R44VC0RP

#!/usr/bin/env bun
/**
 * ============================================================
 * PROOF: Anthropic is specifically blocking "OpenCode" 
 * in Claude Code OAuth system prompts
 * ============================================================
 *
 * Video covering this script here: https://www.youtube.com/watch?v=G9YX6StP2-M
 * 
 * This script demonstrates that Anthropic has specifically blocked

hackermondev

hi, i'm daniel. i'm a 16-year-old high school senior. in my free time, i hack billion dollar companies and build cool stuff.

about a month ago, a couple of friends and I found serious critical vulnerabilities on Mintlify, an AI documentation platform used by some of the top companies in the world.

i found a critical cross-site scripting vulnerability that, if abused, would let an attacker to inject malicious scripts into the documentation of numerous companies and steal credentials from users with a single link open.

(go read my friends' writeups (after this one))
how to hack discord, vercel, and more with one easy trick (eva)
Redacted by Counsel: A supply chain postmortem (MDL)

marckohlbrugge

🆕 Update: See more extensive repo here: https://github.com/marckohlbrugge/unofficial-37signals-coding-style-guide

The Unofficial 37signals/DHH Rails Style Guide

About This Document

This style guide was generated by Claude Code through deep analysis of the Fizzy codebase - 37signals' open-source project management tool.

Why Fizzy matters: While 37signals has long advocated for "vanilla Rails" and opinionated software design, their production codebases (Basecamp, HEY, etc.) have historically been closed source. Fizzy changes that. For the first time, developers can study a real 37signals/DHH-style Rails application - not just blog posts and conference talks, but actual production code with all its patterns, trade-offs, and deliberate omissions.

clashnewbm3

 print "\e[?25l"

 rows, cols = `stty size`.split.map(&:to_i)


 drops = Array.new(cols) { rand(rows) }

 chars = ("0".."9").to_a + ("A".."Z").to_a + ("a".."z").to_a

 loop do

jankeesvw

---

name: tester description: Use this agent when you need to write RSpec tests for new functionality, including feature specs for user workflows and unit tests for models, services, or other classes. Examples: Context: User has just implemented a new authentication feature and needs comprehensive test coverage. user: 'I just added magic link authentication to the User model. Can you write tests for this?' assistant: 'I'll use the rspec-test-writer agent to create comprehensive tests for your magic link authentication feature.' Since the user needs RSpec tests written for new functionality, use the rspec-test-writer agent to create appropriate test coverage. Context: User has created a new controller action and wants to ensure it's properly tested. user: 'I added a new endpoint for project time tracking. Here's the controller code...' assistant: 'Let me use the rspec-test-writer agent to write feature specs and controller tests for your new time tracking en

mdchaney

def fix_encoding(str)
  # The "b" method returns a copied string with encoding ASCII-8BIT
  str = str.b

  # Strip UTF-8 BOM if it's at start of file
  if str.byteslice(0..2) == "\xEF\xBB\xBF".b
    str = str.byteslice(3..-1)
  end

  if str.ascii_only?

rain-1

How large are large language models? (2025)

This aims to be factual information about the size of large language models. None of this document was written by AI. I do not include any information from leaks or rumors. The focus of this document is on base models (the raw text continuation engines, not 'helpful chatbot/assistants'). This is a view from a few years ago to today of one very tiny fraction of the larger LLM story that's happening.

History

• GPT-2,-medium,-large,-xl (2019): 137M, 380M, 812M, 1.61B. Source: openai-community/gpt2. Trained on the unreleased WebText dataset said to 40GB of Internet text - I estimate that to be roughly 10B tokens. You can see a list of the websites that went into that data set here domains.txt.
• GPT-3 aka davinci, davinci-002 (2020): 175B parameters. There is a good breakdown of how those parameters are 'spent' here [How d

arch1t3cht

What you NEED to Know Before Touching a Video File

Hanging out in subtitling and video re-editing communities, I see my fair share of novice video editors and video encoders, and see plenty of them make the classic beginner mistakes when it comes to working with videos. A man can only read "Use Handbrake to convert your mkv to an mp4 :)" so many times before losing it, so I am writing this article to channel the resulting psychic damage into something productive.

If you are new to working with videos (or, let's face it, even if you aren't), please read through this guide to avoid making mistakes that can cost you lots of computing power, storage space, or video quality.

fxn

Namespaces 101

Introduction

Ruby has recently merged namespaces as an experimental feature that is disabled by default, as of this writing.

This is a non-trivial development driven by @matz himself, and mainly implemented by @tagomoris, who just became a Ruby committer (🎉).

The feature has been cooking for a long time, with a first ticket opened a couple of years ago (#19744) and a revised one opened just last week (#21311).

mikker

# Usage:
#
#   class Post < ApplicationRecord
#     include HasNanoid
#     has_nanoid
#   end
#
module HasNanoid
  extend ActiveSupport::Concern