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Michelle Janosi michellejanosi

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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.

#How to remove your SSH public/private keys, recreate them, and then add your newly created public key to the servers and online services you use.
# Remove existing default SSH keys (Ed25519 and RSA)
rm -f ~/.ssh/id_ed25519* ~/.ssh/id_rsa*
# Generate a new Ed25519 SSH key (recommended)
ssh-keygen -t ed25519 -C "$(whoami)@$(hostname)-$(date -I)"
# Add key to SSH agent with macOS Keychain integration
ssh-add --apple-use-keychain ~/.ssh/id_ed25519

Strings

String.prototype.*

None of the string methods modify this – they always return fresh strings.

  • charAt(pos: number): string ES1

    Returns the character at index pos, as a string (JavaScript does not have a datatype for characters). str[i] is equivalent to str.charAt(i) and more concise (caveat: may not work on old engines).

Advanced JavaScript Learning Resources

This is a list of advanced JavaScript learning resources from people who responded to this [Tweet][13] and this [Tweet][20].

  • [You Don't Know JS][3]

  • [Frontend Masters courses by Kyle Simpson][12]

  • [@mpjme][6]'s [YouTube videos][5]