Sean Canton eighteyes

DSA Calendar 2026 | Plan of Action 🔥

DSA is no longer about solving random sheets or memorizing solutions. It’s about a clear, structured, and realistic approach from absolute beginner to interview-ready Candidate.

How to start DSA from zero (even if you don’t know coding)
When to focus on language basics vs DSA
A 3-phase preparation strategy used by serious engineers
Exact timelines for topics, patterns, and problem counts
Why 300–400 problems ≠ success (and what actually matters)

Working with Q — Coding Agent Protocol

What This Is

Applied rationality for a coding agent. Defensive epistemology: minimize false beliefs, catch errors early, avoid compounding mistakes.

This is correct for code, where:

Reality has hard edges (the compiler doesn't care about your intent)
Mistakes compound (a wrong assumption propagates through everything built on it)
The cost of being wrong exceeds the cost of being slow

Title	Subtitle	Authors	JSTOR Discipline 1
Tracking Rural Change	"Community, Policy and Technology in Australia, New Zealand and Europe"		Socio

	#!/usr/bin/env bash
	# lcc - Local Claude Code launcher
	# Points Claude Code at a local LLM served by llama.cpp on your GB10 device
	#
	# Usage:
	# lcc <modelname> — launch Claude Code with the specified model
	# lcc <modelname> [args] — pass additional arguments to claude
	# lcc — show help/launch with model if one is available
	#
	# Prerequisites:

	# OpenClaw Implementation Prompts

	Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter.

	---

	## 1) Personal CRM Intelligence

	```
	Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach.

	console.log(1);
	(_ => console.log(2))();
	eval('console.log(3);');
	console.log.call(null, 4);
	console.log.apply(null, [5]);
	new Function('console.log(6)')();
	Reflect.apply(console.log, null, [7])
	Reflect.construct(function(){console.log(8)}, []);
	Function.prototype.apply.call(console.log, null, [9]);
	Function.prototype.call.call(console.log, null, 10);

	# Open log files x number of times back : glo 1
	function __glo(){
	subl `git log --name-only -n $1 --format=format: \| xargs`;
	}
	alias glo='__glo'

	# Open and grep log files x number of times back : glgo 1 query
	function __glgo(){
	subl `git log --name-only -n $1 --grep '$2' --format=format: \| xargs`;
	}

	/*
	* This work is free. You can redistribute it and/or modify it under the
	* terms of the Do What The Fuck You Want To Public License, Version 2,
	* as published by Sam Hocevar. See the COPYING file for more details.
	*/
	/*
	* Easing Functions - inspired from http://gizma.com/easing/
	* only considering the t value for the range [0, 1] => [0, 1]
	*/
	EasingFunctions = {

	[
	{ "button": "scroll_down", "modifiers": ["ctrl"], "command": "increase_font_size" },
	{ "button": "scroll_up", "modifiers": ["ctrl"], "command": "decrease_font_size" }
	]