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  • Luo Fuli Podcast: “OpenClaw, Agent Frameworks — The AI Paradigm Has Already Changed Dramatically”

    Thinkmasters Editorial
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    Analysed through DIE-system-prompt-v1.0 | program.md v1.3 Source: YouTube transcript, audio62a.txt + audio62a_tail.txtSubject: Luo Fuli (罗弗莉), Head of Large Models, XiaomiContext: Post-OpenClaw release, post-MemoV2 series (Pro, Omni, TTS)DIE PI: r4all | Analysis date: 14 May 2026Provenance: github.com/dbtcs1/die-framework | Zenodo DOI 10.5281/zenodo.19888889 SNAPSHOT PROTOCOL — SS1 → SS2 → DELTA SS1: What the prevailing paradigm believed before…

  • Entry L002: GENIUS Act × Saylor × Bitcoin Store of Value

    Thinkmasters Editorial
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    A Dimensional Analysis — DIE Framework Applied to Regulatory Macro 13 May 2026 | thinkmasters.com/die-framework | Follows Entry L001 (Jeff Booth Podcast) Entry Log ContextL001: Booth × Bitcoin/AI Deflationary Future (macro/protocol layer)L002: GENIUS Act × Saylor STRC play × Bitcoin store of value (regulatory/capital layer)Corpus accumulates. Output improves. This is C1 in real time. PART…

  • Entry L001: Booth × DIE Framework: Bitcoin, AI, and the Deflationary Future

    Thinkmasters Editorial
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    A Dimensional Analysis of “Build with Bitcoin” Episode 100 Published: 12 May 2026 | Author: r4all / thinkmasters.com This document serves two functions: (1) a substantive analysis of Jeff Booth’s macro thesis through the DIE Framework lens, and (2) a live stress-test of the DIE-system-prompt-v1.md as a portable evaluation layer. Both are documented for the…

  • The Platform Built Your Framework. Without Knowing It

    Thinkmasters Editorial
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    A DIE Stress Test Against Claude Sonnet 4.6 — and What It Found Anthropic spent billions building a memory system, a retrieval layer, and a tiered forgetting protocol. They didn’t call it that. They called it Claude. This post is a structured stress test — running the DIE Dimensional Evaluation Protocol against the Claude platform…

  • The $75M Amnesia Machine — And What DIE Does Differently

    Thinkmasters Editorial
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    What a Frontier LLM Actually Is Strip away the hype. A large language model is four numbers in a trench coat. Tokens. The raw material. One token ≈ 3–4 letters. “Tokenizer” becomes two tokens: token + izer. LLaMA 3 was trained on 15.6 trillion of them — the rough equivalent of every book, webpage, and…

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