AskClaude

17 Apr 2026 - 18 Aug 2026
Open in Logseq
    • The other side of this is a small hack to goddinpotty so it renders blocks tagged with #AskClaude in a distinctive way (hover boxes) like this Ask Claude
      • Here are some common patterns for integrating personal writing with LLMs:
      • As input/context
      • Feeding journals or notes to get summaries, patterns, or questions surfaced
      • Using personal writing as style examples for the LLM to match
      • PKM tools like Obsidian with plugins that send note context to LLMs (Smart Connections, etc.)
      • As dialogue
      • What you're doing here - embedding questions in notes, getting responses inline
      • Roam Research's native AI features work similarly
      • Some people maintain a "conversation log" note that they iteratively extend
      • As processing pipeline
      • Running writing through LLMs to extract entities, tags, links automatically
      • Using LLMs to generate "MOC" (maps of content) from a corpus of notes
      • Readwise Reader and similar tools summarizing highlights in your voice
      • As writing partner
      • Logseq has some of this - send a block or page as context
      • People paste drafts and ask for Socratic questioning rather than edits
      • "Rubber duck" use - explaining thinking to the LLM to clarify it for yourself
      • The interesting design question your hack raises is about persistence and visibility - the question stays in the document, the answer is retrievable but non-intrusive (hover). Most integrations treat LLM interaction as ephemeral. Keeping it annotated in the source doc is a different philosophy.
      • What's the goddinpotty stack?
      what are some other ways people integrate their own writing with LLMs? Ask Claude
      • Here are some common patterns for integrating personal writing with LLMs:
      • As input/context
      • Feeding journals or notes to get summaries, patterns, or questions surfaced
      • Using personal writing as style examples for the LLM to match
      • PKM tools like Obsidian with plugins that send note context to LLMs (Smart Connections, etc.)
      • As dialogue
      • What you're doing here - embedding questions in notes, getting responses inline
      • Roam Research's native AI features work similarly
      • Some people maintain a "conversation log" note that they iteratively extend
      • As processing pipeline
      • Running writing through LLMs to extract entities, tags, links automatically
      • Using LLMs to generate "MOC" (maps of content) from a corpus of notes
      • Readwise Reader and similar tools summarizing highlights in your voice
      • As writing partner
      • Logseq has some of this - send a block or page as context
      • People paste drafts and ask for Socratic questioning rather than edits
      • "Rubber duck" use - explaining thinking to the LLM to clarify it for yourself
      • The interesting design question your hack raises is about persistence and visibility - the question stays in the document, the answer is retrievable but non-intrusive (hover). Most integrations treat LLM interaction as ephemeral. Keeping it annotated in the source doc is a different philosophy.
      • What's the goddinpotty stack?
    • Bugs/issues/TODOs

      • Three separate commands, but it isn't obvious what they do (would be nice if difficult to visually show which text is used for prompt)
      • Bug, probably a pain to fix, where the command deletes recent text. Workaround: always issue the command in a sub-block
      • TODO goddinpotty rendering of Claude-gen text
      • IDEA Emacs version (for md and/or org)
    • Meta-level ruminations

      • Obviously this does nothing but slightly smoothe the processs of having AI written texts connect to my own.
        • Which sounds weird, because everyone is doing this and most people I guess do not care, they will mix their woice and the AI voice freely, whatever works.