Skarlso

package main

import (
	"bytes"
	"fmt"
	"io/ioutil"
	"log"

	"golang.org/x/crypto/ssh"
	kh "golang.org/x/crypto/ssh/knownhosts"

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Archisman-Mridha

Anatomy of a motion - Command + Count + Motion

Navigation

• Jump to beginning of line : 0 | jumps to the first non-whitespace character : _
• Jump to end of line : $
• Move forward by 1 word : jumps to beginning of the next word : w | jumps to end of the next word : e
• Move backward by 1 word : jumps to beginning of the previous word : b | jumps to end of the previous word : ge
• Jump to beginning of the file : gg
• Jump to end of the file : G
• Move forward to the next instance of the character (( in this case) : f( // NOTE : Repeat motion using , (for backwards movement) or ; (for forward movement)

dehsilvadeveloper

Installing Docker on WSL 2 with Ubuntu 22.04

Instalando Docker em um WSL 2 com Ubuntu 22.04

Prerequisites

Before start the installation process, make sure you meet the following prerequisites:

• A Windows 10 operating system with WSL 2 support.
• WSL 2 enabled.
• Ubuntu 22.04 installed on WSL 2.

oleksis

Compile Mainline Kernel for WSL2

Steps for compile Kernel Linux 5.15.0

Actual Kernel

$ uname -a
Linux DESKTOP-ID 4.19.128-microsoft-standard #1 SMP Tue Jun 23 12:58:10 UTC 2020 x86_64 GNU/Linux

Work Dir linux

karpathy

"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

liranhason

Agent Capsule

A pattern for building production AI agents as documents, not agent code.

This document presents the core concept, offering a concise and accessible overview to guide implementation.

The Core Idea

Most production agents are built with an Agent SDK (OpenAI, LangChain, LangGraph, etc.). You write code for tool dispatch, memory, sub-agents, session state, and so on. Every new capability requires a code change and a deployment.