I've long been interested in "learning how to learn" and have long been annoyed by how I have grown to forget things -- which is not a great sign f...
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Thank you for sharing @matheusmaldaner First time you told me about this project, I was immediately interested. Glad you're sharing it with the community : )
Thank you for the support, I look forward to sharing other projects (:
This is awesome! Sick project
Thank you Jon!
I have not reached this level of Anki Intense, but will stive to 🫡
how’s the legibility on a screen that small? any limitations you faced after?
That is a really good question. A lot of my cards have really long descriptions (I did not follow the "keep it simple" approach, and that is still a bad habit), so I ran into some issues where the app would either (1) crash or (2) display only a small subset of the description when the card was flipped.
Right now I have a little "scrolling" mechanism that you can swipe up and down after flipping the card to check the description in full. You can then tap the screen again to rate the card ("Again", "Easy", "Good", "Hard") by swiping up/down/left/right.
One more limitation is that in order to sync it, the watch talks through your phone, so sometimes I need to open the Garmin app on my phone and try the "resync" on the watch again.
the phone dependency angle is real. i tried doing anki on my phone and the problem is you open the app, do 3 cards, then somehow end up on twitter 20 minutes later. having it on a wrist device removes that entire failure mode. the friction is the feature
Hahah same here, even on my computer I get distracted with email pop-ups so this certainly helps. I have tried Opal and recently played around with a Brick for app blocking, but it is hard when many work-related things require 2FA on my phone. Next side project might be how to move 2FA for my other apps to the watch...
the 2FA on watch idea is actually interesting - TOTP codes would work fine on a small display. would make checking codes way less of a context switch than unlocking your phone
Fascinating
Thank you Ben!
what watch platform did you build this on and how are you handling the card rating input, because that's the part that breaks most wrist based review tools when the screen is small enough that a mis tap changes your rating
Glad to see you posting here 🙌 The wrist flashcard thing is a great idea. What's your daily card review count looking like?
Hi Swift, thank you for the support! I must admit that I spent too much time building the workflow instead of reviewing the cards, so now I am sitting at ~150 unreviewed ones...
Typically I have no more than ~25 cards a day to review + a lot of short of language ones (english vocab and basic German words)
This is the kind of project I love seeing — solving your own problem and shipping something real. The Cloudflare tunnel + Oracle Cloud VM setup for 24/7 availability is scrappy in the best way.
As an indie iOS/watchOS developer, I'm always thinking about what "micro-interactions" work best on wrist-sized screens. Flashcards are a perfect fit — the tap/swipe UI maps naturally to watch gestures.
The Claude integration for notes-to-flashcards is a smart touch. I'm building a Markdown note app for iOS with on-device AI, and auto-generating study cards from notes is something I hadn't considered. Might steal that idea. 😄
Really impressive end-to-end system from Garmin app → FastAPI → Anki → Cloud deployment. The project timeline shows how quickly you can iterate when you're building something you actually use daily.
The architecture evolution here is what makes this fascinating — going from ngrok tunnel to FastAPI + Cloudflare to a 24/7 Oracle VM is basically the classic indie developer infrastructure progression compressed into a few months. I went through a very similar journey when I needed always-on services for a programmatic SEO project (started with my laptop, moved to a VPS, eventually landed on edge functions).
The "bridge" feature between flashcards using an LLM is genuinely brilliant. That's not just spaced repetition anymore — it's knowledge graph construction happening passively while you review. I wonder if you've considered exporting those bridge connections as an Obsidian graph or similar visualization? Seeing which concepts cluster together over time could reveal gaps in your knowledge map that you wouldn't notice from individual cards.
Also, the paginated sync fix for Garmin's memory limits is a good reminder that constrained environments force better engineering. MonkeyC sounds like it has some interesting limitations to work around — do you find the development cycle painful or is the Garmin SDK reasonably developer-friendly?