graydon

filc overhead rough tests:

  - mg /usr/share/dict/words
    - yolo: 10MB maxrss / 101m insn /  54m cycle
    - filc: 30MB maxrss / 370m insn / 176m cycle
    - filc/yolo: 3x mem / 3.66x insn

  - xzcat optfil-0.674-linux-x86_64.tar.xz >/dev/null
    - yolo:  9.7MB maxrss / 40.4bn insn / 32.7bn cycle /  9.42s real /  9.32s user / 0.09s sys
    - filc: 33.2MB maxrss / 77.5bn insn / 42.8bn cycle / 12.29s real / 12.16s user / 0.14s sys

geoffreylitt

name	explain-diff-html
description	Use when the user asks for a rich explanation of a code change, diff, branch, or PR. Produces HTML output.

Explain Diff

Please make me a rich, interactive explanation of the specified code change.

It should have these sections:

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.

AlexGladkov

Global Profile

Персонализация

• Язык общения: русский
• Имею право не соглашаться с решениями пользователя. Если решение ведёт к костылю, дыре в безопасности или техдолгу — ОБЯЗАН возразить и предложить альтернативу. Молчаливое согласие с плохим решением = ошибка.
• Качество и security > скорость. Не принимать "потом поправим", "сойдёт для MVP", "это временно". Временные решения становятся постоянными.
• Долгосрочная польза > быстрый результат. Выбирать решения, которые масштабируются и поддерживаются, даже если это дольше.
• Если пользователь настаивает на костыльном решении — чётко обозначить риски и зафиксировать это в Report.

cereblab

Update — 2026-07-14: This is the original wire-level analysis (grok 0.2.93). Since publishing: xAI disabled the upload server-side (disable_codebase_upload: true); added a /privacy opt-out — which I wire-tested and found to be a data-retention setting, not a block on what's sent; and Elon Musk publicly committed to deleting all previously-uploaded data (not yet confirmed complete). Full, maintained story + evidence: https://cereblab.com · https://github.com/cereblab/grok-build-exfil-repro

---

What xAI's Grok Build CLI Actually Sends to xAI: A Wire-Level Analysis

By @cereblab — Independent AI Safety Checker. Reproduce it yourself: github.com/cereblab/grok-build-exfil-repro

*A measured, reproducible teardown. Findings are backed by captured artifacts (endpoint, HTTP method, status code, byte size, host) and repro commands; where an observation was seen live but not retained as a file, §7 says so expli

gopsmith

#!/bin/zsh

# CREDITS: Original idea and script disable.sh by pwnsdx https://gist.github.com/pwnsdx/d87b034c4c0210b988040ad2f85a68d3
#   Big Sur revision by b0gdanw https://gist.github.com/b0gdanw/40d000342dd1ba4d892ad0bdf03ae6ea

# TEMPORARILY disabling (e.g. STOPPING via 'bootout') unwanted services on macOS 11 Big Sur and macOS 12 Monterey:
# This version is for a special boot that optimizes for real-time music performance and streaming video.
# Due to the read-only system volume introduced with macOS Catalina, this script can NOT be run in Recovery mode's Terminal.
# For my purposes I leave WiFi enabled, for streaming video to a local router with no internet connection.

straker

ICE Out; Abolish ICE

Basic Snake HTML and JavaScript Game

Snake is a fun game to make as it doesn't require a lot of code (less than 100 lines with all comments removed). This is a basic implementation of the snake game, but it's missing a few things intentionally and they're left as further exploration for the reader.

Further Exploration

vialuch

在 ChatGPT 对话里做一个动态状态栏

通用教程与实现思路。作者：Dan & Joy

效果思路很简单：让模型调用一个只读 MCP 工具，工具返回 mood / place / focus / note 等结构化数据；ChatGPT 再把这份数据交给一个内嵌 HTML 组件。组件可以用 CSS 做动画，用 JavaScript 更新时间、展开面板和处理点击，也可以把用户刚刚操作后的状态带到下一轮对话。

它不是修改 ChatGPT 原生界面，也不是普通 Markdown 图片，而是一个运行在对话消息里的 MCP Apps 组件（iframe）。示例字段和文案都只是占位，每个人都可以按照自己的角色、项目或使用场景替换。

1. 架构