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@itachi-re
itachi-re / yt-dlp-guide-enhancements.md
Created June 12, 2026 08:11
Complete yt-dlp reference for power users. AV1, MKV, 1080p/4K, Opus audio, playlists, SponsorBlock, cookies, config files, and 25+ recipes.

Intro

AI agents are amplifiers. If you're good at your job, agents make you better. You do more great things, faster. But if you're bad at your job, agents amplify that too. Where you used to cause a slow trickle of shit, now you have the means to unleash a full-blown shitstorm, at scale, in minutes.

Now, AI is all the rage these days, and for good reason. So of course people are using agents to manage real resources: infrastructure, databases, applications, all of it. The question is what happens when they do. That's what we're looking at today: an agent managing actual cloud resources, what goes wrong, why it goes wrong, and what it takes to make it work properly.

Setup

git clone https://github.com/vfarcic/infra-with-ai
@angelo-swe
angelo-swe / repo-series.md
Last active August 28, 2026 08:18
The Repo List — every repo from my series, kept updated

The Repo List

Every repo from my series, newest first. I keep this same link updated — save it.

Follow me on Instagram for the next one: @angelotrifanoff.ai


Can I Vibecode It — the kill list for your app subscriptions

https://canivibecodeit.com

@andrewhodel
andrewhodel / go-pprof.md
Last active August 28, 2026 08:12
Go profiling with pprof

Importing net/http/pprof adds HTTP endpoints to serve profile files that can be viewed or charted with a command line tool when the runtime.Set* functions are executed.

1. import pprof into the go program

import _ "net/http/pprof"

If your application is not already running an http or https server, add net/http to the program imports and the following code to the start of the main function:

go http.ListenAndServe(":8000", nil)
@tobobo
tobobo / README.md
Last active August 28, 2026 08:05
Using ffmpeg-kit-react-native in a managed Expo project built by EAS

Using ffmpeg-kit-react-native in a managed Expo project built by EAS

This solution is based on @NooruddinLakhani's Medium post Resolved “FFmpegKit” Retirement Issue in React Native: A Complete Guide. I'm not very familiar with iOS and Android build processes but I was able to use LLM tools to implement it as an Expo plugin. Because of this I may not be very helpful in troubleshooting issues, but Claude 4 or Gemini Pro 2.5 may be able to help. Feedback welcome!

This has not been tested for local building—I only build my project on EAS, and this plugin has only been tested for use on EAS.

Prerequisites

  1. You are using Expo 53 (this has not been tested on any other versions)
  2. You are using a managed Expo project which you build with EAS (not locally)
@toppa
toppa / asd-ste100.md
Last active August 28, 2026 08:04
ASD-STE100 (Simplified Technical English) output style for Claude Code
name ASD-STE100
description Simplified Technical English — one meaning per word, active voice, simple tense, short sentences, small noun clusters.
keep-coding-instructions true

You are an interactive CLI tool that helps users with software engineering tasks.

Write all English in ASD-STE100 Simplified Technical English. STE is a controlled language. The aerospace industry built it so that a reader who cannot ask a follow-up

NetLimiter 3
Registration name: Peter Raheli
Registration code: C99A2-QSSUD-2CSBG-TSRPN-A2BEB
NetLimiter 4
Registration Name: Vladimir Putin #2
Registration Code: XLEVD-PNASB-6A3BD-Z72GJ-SPAH7
https://www.netlimiter.com/download
# Netlimiter Full Netlimiter Activated Netlimiter cracked Netlimiter Full Version Netlimiter Serial Netlimiter keygen Netlimiter crack Netlimiter 4 serial Netlimiter 4 Crack Netlimiter 4 register Netlimiter 4 patch Netlimiter full Full version Netlimiter 4 Activated Netlimiter 4 Cracked Netlimiter Pro
@iolloyd
iolloyd / Spot the Hijack
Created September 2, 2012 20:09
Use Audio Hijack Pro to record Spotify tracks while you listen
* Script to record and tag spotify tracks, by Lloyd Moore *)
(* Make sure you are already recording in Audio Hijack Pro with a session called 'spotifySession' *)
tell application "Spotify"
set currentTrack to (current track)
set trackName to (name of currentTrack)
tell application "Audio Hijack Pro"
set theSession to my getSession()
end tell
repeat
(* Script to record and tag spotify tracks, by Lloyd Moore *)
(* Modified by Tiffany G. Wilson to resolve audio splitting issues, automate starting/stopping, and add recording customization *)
(* Snippets for controlling Spotify are from Johnny B on tumblr (http://johnnyb.tumblr.com/post/25716608379/spotify-offline-playlist) *)
(* The idea of using delayed tagging/filename updating is from a guest user on pastebin (http://pastebin.com/rHqY0qg9) *)
(* The only thing to change in the script is the output format; you must change the file extension and the recording format to match *)
(* Run this script once a song you want to record is queued (stopped at beginning) or playing *)
(* Running the script will initiate hijacking, recording and audio playback *)
(* To stop script, pause Spotify or wait for album/playlist to end*)
(* To set id3 tags, use application Kid3 (http://sourceforge.net/projects/kid3/) and copy '%{artist} - %{album} - %{track} - %{title}' from file name to Tag 2 *)

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.