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.

lucataco

webos-debloat

One shell script that makes a rooted LG webOS TV lighter and quieter:

• hides bloat tiles and background apps from the launcher
• stops preloading apps the TV keeps in RAM whether or not you open them
• turns off home-screen promotions, promo videos, sports alerts, content recommendations and Live Plus (ACR)

Nothing is deleted and the root filesystem is never touched. It only edits

timvisee

Falsehoods programmers believe about time

This is a compiled list of falsehoods programmers tend to believe about working with time.

Don't re-invent a date time library yourself. If you think you understand everything about time, you're probably doing it wrong.

Falsehoods

• There are always 24 hours in a day.
• February is always 28 days long.
• Any 24-hour period will always begin and end in the same day (or week, or month).

lewangdev

patch:
  # 菜单
  menu:
    page_size: 8  # 候选词个数
    # alternative_select_labels: [ ①, ②, ③, ④, ⑤, ⑥, ⑦, ⑧, ⑨, ⑩ ]  # 修改候选项标签
    # alternative_select_keys: ASDFGHJKL  # 如编码字符占用数字键，则需另设选字键
    # ascii_mode、inline、no_inline、vim_mode 等等设定，可参考 /Library/Input Methods/Squirrel.app/Contents/SharedSupport/squirrel.yaml
  # 中西文切换
  #
  # 【good_old_caps_lock】 CapsLock 切换到大写或切换中英。

ry

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.

sugat009

Issue

If you are here, you probably already know the issue.

Cause

When you pair your devices with an operating system (OS), a unique "link key" is generated and stored on both the devices and the OS. The catch is that both Windows and Linux see your laptop's internal Bluetooth adapter as the same hardware, and thus, the same MAC address. When you switch OSes and reconnect, the new OS generates a different link key, which overwrites the previous one on your devices. This invalidates the pairing for the other OS, forcing you to "forget" and re-pair.

My PC

• OS: Manjaro 25 and Windows 11
• Device: Lenovo Legion 5 Pro i