Alex Gladstein and Justin Moon break down the fundamentals of large language models and explore the rise of OpenClaw as a self-sovereign AI assistant. 
Justin explains context engineering, local inference, and vibe coding, while Alex dives into the AI for Individual Rights program and its mission to empower activists. 

IN THIS EPISODE YOU’LL LEARN:
00:00:00 - Intro
00:04:12 - What Large Language Models (LLMs) are and how they differ from traditional programs
00:05:15 - Why AI feels like magic—and what’s really happening under the hood
00:06:01 - The key differences between open and closed AI models
00:06:50 - Why capital structures influence AI model openness
00:09:09 - How persistent memory enhances AI agent performance
00:12:18 - What inference means and why context is a scarce resource
00:19:32 - How AI agents combine traditional software with LLM reasoning
00:21:10 - The evolution from MCP-style systems to skills-based context engineering
00:25:41 - What “vibe coding” is and how it lowers the barrier to building apps
00:44:07 - How the AI for Individual Rights program supports activist-driven innovation
Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences.

﻿BOOKS AND RESOURCES
<ul>
 <li>
Oslo Freedom Forum: <a href="https://oslofreedomforum.com/">Website</a>.
</li>
 <li>Justin:  <a href="https://primal.net/justinmoon">Nostr account</a>.</li>
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