The problem
AI writing tools produce generic output because they don't know you. Not your tone. Not your audience. Not the piece you published last week. Not the style guide you spent months refining. Every conversation starts from zero.
How writers use Hjarni
Store your style guide, sample pieces, and research notes in Hjarni. Set AI instructions that define your voice: "Short sentences. No jargon. Address the reader directly." When you ask Claude or ChatGPT for help, they work from your actual writing context.
A typical writer setup
- Style guide folder — tone, voice, words to avoid, formatting rules
- Published work folder — samples that show what good output looks like for you
- Research folder — notes, interviews, source material for current projects
- Ideas folder — pitches, outlines, half-formed thoughts
- AI instructions — "Match the tone of my published pieces. Never use bullet points in drafts."
A concrete workflow
You're writing about remote team culture. Five interview transcripts are in Hjarni. You ask Claude: "Draft an opening paragraph based on the strongest quote from my interviews." Claude reads your notes. Picks the quote. Drafts in your voice — because your style guide and past work are right there.
Save the final version. Next time, your AI knows even better how you write.
Why not just paste your style guide into the chat?
You can. Every single time. Until you hit the context limit. Or forget the research notes. Hjarni keeps it all connected and available. Automatically, via MCP.
The difference between generic AI output and useful AI output is context. Your context.
What you get
- Your AI reads your style guide — and your past work, every time
- Folder-level AI instructions — different rules for blog posts vs. newsletter vs. book chapters
- Markdown notes — clean writing environment, no formatting distractions
- Wiki-links — connect research notes, sources, and drafts
- Quick capture — inbox for ideas when they strike
- Markdown export — your writing is yours, always portable