligence

Is Claude Tag the Third Paradigm of Large‑Model Interaction? Karpathy’s Take

Anthropic’s new Claude Tag lets teams collaborate with Claude directly in Slack, offering multi‑user visibility, persistent channel context, an ambient proactive mode, and asynchronous project handling, while Karpathy hails it as the third major UI shift for large models amid debates over control, ownership, and open‑source alternatives.

AI collaborationAnthropicClaude

0 likes · 6 min read

Is Claude Tag the Third Paradigm of Large‑Model Interaction? Karpathy’s Take

Code Mala Tang

Jun 12, 2026 · Artificial Intelligence

Loop Engineering: When AI Coding’s Bottleneck Shifts from Prompt to Loop

The article argues that single‑call AI agents have hit their performance ceiling and that the next frontier, called Loop Engineering, moves the heavy lifting from prompt design to automated, self‑checking loops, while outlining real‑world attempts, core components, and practical limitations.

AI AgentsAnthropicAutomation

0 likes · 17 min read

Loop Engineering: When AI Coding’s Bottleneck Shifts from Prompt to Loop

AI Algorithm Path

Jun 3, 2026 · Artificial Intelligence

Why CLAUDE.md’s 166K Stars Matter: The Behavioral Guidelines for Claude Code

CLAUDE.md is a concise Markdown file that gained 166.6K GitHub stars by codifying four behavioral guidelines for Claude Code, directly tackling common AI‑coding failures such as wrong assumptions, over‑design, irrelevant edits, and weak validation, and includes practical usage instructions.

AI programmingClaude CodeGitHub

0 likes · 12 min read

Why CLAUDE.md’s 166K Stars Matter: The Behavioral Guidelines for Claude Code

SuanNi

May 23, 2026 · Artificial Intelligence

How Andrej‑Karpathy‑Skills Fixes Karpathy’s AI Coding Pitfalls

The article examines the open‑source "andrej‑karpathy‑skills" project, which encodes four principled rules to curb LLM‑driven coding errors identified by Andrej Karpathy, and shows how applying these rules improves developer productivity and code quality.

AI AgentsClaude CodeKarpathy

0 likes · 10 min read

How Andrej‑Karpathy‑Skills Fixes Karpathy’s AI Coding Pitfalls

SuanNi

May 2, 2026 · Artificial Intelligence

How Karpathy Envisions Software 3.0: Agents as the New Programming Paradigm

Karpathy argues that AI agents are reshaping software development by turning the LLM context window into a programmable layer, redefining the basic unit of work, and introducing a verifiability‑driven framework that separates domains where models excel from those where they still stumble.

AI AgentsAgentic EngineeringKarpathy

0 likes · 14 min read

How Karpathy Envisions Software 3.0: Agents as the New Programming Paradigm

TonyBai

May 2, 2026 · Artificial Intelligence

From Vibe‑Coding to Agentic Engineering: Andrej Karpathy’s Survival Rules for AI‑Era Programmers

Andrej Karpathy warns that the seductive “Vibe‑Coding” approach will soon become obsolete, urging developers to adopt “Agentic Engineering” by building guardrails, evaluation systems, and embedding their own judgment, while recognizing AI’s jagged intelligence, shifting from implementation to design, and envisioning a Software 3.0 future.

AI engineeringAgentic EngineeringKarpathy

0 likes · 11 min read

From Vibe‑Coding to Agentic Engineering: Andrej Karpathy’s Survival Rules for AI‑Era Programmers

AI Explorer

May 1, 2026 · Artificial Intelligence

Boost AI Coding with Karpathy’s Four Principles in CLAUDE.md

The article presents Karpathy’s four “sins” of LLM coding and shows how a simple CLAUDE.md file implements four guiding principles—thinking before coding, simplicity, surgical edits, and goal‑driven execution—to make Claude Code produce cleaner, more reliable code, with easy installation and broad applicability.

AI programmingCLAUDE.mdClaude Code

0 likes · 7 min read

Boost AI Coding with Karpathy’s Four Principles in CLAUDE.md

AI Explorer

Apr 27, 2026 · Artificial Intelligence

Single-File Hack Boosts Claude Code (92k★) with Four Senior‑Engineer Principles

The author presents a one‑file “CLAUDE.md” that, based on Andrej Karpathy’s four LLM coding pain points, rewrites Claude Code’s behavior using four concrete principles—think before coding, prioritize simplicity, make scalpel‑like edits, and drive execution with tests—turning AI from a noisy intern into a senior‑engineer‑like coder, and explains how to install it.

