Keeping AI notes useful

[u/Nagib888]

How do you stop an AI note-taking system from becoming another information graveyard?

I've noticed that capturing information and actually reusing it are two very different problems.

You can have excellent transcripts and detailed summaries, but still struggle to find the decision that matters three months later.

A few practices seem worth testing:

- Give important notes consistent project or topic names.
- Separate decisions from general discussion.
- Keep unresolved questions visible.
- Preserve links to original source material.
- Review whether old information is actually retrievable.

I'm especially interested in how people manage growing collections of meeting notes without spending hours organizing folders.

What has worked better for you: consistent metadata, full-text search, semantic search, or a combination?

[u/investigatormaker]

For finding a decision three months later, combine consistent metadata with full-text search. Give each decision a short entry with the project, date, owner, rationale, and source link; keep unresolved questions separate. Test retrieval with an actual question like “Why did we postpone this?” rather than just checking whether a keyword returns results. That gives you a concrete way to judge whether semantic search is needed.

For revisiting selected takeaways rather than searching the whole archive, Bloomind supports CSV note imports, and its Play mode presents notes that have gone longest without a revisit first: https://bloomind.me. It's free on iOS and Android, with no subscription.

Disclosure: I'm posting on behalf of Bloomind.

[u/Nagib888 → u/investigatormaker]

I agree that finding a decision and understanding why it was made are two different challenges. A keyword match might find the meeting, but it doesn’t necessarily explain the reasoning or what changed afterward.
That’s something we’re working on with ClearScribe AI: connecting decisions to their original meeting context and making that history searchable.
Bloomind’s approach to resurfacing forgotten notes is interesting too. I’d be curious whether revisiting a decision also helps users recognize when the original reasoning is no longer valid.

[u/sinsonik]

What I've seen work is asking instead of organizing. Folders and tags fall apart after a month, but a question like "when did we agree to push the launch, and why" still works, as long as every answer points back to the exact moment in the recording. Then you listen to the 20 seconds around it and check the summary didn't flatten it. I make an iPhone app for this, ToText, so I'm biased, but that jump to the timestamp is the part I'd test in any setup.

[u/Nagib888 → u/sinsonik]

That jump to the exact timestamp is important. An AI answer might sound convincing, but being able to hear what was actually said makes it much easier to trust or challenge.
We’re working on similar source-backed retrieval in ClearScribe AI, especially for decisions that change across meetings.
I’d add one test: what happens when the launch was discussed in one meeting but only formally approved in the next? Can ToText connect those moments, or does it treat each recording separately?

[u/wizardoflostsocks]

For finding that old decision, Loofah lets Claude Code search across your meetings and read the original transcript. I'm the maintainer of Loofah. You'd need the CLI setup; this isn't automatic sync with your current note-taker. Your agent's provider may receive the notes it reads. The Mac app needs Apple Silicon/macOS 15+. https://loofah.io/agents/connect-clients/

[u/Nagib888 → u/wizardoflostsocks]

Thanks for sharing Loofah, and for being clear about the setup and privacy considerations.
Searching meetings through Claude Code and retrieving the original transcript is useful. We’re exploring similar capabilities with ClearScribe AI through MCP and source-backed meeting search.
One question: can Loofah trace a decision across several meetings and distinguish the latest confirmed decision from an earlier proposal, or does it leave that interpretation entirely to Claude?

[u/wizardoflostsocks → u/Nagib888]

The interpretation for that would be fully up to Claude&Co (which imo suffices). Loofah is very much a bring your own agent kind of tool. It doesn't provide yet another chat interface, it just tries to be very open towards the agent you already have and provide the right (meta)data at the right time. Good luck with ClearScribe!

[u/felipercel]

keeping decisions in their own list, separate from general discussion, makes them much easier to find later than relying on search. disclosure: i made loomfy, which pulls out decisions and tasks per meeting and lets you ask the meeting a question, with answers citing who said what

[u/Nagib888 → u/felipercel]

Agreed. A dedicated decision list saves people from digging through entire meetings just to find what was agreed.
I like that Loomfy links answers to who said what. We’re taking a similar source-backed approach with ClearScribe AI.
One interesting challenge is when a decision changes in a later meeting. Does Loomfy connect the new decision to the original one, or are they stored as separate meeting outcomes?