Victrid

#!/bin/bash

hash git 2>/dev/null || { echo >&2 "Required command 'git' is not installed. ( hmm... why are you using this? ) Aborting."; exit 1; }
hash realpath 2>/dev/null || { echo >&2 "Required command 'realpath' is not installed. Aborting."; exit 1; }
hash pwd 2>/dev/null || { echo >&2 "Required command 'pwd' is not installed. Aborting."; exit 1; }
hash cd 2>/dev/null || { echo >&2 "Required command 'cd' is not installed. Aborting."; exit 1; }
hash echo 2>/dev/null || { echo >&2 "Required command 'echo' is not installed. Aborting."; exit 1; }
hash mv 2>/dev/null || { echo >&2 "Required command 'mv' is not installed. Aborting."; exit 1; }
hash diff 2>/dev/null || { echo >&2 "Required command 'diff' is not installed. Aborting."; exit 1; }
hash diffstat 2>/dev/null || { echo >&2 "Required command 'diffstat' is not installed. Aborting."; exit 1; }

ThaddeusJiang

My tech interview flow

背景

1. 为什么应聘我们公司？

有明确判断标准

1. bugfix of your own code
2. add feature of your own code

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.