Replies: 8 comments 9 replies
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Is there a reason to add LLM's into memos? Like if there's a reason behind it sure but it seems to just be adding LLM for LLM's sake, no? |
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Related memo suggestions and summaries can be wasteful in many instances. It would need caching and extra knobs to keep token usage under control. |
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AI-powered auto-tags are a great idea—I really like that. And I’d also love it if AI could be leveraged further, for example, to improve the structure of the notes we write so they’re neater, clearer, and conform to the required Markdown structure. Of course, this would be a feature that can be turned on or off—it’s optional—and users would need to click a “button” to initiate the refinement process and set up their own AI API key to make it work. |
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Speaking for myself only, I would prefer no A.I. features. In my opinion A.I. is unreliable, a privacy problem, and I wouldn't want it anywhere near my private data. If you do decide to add A.I. features, please also add the ability to completely disable them. |
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Personally I don't want AI powered tags because I don't want Memos to become a dump of things. I have Karakeep for that and Karakeep is using AI Tags, they just become dump tags. One thing that I did was createa n8n workflow that captures my "Past Month" memos, summarize each memos per tag, then create a MD file with them. Basically I have a #nas where I write all the things I did on my NAS. This will take all my NAS notes and summarize them. And he does that for each tag, monthly. Memos -> Ollama model -> MD File -> Post into Memos that I have a new summary -> ntfy push to my phone (my current flow) |
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If AI is added to Memos, I would keep it opt-in, local-first where possible, and focused on capture/retrieval rather than turning the app into a general AI workspace. The safest first features are probably:
For privacy, the important controls are: per-workspace AI enable/disable, per-memo exclusion, provider selection, clear indication when content leaves the device, and user-editable derived artifacts. Auto-tags and summaries should be stored as suggestions or metadata with provenance, not silently mixed into the original note. A useful research/knowledge-work flow would be bilingual or multilingual note discovery: users capture rough notes in one language, then retrieve related memos across languages without needing to manually normalize every tag. That is practical, but still narrow enough to fit the lightweight nature of Memos. |
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Instead of adding AI features, can we get multi-workspace support? I'd love to be able to share this with groups of my friends, but it seems like sharing is an all or nothing approach at the moment, and it prevents me from actually sharing this with people. |
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Notes fully organized and logged by AI tend to turn our notebooks into disorganized clutter. Content churned out without our own critical reflection rarely delivers meaningful value. |
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We’ve been thinking about AI features for Memos, but want to keep it fast, lightweight, and focused.
If AI were added, what would actually help you capture or revisit thoughts better?
Examples:
We’re especially interested in ideas that improve quick capture, without turning Memos into a heavy AI workspace.
Share your use case if possible — that helps us prioritize.
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