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27
| Visual Studio 2026 18.x | |
| Professional: NVTDK-QB8J9-M28GR-92BPC-BTHXK | |
| Enterprise: VYGRN-WPR22-HG4X3-692BF-QGT2V | |
| Product Year Version Product Keys | |
| Visual Studio 2022 2021 17.x | |
| Professional: TD244-P4NB7-YQ6XK-Y8MMM-YWV2J | |
| Enterprise: VHF9H-NXBBB-638P6-6JHCY-88JWH | |
| Visual Studio 2019 2019 16.x |
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.
Git Worktrees: Multiple working directories pointing to different branches of the same repo
Jujutsu (jj): Fundamentally different VCS with operation log, first-class conflicts, and automatic change tracking
They solve different problems and aren't direct alternatives.
| /* eslint-disable no-undef */ | |
| // Right click on the script name and hit "Run" to execute | |
| const { expect } = require("chai"); | |
| const { ethers } = require("hardhat"); | |
| describe("Storage", function () { | |
| it("initial value", async function () { | |
| const Storage = await ethers.getContractFactory("Storage"); | |
| const storage = await Storage.deploy(); | |
| await storage.deployed(); |
| /* eslint-disable no-undef */ | |
| // Right click on the script name and hit "Run" to execute | |
| const { expect } = require("chai"); | |
| const { ethers } = require("hardhat"); | |
| describe("Storage", function () { | |
| it("initial value", async function () { | |
| const Storage = await ethers.getContractFactory("Storage"); | |
| const storage = await Storage.deploy(); | |
| await storage.deployed(); |
Companion to physics_engine.md
Important
All paths cross-verified against raw IDA decompilation on 2026-02-16. DoJump path ordering was corrected (originally had ladder/foothold swapped). HandleGroundedMovement and ClampToBounds were added (previously missing).