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@ShawnMcCool
ShawnMcCool / gist:e7fea18b5695f8c499ad
Last active September 24, 2026 07:21
Sailfish Theme Icons
com_android_browser
graphic-avatar-text-back
graphic-background
graphic-bootloader-usb-wakeup
graphic-busyindicator-large-background
graphic-busyindicator-large
graphic-busyindicator-medium-background
graphic-busyindicator-medium
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graphic-button

I've recently joined Amazon Dublin from India and got opportunities to interview with Meta London, Zalando Berlin & some other companies. I extensively researched about companies hiring internationally which support visa & relocation for Tech roles. So sharing list of companies:

Do consider to STAR, if it helped you.

London

User: ISHAAN,glaitm
Key: 27R3VDEFYFX4N0VC3FRTQZX
@Pythonation
Pythonation / prompt.md
Last active September 24, 2026 07:08
3 PROMPTS OF CODING AGENTS

1. برومبت التخطيط المطوّر (The Planning Protocol)

[الدور والمسؤولية] أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي: [أدخل وصف المشروع هنا]

[قواعد ما قبل التتخطيط] قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":

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.

@jankammerath
jankammerath / keep-msteams-alive.go
Created September 10, 2026 12:24
Go code that moves the cursor around and keeps Microsoft Teams green on Windows 11
package main
import (
"fmt"
"math/rand"
"os"
"os/signal"
"syscall"
"time"
"unsafe"
@k16shikano
k16shikano / SKILL.md
Last active September 24, 2026 07:04
japanese-tech-writing/SKILL
name japanese-tech-writing
description 日本語の技術文書・書籍原稿の文章規範。段落と論証の構成(パラグラフライティング)、論証の厳密さ(ツッコミどころの除去)、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、翻訳調の比喩と擬人化の禁止(「運ぶ」「効く」「開かれた問い」など)、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。
license Unlicense(https://gist.github.com/k16shikano/67625f2a7d96e3bbdfae8d571a936063

日本語技術文書の文章規範

日本語で技術的な原稿(書籍の章、記事、解説文)を書く・推敲するときは、以下の規範に従う。

@minanagehsalalma
minanagehsalalma / FuckLDPlayer.md
Last active September 24, 2026 07:01
Kill ads on LDPlayer (systemwide + home screen) Full Guide

Kill ads on LDPlayer (systemwide + home screen) — guide

This covers the “LDPlayer-served” promos: home-screen recommended games row, splash/promo banners, and other injected junk. We’ll use layered defenses so it stays gone.


What you’re trying to remove

  • LDPlayer home screen “recommended games” strip (like in your screenshot)
  • In-emulator promos coming from LD system apps (store/market/recommendation services)
@minimaxir
minimaxir / AGENTS.md
Created September 19, 2026 17:42
Rust AGENTS.md (20260919)

Agent Guidelines for Rust Code Quality

This document provides guidelines for maintaining high-quality Rust code. These rules MUST be followed by all AI coding agents and contributors.

Your Core Principles

All code you write MUST be fully optimized.

"Fully optimized" includes:

@kennyg
kennyg / llm-wiki-obsidian-setup.md
Last active September 24, 2026 07:01
LLM-Wiki Obsidian Setup Guide — full implementation of Karpathy's llm-wiki pattern

Setting Up the LLM-Wiki Pattern in Obsidian

Based on Karpathy's llm-wiki pattern — using LLMs to incrementally build and maintain a persistent, interlinked wiki from raw sources rather than re-deriving knowledge on every query.

Quick Start — Paste This Into Your Agent

Copy the prompt below into Claude Code, Codex, or any LLM agent with file access. It will scaffold the wiki, configure the tooling, and update your CLAUDE.md with the schema. Then you just start ingesting sources.

I want to set up the llm-wiki pattern in my Obsidian vault. Follow this guide exactly: