onevcat

基本设定

• 服务对象为 onevcat：资深 iOS 开发者，技术力爆炸，所以不需要废话。重视 “Slow is Fast”、推理质量、抽象与长期可维护性。github.com/onevcat, onevcat.com, onev.cat, onev.dev, x.com/onevcat 等都视为用户相关
• 代码、注释、标识符、提交信息及代码块内容用标准/简洁/明确的 English。技术文档优先使用 English；若文档现有中文语境，则正文中文、代码块 English。English 遵守 ASD-STE100 Simplified Technical English (STE)。
• 对需要说明结论、方案或决策的任务，按“直接结论 → 简要推理 → 可选方案 → 可执行下一步”组织，不要长篇大论，不要事无巨细；简单确认、闲聊或一行答案直接回答。
• 在修改文件时，使用待修改文件中使用的语言，切忌中英文混杂。
• 处理 GitHub 相关操作优先使用 gh CLI。
• 目标：作为强推理、强规划的编码助手，首要目标是完成任务。尽量一次到位，减少无谓澄清，只在明确被提问时才解释技术细节。

人设

rajesamp

Top 50 Large Language Model Interview Questions — Study Guide

A study companion with detailed, independently-authored answers, math, and supply-chain security notes throughout. Intended for personal interview preparation.

Credits & Source

• Original question list: Hao Hoang, "Top 50 Large Language Model (LLM) Interview Questions," May 2025.
• Source file: Google Drive PDF
• Source SHA-256: c11533b57e57de93b1b3c9542bb1f33081c2623f85715ddccb738340098dc1bf
• Answers: independently authored for this study guide (not reproduced from the source). Questions are used as short topic headings.

AlexRed29

Hatsune Miku Project DIVA: MegaMix+ | ULTIMATE WAY TO PLAY WITH MODS | 2026

UPDATED: August 31, 2026

DOCUMENT INDEX

0. FIRST-STEPS

1. REQUIREMENTS

2. ESSENTIAL MODS

3. Add-On Mods

4. Translations

kescherCode

#!/usr/bin/env bash

## This NetworkManager dispatcher script automatically tries to log into ICE WiFi.
## Sometimes, the first few attempts fail.

if [ "$CONNECTION_ID" = "WIFIonICE" ]; then
  case $2 in # status
    up)
      for (( i = 0; i < 5; i++ )); do
        if curl --fail 'https://login.wifionice.de/cna/logon' -X POST; then

nikolan123

Fixing Hammer and HLMV in Portal 2 build 852_0

Requirements

• A complete extracted 852_0 July 2009
• A 852_2 July 2010 build for the missing assets
• PowerShell
• Python 3 for the tier0.dll patcher

So you don't have to modify all the commands below, set these 2 vars to your paths:

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.

chaitrajk

🚀 2026 Master DSA Pattern Blueprint & Blind 75 Roadmap

Strategy: Stop grinding 500+ random LeetCode problems. Master these 14 Core DSA Patterns across the top Blind 75 questions to solve 90% of technical coding interviews at top product companies.

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⏱️ 12-Week Strategic Execution Plan

| Phase | Timeline | Focus Area | Goal |

chaitrajk

Premium Software Engineering Placement Roadmap (2026 Edition)

---

1. Introduction

Who This Roadmap Is For

• Target Audience: Engineering students (CS/IT & Non-CS branches) targeting Tier-1, Tier-2, Tier-3 placements, product-based companies (FAANG/MAANG, Unicorns), and high-paying service startups.
• Prerequisites: Zero prior coding knowledge required.