Mike Cavaliere mcavaliere

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.

Workflow Orchestration

Plan Mode Default

Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
If something goes sideways, STOP and re-plan immediately – don't keep pushing
Use plan mode for verification steps, not just building
Write detailed specs upfront to reduce ambiguity

Subagent Strategy

Raw Notes

These are my unstructured notes from the workshop. Read with caution (they're biased to my own interpretation).

Notes

1,000,000 Julian.com visitors

Part 1: What's your objective for your article?

Part 2: pair it with an objective

Advanced memoization and effects in React

Memoization is a somewhat fraught topic in the React world, meaning that it's easy to go wrong with it, for example, by [making memo() do nothing][memo-pitfall] by passing in children to a component. The general advice is to avoid memoization until the profiler tells you to optimize, but not all use cases are general, and even in the general use case you can find tricky nuances.

Discussing this topic requires some groundwork about the technical terms, and I'm placing these in once place so that it's easy to skim and skip over:

Memoization means caching the output based on the input; in the case of functions, it means caching the return value based on the arguments.
Values and references are unfortunately overloaded terms that can refer to the low-level implementation details of assignments in a language like C++, for example, or to memory

Why using the `children` prop makes `React.memo()` not work

I've recently ran into a pitfall of [React.memo()][memo] that seems generally overlooked; skimming over the top results in Google just finds it mentioned in passing in a [React issue][regit], but not in the [FAQ] or API [overview][react-api], and not in the articles that set out to explain React.memo() (at least the ones I looked at). The issue is specifically that nesting children defeats memoization, unless the children are just plain text. To give a simplified code example:

const Memoized = React.memo(({ children }) => (<div>{children}</div>));
// Won't ever re-render
<Memoized>bar</Memoized>
// Will re-render every time; the memoization does nothing

Change your app.json to base-app.json and untrack the original file in your .gitignore

Then add something like "generateConfig": "rimraf app.json && node generateConfig" to your package.json scripts, and yarn generateConfig && react-native-scripts start to scripts like "start" or any others that may need app.json generated.

Shallow

Real unit test (isolation, no children render)

Simple shallow

Calls:

constructor
render

	const stages = ['production', 'staging', 'development', 'test'] as const;

	type Stage = typeof stages[number];

	function getStage(stages: Stage[]) {
	if (!stages.length) return 'production';

	for (const stage of stages) {
	// if any of the provided stages is production, assume we are in production
	if (stage === 'production') {

	/**
	* Example of running BrowserStacks Appium WikipediaSample test app locally
	* using jest and async/await instead of promise chains.
	*
	* Before running, you should install appium and make sure that all dependencies
	* are met with appium-doctor. Get started at:
	*
	* http://appium.io/docs/en/about-appium/getting-started/?lang=en
	*/

	{
	"presets": ["es2015"],
	"plugins": [
	"add-module-exports"
	],
	}