devilankur18

TokenZip — PRD, HLD, LLD

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📋 PRD — Product Requirements Document

1. Executive Summary

TokenZip v2 transforms Karpathy's llm wiki concept into a gzip like token compression engine on top of entire codebase, which can reduce the LLM input token cost upto by 95% when using with Coding Copilots like Claude Code, Codex etc. Instead of generating a flat text summary, it builds a multi-level, queryable, chainable knowledge graph — from repo → modules → files → symbols — stored locally in .tokenzip/db, exposed as an MCP server for any AI copilot, and kept fresh via git hooks

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.

gpolaert

Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36
Mozilla/5.0 (Windows NT 6.3; WOW64; Trident/7.0; MDDCJS; rv:11.0) like Gecko
Mozilla/5.0 (Linux; U; Android 4.4.2; id; SM-G900 Build/KOT49H) AppleWebKit/534.30 (KHTML, like Gecko) Version/4.0 UCBrowser/9.9.2.467 U3/0.8.0 Mobile Safari/534.30
Mozilla/5.0 (Windows NT 10.0; WOW64; Trident/7.0; ASU2JS; rv:11.0) like Gecko
Mozilla/5.0 (X11; Linux i686)
Mozilla/5.0 (Windows NT 10.0; WOW64; Trident/7.0; MAARJS; rv:11.0) like Gecko
Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36 OPR/42.0.2393.517
Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36
Mozilla/5.0 (Windows NT 10.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36

ddh0

# safetensors_convert_fp16_to_8bit.py
# Python 3.11.7

import safetensors.torch
import safetensors
import torch
import os

# blacklist takes priority over whitelist
# a tensor will only be cast if it matches the whitelist but not the blacklist

cedrickchee

AIE Singapore 2026 Leadership Track Recap

Session 1 - Building an AI-Native Startup: Lessons from Belli

Speaker: Jeff Pan and Alex, Belli

• We're going to talk about the unsexy bits today
• We do forward deployed engineering with airlines
  • Cargo softwares
• Palantir - coined FDE

journeymanavi

Production Web Server Setup and Deployment Guide

This is a detailed runbook for setting up a production server on an Ubuntu 16.04 cloud VPS for automated deployment of static web content to be served by an NGINX web server and Node.js web application behind an NGINX reverse-proxy, both with SSL/TLS (https) support.

The steps are as follows:

1. Create a VPS instance
2. Set Up Server Security
   1. Update Server Software
3. Create a non-root user

heiswayi