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LLM Wiki

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.

The core idea

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.

Verified Spec-Driven Development (VSDD)

The Fusion: VDD × TDD × SDD for AI-Native Engineering

Overview

Verified Spec-Driven Development (VSDD) is a unified software engineering methodology that fuses three proven paradigms into a single AI-orchestrated pipeline:

Spec-Driven Development (SDD): Define the contract before writing a single line of implementation. Specs are the source of truth.
Test-Driven Development (TDD): Tests are written before code. Red → Green → Refactor. No code exists without a failing test that demanded it.

When to Use Each Version

claudette-mimir.md ⭐ NEW!!!

✅ Full integration with NornicDB's memory bank
✅ Graph functions enable multi-hop reasoning

CLICK HERE-> Claudette NornicDB

NornicDB Memory Bank

🗺🐘 1000+ PostgreSQL EXTENSIONs

This is a list of URLs to PostgreSQL EXTENSION repos, listed in alphabetical order of parent repo, with active forks listed under each parent.

⭐️ >= 10 stars
⭐️⭐️ >= 100 stars
⭐️⭐️⭐️ >= 1000 stars
Numbers of stars might not be up-to-date.

Comparative Benchmark Numbers @ Rackspace

I've taken the benchmarks from Matthew Rothenberg's phoenix-showdown, updated Phoenix to 0.13.1 and ran the tests on the most powerful machines available at Rackspace.

Results

Framework	Throughput (req/s)	Latency (ms)	Consistency (σ ms)

Specification

Out Of The Tarpit

BOOM Analytics: Exploring Data-Centric, Declarative Programming for the Cloud

Dedalus: Datalog in Time and Space

Logic and Lattices for Distributed Programming

303 See Other

Location: https://github.com/wsargent/docker-cheat-sheet

Hi there!

The docker cheat sheet has moved to a Github project under https://github.com/wsargent/docker-cheat-sheet.

Please click on the link above to go to the cheat sheet.

docker.sh: a small interactive shell hack for docker

Usage: ./docker.sh [base-image-name]

Demo: https://asciinema.org/a/5011

	autodock:
	image: prologic/autodock
	ports:
	- "1338:1338/udp"
	- "1338:1338/tcp"
	volumes:
	- /var/run/docker.sock:/var/run/docker.sock

	autodocklogger:
	image: prologic/autodock-logger

	#!/usr/bin/env perl

	use feature 'switch';
	use strict;
	use warnings;

	use Data::Dumper;
	use File::Basename;
	use File::Copy;
	use File::Path qw/make_path/;