So I've been using Mnemosyne for a few months for physics. (I started it as a quals study-aid, after reading gwern's article.) I've found that two types of card

So I've been using Mnemosyne for a few months for physics. (I started it as a quals study-aid, after reading gwern's article.) I've found that two types of card work well: 1. Frequently (in physics) you can find a core skeleton of fundamental definitions & results. If you know these, you can solve a whole bunch of problems very easily; also, in reviewing those results, you inevitably remind yourself of why they're true (I'm starting to make a re-derivation a criterion for listing a "fact" as memorized), and of the broader logical structure of the discipline. 2. Certain problems exercise a wide variety of important techniques very quickly; I use Mnemosyne to prompt myself to re-work certain problems every so often. I try to be aggressive enough about rating "how well I know this" that I'm actually re-working the problems, not just memorizing. This is sort of like the "code kata" I've seen people suggest every now and then. Now, this is for physics, which is probably not exactly what you mean by "technical knowledge" :-). I expect this approach would generalize very nicely to mathematics and theoretical CS (and in fact I'm using it for bits and pieces in those fields); code & software engineering would be harder, but probably doable. Edit: removed pointer to (link to) Gwern's article: it's in the gp. Also assorted stylistic matters.