Bill Crook billcrook

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.

PostgreSQL is Enough

See the new site: https://postgresisenough.dev

Postgres blogs

(Persons are alphabeticaly sorted by family name, the rest is sorted by name.)

Personal

⚠️ WARNING
The ordering of listed projects or documents is random and has no connection to relevance or maturity levels!

Postgres

Extensions

Extension	Description
`pgaudit`	Postgres auditing extension

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

Effective Engineer - Notes

By Edmond Lau
Highly Recommended 👍
http://www.theeffectiveengineer.com/

What's an Effective Engineer?

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

General Background and Overview

Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

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	#!groovy
	# Best of Jenkinsfile
	# `Jenkinsfile` is a groovy script DSL for defining CI/CD workflows for Jenkins
	node {
	}

	class PostgreSQLConnection(psycopg2.extensions.connection):
	"""
	A custom `connection_factory` for :func:`psycopg2.connect`.

	This
	* puts the connection into unicode mode (for text)
	* modifies the :meth:`cursor` method of a :class:`psycopg2.connection`,
	facilitating easy acquiring of cursors made from
	:cls:`psycopg2.extras.RealDictCursor`.
	"""