I've been using Inkdrop for the last 2 years. Kuku gives me a much better experience when editing markdown files. Love the AI integration and horizontal tabs at the top when working within multiple files. First experience is great so far.
Would love to get some reassurance on security and privacy as I add a lot of private information into my notes apps.
kuku
PicWish
@bigmacfive how does the memory handling compare to obsidian's smart connections plugin or official copilot?
@bigmacfive How does it ensure your personal notes stay truly private and local when feeding context to external AI, without any cloud leakage?
Product Hunt
kuku
@curiouskitty It works best today for structure-heavy edits: summaries, heading cleanup, wikilinks, splitting messy notes, and turning raw notes into reusable context.
It still struggles with personal nuance and deciding what should be remembered.
That’s why we use reviewable diffs — AI suggests, you stay in control.
kuku
@curiouskitty I also think the reviewable part is really important here.
AI is already quite good at general cleanup and writing tasks, but adapting to each person’s own writing habits, structure, and tone still needs a lot of improvement.
That’s why we’re focusing on a flow where AI suggests first, and the user reviews before applying. We’re actively improving this, so any feedback from real usage would be greatly appreciated.
Local-first + plain markdown is the only second-brain shape that survives long-term — closed note apps eventually break trust on either lock-in or pricing, and the migration cost on a 5-year vault is brutal. The portable-memory framing is what most AI-note tools miss; they treat notes as in-app data instead of files you own. I run a podcast (https://open.spotify.com/show/0m1oR8AyQv17DVpc5MmirG) on financial modelling and the listener-feedback I get most is exactly this: "where do I keep the takeaways?" — audio doesn't fold into a closed notes app cleanly, but plain markdown with backlinks does. Curious how Kuku handles AI-edits on existing files: do diffs apply per-paragraph or per-file, and is there a way to reject just one chunk of a multi-edit suggestion?
kuku
@samir_asadov
Thanks for the thoughtful question.
Right now, Kuku shows AI edits in a file-diff style, but you can still preview the actual changes in detail — whether that’s a line, a phrase, or a paragraph. The important part for us is that users can clearly review what will change in the real file before applying it.
At the moment, the flow is closer to approving the full suggestion. If something feels off, the user can ask the AI to revise it again.
That said, the idea of accepting or rejecting specific chunks inside a multi-edit suggestion is a really good one. More precise control is definitely important for AI editing, so we’ll take that as a strong improvement direction.
congrats on the relaunch. the tauri + local-first call is the right one, electron-based note apps always feel like they're fighting the OS. the cursor-style diffs for AI edits is the part that sells it for me, "AI suggests, u review" is way better than the yolo-edit pattern most tools ship with.
curious where ur memory layer goes from here, is the plan to expose it as a context source other AI tools can read from, or keep it inside kuku?
kuku
@saad_el_gueddari
Thank you, really appreciate it.
And yes, that’s exactly the direction. We don’t want the memory layer to stay trapped inside Kuku. The goal is for Kuku to become an open, local-first context source that other AI tools can read from, while the user stays in control of what gets exposed.
Kuku starts as the place where your Markdown vault, wikilinks, graph, search, and AI edits live. But longer term, we want it to work more like a portable memory layer: local API, MCP-style bridges, self-hostable sync, and permissioned access for different agents/tools.
So the principle is: your memory lives with you, Kuku organizes it, and AI tools can use it only when you allow them to.
kuku
@saad_el_gueddari
From the implementation side, I also think the memory layer loses a lot of value if it stays locked inside Kuku. We wanted the memory format to be easy for humans to read, easy for AI to understand, and simple enough to edit from other tools.
That’s one of the main reasons we chose Markdown as the base format. Even for memory, we want to keep it as close as possible to Markdown or plain text, rather than hiding it behind a closed internal format.
The core idea is that your knowledge and context should not be trapped in a single app. Kuku should organize and connect it, but the user should ultimately own and control it as an AI context layer.
How do you handle sync between devices if it’s local first, like is there a recommended setup with Git?
kuku
@othman_katim
Great question. We already have an E2EE sync layer in place, but I’d still consider it alpha, so I don’t want to oversell it yet.
If you’re comfortable with Git, setting up a Git repo per vault is a really good approach. Since your notes are local Markdown files, you can sync them across devices, keep history, and handle changes in a way that feels familiar to developers.
One small recommendation: add the .kuku folder to your .gitignore, since it may contain local indexing/cache data that doesn’t need to be synced.
Local-first is the right call for a second brain cloud sync always feels like a liability for personal notes. Does it handle multiple AI models or is it locked to one?
kuku
@imad_elkhafi
Totally agree. For personal notes and a second brain, local-first feels like the right default.
On the AI side, we’re trying to avoid being tightly locked to a single model. The idea is to keep your Markdown vault and memory/context layer local, then let different models or tools connect on top of it when needed.
We’re still early and expanding the supported flow, but the principle is: your notes and memory should belong to you, and the AI model should be replaceable.
kuku
Hi everyone, I’m one of the developers behind Kuku, mainly working on the core logic and implementation.
We’ve rebuilt a lot of the product from the ground up for this launch, while thinking deeply about how local-first Markdown knowledge management can connect with an AI memory layer.
Kuku is still early, and there’s a lot we want to improve.
Please feel free to share anything. I’d be happy to answer as openly as I can.
We’ll also be shipping frequent updates from here, so please keep an eye on what’s coming next.