priyavrat-misra

LeetCode Study Plans

• Programming Skills
• Data Structure
• Algorithm
• Graph Theory
• Dynamic Programming
• Binary Search
• SQL

x-yuri

Reusing GCP credentials

gcloud and ADC credentials are interchangeable and can be copied.

Gemfile:

source "https://rubygems.org"
gem 'google-cloud-storage'

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.

rxaviers

People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

kibotu

Run Qwen 3.5 Locally with Claude Code — Zero API Bills, Full Agentic Coding

Your Mac has a GPU. Your Mac has RAM. Why are you paying someone else to think?

This guide gets you a fully local agentic coding setup: Claude Code talking to Qwen 3.5-35B-A3B via llama.cpp, all running on your Apple Silicon Mac. No API keys. No cloud. No surprise invoices. Just you, your M-series chip, and 35 billion parameters doing your bidding on localhost.

Based on this article.

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ossa-ma

AI Writing Tropes to Avoid

Add this file to your AI assistant's system prompt or context to help it avoid common AI writing patterns. Source: tropes.fyi by ossama.is

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Word Choice

"Quietly" and Other Magic Adverbs

Impact123

Proxmox VE tips

Just some tips I gathered over time. All in one easily reachable place so I can share it wherever I want.

Please note that unless you see a shebang (#!/...) these code blocks are usually meant to be copy & pasted directly into the shell. Some of the steps will not work if you run part of them in a script and copy paste other ones as they rely on variables set before.
The { and } surrounding some scripts are meant to avoid poisoning your bash history with individual commands, etc. You can ignore them if you manually copy paste the individual commands.

Table of contents

• Proxmox VE tips

hielfx

package domain

import (
	"context"
	"database/sql"

	"github.com/jmoiron/sqlx"
)

//SQLDB An interface to use for both sqlx.DB and sqlx.Tx (to use a transaction or not)

rohitg00

LLM Wiki v2

A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory, a persistent memory engine for AI coding agents.

This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.

What the original gets right

The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.