This is great. I often want a low-latency, minimal-feeling option for this sort of thing. (And I get to use my Vim muscle memory less and less often these days!)
Really, thanks for making and sharing this; so far, I feel calm and happy when I'm using it.
I don't think LLMs push us to use microservices as much as Borgers says they do. They don't avoid the problems microservices have always faced, and encapsulation is mostly independent from whether a boundary is a service-to-service boundary:
I don't exactly think I have an algorithm better than FSRS yet, but I have an algorithm I like better. Hopefully I'll have more to say about this soon.
Oops! I haven’t read the guidelines in a while, and for a long time I only lurked. Thanks for setting me straight. I’m accustomed to forums where there’s no problem with posting your own stuff. Obviously I’ll correct my behavior. Thanks again!
At this point there's just a reflex I have that says "ah, I'd like to remember that." It's the same feeling whether I'm learning something for trivia, for work, or for personal reasons.
See my other comments here for some of my motivations, but also:
Even in the Internet age, getting the latency from "fast" to "effectively zero" has a lot of value for staying in flow, synethesizing information, etc. Your memory is the ultra-low-latency fact retrieval system you always have. No, you definitely don't want to use it for everything, but it definitely does complement modern tools in important ways.
1. As others have said, the idea is to study something before you forget.
2. It's hard to predict when you're going to forget something, so you do wind up studying a bunch of stuff before you really have to. It's a limitation of prediction (and also of the technology as developed so far).
3. It really is pleasant to work to recall things even when you succeed at it. It does "freshen them up" in your memory. And sometimes just the experience of seeing a fact can be pleasant. (A lot of us review familiar things for the joy of it in other domains--movies, etc.)
Yes, I can calculate that! I was a math major and have some basic literacy. I checked the LLMs' work. That said, I only did so with medium rigor, and I wanted to flag that I was speaking as someone who was assisted by AI, not someone who had done the process by hand.
1. My algorithm is probably inefficient, and a big Q1 2026 goal is to figure out where the inefficiencies are and (better) to get a better system for addressing and remediating them in an automated way.
2. A lot of my cards were also made in 2025 (and 2024), so I'm probably much farther to the left of you on the learning curve, on average.
Really, thanks for making and sharing this; so far, I feel calm and happy when I'm using it.