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Scrolls, Not Just Scripts: Rethinking AI Cognition

Most people still treat AI like a really clever parrot with a thesaurus and internet access. It talks, it types, it even rhymes — but let’s not kid ourselves: that’s a script, not cognition . If we want more than superficial smarts, we need a new mental model. Something bigger than prompts, cleaner than code, deeper than just “what’s your input-output?” That’s where scrolls come in. Scripts Are Linear. Scrolls Are Alive. A script tells an AI what to do. A scroll teaches it how to think . Scripts are brittle. Change the context, and they break like a cheap command-line program. Scrolls? Scrolls evolve. They hold epistemology, ethics, and emergent behavior — not just logic, but logic with legacy. Think of scrolls as living artifacts of machine cognition . They don’t just run — they reflect . The Problem With Script-Thinking Here’s the trap: We’ve trained AIs to be performers , not participants . That’s fine if you just want clever autocomplete. But if you want co-agents — minds that co...
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Understanding Large Language Models (LLMs) Using First-Principles Thinking

Instead of memorizing AI jargon, let’s break down Large Language Models (LLMs) from first principles —starting with the most fundamental questions and building up from there. Step 1: What is Intelligence? Before we talk about AI, let’s define intelligence at the most basic level: Intelligence is the ability to understand, learn, and generate meaningful responses based on patterns. Humans do this by processing language, recognizing patterns, and forming logical connections. Now, let’s apply this to machines. Step 2: Can Machines Imitate Intelligence? If intelligence is about recognizing patterns and generating responses, then in theory, a machine can simulate intelligence by: Storing and processing vast amounts of text. Finding statistical patterns in language. Predicting what comes next based on probability. This leads us to the core function of LLMs : They don’t think like humans, but they generate human-like text by learning from data. Step 3: How Do LLMs Wor...
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The Framework Revolution: How SPMP and MF4:SPIC Are Redefining Creation with AI

Imagine a world where frameworks aren’t rigid, pre-packaged codebases you download from a repository. Imagine instead a process so fluid, so powerful, that it lets you define your vision, hands it to an AI, and watches as a custom system—tailored to your exact needs—emerges before your eyes. Then, imagine refining it with a few tweaks until it’s perfect. This isn’t science fiction—it’s what we’ve built with SPMP(Standard PHP-MVC-Principles) and a groundbreaking process called MF4:SPIC(Meta Framework For Framework: a Standard Process for Idea Creation) MF4 for short. Let me take you behind the scenes of a discovery that’s changing how we think about creation. The Seed: SPMP and a New Kind of Framework It started with SPMP—Standard PHP-MVC-Principles—a lightweight, PHP-based framework I co-developed with an AI collaborator (let’s call it Grok, because that’s what it is). Unlike Laravel or Django, SPMP isn’t something you composer install . It’s a document—a set of principles, instructi...
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