AI code generationClaude CodeGitHub

0 likes · 6 min read

Single-File Hack Boosts Claude Code (92k★) with Four Senior‑Engineer Principles

PaperAgent

Apr 25, 2026 · Artificial Intelligence

86K‑Star Repo Turns Karpathy’s Coding Wisdom into Practical AI‑Coding Rules

The article shares four concrete principles distilled from Andrej Karpathy’s experience—captured in the 86.1k‑star "andrej‑karpathy‑skills" repository—to help developers steer large language models toward reliable, concise, and goal‑driven code changes, with installation tips for Claude Code and other AI assistants.

AI codingClaude CodeKarpathy

0 likes · 7 min read

86K‑Star Repo Turns Karpathy’s Coding Wisdom into Practical AI‑Coding Rules

Wuming AI

Apr 19, 2026 · Artificial Intelligence

Why Bigger LLMs Aren’t Smarter: Karpathy Blames Junk Training Data

Karpathy argues that the rapid growth of large language models is driven more by noisy, low‑quality training data than by a need for greater intelligence, urging a split between clean cognition cores and external memory to achieve smarter, more efficient AI.

AI model efficiencyKarpathyLLM scaling

0 likes · 5 min read

Why Bigger LLMs Aren’t Smarter: Karpathy Blames Junk Training Data

Frontend AI Walk

Apr 16, 2026 · Artificial Intelligence

Hands‑On Guide to Karpathy’s Autoresearch: From Setup to Custom Research Loops

This article walks through Karpathy’s open‑source Autoresearch system, explaining its core design principles, file layout, and workflow, and then demonstrates practical AI‑agent applications for code optimization, bug fixing, and article writing, complete with setup commands, code snippets, and example experiment logs.

AI AgentAutomationKarpathy

0 likes · 25 min read

Hands‑On Guide to Karpathy’s Autoresearch: From Setup to Custom Research Loops

AI Explorer

Apr 14, 2026 · Artificial Intelligence

Enhance Claude Code with Karpathy‑Inspired Optimization Guidelines

The article examines common pitfalls of AI coding assistants like Claude Code, then presents the Karpathy‑inspired CLAUDE.md project’s four guiding principles—think before coding, prioritize simplicity, make precise edits, and execute goal‑driven tests—to improve code quality, reduce unwanted changes, and streamline prompt engineering.

AI coding assistantCLAUDE.mdClaude Code

0 likes · 6 min read

Enhance Claude Code with Karpathy‑Inspired Optimization Guidelines

Machine Learning Algorithms & Natural Language Processing

Mar 17, 2026 · Industry Insights

Karpathy’s AI Job‑Risk Chart Sparks Panic: 60 Million White‑Collar Jobs Threatened

Karpathy’s quickly‑removed project scores 342 U.S. occupations for AI exposure, revealing an average risk of 4.9, with 42% of 60 million white‑collar jobs scoring 7 or higher, while physically‑oriented roles like plumbers remain safe; Harvard research corroborates these findings and shows a nuanced shift toward job augmentation rather than wholesale replacement.

AIHarvard studyJob Automation

0 likes · 11 min read

Karpathy’s AI Job‑Risk Chart Sparks Panic: 60 Million White‑Collar Jobs Threatened

AI Engineering

Mar 15, 2026 · Industry Insights

Karpathy’s Chilling Visualization Shows Which Jobs AI Could Replace

Karpathy’s new "karpathy/jobs" visualization scores 342 U.S. occupations on AI exposure using Gemini Flash, revealing that software engineers rank 8‑9, transcriptionists hit 10, while roofers stay near 0, highlighting which jobs may soon be automated.

AI automationBLS dataGemini Flash

0 likes · 3 min read

Karpathy’s Chilling Visualization Shows Which Jobs AI Could Replace

Machine Learning Algorithms & Natural Language Processing

Mar 9, 2026 · Artificial Intelligence

Can Self‑Iterating AI Agents Run on a Single GPU? Karpathy’s Autoresearch Demo

Karpathy’s open‑source “autoresearch” project demonstrates how a compact LLM training environment on a single GPU can let an AI agent autonomously modify code, run five‑minute training experiments, evaluate improvements, and iteratively produce better models, illustrating a new research paradigm where AI conducts experiments while humans design the system.

AI research automationKarpathyLLM training

0 likes · 6 min read

Can Self‑Iterating AI Agents Run on a Single GPU? Karpathy’s Autoresearch Demo