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The Software Factory Playbook — Dex Horthy's 4-gate workflow as a skill

A Claude Code Agent Skill built from Dex Horthy's (HumanLayer) playbook on David Ondrej's podcast.

"Once the model has written thousands of lines of code, it is harder to change. The sessions that generate design docs are context-light — you get the most model intelligence when you do the hard thinking early."

By default, agents build horizontally: all the backend, then all the frontend, then a 2,000-line diff lands in your lap and reviewing it is your problem. This skill flips that. Every decision that matters gets made before the code exists — where changing your mind costs a sentence, not a rewrite.

What it does

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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.

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What would it look like if we just used small tools, everywhere?

Original revision: Sep 6, 2018

Most developers are familiar and proponents of the Unix Philosophy Unix philosophy - Wikipedia particularly, Write programs that do one thing and do it well. In practice though, the tooling just doesn’t exist to build useful network services which follow this approach.

Let’s take a lightweight WebSocket service. In 2018 we’ve no shortage of languages and frameworks - however largely incompatible with each other, to create the service.

I’m most familiar with the Python world so can break out the different frameworks in that world that you could use: twisted, eventlet, gevent, tornado, asyncio, sanic - and even though these use the same base language, using libraries designed to be used with one of these frameworks would likely be difficult to use with another framework. And then there are also a myriad of options with Java, Golang, Erlang, Rust.

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function newCurve = spline3d(curve, dt) 
    % interpote a 3d curve using spline 
    % path 3*x 
    % newPath 3*x
    x = curve(1, :); 
    y = curve(2, :); 
    z = curve(3, :);
    t = cumsum([0;sqrt(diff(x(:)).^2 + diff(y(:)).^2 + diff(z(:)).^2)]); 
    sx = spline(t,x); 
    sy = spline(t,y); 

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"""
The most atomic way to train and inference 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

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Screen sharing on Hyprland (Arch Linux)

Table of contents

• Screen sharing on Hyprland (Arch Linux)
  • Introduction
  • Install PipeWire and friends
  • Install xdg-desktop-portal and friends
    • Option #1: xdg-desktop-portal-hyprland (recommended)
    • Option #2: xdg-desktop-portal-wlr (not recommended)

• Remove other portal implementations

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Mapping Rust Shader to SPIR-V

#[spirv(fragment)]				
pub fn main_fs(output: &mut Vec4) {
 *output = vec4(1.0, 0.0, 0.0, 1.0);
}

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sysctl -w fs.file-max=12000500
sysctl -w fs.nr_open=20000500
ulimit -n 4000000
sysctl -w net.ipv4.tcp_mem='10000000 10000000 10000000'
sysctl -w net.ipv4.tcp_rmem='1024 4096 16384'
sysctl -w net.ipv4.tcp_wmem='1024 4096 16384'
sysctl -w net.core.rmem_max=16384
sysctl -w net.core.wmem_max=16384
wget http://packages.erlang-solutions.com/erlang-solutions_1.0_all.deb
sudo dpkg -i erlang-solutions_1.0_all.deb

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I recently switched over to neovim (see my screenshots at the bottom). Below is my updated config file.

It's currently synchronized with my .vimrc config except for a block of neovim-specific terminal key mappings.

This is still a work in progress (everyone's own config is always a labor of love), but I'm already extremely pleased with how well this is working for me with neovim. While terminal mode isn't enough to make me stop using tmux, it is quite good and I like having it since it simplifies my documentation workflow for yanking terminal output to paste in a markdown buffer.

These days I primarily develop in Go. I'm super thrilled and grateful for fatih/vim-go,

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original = 'ThisIsAStringInCamelCaseWithNumbersLike12And14'

# Convert a CamelCase string to snake_case
snake_case = original.gsub(/([\w^_](?=[A-Z]))|([a-z](?=\d+))/, '\1\2_').downcase

# Convert a snake_case string to CamelCase
camel_case = snake_case.gsub(/^\w|_\w/) { |match| match[-1,1].upcase }

puts snake_case # => "this_is_a_string_in_camel_case_with_numbers_like_12_and_14"
puts camel_case # => "ThisIsAStringInCamelCaseWithNumbersLike12And14"