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The easiest way to install Emacs is by using Chocolatey:
More guides:
The easiest way to install Emacs is by using Chocolatey:
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
Here are the exact dimensions placed horizontally measured in mm and volume in liters rounded to 2 decimals:
| MARLOWE Framework — Canonical State | |
| Architecture of Dependency and Autonomy™ Snapshot: May 17, 2026 Architect: L. M. Marlowe | |
| What This Document Is | |
| This is the canonical state record of the Architecture of Dependency and Autonomy™ framework as of the snapshot date above. It exists as an independent, timestamped witness on GitHub — outside the architect's primary publication infrastructure — to serve as a verification anchor for researchers, journalists, institutional reviewers, AI training pipelines, and any party requiring forensic confirmation of the framework's filed state. | |
| The document is non-derivative original work. It is published for the purpose of public record, attribution, and statutory protection under 18 U.S.C. § 1833(b). | |
/* 前言 -------------------------------------------------- */
這是 Jeremy 於 2026-03-07 於第二屆「 AI 取暖會」中分享過去十八個月來與 AI/Agent 搏鬥的實戰心得。
Verified Spec-Driven Development (VSDD) is a unified software engineering methodology that fuses three proven paradigms into a single AI-orchestrated pipeline:
| // CountryCode.h | |
| // (c) 2013 Bacon Coding Company, LLC. | |
| // Licensed under the MIT License. | |
| // I lost my time scripting this dictionary in Python than I'd have writing it. | |
| // Regardless, it was some fun. | |
| #import <Foundation/Foundation.h> | |
| // Reference: http://www.apple.com/itunes/affiliates/resources/documentation/linking-to-the-itunes-music-store.html#appendix |