Discover gists

Predictable Programming

Indeed, the ratio of time spent reading versus writing is well over 10 to 1. We are constantly reading old code as part of the effort to write new code. ... [Therefore,] making it easy to read makes it easier to write.

― Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship

1. Be Obvious

Solve a problem in the most simple and obvious way as possible.

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.

Workflow Orchestration

1. Plan Node Default

Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
If something goes sideways, STOP and re-plan immediately - don't keep pushing
Use plan mode for verification steps, not just building
Write detailed specs upfront to reduce ambiguity

2. Subagent Strategy

Use subagents liberally to keep main context window clean

Step by step guide: How to install Microsoft Office in any Linux distribution

There are multiple options how to install MS Office on Linux.

VM-based - Integrate Windows apps running in a Windows virtual machine as native-looking in Linux

LinOffice - Microsoft Office Launcher for Linux, my own fork of Winapps which is focused on only running Microsoft Office, with some Office-specific improvements over Winapps and a fully automated setup. Eventually I would like to create a GUI for it. Decribed below
Winapps, based on KVM, QEMU, Docker/Podman and FreeRDP. Still actively maintained (getting Github commits). Decribed below
Cassowary, based on KVM, QEMU, libvirt/virt-manager, and FreeRDP. Last release in Feb 2022 and seems to be abandoned.

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	# FFmpeg / iOS Video Taming

	## General Options:

	# These settings may be applied to both the INPUT and the OUTPUT
	# of the FFmpeg command.

	-r 30 # set the frame rate of the video to Apple's recommended 30 fps

	-pix_fmt yuv420p # set the output video's pixel format

	#EXTM3U
	#EXTINF:-1,www.techedubyte.com
	Https:www.techedubyte.com
	#EXTINF:-1,BEIN_Sports_News
	http://server.sibfungold.info:8080/pacha-man1/e0VaVPskUa/2296
	#EXTINF:-1,BeIN_Sport_NBA_HD
	http://server.sibfungold.info:8080/pacha-man1/e0VaVPskUa/49691
	#EXTINF:-1,AR: Al KASS 1 HD
	http://server.sibfungold.info:8080/pacha-man1/e0VaVPskUa/1138
	#EXTINF:-1,AR: Al KASS 2 HD

	pacman
	======

	view logs: /var/log/pacman.log

	update system
	# pacman -Syu

	list installed packages
	# pacman -Q