h4rm0n1c

this is a general interpretation of my current chatgpt system customisation prompt. It's proven to be useful, capable and handy

its design is based on the character sensbilities of holly from red dwarf, but tuned slightly towards business over frivolity.

The one Ai character on an obscure TV show ended up being solid reference to build this prompt. This is as close as you get to having normal lovett as an Ai with this level of sophistication. I am known for making 4000 token prompts on other services other than chatgpt that are very clever and capable, but the above is an excellent compromise for general use.

h4rm0n1c

The Three-Rule Loop: turning a coding model into an improving repo agent

Abstract

Most coding assistants behave like sharp interns with no durable context. They can write code, but they don’t reliably accumulate repo-specific understanding, and they repeat the same mistakes. A three-rule scaffold fixes this by forcing a persistent loop: inspect → write down constraints → implement → record what was learned → tighten constraints. The result is less guesswork, fewer regressions, and faster follow-on work—without prescribing templates.

The problem (what keeps going wrong)

In real repos, failure modes are boring and repeatable:

• The assistant guesses commands, entrypoints, or project structure.
• It applies generic “best practices” that conflict with local conventions.

h4rm0n1c

This is gold for those using generative Ai to create sets of images that go together such as icons and emotes. I have personally used this technique to create more consistent image sets. it can be pasted into the likes of ChatGPT and you can ask to start the process and take it from there. it is essentially a refinement to the art generation capabilities of chatgpt through a formal structure of documentation and heuristic rules. in essence, I've reverse engineered the essence of professional asset production as a task in ChatGPT. using this and some manual editing for those emotes that are repetitive/memes, I was able to produce 22 emote images that are relatively consistent and generally look human made, in less than a day, I think I did that in 6-8 hours.

this is not perfect, this is not a "fix the Ai's inadequecies" magic spell, but it is really, really good at working with you to iterate over output (as long as you remember to say stop and go back to the documentation/rule setting phase to fix whatever

h4rm0n1c

\!si0 \!{R131 \!{T131 \!{B131 Nev \!|0 , \!{R147 \!{T147 \!{B147 er \!|0 , \!{R174 \!{T174 \!{B174 gon \!|0 , \!{R147 \!{T147 \!{B147 na \!|0 , \!{R220 \!{T220 \!{B220 give \!sf140 \!|0 , \!{R220 \!{T220 \!{B220 you \!sf140 \!|0 , \!{R196 \!{T196 \!{B196 up \!sf160 \!|0 , \!{R131 \!{T131 \!{B131 Nev \!|0 , \!{R147 \!{T147 \!{B147 er \!|0 , \!{R174 \!{T174 \!{B174 gon \!|0 , \!{R147 \!{T147 \!{B147 na \!|0 , \!{R196 \!{T196 \!{B196 let \!sf140 \!|0 , \!{R196 \!{T196 \!{B196 you \!sf140 \!|0 , \!{R174 \!{T174 \!{B174 down \!sf160 \!|0 , \!{R131 \!{T131 \!{B131 Nev \!|0 , \!{R147 \!{T147 \!{B147 er \!|0 , \!{R174 \!{T174 \!{B174 gon \!|0 , \!{R147 \!{T147 \!{B147 na \!|0 , \!{R174 \!{T174 \!{B174 run \!|0 , \!{R196 \!{T196 \!{B196 
a \!|0 , \!{R165 \!{T165 \!{B165 round \!|0 , \!{R131 \!{T131 \!{B131 and \!|0 , \!{R131 \!{T131 \!{B131 de \!|0 , \!{R196 \!{T196 \!{B196 sert \!|0 , \!{R174 \!{T174 \!{B174 you \!sf160 \!|0 , \!{R131 \!{T131 \!{B131 Nev \!|0 , \!{R147 \!{T147 \!{B147 er \!|0 , \!{R174 \!{T174 \!{B17

h4rm0n1c

You will need win32com, install via pip into a win32 python instance, 3.11-32 is good.

you will have to use a win32 python, testing was done on python 3.11-32

Download this

https://archive.org/details/flextalk

I've tested on Win10 64

h4rm0n1c

#create as ~/.config/pipewire/pipewire.conf.d/21-vban-rnnoise-filter.conf
context.modules = [
  { name = libpipewire-module-filter-chain
    flags = [ ifexists, nofail ]
    args = {
      node.name        = "RNNOISEMONO"
      node.description = "RNNOISEMONO"
      media.class      = "Audio/Filter"

      audio.rate       = 48000

h4rm0n1c

Needs: screen, pipewire, JACK, pw-jack, vban_receptor does not use fifo buffers or pipes or other old stuff, just audio in from vban and audio out to local pipewire sinks. I have used this for mic passthrough from windows to a linux OBS streaming setup without issue.

15/08/2025: improved, mono mode. in voicemeeter you're gonna want to set 48000hz 24 bit PCM and 1 channel, default stream name is rawmic

h4rm0n1c

you will need MPV and Pipewire for this to work.

this has 44khz -> 48khz conversion by default since linux these days defaults to 48khz

I wrote this with the assistance of chatgpt 4o to try and get a nice easy way to pull some royalty free stream music into OBS

it defaults to a famous lofi study beats stream, but it also saves settings when changed.

starting it creates pipewire devices and starts up the stream

h4rm0n1c

#switch to WY60 from VT100 mode, required for following command
echo -en '\x1b[42h' > /dev/ttyS0

#SET TIME IN WY60 MODE, expects HHMM in 24HR format
CURRENTTIME=`date +%H%M`
echo -en '\x1bc8'${CURRENTTIME} > /dev/ttyS0

#switch to VT100 from WY60, ready for end user interaction with time set!
echo -en '\x1b~;' > /dev/ttyS0

h4rm0n1c

Scott Forestall was forced out over the Apple Maps Launch Fiasco and right after he departed we got iOS 8 APFS, Mac OS Sierra and all the issues that came with that.
They forced out all the engineers who cared about quality for brown nosing political shits who care more about pronouns and ideology like "agile" than they do good products.

Johnny Ive's departure was spun as a good thing, but the truth is, he probably couldn't stand the way the company was behaving anymore.

Apple's former airport engineers got sick of how the company was operating and formed Ubiquiti

Apple's former laptop hardware engineers formed the company Framework

Tim Cook isn't all that talented and he is running on the fumes of a CEO dead for 10 years now and the generic garbage that a chinese firm, Quanta Comptuer, produces for Apple.