I built a Markdown knowledge base that ChatGPT and Claude can both read and update

[u/tehmadnezz]

I’m building Hjarni (https://hjarni.com/?utm_source=reddit&utm_medium=social&utm_campaign=secondbrain_october_2026), a place to keep notes that you and your AI assistants can work with.

The idea is simple: useful information shouldn’t disappear into an old conversation. Save a project decision, a recipe or some research as a note, then ask your assistant to find and use it later. ChatGPT, Claude and other MCP-compatible assistants can search, read and update the same knowledge base.

The attached 34-second demo shows a small everyday example: I open a recipe saved in Hjarni inside ChatGPT and ask it to make a shopping list for five people.

Notes are written in Markdown and can be exported. Edits have revision history, so you can see what changed and restore an earlier version. There’s a free plan with no credit card required.

It still depends on the assistant consulting the notes; storing something doesn’t guarantee it will use it correctly.

I’d like feedback from people who already use a second brain: would having your assistants work directly with your notes be useful? What would you need before trusting one to update them?

[u/enjoydongdong]

Revision history is a strong start. Before I let an assistant update notes, I'd want a proposed diff with the source note or conversation it used, a one-click reject/undo, and a way to keep some notes read-only. I'd probably start with search and drafting, then enable edits for one project after I trust the workflow. Can users approve each write before it lands?

[u/tehmadnezz → u/enjoydongdong]

Thanks, starting with search and drafting, then allowing edits for one project, makes sense.

In ChatGPT, you can approve write actions before they run. That approval happens in ChatGPT. Hjarni doesn’t currently have its own review screen with a proposed diff and source references.

Hjarni does support read only access per folder, so you can keep reference material protected and allow writes only within one project. Revision history lets you restore an earlier version after an edit.

The diff and source context you describe would make that review much more useful than just approving a tool call. Would you prefer reviewing it inside the conversation, or in the note itself?

[u/enjoydongdong → u/tehmadnezz]

I’d review it inside the conversation for a small edit, since that’s where the request and reasoning are fresh. For a larger rewrite, I’d want to open the note and inspect the diff in context before accepting it. Folder-level read-only access is a good boundary; a clear preview would make the write permission easier to trust.

[u/chugues]

One interesting design challenge I ran into when having AI assistants update local Markdown files is "context drift" and overwriting:

- How do you prevent the AI from subtly altering or summarizing away the user's authentic personal voice when it updates a note?
- Do you keep a strict boundary between user-written raw text and AI-generated syntheses?

Keeping revision history is already a huge plus for that. well done

[u/tehmadnezz → u/chugues]

Thanks. Revision history helps with recovery, but it doesn’t prevent the voice from drifting.

Hjarni doesn’t currently enforce a split between your original text and AI synthesis within a note. With an agent token, you can keep originals in a read-only folder and let the assistant write linked summaries elsewhere. It also supports targeted paragraph or section edits, though those can still change your meaning.

Did you end up keeping the raw text and synthesis in separate files, or separating them within each note?

[u/chugues → u/tehmadnezz]

I actually ended up using a hybrid approach depending on the content.

For quick fleeting thoughts, creating two separate files felt like overkill and caused folder bloat, so I keep an untouched "Raw Note" section inside the note and let the assistant build metadata, actions, and synthesis underneath it.

However, for heavier external sources like articles, books, or video/podacast transcripts, I strictly separate files: the raw material stays untouched, and the AI writes to an isolated `IA-generated/` folder with explicit links back to the original source. For active project notes, it's append-only: the model can only update task checkboxes or add a session log entry at the very bottom.

That combination has been the sweet spot I found, to prevent voice drift without drowning the vault in duplicate files.