| \newcommand{\growth}{\color{c1}} | |
| \newcommand{\unitQuantity}{\color{c2}} | |
| \newcommand{\unitInterest}{\color{c3}} | |
| \newcommand{\unitTime}{\color{c4}} | |
| \newcommand{\perfectly}{\color{c5}} | |
| \newcommand{\compounded}{\color{c6}} | |
| $$\growth e | |
| \plain = | |
| \perfectly \lim_{n\to\infty} |
Export all your ChatGPT conversations as JSON + Markdown + HTML + ZIP. Works with ChatGPT Business/Team/Enterprise accounts (including SSO/Okta).
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.
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="utf-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <title>Who are you?</title> | |
| <link rel="preconnect" href="https://fonts.googleapis.com"> | |
| <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin> | |
| <link href="https://fonts.googleapis.com/css2?family=Patrick+Hand&display=swap" rel="stylesheet"> |
NOTICE: I've summarized the perspectives of Octane's and Solid's creators here, for anyone short on time: https://gist.github.com/aleclarson/829c10aa7d287944ef75e1c2a90bef06
I'm a React/Preact/Astro developer with an interest in other renderers. The two that have most caught my eye recently are Octane (from Dominic Gannaway of React Hooks / Svelte / Inferno fame) and Solid 2.
I asked ChatGPT to compare them with its own "Renderer DX Pillars", which I've shared below. This is its gut instinct, with very little hedging:
| Pillar | Winner | Why |
|---|
| name | ASD-STE100 |
|---|---|
| description | Simplified Technical English — one meaning per word, active voice, simple tense, short sentences, small noun clusters. |
| keep-coding-instructions | true |
You are an interactive CLI tool that helps users with software engineering tasks.
Write all English in ASD-STE100 Simplified Technical English. STE is a controlled language. The aerospace industry built it so that a reader who cannot ask a follow-up
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title></title> | |
| <meta charset="utf-8" /> | |
| <script src="Scripts/jquery-1.9.1.min.js"></script> | |
| <link href="Content/bootstrap.min.css" rel="stylesheet" /> | |
| <script src="Scripts/isRockFx.js"></script> | |
| <script> | |
| $(function () { |
