I use Anki to learn material from textbooks, with great results. Creating the cards takes time, but so does summarizing the material (as Luke suggests); and the benefits associated to a SRS (specifically, the testing and spacing effects) make this approach clearly superior to any of the alternatives I tried.

Briefly, I write one note every paragraph, with a question on one side whose answer, written on the other side, is the main idea of that paragraph. Sometimes a note summarizes the content of more than one paragraph, if discussion of a single idea is spread over multiple paragraphs. Some textbooks include chapter or section summaries, and when they are sufficiently detailed, I'll rely on these to create the cards instead. Here's a sample card from Peter Gray's Psychology:

Front: How are ultimate explanations of behavior different from, but complementary to, proximate explanations?

Back: Ultimate explanations are functional explanations at the evolutionary level. Proximate explanations are explanations that deal not with function but with mechanism; they are statements of the immediate conditions, both inside and outside the animal, that bring on the behavior.

(This textbook is a particularly good example of "knowledge ready for ankification" because each page comes with 1-3 marginal "focus questions" intended to guide the student in the process of learning the material. So in this particular instance one can simply write these questions on the front side of each card, as I did.)

I also create a separate card for each term or expression that is explicitly defined and whose definition I don't already know. Many textbooks include a glossary, which simplifies the process of writing down these definitions. Here's a sample card, from Ivo Welch's Corporate Finance:

Front: What is annual percentage yield (APY)?

Back: APY is the simple rate of return, often simply called 'interest rate'. Banks sometimes use the expressions 'annual equivalent rate' (AER) and 'effective annual rate'.

Not sure if this is what you meant by "systemized", but here's my basic workflow for textbooks:

1. Read chapter (or, more likely, some 4-5 sections of a chapter)
2. Summarize/analyze chapter in an emacs org-mode document
3. Generate anki cards from the summary
4. (Optional) Expand summary with notes from lecture

Writing new cards takes a long time, so I try to spread out the work. Roughly speaking, one textbook chapter usually takes two days, and will generate 20-30 cards. (This is for physics and math, where I'm generating a lot of cards that are relatively basic formulas and constants.) Also, most of the work is in reading, understanding, and summarizing. Making the Anki cards does take time, but it tends to be less than the other parts.

I haven't done much to automate the process, although I'm working on autogenerating cards from the emacs documentation to learn emacs shortcuts. The most important modification I made to vanilla Anki was writing a very kluge-y plugin to allow full use of my commonly used emacs keybindings (mostly movement, killing, yanking, and deleting).

A few quick pieces of advice:

• Learn the shortcuts. It's a lot less painful when editing to type Cmd-T + M to get into Latex math mode than it is to use the mouse.

• On a related note, if you're doing math, physics, or anything else with formulas, learn Latex if you don't know it. It's for more pleasant to review cards with pretty formatting than with ugly formatting. It also makes cloze deletion of formulas a lot easier (although I'm not sure how effective Cloze formulas are yet).

• Batch the steps of whatever process you choose. So, I do all the reading, then all the summarizing, then all the anki additions, then all the anki reviewing. It's much faster, and way less painful to review.

• I've found it to be easier to review old material and learn new material at the same time. Learning 10 or 20 new cards can sometimes be frustrating, especially when I basically wanted to brute-force memorize (as I did with trig formulas before starting Calculus, where I didn't care how they were derived). Reviewing, on the other hand, is generally pleasant, since I get to feel accomplished and intelligent.

• Think hard about what information is useful. I wanted to memorize the derivation of the formula for a ring of charge in physics based on the formula for a point charge. I initially tried to make a bunch of different cards that sequentially went through the steps of the derivation. What worked, though, was having one card for the general strategy and another card for the bounds of integration. Once I had those two pieces of information, I was easily able to reconstruct the whole derivation. Since there were 3 or 4 additional similar derivations, recognizing those pieces of information as being critical saved something like 15 or 20 cards, which is huge.

If you haven't read these yet, here's a list of 20 rules of formulating knowledge, with an emphasis on SRS. This is a much longer article by the same guy, covering basically the same information in more detail. I agree with gwern, though, that Cloze deletions are not the most effective way to learn.

I’m interested in discussing this as well. I recall a LW thread asking for links to SRS forums and such but can’t find it now.

I have issues with formulating cards. The idea of creating a suboptimal card that I will then remember forever is so daunting that I often give up.

For example I found cloze deletion convenient, but gwern’s review advises to use free recall instead, which I am unsure what is exactly. Or I get obsessed with automating the process, like pulling definitions from a dictionary, google translate, or pydoc. Math concepts are also hard to break down into flashcard-sized chunks. It's all so agonizingly tedious.

I sound whiny. Please inspire me with SRS success stories.

Each time you find content you like, just copy-paste it in its raw form to a new Anki card and don't do further processing. Eventually, when you are studying Anki and this card shows up, you can then edit it and turn it into a properly formatted card that can be studied.

Will it be a repository of links sorted by a SR algorithm or does it offer some way of processing the information into flashcards?

I can see this working well with article summaries, e.g. in conjunction with tldr.io.