jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

chriscasola

A python script to generate a table of contents (with links) for a GitHub Flavored markdown file.
The file must contain a level one header with a title that contains "Table of Contents".
The script will generate a TOC containing all level 1, 2, and 3 headers.

Run the script like this:
python tocgen.py inFileName outFileName

BEFORE file:
--------------------------------------------------------
This is my GitHub wiki page.

tuxfight3r

Bash Shortcuts

Moving

command	description
ctrl + a	Goto BEGINNING of command line

wojteklu

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

---

General rules

1. Follow standard conventions.
2. Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
3. Boy scout rule. Leave the campground cleaner than you found it.
4. Always find root cause. Always look for the root cause of a problem.

Design rules

miglen

List of Linux networking tools

netstat (ss)

Displays contents of /proc/net files. It works with the Linux Network Subsystem, it will tell you what the status of ports are ie. open, closed, waiting, masquerade connections. It will also display various other things. It has many different options. Netstat (Network Statistic) command display connection info, routing table information etc. To displays routing table information use option as -r.

Sample output:

Proto Recv-Q Send-Q  Local Address          Foreign Address        (state)    
tcp4 0 0 127.0.0.1.62132 127.0.0.1.http ESTABLISHED

sundowndev

Google dork cheatsheet

Search filters

Filter	Description	Example
allintext	Searches for occurrences of all the keywords given.	allintext:"keyword"
intext	Searches for the occurrences of keywords all at once or one at a time.	intext:"keyword"
inurl	Searches for a URL matching one of the keywords.	inurl:"keyword"
allinurl	Searches for a URL matching all the keywords in the query.	allinurl:"keyword"
intitle	Searches for occurrences of keywords in title all or one.	intitle:"keyword"

upsilun

"\033[0m" // Reset all text attributes to default
"\033[1m" // Bold on
"\033[2m" // Faint off
"\033[3m" // Italic on
"\033[4m" // Underline on
"\033[5m" // Slow blink on
"\033[6m" // Rapid blink on
"\033[7m" // Reverse video on
"\033[8m" // Conceal on
"\033[9m" // Crossed-out on

LukasMFR

(() => {
  function formatDate(date = new Date()) {
    return date.toISOString().split("T")[0];
  }

  function escapeMarkdown(text) {
    return text
      .replace(/\\/g, "\\\\")
      .replace(/\*/g, "\\*")
      .replace(/_/g, "\\_")

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.