Michael Ramos backnotprop

lnr Work Management System

Overview

lnr is an append-only, file-based lnr work management system designed for AI coding agents. Lnr work is organized into phases - coherent units of effort that match how AI agents naturally operate. The system requires no indices, no status tracking, and no complex tooling. State is derived entirely from which files exist in the directory.

Core Principles

Lnr work happens in phases, not issues or tickets. Each phase represents a coherent push toward a specific goal. Phases can be small (refactor a function) or large (implement authentication system).

Looking for a solution to my below game problem. I believe it to require some sort of reinforcement learning, dynamic programming, or probabilistic programming solution, but am unsure... This is my original problem, and is part of an initiative to create "unique and challenging problem that you're able to conceptualize and then solve. 3 Judging criteria: uniqueness, complexity, and solution (no particular weighting and scoring may favor uniqueness/challenge over solution"

Inspirations: Conway's Game of Life, DeepMind's Starcraft Challenge, deep Q-learning, probabilistic programming

BEAR SURVIVAL

A bear is preparing for hibernation. A bear must reach life-strength 1000 in order to rest & survive the winter. A bear starts off at a health of 500. A bear explores an environment of magic berries. A bear makes a move (chosen randomly with no optional direction) and comes across a berry each time. There are 100 different types of berries that all appear across the wilderness equally and

Read data from a public bucket using gzip compression.

First bit of code opens a bucket and lists contents.

Next reads a gzip json file and deserializes it to an array. Please note not very efficient for a large array since the byte array is loaded into memory.

package main

import (
	"compress/gzip"

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

	#!/bin/bash

	HOSTFS="/mnt/hostfs"

	function sleep_forever() {
	while true; do sleep 100; done
	}

	function setup_kubectl() {
	# Setup kubectl

	---
	apiVersion: extensions/v1beta1
	kind: DaemonSet
	metadata:
	namespace: kube-system
	name: node-custom-setup
	labels:
	k8s-app: node-custom-setup
	annotations:
	command: &cmd apt-get update -qy && apt-get install -qy tgt ceph-fs-common ceph-common xfsprogs

	let regex = `import
	(?:
	["'\s]*
	([\w*{}\n, ]+)
	from\s*
	)?
	["'\s]*
	([@\w/_-]+)
	["'\s]*
	;?